Dispersion models and air quality data for population exposure assessment to air pollution

Evaluating the extent of exposure to chemicals in absence of continuous measurements of their concentration in air and direct measures of personal exposure is crucial for epidemiological studies. Dispersion models can be a useful tool for reproducing spatio-temporal distribution of contaminants emitted by a specific source. However, they cannot easily be applied to short-term epidemiological studies because they require precise information on daily emission scenarios for a long time, which are generally not available. The aim of this study was to better assess the exposure in the industrial area of Brindisi, which suffers from various critical epidemiological situations, by integrating air pollution concentration data, emissions and model simulations concerning a specific point source. The results suggest that in the absence of direct exposure data and detailed information on specific pollutants associated to an emission, population exposure may be better assessed by taking into account proxy pollutants and the wind (direction and speed) as a potential health effects modifier.