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The Spatial-Temporal Transition and Influencing Factors of Green and Low-Carbon Utilization Efficiency of Urban Land in China under the Goal of Carbon Neutralization

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  • Jun Fu

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China
    These authors contributed equally to this work.)

  • Rui Ding

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory Big Data of Statistical Analysis of Guizhou Province, Guiyang 550025, China
    These authors contributed equally to this work.)

  • Yilin Zhang

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Tao Zhou

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yiming Du

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yuqi Zhu

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Linyu Du

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Lina Peng

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Jian Zou

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Wenqian Xiao

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang 550025, China)

Abstract

Urban-land development and utilization is one of the main sources of carbon emissions. Improving the green and low-carbon utilization efficiency of urban land (GLUEUL) under the goal of carbon neutrality is crucial to the low-carbon transition and green development of China’s economy. Combining the concept of green and low-carbon development in urban land use, carbon emissions and industrial-pollution emissions are incorporated into the unexpected outputs of the GLUEUL evaluation system. The super-efficient slacks-based measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method and Geographically and Temporally Weighted Regression (GTWR) model were used to analyze the spatial-temporal transition and the influencing factors of GLUEUL in 282 cities in China from 2005 to 2020. The result shows that: (1) From 2005 to 2020, the green and low-carbon land-utilization efficiency of Chinese cities shows an increasing temporal-evolution trend, but the gap between cities is gradually widening. (2) From the spatial-temporal dynamic characteristics of Local Indicators of Spatial Association (LISA), regions with the highest GLUEUL have strong dynamics and instability, while cities at the lowest level have a relatively stable spatial structure. On the whole, the local-spatial-transfer direction of GLUEUL of each city is stable, with certain path-dependent characteristics. (3) There are differences in the degree of influence and direction of action of different factors on GLUEUL. The economic development level, industrial-structure upgrading, financial support, wealth level, and green-technology-innovation ability have positive effects on overall GLUEUL, with industrial-structure upgrading promoting GLUEUL the most, while urban population size, foreign-investment scale, and financial-development level play a negative role. This study can provide some empirical and theoretical references for the improvement of GLUEUL.

Suggested Citation

  • Jun Fu & Rui Ding & Yilin Zhang & Tao Zhou & Yiming Du & Yuqi Zhu & Linyu Du & Lina Peng & Jian Zou & Wenqian Xiao, 2022. "The Spatial-Temporal Transition and Influencing Factors of Green and Low-Carbon Utilization Efficiency of Urban Land in China under the Goal of Carbon Neutralization," IJERPH, MDPI, vol. 19(23), pages 1-25, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:16149-:d:991729
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    References listed on IDEAS

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