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Eco-efficiency of arable land utilization (EALU) emphasizes efficient coordination between land use systems and ecosystems. It is therefore of great significance for agricultural sustainability based on the systematic assessment of EALU. This study took carbon emissions and non-point source pollution resulting from arable land utilization into the measurement system of EALU, and a super-SBM model, kernel density estimation and Tobit regression model were used to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019. The results showed that there was an upward trend in EALU in China from 0.4393 in 2000 to 0.8929 in 2019, with an average annual growth rate of 4.01%. At the regional level, the EALU of three categories of grain functional areas generally maintains an increasing trend, with the highest average value of EALU in main grain marketing areas (MGMAs), followed by grain producing and marketing balance areas (GPMBAs) and main grain producing areas (MGPAs). There are obvious differences in EALU among provinces, and the number of provinces with high eco-efficiency has increased significantly, showing a spatial distribution pattern of “block” clustering. In terms of dynamic evolution, kernel density curves reflect the evolution of EALU in China and grain functional areas with different degrees of polarization characteristics. The results of Tobit regression show that natural conditions, financial support for agriculture, science and technology inputs, level of industrialization, agricultural mechanization, and the living standards of farmers are significant factors resulting in regional disparities of EALU. Therefore, this study proposes the implementation of differentiated arable land use/agricultural management strategies to improve the sustainable utilization of arable land.

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Severe land shortage causes a higher demand for domestic and foreign land‐intensive products. As a result, resource utilization, and related environmental issues, will increase in urban areas. To this respect, the analysis of the impact of environmental regulation on urban land use efficiency helps to identify potential points for interventions designed to ensure sustainable land use. This study first introduces a theoretical framework to investigate the micro‐transmission mechanism of environmental regulation on urban land use efficiency. Our profit decision‐making model concludes that the impact of environmental regulation on urban land use efficiency is influenced by changes in the industrial structure. Empirically, our preliminary analysis suggests that in addition to population density, both formal and informal environmental regulation can promote urban land use efficiency, with a significant spatial heterogeneity across the sample regions. Further, this study shows a remarkable double‐threshold relationship between formal environmental regulation and urban land use efficiency in China. We clarify and confirm that environmental regulation promoted urban land use efficiency only when regulation intensity was higher than 0.8612. Environmental regulation increased urban land use efficiency in high‐level industrial rationalization areas, whereas it had the opposite effect in low‐level ones. Furthermore, there was a clear marginal diminishing effect of the impact of environmental regulation on urban land use efficiency when the optimization of the industrial structure was set as a threshold variable.

Unlocking the relationship between regional integration and urban green development efficiency (UGDE) is of great importance for boosting regional high-quality development and promoting sustainable urban development patterns. Although studies have analyzed the spatio-temporal evolution and influencing factors of regional integration and UGDE, the impact of regional integration on UGDE remains untested. In this paper, we construct a conceptual framework to analyze how regional integration can influence UGDE through promoting the factors mobility and optimizing the industrial layout. In addition, we further choose the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), a rapidly growing urban agglomeration in central China, as a case to investigate the spatial spillover effect of regional integration on UGDE from 2003 to 2017. We quantify the UGDE with a random forest model, then estimate the underlying determinants of the UGDE with a spatial Durbin model. Results indicated that (1) the regional integration level and the UGDE index of the UAMRYR and its three sub-urban agglomerations show an increasing trend; (2) for every 1% increase in the level of regional integration, the level of UGDE will increase by 0.8307%; (3) the impact of regional integration on UGDE has obvious regional heterogeneity; while playing a promoting effect in the Wuhan urban agglomeration and the Changsha-Zhuzhou-Xiangtan urban agglomeration, it shows an inhibitory effect in the Poyang Lake urban agglomeration. We conclude that regional integration in agglomeration areas can accelerate the factors flow and optimize the industrial layout for improving UGDE.

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Land finance has consumed a lot of China’s urban land resources while contributing to its economic growth. Urban land expansion, land finance, and economic growth have attracted significant scholarly and social attention. However, the influence mechanisms among them have not yet been fully investigated. Based on a conceptual framework analysis, in this study, the panel unit-root test, system-GMM, panel Granger causality test, impulse-response analysis, and variance decomposition were used to analyze the interactional relationships among urban land expansion, land finance, and economic growth for 30 provinces in mainland China during the period of 2000–2017. The findings show that these three factors interact with each other. Land finance exhibits a positive effect on urban land expansion and economic growth. This result is further supported by the Granger causality tests. Moreover, the VAR Granger causality-test results show a unidirectional causality flowing from urban land expansion to economic growth. The impulse-response analysis also reveals that the responses of urban land expansion to shocks in land finance appear to be positive throughout the 10 periods, which is similar to the reaction of economic growth to shocks in land finance. The result of variance decomposition indicates that the explanatory power of urban land expansion for land finance increased from 0.20% to 1.90%. In contrast, the changes in economic growth made the lowest contributions to urban land expansion and land finance. The latter made the highest contribution to economic growth, with average contribution rate of 65.26%. The findings of this study provide valuable policy implications for China, heading for a high-quality development stage.