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Analysis of the Spatial and Temporal Evolution of China’s Energy Carbon Emissions, Driving Mechanisms, and Decoupling Levels

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  • Jingyi Ji

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Chao Li

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Xinyi Ye

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Yuelin Song

    (College of Forestry, Northeast Forestry University, Harbin 150040, China)

  • Jiehua Lv

    (College of Economics and Management, Northeast Forestry University, Harbin 150040, China)

Abstract

Excessive carbon emissions will cause the greenhouse effect and global warming, which is not conducive to environmental protection and sustainable development. In order to realize the goal of “carbon peak and carbon neutrality” as soon as possible, this paper utilizes the methodology provided by the IPCC to measure the carbon emissions and carbon intensity of China’s energy consumption. The classification method of carbon emission and the kernel density function method are used to explore the spatial and temporal evolution of regional carbon emissions. Based on the Log Mean Divided Index (LMDI) method, the drivers of China’s energy carbon emissions are measured. Based on the Tapio index function and the catch-up decoupling model, the decoupling status of Chinese provinces and the development gap with the benchmark provinces are examined. The results show that (1) China’s total energy carbon emissions show a “rising-declining-rising” trend from 2005 to 2021, and reach the first peak in 2013, totaling 1,484,984.406 million metric tons. China’s Hebei, Shanxi, and Shandong provinces have the highest energy carbon emissions. (2) China’s energy carbon emissions are influenced by multiple factors, and the contribution of each factor to energy carbon emissions is in the following order: economic development effect > energy intensity effect > energy structure effect > population size effect. (3) China’s catch-up provinces develop their economies at the expense of the environment and energy consumption.

Suggested Citation

  • Jingyi Ji & Chao Li & Xinyi Ye & Yuelin Song & Jiehua Lv, 2023. "Analysis of the Spatial and Temporal Evolution of China’s Energy Carbon Emissions, Driving Mechanisms, and Decoupling Levels," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15843-:d:1278087
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    References listed on IDEAS

    as
    1. Mesut Doğan & Sutbayeva Raikhan & Nurbossynova Zhanar & Bodaukhan Gulbagda, 2023. "Analysis of Dynamic Connectedness Relationships among Clean Energy, Carbon Emission Allowance, and BIST Indexes," Sustainability, MDPI, vol. 15(7), pages 1-13, March.
    2. Linhe Chen & Yanhong Hang & Quanfeng Li, 2023. "Spatial-Temporal Characteristics and Influencing Factors of Carbon Emissions from Land Use and Land Cover in Black Soil Region of Northeast China Based on LMDI Simulation," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
    3. Doğan, Mesut & Raikhan, Sutbayeva & Zhanar, Nurbossynova & Gulbagda, Bodaukhan, 2023. "Analysis of Dynamic Connectedness Relationships among Clean Energy, Carbon Emission Allowance, and BIST Indexes," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(7), pages 1-13.
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