Abstract

Abstract Purpose The ISO 14044 standard for life cycle assessment (LCA) provides the reference decision hierarchy for dealing with multi-functional processes. We observe that, in practice, the consistent implementation of this hierarchy by LCA practitioners and LCA guidance document developers may be limited. In an attempt to explain this observation, and to offer suggestions as to how consistency in LCA practice might be improved, we identify and compare the rationales for (and limitations of) different common approaches to solving multi-functionality problems in LCA. Methods The different prevalent understandings of specific approaches for dealing with multi-functional processes were identified, and their respective rationales were analyzed. This takes into account identifying the implicit underlying assumptions regarding the nature and purpose of LCA that support each approach. Results and discussion We identified what we believe to be three internally consistent but mutually exclusive schools of thought amongst LCA practitioners, which differ in subtle but important ways in terms of their understanding of the nature and purpose of LCA, and the multi-functionality solutions necessary to support them. These three divisions follow two demarcations. The first is between consequential and attributional data modeling approaches. The second is between adherence to a natural science-based approach (privileging physical allocation solutions) and a socioeconomic approach (favoring economic allocation solutions) in attributional data modeling. Conclusions We conclude that the ISO 14044 multi-functionality hierarchy should explicitly differentiate between attributional and consequential data modeling applications. We question the feasibility and practical utility of system expansion (currently privileged in the ISO hierarchy) in attributional data modeling applications. We suggest that ISO 14044 should also make explicit its rationale for privileging natural science-based approaches to solving multi-functionality problems and to more clearly differentiate between natural science and social science-based approaches. We also call for the formulation of additional guidance for solving multi-functionality problems, in particular for justifying the use of lower-tier solutions from the ISO hierarchy when these are applied in LCA studies. We suggest that this additional guidance and clarity in ISO 14044 will contribute to increased consistency in LCA practice and also increase the potential for users of information from LCA studies to make informed decisions as to their relevance within the context of specific intended applications.

Highlights

  • Multi-functionality problems are commonly encountered in life cycle assessment (LCA) studies

  • We conclude that the ISO 14044 multifunctionality hierarchy should explicitly differentiate between attributional and consequential data modeling applications

  • We suggest that ISO 14044 should make explicit its rationale for privileging natural science-based approaches to solving multifunctionality problems and to more clearly differentiate between natural science and social science-based approaches

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Summary

Introduction

Multi-functionality problems are commonly encountered in LCA studies. How such problems are resolved is a critical determinant of LCA study results. Multi-functionality problems may be solved in a variety of ways, depending on the goal and scope of a study and the specifics of a particular problem (Reap et al 2008). Allocation is one common strategy for solving multi-functionality problems. Int J Life Cycle Assess (2015) 20:74–86. ISO 14044 standard for life cycle assessment (LCA) (ISO 2006a), allocation refers to “partitioning the input or output flows of a process or a product system between the product system under study and one or more other product systems.”. Other approaches attempt to avoid the need to allocate via process subdivision or by changing the system boundary of the study ISO 14044 standard for life cycle assessment (LCA) (ISO 2006a), allocation refers to “partitioning the input or output flows of a process or a product system between the product system under study and one or more other product systems.” Other approaches attempt to avoid the need to allocate via process subdivision or by changing the system boundary of the study

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