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)
  • Received : 2012.03.13
  • Accepted : 2012.05.10
  • Published : 2012.06.01


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.


Supported by : National Research Foundation of Korea (NRF)


  1. R. Crawford, "Life Cycle Assessment in the Built Environment", Taylor & Francis, New York, 2011.
  2. R. Horne, K. Verghese, T. Grant, "Life Cycle Assessment : Principles, Practice and Prospects", CSIRO Publishing, 2009.
  3. H. Yan, Q. Shen, L. C. H. Fan, Y. Wang, L. Zhang, "Greenhouse gas emissions in building construction: A case study of One Peking in Hong Kong", Building and Environment, vol. 45, no. 4, pp. 949-955, 2010.
  4. X. Li, Y. Zhu, Z. Zhang, "An LCA-based environmental impact assessment model for construction processes", Building and Environment, vol. 45, no. 3, pp. 766-775, 2010.
  5. R. J. Cole, "Energy and greenhouse gas emissions associated with the construction of alternative structural systems", Building and Environment, vol. 34, no. 3, pp. 335-348, 1999.
  6. W. Kloepffer, "Life cycle Sustainability assessment of products", International Journal of Life Cycle Assessment, vol. 13, no.2, pp. 89-94, Mar 2008.
  7. D. J. Lowe, M. W. Emsley, A. Harding, "Predicting construction cost using multiple regression techniques", Journal of Construction Engineering and Management, vol. 132, no. 7, pp. 750-758, 2006.
  8. T. Hegazy, A. Ayed, "Neural network model for parametric cost estimation of highway projects", Journal of Construction Engineering and Management, vol. 124, no. 3, pp. 210-218, 1998.
  9. G.-H. Kim, K.-I. Kang, "A Study on Predicting Cost Estimation of Apartment Building Using Neural Network's Architecture Optimized by Genetic Algorithms", JOURNAL OF THE ARCHITECTURAL INSTITUTE OF KOREA Structure & Construction, vol. 20, no. 2, pp. 81-88, 2004.
  10. A. A. Abu Hammad, S. M. A. Ali, G. J. Sweis, R. J. Sweis, "Statistical analysis on the cost and duration of public building projects", Journal of Management in Engineering, vol. 26, no. 2, pp. 105-112, 2010.
  11. C. Koo, T. Hong, C. Hyun, "The development of a construction cost prediction model with improved prediction capacity using the advanced CBR approach", Expert Systems with Applications, vol. 38, no. 7, pp. 8597-8606, 2011.
  12. C. Ji, T. Hong, C. Hyun, "CBR revision model for improving cost prediction accuracy in multifamily housing projects", Journal of Management in Engineering, vol. 26, no. 4, pp. 229-236, 2010.
  13. C. Koo, T. Hong, C. Hyun, K. Koo, "A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects", Canadian Journal of Civil Engineering, vol. 37, no. 5, pp. 739-752, 2010.
  14. T. Hong, C. Hyun, H. Moon, "CBR-based cost prediction model-II of the design phase for multi-family housing projects", Expert Systems with Applications, vol. 38, no. 3, pp. 2797-2808, 2011.
  15. R. Freund, "Regression analysis: statistical modeling of a response variable", Elsevier Academic Press, Burlington, MA, 2006.
  16. S. Mindess, J. F. Young, D. Darwin, "Concrete", 2nd ed., Upper Saddle River, NJ: Prentice Hall, 2003.
  17. S. Tae, C. Baek, S. Shin, "Life cycle $CO_2$ evaluation on reinforced concrete structures with high-strength concrete", Environmental Impact Assessment Review, vol. 31, no. 3, pp. 253-260, 2011.
  18. D. J. M. Flower, J. G. Sanjayan, "Greenhouse gas emissions due to concrete manufacture", International Journal of Life Cycle Assessment, vol. 12, no. 5, pp. 282-288, 2007.
  19. Ministry of Environment. Korea LCI Database Information Network,, Accessed 15 April 2011
  20. IPCC, "2006 IPCC Guidelines for National Greenhouse Gas Inventories: In Energy, vol. 2." IPCC,, Accessed 6 April 2011
  21. W. J. Conover, "Practical nonparametric statistics", John Wiley & Sons, Inc., New York, 1999.
  22. Walpole, "Probability & statistics for engineers & scientists", Thomson Brooks/Cole, Belmont, California, 2007.
  23. Dmitrienko, "Pharmaceutical Statistics Using SAS", SAS Institute, Cary, NC, 2007.
  24. G. J. Treloar, "Extracting embodied energy paths from input-output tables: towards an input-output-based hybrid energy analysis method", Economic Systems Research, vol. 9, no. 4, pp. 375-391, 1997.
  25. Seber, "Linear regression analysis", Wiley, New York, 2003.

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