The question of how to achieve the sustainable development of resource-based cities has been a major concern for the whole world. In response, the Chinese government has introduced the National Sustainable Development Planning of Resource-Based Cities Policy (SDPRP) to address sustainable development issues in resource-based cities. However, few studies have evaluated the environmental effects of the implementation of the SDPRP. Therefore, difference-in-differences (DID) and mediation effect models were applied to investigate the impact of the SDPRP on pollution emission intensity using balanced panel data for 270 prefecture-level cities in China from 2003 to 2018. The statistical results reveal that the SDPRP significantly reduced pollution emission intensity. Robustness test results showed that the conclusions are robust. Furthermore, the inhibitory effect of the SDPRP on pollution emission intensity increased year after year. We also found that the SDPRP can reduce pollution emission intensity by facilitating technological innovation, accelerating digital transformation, and improving human capital level, in which the role of human capital is stronger, while the role of digital transformation is weaker. The heterogeneity results suggest that compared with mature resource-based cities, the SDPRP had a stronger inhibitory effect on the pollution emission intensity in declining resource-based cities. However, the impact of the SDPRP on pollution emission intensities in growing resource-based cities was significant, while it was not significant in regenerative resource-based cities. Similarly, the SDPRP had a significantly greater inhibitory effect on pollution emission intensity in megacities than in large cities, while it increased the pollution emission intensity in small- and medium-sized cities.

This study conducted quasi-natural experiments based on the panel data of 239 prefecture-level cities in China from 2005 to 2017. The difference-in-difference (DID) and mediation effect model are used to test the impact and mechanism of the construction of national eco-industrial demonstration parks (NEDP) on green total factor productivity (GTFP). The results show that: (1) The construction of NEDP has significantly improved the urban GTFP, and the conclusion is still valid after running the robustness test. (2) Mechanism analysis shows that the construction of NEDP has improved GTFP through technological innovation and industrial structure upgrading. (3) The heterogeneity results reveal that NEDP has a significant positive effect on GTFP in the central and western regions, while the effect was insignificant in the eastern region. Moreover, NEDP significantly contributes to GTFP in resource-based and non-resource-based cities, while the contribution of resource-based cities is greater than that of non-resource-based cities. This study provides a reference for China to further promote the construction quality of NEDP and green development.

The urban green transformation is the basis for the green development of China’s economy, and the reduction of income inequality between urban and rural areas is necessary to ensure stable economic growth. Therefore, ensuring green and sustainable economic development, while taking into account social equity, is of practical importance for China to achieve comprehensive high-quality development. This paper constructs a spatial Durbin model and a mediating-effects model to examine the spatial effect of urban green transformation on the urban-rural income gap (URG) and its mechanism of action based on panel data of 265 cities in China from 2006 to 2018. It also divides cities by geographical location and urban population size to further investigate the heterogeneity of the impact of the urban green transition on URG. The study found that (1) there is a significant positive spatial correlation for the URG in China, and the urban green transition can reduce the URG, and the results of the study remain reliable after a series of robustness tests. (2) Urban green transformation can reduce the URG through technological innovation effects and digital effects. (3) Urban green transformation significantly reduced the URG in eastern regions and cities of considerable size and above and had no significant impact on the URG in other cities. The study results demonstrate the possibility of reconciling urban and rural economic development and environmental friendliness at the same time.

The regional carbon emission efficiency (RCEE) of 30 provinces in mainland China from 2011 to 2019 was calculated using a super-slack-based measure (Super-SBM) model. Then, using the system generalized method of moments (system GMM) model, spatial Durbin model (SDM), and mediating effect model, we examined the direct effect, spatial effect, and influence mechanism of the digital economy (DE) on RCEE. It was found that DE significantly promoted regional RCEE, but had a negative effect on RCEE in provinces with a high economic correlation. The mechanism studies showed that DE improved RCEE by reducing the energy intensity and promoting industrial upgrading and green technology innovation. Regional heterogeneity analysis found that DE significantly improved RCEE in eastern provinces, but not in central and western provinces. While RCEE in economically developed areas was improved by DE, it was decreased in economically underdeveloped provinces. This paper provides some empirical and theoretical references for the development of DE to improve RCEE.

Using the Super-SBM method, this study calculates the carbon emission efficiency (CEE) of 30 provinces in mainland China from 2011 to 2019. Then, using the systematic GMM model, spatial Durbin model, and mediating effect model, it examines the direct effect, spatial effect, and influence mechanism of the digital economy (DE) on CEE. It was found that (1) the DE significantly promoted regional CEE, but had a negative effect on CEE in provinces with high economic correlation; (2) mechanism studies showed that the DE improved CEE by reducing energy intensity, promoting industrial upgrading and green technology innovation; (3) regional heterogeneity analysis found that the DE significantly improved CEE in eastern provinces, but not in central and western provinces. DE improves CEE in provinces with high level of economic development, but decreases CEE in provinces with low level of economic development.This paper provides some empirical and theoretical references for the development of DE to improve CEE.