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Carbon Emission Intensity Characteristics and Spatial Spillover Effects in Counties in Northeast China: Based on a Spatial Econometric Model

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  • Zhenjun Gao

    (College of Earth Sciences, Jilin University, Changchun 130061, China)

  • Shujie Li

    (College of Earth Sciences, Jilin University, Changchun 130061, China)

  • Xiufeng Cao

    (College of Earth Sciences, Jilin University, Changchun 130061, China)

  • Yuefen Li

    (College of Earth Sciences, Jilin University, Changchun 130061, China)

Abstract

Under the “double carbon” target, it is important to reduce carbon emissions in each region. Using exploratory spatial data analysis (ESDA), the center of gravity method, and spatial econometric models, we analyzed the characteristics and spatial spillover effects of carbon emission intensity in counties in Northeast China from 2000 to 2020 and made recommendations to the government for more reasonable carbon reduction strategies in order to achieve sustainable development. The results were as follows: (1) Since 2000, the carbon emission intensity in Northeast China has increased after first declining, and the carbon emission intensity in the western and northern regions of Northeast China has increased faster than Northeast China’s average. (2) After 2000, the spatial aggregation of carbon emission intensity has improved in Northeast China. (3) Northeast China’s carbon emission intensity has a positive spatial spillover effect. Through the feedback mechanism, the growth in population size, the rise in economic development level, the level of industrialization as well as the rise in living standard, the land use structure dominated by arable land and construction land, and the increase in urbanization level in the region will cause the carbon emission intensity in the surrounding areas to increase. An increase in public expenditures leads to a decrease in carbon emission intensity in the adjacent area. (4) When the vegetation cover exceeds its threshold value, it can have a larger inhibitory influence on carbon emission intensity. To summarize, each county in Northeast China is a carbon emission reduction community, and policymakers must consider the spatial spillover effect of carbon emission intensity when developing policies.

Suggested Citation

  • Zhenjun Gao & Shujie Li & Xiufeng Cao & Yuefen Li, 2022. "Carbon Emission Intensity Characteristics and Spatial Spillover Effects in Counties in Northeast China: Based on a Spatial Econometric Model," Land, MDPI, vol. 11(5), pages 1-19, May.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:5:p:753-:d:820168
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    References listed on IDEAS

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    Cited by:

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    2. Tianyi Zeng & Hong Jin & Xu Gang & Zihang Kang & Jiayi Luan, 2022. "County Economy, Population, Construction Land, and Carbon Intensity in a Shrinkage Scenario," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    3. Zhichao Li & Bojia Liu, 2023. "Understanding Carbon Emissions Reduction in China: Perspectives of Political Mobility," Land, MDPI, vol. 12(4), pages 1-18, April.
    4. 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.
    5. Qing Wang & Yuhang Xiao, 2022. "Has Urban Construction Land Achieved Low-Carbon Sustainable Development? A Case Study of North China Plain, China," Sustainability, MDPI, vol. 14(15), pages 1-29, August.
    6. Luo, Haizhi & Wang, Chenglong & Li, Cangbai & Meng, Xiangzhao & Yang, Xiaohu & Tan, Qian, 2024. "Multi-scale carbon emission characterization and prediction based on land use and interpretable machine learning model: A case study of the Yangtze River Delta Region, China," Applied Energy, Elsevier, vol. 360(C).
    7. Jie He & Jun Yang, 2023. "Spatial–Temporal Characteristics and Influencing Factors of Land-Use Carbon Emissions: An Empirical Analysis Based on the GTWR Model," Land, MDPI, vol. 12(8), pages 1-23, July.

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