The carbon capture and storage (CCS) and enhanced oil recovery (EOR) projects entail the possibility of accidental release of carbon dioxide (CO
2) into the atmosphere. To quantify the spread of CO 2following such release, the ‘Gaussian’ dispersion model is often used to estimate the resulting CO 2concentration levels in the surroundings. The Gaussian model enables quick estimates of the concentration levels. However, the traditionally recommended values of the ‘dispersion parameters’ in the Gaussian model may not be directly applicable to CO 2dispersion. This paper presents an optimisation technique to obtain the dispersion parameters in order to achieve a quick estimation of CO 2concentration levels in the atmosphere following CO 2blowouts. The optimised dispersion parameters enable the Gaussian model to produce quick estimates of CO 2concentration levels, precluding the necessity to set up and run much more complicated models. Computational fluid dynamics (CFD) models were employed to produce reference CO 2dispersion profiles in various atmospheric stability classes (ASC), different ‘source strengths’ and degrees of ground roughness. The performance of the CFD models was validated against the ‘Kit Fox’ field measurements, involving dispersion over a flat horizontal terrain, both with low and high roughness regions. An optimisation model employing a genetic algorithm (GA) to determine the best dispersion parameters in the Gaussian plume model was set up. Optimum values of the dispersion parameters for different ASCs that can be used in the Gaussian plume model for predicting CO 2dispersion were obtained.