Birney Catherine, Young Ben, Li Mo, Conner Melissa, Specht Jacob, Ingwersen Wesley W
U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Solutions and Emergency Response, Cincinnati, OH 45268, USA.
Eastern Research Group, Inc., Lexington, MA 02421, USA.
Appl Sci (Basel). 2022 Jun 5;12(11):1-20. doi: 10.3390/app12115742.
Quantifying industry consumption or production of resources, wastes, emissions, and losses-collectively called flows-is a complex and evolving process. The attribution of flows to industries often requires allocating multiple data sources that span spatial and temporal scopes and contain varied levels of aggregation. Once calculated, datasets can quickly become outdated with new releases of source data. The US Environmental Protection Agency (USEPA) developed the open-source Flow Sector Attribution (FLOWSA) Python package to address the challenges surrounding attributing flows to US industrial and final-use sectors. Models capture flows drawn from or released to the environment by sectors, as well as flow transfers between sectors. Data on flow use and generation by source-defined activities are imported from providers and transformed into standardized tables but are otherwise numerically unchanged in preparation for modeling. FLOWSA sector attribution models allocate primary data sources to industries using secondary data sources and file mapping activities to sectors. Users can modify methodological, spatial, and temporal parameters to explore and compare the impact of sector attribution methodological changes on model results. The standardized data outputs from these models are used as the environmental data inputs into the latest version of USEPA's US Environmentally Extended Input-Output (USEEIO) models, life cycle models of US goods and services for ~400 categories. This communication demonstrates FLOWSA's capability by describing how to build models and providing select model results for US industry use of water, land, and employment. FLOWSA is available on GitHub, and many of the data outputs are available on the USEPA's Data Commons.
量化行业对资源、废物、排放和损失（统称为流量）的消耗或生产是一个复杂且不断发展的过程。将流量归因于行业通常需要整合多个跨越时空范围且聚合程度各异的数据源。一旦计算完成，随着源数据的新发布，数据集可能很快过时。美国环境保护局（USEPA）开发了开源的流量部门归因（FLOWSA）Python包，以应对将流量归因于美国工业和最终使用部门所面临的挑战。模型捕捉各部门从环境中获取或排放到环境中的流量，以及部门之间的流量转移。源定义活动的流量使用和产生数据从提供者处导入并转换为标准化表格，但在准备建模时数值上保持不变。FLOWSA部门归因模型使用辅助数据源将主要数据源分配给各行业，并将文件映射活动分配给各部门。用户可以修改方法、空间和时间参数，以探索和比较部门归因方法变化对模型结果的影响。这些模型的标准化数据输出被用作美国环境保护局最新版美国环境扩展投入产出（USEEIO）模型的环境数据输入，该模型是约400类美国商品和服务的生命周期模型。本通讯通过描述如何构建模型并提供美国工业用水、土地和就业的选定模型结果，展示了FLOWSA的能力。FLOWSA可在GitHub上获取，许多数据输出可在美国环境保护局的数据共享平台上获取。
