Kirchner G, Steiner M, Zähringer M
Bundesamt für Strahlenschutz, Salzgitter, Germany.
J Environ Radioact. 2009 Jun;100(6):484-8. doi: 10.1016/j.jenvrad.2009.03.009. Epub 2009 Apr 19.
Measurements of low-level radioactivity often give results of the order of the detection limit. For many applications, interest is not only in estimating activity concentrations of a single radioactive isotope, but focuses on multi-isotope analyses, which often enable inference on the source of the activity detected (e.g. from activity ratios). Obviously, such conclusions become questionable if the measurement merely gives a detection limit for a specific isotope. This is particularly relevant if the presence of an isotope, which shows a low signal only (e.g. due to a short half-life or a small transition probability), is crucial for gaining the information of interest. This paper discusses a new approach which has the potential to solve these problems. Using Bayesian statistics, a method is presented which allows statistical inference on nuclide ratios taking into account both prior knowledge and all information collected from the measurements. It is shown that our method allows quantitative conclusion to be drawn if counts of single isotopes are low or become even negative after background subtraction. Differences to the traditional statistical approach of specifying decision thresholds or detection limits are highlighted. Application of this new approach is illustrated by a number of examples of environmental low-level radioactivity measurements. The capabilities of our approach for spectrum interpretation and source identification are demonstrated with real spectra from air filters, sewage sludge and soil samples.
低水平放射性测量的结果往往处于检测限的量级。对于许多应用而言,人们不仅关注单一放射性同位素活度浓度的估算,还侧重于多同位素分析,这种分析通常能够推断出所检测到的活度来源(例如通过活度比)。显然,如果测量仅仅给出特定同位素的检测限,那么这样的结论就会受到质疑。如果仅显示低信号的同位素(例如由于半衰期短或跃迁概率小)的存在对于获取感兴趣的信息至关重要,这一点就尤为相关。本文讨论了一种有可能解决这些问题的新方法。利用贝叶斯统计,提出了一种方法,该方法在考虑先验知识和从测量中收集到的所有信息的情况下,允许对核素比率进行统计推断。结果表明,如果单个同位素的计数较低,或者在扣除本底后甚至变为负数,我们的方法也能得出定量结论。文中强调了与指定决策阈值或检测限的传统统计方法的差异。通过一些环境低水平放射性测量的例子说明了这种新方法的应用。利用空气过滤器、污水污泥和土壤样品的真实能谱展示了我们的方法在能谱解释和源识别方面的能力。