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Exploring the Spatiotemporal Heterogeneity of Carbon Emission from Energy Consumption and Its Influencing Factors in the Yellow River Basin

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  • Shumin Zhang

    (Research Institute of Regional Economy, Shandong University of Finance and Economics, Jinan 250014, China)

  • Yongze Lv

    (Research Institute of Regional Economy, Shandong University of Finance and Economics, Jinan 250014, China)

  • Jian Xu

    (Research Institute of Regional Economy, Shandong University of Finance and Economics, Jinan 250014, China)

  • Baolei Zhang

    (College of Geography and Environment, Shandong Normal University, Jinan 250014, China)

Abstract

Scientific estimation and dynamic monitoring on the heterogeneity of carbon emission from energy consumption (CEEC) is the basis for formulating and implementing regional carbon reduction strategies to realize the goal of carbon neutrality and high-quality development. This study analyzes the temporal and spatial differences of CEEC and its driving factors in the Yellow River Basin (YRB) from 2000 to 2018 based on the Log-Mean Divisia Index (LMDI) time decomposition method and the multi-regional (M-R) space decomposition method. The results indicate the following: The amount of CEEC of the YRB increased greatly from 2000 to 2012, and then expressed a convergence trend after 2012, with obvious spatial differences. The economic development is the leading factor that promotes the increase in CEEC in the YRB, energy intensity is the main force for the reduction in CEEC, and their influencing effectiveness varies significantly in different periods and provinces. Spatially, the larger economic development in Shandong, Henan, and Sichuan causes the higher level of CEEC, and the regulation of energy intensity in Shanxi, Ningxia, and Inner Mongolia is important for the reduction in their CEEC. The impact effectiveness of economic structure and energy structure on CEEC in the YRB is relatively weak, and they are potential factors for the reduction in CEEC. Therefore, the corresponding emission reduction measures in nine provinces of the YRB should focus on reducing energy intensity, building a green energy system, and strengthening “green” economic development to achieve high-quality development in the YRB. This study is designed to explore the spatiotemporal variations and influencing factors of carbon emissions in the nine provinces of the YRB, which is of great significance for achieving low-carbon development in the region.

Suggested Citation

  • Shumin Zhang & Yongze Lv & Jian Xu & Baolei Zhang, 2023. "Exploring the Spatiotemporal Heterogeneity of Carbon Emission from Energy Consumption and Its Influencing Factors in the Yellow River Basin," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6724-:d:1124682
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    1. Li-Ming Xue & Shuo Meng & Jia-Xing Wang & Lei Liu & Zhi-Xue Zheng, 2020. "Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective," Sustainability, MDPI, vol. 12(19), pages 1-26, October.
    2. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    3. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    4. Gingrich, Simone & Kusková, Petra & Steinberger, Julia K., 2011. "Long-term changes in CO2 emissions in Austria and Czechoslovakia--Identifying the drivers of environmental pressures," Energy Policy, Elsevier, vol. 39(2), pages 535-543, February.
    5. Shi, Xunpeng & Wang, Keying & Cheong, Tsun Se & Zhang, Hongwu, 2020. "Prioritizing driving factors of household carbon emissions: An application of the LASSO model with survey data," Energy Economics, Elsevier, vol. 92(C).
    6. Sun, J.W., 2000. "An analysis of the difference in CO2 emission intensity between Finland and Sweden," Energy, Elsevier, vol. 25(11), pages 1139-1146.
    7. 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.
    8. Chris Bataille & Nic Rivers & Paulus Mau & Chris Joseph & Jian-Jun Tu, 2007. "How Malleable are the Greenhouse Gas Emission Intensities of the G7 Nations?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 145-170.
    9. Lenzen, Manfred, 1998. "Primary energy and greenhouse gases embodied in Australian final consumption: an input-output analysis," Energy Policy, Elsevier, vol. 26(6), pages 495-506, May.
    10. Ang, B.W. & Mu, A.R. & Zhou, P., 2010. "Accounting frameworks for tracking energy efficiency trends," Energy Economics, Elsevier, vol. 32(5), pages 1209-1219, September.
    11. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    12. Lee, Kihoon & Oh, Wankeun, 2006. "Analysis of CO2 emissions in APEC countries: A time-series and a cross-sectional decomposition using the log mean Divisia method," Energy Policy, Elsevier, vol. 34(17), pages 2779-2787, November.
    13. Li, Li & Chen, Changhong & Xie, Shichen & Huang, Cheng & Cheng, Zhen & Wang, Hongli & Wang, Yangjun & Huang, Haiying & Lu, Jun & Dhakal, Shobhakar, 2010. "Energy demand and carbon emissions under different development scenarios for Shanghai, China," Energy Policy, Elsevier, vol. 38(9), pages 4797-4807, September.
    14. Ang, B. W. & Lee, S. Y., 1994. "Decomposition of industrial energy consumption : Some methodological and application issues," Energy Economics, Elsevier, vol. 16(2), pages 83-92, April.
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    1. Ye Duan & Juanjuan Zhong & Hongye Wang & Caizhi Sun, 2023. "Analysis of the Spatial and Temporal Evolution of Energy-Related CO 2 Emissions in China’s Coastal Areas and the Drivers of Industrial Enterprises above Designated Size—The Case of 82 Cities," Sustainability, MDPI, vol. 15(18), pages 1-18, September.

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