Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/32991
Title: Modeling of radon flux density depending on air temperature and humidity (using the example of the anomalous zone of Mount Beshtau)
Other Titles: Моделирование плотности потока радона в зависимости от температуры и влажности воздуха (на примере аномальной зоны горы Бештау)
Authors: Sidyakin, P. A.
Сидякин, П. А.
Baryshnikov, A. A.
Барышников, А. А.
Pershin, I. M.
Першин, И. М.
Keywords: Mount Beshtau;Radon;Radon anomaly;Radon flux density;Regression analysis
Issue Date: 2026
Publisher: Geophysical Institute of the Vladikavkaz Scientific Centre of the Russian Academy of Sciences
Citation: Sidyakin P. A., Baryshnikov A. A., Pershin I. M., Miklyaev P. S. Modeling of radon flux density depending on air temperature and humidity (using the example of the anomalous zone of Mount Beshtau) // Geologiya i Geofizika Yuga Rossii. - 2026. - 16 (1). - pp. 57 - 68. - DOI: 10.46698/vnc.2026.70.83.001
Series/Report no.: Geologiya i Geofizika Yuga Rossii
Abstract: Relevance. Studying radon transport mechanisms and identifying anomalies, such as on Mount Beshtau (Caucasian Mineral Waters region), where extremely high radon flux density (RFD) values have been recorded, is critically important for assessing radiation risk. The primary source of radon in buildings is its entry from soil, particularly in fault zones where convective transport is most prevalent. Aim. The purpose of the study is to develop a mathematical model for predicting radon flux density based on meteorological and other parameters that potentially influence radon release from rocks into the atmosphere. The study aims to analyze the influence of air temperature and humidity on the flux density in the identified radon anomaly on the western slope of Mount Beshtau. Methods. Data from radon activity, temperature, and humidity measurements taken between 2018 and 2020 were used for the analysis. A prototype mathematical model for predicting radon activity was developed using multiple linear regression. Results. A prototype mathematical model was developed that can predict radon activity based on temperature and humidity with a reliability of approximately 71 %. Validation of the model using independent data showed close agreement between the forecast and actual measured values. It was determined that additional factors, such as atmospheric pressure, soil moisture, and seismic activity, must be considered to improve forecast accuracy. Work has begun on integrating these parameters into the model. The model has also been implemented as software.
URI: https://dspace.ncfu.ru/handle/123456789/32991
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