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http://hdl.handle.net/2122/13478
Authors: | Giustini, Francesca* Ciotoli, Giancarlo* Rinaldini, Alessio* Ruggiero, Livio* Voltaggio, Mario* |
Title: | Mapping the geogenic radon potential and radon risk by using Empirical Bayesian Kriging regression: A case study from a volcanic area of central Italy | Journal: | Science of The Total Environment | Series/Report no.: | /661 (2019) | Issue Date: | 15-Jan-2019 | DOI: | 10.1016/j.scitotenv.2019.01.146 | Abstract: | 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. |
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