Detection of anomalous radioxenon concentrations: A distribution‐free approach

Michele Scagliarini (), Rosanna Gualdi, Giuseppe Ottaviano and Antonietta Rizzo

Environmetrics, 2023, vol. 34, issue 7

Abstract: The detection of anomalous atmospheric radioxenon concentrations plays a key role in detecting both underground nuclear explosions and radioactive emissions from nuclear power plants and medical isotope production facilities. For this purpose, the CTBTO's International Data Centre uses a procedure based on descriptive thresholds. In order to supplement this procedure with a statistical inference‐based method, we compared several non‐parametric change‐point control charts for detecting shifts above the natural radioxenon background. The results indicate that the proposed methods can provide valuable tools for the institutions responsible for the verification and classification of anomalous radioxenon concentrations.

Date: 2023
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