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Research on Database Construction and Calculation of Building Carbon Emissions Based on BIM General Data Framework

Author

Listed:
  • Ruizhe Zhang

    (Institute of Building Technology and Sciences, School of Architecture, Southeast University, Nanjing 211189, China)

  • Hong Zhang

    (Institute of Building Technology and Sciences, School of Architecture, Southeast University, Nanjing 211189, China)

  • Shangang Hei

    (Institute of Building Technology and Sciences, School of Architecture, Southeast University, Nanjing 211189, China)

  • Hongyu Ye

    (Institute of Building Technology and Sciences, School of Architecture, Southeast University, Nanjing 211189, China)

Abstract

China is entering a new era characterized by carbon peaking and carbon neutrality, and the construction industry, which accounts for a high proportion of social carbon emissions, urgently needs a method to calculate and predict building carbon emissions in advance. This study proposes a method for calculating the life cycle carbon emissions (LCCEs) of buildings based on building information modeling (BIM) technology. The method uses a BIM universal data framework to establish a building carbon emission calculation model and a building carbon emission factor database instance. Taking prefabricated construction projects as an example, it is compared with the traditional calculation method. The results show that the method can more accurately predict building carbon emissions and provide methods and a basis for the construction industry to control carbon emissions in advance.

Suggested Citation

  • Ruizhe Zhang & Hong Zhang & Shangang Hei & Hongyu Ye, 2023. "Research on Database Construction and Calculation of Building Carbon Emissions Based on BIM General Data Framework," Sustainability, MDPI, vol. 15(13), pages 1-27, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10256-:d:1181795
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    References listed on IDEAS

    as
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    2. Acquaye, Adolf & Duffy, Aidan & Basu, Biswajit, 2011. "Embodied emissions abatement--A policy assessment using stochastic analysis," Energy Policy, Elsevier, vol. 39(1), pages 429-441, January.
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