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The assessment of local geological factors for the construction of a Geogenic Radon Potential map using regression kriging. A case study from the Euganean Hills volcanic district (Italy)
- Source :
- Science of the total environment 808 (2022): 1–16. doi:10.1016/j.scitotenv.2021.152064, info:cnr-pdr/source/autori:Coletti C, Ciotoli G, Benà E, Brattich E, Cinelli G, Galgaro A, Massironi M, Mazzoli C, Mostacci D, Morozzi P, Mozzi P, Nava J, Ruggiero L, Sciarra A, Tositti L, Sassi R/titolo:The assessment of local geological factors for the construction of a Geogenic Radon Potential map using regression kriging. A case study from the Euganean Hills volcanic district (Italy)./doi:10.1016%2Fj.scitotenv.2021.152064/rivista:Science of the total environment/anno:2022/pagina_da:1/pagina_a:16/intervallo_pagine:1–16/volume:808
- Publication Year :
- 2022
-
Abstract
- The assessment of potential radon-hazardous environments is nowadays a critical issue in planning, monitoring, and developing appropriate mitigation strategies. Although some geological structures (e.g., fault systems) and other geological factors (e.g., radionuclide content, soil organic or rock weathering) can locally affect the radon occurrence, at the basis of a good implementation of radon-safe systems, optimized modelling at territorial scale is required. The use of spatial regression models, adequately combining different types of predictors, represents an invaluable tool to identify the relationships between radon and its controlling factors as well as to construct Geogenic Radon Potential (GRP) maps of an area. In this work, two GRP maps were developed based on field measurements of soil gas radon and thoron concentrations and gamma spectrometry of soil and rock samples of the Euganean Hills (northern Italy) district. A predictive model of radon concentration in soil gas was reconstructed taking into account the relationships among the soil gas radon and seven predictors: terrestrial gamma dose radiation (TGDR), thoron (220Rn), fault density (FD), soil permeability (PERM), digital terrain model (SLOPE), moisture index (TMI), heat load index (HLI). These predictors allowed to elaborate local spatial models by using the Empirical Bayesian Regression Kriging (EBRK) in order to find the best combination and define the GRP of the Euganean Hills area. A second GRP map based on the Neznal approach (GRPNEZ) has been modelled using the TGDR and 220Rn, as predictors of radon concentration, and FD as predictor of soil permeability. Then, the two GRP maps have been compared. Results highlight that the radon potential is mainly driven by the bedrock type but the presence of fault systems and topographic features play a key role in radon migration in the subsoil and its exhalation at the soil/atmosphere boundary.
- Subjects :
- Environmental Engineering
Euganean Hills
chemistry.chemical_element
Radon
Soil science
Settore GEO/09 - Georisorse Miner.Appl.Mineral.-Petrogr.per l'amb.e i Beni Cul
Fault (geology)
Geogenic Radon Potential
Geostatistics
Natural radioactivity
Regression kriging
Kriging
Radiation Monitoring
Environmental Chemistry
Soil Pollutants, Radioactive
Digital elevation model
Waste Management and Disposal
Subsoil
geography
Spatial Analysis
geography.geographical_feature_category
Soil gas
Bedrock
Bayes Theorem
Euganean Hills, Geogenic Radon Potential, Geostatistics, Natural radioactivity, Radon, Regression kriging
Pollution
chemistry
Air Pollutants, Radioactive
Radon, natural radioactivity, Geogenic Radon Potential, Regression kriging, Geostatistics, Euganean Hills
Environmental science
Scale (map)
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Science of the total environment 808 (2022): 1–16. doi:10.1016/j.scitotenv.2021.152064, info:cnr-pdr/source/autori:Coletti C, Ciotoli G, Benà E, Brattich E, Cinelli G, Galgaro A, Massironi M, Mazzoli C, Mostacci D, Morozzi P, Mozzi P, Nava J, Ruggiero L, Sciarra A, Tositti L, Sassi R/titolo:The assessment of local geological factors for the construction of a Geogenic Radon Potential map using regression kriging. A case study from the Euganean Hills volcanic district (Italy)./doi:10.1016%2Fj.scitotenv.2021.152064/rivista:Science of the total environment/anno:2022/pagina_da:1/pagina_a:16/intervallo_pagine:1–16/volume:808
- Accession number :
- edsair.doi.dedup.....cd03a7b18baf6a4e4d02e94130a194b1