In the realistic context of the development of China’s digital economy and carbon peaking and carbon neutrality goals, to efficiently achieve high-quality economic and green and low-carbon transformation, this paper investigates the impact of digital economy development on the carbon emission efficiency of 30 Chinese provinces and cities from 2011–2019. In this paper, firstly, the digital economy development index and carbon emission efficiency are calculated by the entropy method and the Super-SBM-Undesirable Model. Secondly, the Spatial Lag Model (SAR) and the Spatial Durbin Model (SDM) are respectively constructed under the adjacency matrix and the geographic distance matrix to empirically test the spatial impact of the digital economy on carbon emission efficiency. The results show that: the digital economy development and carbon emission efficiency of Chinese provinces and cities both show the spatial distribution characteristics of stronger in the East and weaker in the Middle and West; the digital economy development in Chinese provinces and cities has a significantly positive direct and spatial spillover effect on carbon emission efficiency; there are differences in the direct and spatial spillover effects of various dimensions of the digital economy development on the carbon emission efficiency in Chinese provinces and cities; the direct effect of the digital economy development on the carbon emission efficiency in Chinese provinces and cities has significant regional heterogeneity among eastern, central, and western regions. This paper provides new empirical evidence for developing countries such as China to proactively develop a digital economy to promote energy conservation and emission reduction to realize green and low-carbon transformation.

The rational use of environmental regulation tools has become an important means by which to improve the efficiency of carbon emissions. Different types of environmental regulations and their combinations have different impacts on carbon emission efficiency. In order to determine the environmental regulation configurations that may achieve high carbon emission efficiency or lead to low carbon emission efficiency, we constructed an analytical framework of connections between environmental regulation configurations and carbon emission efficiency. Moreover, 30 Chinese provinces from the period covering 2016 to 2019 were selected as research cases. In addition, the super slacks-based measure of efficiency (SE-SBM) model was applied to evaluate carbon emission efficiency. Finally, the fuzzy-set qualitative comparative analysis (fsQCA) method was employed to analyze the impact of different environmental regulation configurations on carbon emission efficiency. The results showed that the carbon emission efficiency of various regions of China is generally low (with most regions not having reached an effective level) and that there are large regional differences. We found that there are four environmental regulation configurations that can achieve high carbon emission efficiency and two environmental regulation configurations that lead to low carbon emission efficiency. Based on these configurations, we draw three conclusions: (1) There are three paths to achieving high carbon emission efficiency: one that values command-and-control environmental regulation but disfavors market-incentive environmental regulation, another that combines command-and-control environmental regulation with market-incentive environmental regulation, and a third that couples command-and-control environmental regulation with voluntary environmental regulation. (2) Two paths that may lead to low carbon emission efficiency were established: excessive penalties and the lack of specific measures. (3) In some conditions, environmental governance investment and fiscal expenditure could be substituted for each other; environmental protection administrative penalties and pollution charges are synchronized; environmental governance investment in the promotion of carbon emission efficiency is indispensable. Policies and suggestions on how the government can use environmental regulation tools to improve carbon emission efficiency are proposed from a general coordinative perspective in the final section of this paper.

Pteroceltis tatarinowii (Pteroceltis: Ulmaceae) is a deciduous tree that has a cultivation history of more than 2000 years in China. As an excellent afforestation tree species and rare and endangered tertiary relic plant, P. tatarinowii has high ecological protection value. Due to the forest destruction caused by predatory logging and natural environmental factors, the population of P. tatarinowii in China has decreased significantly. In this study, the potential geographical distribution of P. tatarinowii in China under climate change was predicted using MaxEnt model and ArcGIS based on 223 effective distribution points of P. tatarinowii and 11 environmental variables. The results showed that: (1) the prediction accuracy of MaxEnt model was extremely high, and the areas under curve (AUC) value of the training data was 0.936; The area of the potential suitable habitat area of P. tatarinowii under current climate condition was 180.84×10⁴ km², and mainly located in the central and southeast regions of China. (2) The domain environmental variables affecting the potential geographical distribution of P. tatarinowii were min temperature of coldest month (12.1~22.7°C), isothermality (26.6~35.8), mean diurnal range 6.9~9.3°C and precipitation of wettest month (189.5 ~955.5 mm). (3) In 2050s and 2070s, compared with current (4.19×10⁴ km²), the area of highly suitable habitat will increase by 0.2%-0.3% (RCP2.6) and 1.22%-3.84% (RCP8.5) respectively. while the poorly, moderately and total suitable habitats will decrease. The gravity center of P. tatarinowii showed a trend of migration to higher latitudes and northern regions in the future. These results will provide theoretical basis for cultivation management and resource protection of P. tatarinowii.

This study aims to analyze the nonlinear relationship between environmental regulation and carbon emission efficiency and provide scientific reference for achieving the goal for carbon neutrality at a lower cost. Taking 30 provinces in China, using dual carbon policy as the research objects, the slacks-based measure–Malmquist–Luenberger (SBM–ML) index method was used to measure the carbon emission efficiency from 2009 to 2019 and a panel threshold regression model was established to explore the nonlinear effects of environmental regulation and carbon emission efficiency in each province. The results show that: (1) during the sample period, there is geographical variability in CEE, with the eastern coastal provinces having the highest CEE, followed by the central and western provinces, and the resource-dependent provinces having the lowest CEE and their energy consumption and utilization efficiency being significantly lower than other provinces; (2) when the energy consumption intensity is used as a threshold variable, the relationship between environmental regulation and carbon emission rate is an inverted “U” shape; and (3) when green technology innovation is used as a threshold variable, the relationship between environmental regulation and carbon emission rate is a “U” shape. This study provides a new perspective for improving carbon emission efficiency.