International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station

Publication date: June 2016
Source:Journal of Environmental Radioactivity, Volume 157
Author(s): Paul W. Eslinger, Ted W. Bowyer, Pascal Achim, Tianfeng Chai, Benoit Deconninck, Katie Freeman, Sylvia Generoso, Philip Hayes, Verena Heidmann, Ian Hoffman, Yuichi Kijima, Monika Krysta, Alain Malo, Christian Maurer, Fantine Ngan, Peter Robins, J. Ole Ross, Olivier Saunier, Clemens Schlosser, Michael Schöppner, Brian T. Schrom, Petra Seibert, Ariel F. Stein, Kurt Ungar, Jing Yi
The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward. An understanding of natural and man-made radionuclide backgrounds can be used in accordance with the provisions of the treaty (such as event screening criteria in Annex 2 to the Protocol of the Treaty) for the effective implementation of the verification regime.Fission-based production of ⁹⁹Mo for medical purposes also generates nuisance radioxenon isotopes that are usually vented to the atmosphere. One of the ways to account for the effect emissions from medical isotope production has on radionuclide samples from the IMS is to use stack monitoring data, if they are available, and atmospheric transport modeling. Recently, individuals from seven nations participated in a challenge exercise that used atmospheric transport modeling to predict the time-history of ¹³³Xe concentration measurements at the IMS radionuclide station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice.Some of the models predicted the highest measured concentrations quite well. A model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in understanding how to discriminate those releases from releases from a nuclear explosion.



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