Bertolo A, Bigliotto C, Giovani C, Garavaglia M, Spinella M, Verdi L, Pegoretti S
ARPA Veneto, Dipartimento di Padova, via Ospedale 22, 35121 Padova, Italy.
Radiat Prot Dosimetry. 2009 Dec;137(3-4):318-23. doi: 10.1093/rpd/ncp252. Epub 2009 Nov 17.
The study of spatial distribution of the indoor radon has assumed in the last years a lot of interest. The geostatistical techniques turn out to be particularly promising. The present work presents the results of a study where around 4000 indoor radon data from Veneto, Friuli Venezia-Giulia and Alto Adige, collected during the sampling campaigns performed in dwellings and in schools, have been analyzed. After the definition of the common data set, the study of the spatial distribution of the phenomenon has been performed by examining the experimental variograms. Declustering techniques have been applied. Predictive maps were defined by using simulation techniques; they allow to determine the probabilities of exceeding defined concentration levels, the 'radon-prone' areas. Systematic results regarding the validation of these maps are reported. This methodological study indicates how it is possible to understand the geographical variability of the phenomenon, trying to find out correlations among indoor radon, geological characteristics (i.e. lithology, morphology, tectonics, soil gas) and building-specific features, which can significantly influence radon concentrations.
近年来，室内氡气空间分布的研究备受关注。地质统计学技术显示出特别广阔的前景。本研究展示了一项研究的结果，该研究分析了在住宅和学校进行的采样活动期间，从威尼托、弗留利-威尼斯朱利亚和上阿迪杰收集的约4000个室内氡气数据。在定义了公共数据集之后，通过检查实验变差函数对该现象的空间分布进行了研究。应用了去聚类技术。通过使用模拟技术定义了预测图；它们可以确定超过规定浓度水平的概率，即“氡气易发生”区域。报告了关于这些地图验证的系统结果。这项方法学研究表明，如何能够理解该现象的地理变异性，试图找出室内氡气、地质特征（即岩性、形态、构造、土壤气体）和建筑物特定特征之间的相关性，这些因素会显著影响氡气浓度。
