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FLOWSA: Environmental data preparation for life cycle assessment modeling and beyond
Citation:
Birney, C., B. Young, M. Li, M. Conner, J. Specht, AND W. Ingwersen. FLOWSA: Environmental data preparation for life cycle assessment modeling and beyond. International Symposium on Sustainable Systems and Technology (ISSST), Pittsburgh, PA, June 21 - 23, 2022.
Impact/Purpose:
To present an overview of integrating FLOWSA with useeior to generate USEEIO models.
Description:
Presenting on integrating FLOWSA into useeior to generate USEEIO models at the ISSST 2022 Conference. FLOWSA is an open-source Python package developed to attribute physical transfers of resources (environmental, monetary, and human), emissions, wastes, and losses, collectively called flows, to US industrial and final use sectors. Models capture flows drawn from or released to the environment by sectors and flow transfers between sectors. FLOWSA first imports and formats publicly-available data into standardized tables without modifying names, amounts, or units in the original data. FLOWSA sector attribution models then allocate primary data sources to industries using secondary data sources and files that map activities to sectors. Users can modify methodological, geographical, and temporal parameters within sector attribution models to explore and compare methodological changes on model results. The most up-to-date code and data are available via a GitHub repository, enabling transparent and reproducible model results. FLOWSA sector attribution model results are used as model inputs to the US Environmentally-Extended Input-Output (USEEIO) open-source R package, useeior. The useeior models calculate the life cycle environmental and economic impacts of producing or consuming goods and services in the US. The use of FLOWSA allows for timely USEEIO model updates when new environmental data are released. This presentation will demonstrate FLOWSA's utility and flexibility for environmental data preparation by highlighting the environmental data preparation in FLOWSA and showing how FLOWSA datasets can be integrated in useeior to produce USEEIO model results for water and greenhouse gas emissions.