الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Atmospheric dispersion modeling is the mathematical simulation of how air pollutants disperse in the ambient atmosphere. The dispersion models are used to estimate or to predict the downwind concentration of air pollutants.
With respect to the different types of atmospheric pollution dispersion models, we find that Gaussian Plume Model still the basic workhorse for dispersion calculations and it is the one most commonly used because it produces results that agree with experimental data as well as any model. Also it is fairly easy to perform mathematical operations on this equation. In addition, it is consistent with the random nature of turbulence.
The present thesis concentrates on the study of Gaussian plume model and its applications. This thesis consists of four chapters namely; Introduction, Calculation of Crosswind Integrated Concentration by Using Different Dispersion Parameters, Analytical Solution of diffusion equation in two dimensions using two forms of eddy diffusivities, and Maximum air concentrations from Non-Gaussian Plume Model.
In Chapter 1, we give general background about the atmospheric dispersion modeling including, the atmospheric layers, air pollution emission plumes, the different types of the atmospheric pollution dispersion models, and Air pollutant emission sources. Then we review several aspects of meteorology, including vertical temperature structure and stability, turbulence fluxes, plume rise, and source effects, in order to begin the study of applications of the Gaussian Plume model.
In Chapter 2, we illustrate the dispersion scheme of the Gaussian model. Then, the Gaussian formula for a continuous release from a point source (GPM) is integrated to get crosswind integrated concentration. Different schemes such as Irwin, power law, Briggs, Standard methods and split sigma theta can be used to obtain integrated concentration. Also downwind speed in power law, plume rise, and Statistical measures are used in the model to know which is the best scheme agrees with the observed concentration data obtained from Copenhagen, Denmark. A paper has been elaborated with the results and has been published in “MAUSAM”, 62 (India) – January 2011.
In Chapter 3, an analytical solution of the two-dimensional atmospheric diffusion equation has been developed by the method of Separation of variables. Also Fourier transform and square complement methods has been used to solve the integration. The present model is validated with the data sets obtained at the Northern part of Copenhagen of the tracer sulfur hexafluoride (SF6) in unstable conditions. In this model the vertical eddy diffusivity depends on the downwind distance and is calculated using two methodsK(x)=γUx ,andK(x)=K_0 U_* x. Values of the calculated normalized crosswind concentration are calculated differently, according to the different eddy diffusivities. These values are compared with the observed data graphically and statistically. The proposed method No.1 has performed better than method No.2 with the data from the diffusion experiment considered. A paper has been conducted and published in “the Romanian Journal of Physics”, (Romania) – March 2011.
In Chapter 4, the maximum ground level air concentration from elevated point source over simple terrain is estimated using previous work by Essa et al. (2007). The eddy diffusivities in linear forms are used. The critical of the wind speed, plume height and downwind distance are estimated. The results of the maximum concentrations are applied using meteorological data of a plant stack located in, Inshas, Egypt. A paper has been prepared and published in “the International Journal of Research in Management”, 2 (India) – March 2012. Key Words: (Atmospheric dispersion models, atmospheric advection diffusion equation, Gaussian diffusion equation, stability classes, and eddy diffusivities).