CAREER: Geospatial life cycle climate change impacts of solar and ocean renewable energy systems

Life cycle assessment (LCA) practices are used to determine the climate change impacts of energy systems. However, these assessments often miss key geographically specific factors, such as direct land use change (DLUC) impacts, albedo change as a non-greenhouse gas climate forcer, and geospatial data relevant to potential electricity generation. The overarching goal of this project is to systematically integrate these geospatial components in LCA of conventional and renewable energy systems to improve the accuracy of their “carbon footprints” at higher spatial resolutions, and to disseminate this methodology and its results to inform sustainable location-specific design, siting, and implementation decisions for the energy transition. The research objectives are to: (1) first update the baseline comparison to fossil fuels by including DLUC and albedo change impacts of their expansion in the US; (2) develop geospatial LCA models for selected solar and ocean renewable energy technologies and determine their life cycle climate change impacts on potentially available land and water in the US; and (3) adapt the geospatial LCA models to future conditions under climate change. Parametric LCA models of these energy system scenarios will be developed in open-source Python code, informed by publicly available GIS datasets, the physics of these technologies, and algorithms developed for flexibility to variable environmental conditions. In order for the methodology to be disseminated and used by energy stakeholders and future LCA practitioners, the education objectives are to: (1) design and share a course in geospatial LCA modeling; (2) develop and promote a workshop and website on these methods and their results for industry and policy stakeholders; and (3) provide a research group structure designed to recruit, train, and retain students in sustainability engineering fields. This project will develop methodology for determining life cycle climate change impacts of energy technologies that is more precise than previously used methods in LCA. The results will be statistically compared against non-geographically-specific LCA results of the same modeled technologies and against the impacts of fossil fuels to determine the significance of incorporating geospatial components in energy system LCAs. The developed geospatial LCA methods can also be utilized in LCA of other systems beyond energy technologies, such as mining, and can be used for energy system planning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.