Low-Carbon Construction Strategies through BIM-LCA Integration: A Multi-Case Evaluation across Building Types

The construction industry accounts for approximately 31% of global carbon emissions, underscoring the need for integrated digital strategies to reduce environmental impacts. This study investigates the potential of Building Information Modeling (BIM) and Life Cycle Assessment (LCA) integration across three distinct building types—commercial offices, residential high-rises, and industrial warehouses—spanning diverse climatic contexts. By embedding real-time environmental feedback into early design processes, the BIM-LCA framework achieved embodied carbon reductions of up to 30% and operational carbon savings of up to 36%, outperforming conventional project workflows. The study highlights the scalability of this method while identifying critical adoption barriers, including software interoperability and the lack of region-specific LCA datasets, particularly for small and medium-sized enterprises (SMEs). Importantly, it introduces artificial intelligence (AI) and machine learning as key enablers for automating material selection and optimizing energy performance, offering a pathway toward adaptive, low-carbon design automation. Policy recommendations include the development of localized LCA databases and financial incentives for BIM-LCA adoption. The findings contribute to advancing net-zero targets and align with the Paris Agreement and SDG 13. Future research should focus on AI-integrated BIM-LCA platforms to enhance predictive modeling and real-time decision-making across the building lifecycle.