A multivariable regression tool for embodied carbon footprint prediction in housing habitat

Gardezi, S.S.S. and Shafiq, N. and Zawawi, N.A.W.A. and Khamidi, M.F. and Farhan, S.A. (2016) A multivariable regression tool for embodied carbon footprint prediction in housing habitat. Habitat International, 53. pp. 292-300.

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A novel embodied carbon prediction tool has been developed for conventionally constructed housing units. Single and double storey terraced, semi-detached and detached housing projects were evaluated by adoption of partial life cycle assessment (LCA) framework. The statistical technique of multivariable regression analysis was merged with LCA and building information modeling (BIM) for prediction of such environmental issue in housing sector. The assessment was limited to pre-use phase with LCA boundary of "cradle to site". The criteria and requirements for a statistically consistent and efficient prediction tool were successfully satisfied with an acceptable average prediction error of less than ±5. Based on very basic explanatory variables, the tool also helped to manage the barrier of huge data requirements for such environmental studies. The study is expected to act as a milestone and help the researchers and industry professionals for quick, effective and sustainable environmental assessment, decision making and solutions. © 2015 Elsevier Ltd.

Item Type: Article
Impact Factor: cited By 23
Uncontrolled Keywords: building; carbon emission; decision making; environmental modeling; housing project; life cycle analysis; multivariate analysis; prediction; regression analysis
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 25 Mar 2022 07:40
Last Modified: 25 Mar 2022 07:40
URI: http://scholars.utp.edu.my/id/eprint/30879

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