Source identification of uranium-containing materials at mine legacy sites in Portugal. (March 2018)

• Record Type: Journal Article
• Authors: Keatley, A.C.; Martin, P.G.; Hallam, K.R.; Payton, O.D.; Awbery, R.; Carvalho, F.P.; Oliveira, J.M.; Silva, L.; Malta, M.; Scott, T.B.
• Is Part Of: Journal of environmental radioactivity. Volume 183(2018)
• Page Start: 102
• Page End: 111
• Publication Date: 2018-03
• Subjects: Radiation -- Portugal -- Uranium -- Mining -- Heterogeneity -- Forensics -- Mapping; 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.2017.12.009
• Languages: English
• ISSNs: 0265-931X

Abstract

Abstract: Whilst prior nuclear forensic studies have focused on identifying signatures to distinguish between different uranium deposit types, this paper focuses on providing a scientific basis for source identification of materials from different uranium mine sites within a single region, which can then be potentially used within nuclear forensics. A number of different tools, including gamma spectrometry, alpha spectrometry, mineralogy and major and minor elemental analysis, have been utilised to determine the provenance of uranium mineral samples collected at eight mine sites, located within three different uranium provinces, in Portugal. A radiation survey was initially conducted by foot and/or unmanned aerial vehicle at each site to assist sample collection. The results from each mine site were then compared to determine if individual mine sites could be distinguished based on characteristic elemental and isotopic signatures. Gamma and alpha spectrometry were used to differentiate between samples from different sites and also give an indication of past milling and mining activities. Ore samples from the different mine sites were found to be very similar in terms of gangue and uranium mineralogy. However, rarer minerals or specific impurity elements, such as calcium and copper, did permit some separation of the sites examined. In addition, classification rates using linear discriminant analysis were comparable to those in the literature. Highlights: Large field area mapped rapidly. Locations of elevated contamination identified. Distinguishing between different mine sites within a single region. Elemental fingerprinting of ore impurities. Degree of heterogeneity across different uranium ore bodies determined.