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http://dx.doi.org/10.6106/JCEPM.2012.2.2.053

Predicting the CO2 Emission of Concrete Using Statistical Analysis  

Hong, Tae-Hoon (Department of Architectural Engineering, Yonsei University)
Ji, Chang-Yoon (Department of Architectural Engineering, Yonsei University)
Jang, Min-Ho (Department of Architectural Engineering, Yonsei University)
Park, Hyo-Seon (Department of Architectural Engineering, Yonsei University)
Publication Information
Journal of Construction Engineering and Project Management / v.2, no.2, 2012 , pp. 53-60 More about this Journal
Abstract
Accurate assessment of $CO_2$ emission from buildings requires gathering $CO_2$ emission data of various construction materials. Unfortunately, the amount of available data is limited in most countries. This study was conducted to present the $CO_2$ emission data of concrete, which is the most important construction material in Korea, by conducting a statistical analysis of the concrete mix proportion. Finally, regression models that can be used to estimate the $CO_2$ emission of concrete in all strengths were developed, and the validity of these models was evaluated using 24 and 35MPa concrete data. The validation test showed that the error ratio of the estimated value did not exceed a maximum of 5.33%. This signifies that the models can be used in acquiring the $CO_2$ emission data of concrete in all strengths. The proposed equations can be used in assessing the environmental impact of various construction structural designs by presenting the $CO_2$ emission data of all concrete types.
Keywords
Sustainable construction; $CO_2$ emission; Life cycle assessment; Statistical analysis;
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