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.

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.

Re-evaluating how urban and rural development can be integrated is a necessary step towards achieving the “dual-carbon” objective and facilitating a thorough transition towards a green and low-carbon economy and society. This study empirically investigates the geographical disparities, evolving patterns, and determinants of the effectiveness of urban–rural integration development in Sichuan and Chongqing. Results of the study indicate that (1) the effectiveness of urban–rural integration development in Sichuan and Chongqing is generally poor, and external environmental factors adversely affect the urban–rural integration of economically developed cities; (2) the urban–rural integration development efficiency in Sichuan and Chongqing does not show a more obvious polarization phenomenon, but the gap between the cities gradually widens; and (3) regarding influencing factors, market dynamics are favorable to overall urban–rural integration development in the Sichuan and Chongqing regions, while the development of the digital economy and the level of financial development can exacerbate the imbalance of regional urban–rural integration development. Based on this premise, pertinent policy suggestions are offered to facilitate the merger of urban and rural areas and foster efficient development in the regions of Sichuan and Chongqing.

As a major province for hydroelectric power in China, Sichuan Province has witnessed a great amount of seasonal characteristics in its hydroelectric power, endowing the clean energy industry in Sichuan with the characteristics of unstable supply in different seasons, strong power transmission capacity, and low production capacity of other non-fossil energy sources (except hydroelectric power). In this study, the mathematical model method was used to construct a structural optimization model of the clean energy industry in Sichuan Province, and to enable a quantitative analysis of the rationalization of the clean energy industrial structure in Sichuan Province. The results are proved from the cost-effectiveness of low carbon emission that hydroelectric power > wind power > photovoltaic power > natural gas > coal > oil. This study shall find the theoretical structure of the clean energy industry in Sichuan Province in 2030 with a prediction of Sichuan Province’s total future energy output and a constraint of its industrial structure model of clean energy. This paper suggests that Sichuan Province should give priority to the development of non-fossil energy sources, increase the development and utilization of power transmission channels in wet seasons, and develop clean energy and high energy consumption industries and the construction of pumped storage power stations, so as to reduce and avoid the waste of energy resources. It is also suggested that Sichuan Province should focus on developing clean energy with the capability of peak shaving, such as hydrogen energy and natural gas, while developing smart grid and long-distance transmission technology to strengthen energy conservation and emissions-reduced power generation. On this basis, Sichuan will focus on the development and utilization of natural gas as an alternative to high-carbon energy, with a view to optimizing its industrial structure of clean energy and helping China achieve the dual-carbon goals.

Terrestrial net primary productivity (NPP) integrates vegetation responses to climate, terrain, and human activities, yet their combined effects in mountainous–basin regions remain unclear. Focusing on the Chengdu–Chongqing Economic Circle (CCEC) in southwest China, we build a framework that couples spatial diagnosis, interaction-aware attribution, and scenario-based projection. Using 500 m MODIS NPP (2000–2020) with climatic, topographic, land-use, and socio-economic data, we quantify NPP trends, use optimal-parameter GeoDetector and partial correlations to separate driver contributions and interactions, and train a random forest (RF)–SHAP model driven by CMIP6–SSP climate projections to 2050. The CCEC shows strong greening: 85.17% of the area exhibits increasing NPP and 68.56% shows extremely significant increases, with productivity peaking at mid-elevations (~1950 m) and intermediate slopes. Elevation, NDVI, and temperature dominate, while precipitation, slope, and soil moisture are secondary, and enhancement-type interactions, especially between elevation and precipitation, prevail. Land-use statistics and NPP transfer matrices highlight cropland-to-forest/grassland conversion as the main greening source. CMIP6-based simulations indicate stable or modestly higher NPP through 2050, with western mountain forests remaining key carbon sinks and basin lowlands constrained by warming and land-use pressure.