Eric Petermann
Eric Petermann works as a scientific officer at the Federal Office for Radiation Protection (BfS) in Germany in the field of mapping and predicting of environmental radioactivity (mainly radon) with an emphasis on machine learning techniques. He studied Geography, Geology and Geophysics at the University of Leipzig (Germany) and University of Canterbury (New Zealand). After graduation in 2011, he worked for two years for consulting companies in the fields of geophysical site assessment and land management. From 2014 to 2017 he worked as a doctoral researcher at the Helmholtz Centre for Environmental Research (Germany) in a project focusing on sustainable water management along the South African coast. His dissertation (2018 at Technical University Dresden), which was related to this project, focused on localization and quantification of groundwater discharge into the sea and into lakes using radionuclides and stable isotopes. In 2018, Eric Petermann joined the BfS.
Sessions
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.