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<p>Acid mine drainage (AMD) generated from waste rock and tailings poses risks to water supplies globally through effluent acid solutions and mobilized metals and metalloids. Characterization of the environmental risks has traditionally focused on kinetic and static leach tests. However, the application of quantitative mineralogy using scanning electron microscope-based automated mineralogy to predict such risks is a growing field as it provides qualitative and quantitative datasets that directly characterize the acid generating potential of tailings. This study builds on the developing application of automated mineralogy to AMD-prediction by identifying the mineralogical features that control AMD-development and metal(loid) transport. Key mineralogical controls on AMD-development were identified for eight tailings samples representative of eight tailings piles and their respective mineral deposits across five major watersheds in the region of Arequipa, Peru. An integration of net acid generation tests, acid base accounting tests, paste pH tests, leachate aqueous geochemistry, automated mineralogy, and geochemical modeling determined the key mineralogical factors that lead to AMD. AMD, predicted to form in two Arequipa tailings piles, is the biggest threat to surface waters as effluent solutions can contain high acidity and high base metal concentrations. Even though most Arequipa tailings samples generate neutral-basic mine drainage, the most alkaline solutions in this category can transport potentially toxic metal(loid)s, like As, Se, Tl, and V. This study shows that automated mineralogy can provide quantitative information on controlling mineralogical characteristics to predict AMD generation without the time and costs associated with static leach tests and leachate chemical composition analyses. Relationships in sampled tailings highlight the influence of calcite, chlorite, epidote, amphibole, pyroxene, biotite, and pyrite mineral modal abundances on AMD formation. Quantitative automated mineralogy, in conjunction with thermodynamic considerations, is demonstrated to be a powerful tool to quickly and accurately assess environmental threats of tailings and waste rock to local water supplies.</p>

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Mineralogical Controls on Acid Mine Drainage from Tailings in Arequipa, Peru

  • 期刊论文

  • 发表日期：

    2025年7月7日

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  • Isaac J. P. Simon,
  • Katharina Pfaff,
  • James Ranville,
  • Madeleine N. Guillen Gomez,
  • Sergio Ticona-Corrales,
  • Elizabeth Holley

摘要

Acid mine drainage (AMD) generated from waste rock and tailings poses risks to water supplies globally through effluent acid solutions and mobilized metals and metalloids. Characterization of the environmental risks has traditionally focused on kinetic and static leach tests. However, the application of quantitative mineralogy using scanning electron microscope-based automated mineralogy to predict such risks is a growing field as it provides qualitative and quantitative datasets that directly characterize the acid generating potential of tailings. This study builds on the developing application of automated mineralogy to AMD-prediction by identifying the mineralogical features that control AMD-development and metal(loid) transport. Key mineralogical controls on AMD-development were identified for eight tailings samples representative of eight tailings piles and their respective mineral deposits across five major watersheds in the region of Arequipa, Peru. An integration of net acid generation tests, acid base accounting tests, paste pH tests, leachate aqueous geochemistry, automated mineralogy, and geochemical modeling determined the key mineralogical factors that lead to AMD. AMD, predicted to form in two Arequipa tailings piles, is the biggest threat to surface waters as effluent solutions can contain high acidity and high base metal concentrations. Even though most Arequipa tailings samples generate neutral-basic mine drainage, the most alkaline solutions in this category can transport potentially toxic metal(loid)s, like As, Se, Tl, and V. This study shows that automated mineralogy can provide quantitative information on controlling mineralogical characteristics to predict AMD generation without the time and costs associated with static leach tests and leachate chemical composition analyses. Relationships in sampled tailings highlight the influence of calcite, chlorite, epidote, amphibole, pyroxene, biotite, and pyrite mineral modal abundances on AMD formation. Quantitative automated mineralogy, in conjunction with thermodynamic considerations, is demonstrated to be a powerful tool to quickly and accurately assess environmental threats of tailings and waste rock to local water supplies.