Air pollution exposure monitoring and estimation VII. Estimation of population exposure in a central European airshed.

Abstract

In order to clarify the local variation in exposure and source-receptor relationships, a dispersion model for estimating air pollution concentrations was developed for a polluted area in the Czech Republic. Three models characterized by different spatial resolution were integrated into one modelling tool. A regional-scale dispersion model accounted for pollution contribution from sources outside the modelling area. Local- and urban-scale dispersion models were used to calculate local concentration distributions. Calculated concentration distributions were evaluated. Deviations between observed and calculated concentrations were not correlated in space, except in episodes, and concentrations measured at spatially representative stations were assimilated into the model results using statistical interpolation (simple kriging). The results indicated that centralized heating plants and local home heating were the most important sources for sulfur dioxide (SO2) pollution. Both high and low level sources may contribute to the accumulation of pollution concentrations in episodes. The measured concentrations were important for the description of distributions in episodes characterized by complex wind and dispersion conditions. The applicability of source oriented model calculations to correctly represent measured concentrations in the pollution episodes was limited due to the fact that meteorological conditions representative of high concentration episodes were characterized by very low wind speed and variable wind directions. About 8,000 individuals were given an exposure estimate representing contribution from local emissions, based on the estimated hourly outdoor exposure to SO2 at their home/work addresses in the 3 month study period in the autumn of 1991. The results showed that, for 5% of participants, the maximum hourly contribution of local emissions was over 380 microg m(-3). For the 3 month average, both large-scale and local-scale pollution contribute significantly. For primary compounds, such as SO2, steep gradients are observed in the vicinity of strong local sources. These gradients are important for exposure characteristics and health effect quantification, and often will not be captured by an existing monitoring network. The calculations can be extended to other periods or to different compounds.