IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v67y2017icp268-277.html
   My bibliography  Save this article

A regional analysis of carbon intensities of electricity generation in China

Author

Listed:
  • Liu, Nan
  • Ma, Zujun
  • Kang, Jidong

Abstract

Index decomposition analysis (IDA) has been widely applied to study CO2 emissions from electricity generation. However, most have focused on emissions at the country level, less attention has been given to emissions at the regional level. To fill the gap, this study firstly utilized a Logarithmic Mean Divisia Index (LMDI) method to analyze the driving forces of aggregate carbon intensity (ACI) of electricity generation in China from 2000 to 2014. A regional attribution analysis was introduced to look into the contributions from 30 provinces to the driving forces. Then, a multi-regional spatial-IDA was further adopted to assess the emission performance of electricity generation in 30 provinces. The results of temporal-IDA and regional attribution analysis show that the ACI in China dropped notably by 14.5% from 2000 to 2014. Thermal efficiency improvement was a major driver for the decrease, due largely to the significant improvement in thermal generation efficiency in the eastern coastal regions. Clean power penetration reduced ACI remarkably as well, of which the western regions were the main contributors. The spatial-IDA results indicate that the emission performance of electricity generation in different regions varied significantly. While the western regions performed better in clean power penetration, the eastern regions performed better in thermal generation efficiency. Based on the findings, several regional policy strategies were recommended to further lower down ACI of electricity in China.

Suggested Citation

  • Liu, Nan & Ma, Zujun & Kang, Jidong, 2017. "A regional analysis of carbon intensities of electricity generation in China," Energy Economics, Elsevier, vol. 67(C), pages 268-277.
  • Handle: RePEc:eee:eneeco:v:67:y:2017:i:c:p:268-277
    DOI: 10.1016/j.eneco.2017.08.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988317302748
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2017.08.018?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. Choi, Ki-Hong & Oh, Wankeun, 2014. "Extended Divisia index decomposition of changes in energy intensity: A case of Korean manufacturing industry," Energy Policy, Elsevier, vol. 65(C), pages 275-283.
    2. Karmellos, M. & Kopidou, D. & Diakoulaki, D., 2016. "A decomposition analysis of the driving factors of CO2 (Carbon dioxide) emissions from the power sector in the European Union countries," Energy, Elsevier, vol. 94(C), pages 680-692.
    3. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    4. Ang, B. W. & Choi, Ki-Hong, 2002. "Boundary problem in carbon emission decomposition," Energy Policy, Elsevier, vol. 30(13), pages 1201-1205, October.
    5. Shrestha, Ram M. & Anandarajah, Gabrial & Liyanage, Migara H., 2009. "Factors affecting CO2 emission from the power sector of selected countries in Asia and the Pacific," Energy Policy, Elsevier, vol. 37(6), pages 2375-2384, June.
    6. Malla, Sunil, 2009. "CO2 emissions from electricity generation in seven Asia-Pacific and North American countries: A decomposition analysis," Energy Policy, Elsevier, vol. 37(1), pages 1-9, January.
    7. Shrestha, Ram M. & Timilsina, Govinda R., 1996. "Factors affecting CO2 intensities of power sector in Asia: A Divisia decomposition analysis," Energy Economics, Elsevier, vol. 18(4), pages 283-293, October.
    8. Choi, Ki-Hong & Ang, B.W., 2012. "Attribution of changes in Divisia real energy intensity index — An extension to index decomposition analysis," Energy Economics, Elsevier, vol. 34(1), pages 171-176.
    9. Yang, Lisha & Lin, Boqiang, 2016. "Carbon dioxide-emission in China׳s power industry: Evidence and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 258-267.
    10. Wang, Qunwei & Hang, Ye & Zhou, P. & Wang, Yizhong, 2016. "Decoupling and attribution analysis of industrial carbon emissions in Taiwan," Energy, Elsevier, vol. 113(C), pages 728-738.
    11. Yan, Qingyou & Zhang, Qian & Zou, Xin, 2016. "Decomposition analysis of carbon dioxide emissions in China's regional thermal electricity generation, 2000–2020," Energy, Elsevier, vol. 112(C), pages 788-794.
    12. Su, Bin & Ang, B.W., 2014. "Attribution of changes in the generalized Fisher index with application to embodied emission studies," Energy, Elsevier, vol. 69(C), pages 778-786.
    13. Su, Bin & Ang, B.W., 2017. "Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 65(C), pages 137-147.
    14. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    15. Fernández González, P. & Landajo, M. & Presno, M.J., 2013. "The Divisia real energy intensity indices: Evolution and attribution of percent changes in 20 European countries from 1995 to 2010," Energy, Elsevier, vol. 58(C), pages 340-349.
    16. Zhang, Ming & Liu, Xiao & Wang, Wenwen & Zhou, Min, 2013. "Decomposition analysis of CO2 emissions from electricity generation in China," Energy Policy, Elsevier, vol. 52(C), pages 159-165.
    17. Ang, B.W. & Goh, Tian, 2016. "Carbon intensity of electricity in ASEAN: Drivers, performance and outlook," Energy Policy, Elsevier, vol. 98(C), pages 170-179.
    18. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    19. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    20. Hasanbeigi, Ali & Price, Lynn & Fino-Chen, Cecilia & Lu, Hongyou & Ke, Jing, 2013. "Retrospective and prospective decomposition analysis of Chinese manufacturing energy use and policy implications," Energy Policy, Elsevier, vol. 63(C), pages 562-574.
    21. Liu, Nan & Ma, Zujun & Kang, Jidong, 2015. "Changes in carbon intensity in China's industrial sector: Decomposition and attribution analysis," Energy Policy, Elsevier, vol. 87(C), pages 28-38.
    22. Jiankun, He & Zhiwei, Yu & Da, Zhang, 2012. "China's strategy for energy development and climate change mitigation," Energy Policy, Elsevier, vol. 51(C), pages 7-13.
    23. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    24. Ang, B.W. & Su, Bin, 2016. "Carbon emission intensity in electricity production: A global analysis," Energy Policy, Elsevier, vol. 94(C), pages 56-63.
    25. Kang, Jidong & Zhao, Tao & Liu, Nan & Zhang, Xin & Xu, Xianshuo & Lin, Tao, 2014. "A multi-sectoral decomposition analysis of city-level greenhouse gas emissions: Case study of Tianjin, China," Energy, Elsevier, vol. 68(C), pages 562-571.
    26. Kim, Yong-Gun & Yoo, Jonghyun & Oh, Wankeun, 2015. "Driving forces of rapid CO2 emissions growth: A case of Korea," Energy Policy, Elsevier, vol. 82(C), pages 144-155.
    27. Hu, Junfeng & Kahrl, Fredrich & Yan, Qingyou & Wang, Xiaoya, 2012. "The impact of China's differential electricity pricing policy on power sector CO2 emissions," Energy Policy, Elsevier, vol. 45(C), pages 412-419.
    28. Nag, Barnali & Parikh, Jyoti K., 2005. "Carbon emission coefficient of power consumption in India: baseline determination from the demand side," Energy Policy, Elsevier, vol. 33(6), pages 777-786, April.
    29. Steenhof, Paul A., 2007. "Decomposition for emission baseline setting in China's electricity sector," Energy Policy, Elsevier, vol. 35(1), pages 280-294, January.
    30. Lo, Kevin, 2014. "A critical review of China's rapidly developing renewable energy and energy efficiency policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 508-516.
    31. Su, Bin & Ang, B.W., 2015. "Multiplicative decomposition of aggregate carbon intensity change using input–output analysis," Applied Energy, Elsevier, vol. 154(C), pages 13-20.
    32. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    33. Ang, B.W. & Huang, H.C. & Mu, A.R., 2009. "Properties and linkages of some index decomposition analysis methods," Energy Policy, Elsevier, vol. 37(11), pages 4624-4632, November.
    34. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    35. Steenhof, Paul A. & Weber, Chris J., 2011. "An assessment of factors impacting Canada's electricity sector's GHG emissions," Energy Policy, Elsevier, vol. 39(7), pages 4089-4096, July.
    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. Goh, Tian & Ang, B.W. & Xu, X.Y., 2018. "Quantifying drivers of CO2 emissions from electricity generation – Current practices and future extensions," Applied Energy, Elsevier, vol. 231(C), pages 1191-1204.
    2. Liu, Nan & Ma, Zujun & Kang, Jidong & Su, Bin, 2019. "A multi-region multi-sector decomposition and attribution analysis of aggregate carbon intensity in China from 2000 to 2015," Energy Policy, Elsevier, vol. 129(C), pages 410-421.
    3. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    4. Ang, B.W. & Goh, Tian, 2016. "Carbon intensity of electricity in ASEAN: Drivers, performance and outlook," Energy Policy, Elsevier, vol. 98(C), pages 170-179.
    5. 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.
    6. 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.
    7. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    8. Liu, Nan & Ma, Zujun & Kang, Jidong, 2015. "Changes in carbon intensity in China's industrial sector: Decomposition and attribution analysis," Energy Policy, Elsevier, vol. 87(C), pages 28-38.
    9. Wang, Qunwei & Hang, Ye & Zhou, P. & Wang, Yizhong, 2016. "Decoupling and attribution analysis of industrial carbon emissions in Taiwan," Energy, Elsevier, vol. 113(C), pages 728-738.
    10. Ang, B.W. & Goh, Tian, 2019. "Index decomposition analysis for comparing emission scenarios: Applications and challenges," Energy Economics, Elsevier, vol. 83(C), pages 74-87.
    11. Xinlin Zhang & Yuan Zhao & Qi Sun & Changjian Wang, 2017. "Decomposition and Attribution Analysis of Industrial Carbon Intensity Changes in Xinjiang, China," Sustainability, MDPI, vol. 9(3), pages 1-16, March.
    12. 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.
    13. Xiao, Hao & Sun, Ke-Juan & Bi, Hui-Min & Meng, Bo, 2021. "Attribution of changes in an intensity index," Energy, Elsevier, vol. 216(C).
    14. Ma, Jia-Jun & Du, Gang & Xie, Bai-Chen, 2019. "CO2 emission changes of China's power generation system: Input-output subsystem analysis," Energy Policy, Elsevier, vol. 124(C), pages 1-12.
    15. Mathy, Sandrine & Menanteau, Philippe & Criqui, Patrick, 2018. "After the Paris Agreement: Measuring the Global Decarbonization Wedges From National Energy Scenarios," Ecological Economics, Elsevier, vol. 150(C), pages 273-289.
    16. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    17. Zhu, Bangzhu & Su, Bin & Li, Yingzhu & Ng, Tsan Sheng, 2020. "Embodied energy and intensity in China’s (normal and processing) exports and their driving forces, 2005-2015," Energy Economics, Elsevier, vol. 91(C).
    18. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    19. Juan Wang & Tao Zhao & Xiaohu Zhang, 2017. "Changes in carbon intensity of China’s energy-intensive industries: a combined decomposition and attribution analysis," 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. 88(3), pages 1655-1675, September.
    20. Wang, Yaxian & Zhao, Zhenli & Wang, Wenju & Streimikiene, Dalia & Balezentis, Tomas, 2023. "Interplay of multiple factors behind decarbonisation of thermal electricity generation: A novel decomposition model," Technological Forecasting and Social Change, Elsevier, vol. 189(C).

    More about this item

    Keywords

    China; Regions; Carbon intensity of electricity; Temporal-IDA; Regional attribution analysis; Spatial-IDA;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

    Statistics

    Access and download statistics

    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:eneeco:v:67:y:2017:i:c:p:268-277. 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/locate/eneco .

    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.