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Abstract: Projects in carbon capture and storage technologies for energy production involve the transport of vapour, liquid and supercritical CO2 and CO2/hydrocarbon gas mixtures via pipelines and process systems with subsequent injection into wells, e.g. offshore under the seabed. In addition several chemical companies often store and transport large quantities of CO2 and this may also represent a hazard. There is a need to model potential loss of containment scenarios for risk assessment and design purposes for such installations. It is observed that several models used in quantitative risk analyses and hazard assessment studies are not able to take into account modelling of the thermodynamics of CO2 in case of accidental releases from dense or supercritical conditions. Statoil together with DNV therefore initiated a project to further improve the Phast code for modelling of CO2 releases. The work and methodology derived in this project have mainly been developed by Det Norske Veritas (DNV), but with significant co-operation and input by Statoil. The consequence modelling package Phast examines the progress of a potential incident from the initial release to the far-field dispersion including the modelling of rainout and subsequent vaporisation. The original Phast 6.54 models allow the released chemical to occur only in the vapour and liquid phases. The new Phast 6.6 models were extended to also allow for the occurrence of fluid to solid transition in case of CO2 releases. This applies both for the post-expansion state in the discharge model, as well as for the thermodynamic calculations by the dispersion model. Here it is assumed that no solid deposition occurs on the ground. The current paper documents work regarding modelling by Phast 6.6 of discharge and atmospheric dispersion of carbon dioxide, including a detailed sensitivity analysis for a wide range of scenarios (base cases) including high-pressure cold releases (liquid storage) and high-pressure supercritical releases (vapour storage) from vessels, short pipes or long pipes. The objectives of this work were to examine the effect of input parameters on key output data, to ensure robustness of the models, and to identify further model improvements where deemed to be necessary. [Copyright &y& Elsevier]