Spatial modeling for radon concentrations in subway stations in Seoul, Korea.

This study examined the environmental and geological determinants of radon concentration in subway stations by applying a spatial statistical model to the integrated GIS database. The data were collected for 237 underground subway stations located inside the city of Seoul, South Korea and used for mapping to illustrate the spatial distribution of airborne radon exposure and analysis of potential contribution of station-specific and geological determinants. A Bayesian conditional autoregressive regression (CAR) model was developed to explain the radon concentrations, and the predicted radon surface was generated and visualized to identify hotspot regions where elevated radon exposure is likely to be present in underground settings.