Statistically Based Methodologies for Mapping of Radon 'Actual' Concentrations: The Case of Minnesota
A methodology is being developed for identifying 'high radon' areas by correlating actual indoor levels with local soil, housing, and meteorological data. In preliminary multiple regression analyses using 'screening' indoor radon data from Minnesota, radium concentrations from aerial surveys, and information derived from a state soils map, indicate country geometric mean (GM) radon concentrations with an R2 of approximately 0.5, Furthermore, these data have even greater underlying predictive power, considering the substantial variability in GMs arising from the small numbers of homes monitored in most counties. This suggests that most of the variability of actual indoor radon concentrations from one area to another can be predicted quantitatively based on a correlation analysis between suitable indoor monitoring data and physical data on soils and other factors. This contrasts with methods for mapping the radon 'potential' that provide indicators of indoor concentrations without quantifying their relationship to actual indoor levels.