Attention to physical and mental health is becoming more intensive. In China, factors and mechanisms are now a focus of research. We used dynamic air quality monitoring data and the Chinese General Social Survey (CGSS) to assess the spatial differences and the coupling between subjective and objective air pollution. In addition, a logistic model was used to explore the impact mechanisms of social inequality, air pollution, food safety, and lack of green space on health. The results show that (1) the impact of subjective and objective air pollution on the health level of the population is significant; (2) income inequality, air pollution, food pollution, and travel behavior significantly affect the residents’ health; and (3) environmental health has a significant differentiation mechanism between urban and rural areas. The negative health effects of air pollution and insufficient green space are more significant in cities; food pollution is more likely in rural areas. In terms of socioeconomic inequality, gender, family size, travel, and physical exercise had no significant effect on rural health. Health improvement was higher in the low-income group than in the high-income group. The adverse effect of travel behavior on environmental pollution is conducive to improving health. Therefore, social equality, strictly controlled environmental pollution, exercise, and travel can help narrow the gap between rich and poor, promote urban–rural health equity, and improve human health.

Water-related cultural heritage architecture (WRCHA) represents a globally significant and potentially hybrid heritage found across river basins worldwide. Its spatial and temporal evolution characteristics offer insight into the development trends of river basin environments, yet their value within water-related cultural and environmental systems remain incompletely assessed. This study undertakes qualitative and quantitative analyses of the historical spatial and temporal distributions, influencing factors, and environmental changes affecting the water-related culture, climate, population, and urban areas of 295 WRCHA sites in the Li River Basin of China, employing drought–flood indices, GIS analyses, random forest algorithms, and other methodologies. The results reveal that (1) the Lishui Basin contains a significant distribution pattern of agglomeration for WRCHA within the river basin, concentrated along the river, at low altitudes, with minimal terrain variation, and radiating around ancient governance centers, with varying increases observed across different periods and aggregation zones and with significant spatial and temporal heterogeneities; (2) the distribution pattern is influenced by joint natural and human factors, closely tied to variables such as the river network density, DEM, population changes, and distance to ancient government sites; (3) the combination of the architecture’s location and elevation, along with drought–flood curves, reflects the position of the ancient riverbed of the Lishui River and its historical maximum water level. The quantity of new constructions, in conjunction with the distance from ancient government centers and the trends in population change, thus indicates the urban scale and the frequency and severity of disasters. This study provides a research paradigm and historical reference model for investigating environmental changes in watershed systems, aiding in clarifying the historical human–water symbiosis pattern in the middle reaches of the Yangtze River. Such insights will furnish a scientific basis for future regional ecological planning and watershed environmental management.

PM2.5 is the main source of air pollution in China. The problem of air pollution has become the focus of public opinion and academic research in recent years. This article departs from the traditional single-scale approach and adopts a spatial multiscale perspective. Leveraging annual average PM2.5 concentration data and urban socioeconomic data spanning the period from 2009 to 2018, in conjunction with atmospheric PM2.5 remote sensing inversion datasets, a comprehensive analysis is conducted. This analysis encompasses the utilization of GIS spatial-temporal analysis techniques and geographic detectors. The primary objective of this research is to investigate the spatiotemporal evolution characteristics of PM2.5 in the Yangtze River Basin during the years 2009 to 2018, as well as to elucidate the influencing factors therein. This study is crucial to the joint prevention and control of air pollution. The Results showed that (1) The overall trend in the number of cities with annual average PM2.5 concentrations below 35 μg/m3 (the annual limit value in China) exhibits fluctuating upward dynamics. (2) From 2009 to 2018, the low-value area distribution of the annual average PM2.5 concentration in the Yangtze River Basin was stable, whereas the high-value area showed a trend of “first decreasing, then increasing, and then decreasing.” (3) The spatial and temporal agglomeration effect was evident, showing an “east-hot, west-cold” agglomeration pattern. From 2009 to 2018, the high-value aggregation area expanded to the middle part of the Yangtze River Basin and then continued to the north. The low-value concentration area was concentrated in the western part of the Yangtze River Basin, and the range change trend was not large. (4) While each variable concurrently engages in interactions, they also exhibit varying degrees of influence on the spatiotemporal distribution of PM2.5. Among them, population density and the proportion of urban built-up areas in the index layer of population and urbanization are strongly correlated factors.