MESOSCALE MODELS AND THEIR APPLICATION TO AIR-QUALITY STUDIES

The use of mesoscale models in conjunction with air quality models enables better prediction of pollution transport and dispersion in the atmosphere. The accuracy of the prediction depends upon the physical processes included in the models, on the mathematical representation, and on the initial meteorological and other external data. In most situations large power plants are located near the coast or in hilly terrain. Under these situations the meteorological fields which are relevant to air quality studies change tremendously with time and space (both vertically and horizontally). So far most of the air quality studies and consequently the decisions regarding sitting and management of power plants in coastal or hilly sites are made according to simple Gaussian models which are based on limited observational data, and, therefore, are of doubtful meanings. To obtain better prediction of pollutant concentration dense meteorological observations have to be made. Since such observations are very expensive, it is unrealistic to require them. A reliable mesoscal model, however, can supply the necessary meteorological fields with relatively little expenses with any needed resolution, providing that appropriate computers are available. Model results can be very useful in prediction of maximum concentration that can be expected from routine simultaneous release from several sources during critical weather conditions. Since the late seventies, with the huge development of large computers, it has been made possible also to carry out three-dimensional simulations. Lately with the development of advanced microcomputers and appropriate software it is even possible to perform two- and even three-dimensional experiments on such computers within a reasonable time frame.