TY  - JOUR
SN  - 01973975
PB  - Elsevier Ltd
EP  - 300
AV  - none
N1  - cited By 27
TI  - A multivariable regression tool for embodied carbon footprint prediction in housing habitat
SP  - 292
Y1  - 2016///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953924456&doi=10.1016%2fj.habitatint.2015.11.005&partnerID=40&md5=905adab4205a84386d0dc0604e7dbbe7
A1  - Gardezi, S.S.S.
A1  - Shafiq, N.
A1  - Zawawi, N.A.W.A.
A1  - Khamidi, M.F.
A1  - Farhan, S.A.
JF  - Habitat International
VL  - 53
N2  - 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.
KW  - building; carbon emission; decision making; environmental modeling; housing project; life cycle analysis; multivariate analysis; prediction; regression analysis
ID  - scholars7105
ER  -