Extrapolating a uranium map of Norway: Implications for country-scale geogenic radon risk mapping

Abstract

Radon, a radioactive gas produced through the decay of uranium in the earth's crust, poses a significant health risk when it accumulates to high concentrations indoors. This study focuses on identifying areas at higher risk of radon accumulation in Norway by employing a data-driven approach based on geogenic factors, particularly the distribution of uranium on the ground surface.Utilizing two types of uranium measurements and employing a statistical methodology, we classify bedrock geology based on their average uranium content. The classification process integrates Self-organizing maps (SOM) with K-means clustering, facilitating the creation of a country-scale extrapolation. The resulting uranium map is merged from the high-resolution airborne uranium map and the extrapolated uranium map.While acknowledging the presence of uncertainties, our study offers valuable insights into geogenic radon risk, serving as a valuable resource for radon studies and mitigation efforts. Furthermore, the methodology employed in this study is characterized by its flexibility and scalability, enabling future updates and refinements to enhance radon risk assessment and management strategies.

Keywords

• Radon risk
• Natural radiation
• Machine learning
• Uranium concentration
• Geospatial analysis
• Geology