Comparisons between a new point kernel-based scheme and the infinite plane source assumption method for radiation calculation of deposited airborne radionuclides from nuclear power plants.

Radiation from the deposited radionuclides is indispensable information for environmental impact assessment of nuclear power plants and emergency management during nuclear accidents. Ground shine estimation is related to multiple physical processes, including atmospheric dispersion, deposition, soil and air radiation shielding. It still remains unclear that whether the normally adopted "infinite plane" source assumption for the ground shine calculation is accurate enough, especially for the area with highly heterogeneous deposition distribution near the release point. In this study, a new ground shine calculation scheme, which accounts for both the spatial deposition distribution and the properties of air and soil layers, is developed based on point kernel method. Two sets of "detector-centered" grids are proposed and optimized for both the deposition and radiation calculations to better simulate the results measured by the detectors, which will be beneficial for the applications such as source term estimation. The evaluation against the available data of Monte Carlo methods in the literature indicates that the errors of the new scheme are within 5% for the key radionuclides in nuclear accidents. The comparisons between the new scheme and "infinite plane" assumption indicate that the assumption is tenable (relative errors within 20%) for the area located 1 km away from the release source. Within 1 km range, the assumption mainly causes errors for wet deposition and the errors are independent of rain intensities. The results suggest that the new scheme should be adopted if the detectors are within 1 km from the source under the stable atmosphere (classes E and F), or the detectors are within 500 m under slightly unstable (class C) or neutral (class D) atmosphere. Otherwise, the infinite plane assumption is reasonable since the relative errors induced by this assumption are within 20%. The results here are only based on theoretical investigations. They should be further thoroughly evaluated with real measurements in the future.