Study of the possibility of using radon potential maps for identification of areas with high indoor radon concentration

Systematic review of statistical methods for the identification of buildings and areas with high radon levels

Radon is a natural and radioactive noble gas, which may accumulate indoors and cause lung cancers after long term-exposure. Being a decay product of Uranium 238, it originates from the ground and is spatially variable. Many environmental (i.e., geology, tectonic, soils) and architectural factors (i.e., building age, floor) influence its presence indoors, which make it difficult to predict. However, different methods have been developed and applied to identify radon prone areas and buildings. This paper presents the results of a systematic literature review of suitable statistical methods willing to identify buildings and areas where high indoor radon concentrations might be found. The application of these methods is particularly useful to improve the knowledge of the factors most likely to be connected to high radon concentrations. These types of methods are not so commonly used, since generally statistical methods that study factors predictive of radon concentration are focused on the average concentration and aim to identify factors that influence the average radon level. In this paper, an attempt has been made to classify the methods found, to make their description clearer. Four main classes of methods have been identified: descriptive methods, regression methods, geostatistical methods, and machine learning methods. For each presented method, advantages and disadvantages are presented while some applications examples are given. The ultimate purpose of this overview is to provide researchers with a synthesis paper to optimize the selection of the method to identify radon prone areas and buildings.

RADON-PRONE AREAS IN SLOVAKIA PREDICTED BY RESCALED RADON POTENTIAL MAPS

Several scientific studies have shown that high content of radon in the soil environment can be a precursor of increased indoor radon levels. Inhabited areas where elevated indoor radon concentration appears for natural (geogenic) reasons are commonly referred to as radon-prone areas. In this study, radon-prone areas in the Slovak Republic were predicted on the basis of radon potential maps after its specific rescaling. In total, 99 municipalities have been identified in Slovakia where the annual average indoor radon concentration is expected to exceed the reference level of 300 Bq m-3; five of those are even expected to exceed 1000 Bq m-3. In these municipalities it is then required to conduct a survey of indoor radon measurements. Compared with a nationwide survey, the proposed approach of searching for houses with potentially high radon exposure is more efficient.

Experimental Studies to Test a Predictive Indoor Radon Model

The accumulation of the radioactive gas radon in closed environments, such as dwellings, is the result of a quite complex set of processes related to the contribution of different sources. As it undergoes different physical mechanisms, all occurring at the same time, models describing the general dynamic turns out to be difficult to apply because of the dependence on many parameters not easy to measure or calculate. In this context, the authors developed, in a previous work, a simplified approach based on the combination of a physics-mathematical model and on-site experimental measurements. Three experimental studies were performed in order to preliminarily test the goodness of the model to simulate indoor radon concentrations in closed environments. In this paper, an application on a new experimental site was realized in order to evaluate the adaptability of the model to different house typologies and environmental contexts. Radon activity measurements were performed using a portable radon detector and results, showing again good performance of the model. Results are discussed and future efforts are outlined for the refining and implementation of the model into software.