BIM-based life cycle assessment: A systematic review on automation and decision-making during design

Abstract

Life Cycle Assessment (LCA) is essential to achieve a Net-Zero Carbon Built Environment and inform effective mitigation strategies for environmental impacts throughout a building's life cycle. However, collecting Life Cycle Inventory (LCI) data and the Life Cycle Impact Assessment (LCIA) processes are complex and time-consuming. BIM-LCA integration enables automated quantity-take-off, supporting faster evaluation of different design options and decision-making. Consequently, research on BIM-LCA has grown significantly since 2013. However, previous literature reviews on BIM-LCA do not cover developments from the past three years, nor do they assess how BIM-LCA supports decision-making or how decision-making methods can enhance its adoption and use, particularly among non-LCA experts. A systematic literature review was conducted following the PRISMA protocol to address this gap. A total of 115 research articles (2019–2024) were analysed according to design phases, BIM object LOD, LCA application, data exchange and extraction methods, automation degree, and decision-making features, covering Multi-Criteria Decision Analysis, Multi-Objective Optimisation, and Sensitivity/Uncertainty analyses. The findings highlight advancements in LCI automation. However, several challenges remain, including manual BIM-LCA data mapping during LCIA and limited research on: BIM-LCA for renovation projects, dynamic data exchange for OpenBIM, standardised LOD for different LCA applications, and local databases for budget-based targets. Furthermore, few studies integrate LCA with economic and social indicators, and decision-making methods are mainly absent from BIM-LCA tools. This study outlines research directions to address these limitations and improve BIM-LCA automation and decision-making. Future efforts will focus on gathering insights from industry stakeholders to establish priorities for user-centred BIM-LCA development.