Aquaculture and Thermoelectric withdrawals are assigned to the 4-digit NAICS codes 1125 and 2211, respectively. https://www.epa.gov/sites/production/files/2018-07/documents/nei2014v2_tsd_05jul2018.pdf (U.S. Environmental Protection Agency, 2018). USEEIO v2.0 described herein is a commodity model with the full breadth of US economic output split into 411 commodity categories. Derivation of these demand vectors is described in depth in the Final Demand section, since these have not been previously described in USEEIO documentation. Accordingly, the allocation factor to the disaggregated Solid waste collection rows is approximately 44% (21/48) of the total Waste management and remediation services commodity consumption for all USEEIO industries mapped to the Business firms and farms customer class. This EPA report describes supply chain GHG emission factors prepared with versions of the USEEIO, which are life cycle models of all categories of goods and services and industries in the US economy. In general, the final demand in the BEA Use table can be grouped into the following categories: yg=federal, state and local government consumption. The scope 3 emissions for one organization are the scope 1 and 2 emissions of another organization. Sustainable Materials Management Prioritization Tools Provider. Household consumption accounts for the largest share of the global anthropogenic greenhouse gases (GHG) emissions. 11:30-12:15. For example, releases of nitrogen and phosphorous are sourced from the Nitrogen and Phosphorus Release from Agriculture satellite table (NPAG) specifically for agricultural sectors, while data for all other sectors are sourced from the Discharge Monitoring Report via the Point source releases to water satellite table (WATREL). The increase in HRSP for Cattle in v2.0 is due to the improved modeling of dust from livestock31. Where multiple 6-digit NAICS are present, the following assumptions are used: 56211: Most of the flows are to the Hazardous waste collection sector (more detail on this below). environmental pollution waste material air pollution water pollution, economic input-output data environmental release data resource use data. direct emissions, waste generation, or resource use). For most sectors, the commodity values are distributed using the percentages obtained from the disaggregation of the waste management industries in the Use table. A summary of life cycle impact assessment results from v2.0 for 2012 total US production and consumption are presented in Table8. In v1 models, the direct and total requirements were determined from analysis to be adequate in representation of 2013 conditions (see SI1 from Yang et al. The 2021 edition is no longer available for purchase. PubMed Central The right side of Eq. https://www.eia.gov/dnav/ng/ng_prod_sum_a_EPG0_FGW_mmcf_m.htm (2021). ACID in utilities, manufacturing and transportation sectors is largely driven by criteria air pollutant emissions like sulfur dioxide (SO2) and nitrogen oxides (NOX). Birney, C., Li, M. & Ingwersen, W. National employment totals by industry 2017 v1.1. Livestock water withdrawals are allocated proportionally using water use by animal type, calculated from the USDA animal inventory and national median water intake rates by animal type48,50. Sci. The earlier versions of USEEIO used the BLS National Employment Matrix, which also publishes employment data by NAICS sector codes5. Significant decreases in HRSP are visible in agricultural sectors except in Cattle. Overview Emissions Factors FAQ Data sets Emissions factors 2 files Emissions factors File Updated Download IEA Emissions Factors 2021 15/09/2021 XLS IEA Emissions Factors 2021 (light version) 15/09/2021 XLSB Schedule In Eq. Recycl. Young, B. et al. Land for national parks is directly assigned to NAICS code 712190, where previously, in both the original USEEIO land satellite table and in Zengs work, national parks were included in the unaccounted land category. Environ. Birney, C. et al. Impact of locational choices and consumer behaviors on personal land footprints: An exploration across the urban-rural continuum in USA. The v2 industry output and commodity output totals for each commodity and industry in the model were both found to be within 1% of the original totals. As v1.2 represents the most recently previously peer-reviewed and published USEEIO model, but was built with a different set of data inputs and a different software procedure, comparing v2.0 results against v1.2 is a relevant means of performing model validation. The employment sector attribution model is created by importing and formatting the 2017 BLS Quarterly Census of Employment and Wages (QCEW) table58. The model indicators are put in the form of an indicator x flow matrix, C, where the values are the quantitative relation of the flows to the indicator value, also known as characterization factors in the life cycle impact assessment literature. Assessing the flows or processes (i.e. Perspect. The variation between v1.2 and v2.0 employment impact intensities are due to changes in data year and source. The information is tracked by how facilities manage hazardous waste as generators, transporters, or treatment, storage, and disposal facilities (TSDF). J. Econ. The diagonal-only production assumption is a good first approximation that allows the production impacts from a specific type of waste management service to be assigned to a single sector. However, annual tables are also published at a more aggregated level of detail and with less reported data but with only a ~12 year time lag to help address the time lag limitations12. 1. Single sources of data for a given flow are generally insufficient for providing environmental and economic performance at the level of resolution required for v2.0s 400+ industries, and therefore modeling is required to attribute or allocate environmental data from often multiple raw sources to this level of industry resolution. Emissions from purchased goods and services and capital goods represent a significant emissions source for many organizations. However, in v2.0, releases to water also include organic enrichment, sediments, and other compounds tracked within the DMR. and JavaScript. The flow-by-sector method names for the corresponding datasets are shown in Table9. For v2.0, Waste management and remediation services is disaggregated into the seven sectors shown in Table5. USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. The commodity is allocated proportionate to the allocation percentages used for the 562111, 562212, 562213, and 562920 sectors in the Use table row (commodity) totals. Report No. EPA's supply chain GHG emission factors are based on US Environmentally-Extended Input-Output models and are presented in emissions per dollar of spend. For example, if an organization produces electronic equipment, Category 11 (use of sold products) may likely be a large source of emissions. Contact. Overview of Access Formats/Outlets. Priscilla Halloran, Jarrod Bridge and David Meyer provided input to on USEEIO model updates. (Springer Science & Business Media, 2002). Use the Previous and Next buttons to navigate the slides or the slide controller buttons at the end to navigate through each slide. The largest consumers are residential users (F01000, Personal consumption expenditures final demand) at 24% of total consumption; state and local governments (GSLGO, State and local government and other services) at 13% of total consumption; and Other real estates (531ORE) and the Waste management and remediation services sector itself, both at 8% of total consumption. In v2.0, the USDA CoA land in farms data are used as an allocation source, rather than as a primary data source. The Bureau of Economic Analysis (BEA) 2012 Detail IO tables10 define 405 commodity categories. Irrigation Golf Courses water withdrawals are assigned to NAICS 713910. New procedures for preparing and integrating these datasets into the model are described in the Procedure for Model Building section. The 2012 BEA Detail Make and Use Tables Before Redefinitions in Producers Price are used as the underlying IO tables. Additionally, the Water_national_2015_m1 methodology differs from Water Use Satellite table compiled for v1 for Crop Irrigation, Industrial, Mining, Thermoelectric, and Hydroelectric water estimates. The 5-digit NAICS in the RCRAInfo codes do not count flows present in the 6-digit codes. Report No. 16. However, changes in the Make Transactions have resulted in a substantial increase in the quantity assigned to the Corn products commodity; Other basic organic chemicals, which is one of the largest generators of CRHW, supplies a significantly higher share of Corn products in the make transactions, increasing from approximately 4% of total commodity output in 2007 to 37% in 2012. If not, default heat contents are provided. Google Scholar. 13. [email protected]. N is an indicator x sector matrix and contains in each row i the direct and indirect impact result per 1 USD output of sector j. The 562000 commodity represents over 97% of the industrys total output. Report No. The data includes fresh and saline water withdrawn from surface and ground sources and evaporative water loss to the atmosphere. EPA/600/R-20/001). Report No. The GHG Emission Factors Hub provides factors for several scope 3 categories and indicates the calculation methods with which the factors align. State and local general government is split into education and other services in the 2012 IO tables, resulting in a fall in ranking but occupying two spots in the top 20. Emission Factor Database Last modified 23 Nov 2020 1 min read This viewer presents selected emission factors and abatement efficiencies included in the EMEP/EEA Guidebook 2019. The same indicators used in v1.113 along with the three indicators (CNHW, CNHWC, CRHW) for waste generation8 are used in v2.0 (Table3). The Economic Census data provides monetary receipt values by detailed NAICS codes and customer class. This adjustment results in different allocation factors from the Use table columns, and are included in the WasteDisaggregation_Use sheet of the primary data record in the VA disaggregation rows. It is the best value for money option. The emission factor rating takes into account the test rating, the number of sources tested, and whether the sources are selected at random, represent the industry population, and are sufficiently specific (e.g., to fuel type, design, etc.) The EEIO sector also determines whether the project type is for construction or operation more broadly, and each has a very different greenhouse gas emissions profile. In Eq. Chinese environmentally extended input-output database for 2017 and 2018, Implementing the material footprint to measure progress towards Sustainable Development Goals 8 and 12, Contributions of sociometabolic research to sustainability science, CO2 emission accounts of Russias constituent entities 20052019, A low energy demand scenario for meeting the 1.5C target and sustainable development goals without negative emission technologies, Food systems are responsible for a third of global anthropogenic GHG emissions, Variation in trends of consumption based carbon accounts, An emissions-socioeconomic inventory of Chinese cities, US Environmentally-Extended Input-Output (USEEIO) model, Sustainable Materials Management Prioritization Tools, models are listed on the model technical content webpage, https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=CESER&dirEntryId=349324, https://doi.org/10.1016/j.jclepro.2017.04.150, https://pasteur.epa.gov/uploads/10.23719/1365565/documents/USEEIOv1.1-DescriptionofSatelliteTableUpdates.pdf, https://doi.org/10.1016/j.resconrec.2020.104795, https://www.bea.gov/industry/input-output-accounts-data, https://www.bea.gov/resources/methodologies/concepts-methods-io-accounts, https://doi.org/10.1080/0953531042000219286, https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=347251, https://www.census.gov/data/tables/2012/econ/census/aswmrs-services.html, https://www.census.gov/data/tables/2015/econ/services/sas-naics.html, https://www.epa.gov/hwgenerators/biennial-hazardous-waste-report, https://www.census.gov/naics/concordances/2012_to_2007_NAICS.xls, https://www.census.gov/naics/2012NAICS/2-digit_2012_Codes.xls, https://www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei, http://www2.epa.gov/toxics-release-inventory-tri-program/tri-data-and-tools, https://www.eia.gov/consumption/manufacturing/data/2010/, https://www.epa.gov/sites/production/files/2018-07/documents/nei2014v2_tsd_05jul2018.pdf, https://echo.epa.gov/trends/loading-tool/water-pollution-search, https://www.ers.usda.gov/webdocs/publications/84880/eib-178.pdf?v=6791.3, https://www.eia.gov/consumption/commercial/, https://www.blm.gov/sites/blm.gov/files/pls07.pdf, https://www.ers.usda.gov/publications/pub-details/?pubid=44630, https://www.bls.gov/cew/downloadable-data-files.htm, https://www.ers.usda.gov/publications/pub-details/?pubid=101624, https://www.nass.usda.gov/Publications/AgCensus/2017/Full_Report/Volume_1,_Chapter_1_US/usv1.pdf, https://www.nass.usda.gov/Publications/AgCensus/2017/Online_Resources/Farm_and_Ranch_Irrigation_Survey/fris.pdf, https://www.eia.gov/dnav/ng/ng_prod_sum_a_EPG0_FGW_mmcf_m.htm, https://www.usgs.gov/mission-areas/water-resources/science/water-use-terminology?qt-science_center_objects=0#qt-science_center_objects, http://edap-data-commons.s3.amazonaws.com/data_commons_search.html, https://doi.org/10.6084/m9.figshare.17145878.v1, https://databank.worldbank.org/reports.aspx?source=2&type=metadata&series=EN.ATM.CO2E.PC#, https://doi.org/10.6084/m9.figshare.17269211, https://doi.org/10.6084/m9.figshare.17377805, https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks-1990-2016, https://www.epa.gov/ozone-layer-protection/international-actions-montreal-protocol-substances-deplete-ozone-layer, https://doi.org/10.6084/m9.figshare.19100375.v1, https://www.eia.gov/totalenergy/data/monthly/, https://www.bea.gov/products/industry-economic-accounts/underlying-estimates, https://www.blm.gov/sites/blm.gov/files/pls2012-web.pdf, https://s3-us-west-2.amazonaws.com/prd-wret/assets/palladium/production/mineral-pubs/mcs/mcs2014.pdf, https://www.eia.gov/electricity/data/eia923/archive/xls/f923_2014.zip, http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/, https://www2.calrecycle.ca.gov/WasteCharacterization/PubExtracts/2014/GenSummary.pdf, https://www.epa.gov/sites/production/files/2016-11/documents/2014_smmfactsheet_508.pdf, http://creativecommons.org/licenses/by/4.0/, At the intersection of life cycle assessment and indirect greenhouse gas emissions accounting. 3.3), the Ld and a demand vector derived from Yd are used. A similar approach is used to calculate the direct+indirect impacts x sector with the direct perspective as Hr but it uses includes the D direct impact matrix to characterize those flows as shown in Eq. Miller, R. & Blair, P. Input-output analysis: Foundations and extensions. Solley, W. B., Pierce, R. R. & Perlman, H. A. https://echo.epa.gov/trends/loading-tool/water-pollution-search (U.S. Environmental Protection Agency, 2018). U.S. EPA Office of Research and Development (ORD) https://doi.org/10.23719/1368541 (2017). This sector provides a wide range of services from non-hazardous waste landfilling and recycling to contaminated site remediation. Scope 3 emission sources include emissions both upstream and downstream of the organizations activities. Global warming potential (GWP) is a factor describing the radiative forcing impact (degree of harm to the atmosphere) of one unit of a given GHG, relative to one unit of CO 2 over a 100-year time horizon. 25. https://www2.calrecycle.ca.gov/WasteCharacterization/PubExtracts/2014/GenSummary.pdf (Calrecycle, 2015). 26. where HRoW is the contribution from Rest of World, and Hd is the contribution from the US. The Sector Crosswalk can be used to identify a NAICS code associated with a USEEIO code, and tools like the Census NAICS code search75 can be used to identify NAICS codes associated with the purchase. This check is performed by using Eq. AC-17-SS-1 https://www.nass.usda.gov/Publications/AgCensus/2017/Online_Resources/Farm_and_Ranch_Irrigation_Survey/fris.pdf (U.S. Department of Agriculture, 2019). A .gov website belongs to an official government organization in the United States. Google Scholar. To obtain Capital letters indicate matrices and lower case letters indicate vectors. Multiplying emissions of a given GHG by its GWP gives us the CO 2 equivalent emissions. 2012 Economic Census: Administrative and Support and Waste Management and Remediation Services: Subject Series - Product Lines: Product Lines Statistics by Industry for the U.S. And States: 2012. https://www.census.gov/data/tables/2012/econ/census/aswmrs-services.html (U.S. Census Bureau, 2013). - Government published carbon conversion factors. The modeling steps were written in Python and consolidated into a software package called flowsa. 15. where Gr is the direct+indirect flows x sector matrix and s is a scaling vector. 3, B is in flow x commodity form after transforming BI into this form with the market shares matrix transformation. The environmental datasets not updated since v1.2 include the Commercial non-hazardous waste excluding construction activities, Commercial non-hazardous waste from construction activities, Nitrogen and Phosphorus Releases from Agriculture, Pesticide releases, Mineral extraction, and Energy extraction (Table2). The Recycling Economic Information (REI) Report, a primary output of the Recycling Economic Information (REI) Projectrelieson environmental and economic input-output methodologies for estimating environmental and economic impacts associated with recycling. https://www.epa.gov/ozone-layer-protection/international-actions-montreal-protocol-substances-deplete-ozone-layer (2015). For example, the 2014 QCEW estimates 279 thousand private household employees, while the National Employment Matrix estimates 821 thousand employees. Parallel decreases to that seen in ACID can be seen in the SMOG indicator. Ingwersen, W., Yang, Y., Gilkey, K. & Li, M. USEEIOv1.1 - Satellite Tables. We define production as final use, either within the US or abroad, of all goods and services that are produced in the US. 6 above, but using the commodity gross output chain price index in place of the industry gross output chain price index. The same default set of indicators used in the SMM Prioritization Tools were used in this ranking for both models. Pairing the domestic proportion with the ranking figure (Fig. The direct perspective calculation associates the totals with the sectors that produce the given flows (e.g. How are emission factors developed? Conserv. US Territories and Tribal Lands are not included. The Criteria Air and GHG emissions data from 2017 and 2016, respectively, that drive these data replaced 2011 and 2013 data in v1.2 and likely reflect the continued phase out and substitution of ozone depleting substances70. Young, B., Birney, C. & Ingwersen, W. National point source releases to water by industry 2017 v1.1. Young, B., Birney, C. & Ingwersen, W. National commercial hazardous waste totals by industry 2017 v1.1. This can be represented in unit form in Eq. Birney, C., Conner, M., Specht, J. Read more in their annualcarbon disclosurereport. volume9, Articlenumber:194 (2022) Where the BLS is missing data, less aggregated NAICS are summed, or more aggregated NAICS are equally allocated. Emission factors may be quantified in a handful of ways. v1.2 was created using the 2014 BLS National Employment Matrix, while v2.0 was created with 2017 BLS QCEW. These datasets are more current than the IO data, and more closely represent current environmental performance. The construction sectors, Single family homes, Other residential structures, and Housing, have all dropped significantly in the ranking, the latter two no longer appearing in the top 20. The data is built upon the US EPA's National Greenhouse Gas Industry Attribution Model. Chemical releases to water are sourced from 2017 facility reported emissions data from the Toxic Release Inventory (TRI)29 and the Discharge Monitoring Report (DMR)33. A set of ~40 v2 models with only greenhouse gas (GHG) satellite tables were constructed using IO and environmental data for varying years (20102016), number of sectors (~400, ~70, ~15) and model formulation types (commodity-based and industry-based) to generate supply chain GHG emission factors1. v2 models represent a second generation of USEEIO models built using an improved technical infrastructure9. With the pesticide loss model input data remaining the same, but inflation in the commodity as seen in the P matrix between 2012 (USD year of v2.0) and 2013 (USD year of v1.2) created a lower denominator in v2.0, resulting in a higher pesticide-related impact intensity (since dollar output is in the denominator) for this sector. Coverage of these data used in v2.0 is equivalent to that from v1.2 as seen in Table2. While the codes and definitions of commodity categories are not changed from those provided by BEA in v2.0 (except for disaggregated sectors), original names are assigned to the commodity categories to replace the names used in the BEA IO tables. The final model is provided in the National Land Occupation Totals By Industry 2012 v1.1 dataset44. When there is additional data available for specific flows which are not adequately reflected at the 6-digit NAICS to USEEIO mapping (as per Table6), a manual distribution of that data is specified as an input to the disaggregation algorithm. The Use table rows represent the use of commodities by the industries in the IO table. All nomenclature used is defined in the Table 4. In v2.0, one of the BEA commodities is split into 7 further resolved (more specific) commodities (404+7=411). 4, 5. In v2.0, direct impacts decreased between 3050% for crops. The greatest discrepancies in land use impact intensities between the two models occur in agricultural industries, with a decrease in intensity for Cattle ranches and feedlots and an increase in intensity for Animal farms and aquaculture ponds (except cattle and poultry) and Timber and raw forest products. Many organizations quantify greenhouse emissions in their value chain. United States Environmental Protection Agency, email: IPCC Emissions Factor Database. Official websites use .gov The most common sources listed in the table are: To apply the EF Hub scope 1 and 2 factors, the organization can first define the GHG generating activity for each relevant source category, then apply the appropriate factors for stationary combustion, mobile combustion, fugitive emissions, electricity, heat, or steam. Ingwersen, W., Li, M. & Young, B. Emission factors should at a minimum include emissions from fuel combustion, and should, where possible, include cradle-to-gate emissions of the fuel (i.e., from extraction, processing, and transportation to the point of use). Monthly Energy Review - 2014. https://www.eia.gov/totalenergy/data/monthly/ (U.S. Energy Information Administration, 2016). 3. Waste commodity consumption is concentrated within a few sectors, with 55% of the commodity consumed by the top five sectors. USEEIO v2.0, or referred to solely as v2.0, is the latest edition of the US Environmentally-Extended Input-Output (USEEIO) model for assessing a full suite of potential life cycle impacts of US goods and services. Commercial buildings energy consumption survey 2012. https://www.eia.gov/consumption/commercial/ (U.S. Energy Information Administration, 2016). Service Annual Survey Historical Data (NAICS-basis): 2015. https://www.census.gov/data/tables/2015/econ/services/sas-naics.html (U.S. Census Bureau, 2016). PubMed EF Hub. https://www.bls.gov/opub/hom/ (U.S. Bureau of Labor Statistics, 2020). Young, B. et al. Developed by EPA researchers in support of the Agencys sustainable materials management program, USEEIO melds data on economic transactions between 389 industry sectors with a wealth of environmental information, including data on land, water, energy and mineral use, air pollution, nutrients, and toxics. Depending on the table resolution, these categories are further divided into one or more subcategories. This paper presents a summary of the complete v2.0 model attributes and model creation with a focus on describing methodological updates since the publication of the original USEEIO methodology. These flows must be adjusted or mapped to reflect the inclusion of the disaggregated waste sectors.
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