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Life-cycle energy of residential buildings in China

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  • Chang, Yuan
  • Ries, Robert J.
  • Wang, Yaowu

Abstract

In the context of rapid urbanization and new construction in rural China, residential building energy consumption has the potential to increase with the expected increase in demand. A process-based hybrid life-cycle assessment model is used to quantify the life-cycle energy use for both urban and rural residential buildings in China and determine the energy use characteristics of each life cycle phase. An input–output model for the pre-use phases is based on 2007 Chinese economic benchmark data. A process-based life-cycle assessment model for estimating the operation and demolition phases uses historical energy-intensity data. Results show that operation energy in both urban and rural residential buildings is dominant and varies from 75% to 86% of life cycle energy respectively. Gaps in living standards as well as differences in building structure and materials result in a life-cycle energy intensity of urban residential buildings that is 20% higher than that of rural residential buildings. The life-cycle energy of urban residential buildings is most sensitive to the reduction of operational energy intensity excluding heating energy which depends on both the occupants' energy-saving behavior as well as the performance of the building itself.

Suggested Citation

  • Chang, Yuan & Ries, Robert J. & Wang, Yaowu, 2013. "Life-cycle energy of residential buildings in China," Energy Policy, Elsevier, vol. 62(C), pages 656-664.
  • Handle: RePEc:eee:enepol:v:62:y:2013:i:c:p:656-664
    DOI: 10.1016/j.enpol.2013.07.053
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    References listed on IDEAS

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    Cited by:

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    13. Xu, Meijia & Chang, Yuan & Wei, Ying & Wang, Yafei & Zhang, Pengpeng & Huang, Zhiye, 2023. "Quantification and spatial pattern of embodied CO2 footprint of prefabricated buildings in urban agglomerations: A case study of Beijing–Tianjin–Hebei, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
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    15. Wang, Lan & Lee, Eric W.M. & Hussian, Syed Asad & Yuen, Anthony Chun Yin & Feng, Wei, 2021. "Quantitative impact analysis of driving factors on annual residential building energy end-use combining machine learning and stochastic methods," Applied Energy, Elsevier, vol. 299(C).
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    17. Nejat, Payam & Jomehzadeh, Fatemeh & Taheri, Mohammad Mahdi & Gohari, Mohammad & Abd. Majid, Muhd Zaimi, 2015. "A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 843-862.
    18. Chang, Yuan & Huang, Runze & Ries, Robert J. & Masanet, Eric, 2014. "Shale-to-well energy use and air pollutant emissions of shale gas production in China," Applied Energy, Elsevier, vol. 125(C), pages 147-157.
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