The production vector is defined in Eq. PDF Emission Factors for Greenhouse Gas Inventories The operator is used for elementwise multiplication in contrast with no symbol between adjacent matrices or vectors which denotes a matrix multiplication. The full names of the indicators in the columns are given in Table3. 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. volume9, Articlenumber:194 (2022) Young, B. et al. Timberland estimates are based on MLUs ungrazed forest land rather than total timberland, which reduces land use attributed to forest. Pathzero US EEIO Emissions Factors 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. This then must be further transformed into commodity form before use, which is done so by multiplication with the market shares matrix, Vn, which itself is obtained from the model Make table and the model commodity output, q. The Federal LCA Commons Elementary Flow List (FEDEFL) v1.0.7 is used to represent the substance, environmental compartment or origin or release, and the unit in a common format with Federal LCA data14,15. 36. The correspondence stems from BEA-NAICS relationship table released with national input-output (IO) accounts by BEA10. The Use table rows represent the use of commodities by the industries in the IO table. US Enviro nmental Protection Agency, Office . Additionally, QCEW publishes state and county employment data used in other sector attribution models used in USEEIO v2.0. It has been subjected to the Agencys peer and administrative review and has been approved for publication as an EPA document. Using these assumptions, the waste flows between the disaggregated waste management sectors are divided by the total waste shipped between 562 sectors (as indicated in the RCRAInfo data) to obtain a percent allocation value. Report No. The R package useeior v1.0.061 was used for USEEIO v2.0 model creation. U.S. EPA Office of Research and Development (ORD) https://doi.org/10.23719/1365565 (2017). Each demand vector was derived from the BEA Detail 2012 Use table. There are five industries that produce the 562000 commodity. It is widely used by EPA program offices and other government agencies, corporations, nonprofits, nongovernmental organizations, and academia for applications such as calculating carbon footprints and environmental assessments. The result is available in the National Point Source Releases to Ground By Industry 2017 v1.1 dataset35. 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). These sections are disaggregated sequentially, and all the disaggregated components of the tables are combined at the end of the process. The Make table columns represent which commodities are produced by different industries. Handbook of methods. 11. where Pm,y for a margin type (t, w or r) is calculated in Eq. EPA 430-R-18-003 https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks-1990-2016 (U.S. Environmental Protection Agency, 2018). v1.2 was created using the 2014 BLS National Employment Matrix, while v2.0 was created with 2017 BLS QCEW. The US Economic Census (EC), published by the US Census Bureau, provides economic data for all sectors of the US economy and is used to estimate industry consumption of the disaggregated waste management commodities (i.e., Use table rows)20. If value added inputs are excluded, the biggest input is the Waste management and remediation services sector itself, representing 19% of all intermediate inputs. Secure .gov websites use HTTPS U.S. EPA Office of Research and Development (ORD) https://doi.org/10.23719/1522413 (2021). As the original flow totals in Ei are in various dollar years but the model economic components are all in a consistent 2012, to validate the model, an output adjustment is required to Bi, which is achieved through multiplication with , an output adjustment matrix, as well as transforming it to commodity form. https://www.epa.gov/ozone-layer-protection/international-actions-montreal-protocol-substances-deplete-ozone-layer (2015). 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). However, Fig. EPA/600/R-19/092 https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=347251 (U.S. Environmental Protection Agency, 2019). Sci. For waste management disaggregation, a subset of the RCRAInfo database that contains waste flows from shipping facilities to receiving/storage facilities (arranged by NAICS sector codes) was used. Social cost of household emissions: cross-country comparison - Springer The intent of this detailed analysis is to provide information and recommendations on available opportunities to work with County vendors to improve environmental performance and advance the health and wellbeing of the residents of Alameda County and beyond., US Department of Energy Prioritization of sectors in the US economy by greatest opportunities for environmental improvements through the use of the Sustainable Materials Management Prioritization Tools will be a primary use of v2.0. Total flows or impacts associated with a given amount of final demand are calculated using two perspectives that produce the same overall flow or impact totals but associate the totals with different sectors. 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 Fig. The national release estimates for pesticides were not updated in v2.0, where data on application for these chemicals to vegetables was from 2010. In general, the final demand in the BEA Use table can be grouped into the following categories: yg=federal, state and local government consumption. Researchers at the National Renewable Energy Laboratory (NREL), with support of theDepartment of Energys Bioenergy Technology Office (BETO), are using USEEIO as a key resource for the development of their Bio-Economy Input-Output Model. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. 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. 18. 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. 35, is a vector of the column sums of the given H (see Eqs. In v2.0, these data sources are used to allocate MLU land use categories to relevant sectors. Some changes in HCAN and NCAN result from the inclusion of characterization factors from TRACI 2.1 for metals, which were not included for v1.2. Provided by the Springer Nature SharedIt content-sharing initiative, The International Journal of Life Cycle Assessment (2023), Scientific Data (Sci Data) 2014 generator-based characterization of commercial sector disposal and diversion in california. 3, B is in flow x commodity form after transforming BI into this form with the market shares matrix transformation. The original relation between the environmental data in the form of national totals by industry, E, and the model economic data uses the model industry output, as described in Eq. These novel elements as well as model fundamentals are described in this paper. Environ. Notable in the BEA data is that imports in ym are represented with negative values. The first complete and peer-reviewed USEEIO model, v1.0, was released in early 2017 and described in Yang et al.2 and related datasets3,4. 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). The water methodology in the Water Use Satellite table compiled for v1.1 tracked water returns, allowing for the calculation of water consumption by industry. & Birney, C. useeior. The production vector adds to the consumption vector the net trade balance as well as inventory/stock changes. 4, EI is a emission x industry matrix of national totals of each flow by industry sector in year y, and xz,y is a vector of gross output by industry in year z, given in year y dollars. Fresh vegetables, melons, and potatoes climbed from 10th to 6th position. Emission Factor Database European Environment Agency 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. In Eq. Emissions factors The emissions factors can be collected from: - Emissions sourced direct from suppliers based on the specific goods and services used. v2 models represent a second generation of USEEIO models built using an improved technical infrastructure9. ERR-288 https://www.ers.usda.gov/publications/pub-details/?pubid=101624 (U.S. Department of Agriculture, 2021). Model coefficient matrices can be converted to reflect different currency years. 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. For the disaggregated waste management sectors, this represents the materials and services that these industries consume in the process of collecting, managing, and remediating wastes. A .gov website belongs to an official government organization in the United States. BLM/OC/ST-13/002+1165 https://www.blm.gov/sites/blm.gov/files/pls2012-web.pdf (U.S. Bureau of Land Management, 2013). Data are assigned to sectors based on facility-reported NAICS. These include all the types of resource use and environmental releases/losses from v1.15 plus the three additional waste generation datasets created for v1.27,8. 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. 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 v2.0, one of the BEA commodities is split into 7 further resolved (more specific) commodities (404+7=411). Water withdrawal by industry was allocated to NAICS using BLS QCEW employment data. The Make table is normalized by the commodity output vector, q to create what is also known as the market shares matrix. Complete Hr and Hf matrices with results for all indicators and by sector are available online73. Report No. Meyer, D. E., Li, M. & Ingwersen, W. W. Analyzing economy-scale solid waste generation using the United States environmentally-extended input-output model. Although QCEW employment data is one of the main sources in the creation of the National Employment Matrix, the National Employment Matrix also incorporates data from the Occupational Employment Statistics program (OES), the Current Employment Statistics program (CES), and the Current Population Survey (CPS)60. For v2.0, value added direct and indirect impact coefficients from N are ~1 for all sectors. Once all the requirements are installed, the generation of v2.0 takes place in a single buildModel function to load the various data components and build the model. Amazon used USEEIO as a source for life cycle CO2e factors in their corporate carbon footprint calculation for estimating part of their carbon footprint related to purchased goods and services and their facilities. Changes in GHG intensity were less than 0.5kg CO2e/$ for >95% of sectors. This excel file includes 10 sheets with a set of carbon emission factors for electricity and electricity/heat generation. The final demand vectors represent purchases of goods and services by final consumers, including by households, investors and governments. Agricultural chemical use survey. Where a 5-digit NAICS contains only a single 6-digit child NAICS (e.g., 56291), flows are automatically assigned to that sector. Cite this article. U.S. Environmental Protection Agency. Changes in selection of data sources and methodologies for compiling these into a standard format are described below. 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. The first ranking uses Hr calculated where y is the US production vector, yp (see Eq. A .gov website belongs to an official government organization in the United States. 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.
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