Regression model for automated assessment of radiation risks from radon

by

M.V. Kalashnikova

St. Petersburg State University of Aerospace Instrumentation,

RF, St. Petersburg, Bolshaya Morskaya str., 67, lit. A.

E-mail: mgovor42@gmail.com

DOI: 10.33075/2220-5861-2025-4-106-115

UDC 614.876                                                                

EDN: https://elibrary.ru/vnmdsu

Abstract:

The present study is aimed at developing a comprehensive automated system for assessing the carcinogenic risk of developing lung cancer caused by internal exposure to radon and its decay products. The system is based on a verified quadratic regression model developed based on epidemiological data from the International Commission on Radiological Protection (ICRP, Publication No. 115). The model takes into account the non-linear nature of the dose-response relationship and the pronounced synergistic effect of combined exposure to radon and tobacco smoking. The key element of the model is an improved territorial adaptation algorithm, implemented through a dynamic calculation of the conversion factor (K), which establishes a quantitative relationship between the individual expected radiation dose and the average annual equivalent equilibrium volumetric activity of radon isotopes in indoor air. The system has been verified using data on the equivalent equilibrium volumetric activity of radon isotopes.

Keywords: radon, monitoring, internal radiation, carcinogenic risk, diagnostics, software package, automation

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