Abstract

Biodiversity loss has been recognized as one of the major global challenges of current and future society. Land-using processes have been found to be among the most important direct drivers for biodiversity loss. Life cycle assessment (LCA) has established itself as a standardized tool for measuring environmental impacts of products and processes. However, there is no clear consensus on the integration of land-use related impacts on biodiversity in LCA-frameworks due to a lack of methodological guidance, suitable datasets and experience in real-world applications. Closing these gaps could enable political institutions and companies to determine the effects of their products on biodiversity over the entire life cycle. In this study, a method, aiming to integrate the biodiversity impact in LCA, is successfully applied on a product with a complex supply chain. A suitable dataset of the material composition of a modern electric vehicle adapted to match the specifications of the Volkswagen ID.3 is developed. To estimate land use requirements of five important metals a GIS-based approach is elaborated. 164 mines covering an area of 4,123 km2 in eight different countries are inspected by means of satellite imagery and enhanced with data from industrial reports to build suitable datasets for the impact assessment. Based on these datasets, five unit processes are developed and applied to the VW ID.3 model. The results indicate that cobalt, lithium and copper account for the major biodiversity impact among the assessed metals. A scenario analysis reveals a biodiversity impact reduction potential of at least 23%. To the best knowledge of the authors, this study presents the first biodiversity impact assessment in the supply chain of a modern vehicle. The datasets, the application example and the workflow developed and applied in this study can serve as methodological guidance to support LCA-practitioners and researchers in the integration and application of biodiversity impacts in LCA-frameworks and LCA-studies. Thus, it supplements existing indicators in a meaningful way and makes them usable for future LCA studies.

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