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Study on the Spatial and Temporal Differentiation Pattern of Carbon Emission and Carbon Compensation in China’s Provincial Areas

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  • Hequ Huang

    (College of Geographical Science, Harbin Normal University, Harbin 150025, China
    Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China)

  • Jia Zhou

    (College of Geographical Science, Harbin Normal University, Harbin 150025, China
    Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China)

Abstract

Excessive carbon emissions lead to global warming, which has attracted widespread attention in the global society. Carbon emissions and land use are closely related. An analysis of land use carbon emissions and carbon fairness can provide guidance for the formulation of energy conservation and emission reduction policies. This study uses data on agricultural production activities, land use and energy consumption and uses the carbon emission coefficient method to calculate carbon emissions and carbon absorption. The tendency value is used to analyze trends in land use carbon emissions and carbon absorption. The Gini coefficient, ecological support coefficient and economic contributive coefficient are used to analyze the fairness and difference of carbon emissions. The results showed that: (1) During the study period, there were fewer provinces with rapid growth in carbon emissions and carbon absorption and more provinces with slow growth. (2) Cultivated land and woodland are the main carriers of land use carbon absorption, and most provinces steadily maintain the type of carbon absorption to which they belong. (3) Carbon emissions from construction land are the main source of total carbon emissions, and the high concentration areas of carbon emissions are mainly located in the more economically developed areas. (4) There are obvious regional differences in the net carbon emissions. By 2015, Shanxi–Shandong High–High agglomeration areas and Yunnan–Guangxi Low–Low agglomeration areas were finally formed. (5) The distribution of carbon emissions in different provinces is not fair, and the spatial distribution is obviously different. Based on the analysis results, relevant suggestions are made from the perspectives of carbon emission reduction and carbon sink enhancement.

Suggested Citation

  • Hequ Huang & Jia Zhou, 2022. "Study on the Spatial and Temporal Differentiation Pattern of Carbon Emission and Carbon Compensation in China’s Provincial Areas," Sustainability, MDPI, vol. 14(13), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7627-:d:845209
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    References listed on IDEAS

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    1. Ahmed Laamrani & Paul R. Voroney & Adam W. Gillespie & Abdelghani Chehbouni, 2021. "Development of a Land Use Carbon Inventory for Agricultural Soils in the Canadian Province of Ontario," Land, MDPI, vol. 10(7), pages 1-20, July.
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    3. Fan, Jianshuang & Zhou, Lin & Zhang, Yan & Shao, Shuai & Ma, Miao, 2021. "How does population aging affect household carbon emissions? Evidence from Chinese urban and rural areas," Energy Economics, Elsevier, vol. 100(C).
    4. Zhao, Jun & Shahbaz, Muhammad & Dong, Xiucheng & Dong, Kangyin, 2021. "How does financial risk affect global CO2 emissions? The role of technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
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    Cited by:

    1. Hui Wen & Yi Li & Zirong Li & Xiaoxue Cai & Fengxia Wang, 2022. "Spatial Differentiation of Carbon Budgets and Carbon Balance Zoning in China Based on the Land Use Perspective," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    2. Jia Peng & Xianli Hu & Xinyue Fan & Kai Wang & Hao Gong, 2023. "The Impact of the Green Economy on Carbon Emission Intensity: Comparisons, Challenges, and Mitigating Strategies," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    3. Zhenhua Wu & Linghui Zhou & Yabei Wang, 2022. "Prediction of the Spatial Pattern of Carbon Emissions Based on Simulation of Land Use Change under Different Scenarios," Land, MDPI, vol. 11(10), pages 1-19, October.

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