OEnergy efficiency is a vital factor to promote sustainable development. In this paper, the directional distance function–global Malmquist–Luenberger model (DDF-GML) is applied to measure the energy efficiency levels of 30 provinces in China from 2000 to 2017. Simultaneously, the impacts of the economic growth targets and marketization on energy efficiency are empirically tested using the generalized system moment estimation (SYS-GMM) and mediation effect model. The statistical results reveal that energy efficiency is on the rise every year as a whole. Mediated by marketization, economic growth targets inhibit energy efficiency by distorting marketization. Moreover, there is significant regional heterogeneity in the impacts of economic growth targets on energy efficiency. The inhibition effect of economic growth targets on energy efficiency in the eastern region is greater than in the central and western regions. The above empirical results are determined to be robust through testing.

As a comprehensive environmental regulation, the low-carbon city pilot policy (LCCP) may have an impact on haze pollution. The evaluation of the effectiveness of LCCP on haze pollution is greatly significant for air pollution prevention and control. Taking LCCP as the starting point, in this study we constructed DID, PSM-DID, and intermediary effect models to empirically test the impact and mechanism of LCCP on haze pollution, based on the panel data of 271 cities in China from 2005 to 2018. The findings show that (1) LCCP has significantly reduced the urban haze pollution, and the average annual concentration of PM2.5 in pilot cities decreased by 14.29%. (2) LCCP can inhibit haze pollution by promoting technological innovation, upgrading the industrial structure, and reducing energy consumption. Among these impacts, the effect of technological innovation is the strongest, followed by industrial structure, and energy consumption. (3) LCCP has significantly curbed the haze pollution of non-resource dependent cities, Eastern cities, and large cities, but exerted little impact on resource-dependent cities, Central and Western regions, and small and medium-sized cities. (4) LCCP has a spatial spillover effect. It can inhibit the haze pollution of adjacent cities through demonstration and warning effects. This study enriches the relevant research on LCCP and provides empirical support and policy enlightenment for pollution reduction.

Achieving carbon peak and carbon neutrality is an inherent requirement for countries to promote green recovery and transformation of the global economy after the COVID-19 pandemic. As “a smoke-free industry,” producer services agglomeration (PSA) may have significant impacts on CO 2 emission reduction. Therefore, based on the nightlight data to calculate the CO 2 emissions of 268 cities in China from 2005 to 2017, this study deeply explores the impact and transmission mechanism of PSA on CO 2 emissions by constructing dynamic spatial Durbin model and intermediary effect model. Furthermore, the dynamic threshold model is used to analyze the nonlinear characteristics between PSA and CO 2 emissions under different degrees of government intervention. The results reveal that: (1) Generally, China’s CO 2 emissions are path-dependent in the time dimension, showing a “snowball effect.” PSA significantly inhibits CO 2 emissions, but heterogeneous influences exist in different regions, time nodes, and sub-industries; (2) PSA can indirectly curb CO 2 emissions through economies of scale, technological innovation, and industrial structure upgrading. (3) The impact of PSA on China’s CO 2 emissions has an obvious double threshold effect under different degree of government intervention. Accordingly, the Chinese government should increase the support for producer services, dynamically adjust industrial policies, take a moderate intervention, and strengthen market-oriented reform to reduce CO 2 emissions. This study opens up a new path for the low-carbon economic development and environmental sustainability, and also fills in the theoretical gaps on these issues. The findings and implications will offer instructive guideline for early achieving carbon peak and carbon neutrality.

No abstract

No abstract

No abstract

No abstract

Digitization and greening are the vital driving force of China’s economic transformation. Whether they can drive collaboratively China’s economy is the key to realizing sustainable development. In this study, a super efficiency EBM model is applied to calculate the urban green economy development (UGED) level of 266 Chinese cities between 2011 and 2020, and then the dynamic SDM and intermediary effect models are employed to explore the impact and transmission mechanism of digital economy on UGED. Furthermore, it is also investigated whether digital economy and UGED have a nonlinear relationship. In the findings, digital economy is capable of significantly boosting UGED in the local city and its neighborhood, but significant differences exist in different regions and economic development stages. As a result of the transmission mechanism test, it may be found that digital economy could indirectly boost UGED through technology, structure, and allocation effects. The impact of digital economy on UGED has a double threshold due to the significant difference in the urban economic development level. The digital economy is increasingly contributing to UGED as the local economy develops. Therefore, local governments should develop digital economy in line with the local conditions so that its engine role in driving UGED can be given full play.