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dc.contributorDepartment of Building Environment and Energy Engineering-
dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorLin, MQ-
dc.creatorChau, CK-
dc.creatorXu, MY-
dc.creatorJi, C-
dc.creatorFeng, XH-
dc.publisherEDP Sciencesen_US
dc.rights© The Authors, published by EDP Sciences, 2021en_US
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rightsThe following publication Lin, M. Q., Chau, C. K., Xu, M. Y., Cheng, J., & Feng, X. H. (2021). Assessment of the impacts of building materials on the reduction of CO 2 emissions from high-rise commercial buildings in Hong Kong. In E3S Web of Conferences (Vol. 261). EDP Sciences is available at
dc.titleAssessment of the impacts of building materials on the reduction of CO₂ emissions from high-rise commercial buildings in Hong Kongen_US
dc.typeJournal/Magazine Articleen_US
dcterms.abstractBased on data collected in 20 A-level high-rise commercial concrete buildings in Hong Kong, the research successfully established a probability density function model, which is used to describe the carbon emissions profile of a commercial building. Results indicate that the superstructure of a commercial building, on average, had a footprint of 226.65 kg CO2/m and 10.6 kg CO2/m separately in the material use stage and transportation stages. It also evaluates the carbon emissions of various building elements and divides them into three levels according to the magnitude of their contribution. The results show that upper floor construction and external wall in Tier 1 contribute nearly 80% of emissions and should be of great concern. In addition to the probability density function model, a regression model was also successfully established in the study to predict carbon emissions. Research has shown that building layers and gross floor area can predict carbon emissions per unit area, and there is a positive relationship between the independent variable and the dependent variable. The regression model can help building designers determine design options to reduce carbon emissions in the early stages of design.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationE3S Web of conferences, 2021, v. 261, 4026-
dcterms.isPartOfE3S Web of conferences-
dc.description.validate202110 bcvc-
dc.description.oaVersion of Recorden_US
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