van Donkelaar, A, Martin, RV, Brauer, M, Kahn, R, Levy, R, Verduzco, C, Villeneuve, PJ (2010). Global Estimates of Ambient Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth: Development and Application. ENVIRONMENTAL HEALTH PERSPECTIVES, 118(6), 847-855.
BACKGROUND: Epidemiologic and health impact studies of fine particulate matter with diameter < 2.5 mu m (PM2.5) are limited by the lack of monitoring data, especially in developing countries. Satellite observations offer valuable global information about PM2.5 concentrations. OBJECTIVE: In this study, we developed a technique for estimating surface PM2.5 concentrations from satellite observations. METHODS: We mapped global ground-level PM2.5 concentrations using total column aerosol optical depth (AOD) from the MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multiangle Imaging Spectroradiometer) satellite instruments and coincident aerosol vertical profiles from the GEOS-Chem global chemical transport model. RESULTS: We determined that global estimates of long-term average (1 January 2001 to 31 December 2006) PM2.5 concentrations at approximately 10 km x 10 km resolution indicate a global population-weighted geometric mean PM2.5 concentration of 20 mu g/m(3). The World Health Organization Air Quality PM2.5 Interim Target-1 (35 mu g/m(3) annual average) is exceeded over central and eastern Asia for 38% and for 50% of the population, respectively. Annual mean PM2.5 concentrations exceed 80 mu g/m(3) over eastern China. Our evaluation of the satellite-derived estimate with ground-based in situ measurements indicates significant spatial agreement with North American measurements (r = 0.77; slope = 1.07; n = 1057) and with noncoincident measurements elsewhere (r = 0133; slope = 0.86; n = 244). The 1 SD of uncertainty in the satellite-derived PM2.5 is 25%, which is inferred from the AOD retrieval and from aerosol vertical profile errors and sampling. The global population-weighted mean uncertainty is 6.7 mu g/m(3). CONCLUSIONS: Satellite-derived total-column AOD, when combined with a chemical transport model, provides estimates of global long-term average PM2.5 concentrations.