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. 2022 Dec 2;19(23):16149.
doi: 10.3390/ijerph192316149.

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

Jun Fu  1   2 , Rui Ding  1   2   3 , Yilin Zhang  1 , Tao Zhou  1 , Yiming Du  1 , Yuqi Zhu  1   2 , Linyu Du  1   2 , Lina Peng  1   2 , Jian Zou  1   2 , Wenqian Xiao  1   2
Affiliations

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

Jun Fu et al. Int J Environ Res Public Health. .

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.

Keywords: GLUEUL; carbon neutrality; influencing factors; spatial-temporal transition.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Research area.
Figure 2
Figure 2
The time-series changes in the number of areas at different levels of GLUEUL from 2005 to 2020.
Figure 3
Figure 3
The characteristics of the spatial pattern of GLUEUL from 2005 to 2020.
Figure 4
Figure 4
Spatial distribution of LISA time path characteristics of GLUEUL, 2005–2020.
Figure 5
Figure 5
Four-year regression coefficients of EDL.
Figure 6
Figure 6
Four-year regression coefficients of ISU.
Figure 7
Figure 7
Four-year regression coefficients of UPS.
Figure 8
Figure 8
Four-year regression coefficients of FS.
Figure 9
Figure 9
Four-year regression coefficients of FIS.
Figure 10
Figure 10
Four-year regression coefficients of FDL.
Figure 11
Figure 11
Four-year regression coefficients of WL.
Figure 12
Figure 12
Four-year regression coefficients of GTIA.
See this image and copyright information in PMC

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