Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

The negative impacts of fine particulate matter (PM2.5) exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the datasets and methodology. Satellite observations of aerosol optical depth (AOD) have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and datasets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model.

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