Many organizations quantify greenhouse emissions in their value chain. Emissions from purchased goods and services and capital goods, referred to as Scope 3 emissions in the Greenhouse Gas Protocol Scope 3 Accounting and Reporting Standard, represent a significant emissions source for many organizations. To assist in quantifying these emissions, we have developed a comprehensive set of supply chain emission factors covering all categories of goods and services in the US economy. These factors are intended for quantifying emissions from purchased goods and services using the spend-based method defined in the Greenhouse Gas Protocol Technical Guidance for Calculating Scope 3 Emissions. The factors were prepared using USEEIO models, which are a life cycle models of goods and services in the US economy. The supply chain emission factors are presented in units of kilogram emissions per US dollar of purchases for a category of goods and services with a defined life cycle scope. Sets of factors covering all sectors of the economy are provided for years from 2010 to 2016 with two levels of sector aggregation. The factors are provided for both industries and commodities, where commodities are equivalent to a category of good or service, and industries are producers of one or more commodities. A set of five data quality scores covering data reliability, temporal, geographical and technological correlation and completeness of data collection is provided along with each factor. The factors presented are as follows: 1. Supply Chain Emission Factors without Margins: emissions associated with cradle to factory gate 2. Margins of Supply Chain Emission Factors: emissions associated with factory gate to shelf, which includes emissions from transportation, wholesale and retail as well as adjustments for price markups 3. Supply Chain Emission Factors with Margins: emissions associated with cradle to shelf (equal to the sum of the above two factors) End users of products will likely find the Supply Chain Emission Factors with Margins most appropriate for their use. Organizations purchasing intermediate products at the factory gate will likely find the Supply Chain Emission Factors without Margins to be most appropriate. See the Executive Summary of the associated report for an example calculation using the factors. All factors are associated with limitations and variations in underlying data quality. We encourage the reader to carefully read the report to understand the differences across these sets, underlying assumptions in their calculation, their limitations to decide if they are appropriate for their intended use. If the reader deems the factors are appropriate, this report along with the factor data quality scores will aid in selection of factors best fit for their intended use. This dataset is associated with the following publication: Ingwersen, W., and M. Li. Supply Chain Greenhouse Gas Emission Factors for US Industries and Commodities. U.S. Environmental Protection Agency, Washington, DC, USA, 2020.

The datasets comprise greenhouse gas (GHG) emission factors (Factors) for 1,016 U.S. commodities as defined by the 2017 version of the North American Industry Classification System (NAICS). The Factors are based on GHG data for 2022. Factors are given for all NAICS-defined commodities at the 6-digit level except for electricity, government, and households. Each record consists of three factor types as in the previous releases: Supply Chain Emissions without Margins (SEF), Margins of Supply Chain Emissions (MEF), and Supply Chain Emissions with Margins (SEF+MEF). One set of Factors provides kg carbon dioxide equivalents (CO2e) per 2022 U.S. dollar (USD) for all GHGs combined using 100-yr global warming potentials from IPCC 5th report (AR5) to calculate the equivalents. In this dataset there is one SEF, MEF and SEF+MEF per commodity. The other dataset of Factors provides kg of each unique GHG emitted per 2022 dollar per commodity without the CO2e calculation. The dollar in the denominator of all factors uses purchaser prices. See the supporting file 'Aboutv1.3SupplyChainGHGEmissionFactors.docx' for complete documentation of this dataset.

Tables presenting supply chain and margin emission factors and data quality scores for US commodities and industries calculated from USEEIO models at two levels of commodity/industry categorization, detail and summary, for both industries and commodity, and annually from 2010-2016. See the EPA report for full details on emission factor preparation. These factors were produced by knitting the GenerateEmissionFactorsDataset.Rmd file in RStudio using the supply-chain-factors code, v1.1.1 at https://github.com/USEPA/supply-chain-factors/releases/tag/v1.1.1. This dataset is associated with the following publication: Ingwersen, W., and M. Li. Supply Chain Greenhouse Gas Emission Factors for US Industries and Commodities. U.S. Environmental Protection Agency, Washington, DC, USA, 2020.

This dataset consists of various USEEIO v2.5 models. All models are built using the coupled model approach described in the EPA 2024 report "Estimating embodied environmental flows in international imports for the U.S. Environmentally-Extended Input-Output (USEEIO) Model" and using the v1.7.0 release of useeior. Models are named using an alias that corresponds with a unique set of model attributes, and the final two digits represent the last two digits of the year intended to be represented. Model alias attributes are defined at https://github.com/USEPA/USEEIO/blob/master/models.md#aliases. Catbird and oriole are detailed and summary-level models, respectively, coupled with CEDA 2024 for representing GHGs in imports. Kinglet and kingbird are detailed and summary-level models, respectively, coupled with EXIOBASE v3.8.2 for representing GHGs in imports. Waxwing and yellowthroat are detailed and summary-level models, respectively, coupled with the GLORIA v59a model for representing GHGs and material flows in imports. The summary level models are available for 2017-2022 for EXIOBASE- and GLORIA-coupled models and 2022 for the CEDA-coupled model. The detailed CEDA, EXIOBASE and GLORIA coupled models are only available for 2022 (note underlying U.S. IO data represents 2017 for detailed models). "v2.5-kingbird-" models replace "v2.3-s-GHG-" models, published under "USEEIO Models with Import Emission Factors for Greenhouse Gases for 2017-2022 from EXIOBASE coupled model". "v2.5-oriole-22" replaces "v2.4-oriole-22" , published under "USEEIO Models with Import Emission Factors for Greenhouse Gases for 2022 from CEDA coupled model". The model objects are in unique tabs/worksheets of each file and defined in https://github.com/USEPA/useeior/blob/v1.7.0/format_specs/Model.md. Links to the model specification files are provided below. More information can be found on these models in two additions to the original EPA report "Estimating embodied environmental flows in international imports for the USEEIO Model" https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=362470. The "Corrigendum: Updated Results for Consumption-based GHG Emissions" describes updates related to the EXIOBASE and CEDA coupled models. Addendum 2 describes the GLORIA coupled models. Please cite this dataset as "Young, Ben, and Wesley Ingwersen. 2025. USEEIO v2.5 Models. Data.gov. https://doi.org/10.23719/1532178.". This dataset is associated with the following publication: Ingwersen, W.W., J. Namovich, B. Young, and J. Vendries. Estimating embodied environmental flows in international imports for the USEEIO Model. U.S. Environmental Protection Agency, Washington, DC, USA, 2024.

These data are fully described in the associated EPA report. The Import Shares (ISs) are provided in a single Excel file covering all years. The Import Emission Factors (IEFs) are provided in csv files by year and by level of commodity classification, with names starting with "US_detail_import_factors" for detail-level commodity classification and "US_summary_import_factors" for summary-level commodity classification. USEEIO models (v2.3) with these IEFs were built using useeior v1.6.0 and written out to Excel files. Import emission factors are incorporated into these USEEIO models where they are further transformed into producer price and found in the M_n sheet of the model Excel files. Table 6 in the report shows year and level of commodity classification for each model along with which IEF file is used. The files with model names ending in *.yml are the model specification files for each of the published models. Correspondence files are provided that are used to (1) map EXIOBASE commodities to USEEIO commodities, (2) map BEA service category data to USEEIO sectors, and (3) map EXIOBASE Country/Region to BEA Service, Census Goods and TiVA trade regions. Data dictionaries for file types: USEEIO models (Excel) - https://github.com/USEPA/useeior/blob/v1.6.0/format_specs/Model.md Model spec files https://github.com/USEPA/useeior/blob/v1.6.0/format_specs/ModelSpecification.md Import shares - Data dictionary found in file Import Emission Factors (csv) - https://github.com/USEPA/USEEIO/blob/6cdd903fe5be58941c833f4cf585313f7e40d2a7/import_factors_exio/README.md Correspondence files - https://github.com/USEPA/USEEIO/blob/fe48b5bc79ca994624838ce3b8171b9c65b691e2/import_factors_exio/concordances/README.md

The Eora global supply chain database consists of a multi-region input-output table (MRIO) model that provides a time series of high-resolution IO tables with matching environmental and social satellite accounts for 190 countries.