Identifying PM2.5-Related Health Burden in the Context of the Integrated Development of Urban Agglomeration Using Remote Sensing and GEMM Model

Abstract

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 PM2.5 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 PM2.5 and innovatively incorporated exposure factors to improve accuracy. Results indicated that while PM2.5 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.