IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v87y2017i3d10.1007_s11069-017-2847-x.html
   My bibliography  Save this article

A STIRPAT model-based methodology for calculating energy savings in China’s existing civil buildings from 2001 to 2015

Author

Listed:
  • Minda Ma

    (Chongqing University)

  • Ran Yan

    (Chongqing University)

  • Weiguang Cai

    (Chongqing University
    Lawrence Berkeley National Laboratory)

Abstract

Evaluating energy savings in China’s existing civil buildings (ESCECB) plays an essential role in China building energy efficiency (BEE) work. Nevertheless, one missing possibility along this direction is that the said work is currently challenged by the lack of effective method for calculating ESCECB data by summarizing all the quantifiable and unquantifiable impact factors. To overcome this problem, this study employed the method of Stochastic Impacts by Regression on Population, Affluence, and Technology, and the index decomposition approach of Logarithmic Mean Divisia Index to establish an effective ESCECB calculation method, and then calculated ESCECB data during the period of 2001–2015. Results reflect that ESCECB has significantly accumulated with the rapid development of China BEE work in the past 15 years. In particular, ESCECB data in 2001–2005, 2006–2010, and 2011–2015 are 111, 138, and 248 million tons of standard coal equivalent, respectively. Furthermore, the comparison between the calculated ESCECB and the officially planned ones in the said periods indicates that China has surpassed its BEE targets and China BEE policies obtained a good implementation effect. This study proves the feasibility of calculating ESCECB data and fills the lack of research on effective ESCECB calculation methods. Moreover, this calculation model is also applicable for calculating energy savings in existing civil buildings at a provincial or regional level.

Suggested Citation

  • Minda Ma & Ran Yan & Weiguang Cai, 2017. "A STIRPAT model-based methodology for calculating energy savings in China’s existing civil buildings from 2001 to 2015," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1765-1781, July.
  • Handle: RePEc:spr:nathaz:v:87:y:2017:i:3:d:10.1007_s11069-017-2847-x
    DOI: 10.1007/s11069-017-2847-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-017-2847-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-017-2847-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    2. Wang, Qiang & Li, Rongrong, 2016. "Drivers for energy consumption: A comparative analysis of China and India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 954-962.
    3. Zhang, Ming & Guo, Fangyan, 2013. "Analysis of rural residential commercial energy consumption in China," Energy, Elsevier, vol. 52(C), pages 222-229.
    4. Ang, B.W & Zhang, F.Q & Choi, Ki-Hong, 1998. "Factorizing changes in energy and environmental indicators through decomposition," Energy, Elsevier, vol. 23(6), pages 489-495.
    5. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    6. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Weimin Ma & Zitong Ren & Hua Ke, 2022. "Green Housing Subsidy Strategies Considering Consumers’ Green Preference," Sustainability, MDPI, vol. 14(5), pages 1-22, February.
    2. Qianwen Li & Ruyin Long & Hong Chen & Feiyu Chen & Xiu Cheng, 2019. "Chinese urban resident willingness to pay for green housing based on double-entry mental accounting theory," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 129-153, January.
    3. Wang, Yuanping & Hou, Lingchun & Cai, Weiguang & Zhou, Zhaoyin & Bian, Jing, 2023. "Exploring the drivers and influencing mechanisms of urban household electricity consumption in China - Based on longitudinal data at the provincial level," Energy, Elsevier, vol. 273(C).
    4. Minda Ma & Liyin Shen & Hong Ren & Weiguang Cai & Zhili Ma, 2017. "How to Measure Carbon Emission Reduction in China’s Public Building Sector: Retrospective Decomposition Analysis Based on STIRPAT Model in 2000–2015," Sustainability, MDPI, vol. 9(10), pages 1-16, September.
    5. Cai, Wei & Liu, Conghu & Zhang, Cuixia & Ma, Minda & Rao, Weizhen & Li, Wenyi & He, Kang & Gao, Mengdi, 2018. "Developing the ecological compensation criterion of industrial solid waste based on emergy for sustainable development," Energy, Elsevier, vol. 157(C), pages 940-948.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rui Jiang & Rongrong Li, 2017. "Decomposition and Decoupling Analysis of Life-Cycle Carbon Emission in China’s Building Sector," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    2. Jie-Fang Dong & Chun Deng & Xing-Min Wang & Xiao-Lei Zhang, 2016. "Multilevel Index Decomposition of Energy-Related Carbon Emissions and Their Decoupling from Economic Growth in Northwest China," Energies, MDPI, vol. 9(9), pages 1-17, August.
    3. Fernández-Amador, Octavio & Francois, Joseph F. & Oberdabernig, Doris A. & Tomberger, Patrick, 2023. "Energy footprints and the international trade network: A new dataset. Is the European Union doing it better?," Ecological Economics, Elsevier, vol. 204(PA).
    4. Xiao, Hao & Sun, Ke-Juan & Bi, Hui-Min & Xue, Jin-Jun, 2019. "Changes in carbon intensity globally and in countries: Attribution and decomposition analysis," Applied Energy, Elsevier, vol. 235(C), pages 1492-1504.
    5. Wang, Juan & Hu, Mingming & Rodrigues, João F.D., 2018. "The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis," Applied Energy, Elsevier, vol. 228(C), pages 2195-2206.
    6. Kaltenegger, Oliver, 2019. "What drives total real unit energy costs globally? A novel LMDI decomposition approach," CAWM Discussion Papers 110, University of Münster, Münster Center for Economic Policy (MEP).
    7. Wang, Miao & Feng, Chao, 2018. "Decomposing the change in energy consumption in China's nonferrous metal industry: An empirical analysis based on the LMDI method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2652-2663.
    8. Chen, Jiandong & Cheng, Shulei & Song, Malin, 2017. "Decomposing inequality in energy-related CO2 emissions by source and source increment: The roles of production and residential consumption," Energy Policy, Elsevier, vol. 107(C), pages 698-710.
    9. Jain, Princy & Goswami, Binoy, 2021. "Energy efficiency in South Asia: Trends and determinants," Energy, Elsevier, vol. 221(C).
    10. Minda Ma & Ran Yan & Weiguang Cai, 2017. "An extended STIRPAT model-based methodology for evaluating the driving forces affecting carbon emissions in existing public building sector: evidence from China in 2000–2015," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(2), pages 741-756, November.
    11. Román-Collado, Rocío & Cansino, José M. & Botia, Camilo, 2018. "How far is Colombia from decoupling? Two-level decomposition analysis of energy consumption changes," Energy, Elsevier, vol. 148(C), pages 687-700.
    12. Jiyong Park & Taeyoung Jin & Sungin Lee & Jongroul Woo, 2021. "Industrial Electrification and Efficiency: Decomposition Evidence from the Korean Industrial Sector," Energies, MDPI, vol. 14(16), pages 1-18, August.
    13. Kaltenegger, Oliver, 2020. "What drives total real unit energy costs globally? A novel LMDI decomposition approach," Applied Energy, Elsevier, vol. 261(C).
    14. Lin, Yuancheng & Ma, Linwei & Li, Zheng & Ni, Weidou, 2023. "The carbon reduction potential by improving technical efficiency from energy sources to final services in China: An extended Kaya identity analysis," Energy, Elsevier, vol. 263(PE).
    15. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Multilevel LMDI decomposition of changes in aggregate energy consumption. A cross country analysis in the EU-27," Energy Policy, Elsevier, vol. 68(C), pages 576-584.
    16. Xiaoping Zhu & Rongrong Li, 2017. "An Analysis of Decoupling and Influencing Factors of Carbon Emissions from the Transportation Sector in the Beijing-Tianjin-Hebei Area, China," Sustainability, MDPI, vol. 9(5), pages 1-19, April.
    17. Chen, Jiandong & Xu, Chong & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2019. "Driving factors of CO2 emissions and inequality characteristics in China: A combined decomposition approach," Energy Economics, Elsevier, vol. 78(C), pages 589-597.
    18. Wang, Qunwei & Hang, Ye & Su, Bin & Zhou, Peng, 2018. "Contributions to sector-level carbon intensity change: An integrated decomposition analysis," Energy Economics, Elsevier, vol. 70(C), pages 12-25.
    19. Chen, Jiandong & Cheng, Shulei & Song, Malin, 2018. "Changes in energy-related carbon dioxide emissions of the agricultural sector in China from 2005 to 2013," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 748-761.
    20. Banie Naser Outchiri, 2020. "Contributing to better energy and environmental analyses: how accurate are decomposition analysis results?," Cahiers de recherche 20-11, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:87:y:2017:i:3:d:10.1007_s11069-017-2847-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.