A tool for determining urban emission characteristics to be used in exposure assessment

The exposure of citizens to elevated air pollution concentrations is one of the major factors leading to the deterioration of the quality of life and possibly to health problems in urban areas. The concentration of air pollutants depends largely on pollutant emission levels. If the statistical probability distribution function of the concentration of an air pollutant is known, it is possible to estimate how many times this concentration exceeds the air quality standards, or estimate changes in the emission levels in an area. It can be also used to estimate the long term exposure of population to certain pollutants. In this paper fifteen theoretical probability distribution functions, were used to fit the actual concentration frequency distributions of CO, NO(2), O(3,) SO(2), and Black Smoke (BS) in Athens, Greece for a 23-year period. The results showed that the theoretical distribution type best describing the distribution of the pollutants is Inverse Gaussian followed by the Extreme value distribution. The number of exceedances of air quality limits was used to validate the performance of the theoretical distributions that were best fitted to the observed ones. The temporal evolution of emission strength was estimated through the temporal evolution of the parameters of the probability distribution functions. Missing periods were accounted for by estimating the respective distribution functions through interpolation or extrapolation from the existing ones. The derived variation of emission levels consistently represents the emission reduction strategies enforced over the years, as well as the escalating growth of the passenger car fleet volume, and could be a useful tool for the design and assessment of emission control strategies.