Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems

Abstract Radon exhalation is a natural process by which atoms of the radioactive gas radon diffuse in the soil and then exhale to an indoor and/or outdoor environment. High radon concentration levels, possibly from high radon exhalation rate levels, can generate an impact on public health and enviro...

Full description

Saved in:
Bibliographic Details
Main Authors: B. Pérez, L. C. Stieff, R. E. Ponce-Amanca, C. J. Guevara-Pillaca, D. Palacios
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-08108-w
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849334548189413376
author B. Pérez
L. C. Stieff
R. E. Ponce-Amanca
C. J. Guevara-Pillaca
D. Palacios
author_facet B. Pérez
L. C. Stieff
R. E. Ponce-Amanca
C. J. Guevara-Pillaca
D. Palacios
author_sort B. Pérez
collection DOAJ
description Abstract Radon exhalation is a natural process by which atoms of the radioactive gas radon diffuse in the soil and then exhale to an indoor and/or outdoor environment. High radon concentration levels, possibly from high radon exhalation rate levels, can generate an impact on public health and environmental safety, particularly in agricultural areas where prolonged exposure may affect nearby populations. While studies have examined radon exhalation, few have focused on modeling its behavior in agricultural settings or identifying key environmental and soil parameters that influence its variation. This study addresses this gap by applying Artificial Neural Network (ANN) models and Monte Carlo methods. Three distinct approaches were developed based on radon exhalation measurements from four Peruvian agricultural regions, incorporating meteorological and soil physicochemical data. First, the ANN model determined environmental factors affecting radon exhalation, achieving $$\hbox {R}^{2}$$ values of 0.7949 (training) and 0.7656 (validation). Second, simulations analyzed radon diffusion under varying wind conditions, assessing dispersion risks. Third, gamma radiation measurements quantified radon progeny contributions ( $$2.82 \times 10^{-4} \pm 1.15 \times 10^{-5}$$ efficiency) for soil moisture detection. This integrated methodology advances understanding of agricultural radon dynamics, supporting improved radiological safety protocols and soil monitoring techniques.
format Article
id doaj-art-8149ad69bd354cb98fe2c5e240d38ec0
institution Kabale University
issn 2045-2322
language English
publishDate 2025-07-01
publisher Nature Portfolio
record_format Article
series Scientific Reports
spelling doaj-art-8149ad69bd354cb98fe2c5e240d38ec02025-08-20T03:45:32ZengNature PortfolioScientific Reports2045-23222025-07-0115112010.1038/s41598-025-08108-wEdaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystemsB. Pérez0L. C. Stieff1R. E. Ponce-Amanca2C. J. Guevara-Pillaca3D. Palacios4Departamento de Ciencias, Pontificia Universidad Católica del PerúRad Elec Inc.Investigación, Desarrollo e Innovación, Anphysrad SACInvestigación, Desarrollo e Innovación, Anphysrad SACDepartamento de Ciencias, Pontificia Universidad Católica del PerúAbstract Radon exhalation is a natural process by which atoms of the radioactive gas radon diffuse in the soil and then exhale to an indoor and/or outdoor environment. High radon concentration levels, possibly from high radon exhalation rate levels, can generate an impact on public health and environmental safety, particularly in agricultural areas where prolonged exposure may affect nearby populations. While studies have examined radon exhalation, few have focused on modeling its behavior in agricultural settings or identifying key environmental and soil parameters that influence its variation. This study addresses this gap by applying Artificial Neural Network (ANN) models and Monte Carlo methods. Three distinct approaches were developed based on radon exhalation measurements from four Peruvian agricultural regions, incorporating meteorological and soil physicochemical data. First, the ANN model determined environmental factors affecting radon exhalation, achieving $$\hbox {R}^{2}$$ values of 0.7949 (training) and 0.7656 (validation). Second, simulations analyzed radon diffusion under varying wind conditions, assessing dispersion risks. Third, gamma radiation measurements quantified radon progeny contributions ( $$2.82 \times 10^{-4} \pm 1.15 \times 10^{-5}$$ efficiency) for soil moisture detection. This integrated methodology advances understanding of agricultural radon dynamics, supporting improved radiological safety protocols and soil monitoring techniques.https://doi.org/10.1038/s41598-025-08108-wRadon exhalationEnvironmental parametersSoil characteristicsArtificial neural networksMonte Carlo methodsPublic health risk
spellingShingle B. Pérez
L. C. Stieff
R. E. Ponce-Amanca
C. J. Guevara-Pillaca
D. Palacios
Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems
Scientific Reports
Radon exhalation
Environmental parameters
Soil characteristics
Artificial neural networks
Monte Carlo methods
Public health risk
title Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems
title_full Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems
title_fullStr Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems
title_full_unstemmed Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems
title_short Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in Peruvian agroecosystems
title_sort edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in peruvian agroecosystems
topic Radon exhalation
Environmental parameters
Soil characteristics
Artificial neural networks
Monte Carlo methods
Public health risk
url https://doi.org/10.1038/s41598-025-08108-w
work_keys_str_mv AT bperez edaphicandmeteorologicalparametersasdeterminantsofradonexhalationanditsenvironmentalimplicationinperuvianagroecosystems
AT lcstieff edaphicandmeteorologicalparametersasdeterminantsofradonexhalationanditsenvironmentalimplicationinperuvianagroecosystems
AT reponceamanca edaphicandmeteorologicalparametersasdeterminantsofradonexhalationanditsenvironmentalimplicationinperuvianagroecosystems
AT cjguevarapillaca edaphicandmeteorologicalparametersasdeterminantsofradonexhalationanditsenvironmentalimplicationinperuvianagroecosystems
AT dpalacios edaphicandmeteorologicalparametersasdeterminantsofradonexhalationanditsenvironmentalimplicationinperuvianagroecosystems