Evaluation of stochastic method on track density analysis for passive radon measurement

Passive radon monitors with CR-39s are commonly used in major epidemiological studies. However, the conventional CR-39 track density analysis method makes it difficult to estimate the concentration accurately due to the heterogeneity of tracks on CR-39s and the small track reading area. Track heterogeneity in CR-39 detectors arises from exposure-related and detector-related factors. To improve the accuracy of track density analysis in passive radon monitors, this study implemented a new stochastic approach utilizing Latin Hypercube Sampling (LHS) to compare the performance to the conventional method. Consequently, the stochastic method reduces the root mean square deviation of mean track density by 15.6 % compared to the conventional method. The coefficient of determination of the stochastic method is significantly higher than that of the conventional method in the linear correlation of estimated track density and accumulated exposure. The stochastic method utilizing the LHS for track density analysis decreased the total counting area of CR-39 and performed congruently and effectively, as the large counting area using the conventional strategy. These findings suggest the stochastic approach is a promising method for improving track density determination in passive radon measurements with CR-39 detectors.