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  • 1
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    Evaluation of tectonically enhanced radon in fault zones by quantification of the radon activity index (2023)
    Nature PG
    Details
    Publication Date: 2023-03-09
    Description: This work highlights the importance of the Geogenic Radon Potential (GRP) component originated by degassing processes in fault zones. This Tectonically Enhanced Radon (TER) can increase radon concentration in soil gas and the inflow of radon in the buildings (Indoor Radon Concentrations, IRC). Although tectonically related radon enhancement is known in areas characterised by active faults, few studies have investigated radon migration processes in non-active fault zones. The Pusteria Valley (Bolzano, north-eastern Italy) represents an ideal geological setting to study the role of a non-seismic fault system in enhancing the geogenic radon. Here, most of the municipalities are characterised by high IRC. We performed soil gas surveys in three of these municipalities located along a wide section of the non-seismic Pusteria fault system characterised by a dense network of faults and fractures. Results highlight the presence of high Rn concentrations (up to 800 kBq·m-3) with anisotropic spatial patterns oriented along the main strike of the fault system. We calculated a Radon Activity Index (RAI) along north-south profiles across the Pusteria fault system and found that TER is linked to high fault geochemical activities. This evidence confirms that TER constitutes a significant component of GRP also along non-seismic faults.
    Description: Published
    Description: 21586
    Description: 6A. Geochimica per l'ambiente e geologia medica
    Description: JCR Journal
    Keywords: Radon ; Soil Gas ; Geochemistry ; Radon Hazard
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
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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) (2022)
    Elsevier
    Details
    Publication Date: 2022-05-24
    Description: 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.
    Description: Published
    Description: 152064
    Description: 6A. Geochimica per l'ambiente e geologia medica
    Description: JCR Journal
    Keywords: Euganean Hills ; Geogenic Radon Potential ; Geostatistics ; Natural radioactivity ; Radon ; Regression kriging ; 04. Solid Earth
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 3
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    Rock deformation vs. radon emission: some constraints from shear stress-controlled experiments (2024)
    Nature PG
    Details
    Publication Date: 2024-04-10
    Description: Numerous field and laboratory studies have been conducted to investigate the relationship between radon variation and seismic events, as well as the complex link between radon emission and rock deformation mechanisms. However, a clear understanding of this correspondence and systematic observations of these phenomena are still lacking, and recent experimental studies have yet to yield conclusive results. In this study, we investigate the possible relationships between radon migration dynamics and rock deformation at the micro-scale through laboratory experiments using the SHIVA apparatus under shear stress-controlled conditions and simultaneous high-resolution radon measurements. We studied the behaviour of three different lithologies to show that radon emission varies in response to rock deformation and this variation is highly dependent on the mineralogy and microstructure. This study represents the first attempt to define radon gas as an indicator of transient and rapid rock deformation at the micro-scale.
    Description: Published
    Description: 16399
    Description: OST4 Descrizione in tempo reale del terremoto, del maremoto, loro predicibilità e impatto
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 4
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    A new perspective in radon risk assessment: Mapping the geological hazard as a first step to define the collective radon risk exposure (2024)
    Elsevier
    Details
    Publication Date: 2024-05-03
    Description: Radon is a radioactive gas and a major source of ionizing radiation exposure for humans. Consequently, it can pose serious health threats when it accumulates in confined environments. In Europe, recent legislation has been adopted to address radon exposure in dwellings; this law establishes national reference levels and guidelines for defining Radon Priority Areas (RPAs). This study focuses on mapping the Geogenic Radon Potential (GRP) as a foundation for identifying RPAs and, consequently, assessing radon risk in indoor environments. Here, GRP is proposed as a hazard indicator, indicating the potential for radon to enter buildings from geological sources. Various approaches, including multivariate geospatial analysis and the application of artificial intelligence algorithms, have been utilised to generate continuous spatial maps of GRP based on point measurements. In this study, we employed a robust multivariate machine learning algorithm (Random Forest) to create the GRP map of the central sector of the Pusteria Valley, incorporating other variables from census tracts such as land use as a vulnerability factor, and population as an exposure factor to create the risk map. The Pusteria Valley in northern Italy was chosen as the pilot site due to its well-known geological, structural, and geochemical features. The results indicate that high Rn risk areas are associated with high GRP values, as well as residential areas and high population density. Starting with the GRP map (e.g., Rn hazard), a new geological-based definition of the RPAs is proposed as fundamental tool for mapping Collective Radon Risk Areas in line with the main objective of European regulations, which is to differentiate them from Individual Risk Areas.
    Description: Published
    Description: 169569
    Description: OSA5: Energia e georisorse
    Description: JCR Journal
    Keywords: Collective Radon Risk Areas; Geogenic Radon Potential; Machine learning; Pusteria Valley; Radon risk
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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