Prediction of sub-surface 37Ar concentrations at locations in the Northwestern United States. (January 2018)

• Record Type: Journal Article
• Authors: Fritz, Bradley G.; Aalseth, Craig E.; Back, Henning O.; Hayes, James C.; Humble, Paul H.; Ivanusa, Pavlo; Mace, Emily K.
• Is Part Of: Journal of environmental radioactivity. Volume 181(2018)
• Page Start: 1
• Page End: 7
• Publication Date: 2018-01
• Subjects: Radioactivity -- Periodicals; Radiation, Background -- Periodicals; Radioecology -- Periodicals; Radioactive pollution -- Periodicals; Environmental Pollutants -- Periodicals; Radioactive Pollutants -- Periodicals; Radioactivity -- Periodicals; Radioécologie -- Périodiques; Pollution radioactive -- Périodiques; Fond de rayonnement -- Périodiques; 539.752
• DOI: 10.1016/j.jenvrad.2017.10.005
• Languages: English
• ISSNs: 0265-931X

Abstract

Abstract: The Comprehensive Nuclear-Test-Ban Treaty, which is intended to prevent nuclear weapon test explosions and any other nuclear explosions, includes a verification regime, which provides monitoring to identify potential nuclear explosions. The presence of elevated 37 Ar is one way to identify subsurface nuclear explosive testing. However, the naturally occurring formation of 37 Ar in the subsurface adds a complicating factor. Prediction of the naturally occurring concentration of 37 Ar can help to determine if a measured 37 Ar concentration is elevated relative to background. The naturally occurring 37 Ar background concentration has been shown to vary between less than 1 mBq/m 3 to greater than 100 mBq/m 3 (Riedmann and Purtschert, 2011). The purpose of this work was to enhance the understanding of the naturally occurring background concentrations of 37 Ar, allowing for better interpretation of results. To that end, we present and evaluate a computationally efficient model for predicting the average concentration of 37 Ar at any depth under transient barometric pressures. Further, measurements of 37 Ar concentrations in samples collected at multiple locations are provided as validation of the concentration prediction model. The model is shown to compare favorably with concentrations of 37 Ar measured at multiple locations in the Northwestern United States. Highlights: This paper includes measured concentrations of 37 Ar in 19 shallow soil gas samples collected at various sampling locations. Also included is a predictive model of 37 Ar concentrations in shallow soil gas. This model is a solution of a previously published differential equation describing steady state transport of 37 Ar in soil gas, and a previously published 37 Ar production equation.