News#
New publication
What can life cycle assessment modeling gain from agent-based modeling?
Ryu Koide, Gustavo Larrea-Gallegos, Jonathan Cohen, Tianran Ding, Michał Bączyk, and Kasper Lange
Members of the initiative have just published a new article in the Journal of Industrial Ecology. In this work, they revisit the integration of agent-based modeling (ABM) and life cycle assessment (LCA) from a conceptual standpoint, examining how ABM can strengthen LCA across four key dimensions — temporality, dynamicity, scale/spatiality, and causality. They position ABM as an enhancer of emerging LCA approaches (dynamic, prospective, territorial, and consequential) and argue that an agent-based LCA constitutes a paradigm shift in sustainability assessment: it enables holistic modeling of consumption-production systems, explicit representation of policy interventions beyond technological change, and decision-making under deep uncertainty — while also requiring fundamentally different data and validation strategies. The paper closes with a practical guide for researchers and practitioners designing interdisciplinary ABM–LCA studies.
New publication
Agent-based modeling and life cycle assessment: A systematic review
Paul Carrey, Pierre Jouannais, Arnaud Hélias, and Eléonore Loiseau
Paul Carrey, member of the initiative, together with colleagues from ITAP, University of Montpellier, INRAE, Institut Agro, Montpellier, France, and ELSA, Research Group for Environmental Lifecycle and Sustainability Assessment, Montpellier, France, have just published a systematic review paper in the Cleaner Environmental Systems journal. In this work, they analyze 33 studies that couple ABM and LCA, updating and extending a previous review from 2019. The paper describes each coupling step by step, with a focus on how decision models are operationalized in ABM across different economic sectors. They find that coupling strategies range from simple if-then behavioral rules with simplified impact calculations to fully integrated multi-parameter models, and that most studies assess only a limited number of impact categories — often climate change alone. Critical gaps are identified in consequential modeling, behavioral theory, and data transparency, and the paper concludes by proposing archetypes of ABM–LCA integration to guide future modelers.