Modeling and predicting mean indoor radon concentrations in Austria by generalized additive mixed models

Abstract

AbstractRadon is a noble gas that occurs naturally as a decay product of uranium. Aside from smoking, radon is considered to be one of the major causes of lung cancer. Indoor environments, where radon can accumulate and potentially reach high concentrations, are of a particular concern. A mixed effects additive model along with a data-driven cross validation model selection method is applied to model the mean indoor radon concentration of dwellings in Austria. For this model a prediction approach is introduced, which enables the mapping of indoor radon potential to identify radon areas in Austria. The data used for modeling was collected in monitoring campaigns for private dwellings in Austria from 2013 to 2019. The proposed method allows policy makers to identify regions with high indoor radon concentrations and enables them to meet regulatory requirements or prioritize radon protection measures. The currently published Austrian radon map and the delineation of radon areas in Austria is based on this proposed method.