Developing land use inventories for life cycle assessment of electricity generation

Main Presenter:    Sarah Jordaan 


Life cycle inventories of the direct land area required by energy technologies have been limited to date. Research efforts have emphasized the development of impact assessment methods for land use in life cycle assessment, opening the need for systems-wide land use inventories to leverage such methods. This project focused on developing inventories for energy technologies in the U.S. portion of the Western Interconnection, including the fuel supply where applicable. The presentation will describe a series of collaborations published and under review from this initiative. The analyses involved deep learning models that quantified direct land use by solar PV, wind power, as well as coal- and gas-fired electricity by processing more than 500,000 images with a resolution of 1024 by 1024 for of ~800 solar farms, ~350 wind power projects, and > 100,000 natural gas production wells. A workflow was developed that combines deep learning, energy data, and geospatial analysis to
quantify land transformation and power density. Coal-fired power and concentrating solar power were manually completed due to the smaller number of infrastructure elements and facilities (less than 50 for each unit process for both energy types). Progress to date will be discussed, noting future research efforts. The aim is to contribute large-scale inventories to support the advancement of land use-related impact categories in life cycle assessment.

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