Kendall G M, Chernyavskiy P, Appleton J D, Miles J C H, Wakeford R, Athanson M, Vincent T J, McColl N P, Little M P
Cancer Epidemiology Unit, NDPH, University of Oxford, Richard Doll Building, Old Road Campus, Headington, Oxford, OX3 7LF, UK.
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, DHHS, NIH, Bethesda, MD, 20892-9778, USA.
Radiat Environ Biophys. 2018 Nov;57(4):321-347. doi: 10.1007/s00411-018-0752-7. Epub 2018 Aug 21.
Gamma radiation from naturally occurring sources (including directly ionizing cosmic-rays) is a major component of background radiation. An understanding of the magnitude and variation of doses from these sources is important, and the ability to predict them is required for epidemiological studies. In the present paper, indoor measurements of naturally occurring gamma-rays at representative locations in Great Britain are summarized. It is shown that, although the individual measurement data appear unimodal, the distribution of gamma-ray dose-rates when averaged over relatively small areas, which probably better represents the underlying distribution with inter-house variation reduced, appears bimodal. The dose-rate distributions predicted by three empirical and geostatistical models are also bimodal and compatible with the distributions of the areally averaged dose-rates. The distribution of indoor gamma-ray dose-rates in the UK is compared with those in other countries, which also tend to appear bimodal (or possibly multimodal). The variation of indoor gamma-ray dose-rates with geology, socio-economic status of the area, building type, and period of construction are explored. The factors affecting indoor dose-rates from background gamma radiation are complex and frequently intertwined, but geology, period of construction, and socio-economic status are influential; the first is potentially most influential, perhaps, because it can be used as a general proxy for local building materials. Various statistical models are tested for predicting indoor gamma-ray dose-rates at unmeasured locations. Significant improvements over previous modelling are reported. The dose-rate estimates generated by these models reflect the imputed underlying distribution of dose-rates and provide acceptable predictions at geographical locations without measurements.
来自自然源（包括直接电离的宇宙射线）的伽马辐射是背景辐射的主要组成部分。了解这些源的剂量大小和变化很重要，流行病学研究需要具备预测这些剂量的能力。在本文中，总结了在英国代表性地点对天然伽马射线的室内测量结果。结果表明，尽管单个测量数据呈现单峰分布，但在相对较小区域上平均后的伽马射线剂量率分布似乎是双峰的，这种分布可能更能代表潜在分布，同时减少了房屋间的差异。由三种经验模型和地质统计模型预测的剂量率分布也是双峰的，并且与面积平均剂量率的分布相符。将英国室内伽马射线剂量率的分布与其他国家的进行了比较，其他国家的分布也往往呈现双峰（或可能是多峰）。探讨了室内伽马射线剂量率随地质、该地区社会经济状况、建筑类型和建造时期的变化。影响背景伽马辐射室内剂量率的因素复杂且常常相互交织，但地质、建造时期和社会经济状况具有影响力；也许第一个因素潜在影响最大，因为它可以用作当地建筑材料的一般替代指标。测试了各种统计模型以预测未测量地点的室内伽马射线剂量率。报告了相对于以前建模的显著改进。这些模型生成的剂量率估计反映了推算的剂量率潜在分布，并在没有测量的地理位置提供了可接受的预测。
