IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v162y2016icp1303-1312.html
   My bibliography  Save this article

Modelling building’s decarbonization with application of China TIMES model

Author

Listed:
  • Shi, Jingcheng
  • Chen, Wenying
  • Yin, Xiang

Abstract

Over the recent decades, China’s building energy consumption has been growing rapidly. Also the fuel mix has been changing quickly with more natural gas & electricity and less coal being used. Meanwhile, the technologies used in building sector are improving in efficiency. In this paper, the impact of technical progress and the use of renewable energy in building sector are analyzed. The energy saving and emission reduction potential of building sector are also measured. China TIMES model is used to model the future energy consumption and carbon emissions in building sector. The modelling results indicate that building energy consumption is expected to grow to around 41.6EJ in the reference scenario in 2050. The energy saving potential in 2050 can be up to 4EJ due to the improvement of both building insulation (envelop) and energy use technologies. Renewable energy used in buildings can be a great contributor to the carbon mitigation in buildings. China’s building sector can reach a relatively low-carbon future with more low- and non-carbon fuels consumed.

Suggested Citation

  • Shi, Jingcheng & Chen, Wenying & Yin, Xiang, 2016. "Modelling building’s decarbonization with application of China TIMES model," Applied Energy, Elsevier, vol. 162(C), pages 1303-1312.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1303-1312
    DOI: 10.1016/j.apenergy.2015.06.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915008144
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.06.056?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. Chaturvedi, Vaibhav & Eom, Jiyong & Clarke, Leon E. & Shukla, Priyadarshi R., 2014. "Long term building energy demand for India: Disaggregating end use energy services in an integrated assessment modeling framework," Energy Policy, Elsevier, vol. 64(C), pages 226-242.
    2. Chen, Wenying, 2005. "The costs of mitigating carbon emissions in China: findings from China MARKAL-MACRO modeling," Energy Policy, Elsevier, vol. 33(7), pages 885-896, May.
    3. Seljom, Pernille & Rosenberg, Eva & Fidje, Audun & Haugen, Jan Erik & Meir, Michaela & Rekstad, John & Jarlset, Thore, 2011. "Modelling the effects of climate change on the energy system—A case study of Norway," Energy Policy, Elsevier, vol. 39(11), pages 7310-7321.
    4. Chen, Wenying & Li, Hualin & Wu, Zongxin, 2010. "Western China energy development and west to east energy transfer: Application of the Western China Sustainable Energy Development Model," Energy Policy, Elsevier, vol. 38(11), pages 7106-7120, November.
    5. Huo, Hong & Wang, Michael, 2012. "Modeling future vehicle sales and stock in China," Energy Policy, Elsevier, vol. 43(C), pages 17-29.
    6. De Rosa, Mattia & Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Heating and cooling building energy demand evaluation; a simplified model and a modified degree days approach," Applied Energy, Elsevier, vol. 128(C), pages 217-229.
    7. Yin, Xiang & Chen, Wenying, 2013. "Trends and development of steel demand in China: A bottom–up analysis," Resources Policy, Elsevier, vol. 38(4), pages 407-415.
    8. Richard Loulou, 2008. "ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation," Computational Management Science, Springer, vol. 5(1), pages 41-66, February.
    9. Chen, Wenying & Wu, Zongxin & He, Jiankun & Gao, Pengfei & Xu, Shaofeng, 2007. "Carbon emission control strategies for China: A comparative study with partial and general equilibrium versions of the China MARKAL model," Energy, Elsevier, vol. 32(1), pages 59-72.
    10. Cai, W.G. & Wu, Y. & Zhong, Y. & Ren, H., 2009. "China building energy consumption: Situation, challenges and corresponding measures," Energy Policy, Elsevier, vol. 37(6), pages 2054-2059, June.
    11. Yang, Li & He, Bao-jie & Ye, Miao, 2014. "The application of solar technologies in building energy efficiency: BISE design in solar-powered residential buildings," Technology in Society, Elsevier, vol. 38(C), pages 111-118.
    12. 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.
    13. Olonscheck, Mady & Holsten, Anne & Kropp, Jürgen P., 2011. "Heating and cooling energy demand and related emissions of the German residential building stock under climate change," Energy Policy, Elsevier, vol. 39(9), pages 4795-4806, September.
    14. Yuan, Xueliang & Wang, Xujiang & Zuo, Jian, 2013. "Renewable energy in buildings in China—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 1-8.
    15. Richard Loulou & Maryse Labriet, 2008. "ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure," Computational Management Science, Springer, vol. 5(1), pages 7-40, February.
    16. 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.
    17. Chen, Wenying & Yin, Xiang & Ma, Ding, 2014. "A bottom-up analysis of China’s iron and steel industrial energy consumption and CO2 emissions," Applied Energy, Elsevier, vol. 136(C), pages 1174-1183.
    18. Verbai, Zoltán & Lakatos, Ákos & Kalmár, Ferenc, 2014. "Prediction of energy demand for heating of residential buildings using variable degree day," Energy, Elsevier, vol. 76(C), pages 780-787.
    Full references (including those not matched with items on IDEAS)

    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. Li, Nan & Chen, Wenying, 2019. "Energy-water nexus in China's energy bases: From the Paris agreement to the Well Below 2 Degrees target," Energy, Elsevier, vol. 166(C), pages 277-286.
    2. Huan Wang & Wenying Chen & Hongjun Zhang & Nan Li, 2020. "Modeling of power sector decarbonization in China: comparisons of early and delayed mitigation towards 2-degree target," Climatic Change, Springer, vol. 162(4), pages 1843-1856, October.
    3. Ma, Ding & Chen, Wenying & Yin, Xiang & Wang, Lining, 2016. "Quantifying the co-benefits of decarbonisation in China’s steel sector: An integrated assessment approach," Applied Energy, Elsevier, vol. 162(C), pages 1225-1237.
    4. Wang, Huan & Chen, Wenying & Shi, Jingcheng, 2018. "Low carbon transition of global building sector under 2- and 1.5-degree targets," Applied Energy, Elsevier, vol. 222(C), pages 148-157.
    5. Yin, Xiang & Chen, Wenying & Eom, Jiyong & Clarke, Leon E. & Kim, Son H. & Patel, Pralit L. & Yu, Sha & Kyle, G. Page, 2015. "China's transportation energy consumption and CO2 emissions from a global perspective," Energy Policy, Elsevier, vol. 82(C), pages 233-248.
    6. Zhang, Qiang & Chen, Wenying, 2020. "Modeling China’s interprovincial electricity transmission under low carbon transition," Applied Energy, Elsevier, vol. 279(C).
    7. Li, Nan & Ma, Ding & Chen, Wenying, 2017. "Quantifying the impacts of decarbonisation in China’s cement sector: A perspective from an integrated assessment approach," Applied Energy, Elsevier, vol. 185(P2), pages 1840-1848.
    8. Sachs, Julia & Moya, Diego & Giarola, Sara & Hawkes, Adam, 2019. "Clustered spatially and temporally resolved global heat and cooling energy demand in the residential sector," Applied Energy, Elsevier, vol. 250(C), pages 48-62.
    9. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
    10. Li, Nan & Chen, Wenying, 2018. "Modeling China’s interprovincial coal transportation under low carbon transition," Applied Energy, Elsevier, vol. 222(C), pages 267-279.
    11. Chen, Han & Yang, Lei & Chen, Wenying, 2020. "Modelling national, provincial and city-level low-carbon energy transformation pathways," Energy Policy, Elsevier, vol. 137(C).
    12. Li, Nan & Chen, Wenying & Zhang, Qiang, 2020. "Development of China TIMES-30P model and its application to model China's provincial low carbon transformation," Energy Economics, Elsevier, vol. 92(C).
    13. Huang, Weilong & Ma, Ding & Chen, Wenying, 2017. "Connecting water and energy: Assessing the impacts of carbon and water constraints on China’s power sector," Applied Energy, Elsevier, vol. 185(P2), pages 1497-1505.
    14. Zhang, Hongjun & Chen, Wenying & Huang, Weilong, 2016. "TIMES modelling of transport sector in China and USA: Comparisons from a decarbonization perspective," Applied Energy, Elsevier, vol. 162(C), pages 1505-1514.
    15. Ettore Bompard & Daniele Grosso & Tao Huang & Francesco Profumo & Xianzhang Lei & Duo Li, 2018. "World Decarbonization through Global Electricity Interconnections," Energies, MDPI, vol. 11(7), pages 1-29, July.
    16. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    17. Hartin, Corinne & Link, Robert & Patel, Pralit & Mundra, Anupriya & Horowitz, Russell & Dorheim, Kalyn & Clarke, Leon, 2021. "Integrated modeling of human-earth system interactions: An application of GCAM-fusion," Energy Economics, Elsevier, vol. 103(C).
    18. Yu, Sha & Tan, Qing & Evans, Meredydd & Kyle, Page & Vu, Linh & Patel, Pralit L., 2017. "Improving building energy efficiency in India: State-level analysis of building energy efficiency policies," Energy Policy, Elsevier, vol. 110(C), pages 331-341.
    19. Huo, Tengfei & Ma, Yuling & Xu, Linbo & Feng, Wei & Cai, Weiguang, 2022. "Carbon emissions in China's urban residential building sector through 2060: A dynamic scenario simulation," Energy, Elsevier, vol. 254(PA).
    20. Li, Danyang & Chen, Wenying, 2019. "TIMES modeling of the large-scale popularization of electric vehicles under the worldwide prohibition of liquid vehicle sales," Applied Energy, Elsevier, vol. 254(C).

    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:eee:appene:v:162:y:2016:i:c:p:1303-1312. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.