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Decomposition Analysis of Carbon Emissions from Energy Consumption in Beijing-Tianjin-Hebei, China: A Weighted-Combination Model Based on Logarithmic Mean Divisia Index and Shapley Value

Author

Listed:
  • Yi Liang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Dongxiao Niu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Weiwei Zhou

    (Department of Comprehensive Management, The Second Branch of Transformation Construction, Beijing Electricity Transmission and Transformation Corporation, Beijing 102401, China)

  • Yingying Fan

    (School of Art Design, Hebei GEO University, Shijiazhuang 050031, China)

Abstract

The Beijing-Tianjin-Hebei (B-T-H) region, who captures the national strategic highland in China, has drawn a great deal of attention due to the fog and haze condition and other environmental problems. Further, the high carbon emissions generated by energy consumption has restricted its further coordinated development seriously. In order to accurately analyze the potential influencing factors that contribute to the growth of energy consumption carbon emissions in the B-T-H region, this paper uses the carbon emission coefficient method to measure the carbon emissions of energy consumption in the B-T-H region, using a weighted combination based on Logarithmic Mean Divisia Index (LMDI) and Shapley Value (SV). The effects affecting carbon emissions during 2001–2013 caused from five aspects, including energy consumption structure, energy consumption intensity, industrial structure, economic development and population size, are quantitatively analyzed. The results indicated that: (1) The carbon emissions had shown a sustained growth trend in the B-T-H region on the whole, while the growth rates varied in the three areas. In detail, Hebei Province got the first place in carbon emissions growth, followed by Tianjin and Beijing; (2) economic development was the main driving force for the carbon emissions growth of energy consumption in B-T-H region. Energy consumption structure, population size and industrial structure promoted carbon emissions growth as well, but their effects weakened in turn and were less obvious than that of economic development; (3) energy consumption intensity had played a significant inhibitory role on the carbon emissions growth; (4) it was of great significance to ease the carbon emission-reduction pressure of the B-T-H region from the four aspects of upgrading industrial structure adjustment, making technological progress, optimizing the energy structure and building long-term carbon-emission-reduction mechanisms, so as to promote the coordinated low-carbon development.

Suggested Citation

  • Yi Liang & Dongxiao Niu & Weiwei Zhou & Yingying Fan, 2018. "Decomposition Analysis of Carbon Emissions from Energy Consumption in Beijing-Tianjin-Hebei, China: A Weighted-Combination Model Based on Logarithmic Mean Divisia Index and Shapley Value," Sustainability, MDPI, vol. 10(7), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:7:p:2535-:d:158841
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    References listed on IDEAS

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    Cited by:

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    2. Qifan Guan, 2023. "Decomposing and Decoupling the Energy-Related Carbon Emissions in the Beijing–Tianjin–Hebei Region Using the Extended LMDI and Tapio Index Model," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    3. Xiaodan Wang & Zhengyu Yang, 2019. "Application of Fuzzy Optimization Model Based on Entropy Weight Method in Atmospheric Quality Evaluation: A Case Study of Zhejiang Province, China," Sustainability, MDPI, vol. 11(7), pages 1-19, April.
    4. Li Wang & Jie Pei & Jing Geng & Zheng Niu, 2019. "Tracking the Spatial–Temporal Evolution of Carbon Emissions in China from 1999 to 2015: A Land Use Perspective," Sustainability, MDPI, vol. 11(17), pages 1-27, August.

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