Comparison of Northern Ireland radon maps based on indoor radon measurements and geology with maps derived by predictive modelling of airborne radiometric and ground permeability data

doi:10.1016/j.scitotenv.2011.01.023

Science of The Total Environment

Volume 409, Issue 8, 15 March 2011, Pages 1572-1583

https://doi.org/10.1016/j.scitotenv.2011.01.023 Get rights and content

Abstract

Publicly available information about radon potential in Northern Ireland is currently based on indoor radon results averaged over 1-km grid squares, an approach that does not take into account the geological origin of the radon. This study describes a spatially more accurate estimate of the radon potential of Northern Ireland using an integrated radon potential mapping method based on indoor radon measurements and geology that was originally developed for mapping radon potential in England and Wales. A refinement of this method was also investigated using linear regression analysis of a selection of relevant airborne and soil geochemical parameters from the Tellus Project. The most significant independent variables were found to be eU, a parameter derived from airborne gamma spectrometry measurements of radon decay products in the top layer of soil and exposed bedrock, and the permeability of the ground. The radon potential map generated from the Tellus data agrees in many respects with the map based on indoor radon data and geology but there are several areas where radon potential predicted from the airborne radiometric and permeability data is substantially lower. This under-prediction could be caused by the radon concentration being lower in the top 30 cm of the soil than at greater depth, because of the loss of radon from the surface rocks and soils to air.

Research Highlights

► A new radon map for Northern Ireland is derived from indoor radon and geology data. ► Linear regression used to map radon potential (RP) from airborne and soil data. ► Gamma-ray spectrometry estimated U is the most significant independent variable. ► RP maps based on separate models for distinct geological terrains are most effective. ► Under-prediction of RP may be caused by loss of radon from surface rocks and soils.

Introduction

In order to prevent the public receiving high exposures to radon, it is necessary to identify those areas most at risk. The potential for high indoor radon concentrations depends on multiple factors including the amount of radium-226 in the ground underneath buildings, and the permeability of the ground. As a result, indoor radon tends to be correlated with local geology (Appleton and Miles, 2005, Barnet et al., 2008, Kemski et al., 2009, Scheib et al., 2009). The probability of homes in Northern Ireland having radon concentrations above the UK Action Level (AL, 200 becquerels per cubic metre of air, Bq m⁻³) is currently estimated on the basis of the results of radon measurements in homes, grouped by 1-km squares where there are sufficient results in the square, or interpolated from the nearest measurements for squares where there are too few results (Green et al., 2009). This approach does not take any account of the geological influence on indoor radon (Appleton and Miles, 2010). An integrated mapping method has been developed to use indoor radon results in conjunction with geological boundaries to map radon potential (RP_irg) with greater accuracy and detail than currently available for Northern Ireland (Miles and Appleton, 2005). This method is applied to indoor radon and geological data available in Northern Ireland and the results are compared with the 1-km grid square radon potential (RP_ir) map based solely on indoor radon measurements.

Both the 1-km grid and the integrated mapping methods can have significant uncertainties where indoor radon data are sparse. It is difficult to provide a consistent indication of the spatial variation of the likely reliability of the RP_ir and RP_irg maps although the density of indoor radon measurements is probably the best indicator (Green et al., 2009). Uranium concentrations in surface rocks and soils, estimated by airborne gamma spectrometry surveys of gamma-rays from ²¹⁴Bi, and referred to as eU (equivalent uranium), have been used to inform radon potential mapping in many countries (Appleton, 2007, Smethurst et al., 2008). The integrated geological–grid square radon mapping of England, Wales and Scotland did not use airborne geophysics or soil geochemical data, because neither is universally available in GB. In Northern Ireland, the Tellus Project has produced new geochemical and geophysical maps designed to support mineral exploration, inform land-use planning and provide environmental baseline data (Young and Earls, 2007, Beamish and Young, 2009). The study reported here develops and applies to the whole of Northern Ireland the predictive modelling methods of a pilot study (Appleton et al., 2008) which used linear regression analysis of a selection of relevant Tellus airborne and soil geochemical parameters in an attempt to refine the radon map based solely on indoor radon data and geology. In this study, a range of national and terrain specific linear regression models is statistically validated against the radon map based on indoor radon and geology in order to assess whether radon potential maps derived by predictive modelling of ground permeability, airborne gamma-ray spectrometry and soil geochemical data could usefully inform future indoor radon measurement programmes.

Section snippets

Materials and methods

Appleton et al. (2008) describe the airborne gamma-ray spectrometry and soil geochemistry data from the Tellus Project, together with ground permeability information based largely on aquifer character (Ball et al., 2005, McConvey, 2005) and the approximately 23,000 indoor radon measurements available for Northern Ireland (Green et al., 2009). Uncertainties related to indoor radon measurements are documented by Hunter et al., 2005, Hunter et al., 2009, Miles and Appleton, 2005. For the

Radon map based on indoor radon data and geology

Comparison of a provisional geology–grid square radon potential map with the published 1-km grid map produced by the Health Protection Agency (HPA; Green et al., 2009) revealed a number of differences which were investigated. The majority of apparently anomalous areas on the provisional RP_irg map were caused by high indoor radon associated with a geological combination in the SE and W sectors of Northern Ireland influencing relatively isolated occurrences of the same geological combinations in

Conclusions

The RP_mod map produced from Tellus data using separate linear regression models for different geological terrains provides the best visual agreement with the RP_irg map. Also the lowest Bias values were generally obtained when terrain specific regression models were used. However, radon potential maps produced using the Tellus data appear to underestimate radon potential especially where the highest radon potential is indicated on the integrated RP_irg radon map. For example, there are several

Acknowledgements

Tellus is funded by the Department of Enterprise, Trade and Investment of the Northern Ireland government, managed by Mike Young and staffed by GSNI, though parts of the work are contracted out to other organisations, including the BGS and the HPA. Indoor radon data used to produce the new radon map for Northern Ireland were collected during surveys carried out by the HPA (or by the National Radiological Protection Board before it joined HPA) on behalf of the Northern Ireland Environment Agency

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Geology provides information on the distribution of the materials that may contribute to radon release while the latter three items provide more direct observations on the distributions of the radionuclide elements uranium (U), thorium (Th) and potassium (K). In addition, (c) and (d) provide multi-element assessments of geochemistry which are also included in this study.
The effectiveness of datasets for predicting the existing indoor radon data is assessed through the level (the higher the better) of explained variation (% of variance or ANOVA) obtained from the tested models. A multiple linear regression using a compositional data (CODA) approach is carried out to obtain the required measure of determination for each analysis.
Results show that, amongst the four tested datasets, the soil geochemistry (TSG, i.e. including all the available 41 elements, 10 major – Al, Ca, Fe, K, Mg, Mn, Na, P, Si, Ti - plus 31 trace) provides the highest explained variation of indoor radon (about 40%); more than double the value provided by U alone (ca. 15%), or the sub composition U, Th, K (ca. 16%) from the same TSG data. The remaining three datasets provide values ranging from about 27% to 32.5%. The enhanced prediction of the AGR model relative to the U, Th, K in soils suggests that the AGR signal captures more than just the U, Th and K content in the soil.
The best result is obtained by including the soil geochemistry with geology and AGR (TSG + G + AGR, ca. 47%). However, adding G and AGR to the TSG model only slightly improves the prediction (ca. +7%), suggesting that the geochemistry of soils already contain most of the information given by geology and airborne datasets together, at least with regard to the explanation of indoor radon.
From the present analysis performed in the SW of England, it may be concluded that each one of the four datasets is likely to be useful for radon mapping purposes, whether alone or in combination with others. The present work also suggest that the complete soil geochemistry dataset (TSG) is more effective for indoor radon modelling than using just the U (+Th, K) concentration in soil.

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Comparison of Northern Ireland radon maps based on indoor radon measurements and geology with maps derived by predictive modelling of airborne radiometric and ground permeability data

Abstract

Research Highlights

Introduction

Section snippets

Materials and methods

Radon map based on indoor radon data and geology

Conclusions

Acknowledgements

J Environ Radioactiv

J Environ Radioactiv

Sci Total Environ

Radon: sources, health risks, and hazard mapping

Ambio

Radon in Wales

Soil radium, soil gas radon and indoor radon empirical relationships to assist in post-closure impact assessment related to near-surface radioactive waste disposal

J Environ Radioactiv

A groundwater vulnerability screening methodology for Northern Ireland

Radon in geological environment – Czech experience

Geophysics of Northern Ireland: the Tellus effect

First Break

Towards multivariate modelling of geogenic radon. Part 2: estimation