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Facilitating the coordinated and effective progress of green finance (GF) and ecological efficiency (EE) stands as a potent approach to support our nation in attaining sustainable development goals. This paper Utilized panel data encompassing 84 cities in Western China spanning from 2007 to 2021, this paper empirically analyzes the spatio-temporal characteristics and driving factors of the coupling coordination degree between green finance and ecological efficiency (CCD-GFEE) in western cities. The findings indicate that: (1) The level of GF demonstrates a rising trajectory, with significant regional disparities. Besides, the high level area progressively moves from the northwest to the southwest. (2) On the whole, urban EE demonstrates a relatively elevated level, but it still fails to reach DEA effectiveness. Compared to the northwest region, the southwest region has poorer efficiency. (3) The CCD-GFEE in western China showing a slight growth trend. The coupling coordination degree (CCD) in Northwest China is higher than that in Southwest China, and cities with higher CCD are primarily found in Inner Mongolia, Sichuan Province and Shaanxi Province. Within them, the CCD of Chengdu is the highest, Chongqing has achieved the largest stage leap. (4) The global Moran’s I consistently remained positive and exhibited a tendency of initially rising and subsequently falling, indicating that the spatial aggregation effect of CCD-GFEE first increased and then decreased. (5) The CCD-GFEE driving factors are examined using the spatial econometric model, and it has been observed that the impact of population size and government intervention on CCD-GFEE is negative, while the impact of industrial structure, technological progress and economic level on the coupling and coordination of CCD-GFEE is positive. Finally, the paper presents certain policy enlightenments to guide the coordinated development of GF and EE from the aspects of GF system formulation, economic construction and technological progress.

In this study, an EIORES-DEA high-quality development indicator system based on efficiency was constructed by selecting multiple indicators from six aspects: economic development, innovation vitality, openness to the outside world, resource utilization, ecological security, and social progress. The weights of the indicators were determined via the entropy weighting method, and the high-quality development (HQD) efficiency of 38 districts and counties in Chongqing municipality from 2010 to 2021 was measured by the Super epsilon-based measure (EBM) model. The spatial and temporal evolutions of efficiency were visualized by combining GIS technology, and the spatial pattern of the HQD level was determined using the LISA time path. The spatial aggregation characteristics of efficiency were revealed utilizing Moran’s I index and spatial trend surface analysis. The results showed that the HQD level in Chongqing rose in an N-shaped fluctuation, and the HQD level in the central city was much higher than that in the new main city, southeast Chongqing, and northeast Chongqing. The high-efficiency (H-efficiency) regions were not connected together but rather distributed independently, with most of the medium–high-efficiency districts and counties distributed around the H-efficiency districts and counties. Meanwhile, the H–H agglomeration area had frequent turnovers in different years, indicating that the competition between H-efficiency districts and counties is intense and that the development synergy among them is poor, while the L–L agglomeration area fluctuated greatly in a given year but gradually stabilized in recent years. The spatial trajectory of HQD in Chongqing municipality mainly moved back and forth along the southwest–northeast direction, which is consistent with the direction of the Yangtze River. Finally, the imbalance of HQD development in Chongqing municipality mainly stems from the regional east–west development differences.

The relationship between urbanization and the ecological environment has received increasing attention worldwide. Studying the coupling and coordination relationship between urbanization and the ecological environment is conducive to resolving the contradiction between development and environmental protection. This paper focuses on cities in western China, which are characterized by ecological vulnerability and delayed urbanization. By introducing spatiotemporal exploratory data analysis methods and spatial econometric models, the paper systematically explores the spatiotemporal evolution characteristics of the coupling coordination degree (CCD) between ecological efficiency (EE) and new urbanization (NU) and identifies possible spatial effect issues related to CCD. Time series changes show that the CCD between EE and NU in western Chinese cities has generally shifted from the Little Imbalance stage to the primary coordination level. By the end of the observation period, all cities in the study area—except Chongqing—had reached the bare coordination level or higher. Spatial evolution reveals a significant and stable positive agglomeration effect in the spatial distribution of CCD. The coupling and coordinated development of EE and NU in local cities tends to drive coordination between the two systems in neighboring cities. In addition, through spatial econometric models, it was found that economic development, educational investment, and technological progress promote the CCD between NU and EE within a city, while industrial structure and financial development hinder CCD. At the same time, a city’s educational investment and industrial structure have positive spillover effects on the CCD of neighboring cities. These findings have reference value for the scientific advancement of urbanization and the balance between EE and NU.

For a long time, China ’s extensive economic development model has produced a large amount of emissions, which has brought indelible damage to the environment. Green development is of vital importance for China to achieve high-quality development, and it is the core of alleviating environmental problems and promoting sustainable development. How to achieve China ’s green development requires us to evaluate the level of green development in China ’s provinces and analyze the reasons. In this study, an evaluation index system including undesired output of green development efficiency is constructed, and then the Supe-SBM model is used to assess the green development efficiency of 30 Chinese provinces. This paper also discusses the spatial and temporal differences as well as the factors affecting green development efficiency of green development efficiency among provinces. The findings demonstrate: (1) The green development efficiency in the eastern region is the highest, followed by the western region, while the central region has the lowest, but they all show a downward trend. (2) The spatial characteristics of green development efficiency are remarkable, according to the Global Moran’s I index. However, the results of local spatial agglomeration demonstrate \"small agglomeration and large dispersion,\" with the majority of provinces exhibiting L-L agglomeration. (3) Technological Progress, Opening Up, Urbanization Level are positively correlated with the green development efficiency. Industrial Structure, Financial Development, Energy Structure and green development efficiency are significantly negatively correlated, while Environmental Regulation shows no significant impact.

China’s rapid urbanization has had a tremendous impact on the country’s limited land resources, and one of the major issues of green development is how to utilize the limited land resources to maximize social, economic, and environmental advantages. From 2005 to 2019, the super epsilon-based measure model (EBM) was employed to assess the green land use efficiency of 108 prefecture-level and above cities in the Yangtze River Economic Belt (YREB), as well as investigate its spatial and temporal evolution and influential factors. The findings demonstrate that overall, urban land green use efficiency (ULGUE) in the YREB has been ineffective; in terms of city scale, megacities have the highest efficiency, followed by large cities and small and medium-sized cities; and at the regional level, downstream efficiency does have the greatest average value, followed by upstream efficiency and middle efficiency. The results of temporal and spatial evolution reveal that the number of cities with a high ULGUE is increasing in general but that their spatial characteristics are relatively dispersed. Population density, environmental regulation, industrial structure, technology input, and the intensity of urban land investment all have major beneficial effects on ULGUE, whereas urban economic development level and urban land use scale clearly have inhibitory effects. In light of the previous conclusions, some recommendations are made to continuously improve ULGUE.

Effectively utilizing water resources, which is a fundamental natural resource and a vital economic resource, directly impacts how a country’s economy develops. In this study, the Super-SBM model is used to calculate the city water resource green efficiency (CWRGE) of the Yangtze River Economic Belt (YREB), 108 cities that are prefecture level or higher, from 2006 to 2021. And its temporal and spatial evolution as well as its affecting variables are examined. The results indicate that, as a whole, the YREB’s CWRGE has not yet achieved an effective level. The CWRGE in the YREB generally exhibits a trend of “first decreasing and then increasing, then decreasing and then increasing” and shows a “W”-shaped evolution law, and the overall trend is upward. There are just seven cities with effective data envelopment analysis (DEA), namely Changzhou, Hangzhou, Shanghai, Xuzhou, Changde, Changsha, and Yuxi. During the reporting period, the CWRGE of cities of various scales showed significant gaps: mega cities > big cities > small and medium-sized cities. From a regional perspective, the highest rate of CWRGE was found downstream of the YREB cities, then upstream, and the middle was the lowest. Spatial correlation findings demonstrated that both the agglomeration range and the outlier range were distributed, and there were mainly two positive aggregations of space forms (“high-high (H-H) type” and “low-low (L-L) type”), and the spatial distribution changed. The results of the spatiotemporal evolution demonstrate that there are more and more cities with high efficiency, as well as cities with low efficiency. From the results of the Tobit regression model, the CWRGE in the YREB are significantly improved by the economical development level, industrial scale, and water usage structure. While foreign direct investment and environmental regulation have considerable detrimental impacts, the impact of scientific and technological investment is not significant.

With the proposal of the “carbon peak, carbon neutral“ goal, energy efficiency has become one of the key means to achieve energy conservation and emission reduction at this stage. The construction industry, as a cornerstone of China’s economy, is characterized by serious overcapacity, energy waste, and pollution. As a result, academic research on its energy efficiency is gaining traction. This paper employed the Super-EBM model considering undesirable output to evaluate the green total-factor energy efficiency of the construction industry (CIGTFEE) in the Yangtze River Economic Belt (YREB) from 2003 to 2018. The spatial-temporal evolution characteristics and spatial heterogeneity of CIGTFEE were analyzed in detail through geospatial analysis. Finally, the driving factors of CIGTFEE were analyzed through a spatial econometric model. The results indicated that, during the sample research period, the CIGTFEE showed a holistic growth trend with volatility. By region, the downstream CIGTFEE grew sharply until 2006 and then remained fairly stable, while the midstream conformed to the “M” trend and the upstream region showed an inverted u-shaped trend; From the perspective of spatial differentiation, the CIGTFEE in YREB shows a significant spatial agglomeration situation, while the spatial agglomeration degree weakened. It existed a ladder-shaped change trend, with the regional average CIGTFEE from high to low levels as follows: Downstream, Midstream, and Upstream, and showed an obvious polarization in the upstream and downstream. From the analysis of the driving factors, CIGTFEE is significantly promoted by economic growth, energy structure, and human capital and suppressed by urbanization level, yet the impact of technological progress and the level of technology and equipment is not significant. In summary, province-specific policies based on spatial and temporal heterogeneity were proposed to improve the CIGTFEE of YREB.