Land use change affects the supply and demand of water, energy and food and the integration of land elements into the common water-energy-food (WEF) nexus, which is an effective way to strictly adhere to the bottom line of natural resources. First, this study used the entropy method and coupling coordination model to measure the coupling coordination degree of the water-energy-land-food (WELF) nexus in 30 provinces in China during the period of 2006–2019. Then, the regional differences and distribution dynamics were examined with the Dagum Gini coefficient and Kernel density estimation, respectively. Finally, the spatial correlation was analyzed using the global Moran’s I, and a spatial β convergence model was constructed to empirically test its spatial β convergence characteristics. The results show that the coupling coordination degree of the WELF nexus in most of the provinces was at the stage of barely coordinated, with a decreasing trend; the intensity of transvariation was the main source of regional differences in the coupling coordination degree of the WELF nexus, followed by intra-regional differences, while inter-regional differences were small. The national, eastern and central regions had a slight gradient effect, showing regional dispersion characteristics, albeit less obvious; there was a spatial absolute-β convergence and spatial conditional-β convergence nationally and in the three regions. On this basis, policy recommendations were made to realize the synergistic development of land planning, water resources allocation, energy utilization, and food production and to balance regional differences in resources.

Introduction: Pollution reduction, carbon reduction, green expansion and economic growth—the synergistic effects of the four—have become essential in maintaining urban ecological security and promoting a green and low-carbon transition. And it is inherently consistent with the globally accepted concept of sustainable development. Methods: Based on the evaluation index system and the coupling mechanism of the four, we adopt the entropy method and the coupling coordination model to measure the synergistic level of “pollution reduction, carbon reduction, green expansion and economic growth” in 243 cities above prefecture level in China from 2005 to 2020. Furthermore, the study examined the temporal and spatial evolution and regional differences by utilizing the center of gravity-standard deviation ellipse, Dagum Gini coefficient method, Kernel density estimation, and Markov chain. In addition, the spatial econometric model was used to analyze the driving factors affecting the synergistic development.Results: The results show that the overall synergistic level is rising, the spatial distribution characteristics of “high in the east and low in the west.” The standard deviation ellipse shows a “northeast–southwest” pattern, and the center of gravity moves in a “southeast–northwest–southwest” migration trend. Regional differences are mainly rooted in inter-regional differences. The intra-regional differences are East > West > Central, with the most prominent East–West inter-regional differences. Without considering the spatial factor, the synergistic level shows a steady increase and has continuity. Under the spatial condition, the synergistic level has a positive spatial correlation. However, the positive spatial correlation decreases significantly as the years go by. Also, the probability of “rank locking” of synergistic development has been reduced, and there is a leapfrog shift. In terms of driving factors, the innovation level, level of external openness, population size, and industrial structure positively drive synergistic development. While government intervention negatively affects synergistic development. Discussions: Based on the above findings,policy recommendations are proposed to strengthen the top-level design and build a policy system, play the radiation linkage, apply precise policies according to local conditions, and optimize the industrial structure fully. Which is of great significance for improving the urban ecological resilience and helping to achieve the “double carbon” target.

Under the urban development trend of sprawl, improving energy use efficiency is a proper way to promote green and low-carbon construction in cities. This paper uses panel data from 283 prefecture-level and above cities in China from 2008 to 2019 to measure the urban sprawl index, and analyze the spatial-temporal evolution law of urban sprawl and electricity consumption. The relationship between urban sprawl and electricity consumption is empirically examined, and the differential effect of urban sprawl on electricity consumption is analyzed. Finally, the impact of urban sprawl on electricity consumption based on a spatial perspective is explored in depth by establishing a spatial error model. We found the following: (1) The levels of urban sprawl and urban electricity consumption are on the rise. The spatial distribution of urban sprawl is more dispersed, and cities with high electricity consumption levels are mostly concentrated in the eastern coastal areas. (2) Urban sprawl exacerbates electricity consumption, and this conclusion is still robust after a series of robustness tests were conducted and endogeneity issues were taken into account. In terms of the influence mechanism, urban sprawl mainly affects electricity consumption by changing the allocation of land resources, increasing the dependence on private transportation, and inhibiting green technology innovation. (3) The incremental effect of urban sprawl on electricity consumption is more pronounced in cities with high sprawl levels, weak environmental regulations, and low green innovation levels, as well as in west cities. (4) Urban sprawl and electricity consumption both have a significant positive spatial correlation. Electricity consumption of cities is not only related to their own regions but also influenced by the adjacent regions, and the spatial correlation is mainly reflected in the random error term. This paper deepens the understanding of the basic laws of urban sprawl affecting urban low-carbon development, which also has implications for new urbanization strategies and green development.

Exploring the effect of new-type urbanization (NTU) on urban carbon abatement is of great practical significance for promoting urban green construction and coping with the challenge of global climate change. This study used data from 250 cities in China from 2008 to 2020 and constructed the NTU evaluation indicator system from five dimensions. We used classical panel regression models to examine the effects of NTU on urban CO₂ emissions, and further used spatial econometric models of SEM, SAR, and SDM to identify the spatial spillover effects of NTU on urban CO₂ emissions. The main results are that China’s NTU and CO₂ emissions are generally rising, and NTU has a significantly negative effect on urban CO₂ emissions, with an impact coefficient of −0.9339; the conclusions still hold after subsequent robustness tests. Heterogeneity analysis reveals that NTU’s carbon abatement effect is more pronounced in resource-based cities, old industrial areas, and cities with lower urbanization levels and higher innovation levels. Mechanism analysis shows that improving urban technological innovation and optimizing resource allocation are important paths for realizing urban CO₂ emission reduction. NTU’s effect on urban CO₂ emissions has a noticeable spatial spillover. Our findings provide policy makers with solid support for driving high-quality urban development and dual-carbon targets.

Within the “dual carbon” framework, sustainable agriculture is pivotal for climate change mitigation and long-term agricultural health. To explore the environmental effects of agricultural trade, this study assesses the carbon emissions from agriculture using information from 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan due to a lack of available data) from 2001 to 2021. Then, we analyzed the impact of agricultural trade on agricultural carbon emissions and tested for the possible existence of mechanisms. Finally, we validate the synergistic effects of agricultural trade on pollution and carbon abatement. The findings were as follows: (1) Agricultural trade significantly suppresses agricultural carbon emissions. (2) Agricultural technological progress and the rationalization of the structure of the agricultural industry are the two influencing mechanisms. (3) The inhibitory effect of agricultural trade on agricultural carbon emissions is more pronounced in southern regions and regions with lower degree of topographic relief and higher agricultural industrial agglomeration. (4) Agricultural trade fosters the collaborative advancement of mitigating agricultural pollution and reducing carbon emissions. As a result, this study confirms that agricultural trade has a role in reducing carbon emissions and that giving full play to the environmental effects of trade in agricultural products contributes to the high-quality development of agriculture.

This paper took the panel data of 1052 heavily-polluting listed companies from both the Shanghai and Shenzhen Stock Exchange from 2010 to 2017 to empirically analyze the impact of environmental regulation (ERG) on firm performance (FP). The article introduces a mediating effect model to test the mediating role of corporate tax burden (ETR) within the relationship between ERG on FP. The results showed that: (1) ERG has exerted a significant enhancement effect on the performance of heavily polluted firms via the ETR reduction mechanism. (2) The mediating effect of ETR depends on the duration of ERG. A significant time lag exists before the mediating effect starts to work, and the magnitude of the mediating effect increases with the time lag from the execution of the ERG. (3) The mediating effect of ETR varies significantly with the nature of corporate property rights. It is significant for the state-owned firms, while for non-state-owned firms, there is no evidence supporting the existence of the mediating effect of ETR despite ERG still having a significant direct-impact on FP. Based on these findings, we discuss the policy suggestion to optimize the impact of environmental regulation policies in terms of incentivizing the green development of polluting firms.