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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, PM 2.5 , and PM 2.5 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 (FEV 1 ) and forced vital capacity (FVC), adjusting for study community and biological factors. Gradient Boosting and Support Vector Machines showed excellent predictive performance for PM 2.5 (test R 2 = 0.68 ) and its chemical components (test R 2 = –0.71). In single-pollutant models, FEV 1 decreased by 131 mL (95% CI: − 232 , − 35 ) per 10.7-µg/m 3 increase in PM 2.5 , by 158 mL (95% CI: − 273 , − 43 ) per 1.2-µg/m 3 in sulfates (SO 4 2 − ), and by 177 mL (95% CI: − 306 , − 56 ) per 1.6-µg/m 3 increase in dust; FVC decreased by 175 mL (95% CI: − 310 , − 29 ) per 1.2-µg/m 3 increase in SO 4 2 − and by 212 mL (95% CI: − 391 , − 28 ) per 2.5-µg/m 3 increase in nitrates (NO 3 − ). These results demonstrate that satellite observations can strengthen epidemiological studies investigating air pollution health effects by providing spatially and temporally resolved exposure estimates.

Satellite-Derived PM2.5 Composition and Its Differential Effect on Children’s Lung Function