NDLI: Levels of naturally occurring gamma radiation measured in British homes and their prediction in particular residences

Content Provider	Springer Nature Link
Author	Kendall, G. M. Wakeford, R. Athanson, M. Vincent, T. J. Carter, E. J. McColl, N. P. Little, M. P.
Copyright Year	2016
Abstract	Gamma radiation from natural sources (including directly ionising cosmic rays) is an important component of background radiation. In the present paper, indoor measurements of naturally occurring gamma rays that were undertaken as part of the UK Childhood Cancer Study are summarised, and it is shown that these are broadly compatible with an earlier UK National Survey. The distribution of indoor gamma-ray dose rates in Great Britain is approximately normal with mean 96 nGy/h and standard deviation 23 nGy/h. Directly ionising cosmic rays contribute about one-third of the total. The expanded dataset allows a more detailed description than previously of indoor gamma-ray exposures and in particular their geographical variation. Various strategies for predicting indoor natural background gamma-ray dose rates were explored. In the first of these, a geostatistical model was fitted, which assumes an underlying geologically determined spatial variation, superimposed on which is a Gaussian stochastic process with Matérn correlation structure that models the observed tendency of dose rates in neighbouring houses to correlate. In the second approach, a number of dose-rate interpolation measures were first derived, based on averages over geologically or administratively defined areas or using distance-weighted averages of measurements at nearest-neighbour points. Linear regression was then used to derive an optimal linear combination of these interpolation measures. The predictive performances of the two models were compared via cross-validation, using a randomly selected 70 % of the data to fit the models and the remaining 30 % to test them. The mean square error (MSE) of the linear-regression model was lower than that of the Gaussian–Matérn model (MSE 378 and 411, respectively). The predictive performance of the two candidate models was also evaluated via simulation; the OLS model performs significantly better than the Gaussian–Matérn model.
Starting Page	103
Ending Page	124
Page Count	22
File Format	PDF
ISSN	0301634X
Journal	Radiation and Environmental Biophysics
Volume Number	55
Issue Number	1
e-ISSN	14322099
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-02-15
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Gamma radiation Natural background radiation Childhood cancer Leukaemia Biophysics and Biological Physics Effects of Radiation/Radiation Protection Environmental Physics Environmental Monitoring/Analysis Ecosystems
Content Type	Text
Resource Type	Article
Subject	Biophysics Environmental Science Radiation

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