Increasing the popularity of distributed photovoltaic technology among Chinese residents is of great significance to achieve the dual carbon goal (emission peak and carbon neutrality). In this study, we collected 1424 questionnaire samples and used PLS-SEM for group modeling and comparative analysis of bungalow and building residents. The results show that living conditions, costs, risks of installation, maintenance, and economic efficiency are the five significant influencing factors for residents to decide whether to install a distributed residential photovoltaic equipment. Compared with building residents, bungalow residents tend to feel more concerned about the cost and risk of residential photovoltaic equipment during installation, maintenance, and use. On the other hand, bungalow residents show greater sensitivity to the corresponding photovoltaic promotion policies. By contrast, building residents pay more attention to the direct benefit created by the installation of residential photovoltaic equipment. Therefore, adopting the strategy from bungalow residents to building residents could help promote the distributed photovoltaic system progressively. As for the subsidy decline, more attention shall be paid to the progress of a gradual reduction of the subsidies. It is advisable to pay attention to integrating the upstream and downstream industry chains of the distributed photovoltaic systems, thus reducing the concern of residents about the difficulty in installing, maintaining, and protecting the distributed photovoltaic equipment. By clarifying the different impacts of promotion policies on the demand side, this study provides a practical reference for the further adjustment made to distributed photovoltaic promotion policies.

Utilizing China’s air quality monitoring data from 2013 to 2023, this study employs spatial autocorrelation analysis and health impact assessment methodologies to quantify the health economic costs and temporal trends of PM _2.5 and O ₃ pollution across mainland China. Results indicate a substantial decline in PM _2.5 -attributable mortality over the study period. With 0 and 15 μg/m ³ taken as the reference concentrations, all-cause mortality decreased by 47.41% (233,173 cases) and 65.55% (240,448 cases), respectively. Cardiovascular disease mortality declined by 47.71% (56,086 cases) and 65.75% (57,504 cases), while respiratory disease mortality reduced by 46.97% (38,519 cases) and 65.27% (40,055 cases). Conversely, O ₃ -related mortality exhibited a significant upward trend. At reference concentrations of 0 and 60 μg/m ³ , all-cause mortality increased by 24.25% (365,084 cases) and 79.70% (372,724 cases), respectively. Cardiovascular mortality rose by 25.43% (80,056 cases) and 81.52% (77,497 cases), and respiratory mortality increased by 15.46% (98,620 cases) and 64.54% (163,165 cases). Spatially, health economic costs and their GDP proportions for both pollutants followed a high distribution in the east and a low distribution in the west. Shandong, Henan and Jiangsu were the top regions for PM _2.5 -related economic costs, with Henan, Hebei and Tianjin exhibiting the highest GDP ratios. For O ₃ , Guangdong, Jiangsu and Shandong incurred the greatest economic costs, while Henan, Hebei and Gansu showed the highest GDP proportions. These findings underscore the divergent trends in PM _2.5 and O ₃ health impacts and provide critical evidence for targeted air pollution control strategies in China.

Digital–intelligent technologies and their extensive application across real-world scenarios are profoundly reshaping traditional industries while fostering emerging and future industries, becoming a key engine for industrial intelligence and the development of new quality productive forces. Advancing new quality productive forces in coal enterprises is a core pathway to overcome bottlenecks such as high safety risks and stringent environmental constraints in the traditional coal sector and to achieve high-quality industrial development; digital–intelligent transformation provides critical support for this process. Using panel data from 30 Chinese A-share listed coal companies from 2012 to 2024, this study empirically examines the impact of digital–intelligent transformation on the development of new quality productive forces in coal enterprises, and explores the mediating role of resource allocation efficiency and the moderating role of local governments’ economic performance assessment pressure. The results show that digital–intelligent transformation significantly promotes the development of new quality productive forces in coal enterprises. Resource allocation efficiency plays a mediating role in this relationship, accounting for 14.89% of the total effect. Moreover, local economic performance assessment pressure negatively moderates the effect of digital–intelligent transformation on the development of new quality productive forces, and this negative moderating effect persists along the mediating pathway via resource allocation efficiency. This study aims to uncover the internal mechanism through which digital–intelligent transformation promotes new quality productive forces in coal enterprises, providing a new theoretical basis and research perspective for coal enterprises to cultivate new quality productive forces.

As a key engine driving the high-quality development of agriculture and rural areas, digital rural construction plays a pivotal role in the structural extension of the nighttime economy from urban to rural areas. This study systematically examines the influence mechanism between digital rural construction and the prosperity of the nighttime economy by constructing a two-way fixed effects model, a threshold regression model, and a spatial Durbin model. The findings reveal the following three key insights: (1) the construction of digital rural facilities effectively drives the growth of the nighttime economy by reducing market transaction costs and fostering new consumption patterns, with this effect being particularly prominent in economically developed regions; (2) environmental quality and balanced urban–rural development exhibit nonlinear moderating effects on the enabling role of digital technologies, as when air pollution concentrations and the urban–rural income gap exceed specific thresholds, the marginal promotion effect weakens significantly; and (3) digital rural construction has a significant positive effect on the local nighttime economy, but its impact on nonlocal nighttime economies is insignificant. High-quality development of the nighttime economy can be promoted by balancing digital infrastructure, implementing differentiated environmental governance, and optimizing the urban–rural income distribution. This study provides a new theoretical perspective and research reference for rural economic prosperity in the era of the digital economy.