[en] Automobile exhaust has been identified as a major source of carbon monoxide (CO), a pollutant gas known to have physiological effects on people. This study emphasized the importance of CO modelling, given the increased use of automobiles and the resulting increase in ambient air pollution. Computational models plays an important role in the environmental regulatory process because modeling processes can clarify the complex relationship between environmental emissions, the quality of the environment, and human and ecological impacts. Carbon monoxide (CO) is given the least attention for imperative modeling, despite the fact that frequent exceedance of CO emissions can be harmful to human health and the environment. An accurate emissions estimate and an efficient model for forecasting the future status of CO is needed in order to effectively manage CO. Most CO forecast models describe the temporal and spatial distribution of CO on roadways. The main categories of CO models are deterministic, statistical, hybrid, and neural network in nature. This paper reviewed recent studies that attempted CO dispersion modeling. The Gaussian model was generally accepted for prediction of long-term average concentrations, but it is best suited to explain routine behaviour of dispersion. The scope and restraint associated with various modeling attempts was also discussed. 345 refs., 1 tab.