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China’s energy consumption in construction and building sectors: An outlook to 2100

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  • Xu, Guangyue
  • Wang, Weimin

Abstract

As China takes great efforts to cap its total energy consumption, it is important to understand the future energy use in all sectors. This paper aims to present a long-term prediction of energy use in China’s construction and building sectors (CBS) up to the year 2100. A STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model is used to establish the relationship between six socioeconomic and technological factors and China’s CBS energy consumption. Based on the statistical data from 2000 to 2016, ridge regression is applied to derive the coefficients of the STIRPAT model to counter the impact of multicollinearity on regression results. The projections are performed for three scenarios: a benchmark scenario, an intensive scenario, and an extensive scenario. The results show that for all three scenarios, the overall trend of China’s CBS energy consumption is to continuously increase from the present, reach a peak in the range between 1155 and 1243 million tons of standard coal equivalent (Mtce) in 2050, and then decrease to 942–1116 Mtce in 2100. The above projection and the associated STIRPAT model are valuable for developing policies on construction and buildings to control the total energy use in China.

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  • Xu, Guangyue & Wang, Weimin, 2020. "China’s energy consumption in construction and building sectors: An outlook to 2100," Energy, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:energy:v:195:y:2020:i:c:s0360544220301523
    DOI: 10.1016/j.energy.2020.117045
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    as
    1. Wang, Zhaohua & Huang, Wanjing & Chen, Zhongfei, 2019. "The peak of CO2 emissions in China: A new approach using survival models," Energy Economics, Elsevier, vol. 81(C), pages 1099-1108.
    2. Yang, Yingchun & Liu, Jianghua & Lin, Yingying & Li, Qiongyuan, 2019. "The impact of urbanization on China’s residential energy consumption," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 170-182.
    3. Li, Ke & Lin, Boqiang, 2017. "An application of a double bootstrap to investigate the effects of technological progress on total-factor energy consumption performance in China," Energy, Elsevier, vol. 128(C), pages 575-585.
    4. Yu, Sha & Eom, Jiyong & Zhou, Yuyu & Evans, Meredydd & Clarke, Leon, 2014. "Scenarios of building energy demand for China with a detailed regional representation," Energy, Elsevier, vol. 67(C), pages 284-297.
    5. Li, Jun, 2008. "Towards a low-carbon future in China's building sector--A review of energy and climate models forecast," Energy Policy, Elsevier, vol. 36(5), pages 1736-1747, May.
    6. Porse, Erik & Derenski, Joshua & Gustafson, Hannah & Elizabeth, Zoe & Pincetl, Stephanie, 2016. "Structural, geographic, and social factors in urban building energy use: Analysis of aggregated account-level consumption data in a megacity," Energy Policy, Elsevier, vol. 96(C), pages 179-192.
    7. Xu, Guangyue & Schwarz, Peter & Yang, Hualiu, 2019. "Determining China's CO2 emissions peak with a dynamic nonlinear artificial neural network approach and scenario analysis," Energy Policy, Elsevier, vol. 128(C), pages 752-762.
    8. Eom, Jiyong & Clarke, Leon & Kim, Son H. & Kyle, Page & Patel, Pralit, 2012. "China's building energy demand: Long-term implications from a detailed assessment," Energy, Elsevier, vol. 46(1), pages 405-419.
    9. Tan, Xianchun & Lai, Haiping & Gu, Baihe & Zeng, Yuan & Li, Hui, 2018. "Carbon emission and abatement potential outlook in China's building sector through 2050," Energy Policy, Elsevier, vol. 118(C), pages 429-439.
    10. Yang, Tao & Pan, Yiqun & Yang, Yikun & Lin, Meishun & Qin, Bingyue & Xu, Peng & Huang, Zhizhong, 2017. "CO2 emissions in China's building sector through 2050: A scenario analysis based on a bottom-up model," Energy, Elsevier, vol. 128(C), pages 208-223.
    11. Zhou, Nan & Fridley, David & Khanna, Nina Zheng & Ke, Jing & McNeil, Michael & Levine, Mark, 2013. "China's energy and emissions outlook to 2050: Perspectives from bottom-up energy end-use model," Energy Policy, Elsevier, vol. 53(C), pages 51-62.
    12. Ahmed Gassar, Abdo Abdullah & Yun, Geun Young & Kim, Sumin, 2019. "Data-driven approach to prediction of residential energy consumption at urban scales in London," Energy, Elsevier, vol. 187(C).
    Full references (including those not matched with items on IDEAS)

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