The development of digital financial inclusion helps create a healthy rural financial ecological environment and plays an important role in integrating rural tertiary industries. This paper incorporates digital financial inclusion into the rural tertiary industry integration research framework. Furthermore, it adopts the double-difference method to empirically analyze the impact of the development of digital financial inclusion on rural tertiary industry integration from the perspective of policy impact. In addition, it considers regional differences in the financial ecological environment; robustness tests were carried out using methods such as placebo tests and validated the conduction mechanism. The study through the double-difference model found that digital financial inclusion is very conducive to promoting rural tertiary industry integration; using the quantile DID (difference in differences) method to analyze the heterogeneity, it is concluded that there is a heterogeneous impact on rural tertiary industry integration. It exerts a more significant improvement in provinces and cities with higher rural tertiary industry integration levels. Constructing an intermediary effect model to verify the transmission mechanism concludes that the policy has promoted the improvement of rural tertiary industry integration efficiency by promoting technological innovation, improving agricultural modernization, and building a risk-sharing mechanism. Finally, it puts forward policy recommendations from optimizing the financial ecological environment, rationally allocating financial resources, and perfecting the transmission mechanism.

Low-visibility air pollution frequently occurs in the major cities of China and affects residents’ physical and mental health. This study, using Gaoyou City as a case study, selected 10 typical residential communities with different locations and types and conducted a questionnaire survey for two consecutive weeks to measure commuting behavior characteristics and health effects among residents in environments with different degrees of air pollution from November to December 2022. Concerning commuting distance, the average straight distance for short-distance commuting was 1.4 km, and the median commuting distance was 13.2 km. In air-polluted environments, residents’ commuting times were mainly concentrated within 1.5 h, with a majority taking 20 min to 30 min. The working and living spaces presented a circular core distribution pattern, with low-visibility air pollution significantly affecting the choice of commuting mode and having an indirect impact on health. The proportion of people who chose bus commuting significantly increased as air pollution changed from mild to moderate, whereas the proportion of people choosing slower commuting, such as walking, significantly decreased. While no significant fluctuations in physical health levels occurred, psychological health levels significantly decreased. In high air pollution environments, residents’ sleep quality, attitudes towards life, emotional states, and other assessed factors exhibited an inverted U-shaped correlation with commuting patterns. Low-visibility air pollution indirectly damaged the health of residents by affecting their commuting patterns, reducing their physical activity intensity and commuting options, and increasing their psychological stress and anxiety.

Research on public service facility evaluation has mainly focused on spatial accessibility and facility quality from a supply perspective, but has rarely focused on the evaluation of service facilities from a usage perspective. Researchers can observe the service quality, frequency of use, functional connotation, satisfaction level, and other aspects of facilities from the user’s perspective, effectively compensating for the disadvantage of insufficient precision in traditional macro statistical data. This study proposes a new method for evaluating medical facility usage and service quality based on residents’ activity data. We established an evaluation index system from the perspective of residents’ activity by measuring intensity, frequency, and service satisfaction through network grading data and online comments context. Then, we evaluated the supply and demand relationship of medical facilities, identifying the influencing factors of medical satisfaction. We have also proposed specific strategies for sustainable optimization of medical services. The results show that (1) the service attitude (0.024, 0.002**), service efficiency (0.133, 0.001*), and service quality (0.017, 0.001**) of medical institutions are the core factors that affect medical satisfaction, followed by the convenience of residents in accessing medical resources, showing a significant positive correlation (p < 0.01, Total R² = 0.9061); and (2) the medical service level in Nanjing City is generally balanced, although spatial heterogeneity exists in the Qixia and Jiangning boroughs.