Integrated development of urban agglomeration is emerging as the main pattern of China’s new modernization. Yet, atmospheric pollution continues to have an adverse impact on public health, challenging efforts to promote coordinated regional development. To better understand the interaction between atmospheric pollution-related health burdens and urbanization, this study employed deep learning technology to obtain high-resolution satellite-derived PM_2.5 concentration data across the Yangtze River Delta (YRD) region. Using the Global Exposure Mortality Model (GEMM), this study estimated premature mortality resulting from long-term exposure to PM_2.5 and innovatively incorporated exposure factors to improve accuracy. Results indicated that while PM_2.5 concentrations decreased by 16.13% from 2015 to 2019, the region still experienced 239,000 premature mortalities in 2019, with notable disparities among cities of different economic levels and sizes. Furthermore, it was found through correlation analysis that residential density and GDP per capita were highly associated with premature mortality. In conclusion, these findings highlight the continuing challenge of achieving equitable effectiveness of joint air pollution control across regions in the context of integrated development of urban agglomeration.

Cultural ecosystem service (CES) assessment is essential for comprehensively understanding and evaluating ecosystem services. Optimizing the spatial zoning of CESs can provide more targeted information for ecosystem management. By identifying the typical landscape characteristics of different CESs, rural landscape value can be more effectively recognized. This study constructed a set of rural landscape characteristics indicators, identified the typical characteristics of different CESs based on public preferences, mapped their spatial distributions using the Maxent model, and applied K-means clustering analysis to optimize the spatial zoning in rural Huzhou. The results show that the four CESs categories are associated with different rural landscape characteristics. The spatial distributions of the CESs showed substantial overlap and were mainly concentrated in southern Anji County, around the Moganshan Scenic Area, and along the shoreline of Lake Taihu. Five types of rural landscapes were identified based on spatial distribution of the CESs. This study provides a reference for identifying the landscape value of CESs in rural areas and supports the incorporation of CES assessment into rural landscape management decision-making.