The integration of Life Cycle Assessment (LCA) into Building Information Modeling (BIM) processes is becoming increasingly important for enhancing the environmental performance of construction projects. This scoping review examines how LCA methods and environmental data are currently integrated into BIM workflows, focusing on automation, data standardization, and visualization strategies. We selected 43 peer-reviewed studies (January 2010–May 2025) via structured searches in five major academic databases. The review identifies five main types of BIM–LCA integration workflows; the most common approach involves exporting quantity data from BIM models to external LCA tools. More recent studies explore the use of artificial intelligence for improving automation and accuracy in data mapping between BIM objects and LCA databases. Key challenges include inconsistent levels of data granularity, a lack of harmonized EPD formats, and limited interoperability between BIM and LCA software environments. Visualization methods such as color-coded 3D models are used to support early-stage decision-making, although uncertainty representation remains limited. To address these issues, future research should focus on standardizing EPD data structures, enriching BIM objects with validated environmental information, and developing explainable AI solutions for automated classification and matching. These advancements would improve the reliability and usability of LCA in BIM-based design, contributing to more informed decisions in sustainable construction.
An Overview on LCA Integration in BIM: Tools, Applications, and Future Trends
C. Bolognesi;D. Bassorizzi;S. Balin;V. Manfredi
2025-01-01
Abstract
The integration of Life Cycle Assessment (LCA) into Building Information Modeling (BIM) processes is becoming increasingly important for enhancing the environmental performance of construction projects. This scoping review examines how LCA methods and environmental data are currently integrated into BIM workflows, focusing on automation, data standardization, and visualization strategies. We selected 43 peer-reviewed studies (January 2010–May 2025) via structured searches in five major academic databases. The review identifies five main types of BIM–LCA integration workflows; the most common approach involves exporting quantity data from BIM models to external LCA tools. More recent studies explore the use of artificial intelligence for improving automation and accuracy in data mapping between BIM objects and LCA databases. Key challenges include inconsistent levels of data granularity, a lack of harmonized EPD formats, and limited interoperability between BIM and LCA software environments. Visualization methods such as color-coded 3D models are used to support early-stage decision-making, although uncertainty representation remains limited. To address these issues, future research should focus on standardizing EPD data structures, enriching BIM objects with validated environmental information, and developing explainable AI solutions for automated classification and matching. These advancements would improve the reliability and usability of LCA in BIM-based design, contributing to more informed decisions in sustainable construction.| File | Dimensione | Formato | |
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MDPI.pdf
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