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Fang, Yuan; Lu, Xiaoqing; Li, Hongyang
Journal of cleaner production, 12/2021, Letnik: 328Journal Article
Carbon dioxide (CO2) emissions is a major greenhouse gas that causes global warming. Many researchers in the fields of architecture, engineering, and construction try to measured CO2 emissions during a building's lifecycle. However, research on the CO2 emissions during construction stage are less studied than those during other stages because they are considered to be lower than the emissions from the building's materials' production or operational stage. In addition, research has been hindered by a complicated calculation process and a lack of data, and thus few methods are available for forecasting construction-stage carbon emissions, especially at the early design stage. In order to estimate the environmental effects of the emissions from the vast number of construction activities, this study applies a random forest (RF) based predictive method to predict construction-stage carbon emissions. The RF-based model uses data from 38 buildings in the Pearl River Delta region of China for the initial training set to find the relation between construction-stage carbon emissions and design parameters. Compared with the multilinear regression method, the RF-based model has a higher coefficient of determination and lower mean square error. The model developed in this study facilitates the prediction of construction-stage carbon emissions at the early design stage of a building. This opens up novel opportunities to reduce carbon emissions from buildings, which had previously been possible only at the latter stages of a building's life cycle. It will also help policymakers account for the probable distribution and amount of CO2 emissions in a city when multiple construction projects are proceeding simultaneously, so that measures can be implemented to avoid excessive emissions. •A random forest-based model is developed for the prediction of construction-stage carbon emissions at the early design stage.•The relationships between design parameters and predicted construction-stage carbon emissions are quantitatively determined.•The building's foundation area, underground area, and height are found to have the greatest effect on its construction-stage carbon emissions.•The random forest-based model facilitates the prediction of construction-stage carbon emissions at the early design stage of a building project.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Vir: Osebne bibliografije
in: SICRIS
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