『Abstract
　Spatial distribution of concentrations of radon gas in the soil is important for defining high risk areas because geogenic radon is the major potential source of indoor radon concentrations regardless of the construction features of buildings. An area of southern Italy (Catanzaro-Lamezia plain\9 was surveyed to study the relationship between radon gas concentrations in the soil, geology and structural patterns. Moreover, the uncertainty associated with the mapping of geogenic radon in soil gas was assessed. Multi-Gaussian kriging was used to map the geogenic soil gas radon concentration, while conditional sequential Gaussian simulation was used to yield a series of stochastic images representing equally probable spatial distributions of soil radon across the study area. The stochastic images generated by the sequential Gaussian simulation were used to assess the uncertainty associated with the mapping of geogenic radon in the soil and they were combined to calculate the probability of exceeding a specified critical threshold that might cause concern for human health. The study showed that emanation of radon gas radon was also dependent on geological structure and lithology. The results have provided insight into the influence of basement geochemistry on the spatial distribution of radon levels at the soil/atmosphere interface and suggested that knowledge of the geology of the area may be helpful in understanding the distribution pattern of radon near the earth's surface.

Keywords: Radon mapping; Uncertainty; Stochastic simulation; Radon gas in soil; Faults』

Introduction
Materials and methods
　The study area: geological and structural setting
　Sampling radon gas in soil
　Geostatistical approach
　　Variogram estimation and modeling
　　Multi-Gaussian approach
　　Multi-Gaussian kriging
　　Stochastic simulation
　　Probabilistic summary of the set of simulations
　　Decision-making in the presence of uncertainty
Results and discussion
Conclusions
Acknowledgements
References