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

Gardezi, S. S. S., Shafiq, N., Zawawi, N. A. W. A., Khamidi, M. F. and Farhan, S. A. (2016) A multivariable regression tool for embodied carbon footprint prediction in housing habitat. Habitat International, 53 (2016). pp. 292-300. ISSN 0197-3975 doi: 10.1016/j.habitatint.2015.11.005

Abstract/Summary

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.