DEVELOPMENT OF CARBON EMISSION PREDICTION MODEL FOR HALLS OF RESIDENCE IN TERTIARY INSTITUTION IN OGUN STATE, NIGERIA

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dc.contributor.author IBITOYE, OLAYINKA SEUN
dc.date.accessioned 2022-10-26T10:14:39Z
dc.date.available 2022-10-26T10:14:39Z
dc.date.issued 2022-01
dc.identifier.uri http://196.220.128.81:8080/xmlui/handle/123456789/5374
dc.description.abstract Extensive research has been carried out on operational carbon in the building industry in Nigeria while less consideration is given to embodied carbon. This is a challenge as embodied carbon accounts for about thirty percent of a building carbon emissions, this created a gap for this study. This study identified carbon intensive element of building projects, evaluated the relationship between embodied carbon and cost of building elements and developed a carbon prediction model that could serve as a tool for estimating embodied carbon in the building industry. Relevant data were extracted from Bills of quantities and project drawings of thirty halls of residence of tertiary institution in Nigerian. The data collected were analyzed using percentage to identify the carbon intensive elements, Pearson correlation was used to rank the significance of the relationship between embodied carbon and life cycle cost. In addition, regression analysis was used to establish the predictive power of the independent variables (floor area, gross internal floor area, wall area, number of floors and average building height) on embodied carbon. The regression model was trained and cross-validated to develop the model. Finishes, frames and upper floors were identified as the carbon intensive elements of building projects. The findings suggested that there was significant relationship between embodied carbon and life cycle cost as reducing embodied carbon led to significant reduction in the cost of the projects. Floor area and gross internal wall area were found to be the significant predictors of the model. The model successfully predicted embodied carbon of building projects at the accuracy of 96.7% which was considered reasonable. Based on the findings it was recommended that there is need for early design stage carbon estimation, prioritizing carbon intensive elements, and embracing low carbon alternative materials as these will go a long way to achieving carbon emission reduction in the industry. en_US
dc.description.sponsorship FEDERAL UNIVERSITY OF TECHNOLOGY, AKURE en_US
dc.language.iso en en_US
dc.publisher FEDERAL UNIVERSITY OF TECHNOLOGY, AKURE. en_US
dc.subject DEVELOPMENT OF CARBON EMISSION PREDICTION MODEL en_US
dc.subject CARBON EMISSION PREDICTION MODEL FOR HALLS OF RESIDENCE en_US
dc.subject HALLS OF RESIDENCE IN TERTIARY INSTITUTION IN OGUN STATE, NIGERIA en_US
dc.subject CARBON EMISSION en_US
dc.title DEVELOPMENT OF CARBON EMISSION PREDICTION MODEL FOR HALLS OF RESIDENCE IN TERTIARY INSTITUTION IN OGUN STATE, NIGERIA en_US
dc.type Thesis en_US


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