Assessing robustness of consequential LCA: Insights from a multiregional economic model tailored to the cement industrial symbiosis

Abstract

One of the key challenges in conducting consequential life cycle assessment (LCA) is to identify and quantify what is likely to be affected by changes in market behavior—so‐called marginal effects. Although the critical importance of uncertainty and sensitivity assessments in attributional LCA is recognized, they are rarely conducted in consequential studies. Thus, this paper aims to address two objectives: first, to examine the uncertainty and robustness of marginal effects in consequential LCA and second, to identify the most influential group of inputs contributing to the overall variance in climate change impact scores. To accomplish this, the study employs an enhanced consequential LCA framework that integrates a multiregional economic optimization model with consequential LCA tools. The framework is applied to assess the climate implications of a 6% increase in clinker substitution within average Eastern North American cement production by 2030, relative to 2020 levels. Through this framework, a Monte Carlo simulation is conducted to evaluate the dispersion of the results. Subsequently, a variance‐based one‐at‐a‐time sensitivity analysis is performed to rank the most influential groups of inputs affecting the robustness of result across macroeconomic, material flow, economic, transport, and consequential life cycle inventory databases. Afterward, a conceptual framework is proposed to guide practitioners in prioritizing areas for testing consequential LCA results based on region‐specific information. This work aims to contribute to decision‐makers' access to more reliable information to support the development of effective environmental regulatory measures.