Uncertainties Analysis of Doses Resulting From Chronic Inhalation of Plutonium at the Mayak Production Association

Abstract

A method is presented to determine the uncertainties in the reported dose due to incorporated plutonium for the Mayak Worker Cohort. The methodology includes errors generated by both detection methods and modeling methods. To accomplish the task, the method includes classical statistics, Monte Carlo, perturbation, and reliability groupings. Uncertainties are reported in percent of reported dose as a function of total body burden. The cohort was initially sorted into six reliability groups, with "A" being the data set that the investigators are most confident is correct and "G" being the data set with the most ambiguous data. Categories were adjusted based on preliminary calculation of uncertainties using the sorting criteria. Specifically, the impact of transportability (the parameter used to describe the transport of plutonium from the lung to systemic organs) was underestimated, and the structure of the sort was reorganized to reflect the impact of transportability. The finalized categories are designated with Roman numerals I through V, with "I" being the most reliable. Excluding Category V (neither bioassay nor autopsy), the highest uncertainty in lung doses is for individuals from Category IV-which ranged from 90-375% for total body burdens greater than 10 Bq, along with work histories that indicated exposure to more than one transportability class. The smallest estimated uncertainties for lung doses were determined by autopsy. Category I has a 32-38% uncertainty in the lung dose for total body burdens greater than 1 Bq. First, these results provide a further definition and characterization of the cohort and, second, they provide uncertainty estimates for these plutonium exposure categories.

Uncertainties Analysis for the Plutonium Dosimetry Model, Doses-2005, Using Mayak Bioassay Data

“…The uncertainty introduced to the model from the urine bioassay measurements and MDA have been previously discussed by Krahenbuhl et al (2005). Krahenbuhl et al also discuss the inapplicability of Bayesian statistics due to the irregularity in bioassay measurements of the Mayak cohort.…”

“…The total uncertainty in doses computed using the Doses-2005 algorithm is compiled using perturbation theory (Lyons 1991;Skorokhod et al 2002;Konstantinov et al 2003) as discussed previously by Krahenbuhl et al (2005). Krahenbuhl et al (2005). c Confirmed quality assurance from SUBI.…”

“…Previous uncertainty analysis has been performed on the ICRP-66 lung model (Bolch et al 2001Farfán et al 2003;Huston et al 2003;Fritsch 2006) but was not included in the Doses-2005 uncertainties analysis because it was not specific to the complete model and parameters being evaluated. The total uncertainty in doses computed using the Doses-2005 algorithm is compiled using perturbation theory (Lyons 1991;Skorokhod et al 2002;Konstantinov et al 2003) as discussed previously by Krahenbuhl et al (2005). Krahenbuhl et al (2005).…”

Influence of Alpha and Gamma Radiations and Non-Radiation Risk Factors on the Incidence of Malignant Liver Tumors Among Mayak Pa Workers

“…The 239 Pu body burden and D ␣ were extrapolated for the period of interest using a retention function based on the indicated biokinetic model. Error in D ␣ may be higher than 30%, because additional sources of error contribute to alpharadiation doses (e.g., statistical and systematic error associated with the biokinetic model used to obtain doses) (Krahenbuhl et al 2005). The risk of exceeding the permissible level for inhaled airborne 239 Pu remained high until a special respirator, "Lepestok," was introduced in 1957.…”

Errors and Uncertainties in Dose Reconstruction for Radiation Effects Research

“…The expert-elicitation process will include discussions during meetings, exchanges of electronic mail, and telephone communications. The process will consider all previous work on uncertainties in doses for radiation health studies, with particular emphasis on products of Project 2.4 such as Krahenbuhl et al (2005) and Zharov et al (Zharov et al2007). …”