IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v99y2019i3d10.1007_s11069-018-3535-1.html
   My bibliography  Save this article

Study of the impact of energy consumption structure on carbon emission intensity in China from the perspective of spatial effects

Author

Listed:
  • Hongwei Xiao

    () (State Information Center
    Beijing Energy Development Research Center)

  • Zhongyu Ma

    (State Information Center
    Renmin University of China)

  • Peng Zhang

    (State Information Center)

  • Ming Liu

    (State Information Center)

Abstract

From now until 2030, China will be in a sprint to achieve reductions of 40–45% in carbon emission intensity by 2020 and 60–65% by 2030 compared to 2005; rigid requirements have thus been imposed for controlling carbon emission intensity. In this study, a spatial Durbin model that integrates a spatial lag model and a spatial error model is used to measure the degree of influence held by the energy consumption structure and other factors over carbon emission intensity and the spatial spillover effect. The results show that there is a spatial demonstration effect on the reduction in interregional carbon emission intensity in China. While the carbon emission intensity in the adjacent region decreases by 1%, the carbon emission intensity in this region will decrease by 0.05%, indicating that China’s regional low-carbon development model is also applicable to neighboring provinces and plays a large role in driving and demonstrating a low-carbon economy. Every additional 1% improvement toward optimizing the energy consumption structure enables the carbon emission intensity of the region to decrease by 0.21%; further, there is a positive spatial spillover effect driving carbon emission intensity decreases in neighboring areas of 0.25%. Industrial structure, energy intensity, energy price, and level of openness are the main factors influencing regional carbon emission intensity. According to the “14th Five-Year Plan,” there is an urgent need to optimize the energy consumption structure in the medium and long term and give full play to its ability to contribute to declines in carbon emission intensity.

Suggested Citation

  • Hongwei Xiao & Zhongyu Ma & Peng Zhang & Ming Liu, 2019. "Study of the impact of energy consumption structure on carbon emission intensity in China from the perspective of spatial effects," 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. 99(3), pages 1365-1380, December.
  • Handle: RePEc:spr:nathaz:v:99:y:2019:i:3:d:10.1007_s11069-018-3535-1
    DOI: 10.1007/s11069-018-3535-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-018-3535-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    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. Greening, Lorna A., 2004. "Effects of human behavior on aggregate carbon intensity of personal transportation: comparison of 10 OECD countries for the period 1970-1993," Energy Economics, Elsevier, vol. 26(1), pages 1-30, January.
    2. Ang, B.W. & Su, Bin, 2016. "Carbon emission intensity in electricity production: A global analysis," Energy Policy, Elsevier, vol. 94(C), pages 56-63.
    3. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    4. Greening, Lorna A. & Ting, Mike & Davis, William B., 1999. "Decomposition of aggregate carbon intensity for freight: trends from 10 OECD countries for the period 1971-1993," Energy Economics, Elsevier, vol. 21(4), pages 331-361, August.
    5. Wang, Peng & Dai, Han-cheng & Ren, Song-yan & Zhao, Dai-qing & Masui, Toshihiko, 2015. "Achieving Copenhagen target through carbon emission trading: Economic impacts assessment in Guangdong Province of China," Energy, Elsevier, vol. 79(C), pages 212-227.
    6. Nag, Barnali & Parikh, Jyoti, 2000. "Indicators of carbon emission intensity from commercial energy use in India," Energy Economics, Elsevier, vol. 22(4), pages 441-461, August.
    7. Fang, Guochang & Tian, Lixin & Fu, Min & Sun, Mei, 2013. "The impacts of carbon tax on energy intensity and economic growth – A dynamic evolution analysis on the case of China," Applied Energy, Elsevier, vol. 110(C), pages 17-28.
    8. Luc Anselin, 2001. "Spatial Effects in Econometric Practice in Environmental and Resource Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 705-710.
    9. Greening, Lorna A. & Ting, Michael & Krackler, Thomas J., 2001. "Effects of changes in residential end-uses and behavior on aggregate carbon intensity: comparison of 10 OECD countries for the period 1970 through 1993," Energy Economics, Elsevier, vol. 23(2), pages 153-178, March.
    10. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China," 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. 73(2), pages 579-595, September.
    11. Bhattacharyya, Subhes C. & Matsumura, Wataru, 2010. "Changes in the GHG emission intensity in EU-15: Lessons from a decomposition analysis," Energy, Elsevier, vol. 35(8), pages 3315-3322.
    12. Zhang, Wei & Li, Ke & Zhou, Dequn & Zhang, Wenrui & Gao, Hui, 2016. "Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method," Energy Policy, Elsevier, vol. 92(C), pages 369-381.
    13. Jianling Jiao & Yufei Yang & Yu Bai, 2018. "The impact of inter-industry R&D technology spillover on carbon emission in China," 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. 91(3), pages 913-929, April.
    14. Feng Dong & Ruyin Long & Zhuolin Li & Yuanju Dai, 2016. "Analysis of carbon emission intensity, urbanization and energy mix: evidence from China," 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. 82(2), pages 1375-1391, June.
    15. Shiyi Chen, 2011. "The Abatement of Carbon Dioxide Intensity in China: Factors Decomposition and Policy Implications," The World Economy, Wiley Blackwell, vol. 34, pages 1148-1167, July.
    16. Ren, Shenggang & Yuan, Baolong & Ma, Xie & Chen, Xiaohong, 2014. "The impact of international trade on China׳s industrial carbon emissions since its entry into WTO," Energy Policy, Elsevier, vol. 69(C), pages 624-634.
    17. Yu, Xiang & Chen, Hongbo & Wang, Bo & Wang, Ran & Shan, Yuli, 2018. "Driving forces of CO2 emissions and mitigation strategies of China’s National low carbon pilot industrial parks," Applied Energy, Elsevier, vol. 212(C), pages 1553-1562.
    18. Hammond, G.P. & Norman, J.B., 2012. "Decomposition analysis of energy-related carbon emissions from UK manufacturing," Energy, Elsevier, vol. 41(1), pages 220-227.
    19. Ramphul Ohlan, 2015. "The impact of population density, energy consumption, economic growth and trade openness on CO 2 emissions in India," 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. 79(2), pages 1409-1428, November.
    20. Fisher-Vanden, Karen & Schu, Kathryn & Sue Wing, Ian & Calvin, Katherine, 2012. "Decomposing the impact of alternative technology sets on future carbon emissions growth," Energy Economics, Elsevier, vol. 34(S3), pages 359-365.
    21. Yanan Chen & Sheng Lin, 2015. "Decomposition and allocation of energy-related carbon dioxide emission allowance over provinces of China," 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. 76(3), pages 1893-1909, April.
    22. Lu, I.J. & Lin, Sue J. & Lewis, Charles, 2007. "Decomposition and decoupling effects of carbon dioxide emission from highway transportation in Taiwan, Germany, Japan and South Korea," Energy Policy, Elsevier, vol. 35(6), pages 3226-3235, June.
    23. Fan, Jing-Li & Liao, Hua & Liang, Qiao-Mei & Tatano, Hirokazu & Liu, Chun-Feng & Wei, Yi-Ming, 2013. "Residential carbon emission evolutions in urban–rural divided China: An end-use and behavior analysis," Applied Energy, Elsevier, vol. 101(C), pages 323-332.
    24. Robaina Alves, Margarita & Moutinho, Victor, 2013. "Decomposition analysis and Innovative Accounting Approach for energy-related CO2 (carbon dioxide) emissions intensity over 1996–2009 in Portugal," Energy, Elsevier, vol. 57(C), pages 775-787.
    Full references (including those not matched with items on IDEAS)

    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:99:y:2019:i:3:d:10.1007_s11069-018-3535-1. See general information about how to correct material in RePEc.

    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). General contact details of provider: http://www.springer.com .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.