Cinelli Giorgia, Tondeur François
European Commission, Joint Research Centre (JRC), Institute for Transuranium Elements (ITU), Nuclear Security Unit, Via Enrico Fermi 2749, 21027 Ispra, VA, Italy.
ISIB, Haute Ecole P.-H. Spaak, Rue Royale 150, 1000 Brussels, Belgium.
J Environ Radioact. 2015 May;143:100-109. doi: 10.1016/j.jenvrad.2015.02.014. Epub 2015 Mar 9.
The deviations of the distribution of Belgian indoor radon data from the log-normal trend are examined. Simulated data are generated to provide a theoretical frame for understanding these deviations. It is shown that the 3-component structure of indoor radon (radon from subsoil, outdoor air and building materials) generates deviations in the low- and high-concentration tails, but this low-C trend can be almost completely compensated by the effect of measurement uncertainties and by possible small errors in background subtraction. The predicted low-C and high-C deviations are well observed in the Belgian data, when considering the global distribution of all data. The agreement with the log-normal model is improved when considering data organised in homogeneous geological groups. As the deviation from log-normality is often due to the low-C tail for which there is no interest, it is proposed to use the log-normal fit limited to the high-C half of the distribution. With this prescription, the vast majority of the geological groups of data are compatible with the log-normal model, the remaining deviations being mostly due to a few outliers, and rarely to a "fat tail". With very few exceptions, the log-normal modelling of the high-concentration part of indoor radon data is expected to give reasonable results, provided that the data are organised in homogeneous geological groups.
研究了比利时室内氡数据分布与对数正态趋势的偏差。生成模拟数据以提供理解这些偏差的理论框架。结果表明,室内氡的三组分结构(来自地下土壤、室外空气和建筑材料的氡)在低浓度和高浓度尾部产生偏差,但这种低浓度趋势几乎可以完全被测量不确定度的影响以及背景扣除中可能存在的小误差所补偿。当考虑所有数据的全局分布时,比利时数据中很好地观察到了预测的低浓度和高浓度偏差。当考虑按均匀地质组组织的数据时,与对数正态模型的一致性得到改善。由于偏离对数正态性通常是由于低浓度尾部,而人们对此并不感兴趣,因此建议使用仅限于分布高浓度一半的对数正态拟合。按照这个规定,绝大多数地质数据组与对数正态模型兼容,其余偏差主要是由于少数异常值,很少是由于“厚尾”。几乎没有例外,只要数据按均匀地质组组织,室内氡数据高浓度部分的对数正态建模预计会给出合理的结果。