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Decomposition analysis of China's electricity intensity with LMDI method

Author

Listed:
  • Yongxiu He
  • Weijun Tao
  • Songlei Zhang
  • Weihong Yang
  • Furong Li

Abstract

Logarithmic Mean Divisia Index I (LMDI I) method is used to decompose China's Aggregate Electricity Intensity (CAEI) into structure effect and intensity effect at the 29-sub-sector level. The decomposition result shows that the intensity effect played a major role on the decline of CAEI during 1995-1999. Both structure effect and intensity effect account for the increase of CAEI since 2000. Structure effect and intensity effect account for 55.2% and 44.8%, respectively, of CAEI decrease during 1995-1999. The intensity effect contributed to the decline of CAEI during 1999-2007. However, the structure effect actually increased CAEI.

Suggested Citation

  • Yongxiu He & Weijun Tao & Songlei Zhang & Weihong Yang & Furong Li, 2009. "Decomposition analysis of China's electricity intensity with LMDI method," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 32(1/2), pages 34-48.
    • Handle: RePEc:ids:ijgeni:v:32:y:2009:i:1/2:p:34-48
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    Cited by:

    1. 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.
    2. Han Sun & Chao Huang & Shan Ni, 2022. "Driving factors of consumption-based PM2.5 emissions in China: an application of the generalized Divisia index," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 10209-10231, August.
    3. Qingyou Yan & Yaxian Wang & Tomas Baležentis & Yikai Sun & Dalia Streimikiene, 2018. "Energy-Related CO 2 Emission in China’s Provincial Thermal Electricity Generation: Driving Factors and Possibilities for Abatement," Energies, MDPI, vol. 11(5), pages 1-25, April.

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