Estimation of PM_2.5 using high-resolution satellite data and its mortality risk in an area of Iran

Satellite-based exposure of fine particulate matters has been seldom used as a predictor of mortality. PM2.5 was predicted using Aerosol Optical Depths (AOD) through a two-stage regression model. The predicted PM2.5 was corrected for the bias using two approaches. We estimated the impact by two different scenarios of PM2.5 in the model. We statistically found different distributions of the predicted PM2.5 over the region. Compared to the reference value (5 mu g/m(3)), 90th and 95th percentiles had significant adverse effect on total mortality (RR (90th percentile):1.45; CI 95%: 1.08-1.95 and RR (95th percentile):1.53; CI 95%: 1.11-2.1). Nearly 1050 deaths were attributed to any range of the air pollution (unhealthy range), of which more than half were attributed to high concentration range. Given the adverse effect of extreme values compared to the both scenarios, more efforts are suggested to define local-specific reference values and preventive strategies.