title: Geostatistical simulations for radon indoor with a nested model including the housing factor.
abstract: The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging.
authors.affiliation: Department of Physics, University of Trieste, Italy. Electronic address: shinacronistic@gmail.com.
authors.forename: C
authors.initials: C
authors.lastname: Cafaro
authors.affiliation: ARPA-FVG, Natural Radioactivity Lab, Italy.
authors.forename: C
authors.initials: C
authors.lastname: Giovani
authors.affiliation: ARPA-FVG, Natural Radioactivity Lab, Italy.
authors.forename: M
authors.initials: M
authors.lastname: Garavaglia
mesh_terms: D000396:Air Pollutants, Radioactive / Q000032:analysis*; D016902:Air Pollution, Indoor / Q000032:analysis*; D006798:Housing; D011834:Radiation Monitoring / Q000379:methods*; D011886:Radon / Q000032:analysis*; D062206:Spatial Analysis
chemical_list: D000396:Air Pollutants, Radioactive; D011886:Radon
keywords: Co-kriging; Geostatistics; Housing; Radon; Risk