Exploring statistical and machine learning techniques to identify factors influencing indoor radon concentration.

Building characteristics Indoor radon Lithology Logistic regression Pedology Random forest

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
20 Dec 2023
Historique:
received: 14 08 2023
accepted: 10 09 2023
medline: 15 9 2023
pubmed: 15 9 2023
entrez: 14 9 2023
Statut: ppublish

Résumé

Radon is a radioactive gas with a carcinogenic effect. The malign effect on human health is, however, mostly influenced by the level of exposure. Dangerous exposure occurs predominantly indoors where the level of indoor radon concentration (IRC) is, in its turn, influenced by several factors. The current study aims to investigate the combined effects of geology, pedology, and house characteristics on the IRC based on 3132 passive radon measurements conducted in Romania. Several techniques for evaluating the impact of predictors on the dependent variable were used, from univariate statistics to artificial neural network and random forest regressor (RFR). The RFR model outperformed the other investigated models in terms of R

Identifiants

DOI: 10.1016/j.scitotenv.2023.167024 PMID: 37709073
pubmed: 37709073
pii: S0048-9697(23)05649-8
doi: 10.1016/j.scitotenv.2023.167024
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

167024

Informations de copyright

Copyright © 2023. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest Dicu Tiberius reports financial support was provided by Babeș-Bolyai University Faculty of Environmental Science and Engineering.

Auteurs

T Dicu (T)

"Constantin Cosma" Radon Laboratory (LiRaCC), Faculty of Environmental Science and Engineering, "Babeş-Bolyai" University, Fântânele Street, no. 30, Cluj-Napoca, Romania.

A Cucoş (A)

"Constantin Cosma" Radon Laboratory (LiRaCC), Faculty of Environmental Science and Engineering, "Babeş-Bolyai" University, Fântânele Street, no. 30, Cluj-Napoca, Romania. Electronic address: alexandra.cucos@ubbcluj.ro.

M Botoş (M)

Faculty of Civil Engineering, Technical University of Cluj-Napoca, C. Daicoviciu Street, no. 15, Cluj-Napoca, Romania.

B Burghele (B)

SC Radon Action SRL, Str. Mărginaşă 51, 400371 Cluj-Napoca, Romania.

Ş Florică (Ş)

"Constantin Cosma" Radon Laboratory (LiRaCC), Faculty of Environmental Science and Engineering, "Babeş-Bolyai" University, Fântânele Street, no. 30, Cluj-Napoca, Romania.

C Baciu (C)

"Constantin Cosma" Radon Laboratory (LiRaCC), Faculty of Environmental Science and Engineering, "Babeş-Bolyai" University, Fântânele Street, no. 30, Cluj-Napoca, Romania.

B Ştefan (B)

"Constantin Cosma" Radon Laboratory (LiRaCC), Faculty of Environmental Science and Engineering, "Babeş-Bolyai" University, Fântânele Street, no. 30, Cluj-Napoca, Romania.

R Bălc (R)

"Constantin Cosma" Radon Laboratory (LiRaCC), Faculty of Environmental Science and Engineering, "Babeş-Bolyai" University, Fântânele Street, no. 30, Cluj-Napoca, Romania.

Classifications MeSH