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

G. M. Kendall*, R. Wakeford, M. Athanson, T. J. Vincent, E. J. Carter, Neil McColl, M. P. Little

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)103-124
Number of pages22
JournalRadiation and Environmental Biophysics
Volume55
Issue number1
DOIs
Publication statusPublished - 1 Mar 2016

Bibliographical note

Funding Information:
We are very grateful to Jill Simpson of the University of York and to the other UKCCS investigators for making available the indoor gamma-ray measurements made for the United Kingdom Childhood Cancer Study and for advice on the interpretation of the data. We are also very grateful to J D Appleton for advice on geological matters generally and in particular for suggesting geological classification schemes. We are grateful to Phil Gilvin, Luke Hager and Rick Tanner at Public Health England (PHE) for advice on the dosimetry of the National Survey and the UKCCS and to Simon Bouffler and other colleagues at PHE for allowing the use of the National Survey data and for advice on its interpretation. They also made helpful comments on the draft. Helpful comments were also made by the two referees and by Bernd Grosche, Michael Murphy and Graham Smith. This work was supported by Children with Cancer (UK) and by the Intramural Research Program of the National Institutes of Health, the National Cancer Institute, Division of Cancer Epidemiology and Genetics. Much of the work by two of the authors (GMK and TJV) was undertaken at the Childhood Cancer Research Group, whose loss is much regretted. The research work of CCRG was supported by the Department of Health for England and Wales, Scottish Government and Children with Cancer (UK).

Publisher Copyright:
© 2016, Springer-Verlag Berlin Heidelberg.

Keywords

  • Childhood cancer
  • Gamma radiation
  • Leukaemia
  • Natural background radiation

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