LCIA Characterization Factors for Mineral and Metal Resources: A Comprehensive Methodological Review

Main Presenter:    Zeena Patel 

Co-Authors:   Rainer Souren                                               

Characterization factors (CFs) are central elements of life cycle impact assessment (LCIA), translating elementary flows into potential environmental impacts. For mineral and metal resources, CFs are formulated using a wide range of variables and assumptions, even when reported under similar impact category labels. Within the plethora of LCIA methods, it is often unclear what specific aspects of resource use each characterization factor quantifies and what method is best for a particular LCA. Existing reviews mainly compare methods or results, while the conceptual content embedded in CF equations has received limited attention.
This study applies a variable-level analysis to LCIA characterization factor formulations for mineral and metal resources. CF equations were collected from established and widely cited LCIA methodologies reported in the literature (Hauschild et al., 2018). Individual variables were identified, decomposed where composite terms were used, and harmonized at the conceptual level. A comprehensive variable map was created, mapping variables according to their functional role and the type of resource impact they represent.
The analysis shows that LCIA characterization factors for mineral and metal resources operationalize multiple, non-equivalent impacts, including physical depletion of geological stocks, future extraction or production effort, thermodynamic inefficiency, and economically mediated availability. Methods addressing similar impact categories were found to rely on fundamentally different variable structures and assumptions, with implications for result interpretation and comparability.
By making the underlying variables and calculation assumptions explicit, this study improves conceptual transparency in LCIA of mineral and metal resources and provides a basis for developing rules and decision-oriented guidelines to support the selection of resource impact models in relation to specific assessment goals and contexts.

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