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 meteor ological data. In preliminary multiple regression analyses using 'scre ening' indoor radon data from Minnesota, radium concentrations from ae rial surveys, and information derived from a state soils map, indicate county geometric mean (GM) radon concentrations with an R(2) of appro ximately 0.5. Furthermore, these data have even greater underlying pre dictive power, considering the substantial variability in GMs arising from the small numbers of homes monitored in most counties. This sugge sts that most of the variability of actual indoor radon concentrations from one area to another can be predicted quantitatively based on a c orrelation analysis between suitable indoor monitoring data and physic al data on soils and other factors. This contrasts with methods for ma pping the radon 'potential' that provide indicators of indoor concentr ations without quantifying their relationship to actual indoor levels.