Investigation of air pollution in the district of mathemathics model Istanbul - Zeytinburnu

Diffusion model has been developed to predict a large number of air pollution. In this study, Zeytinburnu district of Istanbul-from fuel combustion SO2 and particulate matter (PM) in the form of the air pollutants emissions motion, life, are maintained in order to estimate ambient concentrations of the recipient, "Gaussian Beam Type" based ATDL (Atmospheric Turbulence Diffusion Laboratory) Dispersion Model was used.Human and environmental health adversely affecting the contaminated air, water environment is not as clean as possible. Because, in the decontamination of contaminated water and can hold its place, but the air is polluted atmospheric conditions, meteorological and water treatment facilities need to make the process impossible to confine a particular place. Therefore, in order to determine the pollution control strategies to prevent the formation of the Zeytinburnu district in order to estimate the concentration of SO2 and PM 1.5 km2 grid squares, the annual average concentrations of 8 total grid of 2.66 m / s wind speed, and "E-Neutral" atmospheric stability conditions, "Gaussian Beam Type"dispersion based resources for the implementation of the model equation, written in QBASIC computer program calculated the PC.In this study, there is a significant point sources, pollutant concentration, and the calculations are not included in the contribution thought to be negligible. Written in QBASIC program by developing pollutant concentrations calculated and measured values were compared for each grid square. Here, stability is very unstable (A), steady stability, (E) is so different, such as stability, in particular, "D-Neutral" stability pollutant concentrations are taken into account. Measured and model predicted values are compared, the applicability of the model has been demonstrated to reduce air pollution, therefore, to keep an acceptable level or lower concentrations of the standard values were determined to obtain the appropriate scenarios.