IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i24p8052-d1299757.html
   My bibliography  Save this article

Decomposition Analysis of Regional Electricity Consumption Drivers Considering Carbon Emission Constraints: A Comparison of Guangdong and Yunnan Provinces in China

Author

Listed:
  • Haobo Chen

    (Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
    Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Shangyu Liu

    (Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Yaoqiu Kuang

    (School of Environment, Jinan University, Guangzhou 511486, China)

  • Jie Shu

    (Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Zetao Ma

    (Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China)

Abstract

Electricity consumption is closely linked to economic growth, social development, and carbon emissions. In order to fill the gap of previous studies on the decomposition of electricity consumption drivers that have not adequately considered carbon emission constraint, this study constructs the Kaya extended model of electricity consumption and analyzes the effects of drivers in industrial and residential sectors using the Logarithmic Mean Divisia Index (LMDI) method, and empirically explores the temporal and spatial differences in electricity consumption. Results show that: (1) During 2005–2021, the total final electricity consumption growth in Guangdong was much higher than that in Yunnan, but the average annual growth rate in Guangdong was lower, and the largest growth in both provinces was in the industrial sector. (2) The labor productivity level effect is the primary driver that increases total final electricity consumption (Guangdong: 78.5%, Yunnan: 87.1%), and the industrial carbon emission intensity effect is the primary driver that decreases total final electricity consumption (Guangdong: −75.3%, Yunnan: −72.3%). (3) The year-to-year effect of each driver by subsector is overall positively correlated with the year-to-year change in the corresponding driver, and declining carbon emission intensity is a major factor in reducing electricity consumption. (4) The difference in each effect between Guangdong and Yunnan is mainly determined by a change in the corresponding driver and subsectoral electricity consumption. Policy implications are put forward to promote energy conservation and the realization of the carbon neutrality goal.

Suggested Citation

  • Haobo Chen & Shangyu Liu & Yaoqiu Kuang & Jie Shu & Zetao Ma, 2023. "Decomposition Analysis of Regional Electricity Consumption Drivers Considering Carbon Emission Constraints: A Comparison of Guangdong and Yunnan Provinces in China," Energies, MDPI, vol. 16(24), pages 1-25, December.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:8052-:d:1299757
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/24/8052/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/24/8052/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Jiandong & Wang, Ping & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2018. "Decomposition and decoupling analysis of CO2 emissions in OECD," Applied Energy, Elsevier, vol. 231(C), pages 937-950.
    2. Huang, Yun-Hsun, 2020. "Examining impact factors of residential electricity consumption in Taiwan using index decomposition analysis based on end-use level data," Energy, Elsevier, vol. 213(C).
    3. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    4. H. Wang & B.W. Ang & P. Zhou, 2018. "Decomposing aggregate CO2 emission changes with heterogeneity: An extended production-theoretical approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    5. Yang, Xue & Xu, He & Su, Bin, 2022. "Factor decomposition for global and national aggregate energy intensity change during 2000–2014," Energy, Elsevier, vol. 254(PB).
    6. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
    7. Lin, Boqiang & Raza, Muhammad Yousaf, 2021. "Analysis of electricity consumption in Pakistan using index decomposition and decoupling approach," Energy, Elsevier, vol. 214(C).
    8. Shi, Changfeng & Zhao, Yi & Zhang, Chenjun & Pang, Qinghua & Chen, Qiyong & Li, Ang, 2022. "Research on the driving effect of production electricity consumption changes in the Yangtze River Economic Zone - Based on regional and industrial perspectives," Energy, Elsevier, vol. 238(PA).
    Full references (including those not matched with items on IDEAS)

    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. Dong, Kangyin & Hochman, Gal & Timilsina, Govinda R., 2020. "Do drivers of CO2 emission growth alter overtime and by the stage of economic development?," Energy Policy, Elsevier, vol. 140(C).
    2. Cui, Yin, 2023. "The influencing factors of carrying capacity of urban electricity infrastructure: Case study of six Chinese mega-cities," Energy, Elsevier, vol. 282(C).
    3. Shiraki, Hiroto & Matsumoto, Ken'ichi & Shigetomi, Yosuke & Ehara, Tomoki & Ochi, Yuki & Ogawa, Yuki, 2020. "Factors affecting CO2 emissions from private automobiles in Japan: The impact of vehicle occupancy," Applied Energy, Elsevier, vol. 259(C).
    4. Lizhan Cao & Hui Wang, 2022. "The Slowdown in China’s Energy Consumption Growth in the “New Normal” Stage: From Both National and Regional Perspectives," Sustainability, MDPI, vol. 14(7), pages 1-21, April.
    5. Yun-Hsun Huang & Jung-Hua Wu & Hao-Syuan Huang, 2021. "Analyzing the Driving Forces behind CO 2 Emissions in Energy-Resource-Poor and Fossil-Fuel-Centered Economies: Case Studies from Taiwan, Japan, and South Korea," Energies, MDPI, vol. 14(17), pages 1-14, August.
    6. Huang, Yun-Hsun, 2020. "Examining impact factors of residential electricity consumption in Taiwan using index decomposition analysis based on end-use level data," Energy, Elsevier, vol. 213(C).
    7. Xu, Zhongwen & Tan, Shiqi & Yao, Liming & Lv, Chengwei, 2024. "Exploring water-saving potentials of US electric power transition while thirsting for carbon neutrality," Energy, Elsevier, vol. 292(C).
    8. Raza, Muhammad Yousaf & Wu, Rongxin & Lin, Boqiang, 2023. "A decoupling process of Pakistan's agriculture sector: Insights from energy and economic perspectives," Energy, Elsevier, vol. 263(PC).
    9. Fan, Wei & Li, Li & Wang, Feiran & Li, Ding, 2020. "Driving factors of CO2 emission inequality in China: The role of government expenditure," China Economic Review, Elsevier, vol. 64(C).
    10. Patiño, Lourdes Isabel & Alcántara, Vicent & Padilla, Emilio, 2021. "Driving forces of CO2 emissions and energy intensity in Colombia," Energy Policy, Elsevier, vol. 151(C).
    11. Lin, Boqiang & Xu, Mengmeng, 2019. "Quantitative assessment of factors affecting energy intensity from sector, region and time perspectives using decomposition method: A case of China’s metallurgical industry," Energy, Elsevier, vol. 189(C).
    12. Zhou, Xun & Kuosmanen, Timo, 2020. "What drives decarbonization of new passenger cars?," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1043-1057.
    13. Wang, Zhaojing & Jiang, Qingzhe & Dong, Kangyin & Mubarik, Muhammad Shujaat & Dong, Xiucheng, 2020. "Decomposition of the US CO2 emissions and its mitigation potential: An aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 147(C).
    14. Cosimo Magazzino & Parisa Pakrooh & Mohammad Zoynul Abedin, 2024. "A decomposition and decoupling analysis for carbon dioxide emissions: evidence from OECD countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 28539-28566, November.
    15. Wang, H. & Zhou, P. & Xie, Bai-Chen & Zhang, N., 2019. "Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1096-1107.
    16. Chen, Jiandong & Xu, Chong & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2019. "Driving factors of CO2 emissions and inequality characteristics in China: A combined decomposition approach," Energy Economics, Elsevier, vol. 78(C), pages 589-597.
    17. Tao Lv & Duyang Pi & Xu Deng & Xiaoran Hou & Jie Xu & Liya Wang, 2022. "Spatiotemporal Evolution and Influencing Factors of Electricity Consumption in the Yangtze River Delta Region," Energies, MDPI, vol. 15(5), pages 1-12, February.
    18. Ye Yuan & Yumeng Lu & Jiayi Xie & Jiawei Tao & Xiaowei Chuai & Sihua Huang & Rui Zhang & Jiahao Zhai & Xiaoqing Wang & Lijie Pu, 2025. "Decoupling and decomposition analysis of industrial carbon emissions and economic growth in China from a dynamic perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(2), pages 5159-5181, February.
    19. Xie, Rui & Wang, Fangfang & Chevallier, Julien & Zhu, Bangzhu & Zhao, Guomei, 2018. "Supply-side structural effects of air pollutant emissions in China: A comparative analysis," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 89-95.
    20. Mulder, Peter & de Groot, Henri L.F. & Pfeiffer, Birte, 2014. "Dynamics and determinants of energy intensity in the service sector: A cross-country analysis, 1980–2005," Ecological Economics, Elsevier, vol. 100(C), pages 1-15.

    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:jeners:v:16:y:2023:i:24:p:8052-:d:1299757. 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.