IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6724-d1124682.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6724/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/8/6724/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    3. Li, Hao & Zhao, Yuhuan & Qiao, Xiaoyong & Liu, Ya & Cao, Ye & Li, Yue & Wang, Song & Zhang, Zhonghua & Zhang, Yongfeng & Weng, Jianfeng, 2017. "Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models," Energy Economics, Elsevier, vol. 68(C), pages 522-538.
    4. Zhong, Sheng, 2018. "Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD," Energy Policy, Elsevier, vol. 122(C), pages 655-667.
    5. 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.
    6. Wang, Jiqiang & Wang, Ya & Zhang, Shaohui & Fan, Chun & Zhou, Nanqing & Liu, Jinhui & Li, Xin & Liu, Yun & Hou, Xiujun & Yi, Bowen, 2024. "Accounting of aviation carbon emission in developing countries based on flight-level ADS-B data," Applied Energy, Elsevier, vol. 358(C).
    7. Román-Collado, Rocío & Morales-Carrión, Any Viviana, 2018. "Towards a sustainable growth in Latin America: A multiregional spatial decomposition analysis of the driving forces behind CO2 emissions changes," Energy Policy, Elsevier, vol. 115(C), pages 273-280.
    8. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Decomposition of CO2 emissions change from energy consumption in Brazil: Challenges and policy implications," Energy Policy, Elsevier, vol. 39(3), pages 1495-1504, March.
    9. Ang, B.W. & Goh, Tian, 2019. "Index decomposition analysis for comparing emission scenarios: Applications and challenges," Energy Economics, Elsevier, vol. 83(C), pages 74-87.
    10. Xuankai Deng & Yanhua Yu & Yanfang Liu, 2015. "Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011," Energies, MDPI, vol. 8(6), pages 1-22, June.
    11. Zhang, Chenjun & Wu, Yusi & Yu, Yu, 2020. "Spatial decomposition analysis of water intensity in China," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    12. Hasanbeigi, Ali & Price, Lynn & Fino-Chen, Cecilia & Lu, Hongyou & Ke, Jing, 2013. "Retrospective and prospective decomposition analysis of Chinese manufacturing energy use and policy implications," Energy Policy, Elsevier, vol. 63(C), pages 562-574.
    13. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Tracking European Union CO2 emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach," Energy, Elsevier, vol. 73(C), pages 741-750.
    14. Jeong, Kyonghwa & Kim, Suyi, 2013. "LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector," Energy Policy, Elsevier, vol. 62(C), pages 1245-1253.
    15. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    16. Vaninsky, Alexander, 2014. "Factorial decomposition of CO2 emissions: A generalized Divisia index approach," Energy Economics, Elsevier, vol. 45(C), pages 389-400.
    17. Fei Wang & Changjian Wang & Jing Chen & Zeng Li & Ling Li, 2020. "Examining the determinants of energy-related carbon emissions in Central Asia: country-level LMDI and EKC analysis during different phases," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7743-7769, December.
    18. Román-Collado, Rocío & Cansino, José M. & Colinet, María J. & Dugo, Víctor, 2020. "A tool proposal to detect operating anomalies in the Spanish wholesale electricity market," Energy Policy, Elsevier, vol. 142(C).
    19. Duran, Elisa & Aravena, Claudia & Aguilar, Renato, 2015. "Analysis and decomposition of energy consumption in the Chilean industry," Energy Policy, Elsevier, vol. 86(C), pages 552-561.
    20. Ang, B.W. & Goh, Tian, 2016. "Carbon intensity of electricity in ASEAN: Drivers, performance and outlook," Energy Policy, Elsevier, vol. 98(C), pages 170-179.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6724-:d:1124682. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.