Affiliation: College of Arts and Sciences, Department of Statistics and Operations Research
Radon is a naturally occurring radioactive gas and is an intermediate product of the decay of uranium. Exposure to radon is the second leading cause of lung cancer in the United States and is hypothesized to cause strokes and other cardiovascular events. Additionally, radon levels seem to be rising across North America and may be linked to climate change. In the early 1990’s, the US EPA created a grouping of 15 radon "risk levels," classified according to indoor radon measurements (pCi/L) from the State Residential Radon Survey (SRRS), aerial radioactivity (ppm eU), geology, soil permeability and architecture type; this is called the radon index (RI). The goal of this analysis is to create a refined spatial model for the geographic distribution of radon using a latent process modeling approach on indoor radon measurement data (SRRS) and the radon index data. The parameter estimates of our model seem to be well-behaved and we will soon construct a method for interpolation and prediction of unobserved radon values.