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VISUAL–STATISTICAL CLASSIFICATION OF As–Fe-RICH PRODUCTS OF ALTERATION OF TAILINGS FROM THE ENGUIALÈS TUNSGTEN MINE, FRANCE

We have studied the products of alteration of sulfides contained in the tailings of a former tungsten mine at Enguiales, Aveyron, France. Most of these products are poorly crystalline and contain high concentrations of arsenic. A preliminary classification based on visual observations was carried out, and five products were distinguished according to their color and texture. The data obtained by electron-microprobe analysis were submitted to different statistical approaches in order to discriminate among the various materials and to test the efficiency of the visual classification. The statistics involved rely on logratios of the chemical elements because the ratio of any two elements is independent of the perturbations caused by other elements, and remains unchanged whatever the choice of subcompositional space. The statistical discrimination of the groups indicates that log(Fe/As) and log(S/As) best express the chemical differences. Both of these logratios correspond to the system Fe–As–S. In this study, the two approaches, visual observations and statistics, are complementary, and one method without the other could give only partial information or misinterpretations. A hierarchical clustering applied to the whole dataset confirms the existence of five groups, but visual and statistical classifications differ. On one hand, by using the logratio method, different subgroups with the same color were identified. On the other hand, some groups with different colors correspond to the same mineral, which was highlighted by Raman microspectrometry. These observations (concerning As-rich jarosite, for example) are explained mainly by differences in composition.