The predictive power of airborne gamma ray survey data on the locations of domestic radon hazards in Norway: A strong case for utilizing airborne data in large-scale radon potential mapping

It is estimated that exposure to radon in Norwegian dwellings is responsible for as many as 300 deaths a year due to lung cancer. To address this, the authorities in Norway have developed a national action plan that has the aim of reducing exposure to radon in Norway (Norwegian Ministries, 2010). The plan includes further investigation of the relationship between radon hazard and geological conditions, and development of map-based tools for assessing the large spatial variation in radon hazard levels across Norway. The main focus of the present contribution is to describe how we generate map predictions of radon potential (RP), a measure of radon hazard, from available airborne gamma ray spectrometry (AGRS) surveys in Norway, and what impact these map predictions can be expected to have on radon protection work including land-use planning and targeted surveying. We have compiled 11 contiguous AGRS surveys centred on the most populated part of Norway around Oslo to produce an equivalent uranium map measuring 180 km × 102 km that represents the relative concentrations of radon in the near surface of the ground with a spatial resolution in the 100 s of metres. We find that this map of radon in the ground offers a far more detailed and reliable picture of the distribution of radon in the sub-surface than can be deduced from the available digital geology maps. We tested the performances of digital geology and AGRS data as predictors of RP. We find that digital geology explains approximately 40% of the observed variance in ln RP nationally, while the AGRS data in the Oslo area split into 14 bands explains approximately 70% of the variance in the same parameter. We also notice that there are too few indoor data to characterise all geological settings in Norway which leaves areas in the geology-based RP map in the Oslo area, and elsewhere, unclassified. The AGRS RP map is derived from fewer classes, all characterised by more than 30 indoor measurements, and the corresponding RP map of the Oslo area has no unclassified parts. We used statistics of proportions to add 95% confidence limits to estimates of RP on our predictive maps, offering public health strategists an objective measure of uncertainty in the model. The geological and AGRS RP maps were further compared in terms of their performances in correctly classifying local areas known to be radon affected and less affected. Both maps were accurate in their predictions; however the AGRS map out-performed the geo