Impact of dispersion coefficient models on offsite consequence analyses

In Level 3 probabilistic safety assessment (PSA), accurate modeling of atmospheric dispersion is essential for predicting radionuclide concentrations and radiation doses. As a key input to the commonly used Gaussian plume model, the dispersion coefficient directly affects the reliability of offsite consequence assessments. This study compares six representative dispersion coefficient models and quantitatively evaluates how differences among them influence ground-level dilution and mean peak dose estimates. Simulations were conducted using RCAP and MACCS, two consequence assessment codes. Despite some numerical differences, both tools showed consistent trends, with the results demonstrating that the choice of dispersion model can lead to variations of up to 2.65 times in dilution and 1.77 times in dose. Sensitivity analyses revealed that wind speed has a significant impact on model variability and uncertainty, while plume release height has a negligible effect. Overall, the Briggs model produced the most conservative estimates, whereas the Modified Tadmor–Gur model showed the least conservative tendencies. These findings underscore the importance of selecting appropriate dispersion models in Level 3 PSA, as the choice may significantly influence key decisions such as the emergency planning zone boundaries. The results also help to support the credibility and precision of future consequence assessments.