Understanding the spatial variation of intangible cultural heritage (ICH) is essential for protecting and utilizing heritage resources but has rarely been investigated along the Grand Canal in China. Initially, we analyzed the spatial variation of ICH with different categories using GIS spatial analysis and other technologies. Subsequently, we used the geodetector statistical method to explore local factors influencing ICH concentrations in various cities along the Grand Canal. The results show that the distribution of ICH resources in different categories was unbalanced among focal cities, mainly concentrated in the northern and southern ends of the Grand Canal. Although socioeconomic factors have important impacts on the spatial distribution of ICH, the local geographic environments remain important in forming and developing ICH resources. This study provides an important reference for ICH resource systematic regeneration and utilization plans along the Grand Canal.

The scientific promotion of rural revitalization is an important issue in the context of global poverty reduction and sustainable development. For China, the largest developing country in the world, the construction of rural revitalization model villages has become an important measure to achieve agricultural and rural modernization and the coordinated development of urban and rural areas. Research on the rural revitalization model villages in China can provide guidance for the rural transformation development in other developing countries. In this paper, the Yangtze River Delta (YRD) was used as the study area, and the spatial differentiation characteristics and driving factors of 1621 rural revitalization model villages were analyzed using ArcGIS software and the geographical detector method. The results are as follows: (1) The multiscale spatial distributions of rural revitalization model villages in the YRD showed a weak agglomeration and disequilibrium characteristic. Anhui Province has the highest imbalanced distribution of model villages among different provinces in the YRD. (2) The model villages are the most densely distributed along the Yangtze River. Extending to the north and south from areas along the Yangtze River, the distribution of the model villages is first sparse then dense. Model villages agglomerate mainly along rivers and lakes, areas close to traffic arteries and the middle areas of suburban. (3) The spatial differentiation of rural revitalization model villages is the result of the combined effect of multiple factors, and the driving factors also showed significant spatial heterogeneity. The most important driving factors of the spatial differentiation of the model villages of the YRD, Jiangsu, Zhejiang, and Anhui are social development and government intervention, transportation accessibility and economic development, resource endowment and natural conditions, and transportation accessibility and government intervention, respectively. This study has practical significance for optimizing the spatial pattern of rural revitalization model villages in the YRD and facilitating high-quality rural revitalization.

China’s industrialization and urbanization processes have recently accelerated, leading to the rapid expansion of urban built-up areas. Fossil fuels, such as natural gas, oil, and coal, are consumed in large quantities, resulting in the accumulation of atmospheric pollutants. Severe PM2.5 and O₃ pollution poses significant human health risks, including respiratory diseases, cardiovascular and cerebrovascular diseases, and lung cancer. This study utilized data from various observation stations in Jiangsu Province, the annual statistical yearbook data, and statistical data, such as baseline mortality and socioeconomic indicators, to quantitatively analyze the concentration characteristics of PM2.5 and O₃, premature deaths related to pollutant exposure, and negative health effects in Jiangsu Province from 2018 to 2023. The study examined the spatiotemporal evolution patterns of pollutant concentrations, related premature deaths, and negative health effects in various cities within Jiangsu Province under policy-driven conditions. The results show that (1) the annual average concentration of PM2.5 in Jiangsu Province decreased from 105.88 μg/m³ in 2018 to 55.04 μg/m³ in 2023, marking a reduction of 48.01%. (2) The total number of premature deaths due to long-term exposure to PM2.5 decreased by approximately 87%, whereas the total number of premature deaths due to long-term exposure to O₃ increased by approximately 216%. (3) City level (2.377**) and population structure (1.068**) play an important role in the health effects of air pollution. (4) Short-term exposure to high concentrations of pollutants has a significant negative impact on the health of individuals with underlying diseases.