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Exploring the changes of energy-related carbon intensity in China: an extended Divisia index decomposition

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Abstract

To gain a better understanding of the changes in carbon intensity of China, this study firstly adopted logarithmic mean Divisia index decomposition analysis to decompose the carbon intensity into three driving factors, including emission coefficient effect, energy intensity effect and industrial structure effect. Then, the analysis was furtherly conducted to study the contributions of four economic sectors to the percent change in carbon intensity through each influencing factor by attribution analysis. The results illustrated that the carbon intensity dropped by 46.21 % from 1996 to 2012 mainly caused by the decrease in energy intensity, of which the industrial sector, transportation sector and commercial & service sector were the dominant contributors. The emission coefficient effect and industrial structure effect were equally important in terms of increasing carbon intensity, which principally due to the industrial sector and commercial & service sector. In addition, the energy efficiency of agricultural sector should be furtherly improved, and it is imperative to optimize the energy mix and industrial structure of the industrial sector and commercial & service sector. Therefore, more differentiated policies are urgently required to be implemented in different economic sectors to mitigate the China’s carbon intensity.

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Notes

  1. During the period of APEC (Asia–Pacific Economic Cooperation) in 2014, Chinese government made commitment related to climate change in the “Sino-US Joint Statement on Climate Change.”

  2. Refer to Song et al. (2015): statistics show that energy consumption accounts for 80 % of the global anthropogenic CO2 emissions, and traditional fossil energy resources like oil and coal take a large proportion of total energy use.

  3. Heat mainly comes from the combustion of fossil fuels, and the contribution of nuclear and hydro energy is little. So \(E_{{{\text{nuclear}},t}} \,{\text{and}}\,E_{{{\text{hydro}},t}}\) of heat are considered as zero.

  4. Emission coefficient: the ratio of CO2 emission equivalent and energy consumption.

  5. Energy intensity: the ratio of energy consumption and GDP.

  6. Industrial structure: the ratio of GDP for an economic sector and China’s total GDP.

  7. Resource: National Development and Reform Commission. China’s National Plan on Climate Change (2014–2020). Available from: http://www.sdpc.gov.cn/zcfb/zcfbtz/201411/W020141104584717807138.pdf.

  8. Refers to the commitment of Chinese government issued during the APEC period in 2014 in the “Sino-US Joint Statement on Climate Change.”

  9. Chinese government released the “11th FYP for the development of renewable energy” and pointed out the proportion of renewable energy in energy consumption in China would reach 10 %, and the annual utilization of renewable energy would attain 300 million tons of coal equivalent in 2010.

  10. In order to deal with the financial crisis, response to climate change and enhance the international competitiveness, the National Energy Bureau put forward the “New energy industry development planning.”

  11. During the 12th Five-year period, the National Energy Bureau plan to promote the sustainable and healthy development of solar energy industry.

  12. The State Council of China published “12th Five Year national strategic emerging industry development plan” and encouraged the development of new energy etc. emerging industries.

  13. In order to promote the fundamental requirement of new industrialization, the State Council of China plan to adjust and optimize the economic structure, as well as promote transformation and upgrading of industrial sector.

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Acknowledgments

The authors gratefully acknowledge the anonymous reviewers for their valuable suggestions and comments on the earlier draft of our paper. This research is supported by the Ministry of Education of Humanities and Social Science Research Fund Plan (15YJA790091), the Ministry of Education of Philosophy and Social Major Science Project (15JZD021) and the National Natural Science Foundation of China (71373172).

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Authors and Affiliations

  1. College of management and economics, Tianjin University, Tianjin, 300072, China

    Juan Wang, Tao Zhao & Xianshuo Xu

  2. College of Civil Aviation, Nanjing University of Aeronautics and Astronautic, Nanjing, 210016, Jiangsu, China

    Xiaohu Zhang

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  1. Juan Wang
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  2. Tao Zhao
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  3. Xianshuo Xu
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  4. Xiaohu Zhang
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Correspondence to Juan Wang.

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Wang, J., Zhao, T., Xu, X. et al. Exploring the changes of energy-related carbon intensity in China: an extended Divisia index decomposition. Nat Hazards 83, 501–521 (2016). https://doi.org/10.1007/s11069-016-2326-9

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