Eric Petermann

Radon is a natural occurring radioactive gas that is produced in any rock and soil. Radon can enter buildings via fissures and cracks in the building’s foundation. In indoor environments radon can accumulate. Exposure to elevated radon concentrations over a long time poses a serious health risk making radon responsible for more than 200,000 lung cancer fatalities worldwide every year. In the course of mapping radon in Germany we provide maps of 1) hazard and 2) risk. For 1) mapping radon hazard, we utilize >6,000 observations of geogenic radon potential in soil as target variable. We fit a random forest model that uses geology, soil physical properties, climatic parameters and relief derivatives as predictors. A current matter of research is how to improve implementation of information from local measurements into machine learning models. For 2) mapping radon risk, we use >10,000 indoor radon observations as target variables and fit a random forest model that uses the result from 1) in combination with building and population density, building characteristics and climatic parameters. The resulting maps are used manifold 1) to support decision making, i.e. delineation of radon priority areas where specific regulations apply, 2) evaluation of public exposure and related health effects as well as 3) public information.