Satellite-derived PM2.5 composition and its differential effect on children's lung function

Abstract

Studies of the association between air pollution and children's health typically rely on fixed-site monitors to determine exposures, which have spatial and temporal limitations. Satellite observations of aerosols provide the coverage that fixed-site monitors lack, enabling more refined exposure assessments. Using aerosol optical depth (AOD) data from the Multiangle Imaging SpectroRadiometer (MISR) instrument, we predicted fine particulate matter, PM2.5, and PM2.5 speciation concentrations and linked them to the residential locations of 1206 children enrolled in the Southern California Children's Health Study. We fitted mixed-effects models to examine the relationship between the MISR-derived exposure estimates and lung function, measured as forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC), adjusting for study community and biological factors. Gradient Boosting and Support Vector Machines showed excellent predictive performance for PM2.5 (test R2 = 0.68) and its chemical components (test R2 = 0.53-0.71). In single-pollutant models, FEV1 decreased by 131 mL (95% CI:-232,-35) per 10.7-μg/m3 increase in PM2.5, by 158 mL (95% CI:-273,-43) per 1.2-μg/m3 in sulfates, and by 177 mL (95% CI:-306,-56) per 1.6-μg/m3 increase in dust; FVC decreased by 175 mL (95% CI:-310,-29) per 1.2-μg/m3 increase in and by 212 mL (95% CI:-391,-28) per 2.5-μg/m3 increase in nitrates. These results demonstrate that satellite observations can strengthen epidemiological studies investigating air pollution health effects by providing spatially and temporally resolved exposure estimates.