Predictions of Long-term PM10-2.5 in Six US Urban Areas Using Satellite Data

Abstract

BACKGROUND AND AIM: A major challenge in assessing the health risks of PM10-2.5 in the United States is the limited measurement data from which to estimate exposure. This is especially problematic for studying long-term PM10-2.5 health effects since PM10-2.5 is more spatially variable than PM2.5 or PM10, particularly in urban areas, which have considerable PM10-2.5 spatial variability. Fortunately, data from satellites offers opportunities to assess PM10-2.5 across space. Our project leverages Aerosol Optical Depth (AOD) measurements from NASA’s MODIS satellite to estimate long-term PM10-2.5 in six urban areas for 2000-2012. METHODS: We calibrated daily AOD (1 km2 resolution) with EPA monitored PM10 and PM2.5 in six urban areas (Los Angeles, Chicago, St Paul, Baltimore, New York, and Winston-Salem) using land-use regression in a linear mixed-model with daily random slopes. Long-term PM10-2.5 was estimated after taking the difference of spatially matched PM10 and PM2.5 daily predictions. Calibration model performance was evaluated using leave-one-station-out cross-validation and compared to an alternative, nearest-monitor approach. RESULTS:Long-term PM10-2.5 predictions performed very well compared to measurements from co-located PM2.5 and PM10 sites in four of the six urban areas, with spatial R2 from 0.6 to 0.9. Two areas had poor to fair performance (R2: 0 and 0.4). All predictions performed better than the nearest-monitor alternative. CONCLUSIONS:Long-term PM10-2.5 predictions had fair to very good spatial performance in the five study areas with sufficient measured data on which to build our models. Given the superior performance of our spatial predictions compared to the nearest-monitor alternative and the high costs of field sampling, our results show the potential for combining AOD data with land-use regression to estimate long-term PM10-2.5 concentrations in localized areas. KEYWORDS: Air pollution, Exposure assessment, Long-term exposure, Particulate matter