Advancing parametric life cycle assessment (pa-LCA): A systematic review and methodological roadmap for enhanced sustainability assessments

Abstract

Parametric Life Cycle Assessment (Pa-LCA) is a dynamic modeling and analysis approach that integrates predefined variable parameters to enable the assessment of environmental impacts. This methodology enhances the f lexibility of life cycle sustainability assessments, particularly in processes characterized by uncertainty or variability. Given this, the effective selection of parameters is required, in order to develop a meaningful Pa-LCA, which can be adapted accordingly to the objectives identified for the analysis. While Pa-LCA is widely used in the literature, there is still a need to define an assessment path for its effective application, since, unlike conventional LCA, Pa-LCA is not a standardized method. Given this, a comprehensive review of existing Pa-LCA studies has been conducted. This review focuses on how parameters are identified, selected and operationalized, how functional units are adapted to parametric contexts, and if key performance indicators (KPIs) are considered on the definition. Through this analysis, methodological gaps and inconsistencies were identified that hinder the broader adoption and effectiveness of Pa-LCA. To address these challenges, a structured methodological roadmap has been developed, aiming at guiding researchers and practitioners in the development of robust and effective Pa-LCA models. This roadmap encompasses the definition of the parametric model considered, the selection of the most influential parameters, the use of parametric data for the development of a conventional LCA, the design of sensitivity and uncertainty analyses, and the interpretation of results for decision-making. By bridging theoretical and practical implementation strategies, and by the identification of actual gaps and challenges, this guide aims to standardize Pa-LCA practices and promote its use for developing dynamic life cycle assessments. It is hoped that the outcomes of this article could contribute to advancing the methodological maturity of Pa-LCA and unlocking its potential for more adaptive and informed sustainability assessments.