Using airborne hyperspectral data to characterize the surface pH and mineralogy of pyrite mine tailings

Acid mine drainage (AMD) is a key concern of the mining industry due to its impact on the quality of water and soils surrounding mine waste deposits. Acid mine drainage derives from the oxidation of metal sulphides, e.g. pyrite (FeS2), exposed to oxygen and water. The leachate acidity is capable of releasing heavy metals contained in the mining waste rock, which can affect water quality and lead to metal enrichment in sediments and potentially resulting in ecosystem degradation. Predicting tailings leachate pH is key to the management of sulfide-bearing mine wastes and is an emerging remote sensing application with limited studies having been realized. Such a capability would supplement traditional methods (i.e. ground surveys) that are challenging to implement due to the extent and large volume of mine waste. This study reports regional scale tailings mineral maps generated from airborne hyperspectral information of the Sotiel-Migollas complex in Spain and pinpoints sources of AMD. The extraction of spectral endmembers from imagery revealed twenty six endmembers for tailings material that represent mostly mineral mixtures. From these, eleven spectral groups were defined, each encompassing minor variations in mineral mixtures. The mineral maps resulting from the use of these endmembers for the detailed investigation of four tailings serve as indicators of the metal, sulphate, and pH levels of the AMD solution at the time of mineral precipitation. Predicted mineralogy was assessed using spectra from samples collected in the field and associated X-ray diffraction measurements. We also discuss the relative merits of the minerals maps of this study and soil leachate pH maps that we previously reported for the same locality using the same airborne data. The pH maps tend to provide predictions consistent with the mineralogy predicted from the mineral maps and the field and laboratory evidence. The pH maps offer information on the pH conditions of the tailings thus giving an insight on the different types of oxidation reactions that may occur

Identification of materials related to acid mine drainage using multi-source spectra at S. Domingos Mine, southeast Portugal

Imaging spectroscopy (IS) can identify target materials at both mineralogical and geochemical levels. Therefore, in environmental applications, it can be used to assess contamination derived from mining activities, moving from contamination sources along pathways to receptors as acid mine drainage (AMD). This can be based on the spectra of specific assemblages of minerals from spectral libraries, which can indicate pH values at the time of their generation and the subsequent acid-generating potential. Alternatively, field spectral measurements can be used as input data for mapping algorithms. This study presents a new methodological approach to improving the results for mapping contamination sources and pathways, by combining multisource spectra from both these approaches at different scales. In addition to the mineralogical libraries and field spectra already mentioned, additional end-member spectra that are extracted from IS data are used so as to highlight particular site phenomena otherwise undetected by the two previous approaches. The highly correlated spectra are then used as input to the Spectral Angle Mapper algorithm, to establish a map of local field spectra and also one from image end-members. The intersection of the two maps results in an improved map, assigned in terms of correlation ≥0.8 of mineralogical assemblages focused on AMD indicators. This methodology was tested in the abandoned S. Domingos Mine, in southeast Portugal's Iberian Pyrite Belt, with AMD caused by long-term exploitation of volcanogenic massive sulphide deposits. Data from the HyMap™ sensor covered the area, and field spectroradiometric measurements were undertaken and analysed for mineralogical and geochemical content. A flightline containing the open pit was processed according to the aforementioned methodology, focusing directly on the target of interest and minimizing errors. The final map displays the mineralogical assemblage correlations ≥0.8 of variable pH indicators, particularly isolating a low-pH combination of significance to the contamination in the area