An air pollution emissions control strategy to avoid violations of both short- and long-term health standards for particulate levels

A model is constructed which can be used in an emissions control strategy for avoiding violations of both the short- and long-term health standards suggested by the United States Environmental Protection Agency for Total Suspended Particulate (TSP) levels. The model assumes that TSP data are lognormally distributed and the geometric standard deviation for such data can be simply derived from wind speed statistics. The model predicts maximum TSP levels to an accuracy of a factor of 2, which is reasonable for air pollution work. The model is applied to 6 years of TSP data at six monitors in Brisbane, Australia, as well as to nephelometer data at two other sites. The results suggest that an emissions control strategy to avoid violations of the long-term standard will not generally avoid violations of the short-term standard. A worst-case scenario for required emissions control based on the examination of 35 years of wind speed data indicates that the particulate problem in Brisbane is more widespread than that suggested from an examination of the 6 years for which TSP data are available. It is suggested that the model outlined in the paper may be of general use in devising effective emissions control strategies which avoid violations of both sets of particulate health standards.