Air pollution modeling

Abstract

Three air pollution models are presented which address themselves to the specific problems of 1) pinpointing locations of relative maxima, 2) producing air quality maps efficiently, and 3) presenting. graphic representation of patterns of pollution over a mesoscale region. MAXPOL-A is a semiempirical, source-oriented, microscal0, deterministic, climatological air pollution model which uses a simplex search algorithm to walk, one step at a time, towara the area of maximum concentration. Input parameters govern the length of walk and the precision with which the maximum is located. SIMPLOT is a semiempirical, source-oriented, stochastic, climatological air pollution model and employs the concept of stochastic simulation as well as simulation ! in the usual sense to obtain estimates of air quality. SIMPLOT also uses a technique. called the plume projection procedure which allows it to generate all of the receptors for each eliminating source and meteorological extensive checking. DAMPS condition thus is a dynamic, segmented, source-oriented, deterministic, mesoscale model which keeps track of all air parcels over a 60 by 60 kilometer region. DAMPS updates all receptors hourly and produces three types of graphic output. DAMPS also utilizes the plume projection procedure used in SIMPLOT. Computer programs foe each model are included as are several examples of the use of each model.