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Public participation in energy saving retrofitting of residential buildings in China

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  • Liu, Wenling
  • Zhang, Jinyun
  • Bluemling, Bettina
  • Mol, Arthur P.J.
  • Wang, Can

Abstract

Retrofitting existing residential buildings has been claimed as one crucial way to reduce energy consumption and greenhouse gas emissions within the Chinese residential sector. In China’s government-dominated retrofitting projects, the participation of residents is often neglected. The objective of this paper is to assess the influence level of public participation (before, during and after retrofit) on energy saving by comparing three Beijing neighborhoods with different retrofitting models: a central government-led model, a local government-led model, and an old neighborhood retrofit model. In the three cases data were collected through interviews with neighborhood workers and residents. The results show that residents’ involvement in pre-retrofit activities, in technology selection and in the use of technology differs greatly among the three cases. This study concludes that in order to improve the effectiveness of energy saving interventions, the motives, intentions and living habits of residents need to be given more consideration when designing and implementing retrofitting. By highlighting the importance of public participation this paper contributes to energy saving policy development in China.

Suggested Citation

  • Liu, Wenling & Zhang, Jinyun & Bluemling, Bettina & Mol, Arthur P.J. & Wang, Can, 2015. "Public participation in energy saving retrofitting of residential buildings in China," Applied Energy, Elsevier, vol. 147(C), pages 287-296.
    • Handle: RePEc:eee:appene:v:147:y:2015:i:c:p:287-296
    DOI: 10.1016/j.apenergy.2015.02.090
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    References listed on IDEAS

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    Cited by:

    1. Ce Huang & Jiefang Ma & Kun Song, 2021. "Homeowners’ Willingness to Make Investment in Energy Efficiency Retrofit of Residential Buildings in China and Its Influencing Factors," Energies, MDPI, vol. 14(5), pages 1-17, February.
    2. Ling Jia & Queena K. Qian & Frits Meijer & Henk Visscher, 2020. "Stakeholders’ Risk Perception: A Perspective for Proactive Risk Management in Residential Building Energy Retrofits in China," Sustainability, MDPI, vol. 12(7), pages 1-25, April.
    3. Jiefang Ma & Queena Kun Qian & Henk Visscher & Kun Song, 2021. "Homeowners’ Participation in Energy Efficient Renovation Projects in China’s Northern Heating Region," Sustainability, MDPI, vol. 13(16), pages 1-37, August.
    4. Jia, Ling & Qian, Queena K. & Meijer, Frits & Visscher, Henk, 2021. "How information stimulates homeowners’ cooperation in residential building energy retrofits in China," Energy Policy, Elsevier, vol. 157(C).
    5. Jia, Jun-Jun & Xu, Jin-Hua & Fan, Ying & Ji, Qiang, 2018. "Willingness to accept energy-saving measures and adoption barriers in the residential sector: An empirical analysis in Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 56-73.
    6. Handing Guo & Wanzhen Qiao & Jiren Liu, 2019. "Dynamic Feedback Analysis of Influencing Factors of Existing Building Energy-Saving Renovation Market Based on System Dynamics in China," Sustainability, MDPI, vol. 11(1), pages 1-16, January.
    7. Yang, Tianren & Zhang, Xiaoling, 2016. "Benchmarking the building energy consumption and solar energy trade-offs of residential neighborhoods on Chongming Eco-Island, China," Applied Energy, Elsevier, vol. 180(C), pages 792-799.
    8. Alexander Adeyemi Fakere & Clement Oluwole Folorunso & Olatunde Arayela & Felix Kayode Omole, 2020. "Strategic framework for resident’s participation in housing provision in Akure, Southwest Nigeria," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 6(2), pages 137-160, October.
    9. Baldwin, Andrew N. & Loveday, Dennis L. & Li, Baizhan & Murray, Michael & Yu, Wei, 2018. "A research agenda for the retrofitting of residential buildings in China – A case study," Energy Policy, Elsevier, vol. 113(C), pages 41-51.
    10. Beccali, Marco & Ciulla, Giuseppina & Lo Brano, Valerio & Galatioto, Alessandra & Bonomolo, Marina, 2017. "Artificial neural network decision support tool for assessment of the energy performance and the refurbishment actions for the non-residential building stock in Southern Italy," Energy, Elsevier, vol. 137(C), pages 1201-1218.
    11. Craig, Christopher A., 2016. "Energy consumption, energy efficiency, and consumer perceptions: A case study for the Southeast United States," Applied Energy, Elsevier, vol. 165(C), pages 660-669.
    12. Corsini, Filippo & Certomà, Chiara & Dyer, Mark & Frey, Marco, 2019. "Participatory energy: Research, imaginaries and practices on people' contribute to energy systems in the smart city," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 322-332.
    13. Wilson, C. & Pettifor, H. & Chryssochoidis, G., 2018. "Quantitative modelling of why and how homeowners decide to renovate energy efficiently," Applied Energy, Elsevier, vol. 212(C), pages 1333-1344.
    14. Yupei Lai & Yutong Li & Xinyi Feng & Tao Ma, 2022. "Green retrofit of existing residential buildings in China: An investigation on residents’ perceptions," Energy & Environment, , vol. 33(2), pages 332-353, March.
    15. Wenqing Zhang & Biao Luo, 2023. "Predicting consumer intention toward eco-friendly smart home services: extending the theory of planned behavior," Economic Change and Restructuring, Springer, vol. 56(5), pages 3335-3352, October.
    16. Yinan Li & Neng Zhu & Beibei Qin, 2019. "Target Setting Outlook for New Residential Building Energy Efficiency Promotion in China: A Frontline Perspective Using Delphi," Energies, MDPI, vol. 12(9), pages 1-29, April.
    17. Jia, Jun-Jun & Xu, Jin-Hua & Fan, Ying, 2018. "Public acceptance of household energy-saving measures in Beijing: Heterogeneous preferences and policy implications," Energy Policy, Elsevier, vol. 113(C), pages 487-499.
    18. Yang, Tao & Pan, Yiqun & Mao, Jiachen & Wang, Yonglong & Huang, Zhizhong, 2016. "An automated optimization method for calibrating building energy simulation models with measured data: Orientation and a case study," Applied Energy, Elsevier, vol. 179(C), pages 1220-1231.
    19. Ki Uhn Ahn & Han Sol Shin & Cheol Soo Park, 2019. "Energy Analysis of 4625 Office Buildings in South Korea," Energies, MDPI, vol. 12(6), pages 1-16, March.
    20. Xin Liang & Geoffrey Qiping Shen & Li Guo, 2019. "Optimizing Incentive Policy of Energy-Efficiency Retrofit in Public Buildings: A Principal-Agent Model," Sustainability, MDPI, vol. 11(12), pages 1-19, June.

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