Automated Embodied Carbon Quantification for a Typical Building Using BIM and Ontology

Xingbo Gong, Yuqing Xu, Xingyu Tao, Helen H. L. Kwok and Jack C. P. Cheng ()
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Xingbo Gong: The Hong Kong University of Science and Technology
Yuqing Xu: The Hong Kong University of Science and Technology
Xingyu Tao: The Hong Kong University of Science and Technology
Helen H. L. Kwok: The Hong Kong University of Science and Technology
Jack C. P. Cheng: The Hong Kong University of Science and Technology

Chapter Chapter 136 in Proceedings of the 28th International Symposium on Advancement of Construction Management and Real Estate, 2024, pp 1963-1973 from Springer

Abstract: Abstract The construction industry is commonly recognized as one of the most significant contributors to global carbon emissions. Apart from carbon emissions from energy consumption during the building operation stage, embodied carbon, including construction materials and construction activities in the building construction stage, becomes more and more important for life cycle carbon reduction in the construction industry. However, the process of embodied carbon quantification is tedious and error-prone due to the difficulty of collecting massive carbon data. Although Building Information Modelling (BIM) has been applied in this field to extract material information for carbon quantification, the existing studies are still limited in building the semantic domain information related to embodied carbon. Therefore, ontology tools are used and integrated with BIM in this study to create a comprehensive approach in the field of embodied carbon. An ontology-based data model is proposed first to identify information requirements for embodied carbon quantification. After that, this study developed a BIM-based tool to (1) enrich BIM information, (2) map data attributes in the ontology data model to BIM models, and (3) automatically calculate embodied carbon results. A typical building from a construction project is used to validate the proposed approach, which illustrates both feasibility and calculation performance.

Keywords: Embodied carbon; Building information model; Ontology; Automated quantification (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-1949-5_137

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