v2.0 builds on the flow sector attribution modeling approach taken to construct national commercial waste totals8, by estimating totals by industries defined by NAICS codes. Community Sustainability and Prosperity in Georgiaand Beyond 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. The largest visible change in GHG intensity was seen in the electricity sector, with a nearly 2kg CO2e/$ decrease. The direct perspective calculation associates the totals with the sectors that produce the given flows (e.g. USEEIO v2.0, The US Environmentally-Extended Input-Output Model v2.0, $$A=U{\widehat{x}}^{-1}V{\widehat{q}}^{-1}$$, $${B}_{I,y}={E}_{I,z}{\widehat{x}}_{z,y}^{-1}$$, $${x}_{i,y}={x}_{i,a}\ast {\rho }_{i,z- > y}$$, $${\rho }_{i,z- > y}=\frac{p{i}_{i,y}}{p{i}_{i,z}}$$, $${\varPhi }_{c},y=\frac{{q}_{PRO,c,y}}{{q}_{PUR,c,y}}$$, $${q}_{PUR,c,y}={q}_{c}{P}_{c,y}+{t}_{c,y}{P}_{t,y}+{w}_{c,y}{P}_{w,y}+{r}_{c,y}{P}_{r,y}$$, $${P}_{m,y}=\frac{{\sum }_{c\in m}{q}_{c,y}{P}_{c,y}}{{\sum }_{c\in m}{q}_{c,y}}$$, $${y}_{p}={y}_{c}+{y}_{e}+{y}_{m}+{y}_{\delta }$$, $$r{c}_{f},n=\frac{{m}_{f}\circ {c}_{n}^{{\prime} }}{\sum \left({m}_{f}\circ {c}_{n}^{{\prime} }\right)}$$, $$r{c}_{c},n=\frac{{l}_{c}\circ {d}_{n}^{{\prime} }}{\sum ({l}_{c}\circ {d}_{n}^{{\prime} })}$$, $${A}_{d}={U}_{d}{\widehat{x}}^{-1}\ast V{\widehat{q}}^{-1}$$, $${E}_{c}={({C}_{m}{E}_{i}^{{\prime} })}^{{\prime} }$$, $${C}_{m}={V}^{{\prime} }{\widehat{x}}^{-1}$$, $${B}_{\chi ,c}={B}_{i}\,\circ \,\chi V{\widehat{q}}^{-1}$$, $$i=w{\widehat{x}}^{-1}V{\widehat{q}}^{-1}L$$, $${H}_{i,c}={{\rm{\$}}}_{c}{N}_{i,c}{P}_{c,y}{\varPhi }_{c,y}$$, https://doi.org/10.1038/s41597-022-01293-7. https://www.usgs.gov/mission-areas/water-resources/science/water-use-terminology?qt-science_center_objects=0#qt-science_center_objects (2019). Reviewed and released models are listed on the model technical content webpage . Form EIA-923 detailed data. Water_national_2015_m1 was created primarily using water withdrawal data accessed from the USGS National Water Information System Web Interface45. EPA Report: Supply Chain Greenhouse Gas Emission Factors for U.S. Industries and Commodities Emissions are assigned to industries based on the NAICS reported by each facility. Young, B., Li, M. & Ingwersen, W. Direct impact coefficients (D matrix) of USEEIOv1.2 and v2.0.1-411. Primary data must often be collected directly from suppliers through a questionnaire or similar format. Syst. For v2.0, value added direct and indirect impact coefficients from N are ~1 for all sectors. 31. is composed of xs:x output ratios and identical in its indices (rows and column identifiers) to B. Nonpoint criteria and toxic air emissions are sourced from the 2017 Nonpoint, Nonroad, and Onroad NEI datasets28. Where a 5-digit NAICS contains only a single 6-digit child NAICS (e.g., 56291), flows are automatically assigned to that sector. Matrix algebra is used to represent the steps of creating the USEEIO model, using conventions for variable names commonly used in a mix of standard references for IO analysis16 and LCA17, and the existing USEEIO model documentation. Timberland estimates are based on MLUs ungrazed forest land rather than total timberland, which reduces land use attributed to forest. The accuracy of the impact proportion depending on the validity of the assumption that domestic impact intensities are equivalent to foreign impact intensities, which is not likely valid in all cases. More information about this update is provided in the Procedure for Model Building section. The final factors are available in the Supply Chain Emission Factors for US Industries and Commodities dataset. 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. Where particular elementary flows are reported in each dataset, flows are maintained from the DMR when a facility reports to both. 3, B is in flow x commodity form after transforming BI into this form with the market shares matrix transformation. The economic data base year for v2.0 is 2012, corresponding to the latest detailed IO tables10. The waste sector disaggregation procedure required the definition of an additional set of configuration files that provide instructions for this disaggregation procedure. Industry underlying estimates. Recycl. sectors in an EEIO model) that drive a particular indicator value is a conventional analytical practice in life cycle assessment18. Themodified methodology results in significant sector disparities within agriculture, construction, retailing, finance, and household sectors. For v2.0, national totals by sector are modeled by NAICS 6-digit codes. We define production as final use, either within the US or abroad, of all goods and services that are produced in the US. In the original analysis, industrial water was allocated to NAICS 3133 using 3-digit NAICS Canadian Industrial Water Use statistics, scaled to US production by US GDP. Chemical releases to air are sourced from 2017 reported emissions data from the National Emissions Inventory (NEI)28 and Toxic Release Inventory (TRI)29. The GHG Protocol defines 15 categories of scope 3 emissions, though not every category will be relevant to all organizations (see Figure 1). Domestic food supply chains freshwater use over time. Water data for the nation 2015. https://waterdata.usgs.gov/nwis (U.S. Geological Survey, 2018). For MRNL, the only notable changes in the use intensity are the decrease in Dimensional stone and increase in Sand, gravel, clay This can be explained by an error in allocation of the Sand/gravel flows to Dimensional stone rather than to Sand, gravel, clayin v1.2 and prior versions. 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. 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 columns can later be modified with assumptions for individual commodity expenditures by the disaggregated waste management sectors as additional data is found. Article These tables are typically released 5 or more years after the Census is performed. 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. A .gov website belongs to an official government organization in the United States. U.S. Geological Survey. These factors were prepared using USEEIO models, which are a life cycle models of goods and services in the US economy. 2012 NAICS to 2007 NAICS Concordance. The R package useeior v1.0.061 was used for USEEIO v2.0 model creation. USEEIO. The Economic Census data provides monetary receipt values by detailed NAICS codes and customer class. To obtain an allocation percentage for the industries that consume Waste management and remediation services commodity (i.e. The USGS publishes state-level water withdrawal estimates for nine broad categories: Aquaculture, Domestic, Industrial, Irrigation Crop, Irrigation Golf Courses, Livestock, Mining, Public Supply, and Thermoelectric Power. Increase in nonpoint emissions for manufacturing sectors. A series of coefficient matrices are provided that are products of combining more than one of the economic, physical flow, and indicator components. Revised methods for particulate matter estimates in the NEI were implemented since 2011, the data year used in v1.1, that better account for emissions of dust from livestock31. Environmentally extended input-output (EEIO) models have been developed to evaluate the linkages between economic activities and environmental impacts as well as the embodied emissions in goods and . The sets of commodities in the top 20 from v2.0 and v1.2 in the production and consumption-based rankings are nearly identical, with some notable substitutions and some exchanging of places. In the case of the new waste commodity and industry totals, they summed to within 1% of the Waste and Remediation commodity and industry totals in the 2012 BEA Detail Make and Use tables. Sustainable Materials Management Prioritization Tools zenodo https://doi.org/10.5281/zenodo.5557895 (2021). B.Y. Using BLS QCEW for the employment model allows for a consistent data source for all employment data used throughout model construction. Resour. State level USDA CoA data are used to calculate fractions of land use by animal type, which are multiplied by state level MLU pasture and grazed land. The decline in impact intensity for Tobacco, cotton, sugarcane, peanuts, sugar beets, herbs and spices and other crops is attributed to correcting an error in the v1.2 calculation. & Balassiano, K. EPA Data Commons v0.1. U.S. Census Bureau https://www.census.gov/naics/2012NAICS/2-digit_2012_Codes.xls (2019). http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/ (2016). This suggests that trade flows between the disaggregated sectors is an important component of the aggregate sectors input, and its disaggregation was previously discussed. 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). 20. where mf is the column representing the flow of interest from the M matrix, and cn is the transposed row representing the indicator of interest from the C matrix. 25. Other agricultural commodities show the inverse change in v2.0, where the agricultural output in v2.0 is higher and thus the pesticide release and related impact intensities are lower. If fuel activity data are available, the fuel-based method should be used, so the factors presented in Tables 2 and 3 would be applicable. The industries in the E columns match the industries in x. The data is built upon the US EPA's National Greenhouse Gas Industry Attribution Model. Following transformation of all satellite tables, environmental flows are compared across satellite tables to check for potential duplication. the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in For Electricity, for example, SO2 and NOX contribute to 57% and 39% of impact, respectively. Ingwersen, W. et al. EXIOBASE European Environment Agency U.S. EPA Office of Research and Development (ORD) https://doi.org/10.23719/1522414 (2021). In the v2.0, methyl bromide/emission/air/troposphere/rural/ground-level/kg has one of the highest CFC-11 equivalents (0.51, sheet C, cell BMV20 of)71 of all flows, and Fresh vegetables, melons, and potatoes shows the highest at 2.4E-5 kg/$. 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.) Many environmental and employment data sources are available to characterize US industries at the needed level of detail for more recent years. For the disaggregated waste management sectors, the Make table intersection represents the amount of the Waste management and remediation services commodities (rows) produced by each of the waste management industries (columns). U.S. EPA Office of Research and Development (ORD) https://doi.org/10.23719/1522413 (2021). Red text indicates an update from the 2018 version of this document. Agency researchers are using USEEIO as the foundation for the development of a suite of Sustainable Materials Management Prioritization Tools. Flow loss may result from invalid NAICS codes. Electricity and Drinking Water) or construction activities (e.g., Highways, Streets and Bridges, and Utilities Buildings and Infrastructure), which are sectors dominated by domestic activities. Some scope 3 categories may be relevant, but initially lack readily available data to use in estimating emissions. PubMedGoogle Scholar. Point source releases to air reflect facility reported releases in these datasets and include both criteria and toxic air pollutants. Zhuang, X. The result is available in the National Criteria and Hazardous Air Pollutant Totals By Industry 2017 v1.1 dataset32. Bigelow, D. & Borchers, A. National emissions inventory 2017. https://www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei (U.S. Environmental Protection Agency, 2019). The relationship table presents a hierarchy of the BEA codes at three levels of detail: sector (21 sector groups), summary (71 sector groups), and detail (405 sector groups), as well as how each level relates to the NAICS code structure. 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). The matrix M is a flow x sector matrix and contains in each row i the direct plus indirect flows per 1 USD output of the sector in column j. Capital letters indicate matrices and lower case letters indicate vectors. Heijungs, R. & Suh, S. The Computational Structure of Life Cycle Assessment. Improvements in modeling national totals of industry and environmental flows are described. These tables are also known as the benchmark tables because they are based on the US Economic Census which is conducted every five years and the tables correspond to the Census year11. Three standard national level demand vectors were created for use with the model to calculate potential impacts of US consumption, production and consumption from households. For national USEEIO models, results calculated with these variables represent US region results. The USEEIO dataset that comes with Net Zero Cloud is from an analysis performed in the year 2012. Fedelemflowlist v1.0.8. https://www.epa.gov/sites/production/files/2016-11/documents/2014_smmfactsheet_508.pdf (U.S. Environmental Protection Agency, 2016). With the direct impacts D and the total requirements L, the matrix N which contains the direct plus indirect impact coefficients can be calculated via Eq. The footprint of US consumption or production, measured in GHGs, water, or any of the 20+indicators present in Table3 can be calculated using the model. 35, is a vector of the column sums of the given H (see Eqs. Mineral commodity summary 2014. https://s3-us-west-2.amazonaws.com/prd-wret/assets/palladium/production/mineral-pubs/mcs/mcs2014.pdf (U.S. Geological Survey, 2014). However when this demand vector is applied to the model, output of these commodities is positive due to industry consumption, reflecting the commodity output totals. The general equation for emissions estimation is: E = A x EF x (1-ER/100) where: E = emissions; A = activity rate; Manfred Lenzen, Arne Geschke, Heinz Schandl, Helmut Haberl, Dominik Wiedenhofer, Marina Fischer-Kowalski, Arnulf Grubler, Charlie Wilson, Hugo Valin, Richard Wood, Daniel D. Moran, Konstantin Stadler, Scientific Data Coverage of these data used in v2.0 is equivalent to that from v1.2 as seen in Table2. Public Land Statistics 2007. These values are included in the WasteDisaggregation_Make sheet in the primary data record, in the Industry disaggregation rows. Tobacco, cotton, sugarcane, peanuts, sugar beets, herbs and spices, and other crops fell 14 places, apparently to decreased water consumption. https://www.agcensus.usda.gov/ (U.S. Department of Agriculture, 2009). For v2.0, the Sector Crosswalk is built based on 2012 BEA and NAICS codes and includes 2007 NAICS codes according to the 2012 NAICS to 2007 NAICS concordance by Census Bureau23. The values in v2.0 resulting from Eq. This class in turn spent a total of almost $48 billion in services from the Waste management and remediation services sector. Sci. For these datasets, the national totals by sector were extracted directly from the published datasets5,7. While not part of the interindustry transactions, these sectors are somewhat analogous to commodities, and are represented as rows for each industry in the Use table. is a commodity x year price type adjustment matrix prepared using Eq. 1b, rankings reveal some minor shifting of positions. 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. In order to split impacts between US and Rest of World (RoW), the requirements from production need to be split between domestic inputs and foreign inputs. Real time updates can be found in the useeior software repository. Understanding the consumption-based accounting (CBA), production-based accounting (PBA), and emissions embodied in trade is an important prerequisite for designing climate mitigation policies. However, the BEA table is insufficient in two aspects: Most BEA codes have explicit correspondence with NAICS codes, but BEA codes in several sector groups, including construction (23), government (G), and final demand (F), are not aligned with specific NAICS industries. and JavaScript. The relative contribution, rc of a commodity, c, to an impact intensity coefficient from N for a given indicator, n, can be calculated using Eq. Report No. Read more about NETL's work here. EPA Report: Supply Chain Greenhouse Gas Emission Factors for U.S. Industries and Commodities Many organizations quantify greenhouse emissions in their value chain. To assist in quantifying these emissions, EPA has developed a comprehensive set of supply chain emission factors covering all categories of goods and services in the US economy. In addition, because scope 3 sources may represent most of an organizations GHG emissions, they often offer emissions reduction opportunities. in order to minimize inter-plant variability. U.S. Energy Information Administration. Many organizations will improve the accuracy of scope 3 emissions over time and expand to include more categories as adequate data become available. Inventory of u.s. Greenhouse gas emissions and sinks: 19902016. The BEA Use table reports the data for final US demand by these consumers, grouping them at varying levels of resolution depending on the level of resolution of the Use table (i.e., sector, summary or detail). The modeling steps were written in Python and consolidated into a software package called flowsa. 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. Briefly stated, monetary input-output (IO) tables give insight into the value of economic transactions between different sectors in an economy, including output for exports, capital formation and final government and private consumption. 54, 30913102, https://doi.org/10.1021/acs.est.9b06024 (2020). Monthly Energy Review - 2018. https://www.eia.gov/totalenergy/data/monthly/ (U.S. Energy Information Administration, 2020). US Enviro nmental Protection Agency, Office . To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The first step is a relevance assessment to determine which of the 15 categories are relevant to the reporting organization. EEIO can be a powerful tool for analysing the relation between economic and environmental flows. 13). Name of source. The production vector adds to the consumption vector the net trade balance as well as inventory/stock changes. This disproportionate share of the original value of the waste remediation industry, combined with the industry allocations already used for the Use table columns, can result in an imbalance in the allocation totals for the disaggregated waste industries in the Use and Make tables. ADS Quarterly census of employment and wages 2015. https://www.bls.gov/cew/downloadable-data-files.htm (U.S. Bureau of Labor Statistics, 2020). These values are included in the WasteDisaggregation_Make sheet of the primary data record, in the Make table intersection rows. The B or D matrices may be used for similar purposes but only include the direct impact or flow per USD. 5, where xi,z is the year industry output for industry i in the currency year, z, corresponding to the year of the national flow totals. Correspondence to 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. Table 6.1 of the Scope 3 Standard provides criteria to identify relevant scope 3 activities: To determine relevance, the organization can review the Scope 3 Standards description of each scope 3 category and consult appropriate contacts across the organization. There are two exceptions to these allocation values in the Make table row disaggregation. Five categories are reported in year one and 12 in year five. Yang, Y., Berrill, P., Miller, R., Ingwersen, W. & Li, M. National GHG Industry Attribution Model. Scope 3 emissions include all sources not within an organizations scope 1 and 2 boundary. PubMed Crop water use is calculated by multiplying irrigated harvested cropland acreage and water application rates for different crops48,49. Household consumption accounts for the largest share of the global anthropogenic greenhouse gases (GHG) emissions. The 5-digit NAICS in the RCRAInfo codes do not count flows present in the 6-digit codes. This can be represented using Eq. CalRecycle - Californias Department of Resources Recycling and Recovery, CBECS - Commercial Building Energy Consumption Survey, CCDD Commercial Construction & Demolition Debris, CRHW - Commercial Resources Conservation and Recovery Act-Defined Hazardous Waste, EEIO - Environmentally-Extended Input-Output, HRSP - Human Health - Respiratory Effects, IWMS - Irrigation and Water Management Survey, MECS - Manufacturing Energy Consumption Survey, NAICS - North American Industry Classification System, RCRA Resource Conservation and Recovery Act, RCRAInfo - Resource Conservation and Recovery Act Information system, USEEIO United States Environmentally-Extended Input-Output Model, USEPA United States Environmental Protection Agency. EPA Center for Corporate Climate Leadership, Corporate Value Chain (Scope 3) Accounting and Reporting Standard, The Global GHG Accounting and Reporting Standard for the Financial Industry, Partnership for Carbon Accounting Financials, Conversion factors 2022: full set (for advanced users), Greenhouse Gas Inventory Guidance: Indirect Emissions from Events and Conferences, ENERGY STAR Scope 3 Use of Sold Products Analysis Tool V1.2, Renewable Electricity Procurement on Behalf of Others: A Corporate Reporting Guide, Center for Corporate Climate Leadership Home, GHG Inventory Development Process & Guidance, Corporate GHG Inventorying and Target Setting Self-Assessment, Reporting Corporate Climate Risks and Opportunities, 4 (upstream transportation and distribution), 9 (downstream transportation and distribution), 12 (end-of-life treatment of sold products), The UK Department for Environment Food & Rural Affairs provides well-to-tank (i.e., upstream) emission factors for fuel in the ". EPA/600/R-20/001). If value added inputs are excluded, the biggest input is the Waste management and remediation services sector itself, representing 19% of all intermediate inputs. 23 is used for y. The attribution methodology for the remaining water categories follows Rehkamp et al.s sector attribution approach46. QCEW was chosen for the sector attribution model, as QCEW data is one of the primary data sources for the National Employment Matrix and as the National Employment Matrix database primary purpose is for national-level employment predictions60. As described in the Splitting Impacts section, in v2.0, impacts can be split between those originating in the US vs. the rest of the world. Lovelace, J. K. Method for estimating water withdrawals for livestock in the united states, 2005. EPA's GHG Emission Factors Hub provides factors for most scope 3 categories. )2, therefore all environmental data was adjusted to be in 2013 US Dollars (USD). In v2.0, Scrap is left in the model to simplify the accounting procedures, but we do not recommend use of multipliers generated from Scrap because of the lack of a clear material or functional characterization of this commodity. U.S. EPA, 2020. The consumption vector is defined in Eq. The 2016 values are applied across all years and will be updated in more recent years as new data sets are . A main assumption in the disaggregation of waste management sectors is that the receivers of waste flows are being paid for waste treatment. (Springer Science & Business Media, 2002). The state data are summed to calculate national land use by animal type for pasture and grazed land. Notable in the BEA data is that imports in ym are represented with negative values. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. These footprints can be calculated by performing a model calculation as in Eqs. v2.0 is a single region model with the 50 states of the United States modeled as a single region. Environmentally-extended input-output (EEIO) analysis provides a simple and robust method for evaluating the linkages between economic consumption activities and . This research was funded by the USEPAs Sustainable and Healthy Communities Research Program. The data includes fresh and saline water withdrawn from surface and ground sources and evaporative water loss to the atmosphere. This decrease is likely a result of fuel source changes in the electricity production over this period69. The USEEIO Modeling Framework for USEEIO v2.09 provides an overview of the source code along with links to useeior and supporting software packages. In some . The reader should refer to Table3 for the source of the impact method characterization factors used to construct the N and D matrices. You are using a browser version with limited support for CSS. BLM/OC/ST-13/002+1165 https://www.blm.gov/sites/blm.gov/files/pls2012-web.pdf (U.S. Bureau of Land Management, 2013). Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. USEEIO models are under continuous revision with intermittent releases. The change in crop categorization coupled with differences in survey responses resulted in changes in industry impact intensity. The literature assessing the environmental impacts of household consumption is mostly focused on developed economies, thus, leaving a critical gap when it comes to assessing the impacts of household consumption and of related environmental policies in developing countries . 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. Complete Hr and Hf matrices with results for all indicators and by sector are available online73. The three zeroes at the end of the BEA code for Waste management and remediation services indicate that it is at the 3-digit NAICS level. This model was based on the 2007 input-output data with 385 commodities and mixed-year environmental data with the latest representing 2013. v1.1 added additional satellite tables and made methodological updates to some existing tables5,6. Li, M. & Ingwersen, W. H_r and H_f matrices of USEEIOv1.2 and v2.0.1-411. This ensures that, for example, pesticide releases to air are not duplicated in both the Criteria and Hazardous air pollutant satellite table and the pesticide satellite table. EEIO analysis can be used to produce policy relevant data. The composite score for the rankings are calculated as a sum of fractions of sector impact relative to total impact across all sectors by each selected indicator, and then this fraction for a sector was summed across all indicators.
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