Global PM2.5 Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios

Ambient fine particulate matter (PM2.5) hassevere adversehealth impacts, making it crucial to reduce PM2.5 exposurefor public health. Meteorological and emissions factors, which considerablyaffect the PM2.5 concentrations in the atmosphere, varysubstantially under different climate change scenarios. In this work,global PM2.5 concentrations from 2021 to 2100 were generatedby combining the deep learning technique, reanalysis data, emissiondata, and bias-corrected CMIP6 future climate scenario data. Basedon the estimated PM2.5 concentrations, the future prematuremortality burden was assessed using the Global Exposure MortalityModel. Our results reveal that SSP3-7.0 scenario is associated withthe highest PM2.5 exposure, with a global concentrationof 34.5 & mu;g/m(3) in 2100, while SSP1-2.6 scenario hasthe lowest exposure, with an estimated of 15.7 & mu;g/m(3) in 2100. PM2.5-related deaths for individuals under 75years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5,respectively, from 2030s to 2090s. However, premature mortality forelderly individuals (>75 years) will increase, causing the contrarytrends of improved air quality and increased total PM2.5-related deaths in the four SSPs. Our results emphasize the needfor stronger air pollution mitigation measures to offset the futureburden posed by population age. Inthis study, a new set of global-scale, spatially explicitPM(2.5) concentration from 2021 to 2100 with a spatial resolutionof 0.1 & DEG; x0.1 & DEG; was generated, and associated PM2.5 exposure and premature mortality burden were calculated.