Author(s)

Liang T. Chu^1,2, Adam G. Burn^1,2, Clayton J. Bradt¹, Thomas M. Semkow^1,2

¹Wadsworth Center, New York State Department of Health, Albany, NY, USA.
²Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, NY, USA.

In this work, we addressed the inhomogeneity problem in gamma spectrometry caused by hot particles, which are dispersed into environment from large nuclear reactor accidents such as at Chernobyl and Fukushima. Using Monte Carlo simulation, we have determined the response of a gamma spectrometer to individual and grouped hot particles randomly distributed in a soil matrix of 1-L and 0.6-L sample containers. By exploring the fact that the peak-to-total ratio of efficiencies in gamma spectrometry is an empirical parameter, we derived and verified a power-law relationship between the peak efficiency and peak-to-total ratio. This enabled creation of a novel calibration model which was demonstrated to reduce the bias range and bias standard deviation, caused by measuring hot particles, by several times, as compared with the homogeneous calibration. The new model is independent of the number, location, and distribution of hot particles in the samples. In this work, we demonstrated successful performance of the model for a single-peak ¹³⁷Cs radionuclide. An extension to multi-peak radionuclide was also derived.

Chernobyl, Fukushima, Peak Efficiency, Total Efficiency, Signal Detection Theory

Chu, L. , Burn, A. , Bradt, C. and Semkow, T. (2021) Monte Carlo Simulation Study of Hot-Particle Detection in Voluminous Samples by Gamma Spectrometry. Journal of Applied Mathematics and Physics, 9, 1522-1540. doi: 10.4236/jamp.2021.97104.