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Impact Assessment of Abiotic Resources in LCA: Quantitative Comparison of Selected Characterization Models

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Abstract

Resources have received significant attention in recent years resulting in development of a wide range of resource depletion indicators within life cycle assessment (LCA). Understanding the differences in assessment principles used to derive these indicators and the effects on the impact assessment results is critical for indicator selection and interpretation of the results. Eleven resource depletion methods were evaluated quantitatively with respect to resource coverage, characterization factors (CF), impact contributions from individual resources, and total impact scores. We included 2247 individual market inventory data sets covering a wide range of societal activities (ecoinvent database v3.0). Log–linear regression analysis was carried out for all pairwise combinations of the 11 methods for identification of correlations in CFs (resources) and total impacts (inventory data sets) between methods. Significant differences in resource coverage were observed (9–73 resources) revealing a trade-off between resource coverage and model complexity. High correlation in CFs between methods did not necessarily manifest in high correlation in total impacts. This indicates that also resource coverage may be critical for impact assessment results. Although no consistent correlations between methods applying similar assessment models could be observed, all methods showed relatively high correlation regarding the assessment of energy resources. Finally, we classify the existing methods into three groups, according to method focus and modeling approach, to aid method selection within LCA.