Relevance of attributional and consequential life cycle assessment for society and decision support - Schaubroeck, Thomas (Frontiers in Sustainability, 2023)
Life cycle assessment (LCA) is a key tool to assess the environmental impact of product systems. Two prominent types are attributional (ALCA; assessment of the global impact share of a product life cycle) and consequential LCA (CLCA; assessment of the consequential impact of a decision). We analysed to which extent they are of relevance for society and can support decision-making based on two ideological and three pragmatic criteria. First, when it comes to realistic modelling as desired in the context of sustainable development, in theory, CLCA attempts to project these realistically, whereas ALCA falls short to a certain degree because of conceptual constraints. Concerning the second criterion of alignment with ethics, CLCA aligns completely with omnipresent consequential ethics, where an action is judged based on the consequences it causes. ALCA is only partially consequential, as it is restricted by conceptual rules relating with deontological ethics, and for example even covers the relative past of the product. Since deontological ethics, i.e. judging an action based on its alignment with rules, are in general of relevance for our modern human society, there is room for complementarity in ethical relevance between ALCA and CLCA. However, the rules of ALCA (e.g. additivity) and their relevance have not been society-wide accepted. In the context of decision-support, CLCA would evaluate the consequences of decisions and ALCA covers the approval & sharing of potential responsibility of the life cycle environmental impact of the product associated with the decision. We also point out a unique valorisation for Organisational ALCA, covering the latter for the organizations behind a product. Concerning the three practical criteria, , modelling complexity and uncertainty may often be only slightly higher for CLCA than for ALCA due to a consideration of change caused by a decision, but both ALCA and CLCA modelling may be similarly complex and uncertain as both methods cover past and/or future projections. Finally, ALCA modelling may be seen as a practical approximation of CLCA, but current CLCA models are more adequate to study consequential effects, and the further CLCA modelling and databases improve, the more this will be the case.