Life-cycle implications and supply chain logistics of electric vehicle battery recycling in California

Abstract

Plug-in electric vehicle (PEV) use in the United States (US) has doubled in recent years and is projected to continue increasing rapidly. This is especially true in California, which makes up nearly one-third of the current US PEV market. Planning and constructing the necessary infrastructure to support this projected increase requires insight into the optimal strategies for PEV battery recycling. Utilizing life-cycle perspectives in evaluating these supply chain networks is essential in fully understanding the environmental consequences of this infrastructure expansion. This study combined life-cycle assessment and geographic information systems (GIS) to analyze the energy, greenhouse gas (GHG), water use, and criteria air pollutant implications of end-of-life infrastructure networks for lithium-ion batteries (LIBs) in California. Multiple end-of-life scenarios were assessed, including hydrometallurgical and pyrometallurgical recycling processes. Using economic and environmental criteria, GIS modeling revealed optimal locations for battery dismantling and recycling facilities for in-state and out-of-state recycling scenarios. Results show that economic return on investment is likely to diminish if more than two in-state dismantling facilities are constructed. Using rail as well as truck transportation can substantially reduce transportation-related GHG emissions (23–45%) for both in-state and out-of-state recycling scenarios. The results revealed that material recovery from pyrometallurgy can offset environmental burdens associated with LIB production, namely a 6–56% reduction in primary energy demand and 23% reduction in GHG emissions, when compared to virgin production. Incorporating human health damages from air emissions into the model indicated that Los Angeles and Kern Counties are most at risk in the infrastructure scale-up for in-state recycling due to their population density and proximity to the optimal location.