Exploring soil radon (Rn) concentrations and their connection to geological and meteorological factors.

Autor: Muhammad A; Department of Physics and Material Science, College of Arts and Sciences, Qatar University, P. O. Box 2713, Doha, Qatar., Danbatta SJ; Software Engineering Department, Faculty of Engineering and Natural Sciences, Uskudar University, PK: 34662, Istanbul, Turkey. salimdambatta@gmail.com., Muhammad IY; Theoretical and Computational Physics (TCP) Group, Department of Physics, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok, 10140, Thailand., Nasidi II; Department of Physics, Faculty of Science, Fırat University, TR-23119, Elazig, Turkey.
Jazyk: angličtina
Zdroj: Environmental science and pollution research international [Environ Sci Pollut Res Int] 2024 Jan; Vol. 31 (1), pp. 565-578. Date of Electronic Publication: 2023 Nov 28.
DOI: 10.1007/s11356-023-31237-6
Abstrakt: The relationship between soil radon and meteorological parameters in a region can provide insight into natural processes occurring between the lithosphere and the atmosphere. Understanding this relationship can help models establish more realistic results, rather than depending on theoretical consequences. Radon variation can be complicated to model due to the various physical variables which can affect it, posing a limitation in atmospheric studies. To predict Rn variation from meteorological parameters, a hybrid mod el called multiANN, which is a combination of multi-regression and artificial neural network (ANN) models, is established. The model was trained with 70% of the data and tested on the remaining 30%, and its robustness was tested using the Monte-Carlo method. The regions with low performance are identified and possibly related to seismic events. This model can be a good candidate for predicting Rn concentrations from meteorological parameters and establishing the lower boundary conditions in seismo-ionospheric coupling models.
(© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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