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USEEIO: a New and Transparent United States Environmentally-Extended Input-Output Model

机译:USEEIO:一种新的透明的美国环境扩展投入产出模型

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摘要

National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO is assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO files are publicly available bringing a new level of transparency for environmentally-extended input-output models.
机译:国家范围的商品和服务的环境生命周期模型可以用于许多目的,不仅限于量化国家生产和消费的影响,评估整个组织的影响,确定购买热点,分析政策对环境的影响以及简化生活周期评估。 USEEIO是美国针对环境和其他可持续材料管理应用的一种新的,环境扩展的投入产出模型。 USEEIO将389个行业部门之间的经济交易数据与这些行业的环境数据(包括土地,水,能源和矿产的使用以及温室气体的排放,标准的空气污染物,营养物质和有毒物质)进行融合,以建立385种美国商品和服务。与现有的美国模型相比,USEEIO具有更多最新数据,其中包括2013年的大多数数据,其资源和排放量的涵盖范围更广,其数据源的解释和组合更加审慎和详细,并且包括正式的数据质量评估和描述。 USEEIO与称为IO模型构建器的新Python模块组装在一起,该模块能够组装和计算用户定义的输入输出模型的结果,并将模型导出到LCA软件中。通过对美国一家普通医院的环境绩效进行分析,证明了该模型和数据质量评估功能。所有USEEIO文件都是公开可用的,为环境扩展的输入输出模型带来了更高的透明度。

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