Air Quality Modelling Application to Evaluate Effects of PM Air Concentrations on Urban Population Exposure.

Abstract

P-015 Abstract: Air pollution is a major environmental health problem causing approximately three million deaths per year in the world, as result of exposure to particulate matter (PM). For population exposure assessment, a combination of the spatial distribution of both air quality and population density is required. Numerical models are useful tools for the mapping of air pollutants, once the monitoring networks are able to assess the air quality in the single stations of the monitoring network, and not the whole area of interest. Dispersion and photochemical models have been applied, at different scales, to evaluate air pollution due to particulate matter concentrations and its effects on human exposure and health. In Portugal, especially in urban agglomerations, like Porto and Lisboa, particulate matter air concentrations are exceeding the correspondent limit value imposed by the EC Air Quality Framework Directive, with unavoidable effects on populations' health. In fact, during the past four years, most of the air quality monitoring stations of Porto region has registered a number of PM10 daily averaged values above the limit threshold, which was higher than the allowed 35 exceedings per year. Aiming to characterize and evaluate the likely human exposure to air pollution and its effects on the health of an urban population at risk due to the high levels of particulate matter air concentrations, a past particulate matter air pollution episode occurred in Porto region was selected for study. The Comprehensive Air Quality Model with extensions (CAMx) is an Eulerian photochemical dispersion model that simulates the emission, dispersion, chemical reactions, and removal of gaseous and particulate pollutants. To obtain the spatial distribution of particulate matter concentrations in the study area, CAMx was applied to the Porto agglomeration for the selected particulate air pollution episode. Meteorological inputs were obtained by the application of the mesoscale meteorological model MM5 using its nesting capabilities. PM10 simulation results were evaluated against registered concentrations at air quality monitoring stations and were used to estimate population exposure, combining modelling results with information on population regarding their spatial distribution on urban, industrial and rural areas and their time-activity patterns. Preliminary results show that, although high concentrations of PM10 were obtained not exclusively in city centre, exposure is elevated where population density is high. Further research is needed in order to identify more clearly the most significant parameters that affect particulate air pollution in Portuguese urban areas and consequently urban population exposure and health.