Özet:

The air pollution has assumed greater and alarming proportion in urban , industrial & pockets where cluster of air polluting industries are in existence .Various air pollutants, namely, Carbon Monoxide (CO), Sulphur Dioxide (SO2), Oxides of Nitrogen (NOx), Suspended Particulate Matter, Respirable Suspended Particulate Matter (PM10, PM2.5, PM1.0), Hydrogen Sulphide (H2S), Methane, Hydrocarbons (HC), Benzene, Aldehydes, 1-3 Butadiene, PAH, Mercaptans, Carbon Disulphide (CS2) , Fluorine based gases and so on so forth are emitted out from these sources. These pollutants are caused on account of vehicular emissions, industrial, Mining, Commercial and Household fuel burning. These pollutants when released in the atmosphere are subjected to transportation, dispersion, transformation, fall out, wash out and finally reach the ground level at a particular distance. Emissions from stacks are subjected to plume rise which again is dependent on force of buoyancy and momentum. The higher is the plume rise, the lesser will be Ground level Concentration. The relationship between the source of emissions and its magnitude with the ground level concentrations at different receptor points is governed by air dispersion models which takes into account the source strength, plume rise, Atmospheric Stability, mixing height, wind velocity, terrain and other meteorological conditions. Various air dispersion models have been developed world over for different applications under different scenarios. Applications of such models have been made mandatory within the framework of Environmental Impact Assessment (EIA) notification, 1994, as amended from time to time. It has therefore assumed greater importance for the academicians, consultants and regulatory authorities. An attempt has been made in the present paper by the authors to discuss such models with a view to select a particular model that can be used for a particular area or application. An effort has also been made to predict SO2 concentrations from a coal based thermal power plant at various receptor points using model of Gaussian dispersion.

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