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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

Bibliographic Data

ID15475310
AuthorsJun Fu (0000-0002-4843-9202, Guizhou University of Finance and Economics), Rui Ding (0000-0002-5693-6049, Guizhou University of Finance and Economics, corresponding author), Yilin Zhang (0000-0002-8238-2326, Guizhou University of Finance and Economics), Tao Zhou (0000-0003-1295-8331, Guizhou University of Finance and Economics), Yiming Du (0009-0001-6863-0602, Guizhou University of Finance and Economics), Yuqi Zhu (0000-0002-9155-9306, Guizhou University of Finance and Economics), Linyu Du (Guizhou University of Finance and Economics), Lina Peng (0000-0001-6331-4822, Guizhou University of Finance and Economics), Jian Zou (0000-0002-4127-8688, Guizhou University of Finance and Economics), Wenqian Xiao (0000-0001-8445-6125, Guizhou University of Finance and Economics)
Year2022
Volume19
Issue23
Pages16149-16149
Publication date2022-12-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph192316149
PMID36498222
OpenAlexW4311629895
LanguageEN
Citations received3
References cited39

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

Carbon fibers · Carbon neutrality · China · Civil engineering · Driving factors · Geography · Greenhouse gas · Land use · Spatial heterogeneity · Computer Science · Energy, Environment, Economic Growth · Environmental Science · Land Use and Ecosystem Services · Urban Transport and Accessibility · Ecology

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Unique citing works3
Citations per year1
Citation span2023 - 2024 (2)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 3

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