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Spatial–Temporal Difference of Urban Carbon Budget and Carbon Compensation Optimization Partition from the Perspective of Spatial Planning

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  • Haifeng Yang

    (Research Institute of Climatic and Environmental Governance, School of Geographic Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Institute for Disaster Risk Management, School of Geographic Science, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Guofang Zhai

    (School of Architecture and Urban Planning, Nanjing University, Nanjing 210044, China)

  • Yifu Ge

    (School of Architecture and Urban Planning, Nanjing University, Nanjing 210044, China)

  • Tong Jiang

    (Research Institute of Climatic and Environmental Governance, School of Geographic Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Institute for Disaster Risk Management, School of Geographic Science, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Buda Su

    (Research Institute of Climatic and Environmental Governance, School of Geographic Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Institute for Disaster Risk Management, School of Geographic Science, Nanjing University of Information Science and Technology, Nanjing 210044, China)

Abstract

Spatial planning, recognized as a systematic policy instrument for regional development and governance, plays a crucial role in achieving carbon peak and carbon neutrality. This study establishes a framework for carbon sources/sinks estimation and carbon compensation optimization and conducts empirical research in a representative coal resource-based city. We analyzed the spatial–temporal distribution characteristics of net carbon emissions in Huaibei from 2006 to 2020 using a spatial correlation model and an improved Carnegie–Ames–Stanford approach (CASA). Then, we applied the normalized revealed comparative advantage (NRCA) index and the SOM-K-means clustering model to categorize the carbon pattern into payment, balance, and compensation areas. These areas were further integrated with the “Three-zones and Three-lines” to reclassify nine spatial partition optimization types. Finally, we proposed a targeted emission reduction and sink enhancement optimization scheme. We found that urban carbon emissions and carbon sinks exhibit a significant mismatch, with the net carbon emission intensity reaching 166.76–383.27 t·hm −2 from 2006 to 2020, showing a rapid increase followed by stabilization. The high-value area, centered in Xiangshan District, exhibits a circularly decreasing spatial characteristic, gradually extending to the central city of Suixi County. In the optimized payment area, the level of the carbon emission contributive coefficient surpasses the ecological support coefficient (3.92 < ECC < 6.04, 2.09 < ESC < 3.58). The optimized space in the balance area type is primarily situated in mining subsidence areas, leading to a lower overall level (0.42 < ECC < 0.57, 0.49 < ESC < 1.13). The optimized space in the compensation area type (2.24 < ECC < 3.25, 4.59 < ESC < 5.69) requires economic or non-economic compensation from the payment area. The study combines the “Three-zones and Three-lines” with the results of carbon compensation to formulate an urban emission reduction and sink enhancement program, which not only helps to consolidate the theory of low-carbon cities but also effectively promotes the realization of the regional carbon peak goal.

Suggested Citation

  • Haifeng Yang & Guofang Zhai & Yifu Ge & Tong Jiang & Buda Su, 2025. "Spatial–Temporal Difference of Urban Carbon Budget and Carbon Compensation Optimization Partition from the Perspective of Spatial Planning," Land, MDPI, vol. 14(2), pages 1-19, February.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:414-:d:1592786
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    References listed on IDEAS

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