ABSTRACT
To control air quality and reduce air pollution efficiently environmental engineers need to have the reliable data on contaminant emissions, their compositions and concentrations as well as meteorological data. These data are commonly required in predictive models to estimate contaminant dispersion in air over large densely populated areas for long periods of time. Thus, multivariant predictive simulations of dust dispersion will enable assessing the feasibility and environmental impact of engineering solutions reducing the air pollution level in industrial cities like upgrade or replace of dust cleaning facilities.
