Modeling distributions of air pollutant concentrations—III. The hybrid deterministic-statistical distribution approach

Abstract

A general modeling approach is proposed to predict the distribution of air pollutant concentrations and in particular the upper percentiles. The approach is hybrid in that it combines features of both deterministic and statistical distribution models. These features include causality and the attempted quantification of stochastic variability and uncertainty. The properties of deterministic and statistical distribution models are discussed separately and this clarifies the contribution that can be made by hybrid modeling. In this way the underlying assumptions are clearly presented. The range of successful applications of the hybrid approach is briefly reviewed. These involve relatively inert pollutants from urban/industrial, point source, elevated point source and roadway emissions. Areas of further research are outlined which would enhance the routine use of the approach and extend its application. Sufficient development has been undertaken, however, that the present standard set of air pollutant dispersion models could be easily updated to provide hybrid models capable of predicting frequency distributions of air pollutant levels under stipulated assumptions.