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Decomposition Analysis and Trend Prediction of Energy-Consumption CO 2 Emissions in China’s Yangtze River Delta Region

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  • Yue Yuan

    (Graduate School of Fisheries and Environmental Sciences, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521, Japan)

  • Sunhee Suk

    (Graduate School of Fisheries and Environmental Sciences, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521, Japan)

Abstract

This study calculated CO 2 emissions related to the consumption of primary energy by five sectors in the Yangtze River Delta region over 2000 to 2019. The Logarithmic Mean Divisia Index (LMDI) decomposition method was used to establish the factor decomposition model of CO 2 emissions change. The LMDI model was modified to assess the impact of five influencing factors, namely energy structure, energy intensity, industrial structure, economic output, and population size, on CO 2 emissions in the Yangtze River Delta region over the study period. The empirical results show that economic output has the largest positive effect on the growth in CO 2 emissions. Population size is the second most important factor promoting the growth in CO 2 emissions. Energy intensity is the most inhibitory factor to restrain CO 2 emissions, with a significant negative effect. Energy structure and industrial structure contribute insignificantly to CO 2 emissions. Using data on CO 2 emissions in the Yangtze River Delta region from 2000 to 2019, the GM (1, 1) model was applied for future forecasts of primary energy consumption and CO 2 emissions. Specific policy suggestions to mitigate CO 2 emissions in Yangtze River Delta region are provided.

Suggested Citation

  • Yue Yuan & Sunhee Suk, 2023. "Decomposition Analysis and Trend Prediction of Energy-Consumption CO 2 Emissions in China’s Yangtze River Delta Region," Energies, MDPI, vol. 16(11), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4510-:d:1163463
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    References listed on IDEAS

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    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. Chong, ChinHao & Ma, Linwei & Li, Zheng & Ni, Weidou & Song, Shizhong, 2015. "Logarithmic mean Divisia index (LMDI) decomposition of coal consumption in China based on the energy allocation diagram of coal flows," Energy, Elsevier, vol. 85(C), pages 366-378.
    3. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    4. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    5. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    6. Wang, Can & Chen, Jining & Zou, Ji, 2005. "Decomposition of energy-related CO2 emission in China: 1957–2000," Energy, Elsevier, vol. 30(1), pages 73-83.
    7. Zhang, Ming & Li, Huanan & Zhou, Min & Mu, Hailin, 2011. "Decomposition analysis of energy consumption in Chinese transportation sector," Applied Energy, Elsevier, vol. 88(6), pages 2279-2285, June.
    8. Zhang, Wei & Li, Ke & Zhou, Dequn & Zhang, Wenrui & Gao, Hui, 2016. "Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method," Energy Policy, Elsevier, vol. 92(C), pages 369-381.
    9. Xu, Shi-Chun & He, Zheng-Xia & Long, Ru-Yin, 2014. "Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI," Applied Energy, Elsevier, vol. 127(C), pages 182-193.
    10. Wang, W.W. & Zhang, M. & Zhou, M., 2011. "Using LMDI method to analyze transport sector CO2 emissions in China," Energy, Elsevier, vol. 36(10), pages 5909-5915.
    11. Pao, Hsiao-Tien & Fu, Hsin-Chia & Tseng, Cheng-Lung, 2012. "Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model," Energy, Elsevier, vol. 40(1), pages 400-409.
    12. Xu, Jin-Hua & Fleiter, Tobias & Eichhammer, Wolfgang & Fan, Ying, 2012. "Energy consumption and CO2 emissions in China's cement industry: A perspective from LMDI decomposition analysis," Energy Policy, Elsevier, vol. 50(C), pages 821-832.
    13. Liu, Lan-Cui & Fan, Ying & Wu, Gang & Wei, Yi-Ming, 2007. "Using LMDI method to analyze the change of China's industrial CO2 emissions from final fuel use: An empirical analysis," Energy Policy, Elsevier, vol. 35(11), pages 5892-5900, November.
    14. Zhao, Min & Tan, Lirong & Zhang, Weiguo & Ji, Minhe & Liu, Yuan & Yu, Lizhong, 2010. "Decomposing the influencing factors of industrial carbon emissions in Shanghai using the LMDI method," Energy, Elsevier, vol. 35(6), pages 2505-2510.
    15. Wu, Lifeng & Liu, Sifeng & Liu, Dinglin & Fang, Zhigeng & Xu, Haiyan, 2015. "Modelling and forecasting CO2 emissions in the BRICS (Brazil, Russia, India, China, and South Africa) countries using a novel multi-variable grey model," Energy, Elsevier, vol. 79(C), pages 489-495.
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