Atmospheric pollution is one of the biggest problems and concerns in modern society, especially in industrial and highly populated areas. Poor air quality can have adverse impact on human health and ecosystems. For this reason, air quality forecasting becomes increasingly important, especially for governments and administrations, which use these predictions to enhance the design of mitigation actions in order to reduce air pollution in urban areas. In this framework, process of pollutant dispersion simulation is the best way to predict the most affected areas by industrial and other kinds of emissions. To carry out these simulations, there is a great number of computational tools currently available. However, not all of them have the same functionalities, nor can they be applied to the same case studies, so it is necessary to establish the advantages and disadvantages of each one of them in order to choose the most suitable tool in each case. Therefore, the objective of this paper is to identify the main available simulation tools and to make a comparative review between them in order to define advantages and disadvantages.