Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
7
datasets available to search
ShareScore release 0.9.0
Dataset results
7 results for “Historical emissions”
National contributions to climate change due to historical emissions of carbon dioxide, methane and nitrous oxide
<p>A complete description of the dataset is given by <a href="http://doi.org/10.1038/s41597-023-02041-1">Jones et al. (2023)</a>. Key information is provided below.</p> <p><strong>Background</strong></p> <p>A dataset describing the global warming response to national emissions CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O from fossil and land use sources during 1851-2021.</p> <p>National CO<sub>2 </sub>emissions data are collated from the Global Carbon Project (Andrew and Peters, 2024; Friedlingstein et al., 2024). </p> <p>National CH<sub>4</sub> and N<sub>2</sub>O emissions data are collated from PRIMAP-hist (HISTTP) (Gütschow et al., 2024).</p> <p>We construct a time series of cumulative CO2-equivalent emissions for each country, gas, and emissions source (fossil or land use). Emissions of CH<sub>4</sub> and N<sub>2</sub>O emissions are related to cumulative CO2-equivalent emissions using the Global Warming Potential (GWP*) approach, with best-estimates of the coefficients taken from the IPCC AR6 (Forster et al., 2021).</p> <p>Warming in response to cumulative CO2-equivalent emissions is estimated using the transient climate response to cumulative carbon emissions (TCRE) approach, with best-estimate value of TCRE taken from the IPCC AR6 (Forster et al., 2021, Canadell et al., 2021). 'Warming' is specifically the change in global mean surface temperature (GMST).</p> <p>The data files provide emissions, cumulative emissions and the GMST response by country, gas (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O or 3-GHG total) and source (fossil emissions, land use emissions or the total).</p> <p><strong>Data records: overview</strong></p> <p>The data records include three comma separated values (.csv) files as described below.</p> <p>All files are in ‘long’ format with one value provided in the <em>Data</em> column for each combination of the categorical variables <em>Year, Country Name, Country ISO3 code, Gas, and Component</em> columns.</p> <p><em>Component</em> specifies fossil emissions, LULUCF emissions or total emissions of the gas.</p> <p><em>Gas</em> specifies CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O or the three-gas total (labelled 3-GHG).</p> <p><em>Country ISO3 codes</em> are specifically the unique ISO 3166-1 alpha-3 codes of each country.</p> <p><strong>Data records: specifics</strong></p> <p>Data are provided relative to 2 reference years (denoted <em>ref_year </em>below): 1850 and 1991. 1850 is a mutual first year of data spanning all input datasets. 1991 is relevant because the United Nations Framework Convention on Climate Change was operationalised in 1992.</p> <p><em>EMISSIONS_ANNUAL_{ref_year-20}-2023.csv:</em> <em>Data </em>includes annual emissions of CO<sub>2</sub> (Pg CO<sub>2</sub> year<sup>-1</sup>), CH<sub>4</sub> (Tg CH<sub>4</sub> year<sup>-1</sup>) and N<sub>2</sub>O (Tg N<sub>2</sub>O year<sup>-1</sup>) during the period <em>ref_year-20 </em>to 2023. The <em>Data</em> column provides values for every combination of the categorical variables. Data are provided from <em>ref_year-20</em> because these data are required to calculate GWP* for CH<sub>4</sub>.</p> <p><em>EMISSIONS_CUMULATIVE_CO2e100_{ref_year+1}-2023.csv: Data </em>includes the cumulative CO<sub>2</sub> equivalent emissions in units Pg CO<sub>2</sub>-e<sub>100</sub> during the period <em>ref_year+1</em> to 2023 (i.e. since the reference year). The <em>Data</em> column provides values for every combination of the categorical variables. </p> <p><em>GMST_response_{ref_year+1}-2023.csv:</em> <em>Data</em> includes the change in global mean surface temperature (GMST) due to emissions of the three gases in units °C during the period <em>ref_year+1</em> to 2023 (i.e. since the reference year). The <em>Data</em> column provides values for every combination of the categorical variables. </p> <p><strong>Accompanying Code</strong></p> <p>Code is available at: <a href="https://github.com/jonesmattw/National_Warming_Contributions">https://github.com/jonesmattw/National_Warming_Contributions</a> .</p> <p>The code requires Input.zip to run (see README at the GitHub link).</p> <p><strong>Further info: Country Groupings</strong></p> <p>We also provide estimates of the contributions of various country groupings as defined by the UNFCCC:</p> <ul> <li>Annex I countries (number of countries, n = 42)</li> <li>Annex II countries (n = 23)</li> <li>economies in transition (EITs; n = 15)</li> <li>the least developed countries (LDCs; n = 47)</li> <li>the like-minded developing countries (LMDC; n = 24).</li> </ul> <p>And other country groupings:</p> <ul> <li>the organisation for economic co-operation and development (OECD; n = 38)</li> <li>the European Union (EU27 post-Brexit)</li> <li>the Brazil, South Africa, India and China (BASIC) group.</li> </ul> <p>See COUNTRY_GROUPINGS.xlsx for the lists of countries in each group.</p>
Model outputs: Historical (1700–2012) Global Multi-model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP)
<p>This dataset contains the fire model outputs of emissions for 34 species (elements, compounds, and classes of compounds) as described in the following:</p> <p>Li, F., Val Martin, M., Hantson, S., Andreae, M. O., Arneth, A., Lasslop, G., Yue, C., Bachelet, D., Forrest, M., Kaiser, J. W., Kluzek, E., Liu, X., Melton, J. R., Ward, D. S., Darmenov, A., Hickler, T., Ichoku, C., Magi, B. I., Sitch, S., van der Werf, G. R., Wiedinmyer, C., and Rabin, S.: Historical (1700–2012) Global Multi-model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP), <em>Atmos. Chem. Phys. Discuss.</em>, https://doi.org/10.5194/acp-2019-37, accepted pending technical corrections, 2019.</p> <p>See Readme for more information.</p>
Climate Watch Historical Country Greenhouse Gas Emissions Data (1990-2018)
<p>Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. See <a href="http://cait.wri.org/docs/CAIT2.0_CountryGHG_Methods.pdf">http://cait.wri.org/docs/CAIT2.0_CountryGHG_Methods.pdf</a> for details regarding data source and methodology.</p> <p> </p> <p>Climate Watch Historical GHG Emissions. 2021. Washington, DC: World Resources Institute. Available online at: <a href="https://www.climatewatchdata.org/ghg-emissions">https://www.climatewatchdata.org/ghg-emissions</a></p>
Anthropogenic Climate Forcers Historical Emissions Analysis
<p>[DRAFT - final version May 2024] Input data necessary to run the jupyter notebook code script located at the <a href="https://github.com/bwalkowiak/Anthropogenic-Climate-Forcer">Anthropogenic Climate Forcer GitHub</a></p> <p>Files include:</p> <ul> <li>Final Emissions Data for major GHGs and air pollutants from <a href="../records/10904361">Community Emissions Data System (CEDS)</a> version v_2024_04_01. Emissions pre-1970 are from v_2021_04_21 fuel data with sector partitioning from latest version 1970 allocation. <ul> <li>Emissions data files by emission species (SO2, NOx, BC, OC, NH3, NMVOC, CO, CO2, CH4, N2O), country, and sector produced by the April-01-2024 release of CEDS.</li> <li>See the <a href="https://github.com/JGCRI/CEDS/">CEDS GitHub</a> site for details including journal paper reference information and any known issues with this data.</li> </ul> </li> <li> HC (CFC, HCFC) emissions data from <a href="https://csl.noaa.gov/assessments/ozone/2022/">WMO Ozone 2022 Report</a>, HFC and HCFC emission data from <a href="https://edgar.jrc.ec.europa.eu/emissions_data_and_maps">EDGAR - Emissions Database for Global Atmospheric Research</a>, specifically EDGAR v8.0, with other species from <a href="https://ozone.unep.org/countries/data-table">UNEP Ozone Depleting Substance databases</a>]. HC emissions sectoral fractions calculated using UNFCCC AFEAS database and UNEP ODS. See HC Section for specific details.</li> <li><a href="https://github.com/IPCC-WG1/Chapter-6_Fig12_22_24">IPCC AR6 Ch6</a> ouput data for effective radiative forcing (ERF) and temperture response (del_T) over the calculation time period (1750-2022)</li> <li><a href="https://www.iea.org/data-and-statistics/data-product/world-energy-balances">IEA World Energy Balances 2023</a> data used to allocate sectoral emissions data</li> <li>Species lifetime from IPCC AR6</li> <li>CMIP model thermal reponse parameters from <a href="https://gmd.copernicus.org/articles/14/3007/2021/">Leach et al., (2021)</a></li> </ul>
The PRIMAP-hist national historical emissions time series (1750-2024) v2.7
<p><strong>Recommended citation</strong></p> <p>Gütschow, J.; Busch, D.; Pflüger, M. (2025): The PRIMAP-hist national historical emissions time series v2.7 (1750-2024). zenodo. doi:10.5281/zenodo.<em>17090760</em>.</p> <p>Gütschow, J.; Jeffery, L.; Gieseke, R.; Gebel, R.; Stevens, D.; Krapp, M.; Rocha, M. (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, doi:10.5194/essd-8-571-2016</p> <p><strong>Content</strong></p> <ul> <li><a href="#use-of-the-dataset-and-full-description">Use of the dataset and full description</a></li> <li><a href="#abstract">Abstract</a></li> <li><a href="#support">Support</a></li> <li><a href="#sources">Sources</a></li> <li><a href="#files-included-in-the-dataset">Files included in the dataset</a></li> <li><a href="#notes">Notes</a></li> <li><a href="#data-format-description-columns">Data format description (columns)</a></li> <li><a href="#references">References</a></li> <li><a href="#changelog">Changelog</a></li> </ul> <p><strong>Abstract</strong></p> <p>The PRIMAP-hist dataset combines several published datasets to create a comprehensive set of greenhouse gas emission pathways for every country and Kyoto gas, covering the years 1750 to 2024, and almost all UNFCCC (United Nations Framework Convention on Climate Change) member states as well as most non-UNFCCC territories. The data resolves the main IPCC (Intergovernmental Panel on Climate Change) 2006 categories. For CO2, CH4, and N2O subsector data for Energy, Industrial Processes and Product Use (IPPU), and Agriculture are available. The "country reported data priority" (CR) scenario of the PRIMAP-hist datset prioritizes data that individual countries report to the UNFCCC.</p> <p>For developed countries, AnnexI in terms of the UNFCCC, this is the data submitted anually in the "National Inventory Submissions". Until 2023 data was submitted in the "Common Reporting Format" (CRF). Since 2024 the new "Common Reporting Tables" (CRT) are used.For developing countries, non-AnnexI in terms of the UNFCCC our preferred data source are the Common Reporting Tables (CRT) submitted with the Biannial Transparency Reports (BTR). When countries do not provide the tables we read available data from the pdf reports and use additional submissions (Biannial Update Reports (BUR), National Communications (NC), and National Inventory Reports (NIR)) read from pdf and xlsx/csv files and for older submissions obtained from the UNFCCC DI portal (di.unfccc.int). For a list of these submissions please see below. For South Korea the 2024 official GHG inventory has not yet been submitted to the UN but is included in PRIMAP-hist. PRIMAP-hist also includes official data for Taiwan which is not recognized as a party to the UNFCCC. As the USA have not submitted any data to the UNFCCC this year we use the draft inventory report which the Environmental Defense Fund (EDF) obtained from the US Environmental Protection Agency (EPA) through the Freedom of Information Act.</p> <p>Gaps in the country reported data are filled using third party data such as CDIAC, EI (fossil CO2), Andrew cement emissions data (cement), FAOSTAT (agriculture), and EDGAR 2024 (all sectors for CO2, CH4, N2O, HFCs, PFCs, SF6, NF3, except energy CO2). Lower priority data are harmonized to higher priority data in the gap-filling process.</p> <p>For the third party priority time series gaps in the third party data are filled from country reported data sources.</p> <p>Data for earlier years which are not available in the above mentioned sources are sourced from EDGAR-HYDE, CEDS, and RCP (N2O only) historical emissions.</p> <p>The v2.4 release of PRIMAP-hist reduced the time-lag from 2 to 1 years for the October release. Thus the present version 2.7 includes data for 2024. For energy CO2 growth rates from the Energy Institute's *Statistical Review of World Energy* are used to extend the country reported data to 2024. For CO2 from cement production Andrew cement data are used for a few countries. For all other sectors and gases no emission estimates exist. Thus PRIMAP-hist relies on numerical methods and uses a linear extrapolation based on the last 5 years. COVID-19 has primarily impacted energy related emissions and in tests with CRF data no impact of COVID in the performance of linear extrapolation of emissions data in the other sectors has been detected. For the few cases where extrapolation is needed for energy CO2 we use a 15 year trend for the extrapolation.</p> <p>Version 2.7 of the PRIMAP-hist dataset does not include emissions from Land Use, Land-Use Change, and Forestry (LULUCF) in the main file. LULUCF data are included in the file with increased number of significant digits and have to be used with care as they are constructed from different sources using different methodologies and are not harmonized.</p> <p>The PRIMAP-hist v2.7 dataset is an updated version of</p> <p>Gütschow, J.; Pflüger, M.; Busch, D. (2025): The PRIMAP-hist national historical emissions time series v2.6.1 (1750-2023). zenodo. doi:10.5281/zenodo.15016289.</p> <p>The <a href="#changelog">Changelog</a> indicates the most important changes. You can also check the issue tracker on <a href="https://github.com/JGuetschow/PRIMAP-hist">github.com/JGuetschow/PRIMAP-hist</a> for additional information on issues found after the release of the dataset. Detailed per country information is available from the detailed changelog which is available on the <a href="https://primap.org/primap-hist">primap.org</a> website and on zenodo.</p> <p><strong>Use of the dataset and full description</strong></p> <p>Before using the dataset, please read this document and the article describing the methodology, especially the section on uncertainties and the section on limitations of the method and use of the dataset.</p> <p>Gütschow, J.; Jeffery, L.; Gieseke, R.; Gebel, R.; Stevens, D.; Krapp, M.; Rocha, M. (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, doi:10.5194/essd-8-571-2016</p> <p>Please notify us (support@johannes-guetschow@.de) if you use the dataset so that we can keep track of how it is used and take that into consideration when updating and improving the dataset.</p> <p>When using this dataset or one of its updates, please cite the DOI of the precise version of the dataset used and also the data description article which this dataset is supplement to (see above). Please consider also citing the relevant original sources when using the PRIMAP-hist dataset. See the full citations in the References section further below.</p> <p>Since version 2.3 we use the data formats developed for the PRIMAP2 climate policy analysis suite: <a href="https://github.com/pik-primap/primap2">PRIMAP2 on GitHub</a>. The data are published both in the interchange format which consists of a csv file with the data and a yaml file with additional metadata and the native NetCDF based format. For a detailed description of the data format we refer to the <a href="https://primap2.readthedocs.io/en/stable/">PRIMAP2 documentation</a>.</p> <p>We have also included files with more than three significant digits. These files are mainly aimed at people doing policy analysis using the country reported data scenario (HISTCR). Using the high precision data they can avoid questions on discrepancies with the reported data. The uncertainties of emissions data do not justify the additional significant digits and they might give a false sense of accuracy, so please use this version of the dataset with extra care.</p> <p><strong>Support</strong></p> <p>If you encounter possible errors or other things that should be noted, please check our issue tracker at <a href="https://github.com/JGuetschow/PRIMAP-hist">github.com/JGuetschow/PRIMAP-hist</a> and report your findings there. Please use the tag "v2.7" in any issue you create regarding this dataset.</p> <p>If you need support in using the dataset or have any other questions regarding the dataset, please contact nc-support@johannes-guetschow.de.</p> <p>Basic support is free for non-commercial users and most questions can be answered with a short e-mail. However, we do not have the resources to provide extensive support free of charge. For commercial users support will be included with the commercial license (see below).</p> <p><strong>License</strong></p> <p>Since v2.7 PRIMAP-hist is published under a non-commercial license (CC BY-NC-SA). This means that commercial users can not use it freely and have to obtain a commercial license. The commercial license is only available for the country reported priority (CR) time-series as the third party priority (TP) time-series builds heavily on EDGAR and FAOSTAT data. For commercial customers wanting to use the TP time-series we offer to develop custom code to generate the data locally. Please contact commercial-support@johannes-guetschow.de for more information.</p> <p><strong>Sources</strong></p> <ul> <li><strong>Global CO2 emissions from cement production v250226</strong> <a href="https://doi.org/10.5281/zenodo.14931651">data</a>, <a href="https://doi.org/10.5194/essd-11-1675-2019">paper</a>: Andrew<br>(2025), Andrew (2019)</li> <li><strong>EI Statistical Review of World Energy 2025</strong> <a href="https://www.energyinst.org/statistical-review">website</a>: Energy Institute (2025)</li> <li><strong>CDIAC</strong> <a href="https://energy.appstate.edu/cdiac-appstate/data-products">data</a>: Hefner and Marland (2023), <a href="https://doi.org/10.5281/zenodo.10607882">data</a>: Hefner (2024), <a href="https://essd.copernicus.org/articles/13/1667/2021/">paper</a>: Gilfillan and Marland (2021)</li> <li><strong>CEDS</strong>: <a href="http://doi.org/10.5281/zenodo.3606753">data:</a> Hoesly et al. (2020), <a href="https://gmd.copernicus.org/articles/11/369/2018/">paper</a>: Hoesly et al. (2018)</li> <li><strong>EDGAR 2024</strong>: <a href="https://edgar.jrc.ec.europa.eu/report_2024">data/website</a>: European Commission, European Commision, JRC (2024), report: European Commission. Joint Research Centre & IEA. (2024)</li> <li><strong>EDGAR-HYDE 1.4</strong> <a href="http://themasites.pbl.nl/tridion/en/themasites/edgar/emission_data/edgar-hyde-100yr/edgar-hyde-1-4.html">data</a>: Van Aardenne et al. (2001), Olivier and Berdowski (2001)</li> <li><strong>FAOSTAT database</strong> <a href="http://www.fao.org/faostat/en/#data">data</a>: Food and Agriculture Organization of the United Nations (2024)</li> <li><strong>RCP historical data</strong> <a href="http://www.pik-potsdam.de/~mmalte/rcps/">data</a>, <a href="https://doi.org/10.1007/s10584-011-0156-z">paper</a>: Meinshausen et al. (2011)</li> <li><strong>UNFCCC National Communications and National Inventory Reports for developing countries available from the UNFCCC DI portal</strong> <a href="http://di.unfccc.int/detailed_data_by_party">website</a>, <a href="https://doi.org/10.5281/zenodo.12664477">data</a>: UNFCCC (2024e), Pflüger and Gütschow (2024), <a href="https://github.com/primap-community/FAOSTAT_data_primap/">github</a></li> <li><strong>UNFCCC Biannial Update Reports, National Communications, and National Inventory </strong><br><strong>Reports for developing countries</strong> <a href="https://unfccc.int/BURs">website-BURs</a>, <a href="https://unfccc.int/non-annex-I-NCs">website-NCs</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/main/extracted_data/UNFCCC">data</a>: UNFCCC (2024d), UNFCCC (2024b). <ul> <li>Notes: <ol> <li>Not all BUR and NC submissions are included as reading the data is time consuming and not all submission contain sufficient data to be used in PRIMAP-hist.</li> <li>Not all submissions included in PRIMAP-hist are available in the github repository as we do not (yet) have code that we can publish for all submissions.</li> <li>for a list of added submissions see section "Data source updates (v2.7)" in the chnagelogin the pdf data description.</li> </ol> </li> </ul> </li> <li><strong>UNFCCC First Biannial Transparency Reports</strong> <a href="https://unfccc.int/first-biennial-transparency-reports">website</a>, [<a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/main/extracted_data/UNFCCC">data</a>] UNFCCC (2025) <ul> <li>Notes: <ol> <li>For a list of added submissions see section "Data source updates (v2.7)" in the changelog in the pdf data description. </li> </ol> </li> </ul> </li> <li><strong>UNFCCC National Inventory Submissions 2025 (CRTAI)</strong> <a href="https://unfccc.int/ghg-inventories-annex-i-parties/2025">website</a>, <a href="https://doi.org/10.5194/essd-10-1427-2018">paper</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/main/extracted_data/UNFCCC">data</a>: UNFCCC (2024c) (processed based on Jeffery et al. (2018))</li> <li><strong>Official country repositories (non-UNFCCC)</strong> <ul> <li><strong>Belarus</strong>: Greenhouse gas statistics (1990-2022) <a href="https://www.belstat.gov.by/ofitsialnaya-statistika/makroekonomika-i-okruzhayushchaya-sreda/okruzhayuschaya-sreda/sovmestnaya-sistema-ekologicheskoi-informatsii2/b-izmenenie-klimata/b-3-vybrosy-parnikovyh-gazov/?_x_tr_sl=zh-TW&_x_tr_tl=en&_x_tr_hl=en-US&_x_tr_pto=wapp">website</a>: National Statistical Committee of the<br>Republic of Belarus (2024)</li> <li><strong>Mexico</strong>: 2023 Inventory <a href="https://historico.datos.gob.mx/busca/dataset/inventario-nacional-de-emisiones-de-gases-y-compuestos-de-efecto-invernadero-inegycei">website</a>,<a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/master/extracted_data/non-UNFCCC/Mexico"> data</a>: Instituto Nacional de Ecologia y Gambio Climatico (2025)</li> <li><strong>South Korea</strong>: 2024 Inventory <a href="https://www.gir.go.kr/home/index.do?menuId=36">website</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/master/extracted_data/non-UNFCCC/Republic_of_Korea">data</a>: Republic of Korea (2024)</li> <li><strong>Taiwan / Republic of China</strong>: 2024 Inventory <a href="https://www.cca.gov.tw/en/information-service/publications/national-ghg-inventory-report/12003.html">website</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/master/extracted_data/non-UNFCCC/Taiwan">data</a>: Republic of China - Environmental<br>Protection Administration (2024)</li> <li><strong>Pakistan</strong>: 2016 inventory report <a href="https://www.gcisc.org.pk/GHGINVENTORY2011-2012_FINAL_GCISCRR19.pdf">website</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/master/extracted_data/non-UNFCCC/Pakistan">data</a>: Mir and Ijaz (2016)</li> <li><strong>Philippines</strong>: NICCDIES National GHG Inventory <a href="https://niccdies.climate.gov.ph/ghg-inventory/national">website</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/master/extracted_data/non-UNFCCC/Philippines">data</a>: NICCDIES (2025)</li> <li><strong>USA</strong>: Draft 2025 National Inventory <a href="https://www.edf.org/freedom-information-act-documents-epas-greenhouse-gas-inventory">website</a>, <a href="https://github.com/JGuetschow/UNFCCC_non-AnnexI_data/tree/master/extracted_data/non-UNFCCC/United_States_of_America">data</a>: US EPA (2025)</li> </ul> </li> </ul> <p>For the pre-1990 LULUCF time-series we use the following additional data sources:</p> <ul> <li><strong>Houghton land use CO2</strong> <a href="http://cdiac.ornl.gov/trends/landuse/houghton/houghton.html">website</a>: Houghton (2008)</li> <li><strong>HYDE land cover data</strong> <a href="http://themasites.pbl.nl/tridion/en/themasites/hyde/download/index-2.html">website</a>: Klein Goldewijk et al. (2010), Klein Goldewijk et al. (2011)</li> <li><strong>SAGE Global Potential Vegetation Dataset</strong> <a href="https://nelson.wisc.edu/sage/data-and-models/global-potential-vegetation/index.php">website</a>: Ramankutty and Foley (1999)</li> <li><strong>FAO Country Boundaries</strong> <a href="http://ref.data.fao.org/map?entryId=18329470-472d-11db-88e0-000d939bc5d8">website</a>: Food and Agriculture Organization of the United Nations<br>(2015)</li> </ul> <p> </p> <p><strong>Files included in the dataset</strong></p> <p>For each dataset we have three files: the <em>.nc</em> file contains the data and metadata in the native PRIMAP2 netCDF based format. The <em>.csv</em> file contains the data in a csv format following the specifications of the PRIMAP2 interchange format. The metadata for the interchange format file is included in the <em>.yaml</em> file.</p> <ul> <li><strong>Guetschow-et-al-2025a-PRIMAP-hist_v2.7_final_22-Aug-2025.X</strong>: The main dataset with numerical extrapolation of all time series to 2024 and three significant digits.</li> <li><strong>Guetschow-et-al-2025a-PRIMAP-hist_v2.7_final_no_extrap_22-Aug-2025.X</strong>: Variant without numerical extrapolation of missing values and not including the country groups mentioned in section ["area (ISO3)"] (three significant digits).</li> <li><strong>Guetschow-et-al-2025a-PRIMAP-hist_v2.7_final_no_rounding_22-Aug-2025.X</strong>: The main dataset with numerical extrapolation of all time series to 2024 and eleven significant digits.</li> <li><strong>Guetschow-et-al-2025a-PRIMAP-hist_v2.7_final_no_extrap_no_rounding_22-Aug-2025.X</strong>: Variant without numerical extrapolation of missing values and not including the country groups mentioned in section ["area (ISO3)"] (eleven significant digits).</li> <li><strong>PRIMAP-hist_v2.7_data-description.pdf</strong>: Data description including changelog.</li> <li><strong>PRIMAP-hist_v2.7_updated_figures.pdf</strong>: Updated figures from the PRIMAP-hist paper published in ESSD.</li> <li><strong>changes_PRIMAP-hist_v2.7_final_nr_to_v2.6_final_nr.xlsx: </strong>xlsx file which lists relative changes per country, gas and main sector for 2005, 2015, 2020, 2022, 2023, and 1990-2023 (cumulative) from v2.6 to v2.7 (comparison between current version and October 2024 version).</li> <li><strong>changes_PRIMAP-hist_v2.7_final_nr_to_v2.6.1_final_nr.xlsx</strong>: xlsx file which lists relative changes per country, gas and main sector for 2005, 2015, 2020, 2022, 2023, and 1990-2023 (cumulative) from v2.6.1 to v2.7 (comparison between latest version and current version).</li> <li><strong>changes_PRIMAP-hist_v2.7_final_nr_CR_to_TP.xlsx</strong>: xlsx file which lists relative differences per country, gas and main sector for 2005, 2015, 2020, 2023, 2024, and 1990-2024 (cumulative) between country reported priority and third party priority scenarios.</li> <li><strong>changelog_v2.6_final_to_v2.6.1_final.zip</strong>: Detailed changelog in html format containing plots and a breakdown of changes to sectors and gases for all countries. Country specific notes ar also included. To use the changelog locally unpack the zip file and open the file in the "html" directory in your browser. The changelog is also available on the <a href="https://primap.org/primap-hist/">primap.org</a> website.</li> </ul> <p><strong>Notes</strong></p> <ul> <li>Emissions from international aviation and shipping are not included in the dataset.</li> <li>Emissions from Land Use, Land-Use Change, and Forestry (LULUCF) are not included in the main version of this dataset. They are included in the version without rounding as users need to take extra care when using LULUCF data because changes some of the year-to-year changes in the data come from using different sources or methodology changes within a source rather than changes in actual emissions.</li> </ul> <p><strong>Data format description</strong></p> <p>The PRIMAP-hist data in the comma-separated values (CSV) files is formatted consistently with the PRIMAP2 interchange format.</p> <p>The data contained in each column are as follows:</p> <p><em>"source"</em></p> <p>Name of the data source. Here: <em>PRIMAP-hist_v2.7</em> with suffixes <em>_ne</em> for no extrapolation and <em>_nr</em> for no rounding.</p> <p><em>"scenario (PRIMAP)"</em></p> <ul> <li>HISTCR: In this scenario country-reported data (CRT, BUR / NIR / NC / UNFCCCDI) are prioritized over third-party data (CDIAC, FAO, Andrew, EDGAR, BP).</li> <li>HISTTP: In this scenario third-party data (CDIAC, FAO, Andrew, EDGAR, BP) are prioritized over country-reported data (CRT, BUR / NIR / NC / UNFCCCDI)</li> </ul> <p><em>"provenance"</em></p> <p>Provenance of the data. Here: "derived" as it is a composite source.</p> <p><em>"country"</em></p> <p>ISO 3166 three-letter country codes or custom codes for groups:</p> <table> <tbody> <tr> <td><strong>Code</strong></td> <td><strong>Region description</strong></td> </tr> <tr> <td>EARTH</td> <td>Aggregated emissions for all countries.</td> </tr> <tr> <td>ANNEXI</td> <td>Annex I Parties to the Convention</td> </tr> <tr> <td>NONANNEXI</td> <td>Non-Annex I Parties to the Convention</td> </tr> <tr> <td>AOSIS</td> <td>Alliance of Small Island States</td> </tr> <tr> <td>BASIC</td> <td>BASIC countries (Brazil, South Africa, India and China)</td> </tr> <tr> <td>EU27BX</td> <td>European Union post Brexit</td> </tr> <tr> <td>LDC</td> <td>Least Developed Countries</td> </tr> <tr> <td>UMBRELLA</td> <td>Umbrella Group</td> </tr> </tbody> </table> <p>Table: Additional "country" codes.</p> <p><em>"category"</em></p> <p>IPCC (Intergovernmental Panel on Climate Change) 2006 categories for emissions. Some aggregate sectors have been added to the hierarchy. These begin with the prefix <em>M</em>.</p> <table> <tbody> <tr> <td><strong>Code</strong></td> <td><strong>Description</strong></td> <td><strong>Gases covered</strong></td> </tr> <tr> <td>M.0.EL</td> <td>National Total excluding LULUCF</td> <td>all</td> </tr> <tr> <td>1</td> <td>Energy</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>1.A</td> <td>Fuel Combustion Activities</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>1.B</td> <td>Fugitive Emissions from Fuels</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>1.B.1</td> <td>Solid Fuels</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>1.B.2</td> <td>Oil and Natural Gas</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>1.B.3</td> <td>Other Emissions from Energy Production</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>1.C</td> <td>Carbon Dioxide Transport and Storage</td> <td>CO2</td> </tr> <tr> <td>2</td> <td>Industrial Processes and Product Use (IPPU)</td> <td>CO2, CH4, N2O, f-gases</td> </tr> <tr> <td>2.A</td> <td>Mineral Industry</td> <td>CO2</td> </tr> <tr> <td>2.B</td> <td>Chemical Industry</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>2.C</td> <td>Metal Industry</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>2.D</td> <td>Non-Energy Prod. from Fuels and Solvent Use</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>2.E</td> <td>Electronics Industry</td> <td>N2O (f-gases emitted but not resolved)</td> </tr> <tr> <td>2.F</td> <td> <p>Product uses as Substitutes for Ozone Depleting Substances </p> <p>(no data available as the category is only used for fluorinated gases which are only resolved at the level of category 2)</p> </td> <td>--</td> </tr> <tr> <td>2.G</td> <td>Other Product Manufacture and Use</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>2.H</td> <td>Other</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>M.AG</td> <td>Agriculture, sum of 3.A and M.AG.ELV</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>3.A</td> <td>Livestock</td> <td>CH4, N2O</td> </tr> <tr> <td>M.AG.ELV</td> <td>Agriculture excluding Livestock</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>4</td> <td>Waste</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>5</td> <td>Other</td> <td>CO2, CH4, N2O</td> </tr> </tbody> </table> <p>Table: Category descriptions using IPCC 2006 terminology.</p> <p>The categories are organized in a hierarchy where children of each category sum to the parent category. The full IPCC2006 category hierarchy contains many more subcategories, but data availability is not sufficient to resolve the full IPCC category tree in PRIMAP-hist. However, we will regularly assess if the available data allows for resolving addition subcategories. The categories currently resoved by PRIMAP-hist are organized as follows.<br><br> M.0.EL Total emissions excluding LULUCF<br> ├1 Energy<br> │├1.A Fuel Combustion Activities <br> │├1.B Fugitive Emissions from Fuels<br> ││├1.B.1 Solid Fuels<br> ││├1.B.2 Oil and Natural Gas<br> ││╰1.B.3 Other Emissions from Energy Production<br> │╰1.C Carbon Dioxide Transport and Storage<br> ├2 Industrial Processes and Product Use<br> │├2.A Mineral Industry<br> │├2.B Chemical Industry<br> │├2.C Metal Industry<br> │├2.D Non-Energy Products from Fuels and Solvent Use<br> │├2.E Electronics Industry<br> │├2.F Product Uses as Substitutes for Ozone Depleting Substances<br> │├2.G Other Product Manufacture and Use<br> │╰2.H Other<br> ├4 Waste<br> ├5 Other<br> ╰M.AG Agriculture<br> ├3.A Livestock<br> ╰M.AG.ELV Agriculture excluding Livestock<br><br><br>The "no_rounding" version of the dataset additionally contains data for the "Land Use, Land Use Change, and Forestry" sector and sectors sums including this sectors</p> <table> <tbody> <tr> <td><strong>Code</strong></td> <td><strong>Description</strong></td> <td><strong>Gases covered</strong></td> </tr> <tr> <td>0</td> <td>National Total including LULUCF</td> <td>CO2, CH4, N2O, f-gases</td> </tr> <tr> <td>3</td> <td>Agriculture, Forestry and Other Land Use (AFOLU)</td> <td>CO2, CH4, N2O</td> </tr> <tr> <td>M.LULUCF</td> <td>Land Use, Land Use Change, and Forestry</td> <td>CO2, CH4, N2O</td> </tr> </tbody> </table> <p>Table: Additional category descriptions using IPCC 2006 terminology.<br><br>PRIMAP-hist uses a distinction between agriculture and Land Use, Land Use Change and Forestry which are combined into the AFOLU sector in IPCC2006 categories. Thus, in contrast to the standard IPCC 2006 categories, category 3 "Agriculture, Forestry, and Other Land Use" is subdivided as follows:<br><br> 3 Agriculture, Forestry, and Other Land Use<br> ├M.AG Agriculture<br> │├3.A Livestock<br> │╰M.AG.ELV Agriculture excluding Livestock<br> ╰M.LULUCF Land Use, Land Use Change, and Forestry<br><br>Where a national total including LULUCF is reported, it is calculated as the sum of "M.0.EL Total emissions excluding LULUCF" and "M.LULUCF Land Use, Land Use Change, and Forestry":<br><br> 0 National Total<br> ├M.0.EL Total emissions excluding LULUCF<br> │├1 Energy<br> │├2 Industrial Processes and Product Use<br> │├4 Waste<br> │├5 Other<br> │╰M.AG Agriculture<br> ╰M.LULUCF Land Use, Land Use Change, and Forestry<br><br><br>"<em>entity</em>"<br><br>Gas baskets using global warming potentials (GWP) from the Second Assessment Report (SAR), Fourth Assessment Report (AR4), Fifth Assessment Report (AR5), Sixth Assessment Report (AR6).</p> <table> <tbody> <tr> <td><strong>Code</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>CH4</td> <td>Methane</td> </tr> <tr> <td>CO2</td> <td>Carbon Dioxide</td> </tr> <tr> <td>N2O</td> <td>Nitrous Oxide</td> </tr> <tr> <td>HFCS (SARGWP100)</td> <td>Hydrofluorocarbons (SAR)</td> </tr> <tr> <td>HFCS (AR4GWP100)</td> <td>Hydrofluorocarbons (AR4)</td> </tr> <tr> <td>HFCS (AR5GWP100)</td> <td>Hydrofluorocarbons (AR5)</td> </tr> <tr> <td>HFCS (AR6GWP100)</td> <td>Hydrofluorocarbons (AR6)</td> </tr> <tr> <td>PFCS (SARGWP100)</td> <td>Perfluorocarbons (SAR)</td> </tr> <tr> <td>PFCS (AR4GWP100)</td> <td>Perfluorocarbons (AR4)</td> </tr> <tr> <td>PFCS (AR5GWP100)</td> <td>Perfluorocarbons (AR5)</td> </tr> <tr> <td>PFCS (AR6GWP100)</td> <td>Perfluorocarbons (AR6)</td> </tr> <tr> <td>SF6</td> <td>Sulfur Hexafluoride</td> </tr> <tr> <td>NF3</td> <td>Nitrogen Trifluoride</td> </tr> <tr> <td>FGASES (SARGWP100)</td> <td>Fluorinated Gases (SAR): HFCs, PFCs, SF6, NF3</td> </tr> <tr> <td>FGASES (AR4GWP100)</td> <td>Fluorinated Gases (AR4): HFCs, PFCs, SF6, NF3</td> </tr> <tr> <td>FGASES (AR5GWP100)</td> <td>Fluorinated Gases (AR5): HFCs, PFCs, SF6, NF3</td> </tr> <tr> <td>FGASES (AR6GWP100)</td> <td>Fluorinated Gases (AR6): HFCs, PFCs, SF6, NF3</td> </tr> <tr> <td>KYOTOGHG (SARGWP100)</td> <td>Kyoto greenhouse gases (SAR)</td> </tr> <tr> <td>KYOTOGHG (AR4GWP100)</td> <td>Kyoto greenhouse gases (AR4)</td> </tr> <tr> <td>KYOTOGHG (AR5GWP100)</td> <td>Kyoto greenhouse gases (AR5)</td> </tr> <tr> <td>KYOTOGHG (AR6GWP100)</td> <td>Kyoto greenhouse gases (AR6)</td> </tr> </tbody> </table> <p>Table: Gas categories and underlying global warming potentials</p> <p><em>"unit"</em></p> <p>Unit is either <em><substance> * gigagram / a</em> where substance is the entity or for CO2 equivalent units <em>CO2 * gigagram / a</em>. The CO2-equivalent is calculated according to the global warming potential indicated by the entity (see above).</p> <p><em>Remaining columns</em></p> <p>Years from 1750-2024.</p> <p><strong>Changelog</strong></p> <p>For the changelog we refer to the pdf version of the data description available for download here</p> <p><strong>References</strong></p> <p>For the full references we refer to the references section and the pdf version of the data description available for download here.</p>
Historical Emission Inventory Database for Shipping
<p><span>The global historical shipping emission inventory dataset covers CO<sub>2</sub> and five key </span><span>atmospheric pollutants (</span><span>NO<em><sub>x</sub></em>, SO<sub>2</sub>, CO, NMVOCs and PM) over the time period from 1970 – 2021 and has been allocated to 0.1</span><span>°×</span><span>0.1</span><span>°</span><span> grids on a bilateral basis.</span><span> </span></p>
Historical and Future Global Wetland Methane Emissions from 1979 to 2100
<p>This dataset supports the manuscript "Quantifying Global Wetland Methane Emissions with In Situ Methane Flux Data and Machine Learning Approaches" currently under review. Before reusing this data, please contact the first author (chen4371@purdue.edu) for citations and recent updates.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.