A new perspective in radon risk assessment: Mapping the geological hazard as a first step to define the collective radon risk exposure.

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.

Evaluation of tectonically enhanced radon in fault zones by quantification of the radon activity index.

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.

Radon Hazard in Central Italy: Comparison among Areas with Different Geogenic Radon Potential.

Radon (222Rn) is a natural radioactive gas formed in rocks and soil by the decay of its parent nuclide (238-Uranium). The rate at which radon migrates to the surface, be it along faults or directly emanated from shallow soil, represents the Geogenic Radon Potential (GRP) of an area. Considering that the GRP is often linked to indoor radon risk levels, we have conducted multi-disciplinary research to: (i) define local GRPs and investigate their relationship with associated indoor Rn levels; (ii) evaluate inhaled radiation dosages and the associated risk to the inhabitants; and (iii) define radon priority areas (RPAs) as required by the Directive 2013/59/Euratom. In the framework of the EU-funded LIFE-Respire project, a large amount of data (radionuclide content, soil gas samples, terrestrial gamma, indoor radon) was collected from three municipalities located in different volcanic districts of the Lazio region (central Italy) that are characterised by low to high GRP. Results highlight the positive correlation between the radionuclide content of the outcropping rocks, the soil Rn concentrations and the presence of high indoor Rn values in areas with medium to high GRP. Data confirm that the Cimini-Vicani area has inhalation dosages that are higher than the reference value of 10 mSv/y.

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).

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.

Mapping the geogenic radon potential and radon risk by using Empirical Bayesian Kriging regression: A case study from a volcanic area of central Italy.

A detailed geochemical study on radon related to local geology was carried out in the municipality of Celleno, a little settlement located in the eastern border of the Quaternary Vulsini volcanic district (central Italy). This study included soil-gas and terrestrial gamma dose rate survey, laboratory analyses of natural radionuclides (238U, 226Ra, 232Th, 40K) activity in rocks and soil samples, and indoor radon measurements carried out in selected private and public dwellings. Soil-gas radon and carbon dioxide concentrations range from 6 to 253 kBq/m3 and from 0.3 to11% v/v, respectively. Samples collected from outcropping volcanic and sedimentary rocks highlight: significant concentrations of 238U, 226Ra and 40K for lavas (151, 150 and 1587 Bq/kg, respectively), low concentrations for tuffs (126, 123 and 987 Bq/kg, respectively), and relatively low for sedimentary rocks (108, 109 and 662 Bq/kg, respectively). Terrestrial gamma dose rate values range between 0.130 and 0.417 µSv/h, being in good accordance with the different bedrock types. Indoor radon activity ranges from 162 to 1044 Bq/m3; the calculated values of the annual effective dose varied from 4.08 and 26.31 mSv/y. Empirical Bayesian Kriging Regression (EBKR) was used to develop the Geogenic Radon Potential (GRP) map. EBKR provided accurate predictions of data on a local scale developing a spatial regression model in which soil-gas radon concentrations were considered as the response variable; several proxy variables, derived from geological, topographic and geochemical data, were used as predictors. Risk prediction map for indoor radon was tentatively produced using the Gaussian Geostatistical Simulation and a soil-indoor transfer factor was defined for a 'standard' dwelling (i.e., a dwelling with well-defined construction properties). This approach could be successfully used in the case of homogeneous building characteristics and territory with uniform geological characteristics.