The annual permissible atmospheric release levels of radionuclides are established with the condition that the population annual dose should not exceed the dose quota. Two conservative assumptions on the population exposure are applied in handbooks for calculation of the permissible release levels: a person can reside in any point outside the sanitary protection zone of nuclear facility; all exposure pathways, including food consumption, are determined by the place of residence. Calculation of the annual dose for adults living near the Smolensk, Rostov and Bilibino NPP was performed for three scenarios to evaluate the degree of conservatism of these assumptions. Scenario 1 assumed permanent residence in a critical point of the area with production of all food in this point and consumption only local food by the population. Scenario 2 assumed that a certain part of food is imported. In scenario 3 dose assessment was made for a permanent resident of the closest settlement near NPP, taking into consideration realistic characteristics of the exposure conditions. Atmospheric release levels of radionuclides assessed during the radiation and technical surveys of the NPP’s emission sources in 2017 – 2019 were used as the initial data. It is shown that the assumptions on the conditions of population exposure significantly affect the conservatism of the annual dose assessment. The calculated annual dose for the most conservative scenario is higher than for realistic scenario by 6,3 times (for the Smolensk NPP), 8,4 times (Rostov NPP), 883 times (Bilibino NPP). The highest degree of conservatism was shown for the internal radiation dose estimates. The results of calculation of the annual dose from NPP’s emissions strongly depend on the method for dose assessment from releases of 3H and 14C. Use of the regional values of consumption of locally produced food allows reasonable reducing the conservatism of the annual dose estimates from the NPP’s permanent radionuclide releases.
Beta-Ray Dose Assessment from Skin Contamination Using a Point Kernel Method
