Methods For Calculating Thyroid Doses to The Residents Of Ozersk Due to 131I Releases From The Stacks of The Mayak Production Association

Rovny, Sergey I. ; Mokrov, Y. ; Stukalov, Pavel M. ; Beregich, D. A. ; Teplyakov, I. I. ; Anspaugh, L. R. ; Napier, Bruce A.

关键词: AR FACILITIES;    FOOD CHAINS;    IODINE;    MANAGEMENT;    MATHEMATICAL MODELS;    NUCLEAR WEAPONS;    PRODUCTION;    RADIATION DOSES;    RADIATIONS;    RADIOACTIVE WASTES;    THYROID radiation dose reconstruction;    models;    Mayak Production Association;    iodine-131;   

DOI  :  10.2172/983438
RP-ID  :  PNNL-18916
PID  :  OSTI ID: 983438
Others  :  Other: HU2006300
Others  :  TRN: US1004523

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来源: SciTech Connect

【 摘 要 】

The Mayak Production Association (MPA) was established in the late 1940s in accordance with a special Decree of the USSR Government for the production of nuclear weapons. In early years of MPA operation, due to the lack of experience and absence of effective methods of RW management, the enterprise had extensive routine (designed) and non-routine (accidental) releases of gaseous radioactive wastes to the atmosphere. These practices resulted in additional technogenic radiation exposure of residents inhabiting populated areas near the MPA. The primary objective of ongoing studies under JCCRER Project 1.4 is to estimate doses to the residents of Ozersk due to releases of radioactive substances from the stacks of MPA. Preliminary scoping studies have demonstrated that releases of radioactive iodine (131I) from the stacks of the Mayak Radiochemical Plant represented the major contribution to the dose to residents of Ozersk and of other nearby populated areas. The behavior of 131I in the environment and of 131I migration through biological food chains (vegetation-cows-milk-humans) indicated a need for use of special mathematical models to perform the estimation of radiation doses to the population. The goal of this work is to select an appropriate model of the iodine migration in biological food chains and to justify numerical values of the model parameters.