A geostatistical approach for mapping the geogenic soil gas radon potential in a south Italy area (Abstract/Poster in convegno)

Type
Label
  • A geostatistical approach for mapping the geogenic soil gas radon potential in a south Italy area (Abstract/Poster in convegno) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Alternative label
  • Buttafuoco G., Tallarico A., Falcone G., Catalano E. (2007)
    A geostatistical approach for mapping the geogenic soil gas radon potential in a south Italy area
    in Pedometrics 2007. Biannual Conference of Commission 1.5 Pedometrics, Division 1 of the International Union of Soil Sciences (IUSS), Tubingen, Germany, August 27 - 30 2007
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Buttafuoco G., Tallarico A., Falcone G., Catalano E. (literal)
Pagina inizio
  • 63 (literal)
Pagina fine
  • 63 (literal)
Note
  • Abstract (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR - Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFOM), Rende (Cosenza) Università della Calabria, Rende (Cosenza) CNR - IRPI, Rende (Cosenza) (literal)
Titolo
  • A geostatistical approach for mapping the geogenic soil gas radon potential in a south Italy area (literal)
Abstract
  • Radon is a natural radioactive gas emanated constantly in small amounts from the Earth to the atmosphere. Many scientists use to measure outdoor soil gas radon concentrations to assess the geogenic radon potential because it is the main source for indoor radon concentrations independent on the construction features of building. Spatial distribution of soil gas radon concentrations has become an important issue in terms of radiological protection because constitute a serious human health hazard. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping its spatial distribution. Stochastic simulation is a development of geostatistics and estimates the conditional cumulative distribution functions at each location. Statistical information deriving from stochastic simulation allows to estimate the probability that each pixel exceeds a threshold value and to produce the probability map of high radon concentrations in the soil gas. The main aim of this paper was to explore the spatial structure of soil gas radon concentration in a south Italy area and mapping the geogenic soil gas radon potential. Another aim was mapping the risk of occurrence of high soil radon gas concentration. The experimental area was located in the Catanzaro-Lamezia plain (south Italy) with a surface of about 1105 km2. It is a graben bordered by E-W trending normal faults and constitutes the central part of the Calabro-Sicula rift-zone. Measurement of radon concentration were made at 4420 points collecting soil gas radon into Lucas cells and then measuring their alpha activity in the laboratory. Measurements were made in July 2004 and the samples were collected as uniformly as possible with an average sampling density of 4 samples per km2. To reduce the influence of few high values of soil gas radon a Multi-Gaussian approach was used. An isotropic model was fitted to the experimental variogram including three basic structures: 1) a nugget effect; 2) a spherical model with a short range=3.78 km and 3) a spherical model with a long range=23.90 km. Stochastic simulation was used to map the risk of occurrence of high soil radon gas concentration: 500 alternative equi-probable images of the unknown radon concentration were generated using the conditional sequential Gaussian simulation algorithm. Counting the number of times that each pixel exceeded the threshold value and converting the sum to a proportion we produced the probability map of exceedence. We used as threshold value the upper quartile of the data distribution function because in Italy no radon level of risk in outdoor air exists. Map of soil gas radon concentration and probability map reflected the impact of fractures and faults on the spatial distribution of radon concentration because they act as a preferential way for gases migration. The results showed that the highest radon values occur preferentially along elongated zones similar to the most representative trends obtained by geomorphological and mesostructural analyses, i.e. E-W trends and, secondarily, NW-SE orientations. (literal)
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