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Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization

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Listed:
  • Yu, Shiwei
  • Wei, Yi-Ming
  • Fan, Jingli
  • Zhang, Xian
  • Wang, Ke

Abstract

The better to explore the regional characteristics of inter-provincial CO2 emissions and the rational distribution of the reduction of emission intensity reduction in China, this paper proposes an improved PSO-FCM clustering algorithm. This method can obtain the optimal cluster number and membership grade values by utilizing the global capacity of Particle Swarm Optimization (PSO) on Fuzzy C-means (FCM). The clustering results of CO2 emissions indicate that the 30 provinces of China are divided into five clusters and each has its own significant characteristics. Compared with other clustering methods, the results of PSO-FCM are more explanatory. The most important indicators affecting regional emission characteristics are CO2 emission intensity and per capita emissions, whereas CO2 emission per unit of energy is not obvious in clustering. Furthermore, some policy recommendations on setting emission reduction targets according to the emission characteristics of different clusters are made.

Suggested Citation

  • Yu, Shiwei & Wei, Yi-Ming & Fan, Jingli & Zhang, Xian & Wang, Ke, 2012. "Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization," Applied Energy, Elsevier, vol. 92(C), pages 552-562.
    • Handle: RePEc:eee:appene:v:92:y:2012:i:c:p:552-562
    DOI: 10.1016/j.apenergy.2011.11.068
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    1. Gómez, M. & López, A. & Jurado, F., 2010. "Optimal placement and sizing from standpoint of the investor of Photovoltaics Grid-Connected Systems using Binary Particle Swarm Optimization," Applied Energy, Elsevier, vol. 87(6), pages 1911-1918, June.
    2. Unler, Alper & Murat, Alper, 2010. "A discrete particle swarm optimization method for feature selection in binary classification problems," European Journal of Operational Research, Elsevier, vol. 206(3), pages 528-539, November.
    3. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    4. Atkins, Martin J. & Morrison, Andrew S. & Walmsley, Michael R.W., 2010. "Carbon Emissions Pinch Analysis (CEPA) for emissions reduction in the New Zealand electricity sector," Applied Energy, Elsevier, vol. 87(3), pages 982-987, March.
    5. Sharma, Susan Sunila, 2011. "Determinants of carbon dioxide emissions: Empirical evidence from 69 countries," Applied Energy, Elsevier, vol. 88(1), pages 376-382, January.
    6. Wang, Run & Liu, Wenjuan & Xiao, Lishan & Liu, Jian & Kao, William, 2011. "Path towards achieving of China's 2020 carbon emission reduction target--A discussion of low-carbon energy policies at province level," Energy Policy, Elsevier, vol. 39(5), pages 2740-2747, May.
    7. Feng, Kuishuang & Hubacek, Klaus & Guan, Dabo, 2009. "Lifestyles, technology and CO2 emissions in China: A regional comparative analysis," Ecological Economics, Elsevier, vol. 69(1), pages 145-154, November.
    8. Clarke-Sather, Afton & Qu, Jiansheng & Wang, Qin & Zeng, Jingjing & Li, Yan, 2011. "Carbon inequality at the sub-national scale: A case study of provincial-level inequality in CO2 emissions in China 1997-2007," Energy Policy, Elsevier, vol. 39(9), pages 5420-5428, September.
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    More about this item

    Keywords

    Fuzzy C-means cluster; Carbon emission; Characteristics; Mitigation policy;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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