4.6 Article

Measurement and Influencing Factors of Low Carbon Urban Land Use Efficiency-Based on Non-Radial Directional Distance Function

期刊

LAND
卷 11, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/land11071052

关键词

low carbon; low-carbon urban land use efficiency; non-radial directional distance function

资金

  1. National Natural Science Foundation of China [71072066]
  2. Sichuan Soft Science Research Project [2019JDR0345]
  3. Social Science Planning Project of Sichuan Province [SC19TJ026]
  4. Sichuan University [2019hhf-14]

向作者/读者索取更多资源

This study integrates carbon emissions into the evaluation index system of urban land use efficiency and finds that China's low-carbon urban land use efficiency shows a fluctuating development trend and tends to converge. It also indicates that there is still a lot of room for reducing land input and carbon emissions. The study further reveals that land finance, economic level, and population density have positive effects on low-carbon urban land use efficiency, while traffic level has a negative impact.
The development and use of urban land is a major source of carbon emissions. How to reduce carbon emissions in the process of urban land use without harming the economy has become an extremely important issue. This paper integrating carbon emissions into the urban land use efficiency evaluation index system, measures low-carbon urban land use efficiency using a non-radial directional distance function and analyses its spatial and temporal evolution and its influencing factors using a combination of a kernel density estimation method and a Tobit model. The study found that: (1) China's low-carbon urban land use efficiency shows a fluctuating development and tends to converge; (2) there is much room for reducing land input and carbon emissions in China, and in 2016 alone, land input and carbon emissions in the sample could be reduced by 10.38% and 5.31%, respectively; (3) at the national level, land finance, economic level and population density have a positive impact on low-carbon urban land use efficiency, while the traffic level has negative effects, and these effects show regional heterogeneity. Accordingly, the paper proposes corresponding policy recommendations.

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