Global PM_2.5 Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios

Ambient fine particulate matter (PM_2.5) has severe adverse health impacts, making it crucial to reduce PM_2.5 exposure for public health. Meteorological and emissions factors, which considerably affect the PM_2.5 concentrations in the atmosphere, vary substantially under different climate change scenarios. In this work, global PM_2.5 concentrations from 2021 to 2100 were generated by combining the deep learning technique, reanalysis data, emission data, and bias-corrected CMIP6 future climate scenario data. Based on the estimated PM_2.5 concentrations, the future premature mortality burden was assessed using the Global Exposure Mortality Model. Our results reveal that SSP3-7.0 scenario is associated with the highest PM_2.5 exposure, with a global concentration of 34.5 μg/m³ in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 μg/m³ in 2100. PM_2.5-related deaths for individuals under 75 years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5, respectively, from 2030s to 2090s. However, premature mortality for elderly individuals (>75 years) will increase, causing the contrary trends of improved air quality and increased total PM_2.5-related deaths in the four SSPs. Our results emphasize the need for stronger air pollution mitigation measures to offset the future burden posed by population age.