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New methodology for regionalized life cycle assessments

A team from ETH Zurich (Switzerland) report on their new methodology for performing regionalized life cycle assessment (LCA) and systematically choosing the spatial scale of regionalized impact assessment methods in a paper published in the ACS journal Environmental Science & Technology.

Regional patterns of impact for the US electricity grid mix for five impact assessment categories. Power plant circles are logarithmically scaled by annual generation. Colored boxes show each grid cell’s contribution to the total regionalized LCA score of the USA grid mix. Credit: ACS, Mutel et al. Click to enlarge.

Life cycle assessments (LCA) calculate the environmental burdens of goods and services—for example, the well-to-wheels emissions for different fuels. In the life cycle inventory stage, environmental flows (resource consumptions and emissions) are quantified for the supply chain, manufacture, and eventual disposal of a product or service; in the impact assessment stage, the damage caused by the environmental flows is calculated. Regionalization, in the context of LCA, the authors note, is the recognition that industrial production characteristics and the environmental impact of environmental flows can vary with location.

In this paper, we review some key geographic concepts needed to work with regionalized data. We propose a new technique to systematically determine an appropriate spatial support for regionalized impact assessment methods. We then describe a methodology to couple regionalized impact assess- ment methods with regionalized inventories and use a new version of the open source Brightway software that directly includes GIS capabilities in the LCA calculation. Finally, we examine a case study of electricity production in the United States.

—Mutel et al.

To handle spatial uncertainty in regionalized inventory, they use the given locations as the basis for a spatial uncertainty distribution. To handle regionalized impact assessments, they minimize spatial autocorrelation—i.e., how well the values in neighboring spatial units can predict the value of the original unit. Each inventory spatial unit then needs to be mapped onto the impact assessment spatial support.

We have developed and implemented regionalized life cycle assessment, including methods to address uncertainty in inventory spatial data and systematically choosing the most appropriate spatial scale of impact assessment. There are promising areas for future research, such as the inclusion of rasterized data in life cycle inventories and application of the proposed methods to other regionalized inventories and impact assessment methods. Despite the increased complexity of regionalized LCA, the benefits of reduced impact assessment uncertainty, better supply chain modeling, and geographic interpretation of results are widely recognized. With the methodology proposed here and the development of regionalized inventories and impact assessment methods, regionalized LCA can transition from a research topic to routine practice.

—Mutel et al.


  • Christopher L. Mutel, Stephan Pfister, and Stefanie Hellweg (2011) GIS-Based Regionalized Life Cycle Assessment: How Big Is Small Enough? Methodology and Case Study of Electricity Generation. Environmental Science & Technology doi: 10.1021/es203117z


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