Published October 2016 | Version v1
Journal article

Applying multivariate statistics to discriminate uranium ore concentrate geolocations using (radio)chemical data in support of nuclear forensic investigations

  • 1. GAU-Radioanalytical Laboratories, Ocean and Earth Science, University of Southampton, National Oceanography Centre, European Way, Southampton, Hampshire SO14 3ZH (United Kingdom)
  • 2. Faculty of Humanities, University of Southampton, University Road, Highfield, Southampton, Hampshire, SO17 1BJ (United Kingdom)

Description

The application of Principal Components Analysis (PCA) to U and Th series gamma spectrometry data provides a discriminatory tool to help determine the provenance of illicitly recovered uranium ore concentrates (UOCs). The PCA is applied to a database of radiometric signatures from 19 historic UOCs from Australia, Canada, and the USA representing many uranium geological deposits. In this study a key process to obtain accurate radiometric data (gamma and alpha) is to digest the U-ores and UOCs using a lithium tetraborate fusion. Six UOCs from the same sample set were analysed 'blind' and compared against the database to identify their geolocation. These UOCs were all accurately linked to their correct geolocations which can aid the forensic laboratory in determining which further analytical techniques should be used to improve the confidence of the particular location. - Highlights: • Principal Components Analysis is used as geolocating tool for nuclear forensics. • High quality radiometric signatures for uranium ore concentrates obtained using a rapid and effective dissolution technique. • "Unknown" samples are statistically compared against a database of known signatures.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.jenvrad.2016.05.013

Additional details

Identifiers

DOI
10.1016/j.jenvrad.2016.05.013;
PII
S0265-931X(16)30158-8;

Publishing Information

Journal Title
Journal of Environmental Radioactivity
Journal Volume
162-163
Journal Page Range
p. 172-181
ISSN
0265-931X
CODEN
JERAEE

INIS

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.