Source term estimation using multiple xenon isotopes in atmospheric samples. (August 2019)

• Record Type: Journal Article
• Authors: Eslinger, Paul W.; Lowrey, Justin D.; Miley, Harry S.; Rosenthal, W. Steven; Schrom, Brian T.
• Is Part Of: Journal of environmental radioactivity. Volume 204(2019)
• Page Start: 111
• Page End: 116
• Publication Date: 2019-08
• 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.2019.04.004
• Languages: English
• ISSNs: 0265-931X

Abstract

Abstract: Algorithms that estimate the location and magnitude of an atmospheric release using remotely sampled air concentrations typically involve a single chemical or radioactive isotope. A new Bayesian algorithm is presented that makes discrimination between possible types of releases (e.g., nuclear explosion, nuclear power plant, or medical isotope production facility) an integral part of the analysis for samples that contain multiple isotopes. Algorithm performance is demonstrated using synthetic data and correctly discriminated between most release-type hypotheses, with higher accuracy when data are available on three or more isotopes. Highlights: New algorithm for source-term estimation using two or more isotopes. The algorithm selects the most likely type (power plant, explosion, etc.) of release event. More isotopes discriminate between release types better than two isotopes.