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Decomposition analysis of CO2 emissions from electricity generation in China

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  • Zhang, Ming
  • Liu, Xiao
  • Wang, Wenwen
  • Zhou, Min
Abstract
Electricity generation in China mainly depends on coal and its products, which has led to the increase in CO2 emissions. This paper intends to analyze the current status of CO2 emissions from electricity generation in China during the period 1991–2009, and apply the logarithmic mean Divisia index (LMDI) technique to find the nature of the factors influencing the changes in CO2 emissions. The main results as follows: (1) CO2 emission from electricity generation has increased from 530.96Mt in 1991 to 2393.02Mt in 2009, following an annual growth rate of 8.72%. Coal products is the main fuel type for thermal power generation, which accounts for more than 90% CO2 emissions from electricity generation. (2) This paper also presents CO2 emissions factor of electricity consumption, which help calculate CO2 emission from final electricity consumption. (3) In China, the economic activity effect is the most important contributor to increase CO2 emissions from electricity generation, but the electricity generation efficiency effect plays the dominant role in decreasing CO2 emissions.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:enepol:v:52:y:2013:i:c:p:159-165
    DOI: 10.1016/j.enpol.2012.10.013
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    References listed on IDEAS

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    1. 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.
    2. Paul, Shyamal & Bhattacharya, Rabindra Nath, 2004. "CO2 emission from energy use in India: a decomposition analysis," Energy Policy, Elsevier, vol. 32(5), pages 585-593, March.
    3. Ma, Chunbo & Stern, David I., 2008. "China's changing energy intensity trend: A decomposition analysis," Energy Economics, Elsevier, vol. 30(3), pages 1037-1053, May.
    4. 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.
    5. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    6. Steenhof, Paul A., 2006. "Decomposition of electricity demand in China's industrial sector," Energy Economics, Elsevier, vol. 28(3), pages 370-384, May.
    7. Wang, Wenchao & Mu, Hailin & Kang, Xudong & Song, Rongchen & Ning, Yadong, 2010. "Changes in industrial electricity consumption in china from 1998 to 2007," Energy Policy, Elsevier, vol. 38(7), pages 3684-3690, July.
    8. Sun, J.W., 1998. "Accounting for energy use in China, 1980–94," Energy, Elsevier, vol. 23(10), pages 835-849.
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    Keywords

    CO2 emissions; Electricity generation; LMDI;
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