Sustainable battery production with low environmental footprints requires a systematic assessment of the entire value chain, from raw material extraction and processing to battery production and recycling. In order to explore and understand the variations observed in the reported footprints of raw battery materials, it is vital to re-assess the footprints of these material value chains. Identifying the causes of these variations by combining engineering and environmental system analysis expands our knowledge of the footprints of these battery materials. This article disaggregates the value chains of six raw battery materials (aluminum, copper, graphite, lithium carbonate, manganese, and nickel) and identifies the sources of variabilities (levers) for each process along each value chain. We developed a parametric attributional process-based life cycle model to explore the effect of these levers on the greenhouse gas (GHG) emissions of the value chains, expressed in kg of CO2e. The parametric life cycle inventory model is used to conduct distinct life cycle assessments (LCA) for each material value chain by varying the identified levers within defined engineering ranges. 570 distinct LCAs are conducted for the aluminum value chain, 450 for copper, 170 for graphite, 39 for lithium carbonate via spodumene, 20 for lithium carbonate via brine, 260 for manganese, and 440 for nickel. Three-dimensional representations of these results for each value chain in kg of CO2e are presented as contour plots with gradient lines illustrating the intensity of lever combinations on the GHG emissions. The results of this study convey multidimensional insights into how changes in the lever settings of value chains yield variations in the overall GHG emissions of the raw materials. Parameterization of these value chains forms a flexible and high-resolution backbone, leading towards a more reliable life cycle assessment of lithium-ion batteries (LIB).
CITATION STYLE
Manjong, N. B., Usai, L., Burheim, O. S., & Strømman, A. H. (2021). Life cycle modelling of extraction and processing of battery minerals—a parametric approach. Batteries, 7(3). https://doi.org/10.3390/batteries7030057
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