Global PM<sub>2.5</sub> Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios
Wanying Chen, Xingcheng Lu, Dehao Yuan, Yiang Chen, Zhenning Li, Yeqi Huang, Tung Fung, Haochen Sun, Jimmy Chi Hung Fung
Abstract
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/m 3 in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 μg/m 3 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.