2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 28-12
Presentation Time: 9:00 AM-5:30 PM

TOWARD A PREDICTIVE MODEL FOR BACKGROUND RADIATION: PREDICTING GAMMA EXPOSURE RATES IN THE TWIN PEAKS VOLCANIC FIELD, UTAH, US


JOHNSEN, Racheal L., Geoscience, University of Nevada, Las Vegas, 4505 S. Maryland Parkway, Las Vegas, NV 89154-4010, BURNLEY, Pamela, Geoscience, University of Nevada Las Vegas, 4505 S Maryland Parkway, Las Vegas, NV 89154, MALCHOW, Russell, National Security Technologies, 4505 S Maryland Parkway, Las Vegas, NV 89154 and ADCOCK, Christopher T., Department of Geoscience, University of Nevada, Las Vegas, 4505 S. Maryland Parkway, Las Vegas, NV 89154, racheal.johnsen@unlv.edu

Aerial gamma ray surveys can be a powerful tool to aid in mapping mineral resources, describing soil types, and identifying the extent of radiological contamination from nuclear disasters or terrorism. It is radiological contamination from the Fukushima Daiichi nuclear power plant disaster in 2011 that prompted a renewed interest in understanding and distinguishing background, or natural, radiation from anthropogenic radiation sources. In order to predict the terrestrial contribution to background radiation, a good grasp of geological materials and their chemistry in a given area is necessary. To this end, the Plio-Pleistocene Twin Peaks volcanic field in south-central Utah, USA, was chosen as a prime candidate for building predictive models of background gamma radiation. Composed of rhyolite and basalt with lesser andesite, Twin Peaks has been studied extensively over the last several decades and is chemically well-characterized. Using bedrock geochemical analyses, we built predictive models of two small areas within Twin Peaks, totaling six square miles, and compared the models with gamma exposure rates measured by aerial survey (flown by National Security Technologies Aerial Measuring Systems (AMS)). We also developed a predictive model based on data from the National Uranium Resource Evaluation (NURE) survey done in the 1970s, which we extrapolated based on geologic units. We found that the NURE-based predictive model was closest to that measured by AMS. The geochemical model varied in its ability to closely predict AMS measurements. However, most of the geologic units in Twin Peaks are relatively homogeneous, which indicates that the geochemical model is not necessarily wrong. Instead, some of the differences between prediction and measurement may be accounted for by more extensive soil development than previously described, the addition of eolian dust, vegetation cover, disturbance of topsoil from ranching and agricultural activities, or modification of soils by late Pleistocene Lake Bonneville sediments. Several of these factors are currently being explored.

DOE/NV/25946--2553