Controlling emissions to avoid violations of health standards for short term and long term exposures to TSP concentrations

Abstract

A mathematical model is constructed to predict frequency distributions of total suspended particulates (TSP) data for an urban area using only emissions and meteorological data as input. Predictions from this model can then be used to devise source specific emissions control strategies that avoid violations of health standards for short and long term exposure to TSP levels, both in the present situation and for future urban development. The model assumes (a) the Atmospheric Turbulence and Diffusion Laboratories (ATDL) model can be used to estimate annual arithmetic means, (b) the two-parameter lognormal distribution is representative of the TSP data, and (c) there is an inverse relationship between the percentiles of the wind speed and air pollution data sets. It is noted that only assumption (b) may not be generally applicable although the results here imply its use leads to conservative control strategies which may be reasonable first approximations. The importance of studies on the chemical composition of particulate data is stressed and shown here to be essential for accurate model predictions.