Green Land Use Efficiency and Influencing Factors of Resource-Based Cities in the Yellow River Basin under Carbon Emission Constraints

Abstract

Green and low-carbon strategies represent governance orientations for resource-based cities to respond to global changes and achieve sustainable development. Designating the Yellow River Basin (YRB), an important ecological functional area and an ecologically fragile area, as the research area, this study used the super-efficiency SBM model while considering undesirable outputs, including carbon emissions, to analyze green land use efficiency (GLUE) and its temporal and spatial differentiation, then used the Tobit regression model to analyze the influencing factors. The results were as follows: (1) The GLUE of the YRB presented a spatial pattern of “high in the west and low in the east”. (2) Overall, the efficiency values of all areas and types increased annually, but differences occurred in various areas and types of resource-based cities. (3) Overall, the efficiency values of the Yellow River Basin showed a “high-low” polarization. (4) Economic development and population growth factors substantially impacted the GLUE of resource-based cities in this region. It is concluded that increasing the efficiency improvement of low-efficiency regions or cities can improve regional GLUE. To ensure regional green and low-carbon transformation and development, it is essential to enhance urban economic vitality, promote an orderly population flow, and strive to improve social and public services.

Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China

“…Increasing carbon emission is an essential issue in urban green development, which explains the inefficiency of some cities with higher levels of economic growth after the introduction of carbon emissions as an undesirable output in this paper. This is also consistent with the findings of Chen et al [111].…”

The Impact of Industrial Agglomeration on Urban Land Green Use Efficiency and Its Spatio-Temporal Pattern: Evidence from 283 Cities in China

“…However, compared to DEA AHP, PCA and factor analysis can only be used to measure a single aspect of input or output, and cannot measure ULGUE from the land use system as a whole. Addressing the patterns, trends, and development of ULGUE over time and space, mainly at the scale of cities, there are Yellow River Basin [20], Yangtze River Economic Belt [21], 284 prefecture-level cities in China [22], etc. Regarding the mainly influencing factors of ULGUE, there are environmental regulations [23], regional integration [24], new urbanization [25], economic development level, urban land intensification, ecological environment, governmental behavior, and social development level [26], etc.…”

The Influence of Environmental Protection Tax Law on Urban Land Green Use Efficiency in China: The Nonlinear Moderating Effect of Tax Rate Increase

“…Based on traditional land use efficiency measurement, the measurement of LGUE considers the environmental loss during the land use process and incorporates unexpected outputs into the model. In order to comprehensively reflect the urban LGUE, with reference to Chen et al (2022) [56], this paper selects nine indicators to construct the evaluation index system of urban LGUE (Table 1). [57], regional economic development (Lngdp) is determined by the natural logarithm of per capita GDP of a prefecture-level city.…”