A Geologically Based Indoor‐Radon Potential Map of Kentucky

Abstract

We combined 71,930 short‐term (median duration 4 days) home radon test results with 1:24,000‐scale bedrock geologic map coverage of Kentucky to produce a statewide geologically based indoor‐radon potential map. The test results were positively skewed with a mean of 266 Bq/m 3 , median of 122 Bq/m 3 , and 75th percentile of 289 Bq/m 3 . We identified 106 formations with ≥10 test results. Analysis of results from 20 predominantly monolithologic formations showed indoor‐radon concentrations to be positively skewed on a formation‐by‐formation basis, with a proportional relationship between sample means and standard deviations. Limestone (median 170 Bq/m 3 ) and dolostone (median 130 Bq/m 3 ) tended to have higher indoor‐radon concentrations than siltstones and sandstones (median 67 Bq/m 3 ) or unlithified surficial deposits (median 63 Bq/m 3 ). Individual shales had median values ranging from 67 to 189 Bq/m 3 ; the median value for all shale values was 85 Bq/m 3 . Percentages of values falling above the U.S. Environmental Protection Agency (EPA) action level of 148 Bq/m 3 were sandstone and siltstone: 24%, unlithified clastic: 21%, dolostone: 46%, limestone: 55%, and shale: 34%. Mississippian limestones, Ordovician limestones, and Devonian black shales had the highest indoor‐radon potential values in Kentucky. Indoor‐radon test mean values for the selected formations were also weakly, but statistically significantly, correlated with mean aeroradiometric uranium concentrations. To produce a map useful to nonspecialists, we classified each of the 106 formations into five radon‐geologic classes on the basis of their 75th percentile radon concentrations. The statewide map is freely available through an interactive internet map service.

Social Determinants of Health, Environmental Exposures and Home Radon Testing

“…Due to the skewed distribution of radon values, the 75th percentile, or upper quartile of the distribution of county-level residential radon values was used to indicate radon exposure risk potential in each county. Given the skewed distribution, the upper quartile of the distribution of county-level residential radon values was seen as a more stable estimate of radon exposure risk potential than the mean (Haneberg et al, 2020). This method of quantifying elevated exposure risk has been used in prior research (Kioumourtzoglou et al, 2019; Kjos & Schaefer-Graf, 2007; Ohlander et al, 2013).…”

Radon Hazard in Central Italy: Comparison among Areas with Different Geogenic Radon Potential

“…The construction of the GRP of an area is based on the analysis of the spatial distribution of some proxy geological information (e.g., lithological types, U, Th and Ra content, the Rn emanation coefficient from rocks, soil/rock permeability, faults, etc.) that can be related to in situ radon production and migration processes [ 10 , 11 , 17 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. The resulting GPR map defines the spatial distribution of radon risk from sub-surface sources; information that can then be used for land-use zoning and strategic indoor radon monitoring purposes.…”

Citizen Science Approach to Home Radon Testing, Environmental Health Literacy and Efficacy

“…We chose two geologically similar counties in western Kentucky (Christian and Logan counties), along the edge of the Illinois Basin and transected by a band of Mississippian limestone with extremely high radon risk potential (16.01–25.30 pCi/L, the standard U.S. metric for radon) and intense karst (cave) potential (see Figure 1 ). We chose the other two counties (Rowan and Pulaski), also geologically similar to each other, along the boundary between the Mississippian and Cumberland Plateaus and underlain by Mississippian and Pennsylvanian limestone and clastic bedrock, with lower karst and radon risk potential (see Figure 1 ) ( Haneberg et al 2020 ). Rowan and Pulaski counties were chosen from among the rural counties with lower radon risk potential because they matched the two high radon potential counties on population size and median income.…”