Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data

Abstract

Wolframite has been specified as a ‘conflict mineral’ by a U.S. Government Act, which obliges companies that use these minerals to report their origin. Minerals originating from conflict regions in the Democratic Republic of the Congo shall be excluded from the market as their illegal mining, trading, and taxation are supposed to fuel ongoing violent conflicts. The German Federal Institute for Geosciences and Natural Resources (BGR) developed a geochemical fingerprinting method for wolframite based on laser ablation inductively coupled plasma-mass spectrometry. Concentrations of 46 elements in about 5300 wolframite grains from 64 mines were determined. The issue of verifying the declared origins of the wolframite samples may be framed as a forensic problem by considering two contrasting hypotheses: the examined sample and a sample collected from the declared mine originate from the same mine (H1), and the two samples come from different mines (H2). The solution is found using the likelihood ratio (LR) theory. On account of the multidimensionality, the lack of normal distribution of data within each sample, and the huge within-sample dispersion in relation to the dispersion between samples, the classic LR models had to be modified. Robust principal component analysis and linear discriminant analysis were used to characterize samples. The similarity of two samples was expressed by Kolmogorov-Smirnov distances, which were interpreted in view of H1 and H2 hypotheses within the LR framework. The performance of the models, controlled by the levels of incorrect responses and the empirical cross entropy, demonstrated that the proposed LR models are successful in verifying the authenticity of the wolframite samples.