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dc.contributor.authorManjong, Nelson
dc.contributor.authorUsai, Lorenzo
dc.contributor.authorBurheim, Odne Stokke
dc.contributor.authorStrømman, Anders Hammer
dc.date.accessioned2023-04-12T12:08:59Z
dc.date.available2023-04-12T12:08:59Z
dc.date.created2021-09-16T13:21:30Z
dc.date.issued2021
dc.identifier.citationBatteries. 2021, 7 (3), .en_US
dc.identifier.issn2313-0105
dc.identifier.urihttps://hdl.handle.net/11250/3062669
dc.description.abstractSustainable 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).en_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleLife cycle modelling of extraction and processing of battery minerals—a parametric approachen_US
dc.title.alternativeLife cycle modelling of extraction and processing of battery minerals—a parametric approachen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber26en_US
dc.source.volume7en_US
dc.source.journalBatteriesen_US
dc.source.issue3en_US
dc.identifier.doi10.3390/batteries7030057
dc.identifier.cristin1934928
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltextoriginal
cristin.qualitycode1


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