{
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      "title": "Emission cuts from household consumption options (Ivanova et al. 2020)",
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      "entities": ["AFG", "ALB", "ARE", "ARG", "ARM", "AUS", "AUT", "BEL", "BEN", "BFA", "BGD", "BGR", "BIH", "BOL", "BRA", "BWA", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COG", "COL", "CRI", "CYP", "CZE", "DEU", "DNK", "DOM", "DZA", "ECU", "EGY", "ESP", "EST", "FIN", "FRA", "GAB", "GBR", "GEO", "GHA", "GIN", "GRC", "GTM", "HKG", "HND", "HRV", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KOR", "KOS", "LAO", "LBN", "LKA", "LTU", "LVA", "MAR", "MDA", "MDG", "MEX", "MKD", "MLI", "MLT", "MMR", "MNG", "MOZ", "MUS", "MWI", "MYS", "NAM", "NGA", "NIC", "NLD", "NOR", "NPL", "NZL", "PAK", "PAN", "PER", "PHL", "POL", "PRT", "PRY", "ROU", "RUS", "SAU", "SEN", "SGP", "SLE", "SLV", "SRB", "SVK", "SVN", "SWE", "TGO", "THA", "TJK", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VEN", "VNM", "WLD", "ZAF", "ZMB", "ZWE"],
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        "description": "From a survey of nearly 130,000 people in 125 countries (Gallup World Poll 2021–2022): the share willing to give 1% of their household income every month to fight global warming, the share who approve of pro-climate norms, the share who want their government to do more, and what people believe about their compatriots: the average believed share willing to contribute and the share who think a majority is willing. In almost every country, people underestimate how many of their compatriots are willing.",
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            "description": "Cross-check: the release's budget file with the Table 8 assumptions (budget_normal_magicc_True_fair_False_esf_7.1pm26.7_likeli_0.6827_nonCO2pc50.0_GtCO2_permaf_False_zecsd_0.0_asym_False_hdT_1.24NonlinNonCO2_all_None_recEm213.csv) gives 134.22 GtCO₂ for 1.5 °C at 50% likelihood. The paper rounds to the nearest 10 GtCO₂; the build stops if the file value is more than 5 GtCO₂ from the quoted 130. Difference: 4.22 GtCO₂.",
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            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          }
        ],
        "published_value": {
          "document": "igcc-2025",
          "locator": "Sect. 9, p. 3910 (with Table 8 on the same page)",
          "quote": "Note that the RCB estimate of 130 GtCO₂ (50 % likelihood) would be exhausted in a little more than 3 years if global CO₂ emissions remain at 2025 levels (42 GtCO₂ yr⁻¹, from Table 1 with additional accounting for cement carbonation sink)."
        },
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide budget from the start of 2026 (1 January 2026) for 1.5 °C above 1850–1900, 50% likelihood considering only uncertainty in the transient climate response to cumulative emissions (TCRE); rounded by IGCC to the nearest 10 GtCO₂. Non-CO₂ warming from the AR6 scenarios that reach net zero CO₂, modelled with MAGICC; starts from 1.24 °C of human-induced warming over 2016–2025. It counts all net carbon dioxide from human activity (IGCC: \"the total amount of CO₂ that can ever be emitted\"), which IGCC compares with 2025 emissions of 42 GtCO₂ a year from its Table 1, fossil and land-use change together, international aviation and shipping included.",
          "bunkers": "included",
          "geography": "World",
          "gwp": null,
          "lulucf": "included"
        }
      },
      "source_ids": ["igcc-2025"],
      "time_basis": "calendar",
      "title": "Remaining carbon budget for 1.5 °C from the start of 2026 (50% likelihood)",
      "unit": {
        "code": "GtCO2",
        "label": "billion tonnes of carbon dioxide",
        "short": "Gt CO₂"
      },
      "vintage": "IGCC-2025a"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["EU27", "UCPM"],
      "export_sha256": "afbfcba5d413ca733c9baa6447d4923789e77586a79ede383e90594f07cdf45a",
      "geo_coverage": "global-only",
      "id": "burned-area.effis.europe-annual",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "EU27",
        "period": "2026",
        "status": "preliminary",
        "value": 689324.0
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "© European Union, European Forest Fire Information System (EFFIS), https://forest-fire.emergency.copernicus.eu, accessed 2026-10-05, CC BY 4.0. Sedano et al., Advance report on Forest Fires in Europe, Middle East and North Africa 2025, Publications Office of the European Union, 2026, doi:10.2760/3859043.",
        "description": "Hectares burnt each year since 2006 by fires of about 30 hectares or larger, mapped from satellite imagery by the European Forest Fire Information System (EFFIS), for the 27 EU member states and for the wider group EFFIS lists under the EU's Union Civil Protection Mechanism (UCPM). The current year is a running total to date.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (European Commission reuse policy)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
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          {"acquisition": "automatic", "artifact_id": "areas-of-interest", "bytes": 7071, "citation_full": "Sedano, F., Maianti, P., Boca, R., Suarez-Moreno, M., Broglia, M. et al., Advance report on Forest Fires in Europe, Middle East and North Africa 2025, Publications Office of the European Union, Luxembourg, 2026, https://data.europa.eu/doi/10.2760/3859043, JRC146199.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.2760/3859043", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (European Commission reuse policy)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "European Commission, Joint Research Centre (JRC), Copernicus Emergency Management Service", "r2_url": "https://files.environmentdashboard.org/raw/63d59c1da82e0781729b189f501534eb8e820d92e2a5f854999877d8027e0632.zst", "sha256": "63d59c1da82e0781729b189f501534eb8e820d92e2a5f854999877d8027e0632", "source_id": "effis", "title": "European Forest Fire Information System (EFFIS) burnt-area estimates", "url_download": "https://api2.effis.emergency.copernicus.eu/statistics/utils/countriesbyaoi?aoi=effis", "url_main": "https://forest-fire.emergency.copernicus.eu/apps/effis.statistics/estimates", "version_producer": "EFFIS estimates 2006–2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read EFFIS's estimatesbycountry responses for the areas EU and UCPM: hectares burnt (ba) each year 2006–2026, published as served. Number of fires (nf) is not published.",
            "inputs": ["f930f2f3163f05c296e43240c843f0cf1c4b5157842f56cf6362aa5e78350d87", "cdf8e7ba3bf07bd79e9c53650816628eeb84faf1aaa3492f3fd204f5ce649106", "63d59c1da82e0781729b189f501534eb8e820d92e2a5f854999877d8027e0632"],
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          {
            "description": "Checked EFFIS's own membership list (countriesbyaoi): EU has the 27 member states; UCPM has the 27, the ten other states in the Union Civil Protection Mechanism (ALB, BIH, ISL, MDA, MKD, MNE, NOR, SRB, TUR, UKR) and six separately listed areas (GLP, GUY, MAF, MTQ, MYT, REU). Checked that UCPM is never below EU27.",
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          {
            "description": "Year to date, status preliminary: EU27 2026 (as served on 2026-10-05); UCPM 2026 (as served on 2026-10-05).",
            "inputs": ["f930f2f3163f05c296e43240c843f0cf1c4b5157842f56cf6362aa5e78350d87", "cdf8e7ba3bf07bd79e9c53650816628eeb84faf1aaa3492f3fd204f5ce649106", "63d59c1da82e0781729b189f501534eb8e820d92e2a5f854999877d8027e0632"],
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            "script": "pipeline/src/envdash/transforms/impacts/effis_burned_area.py",
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        "published_value": null,
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          "baseline": null,
          "basis": "Fires of about 30 hectares or larger mapped by EFFIS's Rapid Damage Assessment from satellite imagery (MODIS at 250 metres; Sentinel-2 at 20 metres since 2018), by calendar year. Fires burning natural land are counted, including prescribed burns. Figures differ from national statistics, from single-year report totals (which count all mapped fires, also those under 30 hectares) and from GWIS's MODIS-based Europe.",
          "bunkers": null,
          "geography": "Europe as EFFIS defines two areas. EU27: the 27 EU member states. UCPM: the 27, plus Albania, Bosnia and Herzegovina, Iceland, Moldova, Montenegro, North Macedonia, Norway, Serbia, Türkiye and Ukraine, plus Guadeloupe, Martinique, Mayotte, Réunion, Saint-Martin and an area EFFIS lists as Guyana. Not included: Switzerland, the United Kingdom, Andorra, Kosovo, Belarus and Russia.",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["effis"],
      "time_basis": "calendar",
      "title": "Area burnt each year in the EU and in UCPM countries",
      "unit": {
        "code": "ha",
        "label": "hectares",
        "short": "ha"
      },
      "vintage": "EFFIS estimates 2006–2026"
    },
    {
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      "downloadable": true,
      "entities": ["UN_AFR", "UN_AME", "UN_ASI", "UN_EUR", "UN_OCE", "WLD"],
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      "geo_coverage": "global-only",
      "id": "burned-area.gwis.annual-by-land-cover",
      "latest": {
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        "dims": {
          "land_cover": "total"
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        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 332928197.51000077
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      "licence_class": "open",
      "provenance": {
        "attribution": "© European Union, Global Wildfire Information System (GWIS), Country Profile, https://gwis.jrc.ec.europa.eu/apps/country.profile, accessed 2026-10-05, CC BY 4.0. Burned area from NASA MODIS MCD64A1 v061 (Giglio et al. 2021, doi:10.5067/MODIS/MCD64A1.061).",
        "description": "Hectares burned each year since 2002 worldwide and in Africa, the Americas, Asia, Europe and Oceania, split into forest, savannas, shrublands and grasslands, croplands and other land, as mapped by NASA's MODIS satellites and compiled by the EU's Global Wildfire Information System (GWIS). The 500 metre resolution misses many small fires and much cropland burning, so the totals are lower than finer-resolution estimates.",
        "kind": "series",
        "licence": {
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          "spdx": "CC-BY-4.0",
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        "processing": [
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            "description": "Read the banfyear list of each GWIS Country Profile response (level=AOI): World (WORLD) 2002–2025; Africa (UN_AFR) 2002–2025; Americas (UN_AME) 2002–2025; Asia (UN_ASI) 2002–2025; Europe (UN_EUR) 2002–2025; Oceania (UN_OCE) 2002–2025. Published per year: lc_tot (all land cover) and lc1–lc5, labelled Forest, Savannas, Shrublands and grasslands, Croplands and Other as in the GWIS app's legend. Values are hectares as stored, not converted.",
            "inputs": ["2c29af78465ad69fbdc031fd557cc04eae5231cb8adb81dee26e3055b525e7ce", "17e38254598a948a0904d47dd10ce17f86b80c30387ee4f7f13146d507915ecb", "97dced6a94c2ed5710cf4acbdb561ba216c46f4ed284b2ee9d0d2d7425055d5a", "a9a05fdf9e981d9b834090af1c9258b88fc9fba1f6bc472225202dad6948b98e", "e2a738677b01fadedb922f72b1d150f12488ac5b6efad2581dc169d456da99c4", "a8889201d20929bd957b67f84984b91def66c1af407e194b73e9e30b2f8b2664"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/gwis_burned_area.py",
            "transform_sha256": "417670cf2e3f5b072c26808d9312b1c664f128d709ca320fa531a4ce8902d6b4"
          },
          {
            "description": "Checked in every year that the five land-cover classes add up to lc_tot, and that the twelve months of banfmonth add up to the year, each to within 0.01 hectare. The GlobFire fields (ba_area_ha, ba_count, firesize) are not read: they are 0.0 for years GlobFire has not yet processed.",
            "inputs": ["2c29af78465ad69fbdc031fd557cc04eae5231cb8adb81dee26e3055b525e7ce", "17e38254598a948a0904d47dd10ce17f86b80c30387ee4f7f13146d507915ecb", "97dced6a94c2ed5710cf4acbdb561ba216c46f4ed284b2ee9d0d2d7425055d5a", "a9a05fdf9e981d9b834090af1c9258b88fc9fba1f6bc472225202dad6948b98e", "e2a738677b01fadedb922f72b1d150f12488ac5b6efad2581dc169d456da99c4", "a8889201d20929bd957b67f84984b91def66c1af407e194b73e9e30b2f8b2664"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/gwis_burned_area.py",
            "transform_sha256": "417670cf2e3f5b072c26808d9312b1c664f128d709ca320fa531a4ce8902d6b4"
          },
          {
            "description": "Every year to 2025 has twelve months in the file and ended before the fetch: all final.",
            "inputs": ["2c29af78465ad69fbdc031fd557cc04eae5231cb8adb81dee26e3055b525e7ce", "17e38254598a948a0904d47dd10ce17f86b80c30387ee4f7f13146d507915ecb", "97dced6a94c2ed5710cf4acbdb561ba216c46f4ed284b2ee9d0d2d7425055d5a", "a9a05fdf9e981d9b834090af1c9258b88fc9fba1f6bc472225202dad6948b98e", "e2a738677b01fadedb922f72b1d150f12488ac5b6efad2581dc169d456da99c4", "a8889201d20929bd957b67f84984b91def66c1af407e194b73e9e30b2f8b2664"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/gwis_burned_area.py",
            "transform_sha256": "417670cf2e3f5b072c26808d9312b1c664f128d709ca320fa531a4ce8902d6b4"
          }
        ],
        "published_value": null,
        "scope": {
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          "basis": "Burned area mapped by NASA MODIS MCD64A1 Collection 6.1 (500 m, monthly), by calendar year, January to December, unlike the March–February fire seasons of State of Wildfires. GWIS Europe is MODIS-based and differs from EFFIS's estimates for Europe.",
          "bunkers": null,
          "geography": "World, and the five continents of GWIS's Country Profile (Africa, Americas, Asia, Europe, Oceania; codes UN_AFR, UN_AME, UN_ASI, UN_EUR, UN_OCE), each read from its own GWIS response.",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["gwis-burned-area"],
      "time_basis": "calendar",
      "title": "Area burned each year, world and continents, by land cover",
      "unit": {
        "code": "ha",
        "label": "hectares",
        "short": "ha"
      },
      "vintage": "MCD64A1 C6.1 via GWIS, 2002–2025"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "19629b2c52ef25d628f8e6f1b7dea25503130e1e53fdbcfe1ee9ab2390e0bb7a",
      "geo_coverage": "global-only",
      "id": "capacity.irena.renewable-share-world",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 49.4
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "IRENA (2026), Renewable capacity statistics 2026. © IRENA 2026.",
        "description": "The part of the world's installed electricity generating capacity that is renewable, at the end of each year since 2016, as published by IRENA.",
        "kind": "series",
        "licence": {
          "name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)",
          "spdx": null,
          "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "capacity-statistics-pdf", "bytes": 1681315, "citation_full": "IRENA (2026), Renewable capacity statistics 2026, International Renewable Energy Agency, Abu Dhabi.", "date_accessed": "2026-10-05", "date_published": "2026-03-31", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)", "spdx": null, "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"}, "producer": "International Renewable Energy Agency (IRENA)", "r2_url": "https://files.environmentdashboard.org/raw/fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921.zst", "sha256": "fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "source_id": "irena-capacity-2026", "title": "Renewable capacity statistics 2026", "url_download": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf", "url_main": "https://www.irena.org/Publications/2026/Mar/Renewable-capacity-statistics-2026", "version_producer": "2026-03-31", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "capacity-highlights-pdf", "bytes": 1973926, "citation_full": "IRENA (2026), Renewable capacity statistics 2026, International Renewable Energy Agency, Abu Dhabi.", "date_accessed": "2026-10-05", "date_published": "2026-03-31", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)", "spdx": null, "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"}, "producer": "International Renewable Energy Agency (IRENA)", "r2_url": "https://files.environmentdashboard.org/raw/c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b.zst", "sha256": "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b", "source_id": "irena-capacity-2026", "title": "Renewable capacity statistics 2026", "url_download": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_capacity_highlights_2026.pdf", "url_main": "https://www.irena.org/Publications/2026/Mar/Renewable-capacity-statistics-2026", "version_producer": "2026-03-31", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read IRENA's Renewable capacity statistics 2026 (PDF created 31 March 2026, sha256 fc580bd4f4ee…; its metadata title and the citation on page 2 name this edition) and took the World row of each table from the text of pages 14, 18, 21, 25, 26, 29, 32, 33, 37, 41, 42, 53, 64, read with the columns kept apart, for 2016 to 2025.",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          },
          {
            "description": "Checked that Total renewable energy is the sum of renewable hydropower, marine, onshore and offshore wind, solar photovoltaic, concentrated solar power, bioenergy and geothermal in every year, and that the wind, solar and hydropower tables add up from their parts, each to within the rounding of the megawatt values. Pure pumped storage is not part of IRENA's renewable total.",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          },
          {
            "description": "Found the quotes used as publisher checks in the highlights PDF (pages 1, 5).",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          },
          {
            "description": "Published IRENA's share as printed (one decimal).",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "IRENA's 'Renewable energy share of electricity capacity': renewable capacity over the capacity of all power plants at the end of the year. A share of capacity, not of generation.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["irena-capacity-2026"],
      "time_basis": "calendar",
      "title": "Renewables' share of world power capacity",
      "unit": {
        "code": "percent",
        "label": "percent of total electricity generating capacity",
        "short": "%"
      },
      "vintage": "2026-03-31"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "670188ec34155ba6beb33dc36cffc59ed274632a68874726a05ceff8e4bc9a3c",
      "geo_coverage": "global-only",
      "id": "capacity.irena.renewables-by-technology-world",
      "latest": {
        "age_bp": null,
        "dims": {
          "technology": "solar-pv"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 2383.162
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IRENA (2026), Renewable capacity statistics 2026. © IRENA 2026. Changes: converted from megawatts to gigawatts.",
        "description": "Capacity of the world's renewable power plants by technology (hydropower, marine, onshore and offshore wind, solar photovoltaic, concentrated solar power, bioenergy and geothermal) at the end of each year since 2016, as compiled by IRENA.",
        "kind": "series",
        "licence": {
          "name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)",
          "spdx": null,
          "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "capacity-statistics-pdf", "bytes": 1681315, "citation_full": "IRENA (2026), Renewable capacity statistics 2026, International Renewable Energy Agency, Abu Dhabi.", "date_accessed": "2026-10-05", "date_published": "2026-03-31", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)", "spdx": null, "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"}, "producer": "International Renewable Energy Agency (IRENA)", "r2_url": "https://files.environmentdashboard.org/raw/fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921.zst", "sha256": "fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "source_id": "irena-capacity-2026", "title": "Renewable capacity statistics 2026", "url_download": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf", "url_main": "https://www.irena.org/Publications/2026/Mar/Renewable-capacity-statistics-2026", "version_producer": "2026-03-31", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "capacity-highlights-pdf", "bytes": 1973926, "citation_full": "IRENA (2026), Renewable capacity statistics 2026, International Renewable Energy Agency, Abu Dhabi.", "date_accessed": "2026-10-05", "date_published": "2026-03-31", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)", "spdx": null, "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"}, "producer": "International Renewable Energy Agency (IRENA)", "r2_url": "https://files.environmentdashboard.org/raw/c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b.zst", "sha256": "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b", "source_id": "irena-capacity-2026", "title": "Renewable capacity statistics 2026", "url_download": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_capacity_highlights_2026.pdf", "url_main": "https://www.irena.org/Publications/2026/Mar/Renewable-capacity-statistics-2026", "version_producer": "2026-03-31", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read IRENA's Renewable capacity statistics 2026 (PDF created 31 March 2026, sha256 fc580bd4f4ee…; its metadata title and the citation on page 2 name this edition) and took the World row of each table from the text of pages 14, 18, 21, 25, 26, 29, 32, 33, 37, 41, 42, 53, 64, read with the columns kept apart, for 2016 to 2025.",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          },
          {
            "description": "Checked that Total renewable energy is the sum of renewable hydropower, marine, onshore and offshore wind, solar photovoltaic, concentrated solar power, bioenergy and geothermal in every year, and that the wind, solar and hydropower tables add up from their parts, each to within the rounding of the megawatt values. Pure pumped storage is not part of IRENA's renewable total.",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          },
          {
            "description": "Found the quotes used as publisher checks in the highlights PDF (pages 1, 5).",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          },
          {
            "description": "Published the eight technologies that make up IRENA's total, in gigawatts.",
            "inputs": ["fc580bd4f4ee39ef20de6b1ce3926005a4e3e3b8e2c92fd6a16d175a52515921", "c71bd27d8e33f57d817523def77c1189af0132d74fd7a1e594e56ef3b6a0cb8b"],
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            "script": "pipeline/src/envdash/transforms/energy/irena_capacity.py",
            "transform_sha256": "16bd17df3d2b10a759698227214b0e393d75faa0ed366728da5d688b5ed00ab5"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Maximum net generating capacity of renewable power plants installed and connected at the end of each year, as compiled by IRENA from official and unofficial sources and its own estimates. Capacity is not generation. Pure pumped storage hydropower and stationary batteries are not included. Values are revised in later editions.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["irena-capacity-2026"],
      "time_basis": "calendar",
      "title": "World renewable power capacity by technology",
      "unit": {
        "code": "GW",
        "label": "gigawatts",
        "short": "GW"
      },
      "vintage": "2026-03-31"
    },
    {
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      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "a94a8fb5c12da05cbac3875e21760da4ae31af54ec892648057cc0ea8b1f701c",
      "geo_coverage": "global-only",
      "id": "capacity.irena.renewables-world",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 5149.28
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IRENA (2026), Renewable capacity statistics 2026. © IRENA 2026. Changes: converted from megawatts to gigawatts.",
        "description": "Total capacity of the world's renewable power plants (hydropower, wind, solar, bioenergy, geothermal and marine) at the end of each year since 2016, as compiled by IRENA.",
        "kind": "series",
        "licence": {
          "name": "IRENA publication terms (free use with attribution to IRENA and the notation © IRENA 2026)",
          "spdx": null,
          "url": "https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2026/Mar/IRENA_DAT_RE_Capacity_Statistics_2026.pdf"
        },
        "notice": null,
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          {
            "description": "Quoted from Executive summary, p. i. The quote was found in the text of page 3 of the snapshot (sha256 5f28121f4899…) before publishing.",
            "inputs": ["5f28121f4899372929972d5d6f648b272ef702535137abf8f64140e4004cb93c"],
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          },
          {
            "description": "Value: \"estimated at 235 g CO2e/km\" is published as 235 grams of CO2-equivalent per kilometre for cars sold in 2025.",
            "inputs": ["5f28121f4899372929972d5d6f648b272ef702535137abf8f64140e4004cb93c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/literature.py",
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        ],
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          "locator": "Executive summary, p. i",
          "quote": "This is 73% lower than the emissions of gasoline ICEVs running on the average blend of fossil gasoline and ethanol, estimated at 235 g CO2e/km."
        },
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          "basis": "Sales-weighted average medium-segment car (SUVs excluded) registered in the EU in 2023, sold in 2025 and driven for 20 years on the average blend of fossil gasoline and ethanol; vehicle production and recycling, fuel production, tailpipe emissions and maintenance.",
          "bunkers": null,
          "geography": "European Union",
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        }
      },
      "source_ids": ["icct-lca-2025"],
      "time_basis": "calendar",
      "title": "Life-cycle emissions of a petrol car in the EU (ICCT)",
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        "code": "gCO2e/km",
        "label": "grams of CO2-equivalent per kilometre",
        "short": "g CO₂e/km"
      },
      "vintage": "ICCT report ID 392 (July 2025)"
    },
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        "period": "2025",
        "status": "preliminary",
        "value": 1935.94
      },
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        "attribution": "NOAA Global Monitoring Laboratory (Lan, Thoning & Dlugokencky), version 2026-09, doi:10.15138/P8XG-AA10.",
        "description": "Annual mean methane in dry air averaged over NOAA's global network of marine surface air-sampling sites, since 1984.",
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        "licence": {
          "name": "Public domain (work of the US federal government)",
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          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
        "notice": "The NOAA Global Monitoring Laboratory methane and nitrous oxide global marine surface means are US Government material and are not subject to copyright protection in the United States.",
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        ],
        "processing": [
          {
            "description": "Read ch4_annmean_gl.csv, created by NOAA on 5 September 2026. The vintage is the year and month of that creation date, which is how NOAA labels its versions.",
            "inputs": ["fac1f4e1b0e7f0449f8f496da46509c0c20410ccb368d2462ccb9f22900ef88d"],
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            "script": "pipeline/src/envdash/transforms/air/noaa_ch4_n2o.py",
            "transform_sha256": "10dc38222688b6d57bb5a048a714817da27eaad60322fa658a533496b920573d"
          },
          {
            "description": "Lower and upper are the mean minus and plus NOAA's stated uncertainty, which the file defines as the standard deviations of 100 bootstrap (network) and 100 Monte Carlo (measurement) global averages taken in quadrature (one standard deviation).",
            "inputs": ["fac1f4e1b0e7f0449f8f496da46509c0c20410ccb368d2462ccb9f22900ef88d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_ch4_n2o.py",
            "transform_sha256": "10dc38222688b6d57bb5a048a714817da27eaad60322fa658a533496b920573d"
          },
          {
            "description": "The last year is marked preliminary because the file states that the data for the last year are subject to change.",
            "inputs": ["fac1f4e1b0e7f0449f8f496da46509c0c20410ccb368d2462ccb9f22900ef88d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_ch4_n2o.py",
            "transform_sha256": "10dc38222688b6d57bb5a048a714817da27eaad60322fa658a533496b920573d"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Dry-air mole fraction; NOAA's global average of its marine surface air-sampling network, from smoothed site records weighted by latitude.",
          "bunkers": null,
          "geography": "Global mean of marine surface sites",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["noaa-gml-trends-ch4-n2o-sf6"],
      "time_basis": "calendar",
      "title": "Methane, global annual mean",
      "unit": {
        "code": "ppb",
        "label": "parts per billion",
        "short": "ppb"
      },
      "vintage": "2026-09"
    },
    {
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      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "56f0c8f5d4ac55ed3c3588e9c46b8a49c1b1d44c4ac233d76305439fc97bc476",
      "geo_coverage": "global-only",
      "id": "co2-share.sei-inequality.income-groups-global",
      "latest": {
        "age_bp": null,
        "dims": {
          "group": "top-10"
        },
        "entity": "WLD",
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        "status": "final",
        "value": 48.992907074468484
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      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Stockholm Environment Institute data: Emissions Inequality Dashboard (Ghosh, Nazareth, Wang, Kartha and Kemp-Benedict, 2021), https://emissions-inequality.org, accessed 2026-10-05, CC BY 4.0. Changes: emission shares of income slices added up into three groups (poorest 50%, richest 10%, richest 1%) and converted from fractions to percent.",
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        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0 (the About page says \"CC BY\" and links the 4.0 licence)",
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          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-percentile-shares", "bytes": 877309, "citation_full": "Emily Ghosh, Anisha Nazareth, Guozhong Wang, Sivan Kartha, Eric Kemp-Benedict (2021). Emissions Inequality Dashboard. Stockholm Environment Institute (SEI). https://emissions-inequality.org", "date_accessed": "2026-10-04", "date_published": null, "doi": null, "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (the About page says \"CC BY\" and links the 4.0 licence)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Stockholm Environment Institute (SEI)", "r2_url": "https://files.environmentdashboard.org/raw/9ad0752d138df5969a5b5b1069dab34ea2da07de35b18398bfc2fe9360c437f7.zst", "sha256": "9ad0752d138df5969a5b5b1069dab34ea2da07de35b18398bfc2fe9360c437f7", "source_id": "sei-emissions-inequality", "title": "Emissions Inequality Dashboard", "url_download": "https://www.sei-eqtrans-dev.net/api/globalHistoricalDataByYear/search.php", "url_main": "https://emissions-inequality.org/", "version_producer": "1990-2022 consumption-based years of the 1990-2023 historical series, retrieved 2026-10-04", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "national-history-che", "bytes": 7538, "citation_full": "Emily Ghosh, Anisha Nazareth, Guozhong Wang, Sivan Kartha, Eric Kemp-Benedict (2021). Emissions Inequality Dashboard. Stockholm Environment Institute (SEI). https://emissions-inequality.org", "date_accessed": "2026-10-05", "date_published": null, "doi": null, "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (the About page says \"CC BY\" and links the 4.0 licence)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Stockholm Environment Institute (SEI)", "r2_url": "https://files.environmentdashboard.org/raw/e23373e0dc5636820764920383da434f5c51c66ced61a032d2d299cf63f39d38.zst", "sha256": "e23373e0dc5636820764920383da434f5c51c66ced61a032d2d299cf63f39d38", "source_id": "sei-emissions-inequality", "title": "Emissions Inequality Dashboard", "url_download": "https://www.sei-eqtrans-dev.net/api/historicalDataByCountry/search.php?country=CHE&startyear=1990&endyear=2023", "url_main": "https://emissions-inequality.org/", "version_producer": "1990-2022 consumption-based years of the 1990-2023 historical series, retrieved 2026-10-04", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "national-history-usa", "bytes": 7673, "citation_full": "Emily Ghosh, Anisha Nazareth, Guozhong Wang, Sivan Kartha, Eric Kemp-Benedict (2021). Emissions Inequality Dashboard. Stockholm Environment Institute (SEI). https://emissions-inequality.org", "date_accessed": "2026-10-05", "date_published": null, "doi": null, "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (the About page says \"CC BY\" and links the 4.0 licence)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Stockholm Environment Institute (SEI)", "r2_url": "https://files.environmentdashboard.org/raw/ed93564c2981e1279ea88d5ac22b4efe2284c4e7b14cd970a7cca9460b0ec365.zst", "sha256": "ed93564c2981e1279ea88d5ac22b4efe2284c4e7b14cd970a7cca9460b0ec365", "source_id": "sei-emissions-inequality", "title": "Emissions Inequality Dashboard", "url_download": "https://www.sei-eqtrans-dev.net/api/historicalDataByCountry/search.php?country=USA&startyear=1990&endyear=2023", "url_main": "https://emissions-inequality.org/", "version_producer": "1990-2022 consumption-based years of the 1990-2023 historical series, retrieved 2026-10-04", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "national-history-gbr", "bytes": 7638, "citation_full": "Emily Ghosh, Anisha Nazareth, Guozhong Wang, Sivan Kartha, Eric Kemp-Benedict (2021). Emissions Inequality Dashboard. Stockholm Environment Institute (SEI). https://emissions-inequality.org", "date_accessed": "2026-10-05", "date_published": null, "doi": null, "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (the About page says \"CC BY\" and links the 4.0 licence)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Stockholm Environment Institute (SEI)", "r2_url": "https://files.environmentdashboard.org/raw/fde2cd775620ab9e3c9f7edd6659638174e5efbb14ebfa0a8fcbdeae16889629.zst", "sha256": "fde2cd775620ab9e3c9f7edd6659638174e5efbb14ebfa0a8fcbdeae16889629", "source_id": "sei-emissions-inequality", "title": "Emissions Inequality Dashboard", "url_download": "https://www.sei-eqtrans-dev.net/api/historicalDataByCountry/search.php?country=GBR&startyear=1990&endyear=2023", "url_main": "https://emissions-inequality.org/", "version_producer": "1990-2022 consumption-based years of the 1990-2023 historical series, retrieved 2026-10-04", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the Historical Global Shares API response (sha256 9ad0752d138d…, retrieved 2026-10-04): 4318 records, 1990–2023, 127 income slices a year. Checked for every year that the slices run from 0 to 100% of people with no gap or overlap, that each slice's width matches its label, and that the emission shares add up to 1 (within one billionth).",
            "inputs": ["9ad0752d138df5969a5b5b1069dab34ea2da07de35b18398bfc2fe9360c437f7", "e23373e0dc5636820764920383da434f5c51c66ced61a032d2d299cf63f39d38", "ed93564c2981e1279ea88d5ac22b4efe2284c4e7b14cd970a7cca9460b0ec365", "fde2cd775620ab9e3c9f7edd6659638174e5efbb14ebfa0a8fcbdeae16889629"],
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          },
          {
            "description": "Kept 1990–2022 and left out 2023. SEI's national inputs are consumption-based up to 2022 and territorial (where emissions happen) from 2023, so later shares are not comparable. The API's own national values show the break (historicalDataByCountry, NatEmisions as served, rounded here to the tonne; snapshots retrieved 2026-10-05): Switzerland 121,979,300 t in 2022 and 32,737,300 t in 2023 (sha256 e23373e0dc56…); the United States 5,642,856,100 t in 2022 and 4,911,391,000 t in 2023 (sha256 ed93564c2981…); the United Kingdom 488,532,000 t in 2022 and 305,146,300 t in 2023 (sha256 fde2cd775620…). The 2023 values match Global Carbon Budget 2025 territorial emissions, not consumption (research of 2026-10-05, docs/research/sources-ghg-food-personal-2026-10-05.json).",
            "inputs": ["9ad0752d138df5969a5b5b1069dab34ea2da07de35b18398bfc2fe9360c437f7", "e23373e0dc5636820764920383da434f5c51c66ced61a032d2d299cf63f39d38", "ed93564c2981e1279ea88d5ac22b4efe2284c4e7b14cd970a7cca9460b0ec365", "fde2cd775620ab9e3c9f7edd6659638174e5efbb14ebfa0a8fcbdeae16889629"],
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            "script": "pipeline/src/envdash/transforms/emissions/sei_inequality.py",
            "transform_sha256": "292fb86ce87643c7adc8106988c13697f7f00f6ca0220b3428c8b2af2cac8344"
          },
          {
            "description": "For each year, added up the EmissionShare of the slices in each group with exact decimal arithmetic on the values as served: the poorest 50% (slices up to the 50th percentile), the richest 10% (from the 90th) and the richest 1% (from the 99th, which SEI splits into finer slices). The richest 1% are part of the richest 10%.",
            "inputs": ["9ad0752d138df5969a5b5b1069dab34ea2da07de35b18398bfc2fe9360c437f7", "e23373e0dc5636820764920383da434f5c51c66ced61a032d2d299cf63f39d38", "ed93564c2981e1279ea88d5ac22b4efe2284c4e7b14cd970a7cca9460b0ec365", "fde2cd775620ab9e3c9f7edd6659638174e5efbb14ebfa0a8fcbdeae16889629"],
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          {
            "description": "Multiplied by 100 to give percent.",
            "inputs": ["9ad0752d138df5969a5b5b1069dab34ea2da07de35b18398bfc2fe9360c437f7", "e23373e0dc5636820764920383da434f5c51c66ced61a032d2d299cf63f39d38", "ed93564c2981e1279ea88d5ac22b4efe2284c4e7b14cd970a7cca9460b0ec365", "fde2cd775620ab9e3c9f7edd6659638174e5efbb14ebfa0a8fcbdeae16889629"],
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        ],
        "published_value": null,
        "scope": {
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          "basis": "Fossil carbon dioxide only, consumption-based (territorial emissions plus net emissions embodied in trade); other greenhouse gases and land-use change are not included. Each country's emissions are shared among its people in proportion to income between a floor and a ceiling (SEI's elasticity of 1). SEI's pages do not say how international aviation and shipping are allocated.",
          "bunkers": null,
          "geography": "World: everyone in the world, ranked by income per person (2021 US dollars at purchasing power parity)",
          "gwp": null,
          "lulucf": "excluded"
        }
      },
      "source_ids": ["sei-emissions-inequality"],
      "time_basis": "calendar",
      "title": "Share of world consumption carbon dioxide by income group (SEI)",
      "unit": {
        "code": "percent",
        "label": "percent of world consumption carbon dioxide emissions",
        "short": "%"
      },
      "vintage": "1990-2022 consumption-based years of the 1990-2023 historical series, retrieved 2026-10-04"
    },
    {
      "display": {
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      },
      "downloadable": true,
      "entities": ["ANT_ICECORES"],
      "export_sha256": "f35179a701a04986e009479dbedae2fd4f047fe55430157f96b225b8c23f7cbb",
      "geo_coverage": "global-only",
      "id": "co2.bereiter-2015.800k",
      "latest": {
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      },
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      "provenance": {
        "attribution": "Bereiter et al. (2015), Geophysical Research Letters, doi:10.1002/2014GL061957; data: NOAA/WDS Paleoclimatology, Antarctic Ice Cores Revised 800KYr CO2 Data, doi:10.25921/n8y4-bp27, https://www.ncei.noaa.gov/access/paleo-search/study/17975, accessed 2026-10-04.",
        "description": "Carbon dioxide in air trapped in Antarctic ice, from 805,669 years before 1950 to 2001, as the composite record of Bereiter et al. (2015). Each value is one ice or firn sample, dated by the age of its air in years before 1950, with one standard deviation.",
        "kind": "series",
        "licence": {
          "name": "No licence stated; free use with citation (NOAA NCEI World Data Service for Paleoclimatology)",
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        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "composite", "bytes": 51875, "citation_full": "Bereiter, B.; Eggleston, S.; Schmitt, J.; Nehrbass-Ahles, C.; Stocker, T.F.; Fischer, H.; Kipfstuhl, S.; Chappellaz, J.A. (2015-02-04): NOAA/WDS Paleoclimatology - Antarctic Ice Cores Revised 800KYr CO2 Data. Antarctic Ice Core Revised Composite CO2 Data. NOAA National Centers for Environmental Information. https://doi.org/10.25921/n8y4-bp27. Accessed 2026-10-04. Bereiter, B., S. Eggleston, J. Schmitt, C. Nehrbass-Ahles, T. F. Stocker, H. Fischer, S. Kipfstuhl, J. Chappellaz. 2015. Revision of the EPICA Dome C CO2 record from 800 to 600 kyr before present. Geophysical Research Letters, 42(2), 542-549. doi: 10.1002/2014GL061957. Lüthi, D., M. Le Floch, B. Bereiter, T. Blunier, J.-M. Barnola, U. Siegenthaler, D. Raynaud, J. Jouzel, H. Fischer, K. Kawamura, and T.F. Stocker. 2008. High-resolution carbon dioxide concentration record 650,000-800,000 years before present. Nature, 453, 379-382. doi: 10.1038/nature06949", "date_accessed": "2026-10-04", "date_published": "2015-02-04", "doi": "10.25921/n8y4-bp27", "etag": "\"caa3-6204a387e9f70\"", "last_modified": "Thu, 22 Aug 2024 18:56:47 GMT", "licence": {"name": "No licence stated; free use with citation (NOAA NCEI World Data Service for Paleoclimatology)", "spdx": null, "url": null}, "producer": "NOAA NCEI World Data Service for Paleoclimatology (data by Bereiter et al., University of Bern and partners)", "r2_url": "https://files.environmentdashboard.org/raw/40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f.zst", "sha256": "40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f", "source_id": "bereiter-2015-co2", "title": "Antarctic ice cores revised 800,000-year CO2 composite", "url_download": "https://www.ncei.noaa.gov/pub/data/paleo/icecore/antarctica/antarctica2015co2composite-noaa.txt", "url_main": "https://www.ncei.noaa.gov/access/paleo-search/study/17975", "version_producer": "2015-02-04", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read all 1,901 samples of antarctica2015co2composite-noaa.txt (NOAA template v4, contributed 2015-02-04): gas age in calendar years before 1950 (age_gas_calBP), carbon dioxide in parts per million (co2_ppm) and its one standard deviation (co2_1s_ppm), each as printed.",
            "inputs": ["40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/bereiter_co2.py",
            "transform_sha256": "6261d007099e532c2e5b801e76b40b90473facf3b3772c5b5d7bce1cfc404b92"
          },
          {
            "description": "Published each sample's gas age as age_bp, unrounded, with no calendar period (time basis years-before-1950), from the oldest (805668.87) to the youngest (-51.03); the file lists them youngest first.",
            "inputs": ["40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/bereiter_co2.py",
            "transform_sha256": "6261d007099e532c2e5b801e76b40b90473facf3b3772c5b5d7bce1cfc404b92"
          },
          {
            "description": "Range: value minus and plus the published one standard deviation (exact decimal arithmetic on the printed digits). The file's header says that where a sample has no sigma of its own, the average for the system or record is given.",
            "inputs": ["40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/bereiter_co2.py",
            "transform_sha256": "6261d007099e532c2e5b801e76b40b90473facf3b3772c5b5d7bce1cfc404b92"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide in air trapped in Antarctic ice, by gas age (AICC2012 chronology except Law Dome, WAIS and Siple Dome). Composite stitched by the producers from Law Dome (the most recent 2,000 years), Dome C, WAIS Divide (lowered by 4 ppm by the producers), Siple Dome, Talos Dome, EDML, Dome C sublimation, Vostok and Dome C. Ice smooths the air record over decades to centuries, so short peaks do not show. Range: ± one standard deviation as published (an average for the system or record where a sample has none of its own).",
          "bunkers": null,
          "geography": "Antarctica (composite of several ice cores)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["bereiter-2015-co2"],
      "time_basis": "years-before-1950",
      "title": "Carbon dioxide over the last 800,000 years (Antarctic ice cores)",
      "unit": {
        "code": "ppm",
        "label": "parts per million",
        "short": "ppm"
      },
      "vintage": "2015-02-04"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ANT_ICECORES"],
      "export_sha256": "0d4efb44101e02d88bf424c802a2fe3386b2f77d3c073781dd8bd7aaa0da45b4",
      "geo_coverage": "global-only",
      "id": "co2.bereiter-2015.800k.max-before-1000bp",
      "latest": {
        "age_bp": 335102.31,
        "dims": {},
        "entity": "ANT_ICECORES",
        "period": null,
        "status": "final",
        "value": 298.6
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Bereiter et al. (2015), Geophysical Research Letters, doi:10.1002/2014GL061957; data: NOAA/WDS Paleoclimatology, Antarctic Ice Cores Revised 800KYr CO2 Data, doi:10.25921/n8y4-bp27, https://www.ncei.noaa.gov/access/paleo-search/study/17975, accessed 2026-10-04. Changes: selected the highest carbon dioxide value among the samples older than 1,000 years before 1950.",
        "description": "The highest carbon dioxide value in the 800,000-year Antarctic ice-core composite of Bereiter et al. (2015) among the samples older than 1,000 years before 1950 (before 950 CE), with the age of that sample's air and its one standard deviation. Today's carbon dioxide, measured directly in the air, can be compared with it.",
        "kind": "derived",
        "licence": {
          "name": "No licence stated; free use with citation (NOAA NCEI World Data Service for Paleoclimatology)",
          "spdx": null,
          "url": null
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "composite", "bytes": 51875, "citation_full": "Bereiter, B.; Eggleston, S.; Schmitt, J.; Nehrbass-Ahles, C.; Stocker, T.F.; Fischer, H.; Kipfstuhl, S.; Chappellaz, J.A. (2015-02-04): NOAA/WDS Paleoclimatology - Antarctic Ice Cores Revised 800KYr CO2 Data. Antarctic Ice Core Revised Composite CO2 Data. NOAA National Centers for Environmental Information. https://doi.org/10.25921/n8y4-bp27. Accessed 2026-10-04. Bereiter, B., S. Eggleston, J. Schmitt, C. Nehrbass-Ahles, T. F. Stocker, H. Fischer, S. Kipfstuhl, J. Chappellaz. 2015. Revision of the EPICA Dome C CO2 record from 800 to 600 kyr before present. Geophysical Research Letters, 42(2), 542-549. doi: 10.1002/2014GL061957. Lüthi, D., M. Le Floch, B. Bereiter, T. Blunier, J.-M. Barnola, U. Siegenthaler, D. Raynaud, J. Jouzel, H. Fischer, K. Kawamura, and T.F. Stocker. 2008. High-resolution carbon dioxide concentration record 650,000-800,000 years before present. Nature, 453, 379-382. doi: 10.1038/nature06949", "date_accessed": "2026-10-04", "date_published": "2015-02-04", "doi": "10.25921/n8y4-bp27", "etag": "\"caa3-6204a387e9f70\"", "last_modified": "Thu, 22 Aug 2024 18:56:47 GMT", "licence": {"name": "No licence stated; free use with citation (NOAA NCEI World Data Service for Paleoclimatology)", "spdx": null, "url": null}, "producer": "NOAA NCEI World Data Service for Paleoclimatology (data by Bereiter et al., University of Bern and partners)", "r2_url": "https://files.environmentdashboard.org/raw/40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f.zst", "sha256": "40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f", "source_id": "bereiter-2015-co2", "title": "Antarctic ice cores revised 800,000-year CO2 composite", "url_download": "https://www.ncei.noaa.gov/pub/data/paleo/icecore/antarctica/antarctica2015co2composite-noaa.txt", "url_main": "https://www.ncei.noaa.gov/access/paleo-search/study/17975", "version_producer": "2015-02-04", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read all 1,901 samples of antarctica2015co2composite-noaa.txt (contributed 2015-02-04), as for co2.bereiter-2015.800k.",
            "inputs": ["40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/bereiter_co2.py",
            "transform_sha256": "6261d007099e532c2e5b801e76b40b90473facf3b3772c5b5d7bce1cfc404b92"
          },
          {
            "description": "Kept the 1,679 samples with a gas age above 1,000 years before 1950 (before 950 CE) and took the one with the highest co2_ppm: 298.60 ppm at 335102.31 years before 1950, one standard deviation 3.00 ppm. No other sample has that value. The value, age and standard deviation are published as printed; the range is value ± one standard deviation.",
            "inputs": ["40c9c175ab754530be3ecc53d2ac833c1979804f8a1bcccae185af66679ac08f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/bereiter_co2.py",
            "transform_sha256": "6261d007099e532c2e5b801e76b40b90473facf3b3772c5b5d7bce1cfc404b92"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Maximum of co2_ppm over every sample of the composite with a gas age above 1,000 years before 1950. Carbon dioxide in air trapped in Antarctic ice, by gas age (AICC2012 chronology except Law Dome, WAIS and Siple Dome). Composite stitched by the producers from Law Dome (the most recent 2,000 years), Dome C, WAIS Divide (lowered by 4 ppm by the producers), Siple Dome, Talos Dome, EDML, Dome C sublimation, Vostok and Dome C. Ice smooths the air record over decades to centuries, so short peaks do not show. Range: ± one standard deviation as published (an average for the system or record where a sample has none of its own).",
          "bunkers": null,
          "geography": "Antarctica (composite of several ice cores)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["bereiter-2015-co2"],
      "time_basis": "years-before-1950",
      "title": "Highest carbon dioxide in Antarctic ice before the industrial era",
      "unit": {
        "code": "ppm",
        "label": "parts per million",
        "short": "ppm"
      },
      "vintage": "2015-02-04"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["LAWDOME"],
      "export_sha256": "eb580cdc9d16b078de8e6e113805e0005929b49596aebf8b8ed7ac63d68b41ef",
      "geo_coverage": "global-only",
      "id": "co2.law-dome.2k",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "LAWDOME",
        "period": "1996",
        "status": "final",
        "value": 359.38354
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Rubino et al., Law Dome Ice Core 2000-Year CO2, CH4, N2O and d13C-CO2, v3, CSIRO, doi:10.25919/5bfe29ff807fb; Rubino et al. (2019), Earth System Science Data 11, 473-492, doi:10.5194/essd-11-473-2019. CC BY 4.0.",
        "description": "Carbon dioxide in air trapped in ice and firn at Law Dome, East Antarctica, as CSIRO's smoothing-spline fit for each year from 154 to 1996 CE.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "law-dome-ghg-2000years", "bytes": 261755, "citation_full": "Rubino, Mauro; Etheridge, David; Thornton, David; Allison, Colin; Francey, Roger; Langenfelds, Ray; Steele, Paul; Trudinger, Cathy; Spencer, Darren; Curran, Mark; Van Ommen, Tas; & Smith, Andrew (2019): Law Dome Ice Core 2000-Year CO2, CH4, N2O and d13C-CO2. v3. CSIRO. Data Collection. https://doi.org/10.25919/5bfe29ff807fb. Rubino, Mauro; Etheridge, David; Thornton, David; Howden, Russell; Allison, Colin; Francey, Roger; Langenfelds, Ray; Steele, Paul; Trudinger, Cathy; Spencer, Darren; Curran, Mark; van Ommen, Tas; Smith, Andrew. Revised records of atmospheric trace gases CO2, CH4, N2O, and δ13C-CO2 over the last 2000 years from Law Dome, Antarctica. Earth System Science Data. 2019; 11:473-492. https://doi.org/10.5194/essd-11-473-2019", "date_accessed": "2026-10-04", "date_published": "2024-09-04", "doi": "10.25919/5bfe29ff807fb", "etag": "\"f7dd24e36565b2e213b20f90c88c990e\"", "last_modified": "Fri, 12 May 2023 23:12:06 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "CSIRO (with the Australian Antarctic Division and ANSTO)", "r2_url": "https://files.environmentdashboard.org/raw/e2fb9ef0b36b46857c63bc171f3a8fff6af302ccae4d3d9e6f27df04fa6514d4.zst", "sha256": "e2fb9ef0b36b46857c63bc171f3a8fff6af302ccae4d3d9e6f27df04fa6514d4", "source_id": "law-dome-2k", "title": "Law Dome ice core 2000-year CO2, CH4, N2O and delta-13C-CO2", "url_download": "https://data.csiro.au/dap/ws/v2/collections/63432/data/53592973", "url_main": "https://data.csiro.au/collection/csiro:37077", "version_producer": "v3", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the sheet 'Splines fits' of Law_Dome_GHG_2000years.xlsx, CSIRO collection version v3 (data last updated 11/2018).",
            "inputs": ["e2fb9ef0b36b46857c63bc171f3a8fff6af302ccae4d3d9e6f27df04fa6514d4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/law_dome_co2.py",
            "transform_sha256": "c67459fecb8e83feb79e7e5649df410e093a6a529adf10cd7c37368e72fcb62f"
          },
          {
            "description": "Published the column 'CO2 spline (20 yr, ppm)' as printed for each year of its 'Year AD' column, 0154 to 1996, as ISO calendar years. The spline is CSIRO's fit to the ice and firn measurements, which halves variations with periods shorter than 20 years; the growth-rate column and the individual samples are not published here.",
            "inputs": ["e2fb9ef0b36b46857c63bc171f3a8fff6af302ccae4d3d9e6f27df04fa6514d4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/law_dome_co2.py",
            "transform_sha256": "c67459fecb8e83feb79e7e5649df410e093a6a529adf10cd7c37368e72fcb62f"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Smoothing spline (Enting 1987) through ice-core (DSS, DSS0506, DE08, DE08-2) and firn-air (DE08-2, DSSW20K) measurements by gas age; variations with periods under 20 years are halved.",
          "bunkers": null,
          "geography": "Law Dome, East Antarctica (66.7° S, 112.8° E)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["law-dome-2k"],
      "time_basis": "calendar",
      "title": "Carbon dioxide over the last 2,000 years (Law Dome ice cores)",
      "unit": {
        "code": "ppm",
        "label": "parts per million",
        "short": "ppm"
      },
      "vintage": "v3"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "f5727c10bd40c8c3236f481d4791d5a7dcb443cbccb12a7835066793d5c872ca",
      "geo_coverage": "global-only",
      "id": "co2.noaa-gml.annual-global",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 425.62
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA Global Monitoring Laboratory (Lan, Tans & Thoning), version 2026-09, doi:10.15138/9N0H-ZH07. Mauna Loa data March 1958 to April 1974: C. David Keeling, Scripps Institution of Oceanography.",
        "description": "Annual mean carbon dioxide in dry air averaged over NOAA's global network of marine surface sites, since 1979.",
        "kind": "series",
        "licence": {
          "name": "Public domain (work of the US federal government)",
          "spdx": null,
          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
        "notice": "The NOAA Global Monitoring Laboratory greenhouse gas trend values (Mauna Loa carbon dioxide from May 1974, and the global marine surface means) are US Government material and are not subject to copyright protection in the United States.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "co2-annmean-gl", "bytes": 2513, "citation_full": "Lan, X., Tans, P. and K.W. Thoning: Trends in globally-averaged CO2 determined from NOAA Global Monitoring Laboratory measurements. Version 2026-09 https://doi.org/10.15138/9N0H-ZH07", "date_accessed": "2026-10-04", "date_published": "2026-09-05", "doi": "10.15138/9N0H-ZH07", "etag": "\"9d1-65af9c4f70378\"", "last_modified": "Tue, 08 Sep 2026 14:44:18 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NOAA Global Monitoring Laboratory", "r2_url": "https://files.environmentdashboard.org/raw/36d6a6dd6bb5db53100d300b35fc6cb5ea6ad8756dd93326f847e4251c70bd14.zst", "sha256": "36d6a6dd6bb5db53100d300b35fc6cb5ea6ad8756dd93326f847e4251c70bd14", "source_id": "noaa-gml-trends", "title": "Trends in atmospheric carbon dioxide", "url_download": "https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_gl.csv", "url_main": "https://gml.noaa.gov/ccgg/trends/", "version_producer": "2026-09", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read co2_annmean_gl.csv, created by NOAA on 5 September 2026. The vintage is the year and month of that creation date, which is how NOAA labels its versions.",
            "inputs": ["36d6a6dd6bb5db53100d300b35fc6cb5ea6ad8756dd93326f847e4251c70bd14"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_co2.py",
            "transform_sha256": "251a10a6dfe1ae295fbdb6147e6456532529e130f3aca2620ef4cfe1cbf91512"
          },
          {
            "description": "Lower and upper are the mean minus and plus NOAA's stated uncertainty, which the file defines as the mean of the standard deviations of 200 Monte Carlo global averages (one standard deviation).",
            "inputs": ["36d6a6dd6bb5db53100d300b35fc6cb5ea6ad8756dd93326f847e4251c70bd14"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_co2.py",
            "transform_sha256": "251a10a6dfe1ae295fbdb6147e6456532529e130f3aca2620ef4cfe1cbf91512"
          },
          {
            "description": "The last year is marked preliminary because the file states that the data for the last year are subject to change.",
            "inputs": ["36d6a6dd6bb5db53100d300b35fc6cb5ea6ad8756dd93326f847e4251c70bd14"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_co2.py",
            "transform_sha256": "251a10a6dfe1ae295fbdb6147e6456532529e130f3aca2620ef4cfe1cbf91512"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Dry-air mole fraction; NOAA's global marine boundary layer average.",
          "bunkers": null,
          "geography": "Global mean of marine surface sites",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["noaa-gml-trends"],
      "time_basis": "calendar",
      "title": "Carbon dioxide, global annual mean",
      "unit": {
        "code": "ppm",
        "label": "parts per million",
        "short": "ppm"
      },
      "vintage": "2026-09"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["MLO"],
      "export_sha256": "041f80cb5cd858d7842639ea63f74d6ab33c1a78ee45c2cae560ce7f62a7d750",
      "geo_coverage": "global-only",
      "id": "co2.noaa-gml.monthly-mlo",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "MLO",
        "period": "2026-08",
        "status": "final",
        "value": 427.55
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA Global Monitoring Laboratory (Lan, Tans & Thoning), version 2026-09, doi:10.15138/9N0H-ZH07. Mauna Loa data March 1958 to April 1974: C. David Keeling, Scripps Institution of Oceanography.",
        "description": "Monthly mean carbon dioxide in dry air measured at Mauna Loa Observatory, Hawaii, since March 1958: the Keeling Curve. Values before May 1974 were measured by the Scripps Institution of Oceanography.",
        "kind": "series",
        "licence": {
          "name": "Public domain (work of the US federal government)",
          "spdx": null,
          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
        "notice": "The NOAA Global Monitoring Laboratory greenhouse gas trend values (Mauna Loa carbon dioxide from May 1974, and the global marine surface means) are US Government material and are not subject to copyright protection in the United States.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "co2-mm-mlo", "bytes": 38732, "citation_full": "Lan, X., Tans, P. and K.W. Thoning: Trends in globally-averaged CO2 determined from NOAA Global Monitoring Laboratory measurements. Version 2026-09 https://doi.org/10.15138/9N0H-ZH07", "date_accessed": "2026-10-04", "date_published": "2026-09-05", "doi": "10.15138/9N0H-ZH07", "etag": "\"974c-65af9c4f795ec\"", "last_modified": "Tue, 08 Sep 2026 14:44:18 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NOAA Global Monitoring Laboratory", "r2_url": "https://files.environmentdashboard.org/raw/dcf0198658c87ebb5e3b2ce807fe3a52e1d5f000aa0479fb1bf334afb7adde4d.zst", "sha256": "dcf0198658c87ebb5e3b2ce807fe3a52e1d5f000aa0479fb1bf334afb7adde4d", "source_id": "noaa-gml-trends", "title": "Trends in atmospheric carbon dioxide", "url_download": "https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_mm_mlo.csv", "url_main": "https://gml.noaa.gov/ccgg/trends/", "version_producer": "2026-09", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the monthly mean column (average) of co2_mm_mlo.csv, created by NOAA on 5 September 2026. The vintage is the year and month of that creation date, which is how NOAA labels its versions.",
            "inputs": ["dcf0198658c87ebb5e3b2ce807fe3a52e1d5f000aa0479fb1bf334afb7adde4d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_co2.py",
            "transform_sha256": "251a10a6dfe1ae295fbdb6147e6456532529e130f3aca2620ef4cfe1cbf91512"
          },
          {
            "description": "Kept every month as published. Where NOAA's own markers say something about a month (a Scripps-era value, a month with no measurement days that NOAA interpolated, a month without a standard deviation, or a month measured at Maunakea after the 2022 eruption) the observation carries that as a note. The deseasonalized, days, standard deviation and uncertainty columns are not published.",
            "inputs": ["dcf0198658c87ebb5e3b2ce807fe3a52e1d5f000aa0479fb1bf334afb7adde4d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_co2.py",
            "transform_sha256": "251a10a6dfe1ae295fbdb6147e6456532529e130f3aca2620ef4cfe1cbf91512"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Dry-air mole fraction; monthly means of daily means, as published (not deseasonalized).",
          "bunkers": null,
          "geography": "Mauna Loa Observatory, Hawaii (19.5° N, 155.6° W)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["noaa-gml-trends"],
      "time_basis": "calendar",
      "title": "Carbon dioxide at Mauna Loa, monthly mean",
      "unit": {
        "code": "ppm",
        "label": "parts per million",
        "short": "ppm"
      },
      "vintage": "2026-09"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "2a5d9b06555c9238a91331b35b59e0e834a36961ed6ebe39f939a6a1273596fd",
      "geo_coverage": "global-only",
      "id": "coral.noaa-crw.fourth-event-reef-area",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2023-01-01/2025-09-30",
        "status": "final",
        "value": 84.4
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA Coral Reef Watch, Version 3.1 Daily Global 5km Satellite Coral Bleaching Heat Stress products (Skirving et al. 2020, Remote Sensing 12, 3856, doi:10.3390/rs12233856), accessed 2026-10-04.",
        "description": "The share of the world's coral reef area that experienced heat stress high enough to cause bleaching between 1 January 2023 and 30 September 2025, the fourth global coral bleaching event, as published by NOAA Coral Reef Watch. Heat stress measures the risk of bleaching, not observed bleaching or coral death.",
        "kind": "published-value",
        "licence": {
          "name": "Public domain (NOAA Coral Reef Watch; US federal government work)",
          "spdx": null,
          "url": "https://coralreefwatch.noaa.gov/satellite/docs/recommendations_crw_citation.php"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-bleaching-status", "bytes": 25234, "citation_full": "NOAA Coral Reef Watch. 2018, updated daily. NOAA Coral Reef Watch Version 3.1 Daily Global 5km Satellite Coral Bleaching Degree Heating Week Product, Jan. 1, 2023-Dec. 31, 2025. College Park, Maryland, USA: NOAA Coral Reef Watch. Data set accessed 2026-10-04 at https://www.star.nesdis.noaa.gov/pub/socd/mecb/crw/data/5km/v3.1_op/nc/v1.0/annual/. Skirving, W; Marsh, B; De La Cour, J; Liu, G; Harris, A; Maturi, E; Geiger, E; Eakin, CM. CoralTemp and the Coral Reef Watch Coral Bleaching Heat Stress Product Suite Version 3.1. Remote Sens. 2020, 12, 3856; https://doi.org/10.3390/rs12233856.", "date_accessed": "2026-10-04", "date_published": null, "doi": null, "etag": null, "last_modified": null, "licence": {"name": "Public domain (NOAA Coral Reef Watch; US federal government work)", "spdx": null, "url": "https://coralreefwatch.noaa.gov/satellite/docs/recommendations_crw_citation.php"}, "producer": "NOAA NESDIS Center for Satellite Applications and Research, Coral Reef Watch", "r2_url": "https://files.environmentdashboard.org/raw/d48ccb9c370ee02e46c5db311665f9a7d7f2b1a22d474f08e6fb3018ebd11b13.zst", "sha256": "d48ccb9c370ee02e46c5db311665f9a7d7f2b1a22d474f08e6fb3018ebd11b13", "source_id": "noaa-crw", "title": "NOAA Coral Reef Watch coral bleaching heat stress and global bleaching status", "url_download": "https://coralreefwatch.noaa.gov/satellite/research/coral_bleaching_report.php", "url_main": "https://coralreefwatch.noaa.gov/", "version_producer": "Status update of 2 June 2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Quoted from Current Global Bleaching: Status Update (Updated: June 2, 2026), first paragraph under the headline. The quote was found in the visible text of the snapshot (sha256 d48ccb9c370e…) before publishing.",
            "inputs": ["d48ccb9c370ee02e46c5db311665f9a7d7f2b1a22d474f08e6fb3018ebd11b13"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/literature.py",
            "transform_sha256": "a5b5e1344e63f00f27104797d126b6a018b61af35ce032fb5e665703d5e05132"
          },
          {
            "description": "Value: \"~84.4%\" is published as 84.4 percent of the world's coral reef area for 1 January 2023 to 30 September 2025; the page gives no range.",
            "inputs": ["d48ccb9c370ee02e46c5db311665f9a7d7f2b1a22d474f08e6fb3018ebd11b13"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/literature.py",
            "transform_sha256": "a5b5e1344e63f00f27104797d126b6a018b61af35ce032fb5e665703d5e05132"
          }
        ],
        "published_value": {
          "document": "noaa-crw",
          "locator": "Current Global Bleaching: Status Update (Updated: June 2, 2026), first paragraph under the headline",
          "quote": "From 1 January 2023 to 30 September 2025, bleaching-level heat stress has impacted ~84.4% of the world's coral reef area and mass coral bleaching has been documented in at least 83 countries and territories."
        },
        "scope": {
          "baseline": null,
          "basis": "Reef area that had bleaching-level heat stress at least once between 1 January 2023 and 30 September 2025, from satellite sea surface temperature (CRW's 5 km Bleaching Alert Area products). The same page gives 68.2% for the third global event (2014–2017). NOAA said on 2 June 2026 that the fourth event likely ended in 2025.",
          "bunkers": null,
          "geography": "World (coral reef areas in Coral Reef Watch's global 5 km satellite products)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["noaa-crw"],
      "time_basis": "calendar",
      "title": "Coral reef area hit by bleaching-level heat stress in the fourth global bleaching event",
      "unit": {
        "code": "percent",
        "label": "percent of the world's coral reef area",
        "short": "%"
      },
      "vintage": "Status update of 2 June 2026"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "GAB", "GBR", "GEO", "GHA", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TON", "TTO", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "5c69067eb95e0da18dfd798e9fa4b43d692d23fc10e677803ada77b85bcae052",
      "geo_coverage": "country",
      "id": "electricity.ember.clean-share-by-country",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 42.309
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Yearly Electricity Data (file of 2026-09-22), CC BY 4.0.",
        "description": "Share of each country's electricity generation from renewables (solar, wind, hydro, bioenergy and other renewables) and nuclear power together, each year since 2000, as published by Ember, with the world for comparison.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-yearly-global", "bytes": 16084305, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"67122835394a3edc9da6e56901f3d640\"", "last_modified": "Tue, 22 Sep 2026 16:24:55 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7.zst", "sha256": "ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_yearly_global.csv", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methodology-pdf", "bytes": 1487777, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"9e4a04176b5b87901bdf0da81b05935b\"", "last_modified": "Tue, 22 Sep 2026 11:58:42 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908.zst", "sha256": "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/ember_electricity_data_methodology.pdf", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_yearly_global.csv, last modified by Ember on 2026-09-22 (Ember gives no version label, so that date is the vintage), and Ember's data methodology (PDF last modified 2026-09-22, sha256 67c5eaac3bfb…). Every methodology statement this transform relies on was found in the PDF (pages 10, 11, 12, 15, 16) before publishing.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Kept the World and the 209 countries and economies in pipeline/geo/entities.csv, from 2000, the first year of Ember's stated coverage (earlier rows exist for some countries and are partial). Each country is matched by Ember's ISO 3 code; Ember's XKX is Kosovo (KOS).",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Checked, for every country and year, that the shares of the generating sources in the file add up to 100%, that Clean generation is Renewables plus Nuclear and the Clean share is Clean over Total generation, and that the emissions intensity is emissions over generation, each to within the rounding of the printed values.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Left as null, with the reason, every share and intensity of a country-year in which the file gives a negative generation for a source, because those shares do not describe a generation mix. Ember projects the latest year by applying absolute changes from monthly data to annual values, which can go below zero. In this vintage: Azerbaijan 2025 (Solar -0.094 TWh); Belgium 2025 (Other fossil -0.349 TWh); Bangladesh 2025 (Wind -0.038 TWh); Costa Rica 2025 (Other fossil -1.15 TWh); Czechia 2025 (Other renewables -0.111 TWh); Spain 2025 (Other renewables -0.045 TWh); Estonia 2025 (Other renewables -0.001 TWh); Croatia 2025 (Other fossil -0.003 TWh); Kyrgyzstan 2025 (Other fossil -0.144 TWh); Netherlands 2025 (Other renewables -0.005 TWh); Slovenia 2025 (Other fossil -0.019 TWh).",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Status: a World year is preliminary when the file has no Total generation for a country that has it for an earlier year (Ember estimates missing country years from historical trends), as in electricity.ember.mix-world: 2023, 2024, 2025. Each country's values for 2025, the latest year in the file, are preliminary, because Ember estimates the most recent year from monthly data and the file does not say for which countries.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Published Ember's 'Share of generation (%)' of its aggregated source 'Clean' (renewables plus nuclear) as printed.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Share of electricity generation, not of consumption: net imports are not included. Ember reports annual generation as gross generation where it can. The latest year is partly estimated from monthly data. Clean means renewables plus nuclear.",
          "bunkers": null,
          "geography": "Countries and economies, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-yearly"],
      "time_basis": "calendar",
      "title": "Share of electricity from clean sources, by country",
      "unit": {
        "code": "percent",
        "label": "percent of electricity generation",
        "short": "%"
      },
      "vintage": "2026-09-22"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "956cf4de4385a1b4fb5a9a0895874c34d49c3943bed83286ca1cfd8ca66ad799",
      "geo_coverage": "global-only",
      "id": "electricity.ember.clean-share-world",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 42.309
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Yearly Electricity Data (file of 2026-09-22), CC BY 4.0.",
        "description": "Share of the world's electricity generation from renewables (solar, wind, hydro, bioenergy and other renewables) and nuclear power together, each year since 2000, as published by Ember.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-yearly-global", "bytes": 16084305, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"67122835394a3edc9da6e56901f3d640\"", "last_modified": "Tue, 22 Sep 2026 16:24:55 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7.zst", "sha256": "ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_yearly_global.csv", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methodology-pdf", "bytes": 1487777, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"9e4a04176b5b87901bdf0da81b05935b\"", "last_modified": "Tue, 22 Sep 2026 11:58:42 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908.zst", "sha256": "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/ember_electricity_data_methodology.pdf", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_yearly_global.csv, last modified by Ember on 2026-09-22 (Ember gives no version label, so that date is the vintage), and kept the rows for Area 'World'.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          },
          {
            "description": "Checked that the shares mean what is published: the nine non-aggregated sources (Solar, Wind, Hydro, Bioenergy, Other renewables, Nuclear, Coal, Gas, Other fossil) add up to 100%, Clean generation is Renewables plus Nuclear, Renewables is the five renewable sources, and the Clean share is Clean over Total generation, each to within the rounding of the printed values.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          },
          {
            "description": "Marked a year preliminary, with a note giving the count, when the file has no Total generation for that year for a country or economy that has it for an earlier year. Ember's data methodology (PDF last modified 2026-09-22, sha256 67c5eaac3bfb…; both sentences were found on pages 10, 12 before publishing) says it estimates the latest annual generation from monthly data and a country's missing years from historical trends, so the World value for such a year is partly Ember's estimate. Preliminary years in this vintage: 2023, 2024, 2025.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          },
          {
            "description": "Published Ember's 'Share of generation (%)' of its aggregated source 'Clean' (renewables plus nuclear) as printed.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Share of electricity generation, not of consumption: net imports are not included. Ember reports annual generation as gross generation where it can. Clean means renewables plus nuclear.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-yearly"],
      "time_basis": "calendar",
      "title": "Share of world electricity from clean sources",
      "unit": {
        "code": "percent",
        "label": "percent of electricity generation",
        "short": "%"
      },
      "vintage": "2026-09-22"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "GAB", "GBR", "GEO", "GHA", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TON", "TTO", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "c0c98d87e38eaa108850e2798ae02bf052529c0ecaeb02ed19f456842c9e03a2",
      "geo_coverage": "country",
      "id": "electricity.ember.lifecycle-intensity-by-country",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 460.503
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Yearly Electricity Data (file of 2026-09-22), CC BY 4.0.",
        "description": "Greenhouse gas emissions per kilowatt-hour of electricity generated in each country, counting the whole lifecycle of each power source (fuel extraction, methane leaks, building the plants), each year since 2000, as estimated by Ember, with the world for comparison.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-yearly-global", "bytes": 16084305, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"67122835394a3edc9da6e56901f3d640\"", "last_modified": "Tue, 22 Sep 2026 16:24:55 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7.zst", "sha256": "ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_yearly_global.csv", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methodology-pdf", "bytes": 1487777, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"9e4a04176b5b87901bdf0da81b05935b\"", "last_modified": "Tue, 22 Sep 2026 11:58:42 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908.zst", "sha256": "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/ember_electricity_data_methodology.pdf", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_yearly_global.csv, last modified by Ember on 2026-09-22 (Ember gives no version label, so that date is the vintage), and Ember's data methodology (PDF last modified 2026-09-22, sha256 67c5eaac3bfb…). Every methodology statement this transform relies on was found in the PDF (pages 10, 11, 12, 15, 16) before publishing.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Kept the World and the 209 countries and economies in pipeline/geo/entities.csv, from 2000, the first year of Ember's stated coverage (earlier rows exist for some countries and are partial). Each country is matched by Ember's ISO 3 code; Ember's XKX is Kosovo (KOS).",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Checked, for every country and year, that the shares of the generating sources in the file add up to 100%, that Clean generation is Renewables plus Nuclear and the Clean share is Clean over Total generation, and that the emissions intensity is emissions over generation, each to within the rounding of the printed values.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Left as null, with the reason, every share and intensity of a country-year in which the file gives a negative generation for a source, because those shares do not describe a generation mix. Ember projects the latest year by applying absolute changes from monthly data to annual values, which can go below zero. In this vintage: Azerbaijan 2025 (Solar -0.094 TWh); Belgium 2025 (Other fossil -0.349 TWh); Bangladesh 2025 (Wind -0.038 TWh); Costa Rica 2025 (Other fossil -1.15 TWh); Czechia 2025 (Other renewables -0.111 TWh); Spain 2025 (Other renewables -0.045 TWh); Estonia 2025 (Other renewables -0.001 TWh); Croatia 2025 (Other fossil -0.003 TWh); Kyrgyzstan 2025 (Other fossil -0.144 TWh); Netherlands 2025 (Other renewables -0.005 TWh); Slovenia 2025 (Other fossil -0.019 TWh).",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Status: a World year is preliminary when the file has no Total generation for a country that has it for an earlier year (Ember estimates missing country years from historical trends), as in electricity.ember.mix-world: 2023, 2024, 2025. Each country's values for 2025, the latest year in the file, are preliminary, because Ember estimates the most recent year from monthly data and the file does not say for which countries.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Published Ember's 'Emissions intensity (gCO2e/kWh)' of 'Total generation' as printed.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Lifecycle emissions per unit of electricity generated, as Ember labels them: upstream methane, supply chain and manufacturing emissions of each fuel and technology, all gases, in CO₂-equivalent over 100 years with methane counted at 21 times CO₂ (a factor from the IPCC Second Assessment Report, so none of the AR5 or AR6 options applies). Not combustion CO₂, and never comparable with or added to Global Carbon Project emissions. Per unit of generation, net imports excluded.",
          "bunkers": null,
          "geography": "Countries and economies, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-yearly"],
      "time_basis": "calendar",
      "title": "Carbon intensity of electricity (lifecycle), by country",
      "unit": {
        "code": "gCO2e/kWh",
        "label": "grams of carbon dioxide equivalent per kilowatt-hour (lifecycle)",
        "short": "g CO₂e/kWh"
      },
      "vintage": "2026-09-22"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "GAB", "GBR", "GEO", "GHA", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TON", "TTO", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "22c304668b2528190988d15d30d5bae4172f7b106320099b3d9ba5f50d035e3b",
      "geo_coverage": "country",
      "id": "electricity.ember.mix-by-country",
      "latest": {
        "age_bp": null,
        "dims": {
          "source": "solar"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 8.737
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Yearly Electricity Data (file of 2026-09-22), CC BY 4.0.",
        "description": "Share of each country's electricity generation from each source (solar, wind, hydro, bioenergy, other renewables, nuclear, coal, gas and other fossil fuels), each year since 2000, as published by Ember, with the world for comparison.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-yearly-global", "bytes": 16084305, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"67122835394a3edc9da6e56901f3d640\"", "last_modified": "Tue, 22 Sep 2026 16:24:55 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7.zst", "sha256": "ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_yearly_global.csv", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methodology-pdf", "bytes": 1487777, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"9e4a04176b5b87901bdf0da81b05935b\"", "last_modified": "Tue, 22 Sep 2026 11:58:42 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908.zst", "sha256": "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/ember_electricity_data_methodology.pdf", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_yearly_global.csv, last modified by Ember on 2026-09-22 (Ember gives no version label, so that date is the vintage), and Ember's data methodology (PDF last modified 2026-09-22, sha256 67c5eaac3bfb…). Every methodology statement this transform relies on was found in the PDF (pages 10, 11, 12, 15, 16) before publishing.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Kept the World and the 209 countries and economies in pipeline/geo/entities.csv, from 2000, the first year of Ember's stated coverage (earlier rows exist for some countries and are partial). Each country is matched by Ember's ISO 3 code; Ember's XKX is Kosovo (KOS).",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Checked, for every country and year, that the shares of the generating sources in the file add up to 100%, that Clean generation is Renewables plus Nuclear and the Clean share is Clean over Total generation, and that the emissions intensity is emissions over generation, each to within the rounding of the printed values.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Left as null, with the reason, every share and intensity of a country-year in which the file gives a negative generation for a source, because those shares do not describe a generation mix. Ember projects the latest year by applying absolute changes from monthly data to annual values, which can go below zero. In this vintage: Azerbaijan 2025 (Solar -0.094 TWh); Belgium 2025 (Other fossil -0.349 TWh); Bangladesh 2025 (Wind -0.038 TWh); Costa Rica 2025 (Other fossil -1.15 TWh); Czechia 2025 (Other renewables -0.111 TWh); Spain 2025 (Other renewables -0.045 TWh); Estonia 2025 (Other renewables -0.001 TWh); Croatia 2025 (Other fossil -0.003 TWh); Kyrgyzstan 2025 (Other fossil -0.144 TWh); Netherlands 2025 (Other renewables -0.005 TWh); Slovenia 2025 (Other fossil -0.019 TWh).",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Status: a World year is preliminary when the file has no Total generation for a country that has it for an earlier year (Ember estimates missing country years from historical trends), as in electricity.ember.mix-world: 2023, 2024, 2025. Each country's values for 2025, the latest year in the file, are preliminary, because Ember estimates the most recent year from monthly data and the file does not say for which countries.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          },
          {
            "description": "Published Ember's 'Share of generation (%)' of each of the nine sources as printed, for each country and year that has a row for that source.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_countries.py",
            "transform_sha256": "8155ba05603a0ff0a7cd456b75f6d3bde247bb6c7c953191a0a1e7787cbf41a3"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Share of electricity generation, not of consumption: net imports are not included. Ember reports annual generation as gross generation where it can. The latest year is partly estimated from monthly data.",
          "bunkers": null,
          "geography": "Countries and economies, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-yearly"],
      "time_basis": "calendar",
      "title": "Electricity generation by source, by country",
      "unit": {
        "code": "percent",
        "label": "percent of electricity generation",
        "short": "%"
      },
      "vintage": "2026-09-22"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "11f152524db22ca75f61f9622fa8c4ee58f3a65488b4738575d9ac06cfe4972e",
      "geo_coverage": "global-only",
      "id": "electricity.ember.mix-world",
      "latest": {
        "age_bp": null,
        "dims": {
          "source": "solar"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 8.737
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Yearly Electricity Data (file of 2026-09-22), CC BY 4.0.",
        "description": "Share of the world's electricity generation from each source (solar, wind, hydro, bioenergy, other renewables, nuclear, coal, gas and other fossil fuels), each year since 2000, as published by Ember.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-yearly-global", "bytes": 16084305, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"67122835394a3edc9da6e56901f3d640\"", "last_modified": "Tue, 22 Sep 2026 16:24:55 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7.zst", "sha256": "ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_yearly_global.csv", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methodology-pdf", "bytes": 1487777, "citation_full": "Yearly electricity generation data, Ember", "date_accessed": "2026-10-04", "date_published": "2026-09-22", "doi": null, "etag": "\"9e4a04176b5b87901bdf0da81b05935b\"", "last_modified": "Tue, 22 Sep 2026 11:58:42 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908.zst", "sha256": "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908", "source_id": "ember-yearly", "title": "Yearly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/ember_electricity_data_methodology.pdf", "url_main": "https://ember-energy.org/data/yearly-electricity-data/", "version_producer": "2026-09-22", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_yearly_global.csv, last modified by Ember on 2026-09-22 (Ember gives no version label, so that date is the vintage), and kept the rows for Area 'World'.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          },
          {
            "description": "Checked that the shares mean what is published: the nine non-aggregated sources (Solar, Wind, Hydro, Bioenergy, Other renewables, Nuclear, Coal, Gas, Other fossil) add up to 100%, Clean generation is Renewables plus Nuclear, Renewables is the five renewable sources, and the Clean share is Clean over Total generation, each to within the rounding of the printed values.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          },
          {
            "description": "Marked a year preliminary, with a note giving the count, when the file has no Total generation for that year for a country or economy that has it for an earlier year. Ember's data methodology (PDF last modified 2026-09-22, sha256 67c5eaac3bfb…; both sentences were found on pages 10, 12 before publishing) says it estimates the latest annual generation from monthly data and a country's missing years from historical trends, so the World value for such a year is partly Ember's estimate. Preliminary years in this vintage: 2023, 2024, 2025.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          },
          {
            "description": "Published Ember's 'Share of generation (%)' for each of the nine sources as printed, one series per source.",
            "inputs": ["ea214963f4a98b26f52aaf541736d4310349a905e64f83e63425bfc3ab6255d7", "67c5eaac3bfbeb7e67bb786f9ea9680f67f6f26e75318560562ee52d439de908"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_yearly.py",
            "transform_sha256": "56848f85fd86402d110614460abe3045b5d574a8a2a3759781085281977f3425"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Share of electricity generation, not of consumption: net imports are not included. Ember reports annual generation as gross generation where it can.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-yearly"],
      "time_basis": "calendar",
      "title": "World electricity generation by source",
      "unit": {
        "code": "percent",
        "label": "percent of electricity generation",
        "short": "%"
      },
      "vintage": "2026-09-22"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "90f0c5c843359ad48ec7a8075bae2936bbc8ffc502acd855ffd73b11cd5c7cfc",
      "geo_coverage": "global-only",
      "id": "electricity.ember.monthly-clean-share-world",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2026-07",
        "status": "preliminary",
        "value": 43.503
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Monthly Electricity Data (file of 2026-09-18), CC BY 4.0.",
        "description": "Share of the world's electricity generation from renewables and nuclear power together in each month since January 2019, as estimated by Ember.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-monthly-global", "bytes": 28333064, "citation_full": "Monthly electricity generation data, Ember", "date_accessed": "2026-10-05", "date_published": "2026-09-18", "doi": null, "etag": "\"1932fe694a4679159e119c2f6b9255e5\"", "last_modified": "Fri, 18 Sep 2026 21:29:31 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55.zst", "sha256": "6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55", "source_id": "ember-monthly", "title": "Monthly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_monthly_global.csv", "url_main": "https://ember-energy.org/data/monthly-electricity-data/", "version_producer": "2026-09-18", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_monthly_global.csv, last modified by Ember on 2026-09-18 (Ember gives no version label, so that date is the vintage), and kept the rows for Area 'World', 2019-01 to 2026-07.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Checked that every month's shares mean what is published: the nine non-aggregated sources add up to 100%, Clean generation is Renewables plus Nuclear, Renewables is the five renewable sources, and the Clean share is Clean over Total generation, each to within the rounding of the printed values.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Noted on each month how many countries and economies have Total generation in the file for it (from 84 in 2019-01 to 56 in 2026-07), and marked a month preliminary when a country with generation for an earlier month has none for it, because the World total then includes Ember's estimate for that country. Preliminary months in this vintage: 46, the first 2022-10 and the last 2026-07.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Published Ember's 'Share of generation (%)' of its aggregated source 'Clean' (renewables plus nuclear) as printed.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Share of electricity generation in the month, not of consumption: net imports are not included. The World total is Ember's estimate built from the countries with monthly data; values are revised as data arrive. Clean means renewables plus nuclear.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-monthly"],
      "time_basis": "calendar",
      "title": "Share of world electricity from clean sources, monthly",
      "unit": {
        "code": "percent",
        "label": "percent of electricity generation",
        "short": "%"
      },
      "vintage": "2026-09-18"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "09c7da541efc42d433a0684e9611ebb58df74d229edd0245d7f42bf5e882809b",
      "geo_coverage": "global-only",
      "id": "electricity.ember.monthly-fossil-change-world",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2026-07",
        "status": "preliminary",
        "value": -0.886
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Monthly Electricity Data (file of 2026-09-18), CC BY 4.0.",
        "description": "How much more or less electricity the world generated from coal, gas and other fossil fuels in each month than in the same month a year earlier, in percent, since January 2020, as estimated by Ember.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-monthly-global", "bytes": 28333064, "citation_full": "Monthly electricity generation data, Ember", "date_accessed": "2026-10-05", "date_published": "2026-09-18", "doi": null, "etag": "\"1932fe694a4679159e119c2f6b9255e5\"", "last_modified": "Fri, 18 Sep 2026 21:29:31 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55.zst", "sha256": "6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55", "source_id": "ember-monthly", "title": "Monthly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_monthly_global.csv", "url_main": "https://ember-energy.org/data/monthly-electricity-data/", "version_producer": "2026-09-18", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_monthly_global.csv, last modified by Ember on 2026-09-18 (Ember gives no version label, so that date is the vintage), and kept the rows for Area 'World', 2020-01 to 2026-07.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Checked that every month's shares mean what is published: the nine non-aggregated sources add up to 100%, Clean generation is Renewables plus Nuclear, Renewables is the five renewable sources, and the Clean share is Clean over Total generation, each to within the rounding of the printed values.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Noted on each month how many countries and economies have Total generation in the file for it (from 86 in 2020-01 to 56 in 2026-07), and marked a month preliminary when a country with generation for an earlier month has none for it, because the World total then includes Ember's estimate for that country. Preliminary months in this vintage: 46, the first 2022-10 and the last 2026-07.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Checked that the Fossil row's 'Generation YoY change (TWh)' is this month's generation minus the same month's a year earlier in the file, and that 'Generation YoY change (%)' is that change over the earlier month, to within the rounding of the printed values.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Published Ember's 'Generation YoY change (%)' of its aggregated source 'Fossil' as printed.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Ember's aggregated source 'Fossil' (coal, gas and other fossil fuels), generation in the month compared with the same month of the previous year. The World total is Ember's estimate built from the countries with monthly data; values are revised as data arrive.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-monthly"],
      "time_basis": "calendar",
      "title": "Change in world fossil-fuel electricity from a year earlier, monthly",
      "unit": {
        "code": "percent-change",
        "label": "percent change from the same month a year earlier",
        "short": "%"
      },
      "vintage": "2026-09-18"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "46bbffc1da5be387800300fec142e4756cd8e9a672fd204b47fe92904d179814",
      "geo_coverage": "global-only",
      "id": "electricity.ember.monthly-mix-world",
      "latest": {
        "age_bp": null,
        "dims": {
          "source": "solar"
        },
        "entity": "WLD",
        "period": "2026-07",
        "status": "preliminary",
        "value": 11.277
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Ember, Monthly Electricity Data (file of 2026-09-18), CC BY 4.0.",
        "description": "Share of the world's electricity generation from each source (solar, wind, hydro, bioenergy, other renewables, nuclear, coal, gas and other fossil fuels) in each month since January 2019, as estimated by Ember.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "generation-monthly-global", "bytes": 28333064, "citation_full": "Monthly electricity generation data, Ember", "date_accessed": "2026-10-05", "date_published": "2026-09-18", "doi": null, "etag": "\"1932fe694a4679159e119c2f6b9255e5\"", "last_modified": "Fri, 18 Sep 2026 21:29:31 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Ember", "r2_url": "https://files.environmentdashboard.org/raw/6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55.zst", "sha256": "6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55", "source_id": "ember-monthly", "title": "Monthly electricity data", "url_download": "https://files.ember-energy.org/public-downloads/generation/outputs/release_generation_monthly_global.csv", "url_main": "https://ember-energy.org/data/monthly-electricity-data/", "version_producer": "2026-09-18", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read release_generation_monthly_global.csv, last modified by Ember on 2026-09-18 (Ember gives no version label, so that date is the vintage), and kept the rows for Area 'World', 2019-01 to 2026-07.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Checked that every month's shares mean what is published: the nine non-aggregated sources add up to 100%, Clean generation is Renewables plus Nuclear, Renewables is the five renewable sources, and the Clean share is Clean over Total generation, each to within the rounding of the printed values.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Noted on each month how many countries and economies have Total generation in the file for it (from 84 in 2019-01 to 56 in 2026-07), and marked a month preliminary when a country with generation for an earlier month has none for it, because the World total then includes Ember's estimate for that country. Preliminary months in this vintage: 46, the first 2022-10 and the last 2026-07.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          },
          {
            "description": "Published Ember's 'Share of generation (%)' for each of the nine sources as printed.",
            "inputs": ["6c8a587a5dfe32277616135e3c5af8e3cb60dff8eba1d4bc18b9b936b0c75d55"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/ember_monthly.py",
            "transform_sha256": "0cc7356131783d6ac00bb9e260a456b0ab7d721a1beafde0c28984a7c9126efa"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Share of electricity generation in the month, not of consumption: net imports are not included. The World total is Ember's estimate built from the countries with monthly data; values are revised as data arrive.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ember-monthly"],
      "time_basis": "calendar",
      "title": "World electricity generation by source, monthly",
      "unit": {
        "code": "percent",
        "label": "percent of electricity generation",
        "short": "%"
      },
      "vintage": "2026-09-18"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "5b24f6535d589bae06a472c4841668e9c55af436a37c72493fc53e5595bbbeae",
      "geo_coverage": "global-only",
      "id": "emissions.gcb-2025.budget-global",
      "latest": {
        "age_bp": null,
        "dims": {
          "component": "fossil"
        },
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 38.598578032645094
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Global Carbon Project data: Supplemental data of Global Carbon Budget 2025 (Version 1.0), ICOS Carbon Portal, doi:10.18160/GCP-2025, CC BY 4.0. Friedlingstein et al. (2026), Global Carbon Budget 2025, Earth Syst. Sci. Data 18, 3211–3288, doi:10.5194/essd-18-3211-2026. Changes: converted from billion tonnes of carbon to billion tonnes of carbon dioxide (× 3.664); one-sigma ranges added for fossil and land-use change emissions from the uncertainties stated in the sheet.",
        "description": "Each year since 1959, the carbon dioxide released by fossil fuels and industry and by land-use change, and where it went: growth in the atmosphere, uptake by the ocean, by land ecosystems and by cement as it ages (the cement carbonation sink). The budget imbalance is what the estimates of emissions and sinks do not account for.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (ICOS CCBY4 Data Licence)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Atmospheric growth from 1959: NOAA Global Monitoring Laboratory (Lan et al.), with Scripps Institution of Oceanography measurements for 1959 to 1980. Historical budget before 1959: atmospheric growth from Joos and Spahni (2008), Proc. Natl. Acad. Sci. 105, 1425–1430; ocean sink from DeVries et al. (2014), Global Biogeochem. Cycles 28, 631–647, and Khatiwala et al. (2013), Biogeosciences 10, 2169–2191.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-budget", "bytes": 480363, "citation_full": "Global Carbon Project. (2026). Supplemental data of Global Carbon Budget 2025 (Version 1.0) [Data set]. Global Carbon Project. https://doi.org/10.18160/gcp-2025", "date_accessed": "2026-10-04", "date_published": "2026-05-17", "doi": "10.18160/GCP-2025", "etag": "\"d62ae19e36bfa4d1\"", "last_modified": "Sun, 17 May 2026 16:23:09 GMT", "licence": {"name": "CC BY 4.0 (ICOS CCBY4 Data Licence)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project", "r2_url": "https://files.environmentdashboard.org/raw/a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9.zst", "sha256": "a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9", "source_id": "gcb-2025-global", "title": "Global Carbon Budget 2025: global sources and sinks of carbon dioxide", "url_download": "https://data.icos-cp.eu/objects/qSjPBsV1drZnYdH-yCJMmkGn", "url_main": "https://www.icos-cp.eu/GCP/2025", "version_producer": "2025 v1.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the sheet 'Global Carbon Budget' of Global_Carbon_Budget_2025_v1.0.xlsx (Global Carbon Budget 2025 v1.0, ICOS object qSjPBsV1drZnYdH-yCJMmkGn): one row per year 1959–2024, in billion tonnes of carbon per year. Sinks are positive numbers in the sheet and stay positive here.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          },
          {
            "description": "Checked the sheet's definition of the budget imbalance on every year: fossil emissions plus land-use change emissions, minus atmospheric growth, ocean sink, land sink and cement carbonation sink, equals the imbalance column (largest difference 3.3e-14 GtC/yr). This confirms that the fossil column is before the cement carbonation sink is subtracted.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          },
          {
            "description": "Converted from billion tonnes of carbon to billion tonnes of carbon dioxide by multiplying by 3.664, the factor the sheet states (\"multiply the numbers below by 3.664\"), with exact decimal arithmetic on the stored values.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          },
          {
            "description": "Lower and upper are given for two components only, from the one-sigma uncertainties the sheet states: ±5 % of fossil emissions, and ±0.7 billion tonnes of carbon (2.5648 billion tonnes of carbon dioxide) per year for land-use change. The sheet gives the ocean sink (±0.4) and land sink (±0.5 billion tonnes of carbon per year) uncertainties only 'on average' and atmospheric growth's as 'variable', so those components and the imbalance have no range.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide only. Fossil emissions are before the cement carbonation sink is subtracted; sinks are positive numbers. Land-use change is the average of three bookkeeping models (BLUE, OSCAR, LUCE); the ocean and land sinks are model and data-product averages.",
          "bunkers": "included",
          "geography": "World",
          "gwp": null,
          "lulucf": "included"
        }
      },
      "source_ids": ["gcb-2025-global"],
      "time_basis": "calendar",
      "title": "Global carbon dioxide budget: emissions and where they go",
      "unit": {
        "code": "GtCO2/yr",
        "label": "billion tonnes of carbon dioxide per year",
        "short": "Gt CO₂/yr"
      },
      "vintage": "2025 v1.0"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "e6cbcb81086cf54ec9fbd401abf0ad73530e5634202e68ea37fb2540547e1e37",
      "geo_coverage": "global-only",
      "id": "emissions.gcb-2025.fossil-growth-2025-projection",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "projection",
        "value": 1.0
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Friedlingstein et al. (2026), Global Carbon Budget 2025, Earth Syst. Sci. Data 18, 3211–3288, doi:10.5194/essd-18-3211-2026. CC BY 4.0.",
        "description": "The Global Carbon Project's projection that carbon dioxide emissions from fossil fuels and industry grew by 1.0 percent from 2024 to 2025 (range 0.2 to 1.7 percent), made from data for part of 2025.",
        "kind": "published-value",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "article-pdf", "bytes": 13426392, "citation_full": "Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Li, H., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Aas, K., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Bellouin, N., Benoit-Cattin, A., Berghoff, C. F., Bernardello, R., Bopp, L., Brasika, I. B. M., Chamberlain, M. A., Chandra, N., Chevallier, F., Chini, L. P., Collier, N. O., Colligan, T. H., Cronin, M., Djeutchouang, L. M., Dou, X., Enright, M. P., Enyo, K., Erb, M., Evans, W., Feely, R. A., Feng, L., Ford, D. J., Foster, A., Fransner, F., Gasser, T., Gehlen, M., Gkritzalis, T., Goncalves De Souza, J., Grassi, G., Gregor, L., Gruber, N., Guenet, B., Gürses, Ö., Harrington, K., Harris, I., Heinke, J., Hurtt, G. C., Iida, Y., Ilyina, T., Ito, A., Jacobson, A. R., Jain, A. K., Jarníková, T., Jersild, A., Jiang, F., Jones, S. D., Kato, E., Keeling, R. F., Klein Goldewijk, K., Knauer, J., Kong, Y., Korsbakken, J. I., Koven, C., Kunimitsu, T., Lan, X., Liu, J., Liu, Z., Liu, Z., Lo Monaco, C., Ma, L., Marland, G., McGuire, P. C., McKinley, G. A., Melton, J. R., Monacci, N., Monier, E., Morgan, E. J., Munro, D. R., Müller, J. D., Nakaoka, S.-I., Nayagam, L. R., Niwa, Y., Nutzel, T., Olsen, A., Omar, A. M., Pan, N., Pandey, S., Pierrot, D., Qin, Z., Regnier, P., Rehder, G., Resplandy, L., Roobaert, A., Rosan, T. M., Rödenbeck, C., Schwinger, J., Skjelvan, I., Smallman, T. L., Spada, V., Sreeush, M. G., Sun, Q., Sutton, A. J., Sweeney, C., Swingedouw, D., Séférian, R., Takao, S., Tatebe, H., Tian, H., Tian, X., Tilbrook, B., Tsujino, H., Tubiello, F., van Ooijen, E., van der Werf, G. R., van de Velde, S. J., Walker, A. P., Wanninkhof, R., Yang, X., Yuan, W., Yue, X., and Zeng, J.: Global Carbon Budget 2025, Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, 2026.", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.5194/essd-18-3211-2026", "etag": "\"ccded8-65af2497bdb07\"", "last_modified": "Tue, 08 Sep 2026 05:48:41 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project; published by Copernicus Publications in Earth System Science Data", "r2_url": "https://files.environmentdashboard.org/raw/166e10a66b4dfb1e3396be57dc0596a9e3de6c17a293a2f0b933d5f30572df12.zst", "sha256": "166e10a66b4dfb1e3396be57dc0596a9e3de6c17a293a2f0b933d5f30572df12", "source_id": "gcb-2025-essd", "title": "Global Carbon Budget 2025 (Friedlingstein et al. 2026, Earth System Science Data)", "url_download": "https://essd.copernicus.org/articles/18/3211/2026/essd-18-3211-2026.pdf", "url_main": "https://doi.org/10.5194/essd-18-3211-2026", "version_producer": "Global Carbon Budget 2025 (ESSD 18, 3211–3288, 2026)", "wayback_url": null}
        ],
        "processing": [
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        "attribution": "Calculated by Environment Dashboard from Global Carbon Project data: Supplemental data of Global Carbon Budget 2025 (Version 1.0), ICOS Carbon Portal, doi:10.18160/GCP-2025, CC BY 4.0. Friedlingstein et al. (2026), Global Carbon Budget 2025, Earth Syst. Sci. Data 18, 3211–3288, doi:10.5194/essd-18-3211-2026. Changes: cement carbonation sink subtracted from fossil emissions; converted from billion tonnes of carbon to billion tonnes of carbon dioxide (× 3.664).",
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        "kind": "series",
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        },
        "notice": "Atmospheric growth from 1959: NOAA Global Monitoring Laboratory (Lan et al.), with Scripps Institution of Oceanography measurements for 1959 to 1980. Historical budget before 1959: atmospheric growth from Joos and Spahni (2008), Proc. Natl. Acad. Sci. 105, 1425–1430; ocean sink from DeVries et al. (2014), Global Biogeochem. Cycles 28, 631–647, and Khatiwala et al. (2013), Biogeosciences 10, 2169–2191.",
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        ],
        "processing": [
          {
            "description": "Read the sheet 'Global Carbon Budget' of Global_Carbon_Budget_2025_v1.0.xlsx (Global Carbon Budget 2025 v1.0, ICOS object qSjPBsV1drZnYdH-yCJMmkGn): one row per year 1959–2024, in billion tonnes of carbon per year. Sinks are positive numbers in the sheet and stay positive here.",
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          {
            "description": "Checked the sheet's definition of the budget imbalance on every year: fossil emissions plus land-use change emissions, minus atmospheric growth, ocean sink, land sink and cement carbonation sink, equals the imbalance column (largest difference 3.3e-14 GtC/yr). This confirms that the fossil column is before the cement carbonation sink is subtracted.",
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          },
          {
            "description": "Subtracted the cement carbonation sink from fossil emissions (excluding carbonation) for each year, which gives the Global Carbon Budget's headline fossil value.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
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            "description": "Converted from billion tonnes of carbon to billion tonnes of carbon dioxide by multiplying by 3.664, the factor the sheet states (\"multiply the numbers below by 3.664\"), with exact decimal arithmetic on the stored values.",
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      "time_basis": "calendar",
      "title": "Fossil carbon dioxide emissions, world (Global Carbon Budget)",
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        "value": 170.0
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        "attribution": "Friedlingstein et al. (2026), Global Carbon Budget 2025, Earth Syst. Sci. Data 18, 3211–3288, doi:10.5194/essd-18-3211-2026. CC BY 4.0.",
        "description": "How much more carbon dioxide could be emitted from the beginning of 2026 for an even (50 percent) chance of limiting global warming to 1.5 °C, according to the Global Carbon Budget 2025: 170 billion tonnes, which the paper puts at around 4 years of emissions at the 2025 level.",
        "kind": "published-value",
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          {"acquisition": "automatic", "artifact_id": "article-pdf", "bytes": 13426392, "citation_full": "Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Li, H., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Aas, K., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Bellouin, N., Benoit-Cattin, A., Berghoff, C. F., Bernardello, R., Bopp, L., Brasika, I. B. M., Chamberlain, M. A., Chandra, N., Chevallier, F., Chini, L. P., Collier, N. O., Colligan, T. H., Cronin, M., Djeutchouang, L. M., Dou, X., Enright, M. P., Enyo, K., Erb, M., Evans, W., Feely, R. A., Feng, L., Ford, D. J., Foster, A., Fransner, F., Gasser, T., Gehlen, M., Gkritzalis, T., Goncalves De Souza, J., Grassi, G., Gregor, L., Gruber, N., Guenet, B., Gürses, Ö., Harrington, K., Harris, I., Heinke, J., Hurtt, G. C., Iida, Y., Ilyina, T., Ito, A., Jacobson, A. R., Jain, A. K., Jarníková, T., Jersild, A., Jiang, F., Jones, S. D., Kato, E., Keeling, R. F., Klein Goldewijk, K., Knauer, J., Kong, Y., Korsbakken, J. I., Koven, C., Kunimitsu, T., Lan, X., Liu, J., Liu, Z., Liu, Z., Lo Monaco, C., Ma, L., Marland, G., McGuire, P. C., McKinley, G. A., Melton, J. R., Monacci, N., Monier, E., Morgan, E. J., Munro, D. R., Müller, J. D., Nakaoka, S.-I., Nayagam, L. R., Niwa, Y., Nutzel, T., Olsen, A., Omar, A. M., Pan, N., Pandey, S., Pierrot, D., Qin, Z., Regnier, P., Rehder, G., Resplandy, L., Roobaert, A., Rosan, T. M., Rödenbeck, C., Schwinger, J., Skjelvan, I., Smallman, T. L., Spada, V., Sreeush, M. G., Sun, Q., Sutton, A. J., Sweeney, C., Swingedouw, D., Séférian, R., Takao, S., Tatebe, H., Tian, H., Tian, X., Tilbrook, B., Tsujino, H., Tubiello, F., van Ooijen, E., van der Werf, G. R., van de Velde, S. J., Walker, A. P., Wanninkhof, R., Yang, X., Yuan, W., Yue, X., and Zeng, J.: Global Carbon Budget 2025, Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, 2026.", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.5194/essd-18-3211-2026", "etag": "\"ccded8-65af2497bdb07\"", "last_modified": "Tue, 08 Sep 2026 05:48:41 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project; published by Copernicus Publications in Earth System Science Data", "r2_url": "https://files.environmentdashboard.org/raw/166e10a66b4dfb1e3396be57dc0596a9e3de6c17a293a2f0b933d5f30572df12.zst", "sha256": "166e10a66b4dfb1e3396be57dc0596a9e3de6c17a293a2f0b933d5f30572df12", "source_id": "gcb-2025-essd", "title": "Global Carbon Budget 2025 (Friedlingstein et al. 2026, Earth System Science Data)", "url_download": "https://essd.copernicus.org/articles/18/3211/2026/essd-18-3211-2026.pdf", "url_main": "https://doi.org/10.5194/essd-18-3211-2026", "version_producer": "Global Carbon Budget 2025 (ESSD 18, 3211–3288, 2026)", "wayback_url": null}
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        "processing": [
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            "description": "Value: \"170 GtCO₂ left\" is published as 170 billion tonnes of carbon dioxide, dated 2026-01-01 because the paper counts the budget \"from the beginning of 2026\".",
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          "quote": "The remaining carbon budget from the beginning of 2026 for a 50 % likelihood to limit warming to 1.5 °C is nearly exhausted (50 GtC, 170 GtCO₂ left, equivalent to around 4 years at the 2025 emissions levels)"
        },
        "scope": {
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          "basis": "Cumulative carbon dioxide emissions from 1 January 2026 for a 50 percent likelihood of limiting warming to 1.5 °C above 1850–1900, as assessed in the Global Carbon Budget 2025. The budget is for total anthropogenic carbon dioxide, fossil and land-use change together (the paper updates the underlying IPCC AR6 estimate \"accounting for the 2020 to 2025 GCB estimated anthropogenic emissions from fossil combustion (EFOS) and land use change (ELUC)\" and states how long the budgets last \"at the 2025 level of total anthropogenic CO2 emissions\", p. 3259). Assessments made with other methods, such as Indicators of Global Climate Change 2025, give different values from the same date.",
          "bunkers": "included",
          "geography": "World",
          "gwp": null,
          "lulucf": "included"
        }
      },
      "source_ids": ["gcb-2025-essd"],
      "time_basis": "calendar",
      "title": "Remaining carbon budget for 1.5 °C from the start of 2026 (Global Carbon Budget)",
      "unit": {
        "code": "GtCO2",
        "label": "billion tonnes of carbon dioxide",
        "short": "Gt CO₂"
      },
      "vintage": "Global Carbon Budget 2025 (ESSD 18, 3211–3288, 2026)"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
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      "export_sha256": "9758007eb92a4615e7cd55a7d80daa9e9496edf2eecf1f4135ddb283b8a2a3cb",
      "geo_coverage": "mixed",
      "id": "emissions.gcb-2025.territorial-vs-consumption",
      "latest": {
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        "dims": {
          "accounting": "territorial"
        },
        "entity": "WLD",
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        "attribution": "Calculated by Environment Dashboard from Global Carbon Project data: Supplemental data of Global Carbon Budget 2025 (Version 1.0), ICOS Carbon Portal, doi:10.18160/GCP-2025, CC BY 4.0. Friedlingstein et al. (2026), Global Carbon Budget 2025, Earth Syst. Sci. Data 18, 3211–3288, doi:10.5194/essd-18-3211-2026. Changes: converted from million tonnes of carbon to million tonnes of carbon dioxide (× 3.664); years before 1990 left out.",
        "description": "Each country's fossil carbon dioxide emissions counted two ways since 1990: where they are released (territorial), and where the goods and services they went into are finally consumed (consumption-based). Where consumption-based emissions are higher, the country's imports carried more emissions than its exports.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (ICOS CCBY4 Data Licence)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Consumption-based emissions and emissions transfers: updated from Peters, Davis and Andrew (2012), Biogeosciences 9, 3247–3276, doi:10.5194/bg-9-3247-2012. Land-use change by country: BLUE (Hansis et al., 2015, doi:10.1002/2014gb004997), OSCAR (Gasser et al., 2020, doi:10.5194/bg-17-4075-2020) and LUCE (Qin et al., 2024, doi:10.1016/j.oneear.2024.04.002).",
        "origins": [
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        ],
        "processing": [
          {
            "description": "Read the sheets 'Territorial Emissions' and 'Consumption Emissions' of National_Fossil_Carbon_Emissions_2025_v1.0.xlsx (Global Carbon Budget 2025 v1.0, ICOS object loCXyssaalv6DPdO6Qdj90qQ), in million tonnes of carbon per year, and kept the years of the consumption sheet, 1990–2024.",
            "inputs": ["968097cacb1a6a5bfa0cf74ee90763f74a90ef10499e060ab43d1a74c671d46b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_national.py",
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          {
            "description": "Mapped column names to entity codes by the entity table's names and an explicit alias table; left out the producer's regions (Kyoto Protocol Annex B and non-Annex B, OECD and non-OECD, and eight continental regions) and the statistical difference column. EU27 is kept after checking that the Regions sheet lists exactly the 27 member states.",
            "inputs": ["968097cacb1a6a5bfa0cf74ee90763f74a90ef10499e060ab43d1a74c671d46b"],
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            "script": "pipeline/src/envdash/transforms/emissions/gcb_national.py",
            "transform_sha256": "b2048d4a16c8112cc30377657d7b0e3894a02b8aa09d05c1224d4059a5208ef9"
          },
          {
            "description": "Converted from million tonnes of carbon to million tonnes of carbon dioxide by multiplying by 3.664, the factor the sheets state (\"multiply the values below by 3.664\"), with exact decimal arithmetic on the stored values.",
            "inputs": ["968097cacb1a6a5bfa0cf74ee90763f74a90ef10499e060ab43d1a74c671d46b"],
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          {
            "description": "Cells left empty in the file are not published and are never read as zero.",
            "inputs": ["968097cacb1a6a5bfa0cf74ee90763f74a90ef10499e060ab43d1a74c671d46b"],
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          }
        ],
        "published_value": null,
        "scope": {
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          "basis": "Carbon dioxide only, from fossil fuels and cement production, before the cement carbonation sink is subtracted (gross). National values exclude international aviation and shipping bunker fuels, which are separate entities; the world value includes them. Consumption-based accounting follows Peters et al. (2011).",
          "bunkers": "excluded",
          "geography": "Countries and territories, the European Union (27), international aviation, international shipping and the world",
          "gwp": null,
          "lulucf": "excluded"
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      },
      "source_ids": ["gcb-2025-national"],
      "time_basis": "calendar",
      "title": "Territorial and consumption-based fossil carbon dioxide emissions by country",
      "unit": {
        "code": "MtCO2/yr",
        "label": "million tonnes of carbon dioxide per year",
        "short": "Mt CO₂/yr"
      },
      "vintage": "2025 v1.0"
    },
    {
      "display": {
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      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "8294fb4ad81b7d3756fa57fc0ee1cc5dd1b160a7cb74fbd5cac09c72f1eca712",
      "geo_coverage": "global-only",
      "id": "emissions.gcb-2025.total-co2-global",
      "latest": {
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      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Global Carbon Project data: Supplemental data of Global Carbon Budget 2025 (Version 1.0), ICOS Carbon Portal, doi:10.18160/GCP-2025, CC BY 4.0. Friedlingstein et al. (2026), Global Carbon Budget 2025, Earth Syst. Sci. Data 18, 3211–3288, doi:10.5194/essd-18-3211-2026. Changes: cement carbonation sink subtracted from fossil emissions and land-use change emissions added; converted from billion tonnes of carbon to billion tonnes of carbon dioxide (× 3.664).",
        "description": "Carbon dioxide released each year since 1959 by fossil fuels and industry (net of the cement carbonation sink) and by land-use change such as deforestation.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (ICOS CCBY4 Data Licence)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Atmospheric growth from 1959: NOAA Global Monitoring Laboratory (Lan et al.), with Scripps Institution of Oceanography measurements for 1959 to 1980. Historical budget before 1959: atmospheric growth from Joos and Spahni (2008), Proc. Natl. Acad. Sci. 105, 1425–1430; ocean sink from DeVries et al. (2014), Global Biogeochem. Cycles 28, 631–647, and Khatiwala et al. (2013), Biogeosciences 10, 2169–2191.",
        "origins": [
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        "processing": [
          {
            "description": "Read the sheet 'Global Carbon Budget' of Global_Carbon_Budget_2025_v1.0.xlsx (Global Carbon Budget 2025 v1.0, ICOS object qSjPBsV1drZnYdH-yCJMmkGn): one row per year 1959–2024, in billion tonnes of carbon per year. Sinks are positive numbers in the sheet and stay positive here.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
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            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
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          {
            "description": "Checked the sheet's definition of the budget imbalance on every year: fossil emissions plus land-use change emissions, minus atmospheric growth, ocean sink, land sink and cement carbonation sink, equals the imbalance column (largest difference 3.3e-14 GtC/yr). This confirms that the fossil column is before the cement carbonation sink is subtracted.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          },
          {
            "description": "For each year: fossil emissions (excluding carbonation) minus the cement carbonation sink, plus land-use change emissions.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          },
          {
            "description": "Converted from billion tonnes of carbon to billion tonnes of carbon dioxide by multiplying by 3.664, the factor the sheet states (\"multiply the numbers below by 3.664\"), with exact decimal arithmetic on the stored values.",
            "inputs": ["a928cf06c57576b66761d1fec8224c9a41a781eb63442afc03ba902858dd64a9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcb_global.py",
            "transform_sha256": "63ef45577c93e407d829b864e7503055cba3ebf917a19ce9f03bf6f38914a16b"
          }
        ],
        "published_value": null,
        "scope": {
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          "basis": "Carbon dioxide only: fossil fuels and industry net of the cement carbonation sink, plus land-use change (average of three bookkeeping models).",
          "bunkers": "included",
          "geography": "World",
          "gwp": null,
          "lulucf": "included"
        }
      },
      "source_ids": ["gcb-2025-global"],
      "time_basis": "calendar",
      "title": "Total carbon dioxide emissions from human activity, world (Global Carbon Budget)",
      "unit": {
        "code": "GtCO2/yr",
        "label": "billion tonnes of carbon dioxide per year",
        "short": "Gt CO₂/yr"
      },
      "vintage": "2025 v1.0"
    },
    {
      "display": {
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      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "INTL_AIR", "INTL_SEA", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "KWT_OILFIRES", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAC_ISLANDS", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "ROU", "RUS", "RWA", "RYUKYU", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "4f76a454b74557569abc925256bf0cd35dfcf524c453800fad7eb5c5cd99970c",
      "geo_coverage": "mixed",
      "id": "emissions.gcp-2025.fossil-co2-by-country",
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      "provenance": {
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        "description": "Carbon dioxide released each year since 1750 by burning coal, oil and gas, making cement, flaring gas and other industrial uses of carbonates, in each country where it was emitted. International aviation and shipping are shown on their own and counted in the world total.",
        "kind": "series",
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        "origins": [
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          {"acquisition": "automatic", "artifact_id": "mtco2-metadata", "bytes": 3784, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4.zst", "sha256": "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat_metadata.json/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null}
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        "processing": [
          {
            "description": "Read GCB2025v15_MtCO2_flat.csv (version 2025v15): 222 entities (countries, territories, international aviation, international shipping, three historical entities and the world), each 1750–2024, in million tonnes of carbon dioxide. The metadata file's titles, units and version were checked against the columns. Producer codes were mapped to entity codes through an explicit alias table (KSV Kosovo, XIA international aviation, XIS international shipping; the Kuwaiti oil fires, the Pacific Islands (Palau) and the Ryukyu Islands by name).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Checked that the file's Global row equals the sum of all other rows (countries, international aviation and shipping, historical entities) in every year (largest difference 0.000008 Mt).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Published the Total column as stated.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Cells left empty in the file are not published and are never read as zero.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide only, from fossil fuels, cement production (process emissions), gas flaring and other carbonates, before the cement carbonation sink is subtracted (gross). National values exclude international aviation and shipping, which are separate entities; the world value includes them. Territorial (production-based) accounting.",
          "bunkers": "excluded",
          "geography": "Countries and territories, international aviation, international shipping, three historical entities and the world",
          "gwp": null,
          "lulucf": "excluded"
        }
      },
      "source_ids": ["gcp-fossil-co2-2025"],
      "time_basis": "calendar",
      "title": "Fossil carbon dioxide emissions by country",
      "unit": {
        "code": "MtCO2/yr",
        "label": "million tonnes of carbon dioxide per year",
        "short": "Mt CO₂/yr"
      },
      "vintage": "2025v15"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "INTL_AIR", "INTL_SEA", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "KWT_OILFIRES", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAC_ISLANDS", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "ROU", "RUS", "RWA", "RYUKYU", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "793cfad57ac253b6f24d03a7f0e5451f646823eb35a988b27190306868c7e241",
      "geo_coverage": "mixed",
      "id": "emissions.gcp-2025.fossil-co2-by-fuel",
      "latest": {
        "age_bp": null,
        "dims": {
          "fuel": "coal"
        },
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 15805.254152
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Andrew and Peters (2025), The Global Carbon Project's fossil CO2 emissions dataset, version 2025v15, doi:10.5281/zenodo.17417124, CC BY 4.0. Part of the Global Carbon Budget 2025 (Friedlingstein et al., 2026, Earth Syst. Sci. Data 18, 3211–3288).",
        "description": "Each country's fossil carbon dioxide emissions since 1750 split by source: coal, oil, gas, cement production, gas flaring and other carbonates.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "mtco2-flat", "bytes": 3147221, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff.zst", "sha256": "20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat.csv/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "mtco2-metadata", "bytes": 3784, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4.zst", "sha256": "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat_metadata.json/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read GCB2025v15_MtCO2_flat.csv (version 2025v15): 222 entities (countries, territories, international aviation, international shipping, three historical entities and the world), each 1750–2024, in million tonnes of carbon dioxide. The metadata file's titles, units and version were checked against the columns. Producer codes were mapped to entity codes through an explicit alias table (KSV Kosovo, XIA international aviation, XIS international shipping; the Kuwaiti oil fires, the Pacific Islands (Palau) and the Ryukyu Islands by name).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Published the Coal, Oil, Gas, Cement, Flaring and Other columns as stated, one value of the fuel dimension each.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Cells left empty in the file are not published and are never read as zero. The Global row's Other column is empty for 1904–1989, so the world has no 'other carbonates' value in those years, although its Total includes the other carbonates countries report.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide only, from fossil fuels, cement production (process emissions), gas flaring and other carbonates, before the cement carbonation sink is subtracted (gross). National values exclude international aviation and shipping, which are separate entities; the world value includes them. Territorial (production-based) accounting.",
          "bunkers": "excluded",
          "geography": "Countries and territories, international aviation, international shipping, three historical entities and the world",
          "gwp": null,
          "lulucf": "excluded"
        }
      },
      "source_ids": ["gcp-fossil-co2-2025"],
      "time_basis": "calendar",
      "title": "Fossil carbon dioxide emissions by country and fuel",
      "unit": {
        "code": "MtCO2/yr",
        "label": "million tonnes of carbon dioxide per year",
        "short": "Mt CO₂/yr"
      },
      "vintage": "2025v15"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "INTL_AIR", "INTL_SEA", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "KWT_OILFIRES", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAC_ISLANDS", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "ROU", "RUS", "RWA", "RYUKYU", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "e5d4ec2ff0497ad49b9fc3b5eebb722a56886fdfeedb65cd885c8c1f11d9370e",
      "geo_coverage": "mixed",
      "id": "emissions.gcp-2025.fossil-co2-cumulative",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 1849.123858831
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Global Carbon Project data: Andrew and Peters (2025), The Global Carbon Project's fossil CO2 emissions dataset, version 2025v15, doi:10.5281/zenodo.17417124, CC BY 4.0. Changes: annual values added up into a running total since the first year with a value; converted from million to billion tonnes.",
        "description": "All the fossil carbon dioxide each country has emitted from 1750 up to each year: the running total of its annual emissions.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "mtco2-flat", "bytes": 3147221, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff.zst", "sha256": "20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat.csv/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "mtco2-metadata", "bytes": 3784, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4.zst", "sha256": "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat_metadata.json/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read GCB2025v15_MtCO2_flat.csv (version 2025v15): 222 entities (countries, territories, international aviation, international shipping, three historical entities and the world), each 1750–2024, in million tonnes of carbon dioxide. The metadata file's titles, units and version were checked against the columns. Producer codes were mapped to entity codes through an explicit alias table (KSV Kosovo, XIA international aviation, XIS international shipping; the Kuwaiti oil fires, the Pacific Islands (Palau) and the Ryukyu Islands by name).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Checked that the file's Global row equals the sum of all other rows (countries, international aviation and shipping, historical entities) in every year (largest difference 0.000008 Mt).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "For each entity, added up its Total column year by year from the first year the file gives a value (the file starts in 1750), with exact decimal arithmetic. A year whose cell is empty adds nothing: the producer's Global row is built the same way (it equals the sum of the stated values). Observations whose sum spans such years say how many.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Converted from million to billion tonnes (divided by 1,000).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Sum since 1750, the first year of the file",
          "basis": "Carbon dioxide only, from fossil fuels, cement production (process emissions), gas flaring and other carbonates, before the cement carbonation sink is subtracted (gross). National values exclude international aviation and shipping, which are separate entities; the world value includes them. Territorial (production-based) accounting. Running total of annual values.",
          "bunkers": "excluded",
          "geography": "Countries and territories, international aviation, international shipping, three historical entities and the world",
          "gwp": null,
          "lulucf": "excluded"
        }
      },
      "source_ids": ["gcp-fossil-co2-2025"],
      "time_basis": "calendar",
      "title": "Cumulative fossil carbon dioxide emissions since 1750",
      "unit": {
        "code": "GtCO2",
        "label": "billion tonnes of carbon dioxide",
        "short": "Gt CO₂"
      },
      "vintage": "2025v15"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "INTL_AIR", "INTL_SEA", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "KWT_OILFIRES", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAC_ISLANDS", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "ROU", "RUS", "RWA", "RYUKYU", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "ff20ec00dacd64b1fbb51e0a6782f528aab1182d3586aa113b5c68c7320be1cc",
      "geo_coverage": "mixed",
      "id": "emissions.gcp-2025.fossil-co2-cumulative-share",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "USA",
        "period": "2024",
        "status": "final",
        "value": 23.517438582395386
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      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Global Carbon Project data: Andrew and Peters (2025), The Global Carbon Project's fossil CO2 emissions dataset, version 2025v15, doi:10.5281/zenodo.17417124, CC BY 4.0. Changes: annual values added up into running totals and divided by the world's running total (percent).",
        "description": "Each country's cumulative fossil carbon dioxide emissions since 1750 as a percentage of the world's, up to each year.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "mtco2-flat", "bytes": 3147221, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff.zst", "sha256": "20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat.csv/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "mtco2-metadata", "bytes": 3784, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4.zst", "sha256": "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat_metadata.json/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read GCB2025v15_MtCO2_flat.csv (version 2025v15): 222 entities (countries, territories, international aviation, international shipping, three historical entities and the world), each 1750–2024, in million tonnes of carbon dioxide. The metadata file's titles, units and version were checked against the columns. Producer codes were mapped to entity codes through an explicit alias table (KSV Kosovo, XIA international aviation, XIS international shipping; the Kuwaiti oil fires, the Pacific Islands (Palau) and the Ryukyu Islands by name).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Checked that the file's Global row equals the sum of all other rows (countries, international aviation and shipping, historical entities) in every year (largest difference 0.000008 Mt).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "For each entity, added up its Total column year by year from the first year the file gives a value (the file starts in 1750), with exact decimal arithmetic. A year whose cell is empty adds nothing: the producer's Global row is built the same way (it equals the sum of the stated values). Observations whose sum spans such years say how many.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Divided each entity's cumulative total by the cumulative total of the file's Global row for the same year and multiplied by 100. International aviation, international shipping and the historical entities have shares too, so the countries' shares add up to less than 100 %.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Sum since 1750, the first year of the file",
          "basis": "Carbon dioxide only, from fossil fuels, cement production (process emissions), gas flaring and other carbonates, before the cement carbonation sink is subtracted (gross). National values exclude international aviation and shipping, which are separate entities; the world value includes them. Territorial (production-based) accounting. Running totals divided by the world's running total; international aviation and shipping hold their own shares.",
          "bunkers": "excluded",
          "geography": "Countries and territories, international aviation, international shipping, three historical entities and the world",
          "gwp": null,
          "lulucf": "excluded"
        }
      },
      "source_ids": ["gcp-fossil-co2-2025"],
      "time_basis": "calendar",
      "title": "Share of the world's cumulative fossil carbon dioxide emissions since 1750",
      "unit": {
        "code": "percent",
        "label": "percent",
        "short": "%"
      },
      "vintage": "2025v15"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAC_ISLANDS", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "57418721860413e07b15529fc699efd3df5c690ea9deeabc4f640a6f21a8e5c1",
      "geo_coverage": "mixed",
      "id": "emissions.gcp-2025.fossil-co2-per-capita",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 4.729075
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Andrew and Peters (2025), The Global Carbon Project's fossil CO2 emissions dataset, version 2025v15, doi:10.5281/zenodo.17417124, CC BY 4.0. Part of the Global Carbon Budget 2025 (Friedlingstein et al., 2026, Earth Syst. Sci. Data 18, 3211–3288).",
        "description": "Each country's fossil carbon dioxide emissions in a year divided by its population, as the Global Carbon Project publishes them.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "mtco2-flat", "bytes": 3147221, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff.zst", "sha256": "20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat.csv/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "mtco2-metadata", "bytes": 3784, "citation_full": "Andrew, R. M. and Peters, G. P.: The Global Carbon Project’s fossil CO2 emissions dataset (2025v15), https://zenodo.org/records/17417124, 2025.", "date_accessed": "2026-10-04", "date_published": "2025-10-22", "doi": "10.5281/zenodo.17417124", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Global Carbon Project (Robbie M. Andrew and Glen P. Peters, CICERO)", "r2_url": "https://files.environmentdashboard.org/raw/b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4.zst", "sha256": "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4", "source_id": "gcp-fossil-co2-2025", "title": "The Global Carbon Project's fossil CO2 emissions dataset, 2025 release", "url_download": "https://zenodo.org/api/records/17417124/files/GCB2025v15_MtCO2_flat_metadata.json/content", "url_main": "https://zenodo.org/records/17417124", "version_producer": "2025v15", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read GCB2025v15_MtCO2_flat.csv (version 2025v15): 222 entities (countries, territories, international aviation, international shipping, three historical entities and the world), each 1750–2024, in million tonnes of carbon dioxide. The metadata file's titles, units and version were checked against the columns. Producer codes were mapped to entity codes through an explicit alias table (KSV Kosovo, XIA international aviation, XIS international shipping; the Kuwaiti oil fires, the Pacific Islands (Palau) and the Ryukyu Islands by name).",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Published the Per Capita column as the producer states it (tonnes of carbon dioxide per person); it was not recomputed.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Left out international aviation and international shipping: they have no population, and the file's per-person cell for them is 0 or empty.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Published as null, with the reason, the per-person values the file gives for NLD 1900–1949 (Total divided by Per Capita implies fewer than 20,000 people): a thousand times the values of the neighbouring years.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          },
          {
            "description": "Cells left empty in the file are not published and are never read as zero.",
            "inputs": ["20650c19b394d91b6b31cddff2fbc9508bcdbbed7c3f93660336f2f655f367ff", "b41c76163ac6258fee7203c417a0def6b2e7300dc59943de654b913e824f3cd4"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/gcp_fossil_national.py",
            "transform_sha256": "9cbf1047ea48dc4b3cd8bebf1ad58a2f8c972ff9fc41c01d3f110933e694e366"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide only, from fossil fuels, cement production (process emissions), gas flaring and other carbonates, before the cement carbonation sink is subtracted (gross). National values exclude international aviation and shipping, which are separate entities; the world value includes them. Territorial (production-based) accounting. Per person values are the producer's own; the world value counts international aviation and shipping in its emissions.",
          "bunkers": "excluded",
          "geography": "Countries and territories, three historical entities and the world",
          "gwp": null,
          "lulucf": "excluded"
        }
      },
      "source_ids": ["gcp-fossil-co2-2025"],
      "time_basis": "calendar",
      "title": "Fossil carbon dioxide emissions per person",
      "unit": {
        "code": "tCO2/person/yr",
        "label": "tonnes of carbon dioxide per person per year",
        "short": "t CO₂/person"
      },
      "vintage": "2025v15"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ASM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "b54b2fa2df17e0b04c69ee1f7dc0d17674b3daa871e7cda54e84a9e0b1eede18",
      "geo_coverage": "country",
      "id": "energy.eia.fossil-share",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 88.51414645166243
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      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from U.S. Energy Information Administration international energy data (Sep 2026). Changes: fossil-fuel share calculated as coal, natural gas and petroleum consumption over total energy consumption.",
        "description": "The part of each country's and the world's total energy use that comes from coal, oil and natural gas, each year since 1980, calculated from US Energy Information Administration data.",
        "kind": "derived",
        "licence": {
          "name": "Public domain (work of the US federal government)",
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          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "intl-bulk", "bytes": 24153479, "citation_full": "Source: U.S. Energy Information Administration (Sep 2026).", "date_accessed": "2026-10-05", "date_published": "2026-09-30", "doi": null, "etag": "\"80a6e6761c53dd1:0\"", "last_modified": "Sat, 03 Oct 2026 09:49:21 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "U.S. Energy Information Administration", "r2_url": "https://files.environmentdashboard.org/raw/9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9.zst", "sha256": "9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "source_id": "eia-international", "title": "International energy data", "url_download": "https://www.eia.gov/opendata/bulk/INTL.zip", "url_main": "https://www.eia.gov/international/data/world", "version_producer": "Sep 2026", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "bulk-manifest", "bytes": 28398, "citation_full": "Source: U.S. Energy Information Administration (Sep 2026).", "date_accessed": "2026-10-05", "date_published": "2026-09-30", "doi": null, "etag": "\"044131b054dd1:0\"", "last_modified": "Mon, 05 Oct 2026 09:58:00 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "U.S. Energy Information Administration", "r2_url": "https://files.environmentdashboard.org/raw/1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372.zst", "sha256": "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372", "source_id": "eia-international", "title": "International energy data", "url_download": "https://www.eia.gov/opendata/bulk/manifest.txt", "url_main": "https://www.eia.gov/international/data/world", "version_producer": "Sep 2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read INTL.txt from EIA's bulk file INTL.zip. EIA's bulk manifest gives the INTL release as last updated 30 September 2026 and names this zip as its file, so the vintage is 'Sep 2026'. The zip was last modified on the server on Sat, 03 Oct 2026 09:49:21 GMT.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Kept the annual consumption series in quadrillion Btu: total energy consumption and its five fuels (coal, natural gas, petroleum and other liquids, nuclear, renewables and other), checking each series' name and units. Kept the World and the 220 countries and territories in pipeline/geo/entities.csv, matched by EIA's ISO 3 code (EIA's XKS is Kosovo, KOS, and its SCG, Former Serbia and Montenegro, is Serbia and Montenegro as reported together, SRB_MNE); EIA's regional aggregates are left out, and so are these geographies, which have no entity in the crosswalk: Former Czechoslovakia; Former U.S.S.R.; Former Yugoslavia; Germany, East; Germany, West; Hawaiian Trade Zone; Netherlands Antilles; U.S. Pacific Islands; U.S. Territories; Wake Island.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Checked EIA's accounting method against its own generation series: for every country other than the United States, the energy content of hydro, wind, solar, geothermal and tide and wave electricity is 3,412 Btu per kilowatt-hour, the captured-energy approach (11,140 country-years checked). Not on that basis in this file: USA: 72 values, e.g. solar 2023 3676, solar 2024 3622 Btu per kWh. World nuclear consumption is 10,379 Btu per kilowatt-hour of nuclear generation in 2024, the heat input of the plants.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Where EIA's total differs from the sum of its five fuel series, both are published as given. Entities where they differ in this vintage: USA, WLD (World 2024: total minus the sum is -1.442 quad Btu).",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "EIA's codes '--', 'NA' and 'ie' (which the file does not define) are null values whose reason quotes the code.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Fossil share = (coal + natural gas + petroleum and other liquids) / total energy consumption x 100, for each entity and year with all four values (exact decimal arithmetic on EIA's values). A share above 100% carries a note with both numbers.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Primary energy consumption as EIA accounts for it: fossil fuels at their heat content; electricity from hydro, wind, solar, geothermal and tide and wave power at its own energy content, 3,412 Btu per kilowatt-hour (the captured-energy approach; EIA's United States series depart from it for solar and geothermal); nuclear at the heat input of the plants. Not comparable with totals from the Energy Institute or the IEA, which count non-combustible electricity differently. 'Renewables and other' is EIA's own category and can be negative. Fossil fuels are EIA's coal, natural gas, and petroleum and other liquids; the denominator is EIA's total energy consumption.",
          "bunkers": null,
          "geography": "Countries and territories, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["eia-international"],
      "time_basis": "calendar",
      "title": "Share of primary energy from fossil fuels",
      "unit": {
        "code": "percent",
        "label": "percent of total primary energy consumption",
        "short": "%"
      },
      "vintage": "Sep 2026"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ASM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "a28317b3ffdafb3879c2a1d49a99aa45bcaee608567afd4e141e41e601dfdf81",
      "geo_coverage": "country",
      "id": "energy.eia.primary-by-fuel",
      "latest": {
        "age_bp": null,
        "dims": {
          "fuel": "coal"
        },
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 179.6540438797921
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      "licence_class": "open",
      "provenance": {
        "attribution": "Source: U.S. Energy Information Administration (Sep 2026).",
        "description": "Energy each country and the world use each year since 1980, by fuel: coal, natural gas, oil and other liquids, nuclear, and renewables and other sources, as accounted for by the US Energy Information Administration.",
        "kind": "series",
        "licence": {
          "name": "Public domain (work of the US federal government)",
          "spdx": null,
          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "intl-bulk", "bytes": 24153479, "citation_full": "Source: U.S. Energy Information Administration (Sep 2026).", "date_accessed": "2026-10-05", "date_published": "2026-09-30", "doi": null, "etag": "\"80a6e6761c53dd1:0\"", "last_modified": "Sat, 03 Oct 2026 09:49:21 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "U.S. Energy Information Administration", "r2_url": "https://files.environmentdashboard.org/raw/9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9.zst", "sha256": "9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "source_id": "eia-international", "title": "International energy data", "url_download": "https://www.eia.gov/opendata/bulk/INTL.zip", "url_main": "https://www.eia.gov/international/data/world", "version_producer": "Sep 2026", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "bulk-manifest", "bytes": 28398, "citation_full": "Source: U.S. Energy Information Administration (Sep 2026).", "date_accessed": "2026-10-05", "date_published": "2026-09-30", "doi": null, "etag": "\"044131b054dd1:0\"", "last_modified": "Mon, 05 Oct 2026 09:58:00 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "U.S. Energy Information Administration", "r2_url": "https://files.environmentdashboard.org/raw/1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372.zst", "sha256": "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372", "source_id": "eia-international", "title": "International energy data", "url_download": "https://www.eia.gov/opendata/bulk/manifest.txt", "url_main": "https://www.eia.gov/international/data/world", "version_producer": "Sep 2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read INTL.txt from EIA's bulk file INTL.zip. EIA's bulk manifest gives the INTL release as last updated 30 September 2026 and names this zip as its file, so the vintage is 'Sep 2026'. The zip was last modified on the server on Sat, 03 Oct 2026 09:49:21 GMT.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Kept the annual consumption series in quadrillion Btu: total energy consumption and its five fuels (coal, natural gas, petroleum and other liquids, nuclear, renewables and other), checking each series' name and units. Kept the World and the 220 countries and territories in pipeline/geo/entities.csv, matched by EIA's ISO 3 code (EIA's XKS is Kosovo, KOS, and its SCG, Former Serbia and Montenegro, is Serbia and Montenegro as reported together, SRB_MNE); EIA's regional aggregates are left out, and so are these geographies, which have no entity in the crosswalk: Former Czechoslovakia; Former U.S.S.R.; Former Yugoslavia; Germany, East; Germany, West; Hawaiian Trade Zone; Netherlands Antilles; U.S. Pacific Islands; U.S. Territories; Wake Island.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Checked EIA's accounting method against its own generation series: for every country other than the United States, the energy content of hydro, wind, solar, geothermal and tide and wave electricity is 3,412 Btu per kilowatt-hour, the captured-energy approach (11,140 country-years checked). Not on that basis in this file: USA: 72 values, e.g. solar 2023 3676, solar 2024 3622 Btu per kWh. World nuclear consumption is 10,379 Btu per kilowatt-hour of nuclear generation in 2024, the heat input of the plants.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Where EIA's total differs from the sum of its five fuel series, both are published as given. Entities where they differ in this vintage: USA, WLD (World 2024: total minus the sum is -1.442 quad Btu).",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "EIA's codes '--', 'NA' and 'ie' (which the file does not define) are null values whose reason quotes the code.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
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            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
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          {
            "description": "Published EIA's values for the five fuels as given.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
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            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
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        ],
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        "scope": {
          "baseline": null,
          "basis": "Primary energy consumption as EIA accounts for it: fossil fuels at their heat content; electricity from hydro, wind, solar, geothermal and tide and wave power at its own energy content, 3,412 Btu per kilowatt-hour (the captured-energy approach; EIA's United States series depart from it for solar and geothermal); nuclear at the heat input of the plants. Not comparable with totals from the Energy Institute or the IEA, which count non-combustible electricity differently. 'Renewables and other' is EIA's own category and can be negative.",
          "bunkers": null,
          "geography": "Countries and territories, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["eia-international"],
      "time_basis": "calendar",
      "title": "Primary energy consumption by fuel",
      "unit": {
        "code": "quad-Btu",
        "label": "quadrillion British thermal units",
        "short": "quad Btu"
      },
      "vintage": "Sep 2026"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ASM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "0c428008cdca04767c8bd899be7d8f0bc90772b2a4a8666cbc26f7b03c3f1647",
      "geo_coverage": "country",
      "id": "energy.eia.primary-total",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 606.037013293999
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Source: U.S. Energy Information Administration (Sep 2026).",
        "description": "Total energy each country and the world use each year since 1980, counting every fuel, as accounted for by the US Energy Information Administration.",
        "kind": "series",
        "licence": {
          "name": "Public domain (work of the US federal government)",
          "spdx": null,
          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "intl-bulk", "bytes": 24153479, "citation_full": "Source: U.S. Energy Information Administration (Sep 2026).", "date_accessed": "2026-10-05", "date_published": "2026-09-30", "doi": null, "etag": "\"80a6e6761c53dd1:0\"", "last_modified": "Sat, 03 Oct 2026 09:49:21 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "U.S. Energy Information Administration", "r2_url": "https://files.environmentdashboard.org/raw/9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9.zst", "sha256": "9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "source_id": "eia-international", "title": "International energy data", "url_download": "https://www.eia.gov/opendata/bulk/INTL.zip", "url_main": "https://www.eia.gov/international/data/world", "version_producer": "Sep 2026", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "bulk-manifest", "bytes": 28398, "citation_full": "Source: U.S. Energy Information Administration (Sep 2026).", "date_accessed": "2026-10-05", "date_published": "2026-09-30", "doi": null, "etag": "\"044131b054dd1:0\"", "last_modified": "Mon, 05 Oct 2026 09:58:00 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "U.S. Energy Information Administration", "r2_url": "https://files.environmentdashboard.org/raw/1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372.zst", "sha256": "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372", "source_id": "eia-international", "title": "International energy data", "url_download": "https://www.eia.gov/opendata/bulk/manifest.txt", "url_main": "https://www.eia.gov/international/data/world", "version_producer": "Sep 2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read INTL.txt from EIA's bulk file INTL.zip. EIA's bulk manifest gives the INTL release as last updated 30 September 2026 and names this zip as its file, so the vintage is 'Sep 2026'. The zip was last modified on the server on Sat, 03 Oct 2026 09:49:21 GMT.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Kept the annual consumption series in quadrillion Btu: total energy consumption and its five fuels (coal, natural gas, petroleum and other liquids, nuclear, renewables and other), checking each series' name and units. Kept the World and the 220 countries and territories in pipeline/geo/entities.csv, matched by EIA's ISO 3 code (EIA's XKS is Kosovo, KOS, and its SCG, Former Serbia and Montenegro, is Serbia and Montenegro as reported together, SRB_MNE); EIA's regional aggregates are left out, and so are these geographies, which have no entity in the crosswalk: Former Czechoslovakia; Former U.S.S.R.; Former Yugoslavia; Germany, East; Germany, West; Hawaiian Trade Zone; Netherlands Antilles; U.S. Pacific Islands; U.S. Territories; Wake Island.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Checked EIA's accounting method against its own generation series: for every country other than the United States, the energy content of hydro, wind, solar, geothermal and tide and wave electricity is 3,412 Btu per kilowatt-hour, the captured-energy approach (11,140 country-years checked). Not on that basis in this file: USA: 72 values, e.g. solar 2023 3676, solar 2024 3622 Btu per kWh. World nuclear consumption is 10,379 Btu per kilowatt-hour of nuclear generation in 2024, the heat input of the plants.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Where EIA's total differs from the sum of its five fuel series, both are published as given. Entities where they differ in this vintage: USA, WLD (World 2024: total minus the sum is -1.442 quad Btu).",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "EIA's codes '--', 'NA' and 'ie' (which the file does not define) are null values whose reason quotes the code.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          },
          {
            "description": "Published EIA's total energy consumption as given.",
            "inputs": ["9251a5920ebe70448fc7af522c4f938dc9e1f4728aca2928ecc814ca9f216ea9", "1e1d2b9f467bc5032ffe87dd0ff1ab8a3a223d27d0f777fc0a4710cf95cdf372"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/eia_international.py",
            "transform_sha256": "6e68eab86d8f8c9690e0911d97f56bc09271d0b727778bee8df871e19614723c"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Primary energy consumption as EIA accounts for it: fossil fuels at their heat content; electricity from hydro, wind, solar, geothermal and tide and wave power at its own energy content, 3,412 Btu per kilowatt-hour (the captured-energy approach; EIA's United States series depart from it for solar and geothermal); nuclear at the heat input of the plants. Not comparable with totals from the Energy Institute or the IEA, which count non-combustible electricity differently. 'Renewables and other' is EIA's own category and can be negative.",
          "bunkers": null,
          "geography": "Countries and territories, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["eia-international"],
      "time_basis": "calendar",
      "title": "Total primary energy consumption",
      "unit": {
        "code": "quad-Btu",
        "label": "quadrillion British thermal units",
        "short": "quad Btu"
      },
      "vintage": "Sep 2026"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ARE", "AUS", "AUT", "BEL", "BGR", "BRA", "CAN", "CHE", "CHL", "CHN", "COL", "CRI", "CYP", "CZE", "DEU", "DNK", "ESP", "EST", "FIN", "FRA", "GBR", "GRC", "HRV", "HUN", "IDN", "IND", "IRL", "ISL", "ISR", "ITA", "JOR", "JPN", "KHM", "KOR", "LAO", "LTU", "LUX", "LVA", "MEX", "MYS", "NLD", "NOR", "NPL", "NZL", "PHL", "POL", "PRT", "ROU", "RUS", "SGP", "SVK", "SVN", "SWE", "SYC", "THA", "TUR", "URY", "USA", "UZB", "VNM", "WLD", "ZAF"],
      "export_sha256": "a9e204240c3b78e50241092104bfe4e10b90888a18bffd65d77e3f0a3296392e",
      "geo_coverage": "country",
      "id": "ev.iea.sales-share",
      "latest": {
        "age_bp": null,
        "dims": {
          "mode": "cars"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 25.0
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IEA 2026; Global EV Data Explorer, https://www.iea.org/data-and-statistics/data-tools/global-ev-data-explorer, License: CC BY 4.0 Changes: selected the EV sales share rows and wrote each stored single-precision value as the shortest decimal that reproduces it.",
        "description": "The part of new cars, vans, buses, trucks and two- and three-wheelers sold each year since 2010 that were electric (battery-electric or plug-in hybrid), by country and for the world, as published by the IEA.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0, subject to the IEA Notice for CC-licensed Content",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "This is a work derived by Environment Dashboard from IEA material and Environment Dashboard is solely liable and responsible for this derived work. The derived work is not endorsed by the IEA or its Member countries in any manner.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "evs-historical", "bytes": 3505319, "citation_full": "IEA (2026), Global EV Outlook 2026, IEA, Paris https://www.iea.org/reports/global-ev-outlook-2026, Licence: CC BY 4.0", "date_accessed": "2026-10-05", "date_published": "2026-05-20", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0, subject to the IEA Notice for CC-licensed Content", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "International Energy Agency", "r2_url": null, "sha256": "43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "source_id": "iea-gevo-2026", "title": "Global EV Outlook 2026 and Global EV Data Explorer", "url_download": "https://api.iea.org/evs?category=Historical&year=2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025&csv=true", "url_main": "https://www.iea.org/data-and-statistics/data-tools/global-ev-data-explorer", "version_producer": "Global EV Outlook 2026", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "report-pdf", "bytes": 20175354, "citation_full": "IEA (2026), Global EV Outlook 2026, IEA, Paris https://www.iea.org/reports/global-ev-outlook-2026, Licence: CC BY 4.0", "date_accessed": "2026-10-05", "date_published": "2026-05-20", "doi": null, "etag": "0x8DECDFB1A713572", "last_modified": "Fri, 19 Jun 2026 12:05:49 GMT", "licence": {"name": "CC BY 4.0, subject to the IEA Notice for CC-licensed Content", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "International Energy Agency", "r2_url": null, "sha256": "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300", "source_id": "iea-gevo-2026", "title": "Global EV Outlook 2026 and Global EV Data Explorer", "url_download": "https://iea.blob.core.windows.net/assets/857aa690-2a43-453f-9f12-147cc8f0a1dd/GlobalEVOutlook2026.pdf", "url_main": "https://www.iea.org/data-and-statistics/data-tools/global-ev-data-explorer", "version_producer": "Global EV Outlook 2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the IEA Global EV Data Explorer's historical file from api.iea.org/evs (fetched 2026-10-05, sha256 43de47975d08…), which carries no version label; its latest year is 2025, the year the Global EV Outlook 2026 reports on.",
            "inputs": ["43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/iea_evs.py",
            "transform_sha256": "de5e18217fa9b61781e38cd923c77e996345bb5ff9655f767bf6de76b090d190"
          },
          {
            "description": "Kept the 'EV sales share' rows (category Historical, powertrain EV: battery-electric and plug-in hybrid together; unit percent) for cars, vans, buses, trucks and two- and three-wheelers, 2010–2025. The 26,007 car price rows (price_* and sales-historical-price-data), based on S&P Global Mobility data that the IEA's licence does not cover, were not read.",
            "inputs": ["43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/iea_evs.py",
            "transform_sha256": "de5e18217fa9b61781e38cd923c77e996345bb5ff9655f767bf6de76b090d190"
          },
          {
            "description": "Matched IEA region names to countries in pipeline/geo/entities.csv by name (Czech Republic, Korea, Lao PDR, Turkiye, USA and Viet Nam by declared alias). The IEA's regional groupings were left out because the file does not list their members: Advanced Economies, Africa, Asia Pacific, Developing Economies excl. China, Europe, European Union, Latin America, Middle East and Caspian, Southeast Asia.",
            "inputs": ["43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/iea_evs.py",
            "transform_sha256": "de5e18217fa9b61781e38cd923c77e996345bb5ff9655f767bf6de76b090d190"
          },
          {
            "description": "Published each value as the shortest decimal that reproduces the single-precision number stored in the file (for example 0.012 for 0.012000000104308128).",
            "inputs": ["43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/iea_evs.py",
            "transform_sha256": "de5e18217fa9b61781e38cd923c77e996345bb5ff9655f767bf6de76b090d190"
          },
          {
            "description": "Left as null, with the reason, every value above 100%, which cannot be a share of sales. In this vintage: ARE vans 2021; ARE vans 2022; ARE vans 2023; ARE vans 2024; ARE vans 2025.",
            "inputs": ["43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/iea_evs.py",
            "transform_sha256": "de5e18217fa9b61781e38cd923c77e996345bb5ff9655f767bf6de76b090d190"
          },
          {
            "description": "Found the report's statement of the 2025 world share for cars on page 16 of the PDF.",
            "inputs": ["43de47975d08de9458832cccc8574ebbb0bf7a9282636c9c07a242b03608e49b", "7f0e1575fa3679fe195c24b6adfd036c28ac90f7d0680ef127d62b4f481e8300"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/energy/iea_evs.py",
            "transform_sha256": "de5e18217fa9b61781e38cd923c77e996345bb5ff9655f767bf6de76b090d190"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Sales of battery-electric and plug-in hybrid vehicles (the IEA's 'EV') as a share of all new vehicle sales of the same mode in the year. Values as rounded by the IEA.",
          "bunkers": null,
          "geography": "Countries in the IEA's Global EV Data Explorer, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["iea-gevo-2026"],
      "time_basis": "calendar",
      "title": "Electric share of new vehicle sales",
      "unit": {
        "code": "percent",
        "label": "percent of new vehicle sales",
        "short": "%"
      },
      "vintage": "Global EV Outlook 2026"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "f748f8c98851e87a129d2dafd7bc9d5738c0d25c3fb7beb6bd8d55a23ef61f08",
      "geo_coverage": "global-only",
      "id": "food-loss.faostat.sdg-12-3-1a",
      "latest": {
        "age_bp": null,
        "dims": {
          "commodity": "total"
        },
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 13.4
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.",
        "description": "The share of the world's food, by economic value, lost after harvest on the farm, in storage, transport and processing, before it reaches shops, each year since 2015, in total and for four commodity groups, as estimated by FAO for SDG indicator 12.3.1a.",
        "kind": "series",
        "licence": {
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          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
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        "origins": [
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          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2026-09-29", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2026-09-29", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read SDG_BulkDownloads_E_All_Data_(Normalized).csv from FAOSTAT's SDGB bulk zip. The vintage is the domain's DateUpdate, 29 September 2026, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 478,304, the number of data rows in this file. The zip was last modified on the server on Tue, 29 Sep 2026 07:16:22 GMT.",
            "inputs": ["ef0358f2cc8cb786f811f5347818284b6e186b1ce4330f788c7e6d7142fb751e", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_food_loss.py",
            "transform_sha256": "9d21044637cd82720d092f8dd5318737a8ac37a6301c4b1cbf9f2a47b4d5079b"
          },
          {
            "description": "Kept the rows of the five \"12.3.1a Food loss percentage\" items (total and four commodity groups), element \"Value\" (code 6121), unit \"%\", 2015–2024, for WLD; values are published as printed.",
            "inputs": ["ef0358f2cc8cb786f811f5347818284b6e186b1ce4330f788c7e6d7142fb751e", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_food_loss.py",
            "transform_sha256": "9d21044637cd82720d092f8dd5318737a8ac37a6301c4b1cbf9f2a47b4d5079b"
          },
          {
            "description": "Left out FAO regional and analytical groups (Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, Central Asia and Southern Asia, Eastern Africa, Eastern Asia, Eastern Asia and South-eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Melanesia, Micronesia, Middle Africa, Northern Africa, Northern America, Northern America and Europe, Northern Europe, Oceania, Oceania excluding Australia and New Zealand, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Sub-Saharan Africa, Western Africa, Western Asia, Western Asia and Northern Africa, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["ef0358f2cc8cb786f811f5347818284b6e186b1ce4330f788c7e6d7142fb751e", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_food_loss.py",
            "transform_sha256": "9d21044637cd82720d092f8dd5318737a8ac37a6301c4b1cbf9f2a47b4d5079b"
          },
          {
            "description": "Every value used carries FAO's flag A, which the file's codebook defines as \"Official value\".",
            "inputs": ["ef0358f2cc8cb786f811f5347818284b6e186b1ce4330f788c7e6d7142fb751e", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_food_loss.py",
            "transform_sha256": "9d21044637cd82720d092f8dd5318737a8ac37a6301c4b1cbf9f2a47b4d5079b"
          },
          {
            "description": "50 of the values carry FAO's note that before July 2022 the series was disseminated under the SDG code \"AG_FLS_IDX\".",
            "inputs": ["ef0358f2cc8cb786f811f5347818284b6e186b1ce4330f788c7e6d7142fb751e", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_food_loss.py",
            "transform_sha256": "9d21044637cd82720d092f8dd5318737a8ac37a6301c4b1cbf9f2a47b4d5079b"
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        ],
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          "basis": "SDG 12.3.1a food loss percentage (FAO custodian): losses from post-harvest up to, but not including, retail, as a share of production weighted by economic value (international dollar prices). Pre-harvest losses and waste at retail, in food service and in households (SDG 12.3.1b) are not included.",
          "bunkers": null,
          "geography": "World",
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      },
      "source_ids": ["faostat"],
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      "title": "Food lost between harvest and retail (SDG 12.3.1a)",
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        "code": "percent",
        "label": "percent of food produced, by economic value",
        "short": "%"
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        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to million tonnes of CO₂-equivalent.",
        "description": "Greenhouse gas emissions from each country's food and farming system each year since 1990, in carbon dioxide equivalent: on farms, from clearing land for agriculture, and from making, moving, selling, cooking and throwing away food, as estimated by FAO with the same method for every country.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
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          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's GT bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_country_emissions.py",
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          {
            "description": "Kept the \"FAO TIER 1\" rows of item \"Agrifood systems\" (code 6518), element \"Emissions (CO2eq) (AR5)\" (code 723113), 1990–2023, in kilotonnes of CO₂-equivalent (IPCC AR5 100-year global warming potentials), for every area FAO reports. Rows from FAO's \"UNFCCC\" source are not used.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_country_emissions.py",
            "transform_sha256": "1f53eb89d97c96d94e6a061579c266718d1d80749db5adea627555daafe706a8"
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          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
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            "transform_sha256": "1f53eb89d97c96d94e6a061579c266718d1d80749db5adea627555daafe706a8"
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          {
            "description": "Converted kilotonnes to million tonnes by dividing by 1,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_country_emissions.py",
            "transform_sha256": "1f53eb89d97c96d94e6a061579c266718d1d80749db5adea627555daafe706a8"
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          {
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            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          "basis": "FAOSTAT item \"Agrifood systems\" = farm gate (crops and livestock) + land-use change + pre- and post-production (fertilizer manufacturing, processing, packaging, transport, retail, household consumption and waste disposal). Land-use change counts only what FAO attributes to agriculture: net forest conversion (deforestation) plus fires in humid tropical forests and in organic soils (peat); the carbon taken up by forests is not subtracted. International aviation and shipping bunkers are a separate FAOSTAT item and are not included. FAO Tier 1 estimates for every country, not country inventory submissions, so they can differ from a country's own inventory.",
          "bunkers": "excluded",
          "geography": "Countries and territories, the European Union (27) and the world",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
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      "source_ids": ["faostat"],
      "time_basis": "calendar",
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      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHI", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "3cbcfaa6b55781300913b6fc1e0dd2cf914a6abe5a65b9d0d07ec5dcada34621",
      "geo_coverage": "country",
      "id": "food.faostat.agrifood-emissions-by-process",
      "latest": {
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        "dims": {
          "process": "enteric-fermentation",
          "stage": "farm-gate"
        },
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 2947.2047472
      },
      "licence_class": "open",
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        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to million tonnes of CO₂-equivalent.",
        "description": "Greenhouse gas emissions from food and farming each year since 1990, for the world and each country, in carbon dioxide equivalent, split into the 22 processes FAO estimates, within its three stages. Farm gate (11): enteric fermentation, manure management, manure left on pasture, manure applied to soils, synthetic fertilizers, rice cultivation, crop residues, burning crop residues, drained organic soils, on-farm energy use and savanna fires. Land-use change (3): net forest conversion, fires in humid tropical forests and fires in organic soils. Pre- and post-production (8): fertilizers manufacturing, pesticides manufacturing, food processing, food packaging, food transport, food retail, food household consumption and agrifood systems waste disposal. Within each stage the processes add up exactly to FAO's stage total. Where FAO gives no value for a process in a country and year, it is absent, not zero.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
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          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's GT bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Kept the \"FAO TIER 1\" rows of element \"Emissions (CO2eq) (AR5)\" (code 723113), in kilotonnes of CO₂-equivalent (IPCC AR5 100-year global warming potentials), for item \"Agrifood systems\" (6518), its three stage items and their 22 process items. Rows from FAO's \"UNFCCC\" source are not used.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Checked, in all 9,174 areas and years from 1990 where FAO prints them (FAO's regions included), that \"Agrifood systems\" equals the sum of the three stages and each stage equals the sum of its processes present, to within 0.01 kilotonnes. Nothing is computed from this check; it shows that the parts published are FAO's whole total, with no remainder.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Left out 6,293 area-years before 1990 that carry farm process rows only: FAO publishes no stage total or agrifood total before 1990, so those rows could not be checked against one.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Left out FAO's projections for 2030 and 2050, which the file flags F (\"Forecast value\").",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Published the 22 process items, 1990–2023, each value exactly as one row of the file.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe); the European Union (27), a region (only the world and countries and territories are published). Their values are never re-assigned to other entities.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
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            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
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          {
            "description": "Converted kilotonnes to million tonnes by dividing by 1,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Labelled FAO's items in plain words: \"Farm gate\" as \"On the farm\"; \"Land-use change\" as \"Clearing land for farming\"; \"Pre- and post-production\" as \"Before and after the farm\"; \"Enteric Fermentation\" as \"Farm animals' digestion (burps)\"; \"Manure Management\" as \"Storing and handling manure\"; \"Manure left on Pasture\" as \"Manure left on grazing land\"; \"Manure applied to Soils\" as \"Manure spread on fields\"; \"Synthetic Fertilizers\" as \"Synthetic fertiliser on fields\"; \"Rice Cultivation\" as \"Flooded rice fields\"; \"Crop Residues\" as \"Crop leftovers rotting on fields\"; \"Burning - Crop residues\" as \"Burning crop leftovers\"; \"Drained organic soils\" as \"Drained peat soils\"; \"On-farm energy use\" as \"Fuel and electricity used on farms\"; \"Savanna fires\" as \"Grassland (savanna) fires\"; \"Net Forest conversion\" as \"Cutting down forests\"; \"Fires in humid tropical forests\" as \"Tropical forest fires\"; \"Fires in organic soils\" as \"Peat fires\"; \"Fertilizers Manufacturing\" as \"Making fertiliser\"; \"Pesticides Manufacturing\" as \"Making pesticides\"; \"Food Processing\" as \"Processing food\"; \"Food Packaging\" as \"Packaging\"; \"Food Transport\" as \"Transport\"; \"Food Retail\" as \"Shops\"; \"Food Household Consumption\" as \"Cooking and storing food at home\"; \"Agrifood Systems Waste Disposal\" as \"Disposing of food waste\". Only the names shown differ; every value is FAO's item of that name.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "The 22 FAOSTAT process items of item \"Agrifood systems\" (6518), with FAO's names, each under its stage; overlapping FAOSTAT items (Emissions from livestock, Emissions from crops, Emissions on agricultural land, IPCC Agriculture, AFOLU, LULUCF) are not included, so nothing is counted twice. A few synthetic-fertilizer values are negative as published (Somalia and Timor-Leste, some years). FAO TIER 1 estimates for every country with the same method, not country inventory submissions, so they can differ from a country's own inventory. Farm gate is FAO's grouping: it includes on-farm energy use, drained organic soils and savanna fires as well as livestock and crop emissions. Land-use change counts only what FAO attributes to agriculture: net forest conversion (deforestation) plus fires in humid tropical forests and in organic soils (peat). The carbon taken up by standing forests (FAOSTAT item \"Forestland\", a net removal) is outside FAO's agrifood total: it is not subtracted and not shown. Net forest conversion uses FAO Forest Resources Assessment period averages, so it is constant within each assessment period and steps between periods, including a method break between 2000 and 2001; year-to-year changes in land-use change are partly an artefact of that method. Pre- and post-production covers fertilizer and pesticide manufacturing, food processing, packaging, transport, retail, household consumption (cooking, storing) and agrifood waste disposal. International aviation and shipping bunkers are a separate FAOSTAT item and are not included. Stage totals start in 1990.",
          "bunkers": "excluded",
          "geography": "Countries and territories, and the world",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions from agrifood systems, by process",
      "unit": {
        "code": "MtCO2e",
        "label": "million tonnes of carbon dioxide equivalent",
        "short": "Mt CO₂e"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHI", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "a3a73780c89d5db243d98277f43ea999c9f9951e28a74497d7682696f9a5907c",
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      "latest": {
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        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to million tonnes of CO₂-equivalent.",
        "description": "Greenhouse gas emissions from food and farming each year since 1990, for the world and each country, in carbon dioxide equivalent, split into FAO's three stages: within the farm gate (animals, manure, fertilisers, rice fields, crop residues, drained peat soils, savanna fires and energy used on farms), land-use change (clearing forests for farming, fires in humid tropical forests and fires in peat soils), and pre- and post-production (making fertilisers and pesticides, processing, packaging, transport, retail, household food consumption and waste disposal). The three stages add up exactly to FAO's agrifood systems total. The forest carbon sink is not part of that total and is not shown.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's GT bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Kept the \"FAO TIER 1\" rows of element \"Emissions (CO2eq) (AR5)\" (code 723113), in kilotonnes of CO₂-equivalent (IPCC AR5 100-year global warming potentials), for item \"Agrifood systems\" (6518), its three stage items and their 22 process items. Rows from FAO's \"UNFCCC\" source are not used.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Checked, in all 9,174 areas and years from 1990 where FAO prints them (FAO's regions included), that \"Agrifood systems\" equals the sum of the three stages and each stage equals the sum of its processes present, to within 0.01 kilotonnes. Nothing is computed from this check; it shows that the parts published are FAO's whole total, with no remainder.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Left out 6,293 area-years before 1990 that carry farm process rows only: FAO publishes no stage total or agrifood total before 1990, so those rows could not be checked against one.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Left out FAO's projections for 2030 and 2050, which the file flags F (\"Forecast value\").",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Published the three stage items, 1990–2023, each value exactly as one row of the file.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe); the European Union (27), a region (only the world and countries and territories are published). Their values are never re-assigned to other entities.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Converted kilotonnes to million tonnes by dividing by 1,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          },
          {
            "description": "Labelled FAO's items in plain words: \"Farm gate\" as \"On the farm\"; \"Land-use change\" as \"Clearing land for farming\"; \"Pre- and post-production\" as \"Before and after the farm\". Only the names shown differ; every value is FAO's item of that name.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_agrifood_stages.py",
            "transform_sha256": "636550f9686b9778d2e38caf6333b1c12ef9cc29ddb9813753ae715af65a10ad"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT items \"Farm gate\" (6996), \"Land-use change\" (6516) and \"Pre- and post-production\" (6517), which add up to item \"Agrifood systems\" (6518). FAO TIER 1 estimates for every country with the same method, not country inventory submissions, so they can differ from a country's own inventory. Farm gate is FAO's grouping: it includes on-farm energy use, drained organic soils and savanna fires as well as livestock and crop emissions. Land-use change counts only what FAO attributes to agriculture: net forest conversion (deforestation) plus fires in humid tropical forests and in organic soils (peat). The carbon taken up by standing forests (FAOSTAT item \"Forestland\", a net removal) is outside FAO's agrifood total: it is not subtracted and not shown. Net forest conversion uses FAO Forest Resources Assessment period averages, so it is constant within each assessment period and steps between periods, including a method break between 2000 and 2001; year-to-year changes in land-use change are partly an artefact of that method. Pre- and post-production covers fertilizer and pesticide manufacturing, food processing, packaging, transport, retail, household consumption (cooking, storing) and agrifood waste disposal. International aviation and shipping bunkers are a separate FAOSTAT item and are not included. Stage totals start in 1990.",
          "bunkers": "excluded",
          "geography": "Countries and territories, and the world",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions from agrifood systems, by stage: within the farm gate (including savanna fires and drained peat soils), land-use change, and before and after the farm",
      "unit": {
        "code": "MtCO2e",
        "label": "million tonnes of carbon dioxide equivalent",
        "short": "Mt CO₂e"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "20ea39c1768812a1383cf5ae6fb68c9f7479c4e1eeb613b0cfc9119f0b44b391",
      "geo_coverage": "global-only",
      "id": "food.faostat.agrifood-emissions-world",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 16.5350723737
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      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to billion tonnes of CO₂-equivalent.",
        "description": "Greenhouse gas emissions from the world's food and farming systems each year since 1990, in carbon dioxide equivalent: on farms, from clearing land for agriculture, and from making, moving, selling, cooking and throwing away food, as estimated by FAO.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's Emissions totals (GT) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Kept the World (area code 5000), \"FAO TIER 1\" rows of item \"Agrifood systems\" (code 6518), element \"Emissions (CO2eq) (AR5)\" (code 723113): one value per year, 1990–2023, in kilotonnes of CO₂-equivalent (IPCC AR5 100-year global warming potentials). Rows from FAO's \"UNFCCC\" source are not used.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Converted kilotonnes to billion tonnes by dividing by 1,000,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT item \"Agrifood systems\": emissions within the farm gate (crops and livestock), from land-use change, and from pre- and post-production (fertilizer manufacturing, processing, packaging, transport, retail, household consumption and waste disposal). Land-use change counts only what FAO attributes to agriculture: its item \"Land-use change\" is net forest conversion (deforestation) plus fires in humid tropical forests and fires in organic soils (peat). The carbon taken up by forests (FAOSTAT item \"Forestland\", a net removal) is not subtracted. FAO Tier 1 estimates, not country inventory submissions.",
          "bunkers": null,
          "geography": "World",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions from agrifood systems, world",
      "unit": {
        "code": "GtCO2e",
        "label": "billion tonnes of carbon dioxide equivalent",
        "short": "Gt CO₂e"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "f09abfbe228a0f426bcc5220125aa20c6fab69dfe4a9db5d807584c7c64024d5",
      "geo_coverage": "global-only",
      "id": "food.faostat.agrifood-emissions-world.share",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 31.73
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions from Gütschow, J., Busch, D. & Pflüger, M. (2025), The PRIMAP-hist national historical emissions time series (1750-2024) v2.7, doi:10.5281/zenodo.17090760, licensed CC BY-NC-SA 4.0; method in Gütschow et al. (2016), Earth System Science Data 8, 571-603, doi:10.5194/essd-8-571-2016.",
        "description": "The part of FAO's all-sector greenhouse gas total that comes from food and farming systems each year since 1990, as published by FAO: FAO's agrifood-systems emissions (on farms, from clearing land for agriculture, and from making, moving, selling, cooking and throwing away food) as a percentage of FAO's own total of all sectors, which includes net land use, land-use change and forestry and excludes international aviation and shipping. The agrifood figure counts clearing land for farming without subtracting what forests take up, while the total's land use is net of that uptake, so this is not a share of gross global emissions. Food's emissions run across the agriculture, land-use, energy, industry and waste sectors; they are not a sector of their own.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "FAOSTAT's energy, industrial processes, waste and other emissions, and every total, share or per-person value that includes them, are PRIMAP-hist v2.7 data (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values from this source are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-indicators", "bytes": 4655416, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "\"09064d9dbb13662b004da75f13044915\"", "last_modified": "Wed, 29 Oct 2025 11:06:06 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34.zst", "sha256": "d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/Climate_change_Emissions_indicators_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/#data/EM", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/#data/EM", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Climate_change_Emissions_indicators_E_All_Data_(Normalized).csv from FAOSTAT's Emissions indicators (EM) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 678,370, the number of data rows in this file. The zip was last modified on the server on Wed, 29 Oct 2025 11:06:06 GMT.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept the World (area code 5000) rows of item \"Agrifood systems\" (code 6518), element \"Emissions Share (CO2eq) (AR5)\" (code 726313), unit \"%\", 1990–2023, as FAO prints them: FAO's own share of agrifood-system emissions in its \"All sectors with LULUCF\" total. Nothing is computed here.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAO's published share (FAOSTAT Emissions indicators, item \"Agrifood systems\", element \"Emissions Share (CO2eq) (AR5)\"). Numerator: emissions within the farm gate, from land-use change and from pre- and post-production (fertilizer manufacturing, processing, packaging, transport, retail, household consumption and waste disposal); its land-use change counts only what FAO attributes to agriculture (deforestation and fires in humid tropical forests and organic soils), with the carbon taken up by forests not subtracted. Denominator: FAO's \"All sectors with LULUCF\" total of the six IPCC sectors, in which land use is net of the forest sink; international aviation and shipping bunkers are a separate item and are not in it.",
          "bunkers": "excluded",
          "geography": "World",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat-all-sectors"],
      "time_basis": "calendar",
      "title": "Agrifood systems' share of FAO's all-sector greenhouse gas total (net land use, no international transport)",
      "unit": {
        "code": "percent",
        "label": "percent of FAO's all-sector total (net land use, no international transport)",
        "short": "%"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SOM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "ea3a86422deb33b01c1f5c8637064e5cbeb046edcda3a614b91fa1d8935bd1b5",
      "geo_coverage": "country",
      "id": "food.faostat.commodity-emissions",
      "latest": {
        "age_bp": null,
        "dims": {
          "commodity": "cattle-meat"
        },
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 2113.655572
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to million tonnes of CO₂-equivalent.",
        "description": "Methane and nitrous oxide emitted on farms each year since 1961 in producing each of 14 farm products, for the world and each country, in carbon dioxide equivalent, as allocated by FAO. Counts only emissions on the farm from: methane from animals' digestion (enteric fermentation) and from manure management; nitrous oxide from manure management, from manure applied to soils and from manure left on pasture; and, for rice and other cereals, nitrous oxide from crop residues and from synthetic fertiliser, methane and nitrous oxide from burning crop residues, plus methane from flooded rice paddies. Not counted: energy used on farms, drained organic (peat) soils, savanna fires, clearing land (land-use change), and everything before and after the farm (making fertiliser and feed, processing, packaging, transport, retail, cooking and waste). Only 14 products: meat of cattle, buffalo, sheep, goats, pigs and chickens; raw milk of cattle, buffalo, sheep, goats and camels; hen eggs; rice; and other cereals together. Soy, palm oil, fruit, vegetables, sugar, pulses, fish and other farm animals are not covered, so the products do not add up to food's emissions. These are farm-gate values, not life-cycle footprints: FAO says they should not be compared with life-cycle assessment figures. FAO's split of sheep, goat, buffalo and camel emissions between meat and milk makes 75 meat values negative in the February 2026 release, all goat, buffalo or sheep meat and most of them in Mali and Bhutan, down to about -6.3 million tonnes for goat meat in Mali in 2011. They are published as printed.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-intensities", "bytes": 3640396, "citation_full": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2026-02-20", "doi": null, "etag": "\"35b5bf70d1fa8cf6d73beff11a963236\"", "last_modified": "Fri, 20 Feb 2026 15:00:03 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7.zst", "sha256": "1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/Environment_Emissions_intensities_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2026-02-20", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2026-02-20", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2026-02-20", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Environment_Emissions_intensities_E_All_Data_(Normalized).csv from FAOSTAT's EI bulk zip. The vintage is the domain's DateUpdate, 20 February 2026, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 409,511, the number of data rows in this file. The zip was last modified on the server on Fri, 20 Feb 2026 15:00:03 GMT. FAO's methodological note for this domain (release October 2025) says its emissions come from FAOSTAT's Emissions from crops and Emissions from livestock domains and its production from FAOSTAT Production (QCL).",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          },
          {
            "description": "Kept the rows of element \"Emissions (CO2eq) (AR5)\" (code 723113, unit \"kt\") for the 14 items of the file, matched by Item Code, 1961–2023.",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe); the European Union (27), a region (only the world and countries and territories are published). Their values are never re-assigned to other entities.",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          },
          {
            "description": "75 published values are below zero (buffalo-meat, goat-meat, sheep-meat; AUT, BTN, ISR, LTU, MKD, MLI, PSE), from FAO's split of sheep, goat, buffalo and camel emissions between meat and milk by the share of animals milked; the lowest is MLI goat-meat 2011 (-6.3167537 million tonnes). Published as printed.",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          },
          {
            "description": "Converted kilotonnes to million tonnes by dividing by 1,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          },
          {
            "description": "Labelled FAO's items in plain words: \"Meat of cattle with the bone, fresh or chilled\" as \"Beef\"; \"Raw milk of cattle\" as \"Cow's milk\"; \"Cereals excluding rice\" as \"Cereals other than rice\"; \"Meat of buffalo, fresh or chilled\" as \"Buffalo meat\"; \"Meat of sheep, fresh or chilled\" as \"Lamb and mutton\"; \"Meat of goat, fresh or chilled\" as \"Goat meat\"; \"Meat of pig with the bone, fresh or chilled\" as \"Pork\"; \"Raw milk of buffalo\" as \"Buffalo milk\"; \"Meat of chickens, fresh or chilled\" as \"Chicken\"; \"Raw milk of sheep\" as \"Sheep's milk\"; \"Raw milk of goats\" as \"Goat's milk\"; \"Hen eggs in shell, fresh\" as \"Eggs\"; \"Raw milk of camel\" as \"Camel's milk\". Only the names shown differ; every value is FAO's item of that name.",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_commodity_emissions.py",
            "transform_sha256": "9a5d1496e68aed6012f5ed33ca66264199827d6cc306d23925a63b02420945dd"
          }
        ],
        "published_value": null,
        "scope": {
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          "basis": "FAOSTAT Emissions intensities (EI). FAO assigns each kind of animal to a product: non-dairy cattle to cattle meat, dairy cattle to cattle milk, all pigs to pig meat, broilers to chicken meat and laying hens to eggs; sheep, goat, buffalo and camel emissions are split between meat and milk by the share of animals milked, which gives some negative meat values, published as printed (the processing steps count them). Synthetic fertiliser is shared among crops by FAO's 1995-2000 fertiliser use by crop. Milk is raw milk, not corrected for fat and protein, and products are compared by weight, not by protein or energy. FAO TIER 1 estimates (IPCC 2006 Guidelines), not country inventory submissions. The products do not add up to any FAO total and overlap FAO's farm-gate process items (for example rice includes rice's share of fertiliser), so they are never stacked with them.",
          "bunkers": null,
          "geography": "Countries and territories, and the world",
          "gwp": "AR5-GWP100",
          "lulucf": "excluded"
        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "On-farm methane and nitrous oxide from animals, manure, fertiliser and rice fields, by farm product (14 products)",
      "unit": {
        "code": "MtCO2e",
        "label": "million tonnes of carbon dioxide equivalent",
        "short": "Mt CO₂e"
      },
      "vintage": "2026-02-20"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
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        "description": "Methane and nitrous oxide emitted on farms per kilogram of each of 14 farm products, each year since 1961, for the world and each country, in kilograms of carbon dioxide equivalent, as published by FAO (the product's farm emissions divided by its production). The kilogram is FAO's production weight: carcass weight for meat (FAO's items are meat 'with the bone'), raw whole milk, eggs in shell and harvested cereals. It is not a kilogram of boneless meat or of food as bought, so these values are not comparable with retail or life-cycle figures per kilogram of food. Counts only emissions on the farm from: methane from animals' digestion (enteric fermentation) and from manure management; nitrous oxide from manure management, from manure applied to soils and from manure left on pasture; and, for rice and other cereals, nitrous oxide from crop residues and from synthetic fertiliser, methane and nitrous oxide from burning crop residues, plus methane from flooded rice paddies. Not counted: energy used on farms, drained organic (peat) soils, savanna fires, clearing land (land-use change), and everything before and after the farm (making fertiliser and feed, processing, packaging, transport, retail, cooking and waste). Only 14 products: meat of cattle, buffalo, sheep, goats, pigs and chickens; raw milk of cattle, buffalo, sheep, goats and camels; hen eggs; rice; and other cereals together. Soy, palm oil, fruit, vegetables, sugar, pulses, fish and other farm animals are not covered, so the products do not add up to food's emissions. These are farm-gate values, not life-cycle footprints: FAO says they should not be compared with life-cycle assessment figures. Where a country produces little of a product the value can be very large, and where FAO gives no production figure there is no value. FAO's split of sheep, goat, buffalo and camel emissions between meat and milk makes 72 meat values negative in the February 2026 release, most of them in Mali and Bhutan, down to about -854 kilograms per kilogram for goat meat in Mali in 2010. They are published as printed.",
        "kind": "series",
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        "origins": [
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        ],
        "processing": [
          {
            "description": "Read Environment_Emissions_intensities_E_All_Data_(Normalized).csv from FAOSTAT's EI bulk zip. The vintage is the domain's DateUpdate, 20 February 2026, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 409,511, the number of data rows in this file. The zip was last modified on the server on Fri, 20 Feb 2026 15:00:03 GMT. FAO's methodological note for this domain (release October 2025) says its emissions come from FAOSTAT's Emissions from crops and Emissions from livestock domains and its production from FAOSTAT Production (QCL).",
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          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe); the European Union (27), a region (only the world and countries and territories are published). Their values are never re-assigned to other entities.",
            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          {
            "description": "72 published values are below zero (buffalo-meat, goat-meat, sheep-meat; AUT, BTN, ISR, LTU, MLI, PSE), from FAO's split of sheep, goat, buffalo and camel emissions between meat and milk by the share of animals milked; the lowest is MLI goat-meat 2010 (-854.2702 kg CO2eq/kg). Published as printed.",
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          {
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            "inputs": ["1c2991089fec6bd5e762a290e5f78eb018739b700cb253620faa161f3a21e7e7", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          {
            "description": "Labelled FAO's items in plain words: \"Meat of cattle with the bone, fresh or chilled\" as \"Beef\"; \"Raw milk of cattle\" as \"Cow's milk\"; \"Cereals excluding rice\" as \"Cereals other than rice\"; \"Meat of buffalo, fresh or chilled\" as \"Buffalo meat\"; \"Meat of sheep, fresh or chilled\" as \"Lamb and mutton\"; \"Meat of goat, fresh or chilled\" as \"Goat meat\"; \"Meat of pig with the bone, fresh or chilled\" as \"Pork\"; \"Raw milk of buffalo\" as \"Buffalo milk\"; \"Meat of chickens, fresh or chilled\" as \"Chicken\"; \"Raw milk of sheep\" as \"Sheep's milk\"; \"Raw milk of goats\" as \"Goat's milk\"; \"Hen eggs in shell, fresh\" as \"Eggs\"; \"Raw milk of camel\" as \"Camel's milk\". Only the names shown differ; every value is FAO's item of that name.",
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          "basis": "FAOSTAT Emissions intensities (EI). FAO assigns each kind of animal to a product: non-dairy cattle to cattle meat, dairy cattle to cattle milk, all pigs to pig meat, broilers to chicken meat and laying hens to eggs; sheep, goat, buffalo and camel emissions are split between meat and milk by the share of animals milked, which gives some negative meat values, published as printed (the processing steps count them). Synthetic fertiliser is shared among crops by FAO's 1995-2000 fertiliser use by crop. Milk is raw milk, not corrected for fat and protein, and products are compared by weight, not by protein or energy. FAO TIER 1 estimates (IPCC 2006 Guidelines), not country inventory submissions. The products do not add up to any FAO total and overlap FAO's farm-gate process items (for example rice includes rice's share of fertiliser), so they are never stacked with them.",
          "bunkers": null,
          "geography": "Countries and territories, and the world",
          "gwp": "AR5-GWP100",
          "lulucf": "excluded"
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      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "On-farm methane and nitrous oxide per kilogram of farm product, from animals, manure, fertiliser and rice fields (14 products)",
      "unit": {
        "code": "kgCO2e/kg",
        "label": "kilograms of carbon dioxide equivalent per kilogram produced (carcass weight for meat, raw whole milk, eggs in shell)",
        "short": "kg CO₂e/kg"
      },
      "vintage": "2026-02-20"
    },
    {
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      "downloadable": true,
      "entities": ["AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GTM", "GUF", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SOM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
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      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to million tonnes of methane.",
        "description": "Methane released each year since 1961 by farm animals, for the world and each country, from their digestion (enteric fermentation) and from manure management, for each of the 16 kinds of animal FAO estimates separately: dairy and non-dairy cattle, buffalo, sheep, goats, market and breeding pigs, broiler and laying chickens, ducks, turkeys, horses, asses, mules and hinnies, camels and llamas. They add up exactly to FAO's total for all animals. Manure here is only the methane from managing manure (storing and handling it); nitrous oxide from manure, and manure left on pasture or spread on fields (which emit nitrous oxide, not methane), are not included. In tonnes of methane, not carbon dioxide equivalent, so these values cannot be added to or compared with values in carbon dioxide equivalent.",
        "kind": "series",
        "licence": {
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        "processing": [
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            "description": "Read Emissions_livestock_E_All_Data_(Normalized).csv from FAOSTAT's GLE bulk zip as a stream. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip as its FileLocation and gives FileSize 54572KB, this zip's 55,881,712 bytes in kilobytes rounded up. Its FileRows, 6,941,916, is not the number of data rows in this file (6,650,421), so it does not identify the file. The zip was last modified on the server on Wed, 29 Oct 2025 12:20:38 GMT.",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          },
          {
            "description": "Kept the \"FAO TIER 1\" rows of element \"Livestock total (Emissions CH4)\" (code 72441): methane from enteric fermentation and manure management, in kilotonnes of methane, for the 16 animal items FAO estimates separately, 1961–2023. FAO's aggregate items are not used. Rows from FAO's \"UNFCCC\" source are not used.",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          },
          {
            "description": "Checked, in all 14,264 areas and years where FAO prints them (FAO's regions included), that item \"All Animals\" (1755) equals the sum of the 16 animals present, to within 0.01 kilotonnes. Nothing is computed from this check; it shows that the animals published are FAO's whole total, with no remainder.",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Sub-Saharan Africa, Western Africa, Western Asia, Western Europe); the European Union (27), a region (only the world and countries and territories are published). Their values are never re-assigned to other entities.",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          },
          {
            "description": "Converted kilotonnes to million tonnes by dividing by 1,000 (exact decimal arithmetic on the printed values). The values stay in tonnes of methane; they are not converted to CO₂-equivalent.",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          },
          {
            "description": "Labelled FAO's items in plain words: \"Cattle, dairy\" as \"Dairy cattle\"; \"Cattle, non-dairy\" as \"Beef and other cattle\"; \"Swine, market\" as \"Pigs raised for meat\"; \"Swine, breeding\" as \"Breeding pigs\"; \"Chickens, broilers\" as \"Chickens raised for meat\"; \"Chickens, layers\" as \"Egg-laying hens\"; \"Asses\" as \"Donkeys\". Only the names shown differ; every value is FAO's item of that name.",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          },
          {
            "description": "Left out FAO's projections for 2030 and 2050, which the file flags F (\"Forecast value\").",
            "inputs": ["1eca81ff01c2064e54feea179911414700539eb38b9bb29b3e123955fe38309f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_livestock_by_animal.py",
            "transform_sha256": "f3ea399553a6c18cee9b434fda24bcd2faf88a78bee9b80a0ed0dbc24cbc1f4e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT Emissions from livestock (GLE), element \"Livestock total (Emissions CH4)\": methane from enteric fermentation and manure management, mass of methane (not CO₂-equivalent), for 16 non-overlapping animal items that add up to FAO's item \"All Animals\". FAO's aggregate items (Cattle, Swine, Chickens, Poultry Birds, Sheep and Goats, Mules and Asses, Camels and Llamas) are not included. FAO Tier 1 estimates (IPCC 2006 Guidelines) from FAOSTAT animal numbers, not country inventory submissions; FAO's projections for 2030 and 2050 are not included.",
          "bunkers": null,
          "geography": "Countries and territories, and the world",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "Methane from farm animals' digestion and manure, by animal",
      "unit": {
        "code": "MtCH4",
        "label": "million tonnes of methane (not carbon dioxide equivalent)",
        "short": "Mt CH₄"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "7ada750263d37dad64fca4f8fd6c030ad9e6c5549008aa07dd78620ec6b04d42",
      "geo_coverage": "global-only",
      "id": "food.faostat.livestock-ch4-world",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 115.21126
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Changes: converted from kilotonnes to million tonnes of methane.",
        "description": "Methane released each year since 1961 by the world's farm animals, from digestion (enteric fermentation) and from manure management, as estimated by FAO.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's Emissions totals (GT) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Kept the World (area code 5000), \"FAO TIER 1\" rows of item \"Emissions from livestock\" (code 5085), element \"Emissions (CH4)\" (code 7225): methane from enteric fermentation and manure management, one value per year, 1961–2023, in kilotonnes of methane.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Converted kilotonnes to million tonnes by dividing by 1,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          },
          {
            "description": "Left out FAO's projections for 2030 and 2050, which the file flags F (\"Forecast value\").",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_emissions.py",
            "transform_sha256": "ba01ed68c7b4c466eb1989dca4e0bc74f28411d3e01004816bb081b2900bcb2f"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT item \"Emissions from livestock\", element \"Emissions (CH4)\": methane from enteric fermentation and manure management, mass of methane (not CO₂-equivalent). FAO Tier 1 estimates (IPCC 2006 Guidelines), not country inventory submissions.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "Methane from livestock, world",
      "unit": {
        "code": "MtCH4",
        "label": "million tonnes of methane",
        "short": "Mt CH₄"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": false,
      "entities": ["WLD"],
      "export_sha256": "ae1f99e0d66d62a2cef65be3d7d00d1d01e8325a994a0ebb94906b6cfd0fbc5a",
      "geo_coverage": "global-only",
      "id": "food.poore-nemecek-2018.ghg-per-100g-protein",
      "latest": null,
      "licence_class": "display-only",
      "provenance": {
        "attribution": "Poore, J. & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science 360(6392), 987–992, doi:10.1126/science.aaq0216 (erratum doi:10.1126/science.aaw9908). Values as processed by Our World in Data.",
        "description": "Greenhouse gas emissions from producing the amount of each of about 30 foods that holds 100 grams of protein, from land-use change and the farm to the shop, in kilograms of carbon dioxide equivalent: global means from Poore and Nemecek (2018), as published by Our World in Data.",
        "kind": "series",
        "licence": {
          "name": "All rights reserved (Science, exclusive licensee AAAS); no data licence",
          "spdx": null,
          "url": null
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "ghg-per-protein", "bytes": 825, "citation_full": "Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987–992. https://doi.org/10.1126/science.aaq0216 (erratum: https://doi.org/10.1126/science.aaw9908). Poore and Nemecek (2018) – processed by Our World in Data.", "date_accessed": "2026-10-04", "date_published": "2018-06-01", "doi": "10.1126/science.aaq0216", "etag": null, "last_modified": "Mon, 05 Oct 2026 01:11:20 GMT", "licence": {"name": "All rights reserved (Science, exclusive licensee AAAS); no data licence", "spdx": null, "url": null}, "producer": "Joseph Poore (University of Oxford) and Thomas Nemecek (Agroscope); published in Science; series processed by Our World in Data", "r2_url": null, "sha256": "475d7903fe1e012bf369cfaee4fca9905dea6e62aa9025ba126ead7219d7585e", "source_id": "poore-nemecek-2018", "title": "Environmental footprints of food products (Poore & Nemecek 2018)", "url_download": "https://ourworldindata.org/grapher/ghg-per-protein-poore.csv?v=1&csvType=full&useColumnShortNames=true", "url_main": "https://ourworldindata.org/environmental-impacts-of-food", "version_producer": "Science 360, 987–992 (2018); OWID grapher series updated 2019-10-08", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read OWID's grapher CSV of Poore and Nemecek (2018) greenhouse gas emissions per 100 grams of protein (column ghg_emissions_per_100g_protein__poore__and__nemecek__2018): 32 food products, all for the year 2010. Values are published as printed, with no conversion; the food names are OWID's.",
            "inputs": ["475d7903fe1e012bf369cfaee4fca9905dea6e62aa9025ba126ead7219d7585e"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/poore_nemecek_2018.py",
            "transform_sha256": "357d2dccb0239ece8a50ccee970833c5e0335f6c2002d343eed4c51422a5e395"
          },
          {
            "description": "Some of these per-protein values are Our World in Data's own conversions of the per-kilogram values with FAO/INFOODS food composition factors (registry note), labelled as processed by Our World in Data.",
            "inputs": ["475d7903fe1e012bf369cfaee4fca9905dea6e62aa9025ba126ead7219d7585e"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/poore_nemecek_2018.py",
            "transform_sha256": "357d2dccb0239ece8a50ccee970833c5e0335f6c2002d343eed4c51422a5e395"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Global mean of the life-cycle studies in Poore and Nemecek's meta-analysis (about 570 studies, 38,700 farms, 119 countries, median reference year 2010), from land-use change and farm to retail, including packaging and losses. Greenhouse gases weighted by their warming over 100 years (GWP100); the IPCC report the factors come from is not stated in the files used. Impacts vary widely between producers of the same food. Some per-protein values are Our World in Data's conversions of the per-kilogram values with FAO/INFOODS food composition factors.",
          "bunkers": null,
          "geography": "World (global mean of the studies reviewed)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["poore-nemecek-2018"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions per 100 grams of protein",
      "unit": {
        "code": "kgCO2e-per-100g-protein",
        "label": "kilograms of carbon dioxide equivalent per 100 grams of protein",
        "short": "kg CO₂e/100 g protein"
      },
      "vintage": "Science 360, 987–992 (2018); OWID grapher series updated 2019-10-08"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": false,
      "entities": ["WLD"],
      "export_sha256": "de61e40f95cd26bb7e9927db912fb181b5967fc48f7d2b81534e8bbed28019d6",
      "geo_coverage": "global-only",
      "id": "food.poore-nemecek-2018.ghg-per-kg",
      "latest": null,
      "licence_class": "display-only",
      "provenance": {
        "attribution": "Poore, J. & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science 360(6392), 987–992, doi:10.1126/science.aaq0216 (erratum doi:10.1126/science.aaw9908). Values as processed by Our World in Data.",
        "description": "Greenhouse gas emissions from producing a kilogram of each of about 40 foods, from land-use change and the farm to the shop, in kilograms of carbon dioxide equivalent: global means from Poore and Nemecek (2018), as published by Our World in Data.",
        "kind": "series",
        "licence": {
          "name": "All rights reserved (Science, exclusive licensee AAAS); no data licence",
          "spdx": null,
          "url": null
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "ghg-per-kg", "bytes": 844, "citation_full": "Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987–992. https://doi.org/10.1126/science.aaq0216 (erratum: https://doi.org/10.1126/science.aaw9908). Poore and Nemecek (2018) – processed by Our World in Data.", "date_accessed": "2026-10-04", "date_published": "2018-06-01", "doi": "10.1126/science.aaq0216", "etag": null, "last_modified": "Mon, 05 Oct 2026 01:11:20 GMT", "licence": {"name": "All rights reserved (Science, exclusive licensee AAAS); no data licence", "spdx": null, "url": null}, "producer": "Joseph Poore (University of Oxford) and Thomas Nemecek (Agroscope); published in Science; series processed by Our World in Data", "r2_url": null, "sha256": "aa9425a00b37eb1e8d716596e67b3e072864d9c14b67b519aec618d69296e36a", "source_id": "poore-nemecek-2018", "title": "Environmental footprints of food products (Poore & Nemecek 2018)", "url_download": "https://ourworldindata.org/grapher/ghg-per-kg-poore.csv?v=1&csvType=full&useColumnShortNames=true", "url_main": "https://ourworldindata.org/environmental-impacts-of-food", "version_producer": "Science 360, 987–992 (2018); OWID grapher series updated 2019-10-08", "wayback_url": null}
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        "processing": [
          {
            "description": "Read OWID's grapher CSV of Poore and Nemecek (2018) greenhouse gas emissions per kilogram of food product (column ghg_emissions_per_kilogram__poore__and__nemecek__2018): 38 food products, all for the year 2010. Values are published as printed, with no conversion; the food names are OWID's.",
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            "transform_sha256": "357d2dccb0239ece8a50ccee970833c5e0335f6c2002d343eed4c51422a5e395"
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        ],
        "published_value": null,
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          "basis": "Global mean of the life-cycle studies in Poore and Nemecek's meta-analysis (about 570 studies, 38,700 farms, 119 countries, median reference year 2010), from land-use change and farm to retail, including packaging and losses. Greenhouse gases weighted by their warming over 100 years (GWP100); the IPCC report the factors come from is not stated in the files used. Impacts vary widely between producers of the same food.",
          "bunkers": null,
          "geography": "World (global mean of the studies reviewed)",
          "gwp": null,
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        }
      },
      "source_ids": ["poore-nemecek-2018"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions per kilogram of food",
      "unit": {
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        "label": "kilograms of carbon dioxide equivalent per kilogram of food",
        "short": "kg CO₂e/kg"
      },
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      "geo_coverage": "country",
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        "entity": "GBR",
        "period": "1993/1999",
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        "value": 10.24
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        "attribution": "Scarborough, P., Clark, M., Cobiac, L. et al. (2023). Vegans, vegetarians, fish-eaters and meat-eaters in the UK show discrepant environmental impacts. Nature Food 4, 565–574. doi:10.1038/s43016-023-00795-w. CC BY 4.0.",
        "description": "Greenhouse gas emissions caused by producing the food eaten in a day by vegans, vegetarians, fish-eaters and low, medium and high meat-eaters in a large UK study, per 2,000 kilocalories, in kilograms of carbon dioxide equivalent, with the range that holds 95% of the authors' uncertainty estimates (Scarborough et al. 2023).",
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            "description": "Read the text of the article's version-of-record PDF (sha256 b061fbc4e0b2…). Found Table 3's title, column header, note and all 6 rows on PDF page 5 (printed p. 569), and the Methods sentence on the GWP100 factors on PDF page 7, word for word, before publishing.",
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          {
            "description": "Published the GWP100 column (the first of the table's three metrics): for each diet group the median as the value and the 2.5th and 97.5th percentiles of the authors' 1,000-iteration Monte Carlo analysis as the 95% uncertainty interval, exactly as printed. The GTP100 and GWP20 columns are not published here.",
            "inputs": ["b061fbc4e0b22a1a548061df007ced7a17ec66c380f8e19ab5ea870ce5a81ecc"],
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          "quote": "High meat-eaters 10.24 (7.04, 15.95) 8.97 (6.17, 14.15) 14.77 (10.23, 22.55)"
        },
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          "basis": "Dietary footprint from farm to retail of the food eaten (self-reported in a food frequency questionnaire at the cohort's baseline, 1993–1999), standardized to 2,000 kcal a day and to the cohort's age and gender mix; food-level emissions from a database of life-cycle assessments published 2000–2016. Median and 2.5th–97.5th percentiles of a 1,000-iteration Monte Carlo analysis. GWP100 with IPCC AR6 factors (CH4 27, N2O 273). The period is the years the diets were reported.",
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      },
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      "time_basis": "calendar",
      "title": "Greenhouse gas emissions of UK diets, by diet group",
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        "description": "The UK's whole consumption-based greenhouse gas footprint in the latest year of Defra's release, split into the 14 broad categories of end use Defra publishes for that year only, in million tonnes of carbon dioxide equivalent. The first eleven are households' spending and their direct emissions from heating and driving; 'Central and local government', 'Gross fixed capital formation' (investment, including buying houses) and 'Other' (charities, valuables, inventories) are not. 'Food and beverages' covers food and non-alcoholic drinks bought by households; it excludes 'Hotels and restaurants' and 'Alcohol and tobacco', which are separate rows. Flights have no row of their own: households' spending on flights is inside 'Transportation', while business and government travel sits in the supply chains of the other rows. Health and education paid for by government are under government. The rows add up to the published total. Defra revises earlier years in every annual release. UK only.",
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        },
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        "origins": [
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        ],
        "processing": [
          {
            "description": "Read 'Carbon footprint for the UK dataset, 1990 to 2023' (OpenDocument spreadsheet, sha256 a2fa54f975ca…, retrieved 2026-10-05; the cover sheet says the tables were published on 30 June 2026 and are licensed under the Open Government Licence 3.0). Cells were read from the file's content.xml as written.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
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            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
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          {
            "description": "Selected the 14 rows of sheet Summary_2023, Table 3 'Greenhouse gas emissions by broad category of end use, UK, 2023' (ktCO2e), with their labels as published; note markers such as '[note 3]' were moved from the label to the value's note, which quotes that note from the Notes sheet.",
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          },
          {
            "description": "Checked that the 14 rows add up to the table's Total (699201.91686335055 kt) and that this Total equals the 2023 greenhouse gas footprint in Summary_1990_to_2023, both within 0.001 kt.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
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            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Converted kilotonnes to million tonnes (divided by 1,000, exact decimal arithmetic).",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
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            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
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          {
            "description": "Global warming potentials: Defra's 'Consumption-based accounts for the UK, 1990 to 2023: Summary of methods' (University of Leeds; PDF, sha256 1bd24a507911…, retrieved 2026-10-05), section 1.4, page 6: 'Non-CO2 gasses are converted to CO2e using the Global Warming Potential values from the IPCC Fifth Assessment Report (AR5).' The quote was found in the text of that page before publishing; the scope records AR5 100-year values from it.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
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          "bunkers": null,
          "geography": "United Kingdom",
          "gwp": "AR5-GWP100",
          "lulucf": null
        }
      },
      "source_ids": ["defra-uk-carbon-footprint"],
      "time_basis": "calendar",
      "title": "UK carbon footprint by end use, latest year (Defra)",
      "unit": {
        "code": "MtCO2e/yr",
        "label": "million tonnes of carbon dioxide equivalent per year",
        "short": "Mt CO₂e/yr"
      },
      "vintage": "UK carbon footprint 1990 to 2023, published 30 June 2026"
    },
    {
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      "downloadable": true,
      "entities": ["GBR"],
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      "geo_coverage": "country",
      "id": "footprint.defra.households-by-product",
      "latest": {
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        "dims": {
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        },
        "entity": "GBR",
        "period": "2023",
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      "licence_class": "open",
      "provenance": {
        "attribution": "Adapted by Environment Dashboard from Department for Environment, Food & Rural Affairs, UK and England's carbon footprint to 2023 (UK carbon footprint 1990 to 2023, published 30 June 2026), data produced by the University of Leeds. Contains public sector information licensed under the Open Government Licence v3.0. Changes: converted from thousand tonnes to million tonnes of carbon dioxide equivalent.",
        "description": "The consumption-based greenhouse gas footprint of UK households' own spending and their direct emissions from heating fuels and private vehicles, split into the 34 COICOP product groups Defra publishes, in million tonnes of carbon dioxide equivalent per year. Government spending, investment (including buying houses) and charities are not included, so these add up to the households' part of the UK footprint, not to the whole. 'Food' and 'Non-alcoholic beverages' do not include meals and drinks bought in restaurants, cafés and hotels, which are in 'Restaurants and hotels'. Flights have no group of their own; they are inside 'Transport services'. Defra revises earlier years in every annual release, and says the estimates for 1990 to 1996 are more uncertain. UK only.",
        "kind": "series",
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "uk-dataset", "bytes": 98019, "citation_full": "Department for Environment, Food & Rural Affairs (2026). UK and England's carbon footprint to 2023: Carbon footprint for the UK dataset, 1990 to 2023 (UK carbon footprint 1990 to 2023, published 30 June 2026). GOV.UK. https://www.gov.uk/government/statistics/uks-carbon-footprint", "date_accessed": "2026-10-05", "date_published": "2026-06-30", "doi": null, "etag": "\"6a3ce5c9-17ee3\"", "last_modified": "Thu, 25 Jun 2026 08:24:41 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Department for Environment, Food & Rural Affairs (Defra); data produced by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b.zst", "sha256": "a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "source_id": "defra-uk-carbon-footprint", "title": "UK and England's carbon footprint to 2023", "url_download": "https://assets.publishing.service.gov.uk/media/6a3ce5c930b491f55b3c494c/UK_carbon_footprint_dataset_1990_to_2023.ods", "url_main": "https://www.gov.uk/government/statistics/uks-carbon-footprint", "version_producer": "UK carbon footprint 1990 to 2023, published 30 June 2026", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methods", "bytes": 1032209, "citation_full": "Department for Environment, Food & Rural Affairs (2026). UK and England's carbon footprint to 2023: Carbon footprint for the UK dataset, 1990 to 2023 (UK carbon footprint 1990 to 2023, published 30 June 2026). GOV.UK. https://www.gov.uk/government/statistics/uks-carbon-footprint", "date_accessed": "2026-10-05", "date_published": "2026-06-30", "doi": null, "etag": "\"6a3ce627-fc011\"", "last_modified": "Thu, 25 Jun 2026 08:26:15 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Department for Environment, Food & Rural Affairs (Defra); data produced by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5.zst", "sha256": "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5", "source_id": "defra-uk-carbon-footprint", "title": "UK and England's carbon footprint to 2023", "url_download": "https://assets.publishing.service.gov.uk/media/6a3ce626eaee00074150f449/UK_and_England_s_Carbon_Footprint_Summary_of_Methods_2026.pdf", "url_main": "https://www.gov.uk/government/statistics/uks-carbon-footprint", "version_producer": "UK carbon footprint 1990 to 2023, published 30 June 2026", "wayback_url": null}
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        "processing": [
          {
            "description": "Read 'Carbon footprint for the UK dataset, 1990 to 2023' (OpenDocument spreadsheet, sha256 a2fa54f975ca…, retrieved 2026-10-05; the cover sheet says the tables were published on 30 June 2026 and are licensed under the Open Government Licence 3.0). Cells were read from the file's content.xml as written.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Selected the 34 product columns of sheet Summary_product, Table 1 'Greenhouse gas emissions from household and household direct expenditure by broad product category' (ktCO2e), 1990–2023, with their labels as published (note markers moved to the value's note, which quotes the Notes sheet). Table 2 of the sheet (carbon dioxide only) was not used.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Checked that in every year the products add up to the table's Total, and that the Total equals Households plus Households direct in Summary_final_demand Table 1, both within 0.001 kt. 2023: Total 528626.10144782555 kt.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Copied the cover sheet's sentence on 1990 to 1996 as the note of each of those years.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Converted kilotonnes to million tonnes (divided by 1,000, exact decimal arithmetic).",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Global warming potentials: Defra's 'Consumption-based accounts for the UK, 1990 to 2023: Summary of methods' (University of Leeds; PDF, sha256 1bd24a507911…, retrieved 2026-10-05), section 1.4, page 6: 'Non-CO2 gasses are converted to CO2e using the Global Warming Potential values from the IPCC Fifth Assessment Report (AR5).' The quote was found in the text of that page before publishing; the scope records AR5 100-year values from it.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Consumption-based footprint: greenhouse gas emissions anywhere in the world from producing the goods and services used in the UK, plus households' own emissions from heating fuels and private vehicles; emissions from producing UK exports are not counted. Estimated by the University of Leeds with a multi-regional input-output model. Flights have no separate figure; they are inside transport.",
          "bunkers": null,
          "geography": "United Kingdom: households",
          "gwp": "AR5-GWP100",
          "lulucf": null
        }
      },
      "source_ids": ["defra-uk-carbon-footprint"],
      "time_basis": "calendar",
      "title": "UK households' carbon footprint by product (Defra)",
      "unit": {
        "code": "MtCO2e/yr",
        "label": "million tonnes of carbon dioxide equivalent per year",
        "short": "Mt CO₂e/yr"
      },
      "vintage": "UK carbon footprint 1990 to 2023, published 30 June 2026"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["GBR"],
      "export_sha256": "f610c0dba3e166713f8e3e3fe1f05b8cefd6b76f6f32d9e92c4edaa14f0db333",
      "geo_coverage": "country",
      "id": "footprint.defra.per-capita",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "GBR",
        "period": "2023",
        "status": "final",
        "value": 10.2034271610218
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Department for Environment, Food & Rural Affairs, UK and England's carbon footprint to 2023 (UK carbon footprint 1990 to 2023, published 30 June 2026), data produced by the University of Leeds. Contains public sector information licensed under the Open Government Licence v3.0.",
        "description": "The UK's consumption-based greenhouse gas footprint divided by its population, as published by Defra, in tonnes of carbon dioxide equivalent per person per year. It counts emissions anywhere in the world from producing what is used in the UK, by households, government and investment, plus households' own emissions from heating and driving; it is an average over everyone in the UK, not a measure of any one person's choices. Defra revises earlier years in every annual release, and says the estimates for 1990 to 1996 are more uncertain. UK only.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0 (Crown copyright)",
          "spdx": "OGL-UK-3.0",
          "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "uk-dataset", "bytes": 98019, "citation_full": "Department for Environment, Food & Rural Affairs (2026). UK and England's carbon footprint to 2023: Carbon footprint for the UK dataset, 1990 to 2023 (UK carbon footprint 1990 to 2023, published 30 June 2026). GOV.UK. https://www.gov.uk/government/statistics/uks-carbon-footprint", "date_accessed": "2026-10-05", "date_published": "2026-06-30", "doi": null, "etag": "\"6a3ce5c9-17ee3\"", "last_modified": "Thu, 25 Jun 2026 08:24:41 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Department for Environment, Food & Rural Affairs (Defra); data produced by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b.zst", "sha256": "a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "source_id": "defra-uk-carbon-footprint", "title": "UK and England's carbon footprint to 2023", "url_download": "https://assets.publishing.service.gov.uk/media/6a3ce5c930b491f55b3c494c/UK_carbon_footprint_dataset_1990_to_2023.ods", "url_main": "https://www.gov.uk/government/statistics/uks-carbon-footprint", "version_producer": "UK carbon footprint 1990 to 2023, published 30 June 2026", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "methods", "bytes": 1032209, "citation_full": "Department for Environment, Food & Rural Affairs (2026). UK and England's carbon footprint to 2023: Carbon footprint for the UK dataset, 1990 to 2023 (UK carbon footprint 1990 to 2023, published 30 June 2026). GOV.UK. https://www.gov.uk/government/statistics/uks-carbon-footprint", "date_accessed": "2026-10-05", "date_published": "2026-06-30", "doi": null, "etag": "\"6a3ce627-fc011\"", "last_modified": "Thu, 25 Jun 2026 08:26:15 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Department for Environment, Food & Rural Affairs (Defra); data produced by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5.zst", "sha256": "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5", "source_id": "defra-uk-carbon-footprint", "title": "UK and England's carbon footprint to 2023", "url_download": "https://assets.publishing.service.gov.uk/media/6a3ce626eaee00074150f449/UK_and_England_s_Carbon_Footprint_Summary_of_Methods_2026.pdf", "url_main": "https://www.gov.uk/government/statistics/uks-carbon-footprint", "version_producer": "UK carbon footprint 1990 to 2023, published 30 June 2026", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read 'Carbon footprint for the UK dataset, 1990 to 2023' (OpenDocument spreadsheet, sha256 a2fa54f975ca…, retrieved 2026-10-05; the cover sheet says the tables were published on 30 June 2026 and are licensed under the Open Government Licence 3.0). Cells were read from the file's content.xml as written.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Selected the column 'Greenhouse gases (tCO2e per capita)' of sheet Summary_1990_to_2023, 1990–2023, as published (Defra's own per-person figure). No value was changed.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Copied the cover sheet's sentence on 1990 to 1996 ('There is a higher degree of uncertainty around the estimates for 1990 to 1996, so they should be interpreted with caution.') as the note of each of those years.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          },
          {
            "description": "Global warming potentials: Defra's 'Consumption-based accounts for the UK, 1990 to 2023: Summary of methods' (University of Leeds; PDF, sha256 1bd24a507911…, retrieved 2026-10-05), section 1.4, page 6: 'Non-CO2 gasses are converted to CO2e using the Global Warming Potential values from the IPCC Fifth Assessment Report (AR5).' The quote was found in the text of that page before publishing; the scope records AR5 100-year values from it.",
            "inputs": ["a2fa54f975caa9fdb7b2092273683f9ff7b395f2bdc571c8489be79532c2085b", "1bd24a5079114b85d13274f22eead875ac4ef23d974d63118601bde6793dc0f5"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/defra_uk.py",
            "transform_sha256": "d05b1873094a65b4504b86e74a3eaa7e825b1e7f9f71496bac0d1673815d218e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Consumption-based footprint: greenhouse gas emissions anywhere in the world from producing the goods and services used in the UK, plus households' own emissions from heating fuels and private vehicles; emissions from producing UK exports are not counted. Estimated by the University of Leeds with a multi-regional input-output model. Flights have no separate figure; they are inside transport.",
          "bunkers": null,
          "geography": "United Kingdom: average per resident",
          "gwp": "AR5-GWP100",
          "lulucf": null
        }
      },
      "source_ids": ["defra-uk-carbon-footprint"],
      "time_basis": "calendar",
      "title": "UK carbon footprint per resident, average (Defra)",
      "unit": {
        "code": "tCO2e/person/yr",
        "label": "tonnes of carbon dioxide equivalent per person per year",
        "short": "t CO₂e/person/yr"
      },
      "vintage": "UK carbon footprint 1990 to 2023, published 30 June 2026"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["SWE"],
      "export_sha256": "29b5814003f574e8f6af359f6a18b39ffefb9bd75a973c3737e79b4890d1b649",
      "geo_coverage": "country",
      "id": "footprint.naturvardsverket.per-person-by-area",
      "latest": {
        "age_bp": null,
        "dims": {
          "area": "food"
        },
        "entity": "SWE",
        "period": "2023",
        "status": "final",
        "value": 1.35
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Naturvårdsverket, Konsumtionsbaserade växthusgasutsläpp per person och år (2008-2023 series, page reviewed 2025-10-28); official statistics of Sweden, responsible authority Statistics Sweden (SCB). Open data; SCB data CC0 1.0.",
        "description": "The consumption-based greenhouse gas footprint of an average person in Sweden: emissions in Sweden and abroad from producing everything used in Sweden, divided by the population, in tonnes of carbon dioxide equivalent per person per year, as published by Naturvårdsverket from Statistics Sweden's official statistics. Split into the six parts the producer publishes. Four are household consumption (transport, food products, housing, and other goods and services); the page does not say whether meals eaten out count under food products or under other goods and services. The other two, public consumption (schools, hospitals, agencies) and investment (buildings including new homes, machinery, computers, valuables and changes in inventories), are shared out per person but are not personal choices; buying a new home counts under investment, not housing. The parts are rounded by the producer and may differ from the published total by 0.01 t. International flights are undercounted: only jet fuel bought in Sweden is counted, without stopovers or the high-altitude effect. The page shows the IPCC Fourth Assessment Report (AR4) global warming potentials (methane 25, nitrous oxide 298) in a general conversion table, without saying they apply to this series. Sweden only; it is not a world average or a measure of any one person.",
        "kind": "series",
        "licence": {
          "name": "Naturvårdsverket open data (free use, attribution requested); the underlying SCB official statistics are CC0 1.0",
          "spdx": null,
          "url": "https://www.naturvardsverket.se/om-oss/om-webbplatsen/struktur-och-funktion/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "per-person-page", "bytes": 231605, "citation_full": "Naturvårdsverket (2025). Konsumtionsbaserade växthusgasutsläpp per person och år (2008-2023 series, page reviewed 2025-10-28). Official statistics of Sweden; responsible authority Statistics Sweden (SCB). https://www.naturvardsverket.se/data-och-statistik/konsumtion/vaxthusgaser-konsumtionsbaserade-utslapp-per-person/", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "Naturvårdsverket open data (free use, attribution requested); the underlying SCB official statistics are CC0 1.0", "spdx": null, "url": "https://www.naturvardsverket.se/om-oss/om-webbplatsen/struktur-och-funktion/"}, "producer": "Naturvårdsverket (Swedish Environmental Protection Agency); official statistics from Statistics Sweden (SCB)", "r2_url": null, "sha256": "da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30", "source_id": "naturvardsverket-consumption-footprint", "title": "Konsumtionsbaserade växthusgasutsläpp per person och år (consumption-based greenhouse gas emissions per person)", "url_download": "https://www.naturvardsverket.se/data-och-statistik/konsumtion/vaxthusgaser-konsumtionsbaserade-utslapp-per-person/", "url_main": "https://www.naturvardsverket.se/data-och-statistik/konsumtion/vaxthusgaser-konsumtionsbaserade-utslapp-per-person/", "version_producer": "2008-2023 series, page reviewed 2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the statistics page 'Konsumtionsbaserade växthusgasutsläpp per person och år' (sha256 da4e1b4dd620…, retrieved 2026-10-05, reviewed by the producer on 2025-10-28). The series is the CSV inside the page's chart options (page model <script id=\"__model_data\">, content.highChartsOptions, data.csv): 16 years, 2008–2023, in tonnes of carbon dioxide equivalent per person ('Ton koldioxidekvivalenter per person'). Checked the page heading, the responsible authority (SCB), the axis title, the series names and the CSV header before reading any value.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          },
          {
            "description": "Selected the six parts as published, each with its Swedish column name kept in its label: Transporter = transport; Livsmedel = food; Boende = housing; Övrigt = other-household; Offentlig konsumtion = public-consumption; Investeringar = investment. The first four are households' consumption; public consumption and investment are not household spending.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          },
          {
            "description": "Checked that in every year the six parts add up to the published Totalt within 0.01 t (the producer rounds each value to two decimals). Years where they differ by 0.01 t: 2009 (+0.01 t), 2010 (+0.01 t), 2020 (+0.01 t), 2021 (-0.01 t), 2022 (-0.01 t). No value was changed.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          },
          {
            "description": "Checked the page's tab 'Koldioxidekvivalenter': its general conversion table ('Omräkningstabell') gives CO2 1, CH4 25 and N2O 298, the IPCC Fourth Assessment Report (AR4) 100-year values, and links that report ('Koldioxidekvivalenter för ytterligare växthusgaser i IPCC:s fjärde utvärderingsrapport'), but the page does not say that this series uses them. So no global warming potential is recorded in the scope; the basis says what the page shows.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Consumption-based footprint: greenhouse gas emissions in Sweden and abroad from producing the goods and services used in Sweden (by households, the public sector and investment), divided by the population; emissions from producing Sweden's exports are not counted. International flights are undercounted: only jet fuel bought in Sweden is counted, stopovers are missed and the high-altitude effect is not included. Global warming potentials: the page shows the IPCC Fourth Assessment Report (AR4) values (methane 25, nitrous oxide 298) in a general conversion table, without saying they apply to this series.",
          "bunkers": null,
          "geography": "Sweden: the average person in Sweden's population",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["naturvardsverket-consumption-footprint"],
      "time_basis": "calendar",
      "title": "Greenhouse gas footprint of an average person in Sweden, by consumption area (Naturvårdsverket)",
      "unit": {
        "code": "tCO2e/person/yr",
        "label": "tonnes of carbon dioxide equivalent per person per year",
        "short": "t CO₂e/person/yr"
      },
      "vintage": "2008-2023 series, page reviewed 2025-10-28"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["SWE"],
      "export_sha256": "862e956abb199f4ba09ecadc516c849f5a5366cde4ecb79b4a1dcd43849e0452",
      "geo_coverage": "country",
      "id": "footprint.naturvardsverket.per-person-total",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "SWE",
        "period": "2023",
        "status": "final",
        "value": 7.62
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Naturvårdsverket, Konsumtionsbaserade växthusgasutsläpp per person och år (2008-2023 series, page reviewed 2025-10-28); official statistics of Sweden, responsible authority Statistics Sweden (SCB). Open data; SCB data CC0 1.0.",
        "description": "The consumption-based greenhouse gas footprint of an average person in Sweden: emissions in Sweden and abroad from producing everything used in Sweden, divided by the population, in tonnes of carbon dioxide equivalent per person per year, as published by Naturvårdsverket from Statistics Sweden's official statistics. This is the producer's published total (Totalt). It includes household consumption and also public consumption and investment, which are shared out per person but are not personal choices. International flights are undercounted: only jet fuel bought in Sweden is counted, without stopovers or the high-altitude effect. The page shows the IPCC Fourth Assessment Report (AR4) global warming potentials (methane 25, nitrous oxide 298) in a general conversion table, without saying they apply to this series. Sweden only; it is not a world average or a measure of any one person.",
        "kind": "series",
        "licence": {
          "name": "Naturvårdsverket open data (free use, attribution requested); the underlying SCB official statistics are CC0 1.0",
          "spdx": null,
          "url": "https://www.naturvardsverket.se/om-oss/om-webbplatsen/struktur-och-funktion/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "per-person-page", "bytes": 231605, "citation_full": "Naturvårdsverket (2025). Konsumtionsbaserade växthusgasutsläpp per person och år (2008-2023 series, page reviewed 2025-10-28). Official statistics of Sweden; responsible authority Statistics Sweden (SCB). https://www.naturvardsverket.se/data-och-statistik/konsumtion/vaxthusgaser-konsumtionsbaserade-utslapp-per-person/", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": null, "last_modified": null, "licence": {"name": "Naturvårdsverket open data (free use, attribution requested); the underlying SCB official statistics are CC0 1.0", "spdx": null, "url": "https://www.naturvardsverket.se/om-oss/om-webbplatsen/struktur-och-funktion/"}, "producer": "Naturvårdsverket (Swedish Environmental Protection Agency); official statistics from Statistics Sweden (SCB)", "r2_url": null, "sha256": "da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30", "source_id": "naturvardsverket-consumption-footprint", "title": "Konsumtionsbaserade växthusgasutsläpp per person och år (consumption-based greenhouse gas emissions per person)", "url_download": "https://www.naturvardsverket.se/data-och-statistik/konsumtion/vaxthusgaser-konsumtionsbaserade-utslapp-per-person/", "url_main": "https://www.naturvardsverket.se/data-och-statistik/konsumtion/vaxthusgaser-konsumtionsbaserade-utslapp-per-person/", "version_producer": "2008-2023 series, page reviewed 2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the statistics page 'Konsumtionsbaserade växthusgasutsläpp per person och år' (sha256 da4e1b4dd620…, retrieved 2026-10-05, reviewed by the producer on 2025-10-28). The series is the CSV inside the page's chart options (page model <script id=\"__model_data\">, content.highChartsOptions, data.csv): 16 years, 2008–2023, in tonnes of carbon dioxide equivalent per person ('Ton koldioxidekvivalenter per person'). Checked the page heading, the responsible authority (SCB), the axis title, the series names and the CSV header before reading any value.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          },
          {
            "description": "Selected the column Totalt as published (the producer's own total, not a sum of ours). No value was changed.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          },
          {
            "description": "Checked the page's tab 'Koldioxidekvivalenter': its general conversion table ('Omräkningstabell') gives CO2 1, CH4 25 and N2O 298, the IPCC Fourth Assessment Report (AR4) 100-year values, and links that report ('Koldioxidekvivalenter för ytterligare växthusgaser i IPCC:s fjärde utvärderingsrapport'), but the page does not say that this series uses them. So no global warming potential is recorded in the scope; the basis says what the page shows.",
            "inputs": ["da4e1b4dd6201559013bbca3a522d2adeda80e7ffd10d0aeb40a9b8e969ffc30"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/footprints/naturvardsverket.py",
            "transform_sha256": "dcfd45c65b18c23ca05ec4751b1efbaf53fc6223b900cf5c523b3894b5b28a56"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Consumption-based footprint: greenhouse gas emissions in Sweden and abroad from producing the goods and services used in Sweden (by households, the public sector and investment), divided by the population; emissions from producing Sweden's exports are not counted. International flights are undercounted: only jet fuel bought in Sweden is counted, stopovers are missed and the high-altitude effect is not included. Global warming potentials: the page shows the IPCC Fourth Assessment Report (AR4) values (methane 25, nitrous oxide 298) in a general conversion table, without saying they apply to this series.",
          "bunkers": null,
          "geography": "Sweden: the average person in Sweden's population",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["naturvardsverket-consumption-footprint"],
      "time_basis": "calendar",
      "title": "Greenhouse gas footprint of an average person in Sweden (Naturvårdsverket)",
      "unit": {
        "code": "tCO2e/person/yr",
        "label": "tonnes of carbon dioxide equivalent per person per year",
        "short": "t CO₂e/person/yr"
      },
      "vintage": "2008-2023 series, page reviewed 2025-10-28"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "cd925655b3937f65d71c984463585fe20e75c8b5853bd9362ca8ebddd65dc438",
      "geo_coverage": "global-only",
      "id": "forcing.igcc-2025.erf-by-agent",
      "latest": {
        "age_bp": null,
        "dims": {
          "agent": "anthropogenic"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 3.103548614
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Indicators of Global Climate Change 2025: Forster et al. (2026), Earth Syst. Sci. Data 18, 3889–3933, doi:10.5194/essd-18-3889-2026; data: Smith et al. (2026), version IGCC-2025a, doi:10.5281/zenodo.21494229. CC BY 4.0.",
        "description": "Effective radiative forcing: the change in the energy balance at the top of the atmosphere caused by each agent, after the atmosphere has adjusted. Positive values warm the planet, negative values (most aerosols) cool it. Best estimate with the 5–95% range for each year from 1750 to 2025, by greenhouse gas, aerosol and other agents, from Indicators of Global Climate Change 2025. Human-caused agents are counted from zero in 1750; solar and volcanic forcing are IGCC's time series, which do not start from zero in 1750.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "data-igcc-2025a", "bytes": 1495354, "citation_full": "Forster, P. M., Walsh, T., Smith, C., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Andrew, R. M., Atkinson, C., Betts, R. A., Bombelli, A., Burgess, S. N., Cheng, L., Claxton, H. E., Friedlingstein, P., Frölicher, T. L., Domingues, C. M., Gasser, T., Gregory, C. H., Hoesly, R. M., Huppmann, D., Ishii, M., Kadow, C., Karwat, A., Kennedy, J., Killick, R. E., Kovilakam, M. V. M., Krummel, P. B., Lan, X., Lamarque, J.-F., Liné, A., Martín-Míguez, B., Monselesan, D. P., Morice, C., Mühle, J., Mussak, P., Peters, G. P., Pirani, A., Pongratz, J., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Smith, S. J., Taha, G., Tassone, C., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Zecchetto, M., Zhong, J., Zhang, X.-Y., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2025: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, 2026. Smith, C., Walsh, T., Gillett, N., Hauser, M., Krummel, P., Lamb, W., Lamboll, R., Mühle, J., Palmer, M., Ribes, A., Schumacher, D., Seneviratne, S., Slangen, A., Trewin, B., von Schuckmann, K., & Forster, P. (2026). Indicators of Global Climate Change 2025 (Version IGCC-2025a) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.21494229", "date_accessed": "2026-10-04", "date_published": "2026-07-22", "doi": "10.5281/zenodo.21494229", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Indicators of Global Climate Change (IGCC) consortium, led by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd.zst", "sha256": "04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "source_id": "igcc-2025", "title": "Indicators of Global Climate Change 2025", "url_download": "https://zenodo.org/api/records/21494229/files/ClimateIndicator/data-IGCC-2025a.zip/content", "url_main": "https://doi.org/10.5281/zenodo.21494229", "version_producer": "IGCC-2025a", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "erf-best-aggregates", "bytes": 73223, "citation_full": "Forster, P. M., Walsh, T., Smith, C., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Andrew, R. M., Atkinson, C., Betts, R. A., Bombelli, A., Burgess, S. N., Cheng, L., Claxton, H. E., Friedlingstein, P., Frölicher, T. L., Domingues, C. M., Gasser, T., Gregory, C. H., Hoesly, R. M., Huppmann, D., Ishii, M., Kadow, C., Karwat, A., Kennedy, J., Killick, R. E., Kovilakam, M. V. M., Krummel, P. B., Lan, X., Lamarque, J.-F., Liné, A., Martín-Míguez, B., Monselesan, D. P., Morice, C., Mühle, J., Mussak, P., Peters, G. P., Pirani, A., Pongratz, J., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Smith, S. J., Taha, G., Tassone, C., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Zecchetto, M., Zhong, J., Zhang, X.-Y., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2025: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, 2026. Smith, C., Walsh, T., Gillett, N., Hauser, M., Krummel, P., Lamb, W., Lamboll, R., Mühle, J., Palmer, M., Ribes, A., Schumacher, D., Seneviratne, S., Slangen, A., Trewin, B., von Schuckmann, K., & Forster, P. (2026). Indicators of Global Climate Change 2025 (Version IGCC-2025a) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.21494229", "date_accessed": "2026-10-04", "date_published": "2026-07-22", "doi": "10.5281/zenodo.21494229", "etag": "W/\"f14f3e5b037a7b9809583eb68879c94cc187305b2efb91f012209598861dca59\"", "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Indicators of Global Climate Change (IGCC) consortium, led by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/68e66370d5dd13134a275e21998c4ec517ca96d37fd3ee2865dc1a307c2200d9.zst", "sha256": "68e66370d5dd13134a275e21998c4ec517ca96d37fd3ee2865dc1a307c2200d9", "source_id": "igcc-2025", "title": "Indicators of Global Climate Change 2025", "url_download": "https://raw.githubusercontent.com/ClimateIndicator/data/0f2765dc2e96c98aebceb78fb12cd28fcfb9ac6f/data/base/effective_radiative_forcing/ERF_best_aggregates.csv", "url_main": "https://doi.org/10.5281/zenodo.21494229", "version_producer": "IGCC-2025a", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "erf-p05-aggregates", "bytes": 73008, "citation_full": "Forster, P. M., Walsh, T., Smith, C., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Andrew, R. M., Atkinson, C., Betts, R. A., Bombelli, A., Burgess, S. N., Cheng, L., Claxton, H. E., Friedlingstein, P., Frölicher, T. L., Domingues, C. M., Gasser, T., Gregory, C. H., Hoesly, R. M., Huppmann, D., Ishii, M., Kadow, C., Karwat, A., Kennedy, J., Killick, R. E., Kovilakam, M. V. M., Krummel, P. B., Lan, X., Lamarque, J.-F., Liné, A., Martín-Míguez, B., Monselesan, D. P., Morice, C., Mühle, J., Mussak, P., Peters, G. P., Pirani, A., Pongratz, J., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Smith, S. J., Taha, G., Tassone, C., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Zecchetto, M., Zhong, J., Zhang, X.-Y., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2025: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, 2026. Smith, C., Walsh, T., Gillett, N., Hauser, M., Krummel, P., Lamb, W., Lamboll, R., Mühle, J., Palmer, M., Ribes, A., Schumacher, D., Seneviratne, S., Slangen, A., Trewin, B., von Schuckmann, K., & Forster, P. (2026). Indicators of Global Climate Change 2025 (Version IGCC-2025a) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.21494229", "date_accessed": "2026-10-04", "date_published": "2026-07-22", "doi": "10.5281/zenodo.21494229", "etag": "W/\"5b87581f4bc8bf6ed514a05cbeedc2553d0a0c763efd7ad5bff0689c2c09011a\"", "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Indicators of Global Climate Change (IGCC) consortium, led by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/ce98d15a21427bfcc4be9397a86b24706a18d32240a6dc53ca9cfa222f5440ed.zst", "sha256": "ce98d15a21427bfcc4be9397a86b24706a18d32240a6dc53ca9cfa222f5440ed", "source_id": "igcc-2025", "title": "Indicators of Global Climate Change 2025", "url_download": "https://raw.githubusercontent.com/ClimateIndicator/data/0f2765dc2e96c98aebceb78fb12cd28fcfb9ac6f/data/base/effective_radiative_forcing/ERF_p05_aggregates.csv", "url_main": "https://doi.org/10.5281/zenodo.21494229", "version_producer": "IGCC-2025a", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "erf-p95-aggregates", "bytes": 72605, "citation_full": "Forster, P. M., Walsh, T., Smith, C., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Andrew, R. M., Atkinson, C., Betts, R. A., Bombelli, A., Burgess, S. N., Cheng, L., Claxton, H. E., Friedlingstein, P., Frölicher, T. L., Domingues, C. M., Gasser, T., Gregory, C. H., Hoesly, R. M., Huppmann, D., Ishii, M., Kadow, C., Karwat, A., Kennedy, J., Killick, R. E., Kovilakam, M. V. M., Krummel, P. B., Lan, X., Lamarque, J.-F., Liné, A., Martín-Míguez, B., Monselesan, D. P., Morice, C., Mühle, J., Mussak, P., Peters, G. P., Pirani, A., Pongratz, J., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Smith, S. J., Taha, G., Tassone, C., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Zecchetto, M., Zhong, J., Zhang, X.-Y., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2025: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, 2026. Smith, C., Walsh, T., Gillett, N., Hauser, M., Krummel, P., Lamb, W., Lamboll, R., Mühle, J., Palmer, M., Ribes, A., Schumacher, D., Seneviratne, S., Slangen, A., Trewin, B., von Schuckmann, K., & Forster, P. (2026). Indicators of Global Climate Change 2025 (Version IGCC-2025a) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.21494229", "date_accessed": "2026-10-04", "date_published": "2026-07-22", "doi": "10.5281/zenodo.21494229", "etag": "W/\"266fe9b8e7d98b5847a5db67b13bb7d1d2b473a9e5caf7274cd019f8a88e43a0\"", "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Indicators of Global Climate Change (IGCC) consortium, led by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/325755f3a3c50148dbddf55d96e91a9be1c404661a9f643f99b894cc1ca6548a.zst", "sha256": "325755f3a3c50148dbddf55d96e91a9be1c404661a9f643f99b894cc1ca6548a", "source_id": "igcc-2025", "title": "Indicators of Global Climate Change 2025", "url_download": "https://raw.githubusercontent.com/ClimateIndicator/data/0f2765dc2e96c98aebceb78fb12cd28fcfb9ac6f/data/base/effective_radiative_forcing/ERF_p95_aggregates.csv", "url_main": "https://doi.org/10.5281/zenodo.21494229", "version_producer": "IGCC-2025a", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Checked that each file read (ERF_best_aggregates.csv, ERF_p05_aggregates.csv, ERF_p95_aggregates.csv) is byte-identical to the same path inside the IGCC-2025a release zip deposited on Zenodo (doi:10.5281/zenodo.21494229, sha256 04658ff91053…).",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "68e66370d5dd13134a275e21998c4ec517ca96d37fd3ee2865dc1a307c2200d9", "ce98d15a21427bfcc4be9397a86b24706a18d32240a6dc53ca9cfa222f5440ed", "325755f3a3c50148dbddf55d96e91a9be1c404661a9f643f99b894cc1ca6548a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Read the best estimate, 5th and 95th percentile of effective radiative forcing for each year from 1750 and each of 18 agents and aggregates, as published (W/m²). The 5–95% range is IGCC's, taken from its own percentile files; nothing is re-estimated.",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "68e66370d5dd13134a275e21998c4ec517ca96d37fd3ee2865dc1a307c2200d9", "ce98d15a21427bfcc4be9397a86b24706a18d32240a6dc53ca9cfa222f5440ed", "325755f3a3c50148dbddf55d96e91a9be1c404661a9f643f99b894cc1ca6548a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Checked that every human-caused column is exactly zero in 1750 in all three files, so its values are the change since 1750. Solar and volcanic forcing are not zero in 1750 (best estimates 0.02159121 and 0.234943996 W/m²), so the natural and total values are IGCC's time series as published, not changes since 1750. IGCC gives solar for 2025 as a single-year value, separate from its assessment over complete solar cycles, and includes volcanic forcing in the time series without a single-year assessment for 2025 (ESSD Sect. 5).",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "68e66370d5dd13134a275e21998c4ec517ca96d37fd3ee2865dc1a307c2200d9", "ce98d15a21427bfcc4be9397a86b24706a18d32240a6dc53ca9cfa222f5440ed", "325755f3a3c50148dbddf55d96e91a9be1c404661a9f643f99b894cc1ca6548a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Checked in the best-estimate file that each aggregate equals the sum of its parts to 1e-6 W/m² (aerosols, well-mixed greenhouse gases, total human-caused, natural, total), which confirms what each column means. Not published as agents of their own: minor, nonco2wmghg, anthro_nonwmghg, which are sums of published columns (non-CO₂ well-mixed greenhouse gases = methane + nitrous oxide + halogenated gases; minor = contrails + land use + black carbon on snow + stratospheric water vapour; human-caused other than well-mixed greenhouse gases = ozone + stratospheric water vapour + aerosols + contrails + land use + black carbon on snow), checked to 1e-6 W/m² the same way.",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "68e66370d5dd13134a275e21998c4ec517ca96d37fd3ee2865dc1a307c2200d9", "ce98d15a21427bfcc4be9397a86b24706a18d32240a6dc53ca9cfa222f5440ed", "325755f3a3c50148dbddf55d96e91a9be1c404661a9f643f99b894cc1ca6548a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1750 for every human-caused agent (each is zero in 1750 in IGCC's files); solar and volcanic as in IGCC's time series, which are not zero in 1750",
          "basis": "IGCC's ERF time series 1750–2025 (ESSD Fig. 5b), single-year values. Solar is IGCC's single-year solar ERF, separate from its assessment over complete solar cycles; volcanic is included in the time series, though IGCC gives no single-year volcanic assessment for 2025. Natural and total include both. 5th to 95th percentile range from IGCC's ensemble.",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["igcc-2025"],
      "time_basis": "calendar",
      "title": "Effective radiative forcing by agent, 1750–2025 (IGCC 2025)",
      "unit": {
        "code": "W/m2",
        "label": "watts per square metre",
        "short": "W/m²"
      },
      "vintage": "IGCC-2025a"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAF", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "2f8717d284332bddfb0196793c3519781fb881f1890b416331edd9439ccb19e8",
      "geo_coverage": "mixed",
      "id": "forest.fao-fra-2025.area",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 4140443.71
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2026. Global Forest Resources Assessment. https://fra-data.fao.org. Accessed on: 2026-10-04. Licence: CC-BY-4.0. Global estimates: FAO. 2025. Global Forest Resources Assessment 2025. Rome. https://doi.org/10.4060/cd6709en Changes: world total calculated as the sum of all countries and areas.",
        "description": "The area of forest in each country and in the world in 1990, 2000, 2010, 2015, 2020 and 2025, in thousands of hectares, as reported to FAO's Global Forest Resources Assessment 2025.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use; report CC BY 4.0)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "This adaptation was not created by the Food and Agriculture Organization of the United Nations (FAO). FAO is not responsible for the content or accuracy of this adaptation. The original English edition shall be the authoritative edition.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "bulk-download-world", "bytes": 1377159, "citation_full": "FAO. 2025. Global Forest Resources Assessment 2025. Rome. https://doi.org/10.4060/cd6709en. FAO. 2026. Global Forest Resources Assessment. https://fra-data.fao.org. Accessed on: 2026-10-04", "date_accessed": "2026-10-04", "date_published": "2025-10-21", "doi": "10.4060/cd6709en", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use; report CC BY 4.0)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Forestry Division", "r2_url": "https://files.environmentdashboard.org/raw/cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c.zst", "sha256": "cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "source_id": "fao-fra-2025", "title": "Global Forest Resources Assessment 2025", "url_download": "https://fra-data.fao.org/api/file/bulk-download?assessmentName=fra&cycleName=2025&countryIso=WO", "url_main": "https://fra-data.fao.org/assessments/fra/2025/WO/home/overview", "version_producer": "FRA 2025 platform, downloaded 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "report-2025", "bytes": 8585230, "citation_full": "FAO. 2025. Global Forest Resources Assessment 2025. Rome. https://doi.org/10.4060/cd6709en. FAO. 2026. Global Forest Resources Assessment. https://fra-data.fao.org. Accessed on: 2026-10-04", "date_accessed": "2026-10-04", "date_published": "2025-10-21", "doi": "10.4060/cd6709en", "etag": "\"bfcf1b18a9f5360baa693fcd6a04029e\"", "last_modified": "Tue, 21 Oct 2025 06:30:26 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use; report CC BY 4.0)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Forestry Division", "r2_url": "https://files.environmentdashboard.org/raw/9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27.zst", "sha256": "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27", "source_id": "fao-fra-2025", "title": "Global Forest Resources Assessment 2025", "url_download": "https://openknowledge.fao.org/server/api/core/bitstreams/12322cae-5b20-4be2-927a-72a86fd319e9/content", "url_main": "https://fra-data.fao.org/assessments/fra/2025/WO/home/overview", "version_producer": "FRA 2025 platform, downloaded 2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read FRA_Years_2026-10-05.csv from the FRA 2025 platform's bulk download (all countries and areas). The vintage is the download date in the member names, 2026-10-05; the platform has no other version label.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "Kept 1a_forestArea (forest area, thousand hectares, as printed) and its flag for 236 countries and areas and the six reporting years 1990, 2000, 2010, 2015, 2020, 2025. Flags: A \"Normal value, official data reported by country/area\" (194 countries and areas); I \"Imputed value, desk study, data compiled by FAO\" (42 countries and areas); each country's values name their flag in a note.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "Matched each country and area by its ISO 3 code; French Guiana, Mayotte, Réunion and Svalbard and Jan Mayen Islands, which FRA reports separately, are published as their own entities.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "World = the sum of the forest area of all 236 countries and areas in the file for each year (exact decimal arithmetic), as FAO computes its global figure.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "For comparison only, the WORLD row of the report's Table 5 (PDF page 35, published 2025-10-21), in thousand ha: 1990: report 4 343 534, here 4 343 534.45; 2000: report 4 236 587, here 4 236 589.39; 2010: report 4 201 001, here 4 200 995.20; 2015: report 4 181 435, here 4 181 439.67; 2020: report 4 165 241, here 4 165 289.00; 2025: report 4 140 217, here 4 140 443.71. The two differ slightly; the platform data can include country revisions made after the report was published.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FRA definition of forest: land spanning more than 0.5 ha with trees higher than 5 m and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ, not predominantly under agricultural or urban land use. A land-use definition reported by countries (official data, or FAO desk studies where a country did not report), not satellite tree cover.",
          "bunkers": null,
          "geography": "Countries and areas reporting to FRA 2025, and the world (sum of all 236)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["fao-fra-2025"],
      "time_basis": "calendar",
      "title": "Forest area",
      "unit": {
        "code": "kha",
        "label": "thousand hectares",
        "short": "thousand ha"
      },
      "vintage": "FRA 2025 platform, downloaded 2026-10-05"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAF", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "8dd0171499d681739ad85f3813d180a68a831144843ba804c2e5ca172ad054d5",
      "geo_coverage": "mixed",
      "id": "forest.fao-fra-2025.net-change",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2020/2025",
        "status": "final",
        "value": -4969.058
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2026. Global Forest Resources Assessment. https://fra-data.fao.org. Accessed on: 2026-10-04. Licence: CC-BY-4.0. Global estimates: FAO. 2025. Global Forest Resources Assessment 2025. Rome. https://doi.org/10.4060/cd6709en Changes: annual net change calculated from forest area; world total calculated as the sum of all countries and areas.",
        "description": "How much the area of forest grew or shrank each year, on average, in each country and in the world over 1990–2000, 2000–2010, 2010–2015, 2015–2020 and 2020–2025: new forest from planting and natural expansion minus forest lost to deforestation, in thousands of hectares a year, from FAO's Global Forest Resources Assessment 2025. Negative values are net loss.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use; report CC BY 4.0)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "This adaptation was not created by the Food and Agriculture Organization of the United Nations (FAO). FAO is not responsible for the content or accuracy of this adaptation. The original English edition shall be the authoritative edition.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "bulk-download-world", "bytes": 1377159, "citation_full": "FAO. 2025. Global Forest Resources Assessment 2025. Rome. https://doi.org/10.4060/cd6709en. FAO. 2026. Global Forest Resources Assessment. https://fra-data.fao.org. Accessed on: 2026-10-04", "date_accessed": "2026-10-04", "date_published": "2025-10-21", "doi": "10.4060/cd6709en", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use; report CC BY 4.0)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Forestry Division", "r2_url": "https://files.environmentdashboard.org/raw/cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c.zst", "sha256": "cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "source_id": "fao-fra-2025", "title": "Global Forest Resources Assessment 2025", "url_download": "https://fra-data.fao.org/api/file/bulk-download?assessmentName=fra&cycleName=2025&countryIso=WO", "url_main": "https://fra-data.fao.org/assessments/fra/2025/WO/home/overview", "version_producer": "FRA 2025 platform, downloaded 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "report-2025", "bytes": 8585230, "citation_full": "FAO. 2025. Global Forest Resources Assessment 2025. Rome. https://doi.org/10.4060/cd6709en. FAO. 2026. Global Forest Resources Assessment. https://fra-data.fao.org. Accessed on: 2026-10-04", "date_accessed": "2026-10-04", "date_published": "2025-10-21", "doi": "10.4060/cd6709en", "etag": "\"bfcf1b18a9f5360baa693fcd6a04029e\"", "last_modified": "Tue, 21 Oct 2025 06:30:26 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use; report CC BY 4.0)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Forestry Division", "r2_url": "https://files.environmentdashboard.org/raw/9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27.zst", "sha256": "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27", "source_id": "fao-fra-2025", "title": "Global Forest Resources Assessment 2025", "url_download": "https://openknowledge.fao.org/server/api/core/bitstreams/12322cae-5b20-4be2-927a-72a86fd319e9/content", "url_main": "https://fra-data.fao.org/assessments/fra/2025/WO/home/overview", "version_producer": "FRA 2025 platform, downloaded 2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read FRA_Years_2026-10-05.csv from the FRA 2025 platform's bulk download (all countries and areas). The vintage is the download date in the member names, 2026-10-05; the platform has no other version label.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "Kept 1a_forestArea (forest area, thousand hectares, as printed) and its flag for 236 countries and areas and the six reporting years 1990, 2000, 2010, 2015, 2020, 2025. Flags: A \"Normal value, official data reported by country/area\" (194 countries and areas); I \"Imputed value, desk study, data compiled by FAO\" (42 countries and areas); each country's values name their flag in a note.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "Matched each country and area by its ISO 3 code; French Guiana, Mayotte, Réunion and Svalbard and Jan Mayen Islands, which FRA reports separately, are published as their own entities.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "World = the sum of the forest area of all 236 countries and areas in the file for each year (exact decimal arithmetic), as FAO computes its global figure.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "Annual net change for each interval between reporting years = (forest area at the end − forest area at the start) / the number of years, in thousand hectares per year (exact decimal arithmetic); negative values are net loss. The report defines forest area net change the same way, as the difference in forest area between two points in time.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          },
          {
            "description": "For comparison only, the WORLD row of the report's Table 6 (PDF page 36) gives the annual net change as −10 695 thousand ha a year for 1990–2000 (here −10 694.51) and −4 122 for 2015–2025 (from the platform data used here, −4 099.60; that 10-year interval is published here as 2015–2020 and 2020–2025). The platform data can include country revisions made after the report was published.",
            "inputs": ["cd12ea6ef902e1fc9f9dc07f834eb2e29b95791aa38f060fec9f1e67d11c010c", "9b77d433587bec0c6882a3f9e06c96ad6eb33ffe823bfe910e4f6a418cc68d27"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/fra_2025.py",
            "transform_sha256": "effd975216c5bb9a8f729157555998b988e975fb2e933289855c8c89e5e03904"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FRA definition of forest: land spanning more than 0.5 ha with trees higher than 5 m and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ, not predominantly under agricultural or urban land use. A land-use definition reported by countries (official data, or FAO desk studies where a country did not report), not satellite tree cover. Net change = (forest area at the end of the interval − at its start) / years in the interval. Net change is not deforestation: gains elsewhere offset part of the forest lost.",
          "bunkers": null,
          "geography": "Countries and areas reporting to FRA 2025, and the world (sum of all 236)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["fao-fra-2025"],
      "time_basis": "calendar",
      "title": "Annual net change in forest area",
      "unit": {
        "code": "kha-per-year",
        "label": "thousand hectares per year",
        "short": "thousand ha/yr"
      },
      "vintage": "FRA 2025 platform, downloaded 2026-10-05"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["ABW", "AGO", "ARG", "ATG", "AUS", "BDI", "BEN", "BES", "BGD", "BHS", "BLZ", "BOL", "BRA", "BRN", "BTN", "CAF", "CHN", "CIV", "CMR", "COD", "COG", "COL", "CRI", "CUB", "CYM", "DMA", "DOM", "ECU", "ETH", "FJI", "GAB", "GHA", "GIN", "GLP", "GMB", "GNB", "GNQ", "GTM", "GUF", "GUY", "HND", "HTI", "IDN", "IND", "JAM", "KEN", "KHM", "KNA", "LAO", "LBR", "LCA", "LKA", "MAF", "MDG", "MDV", "MEX", "MMR", "MOZ", "MSR", "MTQ", "MWI", "MYS", "NGA", "NIC", "NPL", "PAN", "PER", "PHL", "PLW", "PNG", "PRI", "PRY", "RWA", "SEN", "SGP", "SLB", "SLE", "SLV", "SSD", "SUR", "SXM", "TCA", "TGO", "THA", "TTO", "TWN", "TZA", "UGA", "UMI", "USA", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "2871c260b88c1f4e969d89cc7750a69ce7cc5c6865b1f29ecb060362dec83e60",
      "geo_coverage": "mixed",
      "id": "forest.gfw.primary-forest-loss",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 4286331.282172469
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Hansen/UMD/Google/USGS/NASA (Global Forest Change v1.13), accessed through Global Nature Watch (WRI table gadm__tcl__iso_change v20260424) on 2026-10-05. Tree cover loss due to fire: UMD/GLAD (Tyukavina et al. 2022). Tree cover loss by dominant driver: WRI/Google DeepMind (Sims et al. 2025). Primary humid tropical forest: Turubanova et al. (2018). CC BY 4.0. Changes: Summed WRI's country table by country and year at a tree canopy cover in 2000 of at least 30 percent; world totals of primary forest loss and of loss by driver summed by Environment Dashboard.",
        "description": "Hectares of tree cover lost each year since 2001 inside the humid tropical primary forest that stood in 2001: mature natural forest that had not been cleared and regrown in recent history, mapped by the University of Maryland.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "loss-global-annual", "bytes": 1620, "citation_full": "Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C. M. Slay, D. Purves, and N. Harris. 2025. \"Global Drivers of Forest Loss at 1 Km Resolution.\" Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1126/science.1244693", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "University of Maryland GLAD lab with Google, USGS and NASA; tabulated and served by World Resources Institute", "r2_url": "https://files.environmentdashboard.org/raw/79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e.zst", "sha256": "79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "source_id": "gfw-tree-cover-loss", "title": "Tree cover loss, Global Forest Change v1.13 (via Global Nature Watch)", "url_download": "https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%2C%20SUM%28umd_tree_cover_loss_from_fires__ha%29%20AS%20umd_tree_cover_loss_from_fires__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20umd_tree_cover_loss__year%20ORDER%20BY%20umd_tree_cover_loss__year", "url_main": "https://globalnaturewatch.org/dashboards/global/", "version_producer": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "loss-primary-forest-country-annual", "bytes": 79567, "citation_full": "Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C. M. Slay, D. Purves, and N. Harris. 2025. \"Global Drivers of Forest Loss at 1 Km Resolution.\" Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1126/science.1244693", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "University of Maryland GLAD lab with Google, USGS and NASA; tabulated and served by World Resources Institute", "r2_url": "https://files.environmentdashboard.org/raw/ddb6c3ad59a6e7b84bd718059effd180490b745b58c70ae5d4a6cb1d1a23d37a.zst", "sha256": "ddb6c3ad59a6e7b84bd718059effd180490b745b58c70ae5d4a6cb1d1a23d37a", "source_id": "gfw-tree-cover-loss", "title": "Tree cover loss, Global Forest Change v1.13 (via Global Nature Watch)", "url_download": "https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20iso%2C%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20AND%20is__umd_regional_primary_forest_2001%20%3D%20true%20GROUP%20BY%20iso%2C%20umd_tree_cover_loss__year%20ORDER%20BY%20iso%2C%20umd_tree_cover_loss__year", "url_main": "https://globalnaturewatch.org/dashboards/global/", "version_producer": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read loss-primary-forest-country-annual: WRI's table gadm__tcl__iso_change v20260424 queried through the Global Forest Watch Data API with the SQL in the file's URL (https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20iso%2C%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20AND%20is__umd_regional_primary_forest_2001%20%3D%20true%20GROUP%20BY%20iso%2C%20umd_tree_cover_loss__year%20ORDER%20BY%20iso%2C%20umd_tree_cover_loss__year), at a tree canopy cover in 2000 of at least 30 percent. Hectares as in the file, not rounded.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "ddb6c3ad59a6e7b84bd718059effd180490b745b58c70ae5d4a6cb1d1a23d37a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "A country and year with no row in the file has no loss recorded for it; nothing is filled in.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "ddb6c3ad59a6e7b84bd718059effd180490b745b58c70ae5d4a6cb1d1a23d37a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "World: the sum of every row of the file by year, including the codes left out below.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "ddb6c3ad59a6e7b84bd718059effd180490b745b58c70ae5d4a6cb1d1a23d37a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "Not published as countries: GADM codes with no entity in our table (Z07 97,129 ha, all years together). Their loss is included in the world totals.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "ddb6c3ad59a6e7b84bd718059effd180490b745b58c70ae5d4a6cb1d1a23d37a"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Tree cover loss: stand-replacing disturbance, or the complete removal of tree cover canopy, of vegetation taller than 5 m, mapped each year from Landsat at 30 m (Hansen/UMD, Global Forest Change v1.13), where tree canopy cover was at least 30 percent in 2000. Loss is not deforestation: it includes plantation harvest, fire and natural disturbance, and regrowth is not subtracted. Method changes from 2011 and 2015 make early and late years less comparable. Primary forest: the 2001 extent of humid tropical primary forest (Turubanova et al. 2018); loss outside the humid tropics is not counted.",
          "bunkers": null,
          "geography": "Countries and territories (GADM's country codes, mapped to ISO 3166-1) and the world, which also includes areas GADM codes separately (XAD, Z01, Z06, Z07). Only countries with humid tropical primary forest have rows.",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["gfw-tree-cover-loss"],
      "time_basis": "calendar",
      "title": "Humid tropical primary forest lost each year",
      "unit": {
        "code": "ha",
        "label": "hectares",
        "short": "ha"
      },
      "vintage": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALA", "ALB", "AND", "ARE", "ARG", "ARM", "ATF", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CYM", "CYN", "CYP", "CZE", "DEU", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GTM", "GUF", "GUY", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KNA", "KOR", "KOS", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAF", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TTO", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "UMI", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "354def24e25bd44ead8400f48712639c3ba21bc1b72aee15f42b0c63cb8af003",
      "geo_coverage": "mixed",
      "id": "forest.gfw.tree-cover-loss",
      "latest": {
        "age_bp": null,
        "dims": {
          "part": "all"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 25528555.50870127
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Hansen/UMD/Google/USGS/NASA (Global Forest Change v1.13), accessed through Global Nature Watch (WRI table gadm__tcl__iso_change v20260424) on 2026-10-05. Tree cover loss due to fire: UMD/GLAD (Tyukavina et al. 2022). Tree cover loss by dominant driver: WRI/Google DeepMind (Sims et al. 2025). Primary humid tropical forest: Turubanova et al. (2018). CC BY 4.0. Changes: Summed WRI's country table by country and year at a tree canopy cover in 2000 of at least 30 percent; world totals of primary forest loss and of loss by driver summed by Environment Dashboard.",
        "description": "Hectares of tree cover lost each year since 2001, worldwide and in each country, and how much of it was lost to fire, mapped from Landsat satellites by the University of Maryland and tabulated by World Resources Institute for Global Forest Watch.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "loss-global-annual", "bytes": 1620, "citation_full": "Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C. M. Slay, D. Purves, and N. Harris. 2025. \"Global Drivers of Forest Loss at 1 Km Resolution.\" Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1126/science.1244693", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "University of Maryland GLAD lab with Google, USGS and NASA; tabulated and served by World Resources Institute", "r2_url": "https://files.environmentdashboard.org/raw/79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e.zst", "sha256": "79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "source_id": "gfw-tree-cover-loss", "title": "Tree cover loss, Global Forest Change v1.13 (via Global Nature Watch)", "url_download": "https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%2C%20SUM%28umd_tree_cover_loss_from_fires__ha%29%20AS%20umd_tree_cover_loss_from_fires__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20umd_tree_cover_loss__year%20ORDER%20BY%20umd_tree_cover_loss__year", "url_main": "https://globalnaturewatch.org/dashboards/global/", "version_producer": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "loss-country-annual", "bytes": 273719, "citation_full": "Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C. M. Slay, D. Purves, and N. Harris. 2025. \"Global Drivers of Forest Loss at 1 Km Resolution.\" Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1126/science.1244693", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "University of Maryland GLAD lab with Google, USGS and NASA; tabulated and served by World Resources Institute", "r2_url": "https://files.environmentdashboard.org/raw/d2356e4f4d7ae8edc5830cf84fc5bafc7c69a53a144157751ef507201a210bd1.zst", "sha256": "d2356e4f4d7ae8edc5830cf84fc5bafc7c69a53a144157751ef507201a210bd1", "source_id": "gfw-tree-cover-loss", "title": "Tree cover loss, Global Forest Change v1.13 (via Global Nature Watch)", "url_download": "https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20iso%2C%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%2C%20SUM%28umd_tree_cover_loss_from_fires__ha%29%20AS%20umd_tree_cover_loss_from_fires__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20iso%2C%20umd_tree_cover_loss__year%20ORDER%20BY%20iso%2C%20umd_tree_cover_loss__year", "url_main": "https://globalnaturewatch.org/dashboards/global/", "version_producer": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read loss-country-annual: WRI's table gadm__tcl__iso_change v20260424 queried through the Global Forest Watch Data API with the SQL in the file's URL (https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20iso%2C%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%2C%20SUM%28umd_tree_cover_loss_from_fires__ha%29%20AS%20umd_tree_cover_loss_from_fires__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20iso%2C%20umd_tree_cover_loss__year%20ORDER%20BY%20iso%2C%20umd_tree_cover_loss__year), at a tree canopy cover in 2000 of at least 30 percent. Hectares as in the file, not rounded.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "d2356e4f4d7ae8edc5830cf84fc5bafc7c69a53a144157751ef507201a210bd1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "A country and year with no row in the file has no loss recorded for it; nothing is filled in.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "d2356e4f4d7ae8edc5830cf84fc5bafc7c69a53a144157751ef507201a210bd1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "World: read loss-global-annual (the same query without the country grouping), 2001–2025. Checked that the countries, with the codes left out below, add up to it exactly in every year, for all loss and for loss due to fire.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "d2356e4f4d7ae8edc5830cf84fc5bafc7c69a53a144157751ef507201a210bd1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "Not published as countries: GADM codes with no entity in our table (XAD 80 ha; Z01 4,365 ha; Z06 555 ha; Z07 164,532 ha, all years together). Their loss is included in the world totals.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "d2356e4f4d7ae8edc5830cf84fc5bafc7c69a53a144157751ef507201a210bd1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Tree cover loss: stand-replacing disturbance, or the complete removal of tree cover canopy, of vegetation taller than 5 m, mapped each year from Landsat at 30 m (Hansen/UMD, Global Forest Change v1.13), where tree canopy cover was at least 30 percent in 2000. Loss is not deforestation: it includes plantation harvest, fire and natural disturbance, and regrowth is not subtracted. Method changes from 2011 and 2015 make early and late years less comparable. Loss due to fire: UMD/GLAD (Tyukavina et al. 2022), a part of all loss.",
          "bunkers": null,
          "geography": "Countries and territories (GADM's country codes, mapped to ISO 3166-1) and the world, which also includes areas GADM codes separately (XAD, Z01, Z06, Z07).",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["gfw-tree-cover-loss"],
      "time_basis": "calendar",
      "title": "Tree cover lost each year, and the part due to fire",
      "unit": {
        "code": "ha",
        "label": "hectares",
        "short": "ha"
      },
      "vintage": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALA", "ALB", "AND", "ARE", "ARG", "ARM", "ATF", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CYM", "CYN", "CYP", "CZE", "DEU", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GTM", "GUF", "GUY", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KNA", "KOR", "KOS", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAF", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TTO", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "UMI", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "2c3f598d51fd42b153319e26e9a10daa13d0671ba7b82cddfe1621c1c35cf022",
      "geo_coverage": "mixed",
      "id": "forest.gfw.tree-cover-loss-by-driver",
      "latest": {
        "age_bp": null,
        "dims": {
          "driver": "permanent-agriculture"
        },
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 5728093.192951432
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Hansen/UMD/Google/USGS/NASA (Global Forest Change v1.13), accessed through Global Nature Watch (WRI table gadm__tcl__iso_change v20260424) on 2026-10-05. Tree cover loss due to fire: UMD/GLAD (Tyukavina et al. 2022). Tree cover loss by dominant driver: WRI/Google DeepMind (Sims et al. 2025). Primary humid tropical forest: Turubanova et al. (2018). CC BY 4.0. Changes: Summed WRI's country table by country and year at a tree canopy cover in 2000 of at least 30 percent; world totals of primary forest loss and of loss by driver summed by Environment Dashboard.",
        "description": "Hectares of tree cover lost each year since 2001, worldwide and in each country, split by the dominant driver of loss in each square kilometre: permanent agriculture, mining and energy, shifting cultivation, logging, wildfire, settlements and infrastructure, other natural disturbances, or unknown (WRI and Google DeepMind).",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "loss-global-annual", "bytes": 1620, "citation_full": "Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C. M. Slay, D. Purves, and N. Harris. 2025. \"Global Drivers of Forest Loss at 1 Km Resolution.\" Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1126/science.1244693", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "University of Maryland GLAD lab with Google, USGS and NASA; tabulated and served by World Resources Institute", "r2_url": "https://files.environmentdashboard.org/raw/79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e.zst", "sha256": "79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "source_id": "gfw-tree-cover-loss", "title": "Tree cover loss, Global Forest Change v1.13 (via Global Nature Watch)", "url_download": "https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%2C%20SUM%28umd_tree_cover_loss_from_fires__ha%29%20AS%20umd_tree_cover_loss_from_fires__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20umd_tree_cover_loss__year%20ORDER%20BY%20umd_tree_cover_loss__year", "url_main": "https://globalnaturewatch.org/dashboards/global/", "version_producer": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "loss-drivers-country-annual", "bytes": 1703978, "citation_full": "Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Sims, M.J., R. Stanimirova, A. Raichuk, M. Neumann, J. Richter, F. Follett, J. MacCarthy, K. Lister, C. Randle, L. Sloat, E. Esipova, J. Jupiter, C. Stanton, D. Morris, C. M. Slay, D. Purves, and N. Harris. 2025. \"Global Drivers of Forest Loss at 1 Km Resolution.\" Environmental Research Letters 20 (7): 074027. doi:10.1088/1748-9326/add606.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1126/science.1244693", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "University of Maryland GLAD lab with Google, USGS and NASA; tabulated and served by World Resources Institute", "r2_url": "https://files.environmentdashboard.org/raw/2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63.zst", "sha256": "2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63", "source_id": "gfw-tree-cover-loss", "title": "Tree cover loss, Global Forest Change v1.13 (via Global Nature Watch)", "url_download": "https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20iso%2C%20wri_google_tree_cover_loss_drivers__driver%2C%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20iso%2C%20wri_google_tree_cover_loss_drivers__driver%2C%20umd_tree_cover_loss__year%20ORDER%20BY%20iso%2C%20wri_google_tree_cover_loss_drivers__driver%2C%20umd_tree_cover_loss__year", "url_main": "https://globalnaturewatch.org/dashboards/global/", "version_producer": "GFC-2025-v1.13, WRI table gadm__tcl__iso_change v20260424", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read loss-drivers-country-annual: WRI's table gadm__tcl__iso_change v20260424 queried through the Global Forest Watch Data API with the SQL in the file's URL (https://data-api.globalforestwatch.org/dataset/gadm__tcl__iso_change/v20260424/download/csv?sql=SELECT%20iso%2C%20wri_google_tree_cover_loss_drivers__driver%2C%20umd_tree_cover_loss__year%2C%20SUM%28umd_tree_cover_loss__ha%29%20AS%20umd_tree_cover_loss__ha%20FROM%20data%20WHERE%20umd_tree_cover_density_2000__threshold%20%3D%2030%20GROUP%20BY%20iso%2C%20wri_google_tree_cover_loss_drivers__driver%2C%20umd_tree_cover_loss__year%20ORDER%20BY%20iso%2C%20wri_google_tree_cover_loss_drivers__driver%2C%20umd_tree_cover_loss__year), at a tree canopy cover in 2000 of at least 30 percent. Hectares as in the file, not rounded.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "A country and year with no row in the file has no loss recorded for it; nothing is filled in.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "Driver classes as WRI names them; \"Hard commodities\" is labelled \"Mining and energy (hard commodities)\" and \"Settlements & Infrastructure\" \"Settlements and infrastructure\". Each 1 km cell's loss is assigned to its one dominant driver (WRI/Google DeepMind, Sims et al. 2025).",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "World: the sum of every row of the file by year and driver, including the codes left out below. Checked that the drivers add up to loss-global-annual in every year, to within 0.01 ha.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
            "transform_sha256": "15a82e1f48690b7a720c6627c6ebe816d1ad424d54de3633a13ab1e900bc7ed0"
          },
          {
            "description": "Not published as countries: GADM codes with no entity in our table (XAD 80 ha; Z01 4,365 ha; Z06 555 ha; Z07 164,532 ha, all years together). Their loss is included in the world totals.",
            "inputs": ["79b791bcb241093320fc0e6297babf3c468e58027c31dc8213c328f68c46053e", "2e9dfe9bb94ea744f5f4178fe292ffacc0173caf50609cd1f9981106374a6c63"],
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            "script": "pipeline/src/envdash/transforms/nature/gfw_tree_cover_loss.py",
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          "geography": "Countries and territories (GADM's country codes, mapped to ISO 3166-1) and the world, which also includes areas GADM codes separately (XAD, Z01, Z06, Z07).",
          "gwp": null,
          "lulucf": null
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      },
      "source_ids": ["gfw-tree-cover-loss"],
      "time_basis": "calendar",
      "title": "Tree cover lost each year, by what drove it",
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        "label": "hectares",
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        "attribution": "© European Union 2026. EDGAR Community GHG Database version EDGAR_2026_GHG (2026), European Commission, Joint Research Centre (JRC) and International Energy Agency (IEA), comprising IEA-EDGAR CO2, EDGAR CH4, EDGAR N2O and EDGAR F-gases. IEA-EDGAR CO2 includes or is based on data from IEA (2025) Greenhouse Gas Emissions from Energy, www.iea.org/data-and-statistics, as modified by the Joint Research Centre, licensed CC BY-NC-ND 4.0; other EDGAR material CC BY 4.0. Crippa et al., GHG emissions of all world countries - 2026 Report, doi:10.2760/7717504. https://edgar.jrc.ec.europa.eu/report_2026 and https://edgar.jrc.ec.europa.eu/dataset_ghg2026.",
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        },
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      "title": "Share of each gas in world greenhouse gas emissions, 2025 (EDGAR)",
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        "attribution": "© European Union 2026. EDGAR Community GHG Database version EDGAR_2026_GHG (2026), European Commission, Joint Research Centre (JRC) and International Energy Agency (IEA), comprising IEA-EDGAR CO2, EDGAR CH4, EDGAR N2O and EDGAR F-gases. IEA-EDGAR CO2 includes or is based on data from IEA (2025) Greenhouse Gas Emissions from Energy, www.iea.org/data-and-statistics, as modified by the Joint Research Centre, licensed CC BY-NC-ND 4.0; other EDGAR material CC BY 4.0. Crippa et al., GHG emissions of all world countries - 2026 Report, doi:10.2760/7717504. https://edgar.jrc.ec.europa.eu/report_2026 and https://edgar.jrc.ec.europa.eu/dataset_ghg2026.",
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        "kind": "series",
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            "description": "Read the sheet 'GHG_per_capita_by_country' of EDGAR_2026_GHG_booklet_2026.xlsx (sha256 bb77a0da5735…): one row per country or aggregate, one column per year 1970–2025, in tonnes of CO₂-equivalent per person per year (t CO2eq/cap/yr) as the workbook's info sheet states. Each value is published exactly as stored in its cell: nothing is rounded, added up, divided or converted, because the licence of the fossil CO₂ part (IEA-EDGAR CO2, CC BY-NC-ND 4.0) allows no derivatives.",
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          {
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          {"acquisition": "automatic", "artifact_id": "report-pdf", "bytes": 6465096, "citation_full": "Crippa, M., Guizzardi, D., Pagani, F., Banja, M., Ciarlantini, S., Muntean, M., Amici, L., Luini, C., Honavar Melo Pires, R., Quadrelli, R., Carvalho, P., Ruiz Ponsoda, D., Andrews, S., Köykkä, J., Grassi, G., Rossi, S., Melo, J., Branco, A., Suárez-Moreno, M., Sedano, F., Manca, G., Pisoni, E., Pekar, F., GHG emissions of all world countries - 2026 Report, Publications Office of the European Union, Luxembourg, 2026, doi:10.2760/7717504, JRC147815.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.2760/7717504", "etag": null, "last_modified": "Wed, 09 Sep 2026 07:27:37 GMT", "licence": {"name": "CC BY-NC-ND 4.0 for IEA-EDGAR CO2 and every total that includes it; CC BY 4.0 for EU-owned EDGAR CH4, N2O and F-gases", "spdx": "CC-BY-NC-ND-4.0", "url": "https://creativecommons.org/licenses/by-nc-nd/4.0/"}, "producer": "European Commission, Joint Research Centre (JRC), with the International Energy Agency (IEA) for fossil CO2", "r2_url": null, "sha256": "4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667", "source_id": "edgar-2026-ghg", "title": "EDGAR 2026: greenhouse gas emissions of all world countries", "url_download": "https://edgar.jrc.ec.europa.eu/booklet/GHG_emissions_of_all_world_countries_booklet_2026report.pdf", "url_main": "https://edgar.jrc.ec.europa.eu/report_2026", "version_producer": "EDGAR_2026_GHG", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read from Annex 5, World profile, table of changes by sector, printed page 73 (PDF page 75) of the report, in the text of page 75 of the PDF snapshot (sha256 4e5712706aed…): the columns '2025 vs 1990', '2025 vs 2005' and '2025 vs 2024' for seven sectors and all sectors, exactly as labelled in SECTORS. Each value is the whole percentage printed, including where the report prints a change that rounds to zero.",
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            "script": "pipeline/src/envdash/transforms/emissions/edgar_2026.py",
            "transform_sha256": "e917da7000ab67e89cace025c312093abbec3a5085dc787840c21b7008c936c1"
          },
          {
            "description": "Sectors are the report's: 'Industrial Combustion and Processes' is one row in this table. The changes are in world emissions excluding land use, land-use change and forestry (page 11), including international shipping and aviation (page 74).",
            "inputs": ["4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/edgar_2026.py",
            "transform_sha256": "e917da7000ab67e89cace025c312093abbec3a5085dc787840c21b7008c936c1"
          },
          {
            "description": "Marked preliminary: 2025 is a Fast-Track year (page 50).",
            "inputs": ["4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/edgar_2026.py",
            "transform_sha256": "e917da7000ab67e89cace025c312093abbec3a5085dc787840c21b7008c936c1"
          }
        ],
        "published_value": {
          "document": "edgar-2026-ghg",
          "locator": "Annex 5, World profile, table of changes by sector, printed page 73 (PDF page 75)",
          "quote": null
        },
        "scope": {
          "baseline": "The same sector's emissions in 1990, 2005 or 2024",
          "basis": "CO₂ (fossil only: fuels and industrial processes), CH₄, N₂O and F-gases, added up with IPCC AR5 100-year global warming potentials. Sectors as defined in the report; international aviation and shipping are counted in transport.",
          "bunkers": "included",
          "geography": "World",
          "gwp": "AR5-GWP100",
          "lulucf": "excluded"
        }
      },
      "source_ids": ["edgar-2026-ghg"],
      "time_basis": "calendar",
      "title": "Change in world greenhouse gas emissions by sector (EDGAR)",
      "unit": {
        "code": "percent",
        "label": "percent change",
        "short": "%"
      },
      "vintage": "EDGAR_2026_GHG"
    },
    {
      "display": {
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      },
      "downloadable": false,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "ARE", "ARG", "ARM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FLK", "FRA", "FRO", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "INTL_AIR", "INTL_SEA", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MKD", "MLI", "MLT", "MMR", "MNG", "MOZ", "MRT", "MTQ", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB_MNE", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "48ad7b777d995834e97489b1fd2927a7c29ec5d3ac16c1249a79c87e15a2f1a1",
      "geo_coverage": "mixed",
      "id": "ghg.edgar-2026.total-by-country",
      "latest": null,
      "licence_class": "no-derivatives",
      "provenance": {
        "attribution": "© European Union 2026. EDGAR Community GHG Database version EDGAR_2026_GHG (2026), European Commission, Joint Research Centre (JRC) and International Energy Agency (IEA), comprising IEA-EDGAR CO2, EDGAR CH4, EDGAR N2O and EDGAR F-gases. IEA-EDGAR CO2 includes or is based on data from IEA (2025) Greenhouse Gas Emissions from Energy, www.iea.org/data-and-statistics, as modified by the Joint Research Centre, licensed CC BY-NC-ND 4.0; other EDGAR material CC BY 4.0. Crippa et al., GHG emissions of all world countries - 2026 Report, doi:10.2760/7717504. https://edgar.jrc.ec.europa.eu/report_2026 and https://edgar.jrc.ec.europa.eu/dataset_ghg2026.",
        "description": "Greenhouse gases released each year since 1970 by every country, by international aviation and shipping, by the EU27 and by the world, in carbon dioxide equivalent, as published in EDGAR 2026. Land use, land-use change and forestry are not included. Values for 2024 and 2025 are EDGAR's Fast-Track estimates and will be revised.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-ND 4.0 for IEA-EDGAR CO2 and every total that includes it; CC BY 4.0 for EU-owned EDGAR CH4, N2O and F-gases",
          "spdx": "CC-BY-NC-ND-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-nd/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "ghg-booklet", "bytes": 4767596, "citation_full": "Crippa, M., Guizzardi, D., Pagani, F., Banja, M., Ciarlantini, S., Muntean, M., Amici, L., Luini, C., Honavar Melo Pires, R., Quadrelli, R., Carvalho, P., Ruiz Ponsoda, D., Andrews, S., Köykkä, J., Grassi, G., Rossi, S., Melo, J., Branco, A., Suárez-Moreno, M., Sedano, F., Manca, G., Pisoni, E., Pekar, F., GHG emissions of all world countries - 2026 Report, Publications Office of the European Union, Luxembourg, 2026, doi:10.2760/7717504, JRC147815.", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.2760/7717504", "etag": null, "last_modified": "Thu, 03 Sep 2026 11:58:34 GMT", "licence": {"name": "CC BY-NC-ND 4.0 for IEA-EDGAR CO2 and every total that includes it; CC BY 4.0 for EU-owned EDGAR CH4, N2O and F-gases", "spdx": "CC-BY-NC-ND-4.0", "url": "https://creativecommons.org/licenses/by-nc-nd/4.0/"}, "producer": "European Commission, Joint Research Centre (JRC), with the International Energy Agency (IEA) for fossil CO2", "r2_url": null, "sha256": "bb77a0da5735925b3a6a64be63dade9e71b57174d5ec6c7eff872274df00f88c", "source_id": "edgar-2026-ghg", "title": "EDGAR 2026: greenhouse gas emissions of all world countries", "url_download": "https://edgar.jrc.ec.europa.eu/booklet/EDGAR_2026_GHG_booklet_2026.xlsx", "url_main": "https://edgar.jrc.ec.europa.eu/report_2026", "version_producer": "EDGAR_2026_GHG", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "report-pdf", "bytes": 6465096, "citation_full": "Crippa, M., Guizzardi, D., Pagani, F., Banja, M., Ciarlantini, S., Muntean, M., Amici, L., Luini, C., Honavar Melo Pires, R., Quadrelli, R., Carvalho, P., Ruiz Ponsoda, D., Andrews, S., Köykkä, J., Grassi, G., Rossi, S., Melo, J., Branco, A., Suárez-Moreno, M., Sedano, F., Manca, G., Pisoni, E., Pekar, F., GHG emissions of all world countries - 2026 Report, Publications Office of the European Union, Luxembourg, 2026, doi:10.2760/7717504, JRC147815.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.2760/7717504", "etag": null, "last_modified": "Wed, 09 Sep 2026 07:27:37 GMT", "licence": {"name": "CC BY-NC-ND 4.0 for IEA-EDGAR CO2 and every total that includes it; CC BY 4.0 for EU-owned EDGAR CH4, N2O and F-gases", "spdx": "CC-BY-NC-ND-4.0", "url": "https://creativecommons.org/licenses/by-nc-nd/4.0/"}, "producer": "European Commission, Joint Research Centre (JRC), with the International Energy Agency (IEA) for fossil CO2", "r2_url": null, "sha256": "4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667", "source_id": "edgar-2026-ghg", "title": "EDGAR 2026: greenhouse gas emissions of all world countries", "url_download": "https://edgar.jrc.ec.europa.eu/booklet/GHG_emissions_of_all_world_countries_booklet_2026report.pdf", "url_main": "https://edgar.jrc.ec.europa.eu/report_2026", "version_producer": "EDGAR_2026_GHG", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the sheet 'GHG_totals_by_country' of EDGAR_2026_GHG_booklet_2026.xlsx (sha256 bb77a0da5735…): one row per country or aggregate, one column per year 1970–2025, in million tonnes of CO₂-equivalent per year (Mt CO2eq/yr) as the workbook's info sheet states. Each value is published exactly as stored in its cell: nothing is rounded, added up, divided or converted, because the licence of the fossil CO₂ part (IEA-EDGAR CO2, CC BY-NC-ND 4.0) allows no derivatives.",
            "inputs": ["bb77a0da5735925b3a6a64be63dade9e71b57174d5ec6c7eff872274df00f88c", "4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/edgar_2026.py",
            "transform_sha256": "e917da7000ab67e89cace025c312093abbec3a5085dc787840c21b7008c936c1"
          },
          {
            "description": "Matched EDGAR's codes to ours: ISO 3166-1 alpha-3 codes directly, except GLOBAL TOTAL \"GLOBAL TOTAL\" is WLD, EU27 \"EU27\" is EU27, AIR \"International Aviation\" is INTL_AIR, SEA \"International Shipping\" is INTL_SEA, ANT \"Curaçao\" is CUW, SCG \"Serbia and Montenegro\" is SRB_MNE (ANT is the old code of the Netherlands Antilles; EDGAR names the row Curaçao, here and on its report profile; SCG is one row for Serbia and Montenegro together). Rows that cover a country together with a neighbour (CHE \"Switzerland and Liechtenstein\", ESP \"Spain and Andorra\", FRA \"France and Monaco\", ISR \"Israel and Palestine, State of\", ITA \"Italy, San Marino and the Holy See\", SDN \"Sudan and South Sudan\") are published under the code EDGAR gives them, with EDGAR's row name as a note on every value.",
            "inputs": ["bb77a0da5735925b3a6a64be63dade9e71b57174d5ec6c7eff872274df00f88c", "4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/edgar_2026.py",
            "transform_sha256": "e917da7000ab67e89cace025c312093abbec3a5085dc787840c21b7008c936c1"
          },
          {
            "description": "Checked against the report PDF (sha256 4e5712706aed…): the totals exclude land use, land-use change and forestry (page 11: 'The latest EDGAR estimates indicate that global GHG emissions (excluding LULUCF) reached a new record high of 54.1 Gt CO₂eq in 2025'), and the world total includes international shipping and aviation (page 74: 'Global totals for all countries, including international shipping and aviation').",
            "inputs": ["bb77a0da5735925b3a6a64be63dade9e71b57174d5ec6c7eff872274df00f88c", "4e5712706aed4b9384cd7ffb71c17299b2777644a1b5240539fc6e931418c667"],
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          },
          {
            "description": "Values for 2024 and 2025 are marked preliminary, because the report says (page 50) 'the emissions for the Fast-Track years (2024-2025) reported in this booklet will be updated in subsequent editions of this booklet'.",
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            "transform_sha256": "e917da7000ab67e89cace025c312093abbec3a5085dc787840c21b7008c936c1"
          }
        ],
        "published_value": null,
        "scope": {
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          "basis": "CO₂ (fossil only: fuels and industrial processes), CH₄, N₂O and F-gases, added up with IPCC AR5 100-year global warming potentials. Country values exclude international aviation and shipping, which are their own entities; the world total includes them. Some rows cover a country together with a neighbour, as noted on their values.",
          "bunkers": "included",
          "geography": "Every country EDGAR reports, international aviation and shipping, the EU27 and the world",
          "gwp": "AR5-GWP100",
          "lulucf": "excluded"
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      },
      "source_ids": ["edgar-2026-ghg"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions by country (EDGAR)",
      "unit": {
        "code": "MtCO2e/yr",
        "label": "million tonnes of carbon dioxide equivalent per year",
        "short": "Mt CO₂e/yr"
      },
      "vintage": "EDGAR_2026_GHG"
    },
    {
      "display": {
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      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHI", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "69a6dcec2ce1082abd29bd6dd7d19a15c9473d98afb4f8ae367ae368e0291c78",
      "geo_coverage": "mixed",
      "id": "ghg.faostat.by-gas",
      "latest": {
        "age_bp": null,
        "dims": {
          "gas": "co2"
        },
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 38.2742946684
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions from Gütschow, J., Busch, D. & Pflüger, M. (2025), The PRIMAP-hist national historical emissions time series (1750-2024) v2.7, doi:10.5281/zenodo.17090760, licensed CC BY-NC-SA 4.0; method in Gütschow et al. (2016), Earth System Science Data 8, 571-603, doi:10.5194/essd-8-571-2016. Changes: converted from kilotonnes to billion tonnes of CO₂-equivalent.",
        "description": "Each year's emissions from all sectors, including net land use and excluding international aviation and shipping, split by gas: carbon dioxide, methane, nitrous oxide and fluorinated gases, each in carbon dioxide equivalent (carbon dioxide counts as itself), as published by FAO for the world and each country since 1990. The four gases add up to the all-gas total. Carbon dioxide includes the net carbon dioxide of land use, land-use change and forestry, so it can be below zero for a country whose forests take up more carbon than it emits. Where FAO publishes no fluorinated-gas row (67 countries and territories in the October 2025 release) the gas is left missing, never set to zero.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "FAOSTAT's energy, industrial processes, waste and other emissions, and every total, share or per-person value that includes them, are PRIMAP-hist v2.7 data (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values from this source are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/#data/GT", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/#data/GT", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's Emissions totals (GT) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept the \"FAO TIER 1\" rows of item \"All sectors with LULUCF\" (code 6825) for the elements \"Emissions (CO2)\" (7273), \"Emissions (CO2eq) from CH4 (AR5)\" (724413), \"Emissions (CO2eq) from N2O (AR5)\" (724313), \"Emissions (CO2eq) from F-gases (AR5)\" (717815), in kilotonnes. Carbon dioxide is in kilotonnes of CO₂, which is its own CO₂-equivalent (global warming potential 1); the other three are FAO's CO₂-equivalents at IPCC AR5 100-year global warming potentials (methane 28, nitrous oxide 265).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Checked in every area and year that the four gases present add up to element \"Emissions (CO2eq) (AR5)\" (code 723113) of the same item within 0.001 kt; the transform stops otherwise.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Carbon dioxide includes the net carbon dioxide of land use, land-use change and forestry. 535 published carbon dioxide values are below zero, in 37 areas (ASM, BDI, BEN, BIH, BLR, BMU, BTN, CRI, CYM, ESH, FIN, FJI, GEO, GHA, GLP, HND, HTI, LAO, LCA, LVA, MNE, MNP, MSR, MTQ, NCL, NPL, PRI, PSE, PYF, REU, RWA, SDN, SUR, URY, VIR, VNM, WLF), where land use, land-use change and forestry takes up more carbon than the other emissions counted add up to; the lowest is LAO 2001 (-62024.0466 kt as printed). Published as printed.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "FAO publishes no row for some parts of some areas' all-sector totals. Those parts are left missing, never filled or set to zero, and the published total of those areas is the sum of the parts that exist. ABW, AIA, ASM, ATG, BHS, BMU, BRB, BTN, CHI, COK, COM, CYM, DJI, ESH, FLK, FRO, GIB, GLP, GMB, GRL, GUF, GUM, HTI, IMN, KIR, KNA, LAO, LBR, MAC, MSR, MTQ, MYT, NCL, NFK, NIU, NRU, PCN, PNG, PRI, PSE, PYF, REU, SHN, SJM, SLE, SPM, SWZ, SYC, TCA, TKL, TLS, TON, TUV, TZA, UGA, VCT, VGB, VIR, VUT, WLF: no Fluorinated gases (element 717815) (1990–2023). FSM, MHL, MNP, PLW: no Fluorinated gases (element 717815) (1991–2023). ERI, ETH: no Fluorinated gases (element 717815) (1993–2023). KGZ: no Fluorinated gases (element 717815) (1992–2023).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Converted kilotonnes to billion tonnes by dividing by 1,000,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Carbon dioxide is in tonnes of CO₂, its own CO₂-equivalent (global warming potential 1); methane, nitrous oxide and fluorinated gases are FAO's CO₂-equivalents at IPCC AR5 100-year global warming potentials (methane 28, nitrous oxide 265). The total split is FAOSTAT's six IPCC sectors: energy, industrial processes and product use, agriculture, land use, land-use change and forestry (net: emissions from deforestation, drained organic soils and fires minus the carbon taken up by existing forests, so it can be negative), waste and other. International aviation and shipping (bunker fuels) are not included. Agriculture and land use are FAO's own Tier 1 estimates; energy, industry, waste and other are PRIMAP-hist v2.7 third-party estimates, which count some territories inside their parent country (for example Bermuda in the United Kingdom, Greenland and the Faroe Islands in Denmark, Palestine in Israel, Puerto Rico in the United States). So such a parent country's energy, industry, waste and other emissions include those territories while its agriculture and land use do not, and for 28 territories in the October 2025 release FAO has no energy, industry, waste or other rows, so their total covers agriculture and land use only. Estimates, not country inventory submissions.",
          "bunkers": "excluded",
          "geography": "The world, countries and territories, and the European Union (27)",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat-all-sectors"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions by gas, all sectors including land use",
      "unit": {
        "code": "GtCO2e",
        "label": "billion tonnes of carbon dioxide equivalent",
        "short": "Gt CO₂e"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHI", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "a138cc2ebc868397d6ef60af22e03e11a13210d30b51ffca29ec7b41d7bdea8c",
      "geo_coverage": "mixed",
      "id": "ghg.faostat.by-sector",
      "latest": {
        "age_bp": null,
        "dims": {
          "sector": "energy"
        },
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 38.7879500023
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions from Gütschow, J., Busch, D. & Pflüger, M. (2025), The PRIMAP-hist national historical emissions time series (1750-2024) v2.7, doi:10.5281/zenodo.17090760, licensed CC BY-NC-SA 4.0; method in Gütschow et al. (2016), Earth System Science Data 8, 571-603, doi:10.5194/essd-8-571-2016. Changes: converted from kilotonnes to billion tonnes of CO₂-equivalent.",
        "description": "Each year's emissions of all greenhouse gases, in carbon dioxide equivalent, split into six sectors that do not overlap and add up to the total: energy, industrial processes and product use, agriculture, land use (net, which can be below zero where forests take up more carbon than land clearing releases), waste and other, as published by FAO for the world and each country since 1990. Food is not a seventh sector: its emissions run across agriculture, land use, energy, industry and waste. Where FAO publishes no row for a sector (28 territories in the October 2025 release, whose energy, industry and waste are counted in their parent country; Tokelau, Nauru and Tuvalu in part) the sector is left missing, never set to zero, so for those 28 territories the total is agriculture plus land use only. For 10 of them (American Samoa, the Channel Islands, Gibraltar, Greenland, Guam, the Northern Mariana Islands, Norfolk Island, Pitcairn, Svalbard and Jan Mayen, and Saint Pierre and Miquelon) FAO prints agriculture, land use and the total as exactly 0 in some or all years, where it has no estimate. These territories' values are not comparable with countries'. International aviation and shipping are not included.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "FAOSTAT's energy, industrial processes, waste and other emissions, and every total, share or per-person value that includes them, are PRIMAP-hist v2.7 data (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values from this source are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/#data/GT", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/#data/GT", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's Emissions totals (GT) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept the \"FAO TIER 1\" rows of element \"Emissions (CO2eq) (AR5)\" (code 723113) for the six IPCC sector items \"Energy\" (6821), \"IPPU\" (6817), \"IPCC Agriculture\" (1711), \"LULUCF\" (1707), \"Waste\" (6818), \"Other\" (6819), in kilotonnes of CO₂-equivalent (IPCC AR5 100-year global warming potentials). Rows from FAO's \"UNFCCC\" source and the memo item \"International bunkers\" (6820) are not used.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept each sector's values for the years in which FAO publishes the area's \"All sectors with LULUCF\" total (item 6825; 1990–2023 for the World), so the sectors of every published year make up a published total. 25,259 sector values of area-years without a total are left out, all from 1961–1989, before FAO's land-use and all-sector series begin.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Checked in every area and year that the sectors present add up to \"All sectors with LULUCF\" within 0.001 kt (the rounding of the printed values); the transform stops otherwise.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "FAO publishes no row for some parts of some areas' all-sector totals. Those parts are left missing, never filled or set to zero, and the published total of those areas is the sum of the parts that exist. ASM, BMU, CHI, CYM, ESH, FLK, FRO, GIB, GLP, GRL, GUF, GUM, IMN, MSR, MTQ, MYT, NCL, NFK, PCN, PRI, PSE, PYF, REU, SJM, SPM, VIR, WLF: no Energy (item 6821 \"Energy\") (1990–2023); Industrial processes and product use (item 6817 \"IPPU\") (1990–2023); Waste (item 6818 \"Waste\") (1990–2023); Other (item 6819 \"Other\") (1990–2023). NRU, TUV: no Other (item 6819 \"Other\") (1990–2023). MNP: no Energy (item 6821 \"Energy\") (1991–2023); Industrial processes and product use (item 6817 \"IPPU\") (1991–2023); Waste (item 6818 \"Waste\") (1991–2023); Other (item 6819 \"Other\") (1991–2023). TKL: no Energy (item 6821 \"Energy\") (1990–2023); Other (item 6819 \"Other\") (1990–2023).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "FAO prints a \"All sectors with LULUCF\" total of exactly 0 kt, with every sector it prints for that area and year also 0, for 275 area-years of 10 territories: ASM 1990–2000, 2011–2023; CHI 1990–2023; GIB 2001–2023; GRL 1996–2001; GUM 1990–2010, 2016–2023; MNP 1991–2010, 2016–2023; NFK 1990–2023; PCN 1990–2023; SJM 1990–2023; SPM 1990–2015, 2021–2023. They are published as printed, not removed. Their totals cover agriculture and land use only, and a 0 there is where FAO has no estimate, so these values are not comparable with countries' totals.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Converted kilotonnes to billion tonnes by dividing by 1,000,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT's six IPCC sectors: energy, industrial processes and product use, agriculture, land use, land-use change and forestry (net: emissions from deforestation, drained organic soils and fires minus the carbon taken up by existing forests, so it can be negative), waste and other. International aviation and shipping (bunker fuels) are not included. Agriculture and land use are FAO's own Tier 1 estimates; energy, industry, waste and other are PRIMAP-hist v2.7 third-party estimates, which count some territories inside their parent country (for example Bermuda in the United Kingdom, Greenland and the Faroe Islands in Denmark, Palestine in Israel, Puerto Rico in the United States). So such a parent country's energy, industry, waste and other emissions include those territories while its agriculture and land use do not, and for 28 territories in the October 2025 release FAO has no energy, industry, waste or other rows, so their total covers agriculture and land use only. Estimates, not country inventory submissions.",
          "bunkers": "excluded",
          "geography": "The world, countries and territories, and the European Union (27)",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat-all-sectors"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions by sector, all gases including land use",
      "unit": {
        "code": "GtCO2e",
        "label": "billion tonnes of carbon dioxide equivalent",
        "short": "Gt CO₂e"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "ARE", "ARG", "ARM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FRA", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MUS", "MWI", "MYS", "MYT", "NAM", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "QAT", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "0ed9ade913b997bd84b3d6c0a642a905ab3fe78d9a01bbb50b8f530d774dfd81",
      "geo_coverage": "mixed",
      "id": "ghg.faostat.ch4-share-by-sector",
      "latest": {
        "age_bp": null,
        "dims": {
          "sector": "agriculture"
        },
        "entity": "WLD",
        "period": "2023",
        "status": "final",
        "value": 43.52
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions from Gütschow, J., Busch, D. & Pflüger, M. (2025), The PRIMAP-hist national historical emissions time series (1750-2024) v2.7, doi:10.5281/zenodo.17090760, licensed CC BY-NC-SA 4.0; method in Gütschow et al. (2016), Earth System Science Data 8, 571-603, doi:10.5194/essd-8-571-2016.",
        "description": "Each sector's methane emissions as a percentage of all methane emitted by the world or a country in a year, since 1990, as published by FAO, for the six sectors that make up FAO's total: energy (fossil fuel production and use), industrial processes and product use, agriculture (livestock, rice, manure), land use (fires), waste and other. Where FAO publishes all six, they add up to 100. Food systems' methane runs across several of these sectors.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "FAOSTAT's energy, industrial processes, waste and other emissions, and every total, share or per-person value that includes them, are PRIMAP-hist v2.7 data (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values from this source are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-indicators", "bytes": 4655416, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "\"09064d9dbb13662b004da75f13044915\"", "last_modified": "Wed, 29 Oct 2025 11:06:06 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34.zst", "sha256": "d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/Climate_change_Emissions_indicators_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/#data/EM", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/#data/EM", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Climate_change_Emissions_indicators_E_All_Data_(Normalized).csv from FAOSTAT's Emissions indicators (EM) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 678,370, the number of data rows in this file. The zip was last modified on the server on Wed, 29 Oct 2025 11:06:06 GMT.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept the rows of element \"Emissions Share (CH4)\" (code 7265), unit \"%\", for the six IPCC sector items \"Energy\" (6821), \"IPPU\" (6817), \"IPCC Agriculture\" (1711), \"LULUCF\" (1707), \"Waste\" (6818), \"Other\" (6819), 1990–2023, as FAO prints them: each sector's methane as a percentage of the area's methane from all sectors (item \"All sectors with LULUCF\"). Nothing is computed here.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Checked that the six shares add up to 100 within 0.03 (the rounding of values printed to 0.01) in each of the 1,398 area-years where FAO publishes all six; the transform stops otherwise.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "FAO publishes no row for some parts of some areas' methane splits. Those parts are left missing, never filled or set to zero, and a sector without a share is one for which FAOSTAT's emissions totals (GT) have no methane row for that area and year, so it is not part of the whole. ARE, ARG, AUT, BGD, BHR, BRA, BRN, BTN, CAN, CIV, CYP, DNK, DOM, EGY, FRA, GAB, GBR, GIN, GNQ, GRC, GTM, HKG, IDN, IRL, IRN, IRQ, ISL, ISR, ITA, JAM, JPN, KOR, KWT, LBN, LBY, LCA, MAC, MAR, MDV, MEX, MLT, MMR, MRT, MYS, NGA, NOR, OMN, PAK, PAN, PER, PHL, PRK, PRY, QAT, RWA, SAU, STP, SWE, THA, TTO, TUN, TUR, TWN, URY, VEN, VNM, ZAF, ZMB, ZWE: no Other (item 6819) (1990–2023). ABW, AGO, AIA, ATG, BEN, BFA, BHS, BLZ, BOL, BRB, BWA, CAF, CMR, COD, COG, COK, COM, CPV, CRI, DJI, DMA, FJI, GHA, GMB, GNB, HND, JOR, KEN, KHM, KIR, KNA, LAO, LBR, LKA, LSO, MDG, MLI, MNG, MOZ, MWI, NAM, NER, NIC, NIU, NPL, NRU, PNG, SEN, SHN, SLE, SLV, SOM, SUR, SWZ, SYC, SYR, TCA, TCD, TGO, TLS, TON, TZA, UGA, VCT, VGB, VUT, YEM: no Industrial processes and product use (item 6817) (1990–2023); Other (item 6819) (1990–2023). BIH, EST, GEO, KAZ, LVA, MDA, RUS, SVN, TJK, TKM, UZB: no Other (item 6819) (1992–2023). ERI, ETH: no Industrial processes and product use (item 6817) (1993–2023); Other (item 6819) (1993–2023). SDN, SSD: no Industrial processes and product use (item 6817) (2012–2023); Other (item 6819) (2012–2023). TKL, TUV: no Energy (item 6821) (1990–2023); Industrial processes and product use (item 6817) (1990–2023); Other (item 6819) (1990–2023). CZE: no Other (item 6819) (1993–2023). FSM: no Energy (item 6821) (1991–2023); Industrial processes and product use (item 6817) (1991–2023); Other (item 6819) (1991–2023). HTI: no Industrial processes and product use (item 6817) (1990–2023). KGZ: no Industrial processes and product use (item 6817) (1992–2023); Other (item 6819) (1992–2023). LUX: no Other (item 6819) (2000–2023). MYT: no Energy (item 6821) (1990–1999); Industrial processes and product use (item 6817) (1990–1999); Waste (item 6818) (1990–1999); Other (item 6819) (1990–1999). PLW: no Industrial processes and product use (item 6817) (1991–2023); Other (item 6819) (1991–2023). SRB: no Other (item 6819) (2006–2023).",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Published as printed, although the shares FAO publishes for these areas and years add up to a little less or more than 100 beyond the rounding of their printed values (the sum in brackets): NIU 2001 (99.77), 2008 (99.78), 2010 (99.78), 2012 (99.78), 2014 (99.79), 2022 (99.8), 2023 (99.8).",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
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            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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        ],
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        "scope": {
          "baseline": null,
          "basis": "FAO's published shares (FAOSTAT Emissions indicators, element \"Emissions Share (CH4)\") of methane by mass, so no global warming potential is involved. The whole is FAO's all-sector methane (\"All sectors with LULUCF\"). FAOSTAT's six IPCC sectors: energy, industrial processes and product use, agriculture, land use, land-use change and forestry (for methane, fires in forests and in organic (peat) soils; forests take up carbon dioxide, not methane, so nothing is subtracted and the share is never below zero), waste and other. International aviation and shipping (bunker fuels) are not included. Agriculture and land use are FAO's own Tier 1 estimates; energy, industry, waste and other are PRIMAP-hist v2.7 third-party estimates, which count some territories inside their parent country (for example Bermuda in the United Kingdom, Greenland and the Faroe Islands in Denmark, Palestine in Israel, Puerto Rico in the United States). So such a parent country's energy, industry, waste and other emissions include those territories while its agriculture and land use do not, and for 28 territories in the October 2025 release FAO has no energy, industry, waste or other rows, so their total covers agriculture and land use only. Estimates, not country inventory submissions.",
          "bunkers": "excluded",
          "geography": "The world, countries and territories, and the European Union (27)",
          "gwp": null,
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat-all-sectors"],
      "time_basis": "calendar",
      "title": "Where methane comes from: each sector's share of all methane emissions",
      "unit": {
        "code": "percent",
        "label": "percent of all methane emissions",
        "short": "%"
      },
      "vintage": "2025-10-28"
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    {
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        "attribution": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions from Gütschow, J., Busch, D. & Pflüger, M. (2025), The PRIMAP-hist national historical emissions time series (1750-2024) v2.7, doi:10.5281/zenodo.17090760, licensed CC BY-NC-SA 4.0; method in Gütschow et al. (2016), Earth System Science Data 8, 571-603, doi:10.5194/essd-8-571-2016.",
        "description": "Each country's emissions of all greenhouse gases from all sectors on its territory, including net land use and excluding international aviation and shipping, divided by its population, in tonnes of carbon dioxide equivalent per person per year, as published by FAO since 1990. This is a national average where emissions happen, not one person's footprint: it does not follow what people buy (emissions in imported goods count where they are made) and says nothing about how emissions differ between people in a country. FAO has no row for some sectors of four territories (October 2025 release), so their values leave those sectors out: Mayotte has no energy, industry, waste or other emissions, Tokelau no energy or other, and Nauru and Tuvalu no other. Values can be below zero where forests take up more carbon than the country emits: 94 of the values in the October 2025 release are.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)",
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        },
        "notice": "FAOSTAT's energy, industrial processes, waste and other emissions, and every total, share or per-person value that includes them, are PRIMAP-hist v2.7 data (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values from this source are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-indicators", "bytes": 4655416, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "\"09064d9dbb13662b004da75f13044915\"", "last_modified": "Wed, 29 Oct 2025 11:06:06 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34.zst", "sha256": "d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/Climate_change_Emissions_indicators_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/#data/EM", "version_producer": "2025-10-28", "wayback_url": null},
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        ],
        "processing": [
          {
            "description": "Read Climate_change_Emissions_indicators_E_All_Data_(Normalized).csv from FAOSTAT's Emissions indicators (EM) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 678,370, the number of data rows in this file. The zip was last modified on the server on Wed, 29 Oct 2025 11:06:06 GMT.",
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            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept the rows of item \"All sectors with LULUCF\" (code 6825), element \"Emissions per capita\" (code 7279), unit \"t CO2eq/cap\", 1990–2023, as FAO prints them. FAO divides each area's all-sector emissions by its population; nothing is computed here.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          },
          {
            "description": "94 published per-person values are below zero, in 11 areas (BIH, BLR, BTN, FJI, GHA, HND, LAO, LCA, LVA, MNE, RWA), where land use, land-use change and forestry takes up more carbon than the other emissions counted add up to; the lowest is LAO 2001 (-9.66 t CO2eq/cap as printed). Published as printed.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
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            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d48bf98589ccfd3ffc2aae314091088d3a989cb58d3f149fdc26856178d6da34", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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        "scope": {
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          "basis": "FAO's published value of all-sector emissions (FAOSTAT item \"All sectors with LULUCF\") divided by population, territorial (production-based) accounting. FAOSTAT's six IPCC sectors: energy, industrial processes and product use, agriculture, land use, land-use change and forestry (net: emissions from deforestation, drained organic soils and fires minus the carbon taken up by existing forests, so it can be negative), waste and other. International aviation and shipping (bunker fuels) are not included. Agriculture and land use are FAO's own Tier 1 estimates; energy, industry, waste and other are PRIMAP-hist v2.7 third-party estimates, which count some territories inside their parent country (for example Bermuda in the United Kingdom, Greenland and the Faroe Islands in Denmark, Palestine in Israel, Puerto Rico in the United States). So such a parent country's energy, industry, waste and other emissions include those territories while its agriculture and land use do not, and for 28 territories in the October 2025 release FAO has no energy, industry, waste or other rows, so their total covers agriculture and land use only. Estimates, not country inventory submissions.",
          "bunkers": "excluded",
          "geography": "The world, countries and territories, and the European Union (27)",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
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      },
      "source_ids": ["faostat-all-sectors"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions per person: each country's emissions divided by its population",
      "unit": {
        "code": "tCO2e-per-person",
        "label": "tonnes of carbon dioxide equivalent per person",
        "short": "t CO₂e per person"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
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      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHI", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FLK", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SRB_MNE", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "c542011d01641e5a6876126476ae3d853391878dce9c092876292d3ff974d496",
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      "latest": {
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      "provenance": {
        "attribution": "Calculated by Environment Dashboard from FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions from Gütschow, J., Busch, D. & Pflüger, M. (2025), The PRIMAP-hist national historical emissions time series (1750-2024) v2.7, doi:10.5281/zenodo.17090760, licensed CC BY-NC-SA 4.0; method in Gütschow et al. (2016), Earth System Science Data 8, 571-603, doi:10.5194/essd-8-571-2016. Changes: converted from kilotonnes to billion tonnes of CO₂-equivalent.",
        "description": "Each year's emissions of all greenhouse gases (carbon dioxide, methane, nitrous oxide and fluorinated gases) from all sectors, in carbon dioxide equivalent, including net land use, land-use change and forestry and excluding international aviation and shipping, as published by FAO for the world and each country since 1990. For 28 territories in the October 2025 release, whose energy, industry and waste emissions are counted in their parent country, the total is agriculture plus land use only, and for 10 of them (American Samoa, the Channel Islands, Gibraltar, Greenland, Guam, the Northern Mariana Islands, Norfolk Island, Pitcairn, Svalbard and Jan Mayen, and Saint Pierre and Miquelon) FAO prints a total of exactly 0 in some or all years, where it has no estimate. These territories' values are not comparable with countries'.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)",
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          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "FAOSTAT's energy, industrial processes, waste and other emissions, and every total, share or per-person value that includes them, are PRIMAP-hist v2.7 data (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values from this source are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "emissions-totals", "bytes": 20501708, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-04", "date_published": "2025-10-28", "doi": null, "etag": "\"99a1f7889c9873df9bdb619a99572a1f-3\"", "last_modified": "Sat, 06 Dec 2025 15:13:44 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9.zst", "sha256": "d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/Emissions_Totals_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/#data/GT", "version_producer": "2025-10-28", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2025. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0. Energy, industrial processes, waste and other emissions: Gütschow, J., Busch, D. & Pflüger, M. (2025). The PRIMAP-hist national historical emissions time series (1750-2024) v2.7. Zenodo. https://doi.org/10.5281/zenodo.17090760 Licence: CC BY-NC-SA 4.0.", "date_accessed": "2026-10-05", "date_published": "2025-10-28", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; FAO labels FAOSTAT CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat-all-sectors", "title": "FAOSTAT greenhouse gas emissions from all sectors (with PRIMAP-hist v2.7)", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/#data/GT", "version_producer": "2025-10-28", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Emissions_Totals_E_All_Data_(Normalized).csv from FAOSTAT's Emissions totals (GT) bulk zip. The vintage is the domain's DateUpdate, 28 October 2025, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 2,500,090, the number of data rows in this file. The zip was last modified on the server on Sat, 06 Dec 2025 15:13:44 GMT.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Kept the \"FAO TIER 1\" rows of item \"All sectors with LULUCF\" (code 6825), element \"Emissions (CO2eq) (AR5)\" (code 723113), 1990–2023, in kilotonnes of CO₂-equivalent (IPCC AR5 100-year global warming potentials). Rows from FAO's \"UNFCCC\" source are not used.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "FAO's total is the sum of its six IPCC sector items (energy, industrial processes and product use, agriculture, net land use, land-use change and forestry, waste, other); international aviation and shipping (\"International bunkers\", item 6820) are outside it. FAO publishes no row for some parts of some areas' all-sector totals. Those parts are left missing, never filled or set to zero, and the published total of those areas is the sum of the parts that exist. ASM, BMU, CHI, CYM, ESH, FLK, FRO, GIB, GLP, GRL, GUF, GUM, IMN, MSR, MTQ, MYT, NCL, NFK, PCN, PRI, PSE, PYF, REU, SJM, SPM, VIR, WLF: no Energy (item 6821) (1990–2023); Industrial processes and product use (item 6817) (1990–2023); Waste (item 6818) (1990–2023); Other (item 6819) (1990–2023). NRU, TUV: no Other (item 6819) (1990–2023). MNP: no Energy (item 6821) (1991–2023); Industrial processes and product use (item 6817) (1991–2023); Waste (item 6818) (1991–2023); Other (item 6819) (1991–2023). TKL: no Energy (item 6821) (1990–2023); Other (item 6819) (1990–2023).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "FAO prints a \"All sectors with LULUCF\" total of exactly 0 kt, with every sector it prints for that area and year also 0, for 275 area-years of 10 territories: ASM 1990–2000, 2011–2023; CHI 1990–2023; GIB 2001–2023; GRL 1996–2001; GUM 1990–2010, 2016–2023; MNP 1991–2010, 2016–2023; NFK 1990–2023; PCN 1990–2023; SJM 1990–2023; SPM 1990–2015, 2021–2023. They are published as printed, not removed. Their totals cover agriculture and land use only, and a 0 there is where FAO has no estimate, so these values are not comparable with countries' totals.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Annex I countries, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Non-Annex I countries, Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Converted kilotonnes to billion tonnes by dividing by 1,000,000 (exact decimal arithmetic on the printed values).",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          },
          {
            "description": "Every value used carries FAO's flag E, which the file's codebook defines as \"Estimated value\".",
            "inputs": ["d2c47e116553711f7c2fd6b62437db511038fd9bd9ec77815fa69ff7a18a89a9", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/faostat_all_sectors.py",
            "transform_sha256": "6289feaf5cb49780699c814a3b44c1c4a8d8a6767c9155bbf923967e71fb295e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT's six IPCC sectors: energy, industrial processes and product use, agriculture, land use, land-use change and forestry (net: emissions from deforestation, drained organic soils and fires minus the carbon taken up by existing forests, so it can be negative), waste and other. International aviation and shipping (bunker fuels) are not included. Agriculture and land use are FAO's own Tier 1 estimates; energy, industry, waste and other are PRIMAP-hist v2.7 third-party estimates, which count some territories inside their parent country (for example Bermuda in the United Kingdom, Greenland and the Faroe Islands in Denmark, Palestine in Israel, Puerto Rico in the United States). So such a parent country's energy, industry, waste and other emissions include those territories while its agriculture and land use do not, and for 28 territories in the October 2025 release FAO has no energy, industry, waste or other rows, so their total covers agriculture and land use only. Estimates, not country inventory submissions.",
          "bunkers": "excluded",
          "geography": "The world, countries and territories, and the European Union (27)",
          "gwp": "AR5-GWP100",
          "lulucf": "included"
        }
      },
      "source_ids": ["faostat-all-sectors"],
      "time_basis": "calendar",
      "title": "Greenhouse gas emissions, all gases and all sectors including land use",
      "unit": {
        "code": "GtCO2e",
        "label": "billion tonnes of carbon dioxide equivalent",
        "short": "Gt CO₂e"
      },
      "vintage": "2025-10-28"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "d97665dbbd9eafaea49626b5bb17b205269f33aff0c271d7343b32a8daed570b",
      "geo_coverage": "global-only",
      "id": "glacier-mass.wgms-amce.annual",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": -408.101
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "WGMS (2026), Annual mass-change estimates for the world's glaciers, version 2026-02-10, doi:10.5904/wgms-amce-2026-02-10; Dussaillant et al. (2025), Earth System Science Data 17, 1977–2006, doi:10.5194/essd-17-1977-2025. CC BY 4.0.",
        "description": "Change in the mass of the world's glaciers in each hydrological year since 1976, from the World Glacier Monitoring Service's annual estimates, with the one-sigma uncertainty. Negative values are a loss of ice.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (WGMS data policy, open access on condition of correct citation)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "amce-2026-02-10", "bytes": 53589520, "citation_full": "WGMS (2026): Annual mass-change estimates for the world's glaciers. Individual glacier time series and gridded data products. Digital media. https://doi.org/10.5904/wgms-amce-2026-02-10 Dussaillant, I., Hugonnet, R., Huss, M., Berthier, E., Bannwart, J., Paul, F., and Zemp, M. (2025): Annual mass change of the world's glaciers from 1976 to 2024 by temporal downscaling of satellite data with in-situ observations. Earth System Science Data 17(5): 1977–2006. https://doi.org/10.5194/essd-17-1977-2025", "date_accessed": "2026-10-05", "date_published": "2026-02-10", "doi": "10.5904/wgms-amce-2026-02-10", "etag": "\"331b610-64b93f5a76d99\"", "last_modified": "Tue, 24 Feb 2026 15:58:33 GMT", "licence": {"name": "CC BY 4.0 (WGMS data policy, open access on condition of correct citation)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "World Glacier Monitoring Service (WGMS), University of Zurich", "r2_url": "https://files.environmentdashboard.org/raw/b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc.zst", "sha256": "b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc", "source_id": "wgms-amce", "title": "Annual mass-change estimates for the world's glaciers (version 2026-02-10)", "url_download": "https://wgms.ch/downloads/wgms-amce-2026-02-10.zip", "url_main": "https://wgms.ch/mass_change_estimates/", "version_producer": "2026-02-10", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read global.csv from wgms-amce-2026-02-10.zip (hydrological years 1976 to 2025) and published the gt column (glacier mass change in Gt) as printed.",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          },
          {
            "description": "Lower and upper are gt minus and plus gt_sigma, which the release README defines as the 1-sigma uncertainty (exact decimal arithmetic).",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          },
          {
            "description": "Checked that gt_cumsum and mmsle_cumsum are the running sums of gt and mmsle (within rounding), and that mmsle has the opposite sign of gt, so that positive mm is a rise in sea level.",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "All glaciers outside the Greenland and Antarctic ice sheets (Randolph Glacier Inventory 6.0 outlines), from satellite elevation changes downscaled to single years with field measurements. Hydrological years, labelled by the year they end: from 1 October in the Northern Hemisphere, 1 April in the Southern Hemisphere and 1 January in the tropics.",
          "bunkers": null,
          "geography": "All glaciers worldwide, excluding the two ice sheets",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["wgms-amce"],
      "time_basis": "calendar",
      "title": "Global glacier mass change each year (WGMS)",
      "unit": {
        "code": "Gt",
        "label": "gigatonnes",
        "short": "Gt"
      },
      "vintage": "2026-02-10"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "256fac312d9a1266c48e994eec402b757f760b768cbc1650b3974f3f7e3d7ee3",
      "geo_coverage": "global-only",
      "id": "glacier-mass.wgms-amce.cumulative",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": -9583.132
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "WGMS (2026), Annual mass-change estimates for the world's glaciers, version 2026-02-10, doi:10.5904/wgms-amce-2026-02-10; Dussaillant et al. (2025), Earth System Science Data 17, 1977–2006, doi:10.5194/essd-17-1977-2025. CC BY 4.0.",
        "description": "Cumulative change in the mass of the world's glaciers since the start of hydrological year 1976 (late 1975), from the World Glacier Monitoring Service's annual estimates, with the one-sigma uncertainty. Negative values are a loss of ice.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (WGMS data policy, open access on condition of correct citation)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "amce-2026-02-10", "bytes": 53589520, "citation_full": "WGMS (2026): Annual mass-change estimates for the world's glaciers. Individual glacier time series and gridded data products. Digital media. https://doi.org/10.5904/wgms-amce-2026-02-10 Dussaillant, I., Hugonnet, R., Huss, M., Berthier, E., Bannwart, J., Paul, F., and Zemp, M. (2025): Annual mass change of the world's glaciers from 1976 to 2024 by temporal downscaling of satellite data with in-situ observations. Earth System Science Data 17(5): 1977–2006. https://doi.org/10.5194/essd-17-1977-2025", "date_accessed": "2026-10-05", "date_published": "2026-02-10", "doi": "10.5904/wgms-amce-2026-02-10", "etag": "\"331b610-64b93f5a76d99\"", "last_modified": "Tue, 24 Feb 2026 15:58:33 GMT", "licence": {"name": "CC BY 4.0 (WGMS data policy, open access on condition of correct citation)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "World Glacier Monitoring Service (WGMS), University of Zurich", "r2_url": "https://files.environmentdashboard.org/raw/b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc.zst", "sha256": "b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc", "source_id": "wgms-amce", "title": "Annual mass-change estimates for the world's glaciers (version 2026-02-10)", "url_download": "https://wgms.ch/downloads/wgms-amce-2026-02-10.zip", "url_main": "https://wgms.ch/mass_change_estimates/", "version_producer": "2026-02-10", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read global.csv from wgms-amce-2026-02-10.zip (hydrological years 1976 to 2025) and published the gt_cumsum column (cumulative glacier mass change in Gt) as printed.",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          },
          {
            "description": "Lower and upper are gt_cumsum minus and plus gt_cumsum_sigma, which the release README defines as the 1-sigma uncertainty (exact decimal arithmetic).",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          },
          {
            "description": "Checked that gt_cumsum and mmsle_cumsum are the running sums of gt and mmsle (within rounding), and that mmsle has the opposite sign of gt, so that positive mm is a rise in sea level.",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Zero at the start of hydrological year 1976 (October 1975 in the Northern Hemisphere, April 1975 in the Southern Hemisphere, January 1976 in the tropics).",
          "basis": "All glaciers outside the Greenland and Antarctic ice sheets (Randolph Glacier Inventory 6.0 outlines), from satellite elevation changes downscaled to single years with field measurements. Hydrological years, labelled by the year they end: from 1 October in the Northern Hemisphere, 1 April in the Southern Hemisphere and 1 January in the tropics.",
          "bunkers": null,
          "geography": "All glaciers worldwide, excluding the two ice sheets",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["wgms-amce"],
      "time_basis": "calendar",
      "title": "Global glacier mass change since 1975 (WGMS)",
      "unit": {
        "code": "Gt",
        "label": "gigatonnes",
        "short": "Gt"
      },
      "vintage": "2026-02-10"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "88c1b689fce8812a2d392c0bf06182df60504b6abbd8ad5f40ad5339a255ca82",
      "geo_coverage": "global-only",
      "id": "gmsl.aviso.monthly",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2026-07",
        "status": "final",
        "value": 111.7744299608096
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      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from the AVISO Global Mean Sea Level Indicator (CNES, CLS), doi:10.24400/527896/AVISO-2025.010; credits EU Copernicus Marine Service/CNES/LEGOS/CLS, https://aviso.altimetry.fr/msl, accessed 2026-10-04. Modified from the original. Licence: AVISO License Agreement Issue 20, https://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso_ini.pdf Changes: monthly means of AVISO's cycle values, re-based to their 1993 mean and converted from metres to millimetres.",
        "description": "How much the global average sea level has risen since 1993, month by month, measured by the reference satellite altimetry missions TOPEX/Poseidon, Jason-1, Jason-2, Jason-3 and Sentinel-6 Michael Freilich. Calculated by Environment Dashboard from AVISO's values about every 10 days: averaged to calendar months and set so that the 1993 average is zero. Seasonal (annual and semi-annual) cycles are removed by AVISO.",
        "kind": "series",
        "licence": {
          "name": "AVISO License Agreement, Issue 20 (custom CC BY-like licence; not CC BY 4.0)",
          "spdx": null,
          "url": "https://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso_ini.pdf"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "msl-global-filter2m-nc", "bytes": 66087, "citation_full": "CNES, & CLS. (2026). AVISO Global Mean Sea Level Indicator [Dataset]. CNES. https://doi.org/10.24400/527896/AVISO-2025.010. Credits: EU Copernicus Marine Service/CNES/LEGOS/CLS, https://aviso.altimetry.fr/msl", "date_accessed": "2026-10-04", "date_published": "2026-09-26", "doi": "10.24400/527896/AVISO-2025.010", "etag": "\"10227-65ce67010d8c2\"", "last_modified": "Sat, 03 Oct 2026 02:30:52 GMT", "licence": {"name": "AVISO License Agreement, Issue 20 (custom CC BY-like licence; not CC BY 4.0)", "spdx": null, "url": "https://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso_ini.pdf"}, "producer": "CNES / AVISO+ (produced with CLS and LEGOS)", "r2_url": null, "sha256": "d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862", "source_id": "aviso-gmsl", "title": "AVISO reference global mean sea level from satellite altimetry", "url_download": "https://data.aviso.altimetry.fr/aviso-gateway/data/indicators/msl/MSL_Serie_MERGED_Global_AVISO_GIA_Adjust_Filter2m.nc", "url_main": "https://www.aviso.altimetry.fr/en/data/products/ocean-indicators-products/mean-sea-level.html", "version_producer": "2026-09-26 (doi:10.24400/527896/AVISO-2025.010)", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the msl variable (global mean sea level anomaly, metres) and the cycle times of MSL_Serie_MERGED_Global_AVISO_GIA_Adjust_Filter2m.nc, created by AVISO on 26 September 2026: 1236 values about 10 days apart from 5 January 1993 to 15 August 2026. Checked the product DOI, zone GLOBAL, the glacial isostatic adjustment correction, the 2-month filter and that annual and semi-annual signals are removed, as the file's attributes state.",
            "inputs": ["d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/aviso_gmsl.py",
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          },
          {
            "description": "Averaged the cycle values dated in each calendar month (arithmetic mean). Of the 403 months published, 9 hold 2, 360 hold 3, 34 hold 4 cycles. The month of the last cycle (2026-08) is not published because the record stops part-way through it.",
            "inputs": ["d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/aviso_gmsl.py",
            "transform_sha256": "e2b1d842e3df28d784b2938a85968ab40fddca0cf3c8317beb95f584d8d794c7"
          },
          {
            "description": "Re-based to the mean of the twelve 1993 monthly values (7.233 mm on AVISO's scale, which has no stated reference period) and converted from metres to millimetres.",
            "inputs": ["d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/aviso_gmsl.py",
            "transform_sha256": "e2b1d842e3df28d784b2938a85968ab40fddca0cf3c8317beb95f584d8d794c7"
          },
          {
            "description": "AVISO's 1-sigma uncertainty envelope is defined for its own cycle values and is not published for these monthly means.",
            "inputs": ["d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/aviso_gmsl.py",
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        ],
        "published_value": null,
        "scope": {
          "baseline": "1993 mean of this series (mean of its twelve 1993 monthly values)",
          "basis": "Satellite altimetry, AVISO reference GMSL product (doi:10.24400/527896/AVISO-2025.010): corrected for glacial isostatic adjustment, annual and semi-annual signals removed, 2-month filter, TOPEX-A drift and Jason-3 radiometer corrections included. Monthly means of the cycle values computed by Environment Dashboard; the month in which the record ends is left out.",
          "bunkers": null,
          "geography": "Global ocean mean between about 66° S and 66° N (the reference missions' coverage)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["aviso-gmsl"],
      "time_basis": "calendar",
      "title": "Global mean sea level change since 1993, monthly (AVISO satellite altimetry)",
      "unit": {
        "code": "mm",
        "label": "millimetres",
        "short": "mm"
      },
      "vintage": "2026-09-26 (doi:10.24400/527896/AVISO-2025.010)"
    },
    {
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      "geo_coverage": "global-only",
      "id": "gmsl.aviso.rate",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "1999/2026",
        "status": "final",
        "value": 3.6
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "AVISO Global Mean Sea Level Indicator (CNES, CLS), doi:10.24400/527896/AVISO-2025.010; credits EU Copernicus Marine Service/CNES/LEGOS/CLS, https://aviso.altimetry.fr/msl, accessed 2026-10-04. Licence: AVISO License Agreement Issue 20, https://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso_ini.pdf",
        "description": "AVISO's stated average rate of global mean sea level rise measured by satellite altimetry from 1999: 3.6 millimetres per year, with a 90% confidence interval of plus or minus 0.3 millimetres per year. AVISO's figure, quoted from its product page, not computed by us.",
        "kind": "published-value",
        "licence": {
          "name": "AVISO License Agreement, Issue 20 (custom CC BY-like licence; not CC BY 4.0)",
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        },
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "msl-product-page", "bytes": 51308, "citation_full": "CNES, & CLS. (2026). AVISO Global Mean Sea Level Indicator [Dataset]. CNES. https://doi.org/10.24400/527896/AVISO-2025.010. Credits: EU Copernicus Marine Service/CNES/LEGOS/CLS, https://aviso.altimetry.fr/msl", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.24400/527896/AVISO-2025.010", "etag": null, "last_modified": null, "licence": {"name": "AVISO License Agreement, Issue 20 (custom CC BY-like licence; not CC BY 4.0)", "spdx": null, "url": "https://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso_ini.pdf"}, "producer": "CNES / AVISO+ (produced with CLS and LEGOS)", "r2_url": null, "sha256": "40fb325e7cac42366fd9b020ffda678f2e7b65fe8f527936d33e06acb3ba236a", "source_id": "aviso-gmsl", "title": "AVISO reference global mean sea level from satellite altimetry", "url_download": "https://www.aviso.altimetry.fr/en/data/products/ocean-indicators-products/mean-sea-level.html", "url_main": "https://www.aviso.altimetry.fr/en/data/products/ocean-indicators-products/mean-sea-level.html", "version_producer": "product page read 2026-10-04", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "msl-global-filter2m-nc", "bytes": 66087, "citation_full": "CNES, & CLS. (2026). AVISO Global Mean Sea Level Indicator [Dataset]. CNES. https://doi.org/10.24400/527896/AVISO-2025.010. Credits: EU Copernicus Marine Service/CNES/LEGOS/CLS, https://aviso.altimetry.fr/msl", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.24400/527896/AVISO-2025.010", "etag": "\"10227-65ce67010d8c2\"", "last_modified": "Sat, 03 Oct 2026 02:30:52 GMT", "licence": {"name": "AVISO License Agreement, Issue 20 (custom CC BY-like licence; not CC BY 4.0)", "spdx": null, "url": "https://www.aviso.altimetry.fr/fileadmin/documents/data/License_Aviso_ini.pdf"}, "producer": "CNES / AVISO+ (produced with CLS and LEGOS)", "r2_url": null, "sha256": "d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862", "source_id": "aviso-gmsl", "title": "AVISO reference global mean sea level from satellite altimetry", "url_download": "https://data.aviso.altimetry.fr/aviso-gateway/data/indicators/msl/MSL_Serie_MERGED_Global_AVISO_GIA_Adjust_Filter2m.nc", "url_main": "https://www.aviso.altimetry.fr/en/data/products/ocean-indicators-products/mean-sea-level.html", "version_producer": "product page read 2026-10-04", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Quoted from AVISO's Mean Sea Level product page, section 'At the global scale'. The quote was found in the visible text of the page snapshot (sha256 40fb325e7cac…) before publishing.",
            "inputs": ["40fb325e7cac42366fd9b020ffda678f2e7b65fe8f527936d33e06acb3ba236a", "d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/aviso_gmsl.py",
            "transform_sha256": "e2b1d842e3df28d784b2938a85968ab40fddca0cf3c8317beb95f584d8d794c7"
          },
          {
            "description": "Value: \"3.6 mm per year (+/-0.3 mm/yr, 90%CI)\" is published as 3.6 millimetres per year with the 90% range 3.3 to 3.9 (the value minus and plus 0.3). The page states the period only as \"from 1999\"; it is published as 1999/2026, 2026 being the year the page was read (4 October 2026). The page carries no date, so the vintage is that reading date.",
            "inputs": ["40fb325e7cac42366fd9b020ffda678f2e7b65fe8f527936d33e06acb3ba236a", "d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
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          },
          {
            "description": "Consistency check (not published): an ordinary least-squares slope through the cycle values from 1 January 1999 of the NetCDF created on 26 September 2026 (sha256 d7a57922352a…, to 15 August 2026) is 3.67 mm per year, inside AVISO's stated 90% range; the build stops if it is not.",
            "inputs": ["40fb325e7cac42366fd9b020ffda678f2e7b65fe8f527936d33e06acb3ba236a", "d7a57922352a1d8f9317e41a43b767ef9b67ec5540d67e52627e67837f9da862"],
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          "document": "aviso-gmsl",
          "locator": "Mean Sea Level product page, section 'At the global scale'",
          "quote": "The average sea level rise rate is 3.6 mm per year (+/-0.3 mm/yr, 90%CI) over the globe and from 1999."
        },
        "scope": {
          "baseline": "None: a rate of change, from 1999",
          "basis": "Average rate over the satellite altimetry record from 1999 as stated by AVISO, with its 90% confidence interval; the page names no end date. The same page notes that the processing of the 1993–1999 part of the record changed in the latest release.",
          "bunkers": null,
          "geography": "Global ocean (AVISO: 'over the globe')",
          "gwp": null,
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        }
      },
      "source_ids": ["aviso-gmsl"],
      "time_basis": "calendar",
      "title": "Average rate of global sea level rise since 1999 (AVISO)",
      "unit": {
        "code": "mm/yr",
        "label": "millimetres per year",
        "short": "mm/yr"
      },
      "vintage": "product page read 2026-10-04"
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      "entities": ["WLD"],
      "export_sha256": "800fd882d1131f5078d3c123aa32bf1208abcf4c42a91fd5cb23a1a7ec3f7347",
      "geo_coverage": "global-only",
      "id": "gmsl.ipcc-ar6.rise-2100-likely",
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      "provenance": {
        "attribution": "IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, pp. 3−32. doi:10.1017/9781009157896.001",
        "description": "The IPCC's assessed likely range of global mean sea level rise by 2100, relative to 1995–2014, under four emissions scenarios from very low (SSP1-1.9) to very high (SSP5-8.5), medium confidence. Quoted from the Summary for Policymakers of the IPCC Sixth Assessment Report, Working Group I (2021), statement B.5.3. The same statement says that a rise approaching 2 metres by 2100 under the very high scenario cannot be ruled out because of deep uncertainty in ice-sheet processes (low confidence); that is outside these ranges.",
        "kind": "published-value",
        "licence": {
          "name": "© IPCC, all rights reserved (personal, non-commercial use; no redistribution or derivative works)",
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          "url": "https://www.ipcc.ch/copyright/"
        },
        "notice": "Quoted from the IPCC report with its statement number and page. IPCC material may not be redistributed or altered; the full report is at https://www.ipcc.ch/report/ar6/wg1/.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "spm-pdf", "bytes": 3361797, "citation_full": "IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.", "date_accessed": "2026-10-05", "date_published": "2021", "doi": "10.1017/9781009157896.001", "etag": "\"334c05-5e19fcc0ce4c0\"", "last_modified": "Fri, 17 Jun 2022 07:35:23 GMT", "licence": {"name": "© IPCC, all rights reserved (personal, non-commercial use; no redistribution or derivative works)", "spdx": null, "url": "https://www.ipcc.ch/copyright/"}, "producer": "Intergovernmental Panel on Climate Change (IPCC), Working Group I", "r2_url": null, "sha256": "37c9fa760757524c8d69630a89cecab9ebcacb66786970a3439da0619875e446", "source_id": "ipcc-ar6-wg1-spm", "title": "Climate Change 2021: The Physical Science Basis. Summary for Policymakers", "url_download": "https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_SPM.pdf", "url_main": "https://www.ipcc.ch/report/ar6/wg1/chapter/summary-for-policymakers/", "version_producer": "AR6 WGI (2021)", "wayback_url": null}
        ],
        "processing": [
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            "description": "Quoted from SPM statement B.5.3, p. 21 of the IPCC AR6 Working Group I Summary for Policymakers. The quote was found in the text of page 21 of the PDF snapshot (sha256 37c9fa760757…) before publishing.",
            "inputs": ["37c9fa760757524c8d69630a89cecab9ebcacb66786970a3439da0619875e446"],
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            "description": "Value: the likely ranges by 2100 relative to 1995–2014, one per scenario, are published as printed, in metres, each end of a range as its own value (bound likely-low or likely-high). The build reads the ranges from the quote's words and stops unless they equal the published table. The SPM gives no central estimate, and none is computed.",
            "inputs": ["37c9fa760757524c8d69630a89cecab9ebcacb66786970a3439da0619875e446"],
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        "published_value": {
          "document": "ipcc-ar6-wg1-spm",
          "locator": "SPM statement B.5.3, p. 21",
          "quote": null
        },
        "scope": {
          "baseline": "1995–2014",
          "basis": "Projections for 2100 under SSP1-1.9, SSP1-2.6, SSP2-4.5 and SSP5-8.5 (SSP3-7.0 is not in the statement). Likely range: assessed probability 66–100% (IPCC calibrated language); medium confidence. Each end of the range is a separate value; the SPM gives no central estimate.",
          "bunkers": null,
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      "source_ids": ["ipcc-ar6-wg1-spm"],
      "time_basis": "calendar",
      "title": "Global sea level rise by 2100 by emissions scenario, likely range (IPCC AR6)",
      "unit": {
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      "geo_coverage": "global-only",
      "id": "heat.lancet-2025.deaths-global",
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        "period": "2021",
        "status": "final",
        "value": 558304.0
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      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Lancet Countdown on Health and Climate Change, 2025 report data: indicator 1.1.1 by A. J. Pershing and J. Giguere (attributable heatwave days) and by F. Tartarini and O. Jay (vulnerable populations); indicator 1.1.3 by C. Freyberg, B. Lemke and M. Otto; indicator 1.1.5 by J. Ballester, X. Basagaña and J. Ruiz-Cabrejos. Romanello et al., The Lancet, 2025, doi:10.1016/S0140-6736(25)01919-1. CC BY-NC-SA 4.0.",
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          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "Licensed CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/): non-commercial use only, and anything built from these figures must be shared under the same licence. These indicators are computed from ERA5 and contain modified Copernicus Climate Change Service information 2025; neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "heat-mortality-1-1-5", "bytes": 137358, "citation_full": "Romanello M, Walawender M, Hsu S-C, et al. The 2025 report of the Lancet Countdown on health and climate change. Lancet 2025; published online Oct 29. https://doi.org/10.1016/S0140-6736(25)01919-1.", "date_accessed": "2026-10-04", "date_published": "2025-10-29", "doi": "10.1016/S0140-6736(25)01919-1", "etag": "\"2188e-6425ae150d7bd\"", "last_modified": "Thu, 30 Oct 2025 07:05:54 GMT", "licence": {"name": "CC BY-NC-SA 4.0", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Lancet Countdown on Health and Climate Change (led by University College London)", "r2_url": "https://files.environmentdashboard.org/raw/f6a18bdec8434973269c095727a13a0375e78b0e674124cf8c9827ec267131e0.zst", "sha256": "f6a18bdec8434973269c095727a13a0375e78b0e674124cf8c9827ec267131e0", "source_id": "lancet-countdown-2025", "title": "Lancet Countdown 2025: heat-related deaths, work hours lost to heat and heatwave exposure", "url_download": "https://lancetcountdown.org/wp-content/uploads/2025/10/Indicator-1.1.5_Data-Download_2025-Lancet-Countdown-Report-1.xlsx", "url_main": "https://lancetcountdown.org/explore-our-data/", "version_producer": "2025 report", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the AN column (number of deaths attributable to heat) of the sheet '2025 Report Data_Global' of the indicator 1.1.5 workbook of the Lancet Countdown 2025 report, one value a year 1990–2021. Values are published as in the workbook.",
            "inputs": ["f6a18bdec8434973269c095727a13a0375e78b0e674124cf8c9827ec267131e0"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          },
          {
            "description": "The workbook's guidance sheet gives the unit of AN as deaths. The share of all deaths (AF) and the regional sheets are not published here.",
            "inputs": ["f6a18bdec8434973269c095727a13a0375e78b0e674124cf8c9827ec267131e0"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Modelled in three stages (Zhao et al. 2021): the association between temperature and mortality estimated in each location, pooled by multilevel meta-regression, and predicted for all countries. Inputs include ERA5 temperatures, UN population data, the World Mortality Dataset and the Global Burden of Disease Study 2021.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["lancet-countdown-2025"],
      "time_basis": "calendar",
      "title": "Heat-related deaths, world",
      "unit": {
        "code": "deaths",
        "label": "deaths",
        "short": "deaths"
      },
      "vintage": "2025 report"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "aa4a09f4c5a1f40458cba1b6b2735c4e2ceec88df291514dda0af0ac992d8442",
      "geo_coverage": "global-only",
      "id": "heat.lancet-2025.heatwave-days-global",
      "latest": {
        "age_bp": null,
        "dims": {
          "scenario": "observed"
        },
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 30.7905888162652
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Lancet Countdown on Health and Climate Change, 2025 report data: indicator 1.1.1 by A. J. Pershing and J. Giguere (attributable heatwave days) and by F. Tartarini and O. Jay (vulnerable populations); indicator 1.1.3 by C. Freyberg, B. Lemke and M. Otto; indicator 1.1.5 by J. Ballester, X. Basagaña and J. Ruiz-Cabrejos. Romanello et al., The Lancet, 2025, doi:10.1016/S0140-6736(25)01919-1. CC BY-NC-SA 4.0.",
        "description": "Heatwave days that people were exposed to on average each year, 2020–2024, as observed, as expected in a modelled climate without human-caused warming, and the difference attributable to climate change, from the Lancet Countdown (indicator 1.1.1).",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "Licensed CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/): non-commercial use only, and anything built from these figures must be shared under the same licence. These indicators are computed from ERA5 and contain modified Copernicus Climate Change Service information 2025; neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "heatwave-days-attributable-1-1-1", "bytes": 205138, "citation_full": "Romanello M, Walawender M, Hsu S-C, et al. The 2025 report of the Lancet Countdown on health and climate change. Lancet 2025; published online Oct 29. https://doi.org/10.1016/S0140-6736(25)01919-1.", "date_accessed": "2026-10-04", "date_published": "2025-10-29", "doi": "10.1016/S0140-6736(25)01919-1", "etag": "\"32152-6425ae06a502f\"", "last_modified": "Thu, 30 Oct 2025 07:05:39 GMT", "licence": {"name": "CC BY-NC-SA 4.0", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Lancet Countdown on Health and Climate Change (led by University College London)", "r2_url": "https://files.environmentdashboard.org/raw/53a22362f5b35c8cf91aa9d6c9f8ce0e7c97ce36f198f0b793ad70437989f632.zst", "sha256": "53a22362f5b35c8cf91aa9d6c9f8ce0e7c97ce36f198f0b793ad70437989f632", "source_id": "lancet-countdown-2025", "title": "Lancet Countdown 2025: heat-related deaths, work hours lost to heat and heatwave exposure", "url_download": "https://lancetcountdown.org/wp-content/uploads/2025/10/Indicator-1.1.1_Attributable_Data-Download_2025-Lancet-Countdown-Report-1.xlsx", "url_main": "https://lancetcountdown.org/explore-our-data/", "version_producer": "2025 report", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the sheet '2025_Report _Data_Global' of the indicator 1.1.1 (attributable heatwave days) workbook of the Lancet Countdown 2025 report, 2020–2024: heatwave days observed, expected without climate change (Counterfactual) and attributable to climate change (Attributable_to_CC), published as in the workbook.",
            "inputs": ["53a22362f5b35c8cf91aa9d6c9f8ce0e7c97ce36f198f0b793ad70437989f632"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          },
          {
            "description": "Checked that observed days equal expected days plus attributable days in every year.",
            "inputs": ["53a22362f5b35c8cf91aa9d6c9f8ce0e7c97ce36f198f0b793ad70437989f632"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "A heatwave is at least two consecutive days when both minimum and maximum temperature exceed the local 1986–2005 95th percentile. Observed days from ERA5; days expected without human-caused warming from 24 paired CMIP6 climate model simulations.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["lancet-countdown-2025"],
      "time_basis": "calendar",
      "title": "Heatwave days per person, observed and attributable to climate change, world",
      "unit": {
        "code": "days",
        "label": "days per person",
        "short": "days"
      },
      "vintage": "2025 report"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "08f29bb8007d1eeaf3a083ff2aeda3cf8b619491e70c378790a66b25c5fdae02",
      "geo_coverage": "global-only",
      "id": "heat.lancet-2025.labour-hours-global",
      "latest": {
        "age_bp": null,
        "dims": {
          "sector": "total"
        },
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 639.85500565
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Lancet Countdown on Health and Climate Change 2025 report data: indicator 1.1.1 by A. J. Pershing and J. Giguere (attributable heatwave days) and by F. Tartarini and O. Jay (vulnerable populations); indicator 1.1.3 by C. Freyberg, B. Lemke and M. Otto; indicator 1.1.5 by J. Ballester, X. Basagaña and J. Ruiz-Cabrejos. Romanello et al., The Lancet, 2025, doi:10.1016/S0140-6736(25)01919-1. CC BY-NC-SA 4.0. Changes: work hours lost converted from thousands of hours to billions of hours.",
        "description": "Working hours that heat stress could have cost each year worldwide, 1990–2024, in services, manufacturing, agriculture and construction, as estimated by the Lancet Countdown (indicator 1.1.3).",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "Licensed CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/): non-commercial use only, and anything built from these figures must be shared under the same licence. These indicators are computed from ERA5 and contain modified Copernicus Climate Change Service information 2025; neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "work-hours-lost-1-1-3", "bytes": 1510290, "citation_full": "Romanello M, Walawender M, Hsu S-C, et al. The 2025 report of the Lancet Countdown on health and climate change. Lancet 2025; published online Oct 29. https://doi.org/10.1016/S0140-6736(25)01919-1.", "date_accessed": "2026-10-04", "date_published": "2025-10-29", "doi": "10.1016/S0140-6736(25)01919-1", "etag": "\"170b92-6425ae0fd29e4\"", "last_modified": "Thu, 30 Oct 2025 07:05:49 GMT", "licence": {"name": "CC BY-NC-SA 4.0", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Lancet Countdown on Health and Climate Change (led by University College London)", "r2_url": "https://files.environmentdashboard.org/raw/36d16d2ba3acb43e333fca86f6873b558f9ea4816ea97c740bb5b85c228413cb.zst", "sha256": "36d16d2ba3acb43e333fca86f6873b558f9ea4816ea97c740bb5b85c228413cb", "source_id": "lancet-countdown-2025", "title": "Lancet Countdown 2025: heat-related deaths, work hours lost to heat and heatwave exposure", "url_download": "https://lancetcountdown.org/wp-content/uploads/2025/10/Indicator-1.1.3_PWHL_Data-Download_2025-Lancet-Countdown-Report_v2-1.xlsx", "url_main": "https://lancetcountdown.org/explore-our-data/", "version_producer": "2025 report", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the sheet '2025 Report Data_Global' of the indicator 1.1.3 workbook of the Lancet Countdown 2025 report, 1990–2024: potential work hours lost in services (WHL200Serv), manufacturing (WHL300Manuf), agriculture (WHL400sunAgr), construction (WHL400sunConstr) and in total (TotalSunAgCon), in thousands of hours as the guidance sheet states.",
            "inputs": ["36d16d2ba3acb43e333fca86f6873b558f9ea4816ea97c740bb5b85c228413cb"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          },
          {
            "description": "Checked that the total equals the sum of the four sectors in every year (to one part in a billion).",
            "inputs": ["36d16d2ba3acb43e333fca86f6873b558f9ea4816ea97c740bb5b85c228413cb"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          },
          {
            "description": "Divided every value by one million to give billions of hours (exact decimal arithmetic on the values as stored in the workbook). Employment and hours lost per worker are not published here.",
            "inputs": ["36d16d2ba3acb43e333fca86f6873b558f9ea4816ea97c740bb5b85c228413cb"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/impacts/lancet_countdown.py",
            "transform_sha256": "fd77ef680e8092050c0cd18a7df087fce266b78940d637009930508e0de3e676"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Potential hours lost: wet bulb globe temperature from ERA5 linked to the metabolic rate of typical work (services 200 W and manufacturing 300 W in shade, agriculture and construction 400 W in the sun), applied to employed people aged 15 and over in each sector. Formal employment only. The producer notes that from 2020 grid cells shared between countries are handled differently, which may show as a step between 2019 and 2020.",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["lancet-countdown-2025"],
      "time_basis": "calendar",
      "title": "Potential work hours lost to heat, world",
      "unit": {
        "code": "bn-hours",
        "label": "billion hours",
        "short": "bn hours"
      },
      "vintage": "2025 report"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATF", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BVT", "BWA", "CAF", "CAN", "CCK", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HMD", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IOT", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAF", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "UMI", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "5a591d3b2a1c1a01513271ebd989f172029b09053cfaaf1cc8ad22756848f0af",
      "geo_coverage": "country",
      "id": "hot-days-35c.wb-cckp.cmip6",
      "latest": {
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        "dims": {
          "scenario": "ssp245"
        },
        "entity": "IND",
        "period": "2040/2059",
        "status": "projection",
        "value": 94.78
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "The World Bank: Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree (doi:10.57966/128g-6s70): Copernicus Climate Change Service ERA5. The World Bank: Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree (doi:10.57966/b54h-7s87): CMIP6 multi-model ensemble (World Climate Research Programme).",
        "description": "The average number of days a year whose maximum temperature reaches 35 °C or more, over each country's area, from the CMIP6 climate models as bias-corrected, downscaled and aggregated by the World Bank's Climate Change Knowledge Portal. 1995–2014 is the models' simulation of the recent past (not observations); 2040–2059 is projected under three emissions scenarios. The value is the median of the models and the range runs from the 10th to the 90th percentile of the models.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 with the World Bank Dataset Terms",
          "spdx": "CC-BY-4.0",
          "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"
        },
        "notice": "Shared under the World Bank Dataset Terms (CC BY 4.0 with additional terms), including their attribution requirement, which passes to anyone who shares these data further: https://www.worldbank.org/ext/en/legal/terms-conditions/datasets",
        "origins": [
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        "description": "Cumulative change in the mass of the Antarctic Ice Sheet each month from January 1979 to December 2023, from the IMBIE team's reconciliation of satellite surveys, with the one-sigma uncertainty. Negative values are a loss of ice.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0",
          "spdx": "OGL-UK-3.0",
          "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
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        ],
        "processing": [
          {
            "description": "Read the 'Cumulative mass balance anomaly (Gt)' column of imbie3_antarctica_Gt_partitioned.csv (IMBIE version 1.0), 1979-01 to 2023-12, as printed.",
            "inputs": ["cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2"],
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            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          },
          {
            "description": "Lower and upper are the value minus and plus the file's 'Cumulative mass balance anomaly uncertainty (Gt)', which the file states is one standard deviation (exact decimal arithmetic).",
            "inputs": ["cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Zero just before January 1979, the start of IMBIE's Antarctic record; the first month's value is that month's change.",
          "basis": "Reconciled from 21 independent satellite estimates (altimetry, gravimetry and the input-output method) by IMBIE 2026; total mass balance, the sum of surface mass balance and ice dynamics.",
          "bunkers": null,
          "geography": "Antarctic Ice Sheet (West and East Antarctica and the Antarctic Peninsula)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["imbie-2026"],
      "time_basis": "calendar",
      "title": "Antarctic Ice Sheet mass change since January 1979 (IMBIE)",
      "unit": {
        "code": "Gt",
        "label": "gigatonnes",
        "short": "Gt"
      },
      "vintage": "1.0"
    },
    {
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      "downloadable": true,
      "entities": ["GRL"],
      "export_sha256": "09f985726ecd17e22ad679454a48cf3f8b052c9d7008eb7ef605b62601b978b3",
      "geo_coverage": "global-only",
      "id": "ice-sheet-mass.imbie-2026.greenland",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "GRL",
        "period": "2023-12",
        "status": "final",
        "value": -6196.145791
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "IMBIE: Otosaka et al. (2026), Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0), NERC EDS UK Polar Data Centre, doi:10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0; Otosaka et al. (2026), Scientific Data 13, 1301, doi:10.1038/s41597-026-08088-0. Contains public sector information licensed under the Open Government Licence v3.0.",
        "description": "Cumulative change in the mass of the Greenland Ice Sheet each month from July 1971 to December 2023, from the IMBIE team's reconciliation of satellite surveys, with the one-sigma uncertainty. Negative values are a loss of ice.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0",
          "spdx": "OGL-UK-3.0",
          "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "greenland-gt", "bytes": 101046, "citation_full": "Otosaka, I., Shepherd, A., Amory, C., Horwath, M., King, M., Nowicki, S., Payne, A., Rignot, E., Sørensen, L., Schlegel, N., Simon, K., Smith, B., Sutterley, T., van den Broeke, M., Velicogna, I., A, G., Agosta, C., Ditmar, P., Döhne, T., … Wouters, B. (2026). Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "etag": null, "last_modified": "Mon, 06 Jul 2026 10:07:40 GMT", "licence": {"name": "Open Government Licence v3.0", "spdx": "OGL-UK-3.0", "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "IMBIE Team (led from Northumbria University); archived by the NERC EDS UK Polar Data Centre", "r2_url": "https://files.environmentdashboard.org/raw/1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26.zst", "sha256": "1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26", "source_id": "imbie-2026", "title": "Mass balance of the Greenland and Antarctic ice sheets from the 1970s to 2023 (IMBIE 2026)", "url_download": "https://ramadda.data.bas.ac.uk/repository/entry/get/imbie3_greenland_Gt_partitioned.csv?entryid=synth%3A128c5e33-5224-4197-82f0-19dcc95b80a0%3AL2ltYmllM19ncmVlbmxhbmRfR3RfcGFydGl0aW9uZWQuY3N2", "url_main": "https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/02074", "version_producer": "1.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the 'Cumulative mass balance anomaly (Gt)' column of imbie3_greenland_Gt_partitioned.csv (IMBIE version 1.0), 1971-07 to 2023-12, as printed.",
            "inputs": ["1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          },
          {
            "description": "Lower and upper are the value minus and plus the file's 'Cumulative mass balance anomaly uncertainty (Gt)', which the file states is one standard deviation (exact decimal arithmetic).",
            "inputs": ["1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Zero just before July 1971, the start of IMBIE's Greenland record; the first month's value is that month's change.",
          "basis": "Reconciled from 24 independent satellite estimates (altimetry, gravimetry and the input-output method) by IMBIE 2026; total mass balance, the sum of surface mass balance and ice dynamics.",
          "bunkers": null,
          "geography": "Greenland Ice Sheet",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["imbie-2026"],
      "time_basis": "calendar",
      "title": "Greenland Ice Sheet mass change since July 1971 (IMBIE)",
      "unit": {
        "code": "Gt",
        "label": "gigatonnes",
        "short": "Gt"
      },
      "vintage": "1.0"
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    {
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      "downloadable": true,
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      "latest": {
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        "period": "2024",
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        "attribution": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.",
        "description": "How much land each country, the European Union and the world use as cropland and as permanent meadows and pastures (together, agricultural land), and how much is forest, each year since 1961 (forest since 1990), in thousands of hectares, as reported to and estimated by FAO.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (FAO Statistical Database Terms of Use)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "land-use", "bytes": 2970716, "citation_full": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-04", "date_published": "2026-10-02", "doi": null, "etag": "\"0c5cd521652ac5535fff638d867f975c\"", "last_modified": "Fri, 02 Oct 2026 08:15:20 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f.zst", "sha256": "39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/Inputs_LandUse_E_All_Data_(Normalized).zip", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2026-10-02", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "datasets-catalogue", "bytes": 109120, "citation_full": "FAO. 2026. FAOSTAT. Accessed on 5 October 2026. https://www.fao.org/faostat/en/#data Licence: CC-BY-4.0.", "date_accessed": "2026-10-05", "date_published": "2026-10-02", "doi": null, "etag": "W/\"157c9ec8e5eea09a02497cc10f67bcdb\"", "last_modified": "Mon, 05 Oct 2026 12:49:35 GMT", "licence": {"name": "CC BY 4.0 (FAO Statistical Database Terms of Use)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Food and Agriculture Organization of the United Nations (FAO), Statistics Division", "r2_url": "https://files.environmentdashboard.org/raw/008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda.zst", "sha256": "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda", "source_id": "faostat", "title": "FAOSTAT agrifood emissions, livestock emissions, emissions intensities, land use and food loss", "url_download": "https://bulks-faostat.fao.org/production/datasets_E.json", "url_main": "https://www.fao.org/faostat/en/", "version_producer": "2026-10-02", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Inputs_LandUse_E_All_Data_(Normalized).csv from FAOSTAT's RL bulk zip. The vintage is the domain's DateUpdate, 2 October 2026, from FAOSTAT's bulk-download catalogue (datasets_E.json), whose entry names this zip and gives FileRows 421,850, the number of data rows in this file. The zip was last modified on the server on Fri, 02 Oct 2026 08:15:20 GMT.",
            "inputs": ["39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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            "script": "pipeline/src/envdash/transforms/food/faostat_land_use.py",
            "transform_sha256": "534fd841c2025e33540546bb006b112a181cf353bafcddc6c22133957d0fbb53"
          },
          {
            "description": "Kept the rows of element \"Area\" (code 5110, unit \"1000 ha\") for items \"Agricultural land\" (6610), \"Cropland\" (6620), \"Permanent meadows and pastures\" (6655), \"Forest land\" (6646), 1961–2025, for every area FAO reports; values are published as printed.",
            "inputs": ["39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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            "script": "pipeline/src/envdash/transforms/food/faostat_land_use.py",
            "transform_sha256": "534fd841c2025e33540546bb006b112a181cf353bafcddc6c22133957d0fbb53"
          },
          {
            "description": "Left out former states and territories reported only before their dissolution, with no entity here (Belgium-Luxembourg, Czechoslovakia, Ethiopia PDR, Netherlands Antilles (former), Pacific Islands Trust Territory, Sudan (former), USSR, Yugoslav SFR); FAO regional and analytical groups (Africa, Americas, Asia, Australia and New Zealand, Caribbean, Central America, Central Asia, China, Eastern Africa, Eastern Asia, Eastern Europe, Europe, Land Locked Developing Countries (LLDCs), Latin America and the Caribbean, Least Developed Countries (LDCs), Low Income Food Deficit Countries (LIFDCs), Melanesia, Micronesia, Middle Africa, Net Food Importing Developing Countries (NFIDCs), Northern Africa, Northern America, Northern Europe, OECD, Oceania, Polynesia, Small Island Developing States (SIDS), South America, South-eastern Asia, Southern Africa, Southern Asia, Southern Europe, Sub-Saharan Africa, Western Africa, Western Asia, Western Europe). Their values are never re-assigned to other entities.",
            "inputs": ["39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/food/faostat_land_use.py",
            "transform_sha256": "534fd841c2025e33540546bb006b112a181cf353bafcddc6c22133957d0fbb53"
          },
          {
            "description": "The values used carry several FAO flags (A \"Official value\" (11,493 values); E \"Estimated value\" (284 values); I \"Value imputed by a receiving agency\" (34,023 values); X \"Value from external organization\" (1,416 values)); each observation names its flag in a note.",
            "inputs": ["39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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          {
            "description": "9 values are empty in the file and are published as null, with FAO's flag as the reason.",
            "inputs": ["39b739fbfb694971207a2efa572c41e8de2386fc5cb33caaf2a188e9c9a6ca3f", "008f475c971a7770c69b1bc48f1c3a5fa8bf3873e762d6e1e9516bb0a700ebda"],
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        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "FAOSTAT Land Use (RL) categories: agricultural land = cropland (arable land and permanent crops) + permanent meadows and pastures; forest land as defined by FAO's Global Forest Resources Assessment (land over 0.5 ha with trees over 5 m and canopy cover over 10 percent, not mainly under agricultural or urban use), taken by FAO from FRA 2025 and available from 1990. Country reports, with FAO estimates and imputations where countries did not report (each value's flag is given).",
          "bunkers": null,
          "geography": "Countries and territories, the European Union (27) and the world",
          "gwp": null,
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        }
      },
      "source_ids": ["faostat"],
      "time_basis": "calendar",
      "title": "Agricultural land, cropland, pasture and forest area",
      "unit": {
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        "label": "thousand hectares",
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      },
      "vintage": "2026-10-02"
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    {
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          {
            "description": "Checked that sheet 'Fig S.1' row 'LCOE 2025 (USD/MWh)' equals each technology's 2025 value rounded to a whole dollar, and found the executive summary's statements of the 2025 values on its page 5.",
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      "time_basis": "calendar",
      "title": "Cost of electricity from new renewable power plants",
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            "description": "Quoted from SPM statement C.12, p. 37. The quote was found in the text of page 41 of the snapshot (sha256 fdec68c55cbf…) before publishing.",
            "inputs": ["fdec68c55cbf64ddf2d65c468f9125c1111413fcc35aa01c94810e4548e6c778"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/literature.py",
            "transform_sha256": "a5b5e1344e63f00f27104797d126b6a018b61af35ce032fb5e665703d5e05132"
          },
          {
            "description": "Value: The statement's lower bound is published as a percentage of 2019 global greenhouse gas emissions; the IPCC states no upper bound.",
            "inputs": ["fdec68c55cbf64ddf2d65c468f9125c1111413fcc35aa01c94810e4548e6c778"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/literature.py",
            "transform_sha256": "a5b5e1344e63f00f27104797d126b6a018b61af35ce032fb5e665703d5e05132"
          }
        ],
        "published_value": {
          "document": "ipcc-ar6-wg3-spm",
          "locator": "SPM statement C.12, p. 37",
          "quote": null
        },
        "scope": {
          "baseline": null,
          "basis": "An assessed potential for 2030, not a forecast of what will happen: the reduction that options costing USD100 tCO₂-eq⁻¹ or less could deliver, from the sectoral literature. The statement is a lower bound (\"at least\").",
          "bunkers": null,
          "geography": "World",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ipcc-ar6-wg3-spm"],
      "time_basis": "calendar",
      "title": "Emission cuts available by 2030 from options costing up to 100 US dollars per tonne",
      "unit": {
        "code": "percent",
        "label": "percent of 2019 global greenhouse gas emissions",
        "short": "%"
      },
      "vintage": "AR6 WGIII (2022)"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "cf3dce806dbbee29296fa53dcb2827cbd33a9f66fed98398bc3966091ce75df7",
      "geo_coverage": "global-only",
      "id": "n2o.noaa-gml.annual-global",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "preliminary",
        "value": 338.85
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA Global Monitoring Laboratory (Lan, Thoning & Dlugokencky), version 2026-09, doi:10.15138/P8XG-AA10.",
        "description": "Annual mean nitrous oxide in dry air averaged over NOAA's global network of marine surface air-sampling sites, since 2001.",
        "kind": "series",
        "licence": {
          "name": "Public domain (work of the US federal government)",
          "spdx": null,
          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
        "notice": "The NOAA Global Monitoring Laboratory methane and nitrous oxide global marine surface means are US Government material and are not subject to copyright protection in the United States.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "n2o-annmean-gl", "bytes": 2455, "citation_full": "Lan, X., K.W. Thoning, and E.J. Dlugokencky: Trends in globally-averaged CH4, N2O, and SF6 determined from NOAA Global Monitoring Laboratory measurements. Version 2026-09, https://doi.org/10.15138/P8XG-AA10", "date_accessed": "2026-10-04", "date_published": "2026-09-05", "doi": "10.15138/P8XG-AA10", "etag": "\"997-65af9c509e106\"", "last_modified": "Tue, 08 Sep 2026 14:44:19 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NOAA Global Monitoring Laboratory", "r2_url": "https://files.environmentdashboard.org/raw/4ef7de075201af680fe28b262d4df8f092303c3450d1a7d8c1884e5c3bff070d.zst", "sha256": "4ef7de075201af680fe28b262d4df8f092303c3450d1a7d8c1884e5c3bff070d", "source_id": "noaa-gml-trends-ch4-n2o-sf6", "title": "Trends in globally-averaged methane, nitrous oxide and sulphur hexafluoride", "url_download": "https://gml.noaa.gov/webdata/ccgg/trends/n2o/n2o_annmean_gl.csv", "url_main": "https://gml.noaa.gov/ccgg/trends_doi.html", "version_producer": "2026-09", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read n2o_annmean_gl.csv, created by NOAA on 5 September 2026. The vintage is the year and month of that creation date, which is how NOAA labels its versions.",
            "inputs": ["4ef7de075201af680fe28b262d4df8f092303c3450d1a7d8c1884e5c3bff070d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_ch4_n2o.py",
            "transform_sha256": "10dc38222688b6d57bb5a048a714817da27eaad60322fa658a533496b920573d"
          },
          {
            "description": "Lower and upper are the mean minus and plus NOAA's stated uncertainty, which the file defines as the standard deviations of 100 bootstrap (network) and 100 Monte Carlo (measurement) global averages taken in quadrature (one standard deviation).",
            "inputs": ["4ef7de075201af680fe28b262d4df8f092303c3450d1a7d8c1884e5c3bff070d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_ch4_n2o.py",
            "transform_sha256": "10dc38222688b6d57bb5a048a714817da27eaad60322fa658a533496b920573d"
          },
          {
            "description": "The last year is marked preliminary because the file states that the data for the last year are subject to change.",
            "inputs": ["4ef7de075201af680fe28b262d4df8f092303c3450d1a7d8c1884e5c3bff070d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/air/noaa_ch4_n2o.py",
            "transform_sha256": "10dc38222688b6d57bb5a048a714817da27eaad60322fa658a533496b920573d"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Dry-air mole fraction; NOAA's global average of its marine surface air-sampling network, from smoothed site records weighted by latitude.",
          "bunkers": null,
          "geography": "Global mean of marine surface sites",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["noaa-gml-trends-ch4-n2o-sf6"],
      "time_basis": "calendar",
      "title": "Nitrous oxide, global annual mean",
      "unit": {
        "code": "ppb",
        "label": "parts per billion",
        "short": "ppb"
      },
      "vintage": "2026-09"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["AGO", "AND", "ARE", "ARM", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BFA", "BGD", "BGR", "BHR", "BHS", "BLR", "BLZ", "BOL", "BRA", "BRB", "BRN", "BTN", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COG", "COL", "COM", "CPV", "CRI", "CUB", "CYP", "CZE", "DEU", "DNK", "DOM", "DZA", "ECU", "ERI", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FRA", "FSM", "GAB", "GBR", "GEO", "GIN", "GMB", "GRC", "GUY", "HND", "HRV", "HUN", "IDN", "IND", "IRL", "IRQ", "ISL", "ITA", "JAM", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KOR", "LBN", "LBR", "LCA", "LIE", "LKA", "LTU", "LUX", "LVA", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MLT", "MNE", "MNG", "MOZ", "MRT", "MUS", "MWI", "MYS", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PER", "PHL", "PLW", "POL", "PRT", "PRY", "PSE", "QAT", "ROU", "RUS", "RWA", "SAU", "SGP", "SLB", "SLE", "SLV", "SOM", "SRB", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYC", "TGO", "THA", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "UKR", "URY", "USA", "UZB", "VAT", "VEN", "VUT", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "eaa820ffa3fb593984b677399cb6a4c4d86b38986041016943a975dbd596ca53",
      "geo_coverage": "mixed",
      "id": "ndc.climate-watch.2025-ndc",
      "latest": {
        "age_bp": null,
        "dims": {
          "question": "submitted"
        },
        "entity": "EU27",
        "period": "2025-11-05",
        "status": "final",
        "value": 1.0
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Adapted by Environment Dashboard from Climate Watch NDC Tracker. 2026. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org/ndc-tracker. CC BY-NC 4.0. Changes: Climate Watch's yes/no labels coded as 1 and 0, with the labels kept as notes.",
        "description": "Whether each country has submitted its 2025 nationally determined contribution (NDC 3.0, the national climate plan due under the Paris Agreement), when, and what Climate Watch finds in it: a 2035 greenhouse gas target, an economy-wide target, a target for gases other than carbon dioxide, a stronger 2030 target, stronger adaptation, and added information for clarity. 1 means yes and 0 means no, as coded by the World Resources Institute's Climate Watch from the NDC texts. Countries Climate Watch has no information for are not shown.",
        "kind": "derived",
        "licence": {
          "name": "CC BY-NC 4.0 (Climate Watch dataset metadata; the site-wide text says CC BY 4.0)",
          "spdx": "CC-BY-NC-4.0",
          "url": "https://creativecommons.org/licenses/by-nc/4.0/"
        },
        "notice": "NDC documents: UNFCCC. 2026. NDC Registry. Available at: https://unfccc.int/NDCREG. Climate Watch data shared under CC BY-NC 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "ndc-tracker-2025", "bytes": 303801, "citation_full": "Climate Watch NDC Tracker. 2026. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org/ndc-tracker", "date_accessed": "2026-10-05", "date_published": null, "doi": null, "etag": "W/\"2d0d6af161093f72b8497c3eb07a7918\"", "last_modified": null, "licence": {"name": "CC BY-NC 4.0 (Climate Watch dataset metadata; the site-wide text says CC BY 4.0)", "spdx": "CC-BY-NC-4.0", "url": "https://creativecommons.org/licenses/by-nc/4.0/"}, "producer": "World Resources Institute (Climate Watch)", "r2_url": "https://files.environmentdashboard.org/raw/2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2.zst", "sha256": "2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2", "source_id": "climate-watch-ndc", "title": "Climate Watch NDC Tracker (2025 NDCs)", "url_download": "https://www.climatewatchdata.org/api/v1/ndcs?indicators=2025_status,2025_statement,2025_emissions_compare,2025_source,2025_date,2025_compare_1,2025_compare_2,2025_compare_3,2025_compare_4,2025_compare_5,2025_compare_6,submission,submission_date,pa_status", "url_main": "https://www.climatewatchdata.org/", "version_producer": "NDC Tracker retrieved 2026-10-05 (latest 2025 NDC dated 2026-09-08)", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the Climate Watch API response (sha256 2d0d6af16109…, retrieved 2026-10-05) and checked that every indicator in it has source 'Climate Watch'.",
            "inputs": ["2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/climate_watch_ndc.py",
            "transform_sha256": "090e35ff044de792f434773c5e513471fe4b4c02cb40a3a857a653b5498fbdcd"
          },
          {
            "description": "For the 153 locations with a 2025 NDC status, coded the submission status and the six content questions as 1 (Climate Watch's 'Yes' or 'Submitted' label) or 0 ('No' or 'Withdrawn'); labels that answer neither way are published as missing, with the label. Each value keeps Climate Watch's label as its note.",
            "inputs": ["2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/climate_watch_ndc.py",
            "transform_sha256": "090e35ff044de792f434773c5e513471fe4b4c02cb40a3a857a653b5498fbdcd"
          },
          {
            "description": "Dated each observation by the Party's 2025 NDC date (M/D/YYYY in the file, written as an ISO date). EUU (the European Union) is published as EU27.",
            "inputs": ["2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/climate_watch_ndc.py",
            "transform_sha256": "090e35ff044de792f434773c5e513471fe4b4c02cb40a3a857a653b5498fbdcd"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Qualitative coding by Climate Watch (World Resources Institute) from the NDC documents on the UNFCCC registry. Each observation is dated by the NDC's submission date.",
          "bunkers": null,
          "geography": "Parties to the UNFCCC with a 2025 NDC status in Climate Watch; the EU's NDC is coded for the EU and for each member state",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["climate-watch-ndc"],
      "time_basis": "calendar",
      "title": "2025 climate pledges (NDCs): who has submitted, and what they contain",
      "unit": {
        "code": "yes-no",
        "label": "1 = yes, 0 = no, as coded by Climate Watch",
        "short": ""
      },
      "vintage": "NDC Tracker retrieved 2026-10-05 (latest 2025 NDC dated 2026-09-08)"
    },
    {
      "display": {
        "decimals": 0
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "66ab6f955cd1805fa540804fe3edbdead8ed87afac4e615edc7391fdf24be24c",
      "geo_coverage": "global-only",
      "id": "ndc.climate-watch.2025-ndc-countries",
      "latest": {
        "age_bp": null,
        "dims": {
          "answer": "yes",
          "question": "submitted"
        },
        "entity": "WLD",
        "period": "2026-10-05",
        "status": "final",
        "value": 151.0
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Adapted by Environment Dashboard from Climate Watch NDC Tracker. 2026. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org/ndc-tracker. CC BY-NC 4.0. Changes: Counted the countries Climate Watch codes yes and no for each question.",
        "description": "The number of countries whose 2025 nationally determined contribution (NDC 3.0) Climate Watch has coded, by answer: submitted or withdrawn, and whether the plan includes a 2035 greenhouse gas target, an economy-wide target, a target for gases other than carbon dioxide, a stronger 2030 target, stronger adaptation, and added information for clarity. Each EU member state counts once.",
        "kind": "derived",
        "licence": {
          "name": "CC BY-NC 4.0 (Climate Watch dataset metadata; the site-wide text says CC BY 4.0)",
          "spdx": "CC-BY-NC-4.0",
          "url": "https://creativecommons.org/licenses/by-nc/4.0/"
        },
        "notice": "NDC documents: UNFCCC. 2026. NDC Registry. Available at: https://unfccc.int/NDCREG. Climate Watch data shared under CC BY-NC 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "ndc-tracker-2025", "bytes": 303801, "citation_full": "Climate Watch NDC Tracker. 2026. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org/ndc-tracker", "date_accessed": "2026-10-05", "date_published": null, "doi": null, "etag": "W/\"2d0d6af161093f72b8497c3eb07a7918\"", "last_modified": null, "licence": {"name": "CC BY-NC 4.0 (Climate Watch dataset metadata; the site-wide text says CC BY 4.0)", "spdx": "CC-BY-NC-4.0", "url": "https://creativecommons.org/licenses/by-nc/4.0/"}, "producer": "World Resources Institute (Climate Watch)", "r2_url": "https://files.environmentdashboard.org/raw/2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2.zst", "sha256": "2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2", "source_id": "climate-watch-ndc", "title": "Climate Watch NDC Tracker (2025 NDCs)", "url_download": "https://www.climatewatchdata.org/api/v1/ndcs?indicators=2025_status,2025_statement,2025_emissions_compare,2025_source,2025_date,2025_compare_1,2025_compare_2,2025_compare_3,2025_compare_4,2025_compare_5,2025_compare_6,submission,submission_date,pa_status", "url_main": "https://www.climatewatchdata.org/", "version_producer": "NDC Tracker retrieved 2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the Climate Watch API response (sha256 2d0d6af16109…, retrieved 2026-10-05) and coded its labels as in ndc.climate-watch.2025-ndc.",
            "inputs": ["2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/climate_watch_ndc.py",
            "transform_sha256": "090e35ff044de792f434773c5e513471fe4b4c02cb40a3a857a653b5498fbdcd"
          },
          {
            "description": "Counted, for each question, the 152 countries with a 2025 NDC status that Climate Watch codes yes and those it codes no. The European Union's own entry (EUU) is not counted, because Climate Watch codes its NDC for each member state too; labels that answer neither way are in neither count.",
            "inputs": ["2d0d6af161093f72b8497c3eb07a791841e2df813e09c5f06b7245238153d8a2"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/climate_watch_ndc.py",
            "transform_sha256": "090e35ff044de792f434773c5e513471fe4b4c02cb40a3a857a653b5498fbdcd"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Counts of Climate Watch's qualitative coding of the NDC documents on the UNFCCC registry, on the day the tracker was retrieved.",
          "bunkers": null,
          "geography": "Countries with a 2025 NDC status in Climate Watch, each EU member state counted once and the EU's own entry not counted again; countries Climate Watch has no information for are in neither count",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["climate-watch-ndc"],
      "time_basis": "calendar",
      "title": "How many countries have sent a 2025 climate pledge (NDC), and what the pledges contain",
      "unit": {
        "code": "countries",
        "label": "countries",
        "short": "countries"
      },
      "vintage": "NDC Tracker retrieved 2026-10-05"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "160bfd19940a49ed4dfe9fab39bb938fea2ce6653d229e7fb6f5cbf3e0516e1b",
      "geo_coverage": "global-only",
      "id": "ohc.ncei.pentadal-0-2000m",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2021/2025",
        "status": "final",
        "value": 29.48
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA NCEI Ocean Heat Content Climate Data Record (Levitus, Antonov, Boyer et al.), NCEI Accession 0164586, doi:10.7289/V53F4MVP, accessed 2026-10-05; Levitus et al. (2012), Geophys. Res. Lett. 39, L10603, doi:10.1029/2012GL051106.",
        "description": "Heat stored in the top 2,000 metres of the world ocean as running five-year means since 1955–59 (NCEI's basin time series have no yearly or three-month 0–2,000 m values before 2005), as the difference from NCEI's long-term average, in units of 10²² joules, with one standard error.",
        "kind": "series",
        "licence": {
          "name": "No restrictions on use (NOAA CDR Program Open Data Policy; US federal government work)",
          "spdx": null,
          "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Ocean_Heat_Content/UseAgreement_01B-41.pdf"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "world-0-2000m-pentadal", "bytes": 3876, "citation_full": "Levitus, Sydney; Antonov, John I.; Boyer, Tim P.; Baranova, Olga K.; García, Hernán E.; Locarnini, Ricardo A.; Mishonov, Alexey V.; Reagan, James R.; Seidov, Dan; Yarosh, Evgeney; Zweng, Melissa M. (2017). NCEI ocean heat content, temperature anomalies, salinity anomalies, thermosteric sea level anomalies, halosteric sea level anomalies, and total steric sea level anomalies from 1955 to present calculated from in situ oceanographic subsurface profile data (NCEI Accession 0164586). Global Ocean Heat and Salt Content - Seasonal, Yearly, and Pentadal Fields. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v53f4mvp. Accessed 2026-10-05. Levitus, S., J. I. Antonov, T. P. Boyer, O. K. Baranova, H. E. Garcia, R. A. Locarnini, A.V. Mishonov, J. R. Reagan, D. Seidov, E. S. Yarosh, M. M. Zweng, 2012: World Ocean heat content and thermosteric sea level change (0-2000 m) 1955-2010. Geophys. Res. Lett. , 39, L10603, doi:10.1029/2012GL051106.", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.7289/V53F4MVP", "etag": "\"f24-655f9896b79ae\"", "last_modified": "Mon, 06 Jul 2026 23:21:41 GMT", "licence": {"name": "No restrictions on use (NOAA CDR Program Open Data Policy; US federal government work)", "spdx": null, "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Ocean_Heat_Content/UseAgreement_01B-41.pdf"}, "producer": "NOAA National Centers for Environmental Information (NCEI)", "r2_url": "https://files.environmentdashboard.org/raw/2160656a7afed5d87e95b079374efb83e3ade2f9d1a58e0649290ce0eddf73b4.zst", "sha256": "2160656a7afed5d87e95b079374efb83e3ade2f9d1a58e0649290ce0eddf73b4", "source_id": "ncei-ocean-heat", "title": "Global ocean heat content basin time series", "url_download": "https://www.ncei.noaa.gov/data/oceans/woa/DATA_ANALYSIS/3M_HEAT_CONTENT/DATA/basin/pentad/pent_h22-w0-2000m.dat", "url_main": "https://www.ncei.noaa.gov/access/global-ocean-heat-content/", "version_producer": "2026-07-06", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read pent_h22-w0-2000m.dat (World Ocean heat content, 0-2000 m, in 10^22 joules; last modified by NCEI on 2026-07-06, which is the vintage, since the file carries no version), 67 rows from 1955/1959 to 2021/2025. Each row is a five-year mean; its time column, the middle of the five years (e.g. 1957.5), became the five-year range (1955/1959).",
            "inputs": ["2160656a7afed5d87e95b079374efb83e3ade2f9d1a58e0649290ce0eddf73b4"],
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          {
            "description": "Published the World Ocean column as printed. Lower and upper are that value minus and plus NCEI's standard error from the next column (one standard error). The hemisphere columns are not published.",
            "inputs": ["2160656a7afed5d87e95b079374efb83e3ade2f9d1a58e0649290ce0eddf73b4"],
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        ],
        "published_value": null,
        "scope": {
          "baseline": "Difference from NCEI's long-term climatological mean (the World Ocean Atlas series); the files and product pages do not name the climatology's period",
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          "bunkers": null,
          "geography": "World Ocean (including the Arctic Ocean), sea surface to 2000 m depth",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["ncei-ocean-heat"],
      "time_basis": "calendar",
      "title": "Ocean heat content, 0–2000 m, five-year means (NCEI)",
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        "label": "10²² joules (10 zettajoules)",
        "short": "10²² J"
      },
      "vintage": "2026-07-06"
    },
    {
      "display": {
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      "downloadable": true,
      "entities": ["WLD"],
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      "geo_coverage": "global-only",
      "id": "ohc.ncei.yearly-0-2000m",
      "latest": {
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        "period": "2025",
        "status": "final",
        "value": 32.533
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      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA NCEI Ocean Heat Content Climate Data Record (Levitus, Antonov, Boyer et al.), NCEI Accession 0164586, doi:10.7289/V53F4MVP, accessed 2026-10-05; Levitus et al. (2012), Geophys. Res. Lett. 39, L10603, doi:10.1029/2012GL051106.",
        "description": "Heat stored in the top 2,000 metres of the world ocean in each year since 2005, as the difference from NCEI's long-term average, in units of 10²² joules, with one standard error.",
        "kind": "series",
        "licence": {
          "name": "No restrictions on use (NOAA CDR Program Open Data Policy; US federal government work)",
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          "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Ocean_Heat_Content/UseAgreement_01B-41.pdf"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "world-0-2000m-yearly", "bytes": 1254, "citation_full": "Levitus, Sydney; Antonov, John I.; Boyer, Tim P.; Baranova, Olga K.; García, Hernán E.; Locarnini, Ricardo A.; Mishonov, Alexey V.; Reagan, James R.; Seidov, Dan; Yarosh, Evgeney; Zweng, Melissa M. (2017). NCEI ocean heat content, temperature anomalies, salinity anomalies, thermosteric sea level anomalies, halosteric sea level anomalies, and total steric sea level anomalies from 1955 to present calculated from in situ oceanographic subsurface profile data (NCEI Accession 0164586). Global Ocean Heat and Salt Content - Seasonal, Yearly, and Pentadal Fields. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v53f4mvp. Accessed 2026-10-05. Levitus, S., J. I. Antonov, T. P. Boyer, O. K. Baranova, H. E. Garcia, R. A. Locarnini, A.V. Mishonov, J. R. Reagan, D. Seidov, E. S. Yarosh, M. M. Zweng, 2012: World Ocean heat content and thermosteric sea level change (0-2000 m) 1955-2010. Geophys. Res. Lett. , 39, L10603, doi:10.1029/2012GL051106.", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.7289/V53F4MVP", "etag": "\"4e6-655f989663dd4\"", "last_modified": "Mon, 06 Jul 2026 23:21:40 GMT", "licence": {"name": "No restrictions on use (NOAA CDR Program Open Data Policy; US federal government work)", "spdx": null, "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Ocean_Heat_Content/UseAgreement_01B-41.pdf"}, "producer": "NOAA National Centers for Environmental Information (NCEI)", "r2_url": "https://files.environmentdashboard.org/raw/5b0fabf106dc1473f0a658baaced5245bc19e33a39c6d86294a3cf074ac0f5b4.zst", "sha256": "5b0fabf106dc1473f0a658baaced5245bc19e33a39c6d86294a3cf074ac0f5b4", "source_id": "ncei-ocean-heat", "title": "Global ocean heat content basin time series", "url_download": "https://www.ncei.noaa.gov/data/oceans/woa/DATA_ANALYSIS/3M_HEAT_CONTENT/DATA/basin/yearly/h22-w0-2000m.dat", "url_main": "https://www.ncei.noaa.gov/access/global-ocean-heat-content/", "version_producer": "2026-07-06", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read h22-w0-2000m.dat (World Ocean heat content, 0-2000 m, in 10^22 joules; last modified by NCEI on 2026-07-06, which is the vintage, since the file carries no version), 21 rows from 2005 to 2025. The time column (year + 0.5) became the year.",
            "inputs": ["5b0fabf106dc1473f0a658baaced5245bc19e33a39c6d86294a3cf074ac0f5b4"],
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            "transform_sha256": "dadfc516ad88d8e9af8656cda22e5a4e30fe74867a812e36b38159e21b7c800b"
          },
          {
            "description": "Published the World Ocean column as printed. Lower and upper are that value minus and plus NCEI's standard error from the next column (one standard error). The hemisphere columns are not published.",
            "inputs": ["5b0fabf106dc1473f0a658baaced5245bc19e33a39c6d86294a3cf074ac0f5b4"],
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        ],
        "published_value": null,
        "scope": {
          "baseline": "Difference from NCEI's long-term climatological mean (the World Ocean Atlas series); the files and product pages do not name the climatology's period",
          "basis": "Yearly means. Heat content anomaly integrated over the layer, calculated by NCEI from in situ subsurface temperature profiles quality controlled in the World Ocean Database (method of Levitus et al. 2012).",
          "bunkers": null,
          "geography": "World Ocean (including the Arctic Ocean), sea surface to 2000 m depth",
          "gwp": null,
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        }
      },
      "source_ids": ["ncei-ocean-heat"],
      "time_basis": "calendar",
      "title": "Ocean heat content, 0–2000 m, yearly (NCEI)",
      "unit": {
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        "label": "10²² joules (10 zettajoules)",
        "short": "10²² J"
      },
      "vintage": "2026-07-06"
    },
    {
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      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "b8b364f44cead91c9507aabacc481b1d7166da592100e0b9a5599374e697af63",
      "geo_coverage": "global-only",
      "id": "ohc.ncei.yearly-0-700m",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 22.845
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "NOAA NCEI Ocean Heat Content Climate Data Record (Levitus, Antonov, Boyer et al.), NCEI Accession 0164586, doi:10.7289/V53F4MVP, accessed 2026-10-05; Levitus et al. (2012), Geophys. Res. Lett. 39, L10603, doi:10.1029/2012GL051106.",
        "description": "Heat stored in the top 700 metres of the world ocean in each year since 1955, as the difference from NCEI's long-term average, in units of 10²² joules, with one standard error.",
        "kind": "series",
        "licence": {
          "name": "No restrictions on use (NOAA CDR Program Open Data Policy; US federal government work)",
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        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "world-0-700m-yearly", "bytes": 4104, "citation_full": "Levitus, Sydney; Antonov, John I.; Boyer, Tim P.; Baranova, Olga K.; García, Hernán E.; Locarnini, Ricardo A.; Mishonov, Alexey V.; Reagan, James R.; Seidov, Dan; Yarosh, Evgeney; Zweng, Melissa M. (2017). NCEI ocean heat content, temperature anomalies, salinity anomalies, thermosteric sea level anomalies, halosteric sea level anomalies, and total steric sea level anomalies from 1955 to present calculated from in situ oceanographic subsurface profile data (NCEI Accession 0164586). Global Ocean Heat and Salt Content - Seasonal, Yearly, and Pentadal Fields. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v53f4mvp. Accessed 2026-10-05. Levitus, S., J. I. Antonov, T. P. Boyer, O. K. Baranova, H. E. Garcia, R. A. Locarnini, A.V. Mishonov, J. R. Reagan, D. Seidov, E. S. Yarosh, M. M. Zweng, 2012: World Ocean heat content and thermosteric sea level change (0-2000 m) 1955-2010. Geophys. Res. Lett. , 39, L10603, doi:10.1029/2012GL051106.", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.7289/V53F4MVP", "etag": "\"1008-655f98966e5cc\"", "last_modified": "Mon, 06 Jul 2026 23:21:40 GMT", "licence": {"name": "No restrictions on use (NOAA CDR Program Open Data Policy; US federal government work)", "spdx": null, "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Ocean_Heat_Content/UseAgreement_01B-41.pdf"}, "producer": "NOAA National Centers for Environmental Information (NCEI)", "r2_url": "https://files.environmentdashboard.org/raw/29114e2df7b856f88876f97ca4f073b5a04786ca86c0d643565a9f035046489b.zst", "sha256": "29114e2df7b856f88876f97ca4f073b5a04786ca86c0d643565a9f035046489b", "source_id": "ncei-ocean-heat", "title": "Global ocean heat content basin time series", "url_download": "https://www.ncei.noaa.gov/data/oceans/woa/DATA_ANALYSIS/3M_HEAT_CONTENT/DATA/basin/yearly/h22-w0-700m.dat", "url_main": "https://www.ncei.noaa.gov/access/global-ocean-heat-content/", "version_producer": "2026-07-06", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read h22-w0-700m.dat (World Ocean heat content, 0-700 m, in 10^22 joules; last modified by NCEI on 2026-07-06, which is the vintage, since the file carries no version), 71 rows from 1955 to 2025. The time column (year + 0.5) became the year.",
            "inputs": ["29114e2df7b856f88876f97ca4f073b5a04786ca86c0d643565a9f035046489b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/ncei_ohc.py",
            "transform_sha256": "dadfc516ad88d8e9af8656cda22e5a4e30fe74867a812e36b38159e21b7c800b"
          },
          {
            "description": "Published the World Ocean column as printed. Lower and upper are that value minus and plus NCEI's standard error from the next column (one standard error). The hemisphere columns are not published.",
            "inputs": ["29114e2df7b856f88876f97ca4f073b5a04786ca86c0d643565a9f035046489b"],
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            "transform_sha256": "dadfc516ad88d8e9af8656cda22e5a4e30fe74867a812e36b38159e21b7c800b"
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        ],
        "published_value": null,
        "scope": {
          "baseline": "Difference from NCEI's long-term climatological mean (the World Ocean Atlas series); the files and product pages do not name the climatology's period",
          "basis": "Yearly means. Heat content anomaly integrated over the layer, calculated by NCEI from in situ subsurface temperature profiles quality controlled in the World Ocean Database (method of Levitus et al. 2012).",
          "bunkers": null,
          "geography": "World Ocean (including the Arctic Ocean), sea surface to 700 m depth",
          "gwp": null,
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        }
      },
      "source_ids": ["ncei-ocean-heat"],
      "time_basis": "calendar",
      "title": "Ocean heat content, 0–700 m, yearly (NCEI)",
      "unit": {
        "code": "1e22J",
        "label": "10²² joules (10 zettajoules)",
        "short": "10²² J"
      },
      "vintage": "2026-07-06"
    },
    {
      "display": {
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      "downloadable": true,
      "entities": ["ALOHA"],
      "export_sha256": "c5857c5d4b01156cbfd9e4dde15251f8a598961ab520df44033e1629768b01db",
      "geo_coverage": "global-only",
      "id": "pco2.hot-aloha.surface-insitu",
      "latest": {
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        "dims": {},
        "entity": "ALOHA",
        "period": "2024-12-20",
        "status": "final",
        "value": 389.9
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Hawaii Ocean Time-series (HOT) surface CO2 system data product, Station ALOHA (J. E. Dore, University of Hawai'i at Mānoa), last updated 2026-01-01; adapted from Dore et al. (2009), Proc Natl Acad Sci USA 106:12235-12240, doi:10.1073/pnas.0906044106.",
        "description": "Partial pressure of carbon dioxide in surface seawater at Station ALOHA, north of Oahu, for each Hawaii Ocean Time-series cruise since October 1988, in microatmospheres.",
        "kind": "series",
        "licence": {
          "name": "No licence stated; free and open access with an NSF acknowledgement (HOT data policy)",
          "spdx": null,
          "url": null
        },
        "notice": "This publication is based upon Hawaii Ocean Time-series observations supported by the U.S. National Science Foundation under Award #2241005.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "hot-surface-co2", "bytes": 46975, "citation_full": "Dore, J.E., R. Lukas, D.W. Sadler, M.J. Church, and D.M. Karl. 2009. Physical and biogeochemical modulation of ocean acidification in the central North Pacific. Proc Natl Acad Sci USA 106:12235-12240.", "date_accessed": "2026-10-05", "date_published": "2026-01-01", "doi": "10.1073/pnas.0906044106", "etag": "\"b77f-647be0be1fe1b\"", "last_modified": "Tue, 06 Jan 2026 20:30:28 GMT", "licence": {"name": "No licence stated; free and open access with an NSF acknowledgement (HOT data policy)", "spdx": null, "url": null}, "producer": "Hawaii Ocean Time-series, School of Ocean and Earth Science and Technology, University of Hawai'i at Mānoa", "r2_url": "https://files.environmentdashboard.org/raw/4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665.zst", "sha256": "4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "source_id": "hot-aloha", "title": "Hawaii Ocean Time-series surface CO2 system data, Station ALOHA", "url_download": "https://hahana.soest.hawaii.edu/hot/hotco2/HOT_surface_CO2.txt", "url_main": "https://hahana.soest.hawaii.edu/hot/hotco2/hotco2.html", "version_producer": "2026-01-01", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "readme", "bytes": 573080, "citation_full": "Dore, J.E., R. Lukas, D.W. Sadler, M.J. Church, and D.M. Karl. 2009. Physical and biogeochemical modulation of ocean acidification in the central North Pacific. Proc Natl Acad Sci USA 106:12235-12240.", "date_accessed": "2026-10-05", "date_published": "2026-01-01", "doi": "10.1073/pnas.0906044106", "etag": "\"8be98-647be0c50f0bc\"", "last_modified": "Tue, 06 Jan 2026 20:30:36 GMT", "licence": {"name": "No licence stated; free and open access with an NSF acknowledgement (HOT data policy)", "spdx": null, "url": null}, "producer": "Hawaii Ocean Time-series, School of Ocean and Earth Science and Technology, University of Hawai'i at Mānoa", "r2_url": "https://files.environmentdashboard.org/raw/95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93.zst", "sha256": "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93", "source_id": "hot-aloha", "title": "Hawaii Ocean Time-series surface CO2 system data, Station ALOHA", "url_download": "https://hahana.soest.hawaii.edu/hot/hotco2/HOT_surface_CO2_readme.pdf", "url_main": "https://hahana.soest.hawaii.edu/hot/hotco2/hotco2.html", "version_producer": "2026-01-01", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read HOT_surface_CO2.txt, last updated 1 January 2026 (the vintage), and checked that its readme of the same date still defines the columns, the -999 missing marker and the notes codes as read here.",
            "inputs": ["4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93"],
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            "transform_sha256": "c2648443192ff4296c90a535d2853089cfdde5edad68bd86081289a7db44e582"
          },
          {
            "description": "Published the column pCO2calc_insitu (CO2 partial pressure in µatm calculated from DIC and alkalinity at in situ temperature) for each of the 355 cruises, 1988-10-31 to 2024-12-20, as printed, dated by the cruise's mid-day (1 October 1988 plus the days column). 9 cruises have -999 and are published as missing.",
            "inputs": ["4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93"],
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          },
          {
            "description": "Each cruise's notes codes are carried as a note in the readme's words, except c, r and s, which concern pH samples only. Nothing is averaged or filled.",
            "inputs": ["4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93"],
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        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Mean of the cruise's 0–30 dbar samples; CO₂ partial pressure at in situ temperature, calculated by HOT with CO2SYS from measured dissolved inorganic carbon and total alkalinity (Mehrbach et al. constants as refit by Dickson and Millero; 10 dbar pressure assumed).",
          "bunkers": null,
          "geography": "Station ALOHA, open North Pacific north of Oahu, Hawaii (22°45′N, 158°00′W); one station",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["hot-aloha"],
      "time_basis": "calendar",
      "title": "Seawater carbon dioxide (pCO₂) at Station ALOHA, Hawaii, each cruise",
      "unit": {
        "code": "uatm",
        "label": "microatmospheres",
        "short": "µatm"
      },
      "vintage": "2026-01-01"
    },
    {
      "display": {
        "decimals": 3
      },
      "downloadable": true,
      "entities": ["ALOHA"],
      "export_sha256": "2c3ae608e2f928ed131c142793baab76830c7785832e15e9cc876757e0a01855",
      "geo_coverage": "global-only",
      "id": "ph.hot-aloha.surface-insitu",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "ALOHA",
        "period": "2024-12-20",
        "status": "final",
        "value": 8.055
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Hawaii Ocean Time-series (HOT) surface CO2 system data product, Station ALOHA (J. E. Dore, University of Hawai'i at Mānoa), last updated 2026-01-01; adapted from Dore et al. (2009), Proc Natl Acad Sci USA 106:12235-12240, doi:10.1073/pnas.0906044106.",
        "description": "Surface seawater pH in the open North Pacific at Station ALOHA, north of Oahu, for each Hawaii Ocean Time-series cruise since October 1988. A fall in pH means the water is becoming more acidic.",
        "kind": "series",
        "licence": {
          "name": "No licence stated; free and open access with an NSF acknowledgement (HOT data policy)",
          "spdx": null,
          "url": null
        },
        "notice": "This publication is based upon Hawaii Ocean Time-series observations supported by the U.S. National Science Foundation under Award #2241005.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "hot-surface-co2", "bytes": 46975, "citation_full": "Dore, J.E., R. Lukas, D.W. Sadler, M.J. Church, and D.M. Karl. 2009. Physical and biogeochemical modulation of ocean acidification in the central North Pacific. Proc Natl Acad Sci USA 106:12235-12240.", "date_accessed": "2026-10-05", "date_published": "2026-01-01", "doi": "10.1073/pnas.0906044106", "etag": "\"b77f-647be0be1fe1b\"", "last_modified": "Tue, 06 Jan 2026 20:30:28 GMT", "licence": {"name": "No licence stated; free and open access with an NSF acknowledgement (HOT data policy)", "spdx": null, "url": null}, "producer": "Hawaii Ocean Time-series, School of Ocean and Earth Science and Technology, University of Hawai'i at Mānoa", "r2_url": "https://files.environmentdashboard.org/raw/4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665.zst", "sha256": "4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "source_id": "hot-aloha", "title": "Hawaii Ocean Time-series surface CO2 system data, Station ALOHA", "url_download": "https://hahana.soest.hawaii.edu/hot/hotco2/HOT_surface_CO2.txt", "url_main": "https://hahana.soest.hawaii.edu/hot/hotco2/hotco2.html", "version_producer": "2026-01-01", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "readme", "bytes": 573080, "citation_full": "Dore, J.E., R. Lukas, D.W. Sadler, M.J. Church, and D.M. Karl. 2009. Physical and biogeochemical modulation of ocean acidification in the central North Pacific. Proc Natl Acad Sci USA 106:12235-12240.", "date_accessed": "2026-10-05", "date_published": "2026-01-01", "doi": "10.1073/pnas.0906044106", "etag": "\"8be98-647be0c50f0bc\"", "last_modified": "Tue, 06 Jan 2026 20:30:36 GMT", "licence": {"name": "No licence stated; free and open access with an NSF acknowledgement (HOT data policy)", "spdx": null, "url": null}, "producer": "Hawaii Ocean Time-series, School of Ocean and Earth Science and Technology, University of Hawai'i at Mānoa", "r2_url": "https://files.environmentdashboard.org/raw/95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93.zst", "sha256": "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93", "source_id": "hot-aloha", "title": "Hawaii Ocean Time-series surface CO2 system data, Station ALOHA", "url_download": "https://hahana.soest.hawaii.edu/hot/hotco2/HOT_surface_CO2_readme.pdf", "url_main": "https://hahana.soest.hawaii.edu/hot/hotco2/hotco2.html", "version_producer": "2026-01-01", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read HOT_surface_CO2.txt, last updated 1 January 2026 (the vintage), and checked that its readme of the same date still defines the columns, the -999 missing marker and the notes codes as read here.",
            "inputs": ["4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ocean/hot_aloha_co2.py",
            "transform_sha256": "c2648443192ff4296c90a535d2853089cfdde5edad68bd86081289a7db44e582"
          },
          {
            "description": "Published the column pHcalc_insitu (pH calculated from DIC and alkalinity at in situ temperature, total scale) for each of the 355 cruises, 1988-10-31 to 2024-12-20, as printed, dated by the cruise's mid-day (1 October 1988 plus the days column). 9 cruises have -999 and are published as missing.",
            "inputs": ["4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93"],
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            "script": "pipeline/src/envdash/transforms/ocean/hot_aloha_co2.py",
            "transform_sha256": "c2648443192ff4296c90a535d2853089cfdde5edad68bd86081289a7db44e582"
          },
          {
            "description": "Each cruise's notes codes are carried as a note in the readme's words, except c, r and s, which concern pH samples only. Nothing is averaged or filled.",
            "inputs": ["4356aa4650188b99f623ac2423e4d5a2af4b189077fd1efd1e2cfd8167161665", "95ebe322ac08c965cc859679cad57bddbe596ebc138ec0381ed787ea9a03ba93"],
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        "scope": {
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          "basis": "Mean of the cruise's 0–30 dbar samples; pH on the total scale at in situ temperature, calculated by HOT with CO2SYS from measured dissolved inorganic carbon and total alkalinity (Mehrbach et al. constants as refit by Dickson and Millero; 10 dbar pressure assumed).",
          "bunkers": null,
          "geography": "Station ALOHA, open North Pacific north of Oahu, Hawaii (22°45′N, 158°00′W); one station",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["hot-aloha"],
      "time_basis": "calendar",
      "title": "Seawater pH at Station ALOHA, Hawaii, each cruise",
      "unit": {
        "code": "pH",
        "label": "pH (total hydrogen-ion scale)",
        "short": "pH"
      },
      "vintage": "2026-01-01"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ARG", "AUS", "AUT", "BEL", "BGR", "BRA", "CAN", "CHN", "COL", "CZE", "DEU", "DNK", "ESP", "FRA", "GBR", "GRC", "HUN", "IDN", "IRL", "ITA", "KOR", "MEX", "NOR", "NZL", "POL", "PRT", "ROU", "SAU", "SVK", "SWE", "TUR", "USA", "ZAF"],
      "export_sha256": "1815877b0ad07e1565ebb1a1967511b6dadd3d7d065c795bcd5cba035e392cf2",
      "geo_coverage": "country",
      "id": "policy.stechemesser-2024.successful-interventions",
      "latest": {
        "age_bp": null,
        "dims": {
          "economy_group": "developed",
          "sector": "electricity"
        },
        "entity": "GBR",
        "period": "2016",
        "status": "final",
        "value": -24.572779052668636
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      "licence_class": "open",
      "provenance": {
        "attribution": "Adapted by Environment Dashboard from Stechemesser, A. et al. (2024), replication data for \"Climate policies that achieved major emission reductions: Global evidence from two decades\", Science 385, 884–892 (doi:10.1126/science.adl6547), version v4, doi:10.5281/zenodo.12773811, CC BY 4.0. Changes: break coefficients converted from the log scale to percent change, as the authors do; breaks without a matched policy left out.",
        "description": "The 63 policy interventions that Stechemesser and colleagues found behind large, sudden drops in a sector's emissions in 41 countries over two decades: for each, the country, the sector (buildings, electricity, industry or transport), the year of the drop and its size, as the percent change in the sector's emissions compared with what the model expects without it. Each value names the policies adopted or tightened within two years before or after the drop. Most successful interventions combine several policies; the drop cannot be credited to one policy alone.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Policy data: OECD (2023), Climate Actions and Policies Measurement Framework (CAPMF), pre-release obtained by the authors in July 2023 (current version: https://oe.cd/dx/capmf); US policies from the OECD IPAC Dashboard, March 2023.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "policy-out", "bytes": 1285199, "citation_full": "Stechemesser, A. (2024). Climate policies that achieved major emission reductions: Global evidence from two decades. In Science (Version v4, Vol. 385, Issue 6711, pp. 884–892). Zenodo. https://doi.org/10.5281/zenodo.12773811. Article: Stechemesser, A., Koch, N., Mark, E., Dilger, E., Klösel, P., Menicacci, L., Nachtigall, D., Pretis, F., Ritter, N., Schwarz, M., Vossen, H., & Wenzel, A. (2024). Science, 385(6711), 884–892. https://doi.org/10.1126/science.adl6547", "date_accessed": "2026-10-05", "date_published": "2024-07-18", "doi": "10.5281/zenodo.12773811", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Stechemesser, Koch, Mark, Dilger, Klösel, Menicacci, Nachtigall, Pretis, Ritter, Schwarz, Vossen and Wenzel (PIK, MCC Berlin, OECD and others); article in Science, data and code on Zenodo", "r2_url": "https://files.environmentdashboard.org/raw/a0c67b252c4b671db9306d2dc4e6a341d3d7964041e1c49d56123f2ea17516b6.zst", "sha256": "a0c67b252c4b671db9306d2dc4e6a341d3d7964041e1c49d56123f2ea17516b6", "source_id": "stechemesser-2024", "title": "Climate policies that achieved major emission reductions (Stechemesser et al. 2024), replication data", "url_download": "https://zenodo.org/api/records/12773811/files/Policy_out.RDS/content", "url_main": "https://doi.org/10.5281/zenodo.12773811", "version_producer": "Zenodo v4 (2024-07-18)", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "eu-policies-label", "bytes": 14542, "citation_full": "Stechemesser, A. (2024). Climate policies that achieved major emission reductions: Global evidence from two decades. In Science (Version v4, Vol. 385, Issue 6711, pp. 884–892). Zenodo. https://doi.org/10.5281/zenodo.12773811. Article: Stechemesser, A., Koch, N., Mark, E., Dilger, E., Klösel, P., Menicacci, L., Nachtigall, D., Pretis, F., Ritter, N., Schwarz, M., Vossen, H., & Wenzel, A. (2024). Science, 385(6711), 884–892. https://doi.org/10.1126/science.adl6547", "date_accessed": "2026-10-05", "date_published": "2024-07-18", "doi": "10.5281/zenodo.12773811", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Stechemesser, Koch, Mark, Dilger, Klösel, Menicacci, Nachtigall, Pretis, Ritter, Schwarz, Vossen and Wenzel (PIK, MCC Berlin, OECD and others); article in Science, data and code on Zenodo", "r2_url": "https://files.environmentdashboard.org/raw/1bc4d07bf1862a68f4b19472650d49998ca47dfc377ab17ab2a58e36040bd52c.zst", "sha256": "1bc4d07bf1862a68f4b19472650d49998ca47dfc377ab17ab2a58e36040bd52c", "source_id": "stechemesser-2024", "title": "Climate policies that achieved major emission reductions (Stechemesser et al. 2024), replication data", "url_download": "https://zenodo.org/api/records/12773811/files/EU_policies_label_df.csv/content", "url_main": "https://doi.org/10.5281/zenodo.12773811", "version_producer": "Zenodo v4 (2024-07-18)", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read Policy_out.RDS (sha256 a0c67b252c4b…) with a reader of R's serialization format: 69 negative structural breaks in sectoral emissions across the developed (AC1) and developing (AC6) country samples and four sectors, each with the CAPMF policies the authors matched to it within two years (policy_match_2y, the window used in the paper's main text).",
            "inputs": ["a0c67b252c4b671db9306d2dc4e6a341d3d7964041e1c49d56123f2ea17516b6", "1bc4d07bf1862a68f4b19472650d49998ca47dfc377ab17ab2a58e36040bd52c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/stechemesser_2024.py",
            "transform_sha256": "f2e468c8d8e6713971b8d286900a039fd9ce203d4905a149ff071c654a54069e"
          },
          {
            "description": "Read EU_policies_label_df.csv (sha256 1bc4d07bf186…), the EU policies the model controls for, and matched each break to those in force in its country and sector within two years, as the notes of 06_Fig_4.R do by hand: 4 breaks are matched only by an EU policy.",
            "inputs": ["a0c67b252c4b671db9306d2dc4e6a341d3d7964041e1c49d56123f2ea17516b6", "1bc4d07bf1862a68f4b19472650d49998ca47dfc377ab17ab2a58e36040bd52c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/stechemesser_2024.py",
            "transform_sha256": "f2e468c8d8e6713971b8d286900a039fd9ce203d4905a149ff071c654a54069e"
          },
          {
            "description": "Kept the 63 breaks with at least one matched policy (the paper's successful policy interventions); the other 6 have none and are not published.",
            "inputs": ["a0c67b252c4b671db9306d2dc4e6a341d3d7964041e1c49d56123f2ea17516b6", "1bc4d07bf1862a68f4b19472650d49998ca47dfc377ab17ab2a58e36040bd52c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/stechemesser_2024.py",
            "transform_sha256": "f2e468c8d8e6713971b8d286900a039fd9ce203d4905a149ff071c654a54069e"
          },
          {
            "description": "Effect size = (e^coefficient − 1) × 100, the authors' conversion of the break coefficient (log scale) to the percent change in the sector's emissions. Each value's note lists the matched policies.",
            "inputs": ["a0c67b252c4b671db9306d2dc4e6a341d3d7964041e1c49d56123f2ea17516b6", "1bc4d07bf1862a68f4b19472650d49998ca47dfc377ab17ab2a58e36040bd52c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/stechemesser_2024.py",
            "transform_sha256": "f2e468c8d8e6713971b8d286900a039fd9ce203d4905a149ff071c654a54069e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Detected with machine-learning break detection on sectoral CO2 emissions, 2000–2022; policy data from a July 2023 pre-release of the OECD Climate Actions and Policies Measurement Framework (CAPMF), plus the EU policies the model controls for. Effect size relative to the model's counterfactual, on the log scale converted to percent.",
          "bunkers": null,
          "geography": "41 countries (OECD members and large emerging economies), one value per intervention",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["stechemesser-2024"],
      "time_basis": "calendar",
      "title": "Climate policy interventions that cut emissions (Stechemesser et al. 2024)",
      "unit": {
        "code": "percent",
        "label": "percent change in the sector's emissions at the break",
        "short": "%"
      },
      "vintage": "Zenodo v4 (2024-07-18)"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "72bea868c3dbe8eba4ff10f6121abe4240878f6a37a2b5f3321a4e37993d3ee7",
      "geo_coverage": "global-only",
      "id": "progress.scl.outcome-status",
      "latest": {
        "age_bp": null,
        "dims": {
          "status": "on-track"
        },
        "entity": "WLD",
        "period": "2026-10-05",
        "status": "final",
        "value": 0.5586592178770949
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Systems Change Lab data. Systems Change Lab. 2025. Washington, DC: World Resources Institute, Bezos Earth Fund. https://www.systemschangelab.org, accessed 2026-10-05. CC BY 4.0. Changes: indicators counted by progress status and expressed as percent of the outcome indicators not built from IEA data.",
        "description": "Of the outcome indicators Systems Change Lab tracks across power, buildings, industry, transport, cities, land, food, freshwater, the circular economy, carbon removal and finance, the share it assesses as on track for 2030, off track, well off track, heading in the right direction but too slowly, heading in the wrong direction, or with too little data to say. Indicators built from International Energy Agency data are left out.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0 (Systems Change Lab's own data; third-party data keep their licences, IEA data excluded)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Each indicator also credits the original data source named in its Systems Change Lab metadata, under that source's own licence.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "scl-data-all", "bytes": 2924272, "citation_full": "Systems Change Lab. 2025. Washington, DC: World Resources Institute, Bezos Earth Fund. Available online at: https://www.systemschangelab.org.", "date_accessed": "2026-10-05", "date_published": null, "doi": null, "etag": null, "last_modified": "Mon, 05 Oct 2026 10:33:48 GMT", "licence": {"name": "CC BY 4.0 (Systems Change Lab's own data; third-party data keep their licences, IEA data excluded)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Systems Change Lab (World Resources Institute and Bezos Earth Fund)", "r2_url": null, "sha256": "1c4ed351ea59b67a3b2878c6b7ac9952d83c4993f7eed89c408437232835e568", "source_id": "systems-change-lab", "title": "Systems Change Lab: indicators of progress on the shifts needed for 1.5 °C", "url_download": "https://systemschangelab.org/scl-download/all", "url_main": "https://systemschangelab.org/download", "version_producer": "export retrieved 2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the 438 indicator metadata files in the Systems Change Lab export (sha256 1c4ed351ea59…, retrieved 2026-10-05); 196 are outcome indicators with a progress status, the rest enablers and barriers, which have none.",
            "inputs": ["1c4ed351ea59b67a3b2878c6b7ac9952d83c4993f7eed89c408437232835e568"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/systems_change_lab.py",
            "transform_sha256": "3d70736c6d596bf03250e69cf7b0a3c69ca29ac80873818194c53bd5961a41e4"
          },
          {
            "description": "Left out the 17 outcome indicators whose data sources name the International Energy Agency (BLDG-11, BLDG-15, BLDG-24, BLDG-25, BLDG-37, CTY-21, FIN-86, IN-2, PWR-41, PWR-42, PWR-50, PWR-58, TRNS-27, TRNS-28, TRNS-29, TRNS-31, X-FIN-85).",
            "inputs": ["1c4ed351ea59b67a3b2878c6b7ac9952d83c4993f7eed89c408437232835e568"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/systems_change_lab.py",
            "transform_sha256": "3d70736c6d596bf03250e69cf7b0a3c69ca29ac80873818194c53bd5961a41e4"
          },
          {
            "description": "Counted the remaining 179 outcome indicators by Systems Change Lab's status and divided each count by their total, times 100.",
            "inputs": ["1c4ed351ea59b67a3b2878c6b7ac9952d83c4993f7eed89c408437232835e568"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/systems_change_lab.py",
            "transform_sha256": "3d70736c6d596bf03250e69cf7b0a3c69ca29ac80873818194c53bd5961a41e4"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Systems Change Lab's own progress status for each outcome indicator, as listed in its data export on the day it was downloaded; enabler and barrier indicators carry no status and are not counted.",
          "bunkers": null,
          "geography": "World (Systems Change Lab's global indicators)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["systems-change-lab"],
      "time_basis": "calendar",
      "title": "Progress of the shifts needed for 1.5 °C (Systems Change Lab)",
      "unit": {
        "code": "percent",
        "label": "percent of Systems Change Lab outcome indicators",
        "short": "%"
      },
      "vintage": "export retrieved 2026-10-05"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["NH"],
      "export_sha256": "7445208c6ff15dc399b67cacacc9081e43d13a86de5d6b3ec424639933158c29",
      "geo_coverage": "global-only",
      "id": "sea-ice-extent.nsidc.arctic-minimum-5day",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "NH",
        "period": "2026-09-12",
        "status": "preliminary",
        "value": 4.5976
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Fetterer, Knowles, Meier, Savoie, Windnagel & Stafford (2025), Sea Ice Index, Version 4 (G02135), National Snow and Ice Data Center, Boulder, Colorado, doi:10.7265/a98x-0f50, accessed 2026-10-05. Changes: 5-day trailing means of the daily extent, and the lowest of them in each year.",
        "description": "The lowest Arctic sea ice extent of each year since 1987, on the 5-day trailing mean NSIDC uses for its minimum announcements, and the day it was reached. Earlier years are not shown: the satellite record then has a value only every other day.",
        "kind": "derived",
        "licence": {
          "name": "No licence stated; free use with citation as a condition of use (NSIDC)",
          "spdx": null,
          "url": "https://nsidc.org/about/data-use-and-copyright"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "north-daily-extent", "bytes": 1902717, "citation_full": "Fetterer, F., Knowles, K., Meier, W. N., Savoie, M., Windnagel, A. K. & Stafford, T. (2025). Sea Ice Index. (G02135, Version 4). [Data Set]. Boulder, Colorado USA. National Snow and Ice Data Center. https://doi.org/10.7265/a98x-0f50. Daily and monthly sea ice extent, Northern and Southern Hemispheres. Date Accessed 2026-10-05.", "date_accessed": "2026-10-05", "date_published": "2026-10-05", "doi": "10.7265/a98x-0f50", "etag": "\"6ac38124-1d087d\"", "last_modified": "Mon, 05 Oct 2026 10:51:16 GMT", "licence": {"name": "No licence stated; free use with citation as a condition of use (NSIDC)", "spdx": null, "url": "https://nsidc.org/about/data-use-and-copyright"}, "producer": "NOAA@NSIDC, National Snow and Ice Data Center (CIRES, University of Colorado Boulder)", "r2_url": "https://files.environmentdashboard.org/raw/411d93b321748650ef213a8ff81e72636efef0722248e2b8504c5e284c98c5c7.zst", "sha256": "411d93b321748650ef213a8ff81e72636efef0722248e2b8504c5e284c98c5c7", "source_id": "nsidc-sea-ice-index", "title": "Sea Ice Index, Version 4 (G02135)", "url_download": "https://noaadata.apps.nsidc.org/NOAA/G02135/north/daily/data/N_seaice_extent_daily_v4.0.csv", "url_main": "https://nsidc.org/data/g02135/versions/4", "version_producer": "4.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the Extent column of N_seaice_extent_daily_v4.0.csv (million km², data to 4 October 2026).",
            "inputs": ["411d93b321748650ef213a8ff81e72636efef0722248e2b8504c5e284c98c5c7"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/nsidc_sea_ice.py",
            "transform_sha256": "8b0c8ba6e2a25c0970fbbb9ca3f8eb93d48443340ce1c2ab0a813e5f06a5e10b"
          },
          {
            "description": "For every day whose four preceding days also have a value, took the mean of the five (NSIDC's 5-day trailing mean, exact decimal arithmetic). Windows with a missing day are skipped, never filled; no window may contain 14 September 1984, which NSIDC's user guide says is in error.",
            "inputs": ["411d93b321748650ef213a8ff81e72636efef0722248e2b8504c5e284c98c5c7"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/nsidc_sea_ice.py",
            "transform_sha256": "8b0c8ba6e2a25c0970fbbb9ca3f8eb93d48443340ce1c2ab0a813e5f06a5e10b"
          },
          {
            "description": "For each calendar year, published the lowest of those means, dated by the day it ends on (the earlier day if two tie). Years with no complete window are not published: 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986 (the file has a value only every other day before 21 August 1987).",
            "inputs": ["411d93b321748650ef213a8ff81e72636efef0722248e2b8504c5e284c98c5c7"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/nsidc_sea_ice.py",
            "transform_sha256": "8b0c8ba6e2a25c0970fbbb9ca3f8eb93d48443340ce1c2ab0a813e5f06a5e10b"
          },
          {
            "description": "The last year is marked preliminary until the file reaches 31 December.",
            "inputs": ["411d93b321748650ef213a8ff81e72636efef0722248e2b8504c5e284c98c5c7"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/nsidc_sea_ice.py",
            "transform_sha256": "8b0c8ba6e2a25c0970fbbb9ca3f8eb93d48443340ce1c2ab0a813e5f06a5e10b"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Lowest 5-day trailing mean of NSIDC's daily sea ice extent (area of cells with at least 15% ice concentration) in each calendar year; the period is the last day of that 5-day window.",
          "bunkers": null,
          "geography": "Northern Hemisphere oceans (the Arctic Ocean and surrounding seas)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["nsidc-sea-ice-index"],
      "time_basis": "calendar",
      "title": "Arctic sea ice yearly minimum extent (NSIDC, 5-day mean)",
      "unit": {
        "code": "million-km2",
        "label": "million square kilometres",
        "short": "million km²"
      },
      "vintage": "4.0"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["NH"],
      "export_sha256": "1f0a3ade5cfa2e386a09572308cde8dabf83071742021a8dad4e2c4267098831",
      "geo_coverage": "global-only",
      "id": "sea-ice-extent.nsidc.arctic-september",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "NH",
        "period": "2026-09",
        "status": "final",
        "value": 4.81
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Fetterer, Knowles, Meier, Savoie, Windnagel & Stafford (2025), Sea Ice Index, Version 4 (G02135), National Snow and Ice Data Center, Boulder, Colorado, doi:10.7265/a98x-0f50, accessed 2026-10-05.",
        "description": "Mean extent of Arctic sea ice in September, the month of the yearly minimum, since 1979: the area of ocean where satellites measure at least 15% ice cover, from NSIDC's Sea Ice Index. From 2025 NSIDC uses JAXA's AMSR2 satellite record instead of the DMSP record.",
        "kind": "series",
        "licence": {
          "name": "No licence stated; free use with citation as a condition of use (NSIDC)",
          "spdx": null,
          "url": "https://nsidc.org/about/data-use-and-copyright"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "north-monthly-september", "bytes": 2352, "citation_full": "Fetterer, F., Knowles, K., Meier, W. N., Savoie, M., Windnagel, A. K. & Stafford, T. (2025). Sea Ice Index. (G02135, Version 4). [Data Set]. Boulder, Colorado USA. National Snow and Ice Data Center. https://doi.org/10.7265/a98x-0f50. Daily and monthly sea ice extent, Northern and Southern Hemispheres. Date Accessed 2026-10-05.", "date_accessed": "2026-10-05", "date_published": "2026-10-02", "doi": "10.7265/a98x-0f50", "etag": "\"6abfb390-930\"", "last_modified": "Fri, 02 Oct 2026 13:37:20 GMT", "licence": {"name": "No licence stated; free use with citation as a condition of use (NSIDC)", "spdx": null, "url": "https://nsidc.org/about/data-use-and-copyright"}, "producer": "NOAA@NSIDC, National Snow and Ice Data Center (CIRES, University of Colorado Boulder)", "r2_url": "https://files.environmentdashboard.org/raw/3968dfdbe73b8361712da9136cfeff6dbc9a6d87ab3e75daa30cc254615eab1f.zst", "sha256": "3968dfdbe73b8361712da9136cfeff6dbc9a6d87ab3e75daa30cc254615eab1f", "source_id": "nsidc-sea-ice-index", "title": "Sea Ice Index, Version 4 (G02135)", "url_download": "https://noaadata.apps.nsidc.org/NOAA/G02135/north/monthly/data/N_09_extent_v4.0.csv", "url_main": "https://nsidc.org/data/g02135/versions/4", "version_producer": "4.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the extent column of N_09_extent_v4.0.csv, NSIDC's Northern Hemisphere September file (one row per year, 1979 to 2026), as printed in million km². NSIDC computes each value as the mean of the month's daily extents (cells with at least 15% ice concentration, the unobserved area around the pole counted as ice covered).",
            "inputs": ["3968dfdbe73b8361712da9136cfeff6dbc9a6d87ab3e75daa30cc254615eab1f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/nsidc_sea_ice.py",
            "transform_sha256": "8b0c8ba6e2a25c0970fbbb9ca3f8eb93d48443340ce1c2ab0a813e5f06a5e10b"
          },
          {
            "description": "Rows whose source data set is NSIDC-0803 (JAXA's AMSR2 record, used from 1 January 2025) carry that as a note.",
            "inputs": ["3968dfdbe73b8361712da9136cfeff6dbc9a6d87ab3e75daa30cc254615eab1f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/nsidc_sea_ice.py",
            "transform_sha256": "8b0c8ba6e2a25c0970fbbb9ca3f8eb93d48443340ce1c2ab0a813e5f06a5e10b"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Sea ice extent: mean over the month of the daily area of grid cells with at least 15% ice concentration (25 km grid, passive microwave), the unobserved area around the pole counted as ice covered. Not sea ice area, and not OSI SAF's index.",
          "bunkers": null,
          "geography": "Northern Hemisphere oceans (the Arctic Ocean and surrounding seas)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["nsidc-sea-ice-index"],
      "time_basis": "calendar",
      "title": "Arctic sea ice extent in September (NSIDC)",
      "unit": {
        "code": "million-km2",
        "label": "million square kilometres",
        "short": "million km²"
      },
      "vintage": "4.0"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["NH"],
      "export_sha256": "bfdcfe01a095428868f27921cd5eab12e8fe934924dfba5476a00ff128df277d",
      "geo_coverage": "global-only",
      "id": "sea-ice-extent.osisaf.arctic-september",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "NH",
        "period": "2026-09",
        "status": "final",
        "value": 5.341662
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from EUMETSAT OSI SAF, Sea-Ice Index v3.0 (2026), OSI-420-a, doi:10.15770/EUM_SAF_OSI_0026, produced by the Norwegian Meteorological Institute. CC BY 4.0. Changes: extent converted from km² to million km².",
        "description": "Mean extent of Arctic sea ice in September since 1979 from EUMETSAT's OSI SAF Sea-Ice Index v3.0: the area of ocean with more than 15% ice cover. An independent European estimate made with a different algorithm from NSIDC's Sea Ice Index, so its values are higher; the two are shown side by side, never combined. Recent months come from OSI SAF's operational extension of its climate data record (OSI-438).",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "nh-extent-monthly", "bytes": 17861, "citation_full": "EUMETSAT OSI SAF, Sea-Ice Index (2026), OSI-420-a, doi:10.15770/EUM_SAF_OSI_0026", "date_accessed": "2026-10-05", "date_published": "2026-10-05", "doi": "10.15770/EUM_SAF_OSI_0026", "etag": null, "last_modified": "Mon, 05 Oct 2026 10:22:11 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "EUMETSAT Ocean and Sea Ice SAF (OSI SAF), produced by the Norwegian Meteorological Institute", "r2_url": "https://files.environmentdashboard.org/raw/1df8e747017c43d744a8be016e5a910dc7f36987d6e6c46d26a922eaab8284b0.zst", "sha256": "1df8e747017c43d744a8be016e5a910dc7f36987d6e6c46d26a922eaab8284b0", "source_id": "osisaf-sea-ice-index", "title": "EUMETSAT OSI SAF Sea-Ice Index v3.0 (OSI-420-a)", "url_download": "https://osisaf-hl.met.no/archive/osisaf/sea-ice-index/v3p0/timeseries/nh/ice_extent_nh_sii-v3p0_monthly.txt", "url_main": "https://osi-saf.eumetsat.int/products/osi-420-a", "version_producer": "3.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the September rows of ice_extent_nh_sii-v3p0_monthly.txt (OSI SAF Sea-Ice Index v3.0, Northern Hemisphere monthly mean extent in km²), created by OSI SAF on 5 October 2026. Only Septembers that had ended when the file was created are used.",
            "inputs": ["1df8e747017c43d744a8be016e5a910dc7f36987d6e6c46d26a922eaab8284b0"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/osisaf_sea_ice.py",
            "transform_sha256": "28f380a158835f270ecf4c06ffefa1110e78ea31b9ed6aaaa105f92b6dd36e2e"
          },
          {
            "description": "Converted km² to million km² (divided by 1,000,000, exact decimal arithmetic). Months marked -999 after the record starts would be published as missing.",
            "inputs": ["1df8e747017c43d744a8be016e5a910dc7f36987d6e6c46d26a922eaab8284b0"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/osisaf_sea_ice.py",
            "transform_sha256": "28f380a158835f270ecf4c06ffefa1110e78ea31b9ed6aaaa105f92b6dd36e2e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Sea ice extent: monthly mean area with more than 15% ice concentration, from the OSI SAF sea ice concentration climate data records OSI-450-a1, OSI-430-a and OSI-438. Not sea ice area, and not NSIDC's index.",
          "bunkers": null,
          "geography": "Northern Hemisphere oceans (the Arctic Ocean and surrounding seas)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["osisaf-sea-ice-index"],
      "time_basis": "calendar",
      "title": "Arctic sea ice extent in September (OSI SAF)",
      "unit": {
        "code": "million-km2",
        "label": "million square kilometres",
        "short": "million km²"
      },
      "vintage": "3.0"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ATA"],
      "export_sha256": "ce30f147a114d584a7e09716538a49acc466072df4e458ce3a27b767b632ed80",
      "geo_coverage": "global-only",
      "id": "sea-level-contribution.imbie-2026.antarctica",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "ATA",
        "period": "2023-12",
        "status": "final",
        "value": 13.27631111
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IMBIE: Otosaka et al. (2026), Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0), NERC EDS UK Polar Data Centre, doi:10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0; Otosaka et al. (2026), Scientific Data 13, 1301, doi:10.1038/s41597-026-08088-0. Contains public sector information licensed under the Open Government Licence v3.0. Changes: sign flipped from mass balance (negative for ice loss) to contribution to sea level (positive for a rise).",
        "description": "How much the Antarctic Ice Sheet's loss of ice has added to global mean sea level each month from January 1979 to December 2023, from the IMBIE team's reconciliation of satellite surveys, with the one-sigma uncertainty. IMBIE converts 360 Gt of ice to 1 mm of sea level.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0",
          "spdx": "OGL-UK-3.0",
          "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "antarctica-gt", "bytes": 83257, "citation_full": "Otosaka, I., Shepherd, A., Amory, C., Horwath, M., King, M., Nowicki, S., Payne, A., Rignot, E., Sørensen, L., Schlegel, N., Simon, K., Smith, B., Sutterley, T., van den Broeke, M., Velicogna, I., A, G., Agosta, C., Ditmar, P., Döhne, T., … Wouters, B. (2026). Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "etag": null, "last_modified": "Mon, 06 Jul 2026 10:07:40 GMT", "licence": {"name": "Open Government Licence v3.0", "spdx": "OGL-UK-3.0", "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "IMBIE Team (led from Northumbria University); archived by the NERC EDS UK Polar Data Centre", "r2_url": "https://files.environmentdashboard.org/raw/cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2.zst", "sha256": "cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2", "source_id": "imbie-2026", "title": "Mass balance of the Greenland and Antarctic ice sheets from the 1970s to 2023 (IMBIE 2026)", "url_download": "https://ramadda.data.bas.ac.uk/repository/entry/get/imbie3_antarctica_Gt_partitioned.csv?entryid=synth%3A128c5e33-5224-4197-82f0-19dcc95b80a0%3AL2ltYmllM19hbnRhcmN0aWNhX0d0X3BhcnRpdGlvbmVkLmNzdg%3D%3D", "url_main": "https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/02074", "version_producer": "1.0", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "antarctica-mm", "bytes": 89834, "citation_full": "Otosaka, I., Shepherd, A., Amory, C., Horwath, M., King, M., Nowicki, S., Payne, A., Rignot, E., Sørensen, L., Schlegel, N., Simon, K., Smith, B., Sutterley, T., van den Broeke, M., Velicogna, I., A, G., Agosta, C., Ditmar, P., Döhne, T., … Wouters, B. (2026). Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "etag": null, "last_modified": "Mon, 06 Jul 2026 10:07:40 GMT", "licence": {"name": "Open Government Licence v3.0", "spdx": "OGL-UK-3.0", "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "IMBIE Team (led from Northumbria University); archived by the NERC EDS UK Polar Data Centre", "r2_url": "https://files.environmentdashboard.org/raw/2a45ff6a5ca9492762421fb4dc895dc9c5a9744b91f9e7ad764c48b699cdede9.zst", "sha256": "2a45ff6a5ca9492762421fb4dc895dc9c5a9744b91f9e7ad764c48b699cdede9", "source_id": "imbie-2026", "title": "Mass balance of the Greenland and Antarctic ice sheets from the 1970s to 2023 (IMBIE 2026)", "url_download": "https://ramadda.data.bas.ac.uk/repository/entry/get/imbie3_antarctica_mm_partitioned.csv?entryid=synth%3A128c5e33-5224-4197-82f0-19dcc95b80a0%3AL2ltYmllM19hbnRhcmN0aWNhX21tX3BhcnRpdGlvbmVkLmNzdg%3D%3D", "url_main": "https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/02074", "version_producer": "1.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the 'Cumulative mass balance anomaly (mm)' column and its uncertainty from imbie3_antarctica_mm_partitioned.csv (IMBIE version 1.0), 1979-01 to 2023-12.",
            "inputs": ["cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2", "2a45ff6a5ca9492762421fb4dc895dc9c5a9744b91f9e7ad764c48b699cdede9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          },
          {
            "description": "Checked every month against imbie3_antarctica_Gt_partitioned.csv: the mm value and its uncertainty equal the Gt values divided by 360 (IMBIE's 360 Gt of ice per mm of sea level), so the mm column has the mass-balance sign, negative for a loss of ice.",
            "inputs": ["cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2", "2a45ff6a5ca9492762421fb4dc895dc9c5a9744b91f9e7ad764c48b699cdede9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          },
          {
            "description": "Flipped the sign, so that a positive value is a rise in global mean sea level. Lower and upper are the flipped value minus and plus the one-sigma uncertainty.",
            "inputs": ["cdb5f37c703af3fb36ccbf89f6ca0ba8b444817cb48ff34cc77ca7a9d9a525b2", "2a45ff6a5ca9492762421fb4dc895dc9c5a9744b91f9e7ad764c48b699cdede9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Zero just before January 1979, the start of IMBIE's Antarctic record; the first month's value is that month's change.",
          "basis": "Reconciled from 21 independent satellite estimates (altimetry, gravimetry and the input-output method) by IMBIE 2026; total mass balance, the sum of surface mass balance and ice dynamics. Positive values raise global mean sea level; 360 Gt of ice = 1 mm.",
          "bunkers": null,
          "geography": "Antarctic Ice Sheet (West and East Antarctica and the Antarctic Peninsula)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["imbie-2026"],
      "time_basis": "calendar",
      "title": "Sea level rise from the Antarctic Ice Sheet since January 1979 (IMBIE)",
      "unit": {
        "code": "mm",
        "label": "millimetres",
        "short": "mm"
      },
      "vintage": "1.0"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["GRL"],
      "export_sha256": "a20eff9303dd8f63f6593b6506d587389e195ca3c209e790f3d7ea79781ada37",
      "geo_coverage": "global-only",
      "id": "sea-level-contribution.imbie-2026.greenland",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "GRL",
        "period": "2023-12",
        "status": "final",
        "value": 17.21151609
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IMBIE: Otosaka et al. (2026), Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0), NERC EDS UK Polar Data Centre, doi:10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0; Otosaka et al. (2026), Scientific Data 13, 1301, doi:10.1038/s41597-026-08088-0. Contains public sector information licensed under the Open Government Licence v3.0. Changes: sign flipped from mass balance (negative for ice loss) to contribution to sea level (positive for a rise).",
        "description": "How much the Greenland Ice Sheet's loss of ice has added to global mean sea level each month from July 1971 to December 2023, from the IMBIE team's reconciliation of satellite surveys, with the one-sigma uncertainty. IMBIE converts 360 Gt of ice to 1 mm of sea level.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0",
          "spdx": "OGL-UK-3.0",
          "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "greenland-gt", "bytes": 101046, "citation_full": "Otosaka, I., Shepherd, A., Amory, C., Horwath, M., King, M., Nowicki, S., Payne, A., Rignot, E., Sørensen, L., Schlegel, N., Simon, K., Smith, B., Sutterley, T., van den Broeke, M., Velicogna, I., A, G., Agosta, C., Ditmar, P., Döhne, T., … Wouters, B. (2026). Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "etag": null, "last_modified": "Mon, 06 Jul 2026 10:07:40 GMT", "licence": {"name": "Open Government Licence v3.0", "spdx": "OGL-UK-3.0", "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "IMBIE Team (led from Northumbria University); archived by the NERC EDS UK Polar Data Centre", "r2_url": "https://files.environmentdashboard.org/raw/1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26.zst", "sha256": "1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26", "source_id": "imbie-2026", "title": "Mass balance of the Greenland and Antarctic ice sheets from the 1970s to 2023 (IMBIE 2026)", "url_download": "https://ramadda.data.bas.ac.uk/repository/entry/get/imbie3_greenland_Gt_partitioned.csv?entryid=synth%3A128c5e33-5224-4197-82f0-19dcc95b80a0%3AL2ltYmllM19ncmVlbmxhbmRfR3RfcGFydGl0aW9uZWQuY3N2", "url_main": "https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/02074", "version_producer": "1.0", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "greenland-mm", "bytes": 104333, "citation_full": "Otosaka, I., Shepherd, A., Amory, C., Horwath, M., King, M., Nowicki, S., Payne, A., Rignot, E., Sørensen, L., Schlegel, N., Simon, K., Smith, B., Sutterley, T., van den Broeke, M., Velicogna, I., A, G., Agosta, C., Ditmar, P., Döhne, T., … Wouters, B. (2026). Mass balance of the Greenland and Antarctic Ice Sheets from the 1970s to 2023 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "date_accessed": "2026-10-05", "date_published": "2026-07-06", "doi": "10.5285/128c5e33-5224-4197-82f0-19dcc95b80a0", "etag": null, "last_modified": "Mon, 06 Jul 2026 10:07:40 GMT", "licence": {"name": "Open Government Licence v3.0", "spdx": "OGL-UK-3.0", "url": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "IMBIE Team (led from Northumbria University); archived by the NERC EDS UK Polar Data Centre", "r2_url": "https://files.environmentdashboard.org/raw/956e645443fafc20a706504b0dab5f12a80fe8a59830cf54534942b5461c618c.zst", "sha256": "956e645443fafc20a706504b0dab5f12a80fe8a59830cf54534942b5461c618c", "source_id": "imbie-2026", "title": "Mass balance of the Greenland and Antarctic ice sheets from the 1970s to 2023 (IMBIE 2026)", "url_download": "https://ramadda.data.bas.ac.uk/repository/entry/get/imbie3_greenland_mm_partitioned.csv?entryid=synth%3A128c5e33-5224-4197-82f0-19dcc95b80a0%3AL2ltYmllM19ncmVlbmxhbmRfbW1fcGFydGl0aW9uZWQuY3N2", "url_main": "https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/02074", "version_producer": "1.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the 'Cumulative mass balance anomaly (mm)' column and its uncertainty from imbie3_greenland_mm_partitioned.csv (IMBIE version 1.0), 1971-07 to 2023-12.",
            "inputs": ["1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26", "956e645443fafc20a706504b0dab5f12a80fe8a59830cf54534942b5461c618c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          },
          {
            "description": "Checked every month against imbie3_greenland_Gt_partitioned.csv: the mm value and its uncertainty equal the Gt values divided by 360 (IMBIE's 360 Gt of ice per mm of sea level), so the mm column has the mass-balance sign, negative for a loss of ice.",
            "inputs": ["1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26", "956e645443fafc20a706504b0dab5f12a80fe8a59830cf54534942b5461c618c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          },
          {
            "description": "Flipped the sign, so that a positive value is a rise in global mean sea level. Lower and upper are the flipped value minus and plus the one-sigma uncertainty.",
            "inputs": ["1d4df7c73845ab9194fd07999ce7a7716d01ef5c9fbc2d4a464be5afc6b52a26", "956e645443fafc20a706504b0dab5f12a80fe8a59830cf54534942b5461c618c"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/imbie_2026.py",
            "transform_sha256": "890ecd9e82cc65eb0035bf87823c2a8ed59f083ca51502ecc722709a13032788"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Zero just before July 1971, the start of IMBIE's Greenland record; the first month's value is that month's change.",
          "basis": "Reconciled from 24 independent satellite estimates (altimetry, gravimetry and the input-output method) by IMBIE 2026; total mass balance, the sum of surface mass balance and ice dynamics. Positive values raise global mean sea level; 360 Gt of ice = 1 mm.",
          "bunkers": null,
          "geography": "Greenland Ice Sheet",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["imbie-2026"],
      "time_basis": "calendar",
      "title": "Sea level rise from the Greenland Ice Sheet since July 1971 (IMBIE)",
      "unit": {
        "code": "mm",
        "label": "millimetres",
        "short": "mm"
      },
      "vintage": "1.0"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "a53c8d1d47fbad249d0d0d801c7664fec63cc5369c4ffad5bcf850ac807ffb44",
      "geo_coverage": "global-only",
      "id": "sea-level-contribution.wgms-amce.glaciers-cumulative",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 26.436
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "WGMS (2026), Annual mass-change estimates for the world's glaciers, version 2026-02-10, doi:10.5904/wgms-amce-2026-02-10; Dussaillant et al. (2025), Earth System Science Data 17, 1977–2006, doi:10.5194/essd-17-1977-2025. CC BY 4.0.",
        "description": "How much the world's glaciers have added to global mean sea level since the start of hydrological year 1976 (late 1975), from the World Glacier Monitoring Service's annual estimates, with the one-sigma uncertainty.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (WGMS data policy, open access on condition of correct citation)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "amce-2026-02-10", "bytes": 53589520, "citation_full": "WGMS (2026): Annual mass-change estimates for the world's glaciers. Individual glacier time series and gridded data products. Digital media. https://doi.org/10.5904/wgms-amce-2026-02-10 Dussaillant, I., Hugonnet, R., Huss, M., Berthier, E., Bannwart, J., Paul, F., and Zemp, M. (2025): Annual mass change of the world's glaciers from 1976 to 2024 by temporal downscaling of satellite data with in-situ observations. Earth System Science Data 17(5): 1977–2006. https://doi.org/10.5194/essd-17-1977-2025", "date_accessed": "2026-10-05", "date_published": "2026-02-10", "doi": "10.5904/wgms-amce-2026-02-10", "etag": "\"331b610-64b93f5a76d99\"", "last_modified": "Tue, 24 Feb 2026 15:58:33 GMT", "licence": {"name": "CC BY 4.0 (WGMS data policy, open access on condition of correct citation)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "World Glacier Monitoring Service (WGMS), University of Zurich", "r2_url": "https://files.environmentdashboard.org/raw/b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc.zst", "sha256": "b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc", "source_id": "wgms-amce", "title": "Annual mass-change estimates for the world's glaciers (version 2026-02-10)", "url_download": "https://wgms.ch/downloads/wgms-amce-2026-02-10.zip", "url_main": "https://wgms.ch/mass_change_estimates/", "version_producer": "2026-02-10", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read global.csv from wgms-amce-2026-02-10.zip (hydrological years 1976 to 2025) and published the mmsle_cumsum column (cumulative sea level equivalent in mm) as printed.",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          },
          {
            "description": "Lower and upper are mmsle_cumsum minus and plus mmsle_cumsum_sigma, which the release README defines as the 1-sigma uncertainty (exact decimal arithmetic).",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          },
          {
            "description": "Checked that gt_cumsum and mmsle_cumsum are the running sums of gt and mmsle (within rounding), and that mmsle has the opposite sign of gt, so that positive mm is a rise in sea level.",
            "inputs": ["b88c2355650142160594c96dcb800e3fb58d82abbebd0ab2d976a458153e2ecc"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/wgms_amce.py",
            "transform_sha256": "ee23473d77b7f2d742e94cadcd66d8b346a31a8360b0db01f8f0f177a5ad1d8f"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Zero at the start of hydrological year 1976 (October 1975 in the Northern Hemisphere, April 1975 in the Southern Hemisphere, January 1976 in the tropics).",
          "basis": "All glaciers outside the Greenland and Antarctic ice sheets (Randolph Glacier Inventory 6.0 outlines), from satellite elevation changes downscaled to single years with field measurements. Hydrological years, labelled by the year they end: from 1 October in the Northern Hemisphere, 1 April in the Southern Hemisphere and 1 January in the tropics. Positive values raise global mean sea level.",
          "bunkers": null,
          "geography": "All glaciers worldwide, excluding the two ice sheets",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["wgms-amce"],
      "time_basis": "calendar",
      "title": "Sea level rise from glaciers since 1975 (WGMS)",
      "unit": {
        "code": "mm",
        "label": "millimetres",
        "short": "mm"
      },
      "vintage": "2026-02-10"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["NH"],
      "export_sha256": "98fccf18ece46587e53470636adba9d961cd6117db83a2821c4dcbef4d949c17",
      "geo_coverage": "global-only",
      "id": "snow-cover.rutgers-snow-cdr.nh-monthly",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "NH",
        "period": "2026-08",
        "status": "final",
        "value": 2.6745705806451614
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Robinson, Estilow and NOAA CDR Program (2012), NOAA Climate Data Record of Northern Hemisphere Snow Cover Extent, Version 1 (v01r01), NOAA National Centers for Environmental Information, doi:10.7289/V5N014G9, accessed 2026-10-04. This CDR was originally developed by David Robinson and colleagues for NOAA's CDR Program. Changes: weekly snow maps summed to areas and averaged by month (weighted by days), in million km².",
        "description": "Area of Northern Hemisphere land covered by snow, as a monthly mean since November 1966, computed from the weekly snow maps of the NOAA climate data record made at Rutgers University. Before June 1999 the maps were drawn by NOAA analysts from satellite images; since then they come from the US National Ice Center's daily snow and ice analysis. Nine months in 1968-1971 have no maps.",
        "kind": "derived",
        "licence": {
          "name": "No restrictions on access or use (NOAA CDR Program Open Data Policy)",
          "spdx": null,
          "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Snow_Cover_Extent_Northern_Hemisphere/UseAgreement_01B-12.pdf"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "nhsce-weekly-grid", "bytes": 24602081, "citation_full": "Robinson, David A.; Estilow, Thomas W.; and NOAA CDR Program (2012): NOAA Climate Data Record (CDR) of Northern Hemisphere (NH) Snow Cover Extent (SCE), Version 1. Weekly snow cover grids, nhsce_v01r01 NetCDF. NOAA National Centers for Environmental Information. doi:10.7289/V5N014G9 2026-10-04.", "date_accessed": "2026-10-04", "date_published": "2026-09-03", "doi": "10.7289/V5N014G9", "etag": "\"17765e1-65ab083eec103\"", "last_modified": "Fri, 04 Sep 2026 23:20:34 GMT", "licence": {"name": "No restrictions on access or use (NOAA CDR Program Open Data Policy)", "spdx": null, "url": "https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Snow_Cover_Extent_Northern_Hemisphere/UseAgreement_01B-12.pdf"}, "producer": "NOAA National Centers for Environmental Information (data by the Rutgers University Global Snow Lab)", "r2_url": "https://files.environmentdashboard.org/raw/1268766f7fbf2d314c31d16bdc6dd550d3972fb3371b1ba7d3e55638727f9d69.zst", "sha256": "1268766f7fbf2d314c31d16bdc6dd550d3972fb3371b1ba7d3e55638727f9d69", "source_id": "rutgers-snow-cdr", "title": "Northern Hemisphere snow cover extent climate data record", "url_download": "https://www.ncei.noaa.gov/data/snow-cover-extent/access/nhsce_v01r01_19661004_20260831.nc", "url_main": "https://www.ncei.noaa.gov/products/climate-data-records/snow-cover-extent", "version_producer": "v01r01 to 2026-08-31", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the 3,126 weekly maps of the NOAA snow cover extent CDR (v01r01, file created 3 September 2026, weeks ending 1966-10-10 to 2026-08-31). Each map covers the seven days from Tuesday to the Monday it is dated.",
            "inputs": ["1268766f7fbf2d314c31d16bdc6dd550d3972fb3371b1ba7d3e55638727f9d69"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/rutgers_snow.py",
            "transform_sha256": "6ae9b5115a2b497b5e6fdaf976b148acd077f9a76a9bf352e42e80aa08feae4d"
          },
          {
            "description": "Weekly extent: the summed area of the land cells marked snow covered (cell areas as printed to 0.1 km², exact arithmetic).",
            "inputs": ["1268766f7fbf2d314c31d16bdc6dd550d3972fb3371b1ba7d3e55638727f9d69"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/rutgers_snow.py",
            "transform_sha256": "6ae9b5115a2b497b5e6fdaf976b148acd077f9a76a9bf352e42e80aa08feae4d"
          },
          {
            "description": "Monthly extent: each day takes the extent of the weekly map covering it, and the month is the mean over its days, i.e. weekly extents weighted by their number of days in the month (the CDR's own week-month day counts). Converted from km² to million km².",
            "inputs": ["1268766f7fbf2d314c31d16bdc6dd550d3972fb3371b1ba7d3e55638727f9d69"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/rutgers_snow.py",
            "transform_sha256": "6ae9b5115a2b497b5e6fdaf976b148acd077f9a76a9bf352e42e80aa08feae4d"
          },
          {
            "description": "Only whole months inside the record are published. Months with a day in a week without a map are published as missing, never filled: 1968-07, 1969-06, 1969-07, 1969-08, 1969-09, 1969-10, 1971-07, 1971-08, 1971-09.",
            "inputs": ["1268766f7fbf2d314c31d16bdc6dd550d3972fb3371b1ba7d3e55638727f9d69"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/ice/rutgers_snow.py",
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        "processing": [
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            "description": "Read the table of climate impact by adoption level from the results sheet of 28 solution spreadsheets, checking the title, the four level headers and any row labels of each table cell by cell against the layout declared for that spreadsheet.",
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            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/drawdown_explorer.py",
            "transform_sha256": "d2d6ba22ffd549dc79072e61ac30455fd701b1a8bac29865aedcdde07de2ef54"
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          {
            "description": "Published 136 values for 28 solutions as the spreadsheets give them (cached cell values, billion tonnes of CO2-equivalent per year), on the warming-potential basis each table states. 2 cells that hold text instead of a number are published as missing values, with the text.",
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            "script": "pipeline/src/envdash/transforms/action/drawdown_explorer.py",
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          },
          {
            "description": "Solutions whose spreadsheets give impacts only per sub-solution, by year, or without a stated basis are not published (see the transform's notes).",
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        ],
        "published_value": null,
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          "baseline": null,
          "basis": "Project Drawdown's 2026 assessments against a 2023 baseline; impacts assume each solution's effectiveness stays as it is today. Gases are combined with 100-year or 20-year warming potentials as each spreadsheet states (dimension 'basis'); the two are not comparable.",
          "bunkers": null,
          "geography": "World, each solution as a whole (system level)",
          "gwp": null,
          "lulucf": null
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      },
      "source_ids": ["drawdown-explorer"],
      "time_basis": "calendar",
      "title": "Climate impact of solutions at different levels of adoption (Project Drawdown)",
      "unit": {
        "code": "GtCO2e/yr",
        "label": "billion tonnes of CO2-equivalent per year",
        "short": "Gt CO₂e/yr"
      },
      "vintage": "Drawdown Explorer spreadsheets on Zenodo, June–August 2026 (methodology June 2026)"
    },
    {
      "display": {
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      "downloadable": true,
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      "export_sha256": "f3032a03e8ba67055635d0965ce758fd01a24a61f7f08073e5780ca1aa6b0f63",
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        "dims": {
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        "entity": "WLD",
        "period": "2026",
        "status": "final",
        "value": 49505.0
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IUCN (2026). The IUCN Red List of Threatened Species. Version 2026-1. https://www.iucnredlist.org. Downloaded on 2026-07-28. https://doi.org/10.15468/0qnb58 accessed via GBIF.org on 2026-10-05. CC BY 4.0. Changes: threatened species counted from the species' Red List categories.",
        "description": "How many of the species assessed for the IUCN Red List are listed as Critically Endangered, Endangered or Vulnerable, in total and for nine groups, in the current version of the Red List.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/legalcode"
        },
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "checklist-2026-1", "bytes": 21140648, "citation_full": "IUCN (2026). The IUCN Red List of Threatened Species. Version 2026-1. https://www.iucnredlist.org. Downloaded on 2026-07-28. https://doi.org/10.15468/0qnb58 accessed via GBIF.org on 2026-10-05.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.15468/0qnb58", "etag": "\"14294a8-657ace70f2bf7\"", "last_modified": "Tue, 28 Jul 2026 14:46:22 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/legalcode"}, "producer": "International Union for Conservation of Nature (IUCN), published through GBIF", "r2_url": "https://files.environmentdashboard.org/raw/2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d.zst", "sha256": "2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d", "source_id": "iucn-red-list-gbif", "title": "IUCN Red List of Threatened Species, version 2026-1 (GBIF checklist)", "url_download": "https://hosted-datasets.gbif.org/datasets/iucn/iucn-2026-1.zip", "url_main": "https://www.gbif.org/dataset/19491596-35ae-4a91-9a98-85cf505f1bd3", "version_producer": "2026-1", "wayback_url": null}
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        "processing": [
          {
            "description": "Read meta.xml, eml.xml, taxon.txt and distribution.txt from the IUCN Red List version 2026-1 archive on GBIF; checked the column positions against meta.xml and the version against eml.xml's citation.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Counted accepted taxa of rank species (175,909), each by the category of its single Global distribution row: Least Concern 91,357; Data Deficient 23,037; Endangered 20,372; Vulnerable 18,186; Critically Endangered 10,947; Near Threatened 10,259; Extinct 951; near threatened 442; least concern 160; conservation dependent 115; Extinct in the Wild 83. Left out accepted taxa below species (2 subspecies, 1,133 subspecies (plantae), 967 variety).",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Threatened = Critically Endangered + Endangered + Vulnerable. The lower-case categories are assessments under IUCN's 1994 criteria (Lower Risk) and are counted as not threatened.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Groups, matched exactly on the archive's kingdom and class: Mammals: kingdom ANIMALIA, class MAMMALIA; Birds: kingdom ANIMALIA, class AVES; Amphibians: kingdom ANIMALIA, class AMPHIBIA; Reptiles: kingdom ANIMALIA, class REPTILIA; Ray-finned fishes: kingdom ANIMALIA, class ACTINOPTERYGII; Sharks, rays and chimaeras: kingdom ANIMALIA, class CHONDRICHTHYES; Insects: kingdom ANIMALIA, class INSECTA; Plants: kingdom PLANTAE; Fungi: kingdom FUNGI.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
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        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Species assessed for the IUCN Red List (global assessments); threatened = Critically Endangered, Endangered or Vulnerable. Only assessed species are counted: birds, mammals, amphibians, sharks and rays are almost fully assessed, insects, plants and fungi only in small, non-random part, so their figures describe the assessed species, not the whole group. The period is the year of the Red List version.",
          "bunkers": null,
          "geography": "World (global Red List assessments)",
          "gwp": null,
          "lulucf": null
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      },
      "source_ids": ["iucn-red-list-gbif"],
      "time_basis": "calendar",
      "title": "Number of species threatened with extinction",
      "unit": {
        "code": "species",
        "label": "species",
        "short": "species"
      },
      "vintage": "2026-1"
    },
    {
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      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "25757987b34bcae452767db4c5175f2e083cd69c4c7726ae15627447cc5ece91",
      "geo_coverage": "global-only",
      "id": "species.iucn-red-list.threatened-share",
      "latest": {
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        "dims": {
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        },
        "entity": "WLD",
        "period": "2026",
        "status": "final",
        "value": 28.142391804853645
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      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from IUCN (2026). The IUCN Red List of Threatened Species. Version 2026-1. https://www.iucnredlist.org. Downloaded on 2026-07-28. https://doi.org/10.15468/0qnb58 accessed via GBIF.org on 2026-10-05. CC BY 4.0. Changes: share of assessed species that are threatened calculated from the species' Red List categories.",
        "description": "Of the species assessed for the IUCN Red List, the percentage listed as Critically Endangered, Endangered or Vulnerable, for all assessed species and for nine groups, in the current version of the Red List.",
        "kind": "derived",
        "licence": {
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          "url": "https://creativecommons.org/licenses/by/4.0/legalcode"
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "checklist-2026-1", "bytes": 21140648, "citation_full": "IUCN (2026). The IUCN Red List of Threatened Species. Version 2026-1. https://www.iucnredlist.org. Downloaded on 2026-07-28. https://doi.org/10.15468/0qnb58 accessed via GBIF.org on 2026-10-05.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.15468/0qnb58", "etag": "\"14294a8-657ace70f2bf7\"", "last_modified": "Tue, 28 Jul 2026 14:46:22 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/legalcode"}, "producer": "International Union for Conservation of Nature (IUCN), published through GBIF", "r2_url": "https://files.environmentdashboard.org/raw/2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d.zst", "sha256": "2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d", "source_id": "iucn-red-list-gbif", "title": "IUCN Red List of Threatened Species, version 2026-1 (GBIF checklist)", "url_download": "https://hosted-datasets.gbif.org/datasets/iucn/iucn-2026-1.zip", "url_main": "https://www.gbif.org/dataset/19491596-35ae-4a91-9a98-85cf505f1bd3", "version_producer": "2026-1", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read meta.xml, eml.xml, taxon.txt and distribution.txt from the IUCN Red List version 2026-1 archive on GBIF; checked the column positions against meta.xml and the version against eml.xml's citation.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Counted accepted taxa of rank species (175,909), each by the category of its single Global distribution row: Least Concern 91,357; Data Deficient 23,037; Endangered 20,372; Vulnerable 18,186; Critically Endangered 10,947; Near Threatened 10,259; Extinct 951; near threatened 442; least concern 160; conservation dependent 115; Extinct in the Wild 83. Left out accepted taxa below species (2 subspecies, 1,133 subspecies (plantae), 967 variety).",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Threatened = Critically Endangered + Endangered + Vulnerable. The lower-case categories are assessments under IUCN's 1994 criteria (Lower Risk) and are counted as not threatened.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Groups, matched exactly on the archive's kingdom and class: Mammals: kingdom ANIMALIA, class MAMMALIA; Birds: kingdom ANIMALIA, class AVES; Amphibians: kingdom ANIMALIA, class AMPHIBIA; Reptiles: kingdom ANIMALIA, class REPTILIA; Ray-finned fishes: kingdom ANIMALIA, class ACTINOPTERYGII; Sharks, rays and chimaeras: kingdom ANIMALIA, class CHONDRICHTHYES; Insects: kingdom ANIMALIA, class INSECTA; Plants: kingdom PLANTAE; Fungi: kingdom FUNGI.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
          },
          {
            "description": "Share = threatened species / all assessed species in the group × 100 (exact decimal arithmetic), with every category, including Extinct and Data Deficient, in the denominator.",
            "inputs": ["2ed2c5f75667fa2dee9dc718406b5ba094fa9312e548934916b16c0c509ccb7d"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/nature/iucn_red_list.py",
            "transform_sha256": "704bf4c54d922f196941212fa86bb258d3adffe15ab43c56bc44e7ec0f6e9b8f"
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        ],
        "published_value": null,
        "scope": {
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          "basis": "Species assessed for the IUCN Red List (global assessments); threatened = Critically Endangered, Endangered or Vulnerable. Only assessed species are counted: birds, mammals, amphibians, sharks and rays are almost fully assessed, insects, plants and fungi only in small, non-random part, so their figures describe the assessed species, not the whole group. The period is the year of the Red List version. Denominator: all assessed species in the group, including Extinct, Extinct in the Wild and Data Deficient.",
          "bunkers": null,
          "geography": "World (global Red List assessments)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["iucn-red-list-gbif"],
      "time_basis": "calendar",
      "title": "Share of assessed species that are threatened with extinction",
      "unit": {
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        "label": "percent of assessed species",
        "short": "%"
      },
      "vintage": "2026-1"
    },
    {
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      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "399dde73263b6a62f8ea4b5e5ea5347e8c360cad34324ba094fbabf751081bbc",
      "geo_coverage": "global-only",
      "id": "sst.c3s-climate-pulse.daily-60s-60n-1991-2020",
      "latest": {
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        "period": "2026-10-03",
        "status": "final",
        "value": 0.728
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Generated using Copernicus Climate Change Service information 2026. Data source: ERA5 (Hersbach et al. 2023, doi:10.24381/cds.adbb2d47), C3S Climate Pulse. Credit: C3S/ECMWF.",
        "description": "Daily mean sea-surface temperature over the ocean between 60° S and 60° N since 1 January 1979 from the ERA5 reanalysis, as the difference from the 1991–2020 average for the same day of the year. The newest days can be preliminary.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (ERA5, as licensed on the C3S Climate Data Store)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "sea-surface-temperature-daily", "bytes": 656402, "citation_full": "Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.adbb2d47 (Accessed on 2026-10-05)", "date_accessed": "2026-10-05", "date_published": "2026-10-05", "doi": "10.24381/cds.adbb2d47", "etag": "W/\"6ac32360-a0412\"", "last_modified": "Mon, 05 Oct 2026 04:11:12 GMT", "licence": {"name": "CC BY 4.0 (ERA5, as licensed on the C3S Climate Data Store)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Copernicus Climate Change Service (C3S), implemented by ECMWF for the European Commission", "r2_url": "https://files.environmentdashboard.org/raw/a1aeb7de1f8d2c2c77f1ba0bb026e2447a82b3b2449f7e8edc733ed641da9b6b.zst", "sha256": "a1aeb7de1f8d2c2c77f1ba0bb026e2447a82b3b2449f7e8edc733ed641da9b6b", "source_id": "c3s-climate-pulse", "title": "C3S Climate Pulse daily global temperatures (ERA5)", "url_download": "https://sites.ecmwf.int/data/climatepulse/data/series/era5_daily_series_sst_60S-60N_ocean.csv", "url_main": "https://pulse.climate.copernicus.eu/", "version_producer": "2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the Climate Pulse daily series of 60°S–60°N sea-surface temperature from ERA5, last updated by C3S on 05 October 2026, from 1979-01-01 to 2026-10-03.",
            "inputs": ["a1aeb7de1f8d2c2c77f1ba0bb026e2447a82b3b2449f7e8edc733ed641da9b6b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_climate_pulse.py",
            "transform_sha256": "20988e29489d4b585261de3a2f60b7df2a2cd3d8646521020647b8f0dc7e5d8a"
          },
          {
            "description": "Published the producer's anomaly from its smoothed 1991–2020 daily climatology (column ano_91-20) unchanged, rounded as printed (three decimals).",
            "inputs": ["a1aeb7de1f8d2c2c77f1ba0bb026e2447a82b3b2449f7e8edc733ed641da9b6b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_climate_pulse.py",
            "transform_sha256": "20988e29489d4b585261de3a2f60b7df2a2cd3d8646521020647b8f0dc7e5d8a"
          },
          {
            "description": "Kept the file's status of each day: 0 day(s) marked PRELIMINARY are published as preliminary, because the file states that their values will likely change slightly once the final ERA5 data for the day are available.",
            "inputs": ["a1aeb7de1f8d2c2c77f1ba0bb026e2447a82b3b2449f7e8edc733ed641da9b6b"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_climate_pulse.py",
            "transform_sha256": "20988e29489d4b585261de3a2f60b7df2a2cd3d8646521020647b8f0dc7e5d8a"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1991–2020 daily climatology of this dataset, smoothed by C3S",
          "basis": "ERA5 reanalysis; daily mean sea-surface temperature.",
          "bunkers": null,
          "geography": "Ocean between 60° S and 60° N (area mean)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["c3s-climate-pulse"],
      "time_basis": "calendar",
      "title": "Sea-surface temperature against 1991–2020, 60° S–60° N, daily (ERA5 Climate Pulse)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "2026-10-05"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "5b56234871df04b6c880d942f023e3b4cafcf3037cc90e2e201f87a074faa9f1",
      "geo_coverage": "global-only",
      "id": "sst.hadsst4.annual-1961-1990",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 0.839189
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from HadSST.4.2.0.0. HadSST.4.2.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadsst4 on 2026-10-05 and are © British Crown Copyright, Met Office 2025, provided under an Open Government Licence, https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ Changes: range shown as the anomaly minus and plus the published total uncertainty (one standard deviation).",
        "description": "Global mean sea-surface temperature for each complete year since 1850, from ship and buoy measurements, as the difference from the 1961–1990 average, with a one-standard-deviation range.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0 (Crown copyright)",
          "spdx": "OGL-UK-3.0",
          "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-annual", "bytes": 14097, "citation_full": "Kennedy, J. J., Rayner, N. A., Atkinson, C. P., & Killick, R. E., 2019. An Ensemble Data Set of Sea Surface Temperature Change from 1850: The Met Office Hadley Centre HadSST.4.0.0.0 Data Set. Journal of Geophysical Research: Atmospheres, 124. https://doi.org/10.1029/2018JD029867. Sandford, C., and Rayner, N., 2026. Addressing the World War 2 Warm Anomaly in HadSST.4.2.0.0. International Journal of Climatology. https://doi.org/10.1002/joc.70388.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1029/2018JD029867", "etag": "\"3711-65b81f9231a40\"", "last_modified": "Tue, 15 Sep 2026 09:14:09 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Met Office Hadley Centre", "r2_url": "https://files.environmentdashboard.org/raw/38dd997dc6716cdae019e41d37a5436178d07554a7d69287411904c14e67fa01.zst", "sha256": "38dd997dc6716cdae019e41d37a5436178d07554a7d69287411904c14e67fa01", "source_id": "hadsst4", "title": "HadSST.4 sea-surface temperature anomalies", "url_download": "https://www.metoffice.gov.uk/hadobs/hadsst4/data/data/HadSST.4.2.0.0_annual_GLOBE.csv", "url_main": "https://www.metoffice.gov.uk/hadobs/hadsst4/", "version_producer": "4.2.0.0", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "global-monthly", "bytes": 172297, "citation_full": "Kennedy, J. J., Rayner, N. A., Atkinson, C. P., & Killick, R. E., 2019. An Ensemble Data Set of Sea Surface Temperature Change from 1850: The Met Office Hadley Centre HadSST.4.0.0.0 Data Set. Journal of Geophysical Research: Atmospheres, 124. https://doi.org/10.1029/2018JD029867. Sandford, C., and Rayner, N., 2026. Addressing the World War 2 Warm Anomaly in HadSST.4.2.0.0. International Journal of Climatology. https://doi.org/10.1002/joc.70388.", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.1029/2018JD029867", "etag": "\"2a109-65b81f9231a40\"", "last_modified": "Tue, 15 Sep 2026 09:14:09 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Met Office Hadley Centre", "r2_url": "https://files.environmentdashboard.org/raw/07444a0e9be79dfe546f29d34e8dbbf561036e172b89eea45c3487c2b58dada6.zst", "sha256": "07444a0e9be79dfe546f29d34e8dbbf561036e172b89eea45c3487c2b58dada6", "source_id": "hadsst4", "title": "HadSST.4 sea-surface temperature anomalies", "url_download": "https://www.metoffice.gov.uk/hadobs/hadsst4/data/data/HadSST.4.2.0.0_monthly_GLOBE.csv", "url_main": "https://www.metoffice.gov.uk/hadobs/hadsst4/", "version_producer": "4.2.0.0", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the global annual series of HadSST.4.2.0.0 (sea-surface temperature anomaly in kelvin relative to 1961–1990, as published; a difference of 1 K equals 1 °C, so the values are unchanged). The file holds complete years, 1850 to 2025; each was confirmed to have all 12 months in the global monthly file.",
            "inputs": ["38dd997dc6716cdae019e41d37a5436178d07554a7d69287411904c14e67fa01", "07444a0e9be79dfe546f29d34e8dbbf561036e172b89eea45c3487c2b58dada6"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/hadsst4.py",
            "transform_sha256": "d556dbda6cbcbcbc49a8268c77c5c8258ccb5de152fb04cb6fe453af2d2f716e"
          },
          {
            "description": "Lower and upper are the anomaly minus and plus the file's total_uncertainty, which the Product User Guide defines as the 1σ uncertainty combining uncorrelated measurement, sampling, correlated measurement, bias-correction and coverage uncertainties. The file's 95% bounds cover bias uncertainty only and are not used.",
            "inputs": ["38dd997dc6716cdae019e41d37a5436178d07554a7d69287411904c14e67fa01", "07444a0e9be79dfe546f29d34e8dbbf561036e172b89eea45c3487c2b58dada6"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/hadsst4.py",
            "transform_sha256": "d556dbda6cbcbcbc49a8268c77c5c8258ccb5de152fb04cb6fe453af2d2f716e"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1961–1990, the dataset's own baseline (as published)",
          "basis": "In situ sea-surface temperature from ships and buoys, adjusted for changes in how it was measured.",
          "bunkers": null,
          "geography": "Global ocean, averaged over 5° grid boxes that have measurements (not interpolated)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["hadsst4"],
      "time_basis": "calendar",
      "title": "Global sea-surface temperature against 1961–1990 (HadSST4)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "4.2.0.0"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "a65e6612d15f7d9ddb433f79e544082019eb8d6f3addf5b0f45df76fcf9daa86",
      "geo_coverage": "global-only",
      "id": "temp.c3s-climate-pulse.daily-1991-2020",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2026-10-03",
        "status": "preliminary",
        "value": 0.683
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Generated using Copernicus Climate Change Service information 2026. Data source: ERA5 (Hersbach et al. 2023, doi:10.24381/cds.adbb2d47), C3S Climate Pulse. Credit: C3S/ECMWF.",
        "description": "Daily global mean air temperature at 2 metres since 1 January 1940 from the ERA5 reanalysis, as the difference from the 1991–2020 average for the same day of the year. The newest days are preliminary.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (ERA5, as licensed on the C3S Climate Data Store)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "air-temperature-daily", "bytes": 1197707, "citation_full": "Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.adbb2d47 (Accessed on 2026-10-05)", "date_accessed": "2026-10-05", "date_published": "2026-10-05", "doi": "10.24381/cds.adbb2d47", "etag": "W/\"6ac32360-12468b\"", "last_modified": "Mon, 05 Oct 2026 04:11:12 GMT", "licence": {"name": "CC BY 4.0 (ERA5, as licensed on the C3S Climate Data Store)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Copernicus Climate Change Service (C3S), implemented by ECMWF for the European Commission", "r2_url": "https://files.environmentdashboard.org/raw/dd25b3cec47bf2efa4d9da022aada9e370e8ed25914b23c3c119ed484788e0b6.zst", "sha256": "dd25b3cec47bf2efa4d9da022aada9e370e8ed25914b23c3c119ed484788e0b6", "source_id": "c3s-climate-pulse", "title": "C3S Climate Pulse daily global temperatures (ERA5)", "url_download": "https://sites.ecmwf.int/data/climatepulse/data/series/era5_daily_series_2t_global.csv", "url_main": "https://pulse.climate.copernicus.eu/", "version_producer": "2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the Climate Pulse daily series of global 2 m air temperature from ERA5, last updated by C3S on 05 October 2026, from 1940-01-01 to 2026-10-03.",
            "inputs": ["dd25b3cec47bf2efa4d9da022aada9e370e8ed25914b23c3c119ed484788e0b6"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_climate_pulse.py",
            "transform_sha256": "20988e29489d4b585261de3a2f60b7df2a2cd3d8646521020647b8f0dc7e5d8a"
          },
          {
            "description": "Published the producer's anomaly from its smoothed 1991–2020 daily climatology (column ano_91-20) unchanged, rounded as printed (three decimals).",
            "inputs": ["dd25b3cec47bf2efa4d9da022aada9e370e8ed25914b23c3c119ed484788e0b6"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_climate_pulse.py",
            "transform_sha256": "20988e29489d4b585261de3a2f60b7df2a2cd3d8646521020647b8f0dc7e5d8a"
          },
          {
            "description": "Kept the file's status of each day: 1 day(s) marked PRELIMINARY are published as preliminary, because the file states that their values will likely change slightly once the final ERA5 data for the day are available.",
            "inputs": ["dd25b3cec47bf2efa4d9da022aada9e370e8ed25914b23c3c119ed484788e0b6"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_climate_pulse.py",
            "transform_sha256": "20988e29489d4b585261de3a2f60b7df2a2cd3d8646521020647b8f0dc7e5d8a"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1991–2020 daily climatology of this dataset, smoothed by C3S",
          "basis": "ERA5 reanalysis; daily mean of hourly 2 m air temperature from 00 to 23 UTC.",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["c3s-climate-pulse"],
      "time_basis": "calendar",
      "title": "Global air temperature against 1991–2020, daily (ERA5 Climate Pulse)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "2026-10-05"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "0ee9c230b509fb3b73a92c701596602681be48839599dd1405e9aeca1b05f5d1",
      "geo_coverage": "global-only",
      "id": "temp.c3s-era5-bulletin.monthly-1850-1900",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2026-08",
        "status": "final",
        "value": 1.6457
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Generated using Copernicus Climate Change Service information 2026. Data source: ERA5 (Hersbach et al. 2023, doi:10.24381/cds.f17050d7), C3S Climate Bulletin. Credit: C3S/ECMWF.",
        "description": "Global mean surface air temperature for each month since January 1940 from the ERA5 reanalysis, as the difference from the 1850–1900 level that C3S estimates for that calendar month. Published monthly with the Copernicus Climate Bulletin.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 (ERA5, as licensed on the C3S Climate Data Store)",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
        "notice": "Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-allmonths", "bytes": 51658, "citation_full": "Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 2026-10-04)", "date_accessed": "2026-10-04", "date_published": "2026-09-03", "doi": "10.24381/cds.f17050d7", "etag": "\"6aa1348e-c9ca\"", "last_modified": "Wed, 09 Sep 2026 10:27:26 GMT", "licence": {"name": "CC BY 4.0 (ERA5, as licensed on the C3S Climate Data Store)", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Copernicus Climate Change Service (C3S), implemented by ECMWF for the European Commission", "r2_url": "https://files.environmentdashboard.org/raw/3702df655287919f77ae09e62826b7874634cd0751f331cd604ac136c89fd144.zst", "sha256": "3702df655287919f77ae09e62826b7874634cd0751f331cd604ac136c89fd144", "source_id": "c3s-era5-bulletin", "title": "C3S Climate Bulletin global surface air temperature (ERA5)", "url_download": "https://climate.copernicus.eu/sites/default/files/2026-09/C3S_Bulletin_temp_202608_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv", "url_main": "https://climate.copernicus.eu/climate-bulletin", "version_producer": "2026-08", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the C3S Climate Bulletin file of global monthly ERA5 surface air temperature for data to 2026-08, last updated by C3S on 03 September 2026.",
            "inputs": ["3702df655287919f77ae09e62826b7874634cd0751f331cd604ac136c89fd144"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_era5_bulletin.py",
            "transform_sha256": "5845d2daa53ffa40306f9bf95f55eae21a0d6127141aa1683e8ee72eac96f106"
          },
          {
            "description": "Published C3S's own anomaly from 1850–1900 (column ano_pi) unchanged. C3S computes it as the anomaly from 1991–2020 plus a fixed offset per calendar month (offset_pi), its estimate of the warming from 1850–1900 to 1991–2020 from Berkeley Earth, HadCRUT5 and NOAAGlobalTemp, because ERA5 starts in 1940. Checked on every row that ano_pi equals ano_91-20 plus offset_pi. The offsets in this file (°C): January 0.9600; February 0.9600; March 0.9500; April 0.9100; May 0.8700; June 0.8300; July 0.8000; August 0.8000; September 0.8100; October 0.8500; November 0.8900; December 0.9300.",
            "inputs": ["3702df655287919f77ae09e62826b7874634cd0751f331cd604ac136c89fd144"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_era5_bulletin.py",
            "transform_sha256": "5845d2daa53ffa40306f9bf95f55eae21a0d6127141aa1683e8ee72eac96f106"
          },
          {
            "description": "The file has no status column and marks no month as preliminary, so no month is labelled preliminary here. The latest months rest on ERA5's preliminary data, which C3S may revise; a later Bulletin file then carries the revised values.",
            "inputs": ["3702df655287919f77ae09e62826b7874634cd0751f331cd604ac136c89fd144"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/c3s_era5_bulletin.py",
            "transform_sha256": "5845d2daa53ffa40306f9bf95f55eae21a0d6127141aa1683e8ee72eac96f106"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1850–1900, through C3S's fixed offset per calendar month from 1991–2020 (offset_pi, 0.80 to 0.96 °C), estimated from Berkeley Earth, HadCRUT5 and NOAAGlobalTemp",
          "basis": "ERA5 reanalysis, monthly mean air temperature at 2 metres.",
          "bunkers": null,
          "geography": "Global mean (0–360° E, 90° S–90° N)",
          "gwp": null,
          "lulucf": null
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      },
      "source_ids": ["c3s-era5-bulletin"],
      "time_basis": "calendar",
      "title": "Global surface air temperature above 1850–1900, monthly (ERA5, C3S)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "2026-08"
    },
    {
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      "geo_coverage": "global-only",
      "id": "temp.gistemp-v4.annual-1880-1899",
      "latest": {
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        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 1.4205
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from NASA's Goddard Institute for Space Studies GISTEMP v4 data (GISTEMP Team), accessed 2026-10-04. Changes: annual anomalies re-based from 1951–1980 to the 1880–1899 mean of the same dataset; 2026 left out as a partial year.",
        "description": "Global mean surface temperature for each complete year since 1880, as the difference from the 1880–1899 average of the same dataset. NASA GISS has no observations before 1880, so this series is not relative to 1850–1900.",
        "kind": "series",
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          "url": "https://www.copyright.gov/title17/92chap1.html#105"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "glb-monthly", "bytes": 12887, "citation_full": "GISTEMP Team, 2026: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2026-10-04 at https://data.giss.nasa.gov/gistemp/. Lenssen, N., G.A. Schmidt, M. Hendrickson, P. Jacobs, M. Menne, and R. Ruedy, 2024: A GISTEMPv4 observational uncertainty ensemble. J. Geophys. Res. Atmos., 129, no. 17, e2023JD040179, doi:10.1029/2023JD040179.", "date_accessed": "2026-10-04", "date_published": null, "doi": null, "etag": "\"3257-65af2da6d72dd\"", "last_modified": "Tue, 08 Sep 2026 06:29:13 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NASA Goddard Institute for Space Studies", "r2_url": "https://files.environmentdashboard.org/raw/c9ce0750ca93a8241c42fe86cd5bf54d07b28b21ae650b0ae49a206907018cd9.zst", "sha256": "c9ce0750ca93a8241c42fe86cd5bf54d07b28b21ae650b0ae49a206907018cd9", "source_id": "gistemp-v4", "title": "GISS Surface Temperature Analysis, version 4 (GISTEMP v4)", "url_download": "https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv", "url_main": "https://data.giss.nasa.gov/gistemp/", "version_producer": "v4 2026-08", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the January–December mean (J-D) of GISTEMP v4's global Land-Ocean Temperature Index table GLB.Ts+dSST.csv (°C relative to 1951–1980, two decimals).",
            "inputs": ["c9ce0750ca93a8241c42fe86cd5bf54d07b28b21ae650b0ae49a206907018cd9"],
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            "script": "pipeline/src/envdash/transforms/temperature/gistemp.py",
            "transform_sha256": "8cd1cacfd44b039ea84fa61167c98e2840f2fe9a8fcf7891b03d5c1747ddfbf4"
          },
          {
            "description": "Left out 2026: the table has 8 of its 12 months and prints *** for its J-D mean. A year is published only when GISS prints its J-D value, which it does once all twelve months are in.",
            "inputs": ["c9ce0750ca93a8241c42fe86cd5bf54d07b28b21ae650b0ae49a206907018cd9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/gistemp.py",
            "transform_sha256": "8cd1cacfd44b039ea84fa61167c98e2840f2fe9a8fcf7891b03d5c1747ddfbf4"
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          {
            "description": "Re-based to the dataset's own 1880–1899 mean, the first step of the method in the GISTEMP FAQ: subtracted the mean of the 20 J-D values 1880–1899, -0.2305 °C relative to 1951–1980 (exact decimal arithmetic on the printed values), from every year. GISS has no observations before 1880. The FAQ's second step, about 0.038 °C estimated from the HadCRUT, NOAA and Berkeley Earth analyses to reach 1850–1900, is not applied, so these values are relative to 1880–1899, not 1850–1900.",
            "inputs": ["c9ce0750ca93a8241c42fe86cd5bf54d07b28b21ae650b0ae49a206907018cd9"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/gistemp.py",
            "transform_sha256": "8cd1cacfd44b039ea84fa61167c98e2840f2fe9a8fcf7891b03d5c1747ddfbf4"
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        ],
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          "basis": "GISTEMP v4 Land-Ocean Temperature Index: NOAA GHCN v4 weather-station air temperatures over land and NOAA ERSST v5 sea-surface temperatures over the ocean.",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
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        }
      },
      "source_ids": ["gistemp-v4"],
      "time_basis": "calendar",
      "title": "Global surface temperature above 1880–1899 (GISTEMP v4)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "v4 2026-08"
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    {
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      "downloadable": true,
      "entities": ["WLD"],
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      "latest": {
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        "period": "2025",
        "status": "final",
        "value": 1.432652257
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        "attribution": "Calculated by Environment Dashboard from HadCRUT.5.2.0.0. HadCRUT.5.2.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadcrut5 on 2026-10-04 and are © British Crown Copyright, Met Office 2026, provided under an Open Government License, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ Changes: anomalies and their 95% range re-based from 1961–1990 to the 1850–1900 mean of the same dataset; 2026 left out as a partial year.",
        "description": "Global mean near-surface temperature for each complete year since 1850, as the difference from the 1850–1900 average of the same dataset, with the 95% range.",
        "kind": "series",
        "licence": {
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          "spdx": "OGL-UK-3.0",
          "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
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        ],
        "processing": [
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            "description": "Read the global annual and global monthly summary series of HadCRUT.5.2.0.0 (analysis ensemble means; anomalies relative to 1961–1990 with the 2.5% and 97.5% limits).",
            "inputs": ["7f750b673bb34aad722736ee21f122b5ea692c99877fa0b1066df65e51f32c04", "dd4449a3e25b75396ec4f0445f8647e5b9f5a10f3993929fb82918f3ec135dd1"],
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            "script": "pipeline/src/envdash/transforms/temperature/hadcrut5.py",
            "transform_sha256": "94194861a1d4f1e5a07e8e7cf684084ecfb73690911b7de12c7bafc62bc34c18"
          },
          {
            "description": "Excluded 2026: the monthly file has 8 of its 12 months, so the annual file's value for it is a partial-year average. A year is published only when all 12 months are in the monthly file.",
            "inputs": ["7f750b673bb34aad722736ee21f122b5ea692c99877fa0b1066df65e51f32c04", "dd4449a3e25b75396ec4f0445f8647e5b9f5a10f3993929fb82918f3ec135dd1"],
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            "script": "pipeline/src/envdash/transforms/temperature/hadcrut5.py",
            "transform_sha256": "94194861a1d4f1e5a07e8e7cf684084ecfb73690911b7de12c7bafc62bc34c18"
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          {
            "description": "Re-based to the dataset's own 1850–1900 mean: subtracted the mean of the 51 annual anomalies 1850–1900, -0.359435557 °C relative to 1961–1990 (exact decimal arithmetic on the printed values), from every anomaly and from both limits of the 95% range.",
            "inputs": ["7f750b673bb34aad722736ee21f122b5ea692c99877fa0b1066df65e51f32c04", "dd4449a3e25b75396ec4f0445f8647e5b9f5a10f3993929fb82918f3ec135dd1"],
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            "script": "pipeline/src/envdash/transforms/temperature/hadcrut5.py",
            "transform_sha256": "94194861a1d4f1e5a07e8e7cf684084ecfb73690911b7de12c7bafc62bc34c18"
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        "published_value": null,
        "scope": {
          "baseline": "1850–1900 mean of this dataset",
          "basis": "Blend of land air temperature (CRUTEM5) and sea-surface temperature (HadSST4), with statistical infilling of data-sparse regions (HadCRUT5 analysis).",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
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        }
      },
      "source_ids": ["hadcrut5"],
      "time_basis": "calendar",
      "title": "Global surface temperature above 1850–1900 (HadCRUT5)",
      "unit": {
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        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "5.2.0.0"
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    {
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      "downloadable": true,
      "entities": ["WLD"],
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      "id": "temp.noaaglobaltemp-v6.annual-1850-1900",
      "latest": {
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        "attribution": "Calculated by Environment Dashboard from NOAA National Centers for Environmental Information NOAAGlobalTemp version 6.1.0.202608 (Huang, Yin, Menne & Vose), doi:10.25921/vvaa-wq11, accessed 2026-10-04. Changes: annual anomalies re-based from 1991–2020 to the 1850–1900 mean of the same dataset; 2026 left out as a partial year.",
        "description": "Global mean surface temperature for each complete year since 1850, as the difference from the 1850–1900 average of the same dataset.",
        "kind": "series",
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          "url": "https://www.copyright.gov/title17/92chap1.html#105"
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        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-annual", "bytes": 11505, "citation_full": "Huang, Boyin; Yin, Xungang; Menne, Matthew J.; and Vose, Russell S. 2026. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.1. Areal-average time series. NOAA National Centers for Environmental Information. https://doi.org/10.25921/vvaa-wq11. Accessed 2026-10-04.", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.25921/vvaa-wq11", "etag": "\"2cf1-65afaa2263240\"", "last_modified": "Tue, 08 Sep 2026 15:46:09 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NOAA National Centers for Environmental Information", "r2_url": "https://files.environmentdashboard.org/raw/ce98047f148087859faa7996987c2b717baad14ce0e58cbe6a4b6c41d9f2a666.zst", "sha256": "ce98047f148087859faa7996987c2b717baad14ce0e58cbe6a4b6c41d9f2a666", "source_id": "noaaglobaltemp-v6", "title": "NOAA Global Surface Temperature (NOAAGlobalTemp), version 6.1", "url_download": "https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.land_ocean.90S.90N.v6.1.0.202608.asc", "url_main": "https://www.ncei.noaa.gov/products/land-based-station/noaa-global-temp", "version_producer": "6.1.0.202608", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "global-monthly", "bytes": 220480, "citation_full": "Huang, Boyin; Yin, Xungang; Menne, Matthew J.; and Vose, Russell S. 2026. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.1. Areal-average time series. NOAA National Centers for Environmental Information. https://doi.org/10.25921/vvaa-wq11. Accessed 2026-10-04.", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.25921/vvaa-wq11", "etag": "\"35d40-65afaa244b6c0\"", "last_modified": "Tue, 08 Sep 2026 15:46:11 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NOAA National Centers for Environmental Information", "r2_url": "https://files.environmentdashboard.org/raw/76cc32238bcb7d058703841f8a26731594a03e3d07daf41b82736c06e96f42dc.zst", "sha256": "76cc32238bcb7d058703841f8a26731594a03e3d07daf41b82736c06e96f42dc", "source_id": "noaaglobaltemp-v6", "title": "NOAA Global Surface Temperature (NOAAGlobalTemp), version 6.1", "url_download": "https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc", "url_main": "https://www.ncei.noaa.gov/products/land-based-station/noaa-global-temp", "version_producer": "6.1.0.202608", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "arctic-annual", "bytes": 11505, "citation_full": "Huang, Boyin; Yin, Xungang; Menne, Matthew J.; and Vose, Russell S. 2026. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.1. Areal-average time series. NOAA National Centers for Environmental Information. https://doi.org/10.25921/vvaa-wq11. Accessed 2026-10-04.", "date_accessed": "2026-10-04", "date_published": null, "doi": "10.25921/vvaa-wq11", "etag": "\"2cf1-65afaa2263240\"", "last_modified": "Tue, 08 Sep 2026 15:46:09 GMT", "licence": {"name": "Public domain (work of the US federal government)", "spdx": null, "url": "https://www.copyright.gov/title17/92chap1.html#105"}, "producer": "NOAA National Centers for Environmental Information", "r2_url": "https://files.environmentdashboard.org/raw/19f707255a4fe95bc7da1a93584541cc75668828067423825c7eff1c6708f5b2.zst", "sha256": "19f707255a4fe95bc7da1a93584541cc75668828067423825c7eff1c6708f5b2", "source_id": "noaaglobaltemp-v6", "title": "NOAA Global Surface Temperature (NOAAGlobalTemp), version 6.1", "url_download": "https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.land_ocean.60N.90N.v6.1.0.202608.asc", "url_main": "https://www.ncei.noaa.gov/products/land-based-station/noaa-global-temp", "version_producer": "6.1.0.202608", "wayback_url": null},
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        "processing": [
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            "description": "Read the global (90°S–90°N) annual land-ocean anomaly of NOAAGlobalTemp v6.1.0, release 202608 (kelvin relative to 1991–2020, as the readme states; a difference of 1 K equals 1 °C). The error-variance columns are all -999 and are not used.",
            "inputs": ["ce98047f148087859faa7996987c2b717baad14ce0e58cbe6a4b6c41d9f2a666", "76cc32238bcb7d058703841f8a26731594a03e3d07daf41b82736c06e96f42dc", "19f707255a4fe95bc7da1a93584541cc75668828067423825c7eff1c6708f5b2", "2595d84ca80c3418bb55330e36356c3b1770d40832de4aa9b1c67d1895ec189f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/noaaglobaltemp.py",
            "transform_sha256": "94517bf2e4124d31a70c7b68351a2681f28ce5bf7843a328d2ac4e1e7d25070a"
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          {
            "description": "Confirmed one release: the global annual, global monthly and 60°N–90°N annual file names all carry v6.1.0.202608, and the monthly file's last month is 2026-08.",
            "inputs": ["ce98047f148087859faa7996987c2b717baad14ce0e58cbe6a4b6c41d9f2a666", "76cc32238bcb7d058703841f8a26731594a03e3d07daf41b82736c06e96f42dc", "19f707255a4fe95bc7da1a93584541cc75668828067423825c7eff1c6708f5b2", "2595d84ca80c3418bb55330e36356c3b1770d40832de4aa9b1c67d1895ec189f"],
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          },
          {
            "description": "Left out 2026: the release runs to month 8 of 2026, so the annual file's value for it averages only those months. Earlier years are complete: the file names give the month of the latest data.",
            "inputs": ["ce98047f148087859faa7996987c2b717baad14ce0e58cbe6a4b6c41d9f2a666", "76cc32238bcb7d058703841f8a26731594a03e3d07daf41b82736c06e96f42dc", "19f707255a4fe95bc7da1a93584541cc75668828067423825c7eff1c6708f5b2", "2595d84ca80c3418bb55330e36356c3b1770d40832de4aa9b1c67d1895ec189f"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/temperature/noaaglobaltemp.py",
            "transform_sha256": "94517bf2e4124d31a70c7b68351a2681f28ce5bf7843a328d2ac4e1e7d25070a"
          },
          {
            "description": "Re-based to the dataset's own 1850–1900 mean: subtracted the mean of the 51 annual anomalies 1850–1900, -0.7768811568627451 K relative to 1991–2020 (exact decimal arithmetic on the printed values), from every year.",
            "inputs": ["ce98047f148087859faa7996987c2b717baad14ce0e58cbe6a4b6c41d9f2a666", "76cc32238bcb7d058703841f8a26731594a03e3d07daf41b82736c06e96f42dc", "19f707255a4fe95bc7da1a93584541cc75668828067423825c7eff1c6708f5b2", "2595d84ca80c3418bb55330e36356c3b1770d40832de4aa9b1c67d1895ec189f"],
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            "script": "pipeline/src/envdash/transforms/temperature/noaaglobaltemp.py",
            "transform_sha256": "94517bf2e4124d31a70c7b68351a2681f28ce5bf7843a328d2ac4e1e7d25070a"
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        ],
        "published_value": null,
        "scope": {
          "baseline": "1850–1900 mean of this dataset",
          "basis": "NOAAGlobalTemp 6.1: NOAA GHCN monthly land-station temperatures merged with ERSST version 6 sea-surface temperatures, with gaps filled by an artificial neural network.",
          "bunkers": null,
          "geography": "Global mean (90° S–90° N)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["noaaglobaltemp-v6"],
      "time_basis": "calendar",
      "title": "Global surface temperature above 1850–1900 (NOAAGlobalTemp)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "6.1.0.202608"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATF", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BVT", "BWA", "CAF", "CAN", "CCK", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HMD", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IOT", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAF", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "UMI", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "ef3d3c24e0626e7d85439949683cb3df43516c97578f75017aa14138011cc80c",
      "geo_coverage": "mixed",
      "id": "temp.wb-cckp.era5-annual-1991-2020",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 0.6
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from The World Bank: Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree (doi:10.57966/128g-6s70): Copernicus Climate Change Service ERA5, and The World Bank: Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree (doi:10.57966/b54h-7s87): CMIP6 multi-model ensemble (World Climate Research Programme). Changes: annual mean temperatures expressed as the difference from CCKP's published 1991–2020 mean for the same area.",
        "description": "How much warmer or cooler each year since 1950 was than the 1991–2020 average, for each country and for the world, from the ERA5 reanalysis as aggregated by the World Bank's Climate Change Knowledge Portal. The 1991–2020 average is the one CCKP publishes for the same area; it is a recent baseline, so values near zero already include most of the warming since pre-industrial times.",
        "kind": "derived",
        "licence": {
          "name": "CC BY 4.0 with the World Bank Dataset Terms",
          "spdx": "CC-BY-4.0",
          "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"
        },
        "notice": "Shared under the World Bank Dataset Terms (CC BY 4.0 with additional terms), including their attribution requirement, which passes to anyone who shares these data further: https://www.worldbank.org/ext/en/legal/terms-conditions/datasets",
        "origins": [
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          {"acquisition": "automatic", "artifact_id": "era5-tas-annual-global", "bytes": 1289, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f.zst", "sha256": "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_timeseries_tas_timeseries_annual_1950-2025_mean_historical_era5_x0.25_mean/global?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "era5-tas-climatology-1991-2020-countries", "bytes": 5912, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc.zst", "sha256": "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_climatology_tas_climatology_annual_1991-2020_mean_historical_era5_x0.25_mean/all_countries?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "era5-tas-climatology-1991-2020-global", "bytes": 101, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792.zst", "sha256": "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_climatology_tas_climatology_annual_1991-2020_mean_historical_era5_x0.25_mean/global?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read CCKP's ERA5 0.25° annual mean near-surface air temperature for every country and territory and for the globe, 1950–2025 (absolute °C; CCKP stamps each year's value \"YYYY-07\", read as the year).",
            "inputs": ["62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/country/cckp.py",
            "transform_sha256": "5cfdd50878c9ffae5d481cc971232bf1460dc17d3a486d6b825936085104a74a"
          },
          {
            "description": "Mapped CCKP's codes to the site's entities: ISO 3166-1 alpha-3 codes as they are, KSV (CCKP's code for Kosovo) to KOS and GLOBAL to WLD. Every CCKP area is published, including the overseas territories Natural Earth draws inside another country (envdash/geo.py EXTRA_TERRITORIES).",
            "inputs": ["62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/country/cckp.py",
            "transform_sha256": "5cfdd50878c9ffae5d481cc971232bf1460dc17d3a486d6b825936085104a74a"
          },
          {
            "description": "Read CCKP's published ERA5 1991–2020 annual climatology for the same areas and checked that it belongs to the same series: for every area the mean of the 30 printed annual values 1991–2020 is within 0.01 °C of it (largest difference 0.006 °C, rounding only).",
            "inputs": ["62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/country/cckp.py",
            "transform_sha256": "5cfdd50878c9ffae5d481cc971232bf1460dc17d3a486d6b825936085104a74a"
          },
          {
            "description": "Subtracted each area's 1991–2020 climatology from each of its annual values (exact decimal arithmetic on the printed digits). The baseline is CCKP's own; CCKP publishes no 1951–1980 ERA5 climatology, and none is computed here.",
            "inputs": ["62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/country/cckp.py",
            "transform_sha256": "5cfdd50878c9ffae5d481cc971232bf1460dc17d3a486d6b825936085104a74a"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1991–2020 mean of the same CCKP ERA5 aggregate (CCKP's published climatology)",
          "basis": "ERA5 reanalysis (Copernicus Climate Change Service), 2 m air temperature, annual mean, aggregated by CCKP; difference from CCKP's 1991–2020 climatology computed here.",
          "bunkers": null,
          "geography": "Each country or territory as drawn by the World Bank's official boundaries (an area-weighted mean of the 0.25° grid cells inside it); World is CCKP's global aggregate of the same grid.",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["wb-cckp"],
      "time_basis": "calendar",
      "title": "Annual temperature compared with 1991–2020 by country (ERA5, World Bank CCKP)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "era5-x0.25 1950-2025, fetched 2026-10-05"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALA", "ALB", "AND", "ARE", "ARG", "ARM", "ASM", "ATF", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLM", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BVT", "BWA", "CAF", "CAN", "CCK", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYM", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GGY", "GHA", "GIB", "GIN", "GLP", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUF", "GUM", "GUY", "HKG", "HMD", "HND", "HRV", "HTI", "HUN", "IDN", "IMN", "IND", "IOT", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JEY", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAF", "MAR", "MCO", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MNP", "MOZ", "MRT", "MSR", "MTQ", "MUS", "MWI", "MYS", "MYT", "NAM", "NCL", "NER", "NFK", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAK", "PAN", "PCN", "PER", "PHL", "PLW", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "REU", "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SGP", "SHN", "SJM", "SLB", "SLE", "SLV", "SMR", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKL", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "UMI", "URY", "USA", "UZB", "VAT", "VCT", "VEN", "VGB", "VIR", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "c997de4536b4734d36ae7c69990bd482ec949742e924a458084cad30491625e8",
      "geo_coverage": "mixed",
      "id": "temp.wb-cckp.era5-annual-absolute",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 14.97
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "The World Bank: Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree (doi:10.57966/128g-6s70): Copernicus Climate Change Service ERA5. The World Bank: Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree (doi:10.57966/b54h-7s87): CMIP6 multi-model ensemble (World Climate Research Programme).",
        "description": "Average near-surface air temperature over each country's area for every year since 1950, in degrees Celsius, from the ERA5 reanalysis as aggregated by the World Bank's Climate Change Knowledge Portal. These are reanalysis averages over the whole country, not weather-station records; World is the global average of the same reanalysis.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0 with the World Bank Dataset Terms",
          "spdx": "CC-BY-4.0",
          "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"
        },
        "notice": "Shared under the World Bank Dataset Terms (CC BY 4.0 with additional terms), including their attribution requirement, which passes to anyone who shares these data further: https://www.worldbank.org/ext/en/legal/terms-conditions/datasets",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "era5-tas-annual-countries", "bytes": 295983, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824.zst", "sha256": "62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_timeseries_tas_timeseries_annual_1950-2025_mean_historical_era5_x0.25_mean/all_countries?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "era5-tas-annual-global", "bytes": 1289, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f.zst", "sha256": "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_timeseries_tas_timeseries_annual_1950-2025_mean_historical_era5_x0.25_mean/global?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "era5-tas-climatology-1991-2020-countries", "bytes": 5912, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc.zst", "sha256": "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_climatology_tas_climatology_annual_1991-2020_mean_historical_era5_x0.25_mean/all_countries?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "era5-tas-climatology-1991-2020-global", "bytes": 101, "citation_full": "Climate Change Knowledge Portal: Observed Climate Data, ERA5 0.25-Degree, DOI: https://doi.org/10.57966/128g-6s70. Climate Change Knowledge Portal: Projected Climate Data, CMIP6 0.25-Degree. DOI: https://doi.org/10.57966/b54h-7s87", "date_accessed": "2026-10-05", "date_published": null, "doi": "10.57966/128g-6s70", "etag": null, "last_modified": null, "licence": {"name": "CC BY 4.0 with the World Bank Dataset Terms", "spdx": "CC-BY-4.0", "url": "https://www.worldbank.org/ext/en/legal/terms-conditions/datasets"}, "producer": "World Bank Group", "r2_url": "https://files.environmentdashboard.org/raw/ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792.zst", "sha256": "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792", "source_id": "wb-cckp", "title": "Climate Change Knowledge Portal country climate data", "url_download": "https://cckpapi.worldbank.org/cckp/v1/era5-x0.25_climatology_tas_climatology_annual_1991-2020_mean_historical_era5_x0.25_mean/global?_format=json", "url_main": "https://climateknowledgeportal.worldbank.org/", "version_producer": "era5-x0.25 1950-2025, fetched 2026-10-05", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read CCKP's ERA5 0.25° annual mean near-surface air temperature for every country and territory and for the globe, 1950–2025 (absolute °C; CCKP stamps each year's value \"YYYY-07\", read as the year).",
            "inputs": ["62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/country/cckp.py",
            "transform_sha256": "5cfdd50878c9ffae5d481cc971232bf1460dc17d3a486d6b825936085104a74a"
          },
          {
            "description": "Mapped CCKP's codes to the site's entities: ISO 3166-1 alpha-3 codes as they are, KSV (CCKP's code for Kosovo) to KOS and GLOBAL to WLD. Every CCKP area is published, including the overseas territories Natural Earth draws inside another country (envdash/geo.py EXTRA_TERRITORIES).",
            "inputs": ["62effa974e359adb02b6e4346d385997af9987a9437e31d58cf0f433cf364824", "589d54de415a9c6f6f7a8fdc67b913b9afcf5e147cdfd58cbce54e0c404efe7f", "8b34b2306902cb994e25c3a0cd76f20a185dd09206f36c209db9043006c6b1cc", "ac58ff0206fa4b1fad2e3ac66916c1209e793d4923393499f2defabdd3364792"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/country/cckp.py",
            "transform_sha256": "5cfdd50878c9ffae5d481cc971232bf1460dc17d3a486d6b825936085104a74a"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": null,
          "basis": "Absolute temperature (not an anomaly). ERA5 reanalysis (Copernicus Climate Change Service), 2 m air temperature, annual mean, aggregated by CCKP.",
          "bunkers": null,
          "geography": "Each country or territory as drawn by the World Bank's official boundaries (an area-weighted mean of the 0.25° grid cells inside it); World is CCKP's global aggregate of the same grid.",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["wb-cckp"],
      "time_basis": "calendar",
      "title": "Annual mean temperature by country (ERA5, World Bank CCKP)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "era5-x0.25 1950-2025, fetched 2026-10-05"
    },
    {
      "display": {
        "decimals": 3
      },
      "downloadable": true,
      "entities": ["GBR"],
      "export_sha256": "3febf549bfc974817d68096e052b21fbd1275cd65b196786b7fbafa4f41f9697",
      "geo_coverage": "country",
      "id": "travel.desnz-2026.flight-factors",
      "latest": {
        "age_bp": null,
        "dims": {
          "haul": "long-haul",
          "radiative_forcing": "with-rf",
          "seat_class": "economy"
        },
        "entity": "GBR",
        "period": "2026",
        "status": "final",
        "value": 0.11704
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Department for Energy Security and Net Zero, Greenhouse gas reporting: conversion factors 2026 (flat file version 2026, flat file version 1.2). Contains public sector information licensed under the Open Government Licence v3.0.",
        "description": "Greenhouse gas emissions per passenger per kilometre flown, from the UK Government's 2026 conversion factors: for domestic, short-haul and long-haul flights to or from the UK and for international flights elsewhere, by seat class, with and without the extra warming from aircraft emissions at altitude (radiative forcing). Premium seats take more cabin space, so each passenger in them is assigned more of the flight's emissions. Factors are averages for UK reporting, not measurements of a particular flight.",
        "kind": "series",
        "licence": {
          "name": "Open Government Licence v3.0 (Crown copyright)",
          "spdx": "OGL-UK-3.0",
          "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"
        },
        "notice": null,
        "origins": [
          {"acquisition": "automatic", "artifact_id": "flat-file", "bytes": 515426, "citation_full": "Department for Energy Security and Net Zero (2026). Greenhouse gas reporting: conversion factors 2026, flat file version 2026, flat file version 1.2. GOV.UK. https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2026", "date_accessed": "2026-10-05", "date_published": "2026-06-11", "doi": null, "etag": "\"6a6c9748-7dd62\"", "last_modified": "Fri, 31 Jul 2026 12:38:32 GMT", "licence": {"name": "Open Government Licence v3.0 (Crown copyright)", "spdx": "OGL-UK-3.0", "url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/"}, "producer": "Department for Energy Security and Net Zero (UK Government)", "r2_url": "https://files.environmentdashboard.org/raw/a9a455ab396dae226d510c7be6233748416d490c41a5d20f3dc7a0c45feecd5e.zst", "sha256": "a9a455ab396dae226d510c7be6233748416d490c41a5d20f3dc7a0c45feecd5e", "source_id": "desnz-ghg-factors-2026", "title": "Greenhouse gas reporting: conversion factors 2026", "url_download": "https://assets.publishing.service.gov.uk/media/6a6c9748862aaf18d9c62ac9/ghg-conversion-factors-2026-flat-format-revised.xlsx", "url_main": "https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2026", "version_producer": "2026, flat file version 1.2", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read sheet 'Factors by Category' of the flat file (sha256 a9a455ab396d…) and kept the rows with Level 1 'Business travel- air', Level 2 'Flights', unit 'passenger.km' and GHG/Unit 'kg CO2e' (the all-gas total): 28 factors, one for each haul, seat class and with or without radiative forcing that DESNZ publishes. Checked that each appears exactly once.",
            "inputs": ["a9a455ab396dae226d510c7be6233748416d490c41a5d20f3dc7a0c45feecd5e"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/desnz_flights.py",
            "transform_sha256": "79a892da557e792a5367eef793936f505a9c5e4ee4cafd6855a80dffcdc9d903"
          },
          {
            "description": "Published each factor as printed, with its DESNZ factor ID in the value's note. Well-to-tank rows and the separate CO2, CH4 and N2O rows are not used.",
            "inputs": ["a9a455ab396dae226d510c7be6233748416d490c41a5d20f3dc7a0c45feecd5e"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/action/desnz_flights.py",
            "transform_sha256": "79a892da557e792a5367eef793936f505a9c5e4ee4cafd6855a80dffcdc9d903"
          }
        ],
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        "scope": {
          "baseline": null,
          "basis": "Direct emissions of the flight (CO2, CH4 and N2O as CO2-equivalent, with the warming potentials DESNZ lists in its methodology paper, Table 1), excluding the well-to-tank emissions of producing jet fuel. The factors include DESNZ's 8% uplift on the great-circle distance (methodology paper, paragraph 8.17). 'With radiative forcing' applies DESNZ's 1.7 multiplier to the CO2 for the effects of emissions at altitude (paragraph 2.10); 'without' gives the emissions alone.",
          "bunkers": null,
          "geography": "UK Government factors for reporting by UK organisations (flights to or from the UK, and international flights between non-UK airports)",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["desnz-ghg-factors-2026"],
      "time_basis": "calendar",
      "title": "Flight emission factors by distance and seat class (UK Government 2026)",
      "unit": {
        "code": "kgCO2e/pkm",
        "label": "kilograms of CO2-equivalent per passenger-kilometre",
        "short": "kg CO₂e/pkm"
      },
      "vintage": "2026, flat file version 1.2"
    },
    {
      "display": {
        "decimals": 1
      },
      "downloadable": false,
      "entities": ["WLD"],
      "export_sha256": "c6533311637edeebeb99b0dafe98e8816f6bb3cc0b067a7dd0cd215267f2b4a9",
      "geo_coverage": "global-only",
      "id": "warming.cat-2025.thermometer",
      "latest": null,
      "licence_class": "no-derivatives",
      "provenance": {
        "attribution": "Climate Action Tracker (2025), The CAT Thermometer, November 2025, Climate Analytics and NewClimate Institute, https://climateactiontracker.org/global/cat-thermometer/.",
        "description": "Climate Action Tracker's projection of global warming in 2100 above pre-industrial levels under four sets of assumptions: the policies and action in place now, only the 2030 and 2035 national targets, all submitted pledges and targets, and an optimistic case in which every announced target is met. Each is CAT's median estimate with its lower and upper bound, as CAT publishes them in the CAT Thermometer of November 2025.",
        "kind": "series",
        "licence": {
          "name": "© Climate Analytics and NewClimate Institute, all rights reserved; non-commercial reproduction and distribution allowed with credit and the copyright notice; no adaptation granted",
          "spdx": null,
          "url": "https://climateactiontracker.org/about/legal/"
        },
        "notice": "Copyright © 2025 by Climate Analytics and NewClimate Institute. All rights reserved. Reproduced unmodified for non-commercial use; not to be used for commercial purposes.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "global-temperature-estimates", "bytes": 1165847, "citation_full": "Climate Action Tracker (2025). The CAT Thermometer. November 2025. Available at: https://climateactiontracker.org/global/cat-thermometer/", "date_accessed": "2026-10-04", "date_published": "2025-11-13", "doi": null, "etag": "\"c95fceea86569263ba2e163314ae8999b6605470\"", "last_modified": "Thu, 13 Nov 2025 00:03:30 GMT", "licence": {"name": "© Climate Analytics and NewClimate Institute, all rights reserved; non-commercial reproduction and distribution allowed with credit and the copyright notice; no adaptation granted", "spdx": null, "url": "https://climateactiontracker.org/about/legal/"}, "producer": "Climate Action Tracker (Climate Analytics and NewClimate Institute)", "r2_url": null, "sha256": "44044cda8f851f77d6ca0eeb0750848fb6ee32bab50939df2cc2363e63a8c6c1", "source_id": "cat-2025-thermometer", "title": "Climate Action Tracker: the CAT Thermometer, November 2025 (COP30 global update)", "url_download": "https://climateactiontracker.org/documents/1349/CAT_2025-11_PublicData_GlobalTemperatureEstimates_COP30.xlsx", "url_main": "https://climateactiontracker.org/global/cat-thermometer/", "version_producer": "November 2025", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read the CAT Thermometer sheet of CAT_2025-11_PublicData_GlobalTemperatureEstimates_COP30.xlsx. The Info sheet gives the Date Published, 13 November 2025; the vintage is that month, as CAT labels the update.",
            "inputs": ["44044cda8f851f77d6ca0eeb0750848fb6ee32bab50939df2cc2363e63a8c6c1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/future/cat_thermometer.py",
            "transform_sha256": "94523270ef29587110c626620597d951b0741b5bbf5a652c430b297d01ae0809"
          },
          {
            "description": "Kept the four rows the sheet prints in bold, which it says are the values used in the CAT Thermometer: Policies & action (Combined), 2030 & 2035 Targets only, Pledges & targets, and Optimistic scenario (net-zero pledges). Not published: the High and Low variants of Policies & action, the 2030 targets only row and an unlabelled row, none of which is in bold.",
            "inputs": ["44044cda8f851f77d6ca0eeb0750848fb6ee32bab50939df2cc2363e63a8c6c1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/future/cat_thermometer.py",
            "transform_sha256": "94523270ef29587110c626620597d951b0741b5bbf5a652c430b297d01ae0809"
          },
          {
            "description": "Each value is the sheet's cell unchanged: Median as the value, Lower bound and Upper bound as the range. Every cell was checked to be displayed with one decimal and to store no more digits than it displays, because CAT asks that only the displayed rounded values be reproduced. Nothing was computed.",
            "inputs": ["44044cda8f851f77d6ca0eeb0750848fb6ee32bab50939df2cc2363e63a8c6c1"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/future/cat_thermometer.py",
            "transform_sha256": "94523270ef29587110c626620597d951b0741b5bbf5a652c430b297d01ae0809"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Pre-industrial levels, as CAT defines them",
          "basis": "Warming in the year 2100 from the MAGICC7 climate model run on CAT's emissions pathways: the median with CAT's lower and upper bounds, rounded by CAT to 0.1 °C and reproduced unchanged. CAT's sheet tags the median column '_50' and the upper column '_83' and gives no tag for the lower column, so no probability is attached to the range here.",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["cat-2025-thermometer"],
      "time_basis": "calendar",
      "title": "Projected warming in 2100 under current policies and pledges (Climate Action Tracker)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "November 2025"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "b3ab1364a5f6965ecf47200be646eb339f83f9033f08df20b3f356490062ab1c",
      "geo_coverage": "global-only",
      "id": "warming.igcc-2025.human-induced",
      "latest": {
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        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 1.38
      },
      "licence_class": "open",
      "provenance": {
        "attribution": "Calculated by Environment Dashboard from Indicators of Global Climate Change 2025: Forster et al. (2026), Earth Syst. Sci. Data 18, 3889–3933, doi:10.5194/essd-18-3889-2026; data: Smith et al. (2026), version IGCC-2025a, doi:10.5281/zenodo.21494229. CC BY 4.0. Changes: best estimate and likely range for each year computed from the three methods' annual percentiles with IGCC's stated multi-method assessment rule.",
        "description": "How much of the global surface warming in each year since 1850 was caused by human activity, relative to the 1850–1900 average, with the likely range, by the annual-mean definition. Indicators of Global Climate Change combines three attribution methods; this series applies its stated assessment rule to each year's annual-mean estimate. IGCC's headline figure for a single year uses the trend-based definition of the IPCC 1.5 °C report instead (published separately as human-induced warming in 2025) and can differ by a few hundredths of a degree.",
        "kind": "series",
        "licence": {
          "name": "CC BY 4.0",
          "spdx": "CC-BY-4.0",
          "url": "https://creativecommons.org/licenses/by/4.0/"
        },
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        "processing": [
          {
            "description": "Checked that each file read (Assessment-Update-2025_GMST_headlines.csv, Gillett_GMST_timeseries.csv, Ribes_GMST_timeseries.csv, Walsh_GMST_timeseries.csv) is byte-identical to the same path inside the IGCC-2025a release zip deposited on Zenodo (doi:10.5281/zenodo.21494229, sha256 04658ff91053…).",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879", "ecf9da410624bb9959d38b916be9d6dde6c0a6613a640c2ef842c464f71d146a", "e0abdbb899df3b4b241336fdfd5c07e2eee2a8057ad31e323bd137a2c687d2fe", "5eb8a8883085cccce2330558ec6d0803a3638e40e6b799dd83c6ad67a4e835df"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Read the annual 5th, 50th and 95th percentiles of human-induced (anthropogenic) warming relative to 1850–1900 from the timeseries files of the three attribution methods IGCC assesses: Global Warming Index (Walsh), regularised optimal fingerprinting (Gillett) and kriging for climate change (Ribes).",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879", "ecf9da410624bb9959d38b916be9d6dde6c0a6613a640c2ef842c464f71d146a", "e0abdbb899df3b4b241336fdfd5c07e2eee2a8057ad31e323bd137a2c687d2fe", "5eb8a8883085cccce2330558ec6d0803a3638e40e6b799dd83c6ad67a4e835df"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Applied IGCC's stated assessment rule to every year (ESSD Sect. 8): the best estimate is the mean of the three medians to 0.01 °C (rounded half up), and the likely range runs from the lowest 5th percentile rounded down to 0.1 °C to the highest 95th percentile rounded up to 0.1 °C.",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879", "ecf9da410624bb9959d38b916be9d6dde6c0a6613a640c2ef842c464f71d146a", "e0abdbb899df3b4b241336fdfd5c07e2eee2a8057ad31e323bd137a2c687d2fe", "5eb8a8883085cccce2330558ec6d0803a3638e40e6b799dd83c6ad67a4e835df"],
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            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Checked that this reproduces every single-year annual-mean assessment IGCC published in Assessment-Update-2025_GMST_headlines.csv (2017: 1.14 [0.9 to 1.4] °C; 2025: 1.38 [1.1 to 1.7] °C); it does, exactly. IGCC's headline single-year figure uses the trend-based definition of the IPCC 1.5 °C report instead, which IGCC prioritises where the two differ; it is published as warming.igcc-2025.human-induced-2025, not in this series.",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879", "ecf9da410624bb9959d38b916be9d6dde6c0a6613a640c2ef842c464f71d146a", "e0abdbb899df3b4b241336fdfd5c07e2eee2a8057ad31e323bd137a2c687d2fe", "5eb8a8883085cccce2330558ec6d0803a3638e40e6b799dd83c6ad67a4e835df"],
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            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "1850–1900",
          "basis": "Global mean surface temperature (GMST); warming attributed to all human influences (greenhouse gases, aerosols and other human forcings), annual-mean definition. Best estimate: mean of the three methods' medians to 0.01 °C. Likely range: the smallest 0.1 °C-step range covering each method's 5–95% range.",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["igcc-2025"],
      "time_basis": "calendar",
      "title": "Human-induced warming since 1850–1900, each year, annual-mean definition (IGCC 2025)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "IGCC-2025a"
    },
    {
      "display": {
        "decimals": 2
      },
      "downloadable": true,
      "entities": ["WLD"],
      "export_sha256": "7e328952df084485858a542cab7b17bf1db03385cb0078473abbfe1fe42165f6",
      "geo_coverage": "global-only",
      "id": "warming.igcc-2025.human-induced-2025",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2025",
        "status": "final",
        "value": 1.37
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      "provenance": {
        "attribution": "Indicators of Global Climate Change 2025: Forster et al. (2026), Earth Syst. Sci. Data 18, 3889–3933, doi:10.5194/essd-18-3889-2026; data: Smith et al. (2026), version IGCC-2025a, doi:10.5281/zenodo.21494229. CC BY 4.0.",
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        "kind": "published-value",
        "licence": {
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        "notice": null,
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          {"acquisition": "automatic", "artifact_id": "essd-paper-pdf", "bytes": 9736703, "citation_full": "Forster, P. M., Walsh, T., Smith, C., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Andrew, R. M., Atkinson, C., Betts, R. A., Bombelli, A., Burgess, S. N., Cheng, L., Claxton, H. E., Friedlingstein, P., Frölicher, T. L., Domingues, C. M., Gasser, T., Gregory, C. H., Hoesly, R. M., Huppmann, D., Ishii, M., Kadow, C., Karwat, A., Kennedy, J., Killick, R. E., Kovilakam, M. V. M., Krummel, P. B., Lan, X., Lamarque, J.-F., Liné, A., Martín-Míguez, B., Monselesan, D. P., Morice, C., Mühle, J., Mussak, P., Peters, G. P., Pirani, A., Pongratz, J., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Smith, S. J., Taha, G., Tassone, C., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Zecchetto, M., Zhong, J., Zhang, X.-Y., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2025: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, 2026. Smith, C., Walsh, T., Gillett, N., Hauser, M., Krummel, P., Lamb, W., Lamboll, R., Mühle, J., Palmer, M., Ribes, A., Schumacher, D., Seneviratne, S., Slangen, A., Trewin, B., von Schuckmann, K., & Forster, P. (2026). Indicators of Global Climate Change 2025 (Version IGCC-2025a) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.21494229", "date_accessed": "2026-10-04", "date_published": "2026-06-11", "doi": "10.5194/essd-18-3889-2026", "etag": "\"9491ff-653ed6ee5a83f\"", "last_modified": "Wed, 10 Jun 2026 22:04:53 GMT", "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Indicators of Global Climate Change (IGCC) consortium, led by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/795eb30a2ed5defdffb78499b0c3eac2314eac3a4ab5d7e9f093bef336acafeb.zst", "sha256": "795eb30a2ed5defdffb78499b0c3eac2314eac3a4ab5d7e9f093bef336acafeb", "source_id": "igcc-2025", "title": "Indicators of Global Climate Change 2025", "url_download": "https://essd.copernicus.org/articles/18/3889/2026/essd-18-3889-2026.pdf", "url_main": "https://doi.org/10.5281/zenodo.21494229", "version_producer": "IGCC-2025a", "wayback_url": null},
          {"acquisition": "automatic", "artifact_id": "warming-assessment-headlines", "bytes": 683, "citation_full": "Forster, P. M., Walsh, T., Smith, C., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Andrew, R. M., Atkinson, C., Betts, R. A., Bombelli, A., Burgess, S. N., Cheng, L., Claxton, H. E., Friedlingstein, P., Frölicher, T. L., Domingues, C. M., Gasser, T., Gregory, C. H., Hoesly, R. M., Huppmann, D., Ishii, M., Kadow, C., Karwat, A., Kennedy, J., Killick, R. E., Kovilakam, M. V. M., Krummel, P. B., Lan, X., Lamarque, J.-F., Liné, A., Martín-Míguez, B., Monselesan, D. P., Morice, C., Mühle, J., Mussak, P., Peters, G. P., Pirani, A., Pongratz, J., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Smith, S. J., Taha, G., Tassone, C., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Zecchetto, M., Zhong, J., Zhang, X.-Y., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2025: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, 2026. Smith, C., Walsh, T., Gillett, N., Hauser, M., Krummel, P., Lamb, W., Lamboll, R., Mühle, J., Palmer, M., Ribes, A., Schumacher, D., Seneviratne, S., Slangen, A., Trewin, B., von Schuckmann, K., & Forster, P. (2026). Indicators of Global Climate Change 2025 (Version IGCC-2025a) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.21494229", "date_accessed": "2026-10-04", "date_published": "2026-07-22", "doi": "10.5281/zenodo.21494229", "etag": "W/\"9a20ce76744835485a38171386d4a8dfd0b83afea59b1c94a596a809ea375aee\"", "last_modified": null, "licence": {"name": "CC BY 4.0", "spdx": "CC-BY-4.0", "url": "https://creativecommons.org/licenses/by/4.0/"}, "producer": "Indicators of Global Climate Change (IGCC) consortium, led by the University of Leeds", "r2_url": "https://files.environmentdashboard.org/raw/d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879.zst", "sha256": "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879", "source_id": "igcc-2025", "title": "Indicators of Global Climate Change 2025", "url_download": "https://raw.githubusercontent.com/ClimateIndicator/data/0f2765dc2e96c98aebceb78fb12cd28fcfb9ac6f/data/base/anthropogenic_warming/Assessment-Update-2025_GMST_headlines.csv", "url_main": "https://doi.org/10.5281/zenodo.21494229", "version_producer": "IGCC-2025a", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Quoted from Sect. 8.1, p. 3906 (also the abstract and Table 6) of Forster et al. (2026), Earth Syst. Sci. Data 18. The quote was found in the text of page 18 of the PDF snapshot (sha256 795eb30a2ed5…) before publishing, and so was IGCC's statement on page 17 of which single-year definition it uses: 'where they differ we prioritise the SR1.5 trend-based definition' (rather than the annual mean).",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "795eb30a2ed5defdffb78499b0c3eac2314eac3a4ab5d7e9f093bef336acafeb", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Value: \"1.37 [1.1 to 1.7] °C\" is published as 1.37 °C for 2025 with the likely range 1.1 to 1.7 °C, relative to 1850–1900.",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "795eb30a2ed5defdffb78499b0c3eac2314eac3a4ab5d7e9f093bef336acafeb", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879"],
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            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Checked that each file read (Assessment-Update-2025_GMST_headlines.csv) is byte-identical to the same path inside the IGCC-2025a release zip deposited on Zenodo (doi:10.5281/zenodo.21494229, sha256 04658ff91053…).",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "795eb30a2ed5defdffb78499b0c3eac2314eac3a4ab5d7e9f093bef336acafeb", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          },
          {
            "description": "Cross-check: the release's own 'SR15 definition' row for 2025 in Assessment-Update-2025_GMST_headlines.csv gives 5th, 50th and 95th percentiles 1.1, 1.37 and 1.7 °C, the same as the quoted value and range; the build stops if they differ. (The annual-mean row for 2025 gives 1.38 °C; that definition is published as warming.igcc-2025.human-induced.)",
            "inputs": ["04658ff91053808aced03f65dc977311668aec1610ec83bec72fff303dcbcbcd", "795eb30a2ed5defdffb78499b0c3eac2314eac3a4ab5d7e9f093bef336acafeb", "d419c3f7d513b42052f5635454853610739d8b5f1749f55b5df03862dfe28879"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/climate/igcc_2025.py",
            "transform_sha256": "5a1f11a945b695d391df82051a7702020d761923b52db1f49469838f1f9c172a"
          }
        ],
        "published_value": {
          "document": "igcc-2025",
          "locator": "Sect. 8.1, p. 3906 (also the abstract and Table 6)",
          "quote": "The single year average human-induced warming is assessed to be 1.37 [1.1 to 1.7] °C in 2025 relative to 1850–1900."
        },
        "scope": {
          "baseline": "1850–1900",
          "basis": "Global mean surface temperature (GMST); warming attributed to all human influences (greenhouse gases, aerosols and other human forcings) in the single year 2025, SR1.5 trend-based definition. IGCC's multi-method assessment of three attribution methods: best estimate to 0.01 °C, likely range to 0.1 °C.",
          "bunkers": null,
          "geography": "Global mean",
          "gwp": null,
          "lulucf": null
        }
      },
      "source_ids": ["igcc-2025"],
      "time_basis": "calendar",
      "title": "Human-induced warming in 2025 (IGCC 2025)",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "IGCC-2025a"
    },
    {
      "display": {
        "decimals": 3
      },
      "downloadable": true,
      "entities": ["ABW", "AFG", "AGO", "AIA", "ALB", "AND", "ARE", "ARG", "ARM", "ATA", "ATG", "AUS", "AUT", "AZE", "BDI", "BEL", "BEN", "BES", "BFA", "BGD", "BGR", "BHR", "BHS", "BIH", "BLR", "BLZ", "BMU", "BOL", "BRA", "BRB", "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR", "COD", "COG", "COK", "COL", "COM", "CPV", "CRI", "CUB", "CUW", "CXR", "CYP", "CZE", "DEU", "DJI", "DMA", "DNK", "DOM", "DZA", "ECU", "EGY", "ERI", "ESP", "EST", "ETH", "EU27", "FIN", "FJI", "FRA", "FRO", "FSM", "GAB", "GBR", "GEO", "GHA", "GIN", "GMB", "GNB", "GNQ", "GRC", "GRD", "GRL", "GTM", "GUY", "HKG", "HND", "HRV", "HTI", "HUN", "IDN", "IND", "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ", "KEN", "KGZ", "KHM", "KIR", "KNA", "KOR", "KOS", "KWT", "KWT_OILFIRES", "LAO", "LBN", "LBR", "LBY", "LCA", "LIE", "LKA", "LSO", "LTU", "LUX", "LVA", "MAC", "MAR", "MDA", "MDG", "MDV", "MEX", "MHL", "MKD", "MLI", "MLT", "MMR", "MNE", "MNG", "MOZ", "MRT", "MSR", "MUS", "MWI", "MYS", "NAM", "NCL", "NER", "NGA", "NIC", "NIU", "NLD", "NOR", "NPL", "NRU", "NZL", "OMN", "PAC_ISLANDS", "PAK", "PAN", "PER", "PHL", "PLW", "PNG", "POL", "PRK", "PRT", "PRY", "PSE", "PYF", "QAT", "ROU", "RUS", "RWA", "RYUKYU", "SAU", "SDN", "SEN", "SGP", "SHN", "SLB", "SLE", "SLV", "SOM", "SPM", "SRB", "SSD", "STP", "SUR", "SVK", "SVN", "SWE", "SWZ", "SXM", "SYC", "SYR", "TCA", "TCD", "TGO", "THA", "TJK", "TKM", "TLS", "TON", "TTO", "TUN", "TUR", "TUV", "TWN", "TZA", "UGA", "UKR", "URY", "USA", "UZB", "VCT", "VEN", "VGB", "VNM", "VUT", "WLD", "WLF", "WSM", "YEM", "ZAF", "ZMB", "ZWE"],
      "export_sha256": "e696f952f70ec9222e0e87bfffa3aa43d397b555fe43ee80e2010e6f1d6a9d30",
      "geo_coverage": "mixed",
      "id": "warming.jones-2025.national-contribution",
      "latest": {
        "age_bp": null,
        "dims": {},
        "entity": "WLD",
        "period": "2024",
        "status": "final",
        "value": 1.67836118168202
      },
      "licence_class": "noncommercial",
      "provenance": {
        "attribution": "Jones et al. (2025), National contributions to climate change due to historical emissions of carbon dioxide, methane and nitrous oxide, version 2025.1, doi:10.5281/zenodo.16640595; method in Jones et al. (2023), Scientific Data 10, 155, doi:10.1038/s41597-023-02041-1.",
        "description": "How much each country's emissions of carbon dioxide, methane and nitrous oxide since 1850, from fossil fuels and from land use, have raised the global mean surface temperature, up to each year from 1851. Aerosols and fluorinated gases are not included, so the world value is larger than the observed human-induced warming.",
        "kind": "series",
        "licence": {
          "name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; the Zenodo deposit itself is labelled CC BY 4.0)",
          "spdx": "CC-BY-NC-SA-4.0",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"
        },
        "notice": "Methane and nitrous oxide emissions come from PRIMAP-hist v2.7 (Gütschow, Busch and Pflüger, 2025, doi:10.5281/zenodo.17090760), licensed CC BY-NC-SA 4.0. Values derived from this dataset are shared under CC BY-NC-SA 4.0, for non-commercial use only.",
        "origins": [
          {"acquisition": "automatic", "artifact_id": "gmst-response-1851", "bytes": 29113799, "citation_full": "Jones, M. W., Peters, G. P., Gasser, T., Andrew, R. M., Schwingshackl, C., Gütschow, J., Houghton, R. A., Friedlingstein, P., Pongratz, J., & Le Quéré, C. (2025). National contributions to climate change due to historical emissions of carbon dioxide, methane and nitrous oxide [Dataset]. In Scientific Data (Version 2025.1, Vol. 10, Issue 155). Zenodo. https://doi.org/10.5281/zenodo.16640595", "date_accessed": "2026-10-04", "date_published": "2025-11-13", "doi": "10.5281/zenodo.16640595", "etag": null, "last_modified": null, "licence": {"name": "CC BY-NC-SA 4.0 (inherited from PRIMAP-hist v2.7; the Zenodo deposit itself is labelled CC BY 4.0)", "spdx": "CC-BY-NC-SA-4.0", "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/"}, "producer": "Jones et al. (University of East Anglia, CICERO and others)", "r2_url": "https://files.environmentdashboard.org/raw/84f6cee695abf6a522de77b9899b094a982356ceb421e1c18c109530596de238.zst", "sha256": "84f6cee695abf6a522de77b9899b094a982356ceb421e1c18c109530596de238", "source_id": "jones-2025-national-contributions", "title": "National contributions to climate change due to historical emissions of carbon dioxide, methane and nitrous oxide", "url_download": "https://zenodo.org/api/records/16640595/files/GMST_response_1851-2024.csv/content", "url_main": "https://zenodo.org/records/16640595", "version_producer": "2025.1", "wayback_url": null}
        ],
        "processing": [
          {
            "description": "Read GMST_response_1851-2024.csv (version 2025.1) and kept the rows for the three-gas total (3-GHG) from fossil sources and land use together (Total), 1851–2024, in degrees Celsius relative to 1850.",
            "inputs": ["84f6cee695abf6a522de77b9899b094a982356ceb421e1c18c109530596de238"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/jones_warming.py",
            "transform_sha256": "55996f070bcd5c8420fce5619ce6c8a3695ac28cd4fc04012e4f3aa54d2e3fad"
          },
          {
            "description": "Checked that every entity's three-gas total equals its fossil plus land-use parts and the sum of its carbon dioxide, methane and nitrous oxide totals; that EU27 equals the sum of its 27 member states; and that GLOBAL equals the sum of all country rows, so international aviation and shipping, which have no rows, are not in the world value (largest difference 9.0e-15 °C).",
            "inputs": ["84f6cee695abf6a522de77b9899b094a982356ceb421e1c18c109530596de238"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/jones_warming.py",
            "transform_sha256": "55996f070bcd5c8420fce5619ce6c8a3695ac28cd4fc04012e4f3aa54d2e3fad"
          },
          {
            "description": "Mapped the producer's ISO3 codes to entity codes through an explicit alias table (KSV Kosovo, GLOBAL the world, XKW the Kuwaiti oil fires, XPC the Pacific Islands (Palau), XRY the Ryukyu Islands); left out the producer's groups Annex I, Annex II, BASIC, EIT, LDC, LMDC, non-Annex I and OECD. Values are published as stated.",
            "inputs": ["84f6cee695abf6a522de77b9899b094a982356ceb421e1c18c109530596de238"],
            "lock_sha256": "7e110986c30381965c2e6096466c401cbf72bd1b7a828369f6f6c14c909dcbda",
            "script": "pipeline/src/envdash/transforms/emissions/jones_warming.py",
            "transform_sha256": "55996f070bcd5c8420fce5619ce6c8a3695ac28cd4fc04012e4f3aa54d2e3fad"
          }
        ],
        "published_value": null,
        "scope": {
          "baseline": "Change since 1850 (the reference year)",
          "basis": "Carbon dioxide, methane and nitrous oxide from fossil sources and land use. Methane and nitrous oxide are converted to cumulative CO2-equivalent emissions with GWP* (IPCC AR6 coefficients); warming is the IPCC AR6 best-estimate transient climate response to cumulative emissions times those emissions. International aviation and shipping are not included.",
          "bunkers": "excluded",
          "geography": "Countries and territories, three historical entities, the European Union (27) and the world (the sum of the countries)",
          "gwp": "GWP*",
          "lulucf": "included"
        }
      },
      "source_ids": ["jones-2025-national-contributions"],
      "time_basis": "calendar",
      "title": "Contribution to global warming by country",
      "unit": {
        "code": "degC",
        "label": "degrees Celsius",
        "short": "°C"
      },
      "vintage": "2025.1"
    }
  ],
  "schema_version": 1
}