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Decomposition and Decoupling Analysis of CO 2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China

Author

Listed:
  • Lele Xin

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education/School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

  • Junsong Jia

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education/School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

  • Wenhui Hu

    (Centre de Recherche Sur Madagascar, Foreign Languages College, Jiangxi Normal University, Jiangxi Normal University, Nanchang 330022, China)

  • Huiqing Zeng

    (School of Resources Environmental and Chemical Engineering, Nanchang University, Nanchang 330031, China)

  • Chundi Chen

    (School of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Bo Wu

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education/School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

Abstract

Currently, little attention has been paid to reducing carbon dioxide (CO 2 ) emissions of Gansu, and the two-dimensional decoupling model has been rarely used to study the relationship between the economic development and CO 2 emissions, especially in western China (e.g., Gansu). Thus, here, we first used the Logarithmic Mean Divisia Index (LMDI) to decompose the driving factors of Gansu’s CO 2 emissions between 2000–2017 and then analyzed the decoupling relationship by using the two-dimensional model. Results showed: (1) Gansu’s CO 2 emissions increased from 7805.70 × 10 4 t in 2000 to 19,896.05 × 10 4 t in 2017. The secondary industry accounted for the largest proportion in Gansu’s CO 2 emissions, followed by the tertiary industry and the primary industry. (2) The economic output showed the dominant driving effect on Gansu’s CO 2 emissions growth with the cumulative contribution rate of 201.94%, followed by the effects of industrial structure, population size, and energy structure, and their cumulative contribution rates were 9.68%, 7.81%, and 3.05%, respectively. In contrast, the energy intensity effect presented the most obvious mitigating effect with the cumulative contribution rate of −122.49%. (3) The Environmental Kuznets Curve (EKC) between CO 2 emissions and economic growth was demonstrated the inverted U-shape in Gansu. The two-dimensional decoupling status was the low level-weak decoupling (WD-LE) during 2000–2017. Thus, dropping the proportion of the secondary industry, reducing the use of carbon-intensive fuel like coal, introducing advanced technologies, and increasing the investment of new energy might effectively restrain the growth of Gansu’s CO 2 emissions.

Suggested Citation

  • Lele Xin & Junsong Jia & Wenhui Hu & Huiqing Zeng & Chundi Chen & Bo Wu, 2021. "Decomposition and Decoupling Analysis of CO 2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China," IJERPH, MDPI, vol. 18(11), pages 1-20, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:6013-:d:568254
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    References listed on IDEAS

    as
    1. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    2. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    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. Shiqing Zhang & Jianwei Wang & Wenlong Zheng, 2018. "Decomposition Analysis of Energy-Related CO 2 Emissions and Decoupling Status in China’s Logistics Industry," Sustainability, MDPI, vol. 10(5), pages 1-21, April.
    5. Fayyaz Ahmad & Muhammad Umar Draz & Lijuan Su & Ilhan Ozturk & Abdul Rauf, 2018. "Tourism and Environmental Pollution: Evidence from the One Belt One Road Provinces of Western China," Sustainability, MDPI, vol. 10(10), pages 1-22, September.
    6. Yu Hao & Zirui Huang & Haitao Wu, 2019. "Do Carbon Emissions and Economic Growth Decouple in China? An Empirical Analysis Based on Provincial Panel Data," Energies, MDPI, vol. 12(12), pages 1-15, June.
    7. Rauf, Abdul & Zhang, Jin & Li, Jinkai & Amin, Waqas, 2018. "Structural changes, energy consumption and carbon emissions in China: Empirical evidence from ARDL bound testing model," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 194-206.
    8. Geng, Yong & Zhao, Hongyan & Liu, Zhu & Xue, Bing & Fujita, Tsuyoshi & Xi, Fengming, 2013. "Exploring driving factors of energy-related CO2 emissions in Chinese provinces: A case of Liaoning," Energy Policy, Elsevier, vol. 60(C), pages 820-826.
    9. 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.
    10. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    11. Min Su & Shasha Wang & Rongrong Li & Ningning Guo, 2020. "Decomposition analysis of the decoupling process between economic growth and carbon emission in Beijing city, China: A sectoral perspective," Energy & Environment, , vol. 31(6), pages 961-982, September.
    12. 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.
    13. Li, Aijun & Hu, Mingming & Wang, Mingjian & Cao, Yinxue, 2016. "Energy consumption and CO2 emissions in Eastern and Central China: A temporal and a cross-regional decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 284-297.
    14. Jing-min Wang & Yu-fang Shi & Xue Zhao & Xue-ting Zhang, 2017. "Factors Affecting Energy-Related Carbon Emissions in Beijing-Tianjin-Hebei Region," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-17, July.
    15. Yang Yu & Qiuyue Kong, 2017. "Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1691-1707, September.
    16. Steven J. Davis & Christine Shearer, 2014. "A crack in the natural-gas bridge," Nature, Nature, vol. 514(7523), pages 436-437, October.
    17. Wang, S.S. & Zhou, D.Q. & Zhou, P. & Wang, Q.W., 2011. "CO2 emissions, energy consumption and economic growth in China: A panel data analysis," Energy Policy, Elsevier, vol. 39(9), pages 4870-4875, September.
    18. Zhang, Ming & Mu, Hailin & Ning, Yadong & Song, Yongchen, 2009. "Decomposition of energy-related CO2 emission over 1991-2006 in China," Ecological Economics, Elsevier, vol. 68(7), pages 2122-2128, May.
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