Air dispersion modeling is becoming a significant part of the regulatory process in many states. Most states require all new facilities to obtain a permit prior to construction. Part of this permit application is to demonstrate that once the facility is in operation it will be in compliance with air quality standards for all regulated pollutants. Since it is impossible to measure air quality impacts of a future source, air dispersion modeling is used. In addition to being used in the initial permitting process, modeling could also be used to determine the impact of sources that wish to amend their abatement system, if this amendment will result in increased emissions. Also, any facility that receives a complaint will be evaluated to determine whether they are in violation of the air quality standards. At this point, the regulator could use air dispersion modeling to determine if the facility is in compliance. For all of these cases it is essential to have a model that will accurately predict the concentration of pollutants downwind from the source. One particular model being used for this purpose is the Industrial Source Complex (ISC) Screen2. However, the use of Screen2 results in inaccurate predictions of downwind concentrations. Therefore, a model that will accurately predict downwind concentrations when compared to ISC Screen2 is sought. This paper will describe a dispersion model that more accurately predicts downwind concentrations of particulates from agricultural operations. Both ISC Screen2 and the proposed model, Classical Gaussian Dispersion (CGD), are based upon the Gaussian diffusion equations.