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Coupling LCA and GIS for biodiversity assessments of biofuel production
Jan Paul Lindner, Life Cycle Engineering Department, University of Stuttgart, Germany
David Stoms, Bren School, University of California, Santa Barbara, CA
Roland Geyer,* Bren School, University of California, Santa Barbara, CA
Frank Davis, Bren School, University of California, Santa Barbara, CA
Bastian Wittstock, Life Cycle Engineering Department, University of Stuttgart, GermanyLife cycle assessments of product systems or changes in product systems are supposed to be comprehensive, i.e. include all relevant life cycle stages and environmental concerns. There is widespread agreement that assessing impacts from land use, in particular on biodiversity, is therefore an important part of LCA. This is particularly true for agricultural product systems such as food or fuel crop production. At the same time, biodiversity is one of the least mature impact categories in LCA. In part, this is caused by the fact that the computational structure of inventory modeling and impact assessment is typically non-spatial, while biodiversity assessments require the collection and analysis of spatial data.
In order to advance theory and practice of biodiversity assessments within LCA, we developed a framework for the coupling of LCA and GIS, and applied it to the example of biofuel production in California’s San Joaquin Valley. We studied ethanol production from different fuel crops and for a range of total output levels. Soil information is combined with other data to generate spatially explicit and non-linear process inventories for all fuel crop production scenarios. The biodiversity assessments of the fuel crop production scenarios are based on spatially explicit habitat information for native terrestrial vertebrates. Different biodiversity impact indicators are calculated based on biodiversity concepts such as species richness and evenness, and habitat naturalness and rarity. All exhibit space-dependent and non-linear behavior, which shows that non-spatial, linear analysis is not suited for such biodiversity assessments. We finally used our biodiversity indicators to study the trade-offs between biodiversity and other impact categories, such as climate change. Overall, we find that combining LCA with GIS is relatively straightforward and has large potential to enhance life cycle assessments of product systems.
* corresponding author: geyer@bren.ucsb.edu