Improved Clearance Verification: Direct Application of Measurements’ Distribution

We have developed a method for calculating the probability of doses during clearance of land that makes no a priori assumptions about the statistical distribution of radionuclide measurements. Our method uses the actual distribution of survey and sampling measurements rather than assuming a specific distribution. It applies Monte Carlo simulations to the Sum of Fractions calculation and accounts for all known uncertainties. In addition, it defines the probability and uncertainty of complying with the clearance criterion. In contrast, nearly all demonstrations of compliance with clearance criteria currently are based on nonparametric statistics. As such, the analysis is for the median dose to an individual in the critical group. They are based on an assumed statistical distribution and do not account for all known uncertainties. In contrast, regulatory authorities base compliance on either the dose to representative person or the dose to the average member of the critical group - not the median member of the critical group. Accounting for uncertainties is required as noted in the assertion of at least eight international authorities, including the International Organization for Standardization and the International Union of Pure and Applied Chemistry. They state that a measurement without its stated uncertainties is incomplete, not technically sound, and may not be considered defensible. Our Monte Carlo Sum of Fractions method provides the highly accurate quantified probability and uncertainty of compliance with the clearance criterion because we simulate all the data with randomized uncertainties. Therefore, it improves verification of clearance. In this work we demonstrate the application of Monte Carlo Sum of Fractions method to measurement data from a real site as a "Proof of Concept" for clearance of land. The evaluation of the dose to either of the representative person or the mean dose, and quantified uncertainty due to known parameters are technically sound basis for demonstration of compliance with clearance criteria.

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Publication Details

Journal
Health Physics
Published
2026-01-28
DOI
https://doi.org/10.1097/hp.0000000000002098
Primary Topic
Radioactive contamination and transfer
Type
article
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article

Improved Clearance Verification: Direct Application of Measurements’ Distribution

Jonatan Jiselmark, Robert A Meck, Steven Adams
Health Physics
Radioactive contamination and transfer
article

Improved Clearance Verification: Direct Application of Measurements’ Distribution

Jonatan Jiselmark, Robert A Meck, Steven Adams
article en

Abstract

We have developed a method for calculating the probability of doses during clearance of land that makes no a priori assumptions about the statistical distribution of radionuclide measurements. Our method uses the actual distribution of survey and sampling measurements rather than assuming a specific distribution. It applies Monte Carlo simulations to the Sum of Fractions calculation and accounts for all known uncertainties. In addition, it defines the probability and uncertainty of complying with the clearance criterion. In contrast, nearly all demonstrations of compliance with clearance criteria currently are based on nonparametric statistics. As such, the analysis is for the median dose to an individual in the critical group. They are based on an assumed statistical distribution and do not account for all known uncertainties. In contrast, regulatory authorities base compliance on either the dose to representative person or the dose to the average member of the critical group - not the median member of the critical group. Accounting for uncertainties is required as noted in the assertion of at least eight international authorities, including the International Organization for Standardization and the International Union of Pure and Applied Chemistry. They state that a measurement without its stated uncertainties is incomplete, not technically sound, and may not be considered defensible. Our Monte Carlo Sum of Fractions method provides the highly accurate quantified probability and uncertainty of compliance with the clearance criterion because we simulate all the data with randomized uncertainties. Therefore, it improves verification of clearance. In this work we demonstrate the application of Monte Carlo Sum of Fractions method to measurement data from a real site as a "Proof of Concept" for clearance of land. The evaluation of the dose to either of the representative person or the mean dose, and quantified uncertainty due to known parameters are technically sound basis for demonstration of compliance with clearance criteria.

Health PhysicsVol. 130(3)
University of Nevada, Las Vegas (US), Université de Corse Pascal Paoli (FR), Greenfield Research (Canada) (CA)
Partnerships for the goals
Openalex Percentile: Top 80%
Radioactive contamination and transfer
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