Lagrangian and Eulerian approach to predict the movement of radionuclides in selected potential sites in Malaysia during the monsoon period

Abstract

Abstract In computing the movement of particles through the fluid, three types of dispersion models are used which are Gaussian plume models, Lagrangian puff models, and small-scale numerical models. Lagrangian particle dispersion models are increasingly used for nuclear applications. In this study, the usage of the Lagrangian model is implemented in a Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) which combines with the Eulerian model to predict the movement of radionuclides from the simulated nuclear power plant accident in selected locations in Malaysia. These include nuclear risk studies in these areas, emergency response systems, and source term analyses. This study aims to compare the risk from the dispersion of 137Cs from a simulated Nuclear Power Plant (NPP) at Mukah and Tasik Kenyir during the Northeast monsoon (8th October 2022) and Southeast monsoon (16th May 2022). The HYSPLIT model was set up based on the meteorological data during both monsoon periods and was simulated for 5 days. The outcomes revealed that the concentration of 137Cs is higher at Tasik Kenyir compared to Mukah for both during the Northeast monsoon period (3.5 x 107 Bq/m2) while for Southwest monsoon, the result is vice versa where the concentration of 137Cs at Mukah is (2.2 x 107Bq/m2). The activity concentration is then converted into rate effective dose measurement and compared with the limit suggested by ICRP which is 1 Sv per year. It is concluded that Tasik Kenyir is a more suitable location to build NPP compared to Mukah as the movement of radionuclides was dispersed to the location that contained less population.