Dissipation-based life cycle impact assessment of mineral resource use—a review, case study, and implications for the product environmental footprint

Abstract

Abstract Purpose Impacts of mineral resource use on the availability of resources can be assessed using a broad range of methods. Until recently, life cycle inventory (LCI) and life cycle impact assessment (LCIA) models have been based on resource extraction. As extracted resources are not necessarily “lost” for future use, recent methodological developments have shifted the focus from resource extraction to resource dissipation. This paper aims at reviewing dissipation-based LCIA methods, testing them in a case study, analyzing potential implications for the product environmental footprint (PEF), and providing recommendations for future method development. Method Five recently developed LCIA methods have been reviewed and compared based on 22 criteria, such as the forms and time horizons of dissipation considered, scientific publication, and number of characterization factors (CFs). Additionally, the abiotic depletion potential (ADP) method has been included to serve as a non-dissipation-based reference. All methods are tested in a case study on a theoretical product, designed solely for demonstration purposes, and consisting of 1 kg of the metals aluminum, cobalt, copper, molybdenum, nickel, and zinc. In addition to the absolute LCIA results, the contributions of metal production stages and individual resource extractions/emissions have been investigated. Finally, normalization and weighting have been carried out to analyze consequences of replacing ADP with the new dissipation-based methods in the context of PEF. Results and discussion Most recently developed LCIA methods take a long-term perspective, cover emissions of resources to the environment (and partly technosphere), and vary in the number of CFs and resources covered. The case study results obtained by ADP are dominated by the molybdenum dataset; the results of the dissipation-based LCIA methods are strongly influenced by the cobalt dataset. All results are strongly sensitive to the LCI database used (ecoinvent or GaBi). Normalization and weighting revealed that the mineral resource use impact result dominates the aggregated PEF score (57%), when using the currently recommended ADP model. Shifting from the resource extraction-based ADP to dissipation-based models can reduce the contribution to 23% or < 1% depending on the method. Conclusion The development of methods addressing mineral resource use in LCIA has shifted from resource extraction to dissipation. The analyzed methods are applicable and lead to different findings than the extraction-based ADP. Using the newly developed methods in the context of PEF would significantly change the relevance of the mineral resource use impact category in comparison to other environmental impacts.