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Characterizing hydrogeochemical profiles and metal(loid) transport processes from mining in Arequipa, Peru
Simon, Isaac
Simon, Isaac
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2024
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Abstract
Acid Mine Drainage forms one of the world’s greatest environmental concerns related to metal mining activities. Effluent waters from small scale as well as large scale mining can mobilize metal(loid)s and high acidity which contaminate surrounding surface water supplies. As such, identifying the processes that control metal(loid) contaminant transport from mining related activities, mine waste, and tailings is an important step to mitigation or remediation strategies in the metals mining industry. Previous studies on Acid Mine Drainage prediction and metal(loid) transport have focused on characterizing mine wastes and tailings through through static leach tests, kinetic leach tests, leachate compositional analysis, mineralogical characterization, and geochemical modeling. Furthermore, static and kinetic leach tests are standard practices for Acid Mine Drainage prediction in the mining industry. However, this work focuses on documenting quantitative automated mineralogy as a powerful tool for Acid Mine Drainage prediction as mineral modal abundance and mineral textural properties can be captured in this analytical technique and can be used in thermodynamic models to predict the behavior of metal(loids) in waste rock and tailings. This work also focuses on documenting the contaminant-transport hydrogeochemical profiles that are controlled by tailings mineralogical properties and the mineral deposit type that is being mined. The state of Arequipa in southern Peru features a wide variety of magmatic-hydrothermal mineral deposit types which are mined by both large-scale operators and small-scale and artisanal mining (ASM). The district has diverse mineral deposit styles and diverse mining waste compositions and therefore is a suitable site for characterization of variable mining-related hydrogeochemical profiles and contaminant-transport mechanisms. Presentation of results by mineral deposit type is particularly useful for intrusion-related gold deposits which are commonly operated by ASM workers, allowing implementation of results as screening tools in formalization of this important livelihood.
In this dissertation I present studies which show 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. Futhermore, in this dissertation I present workflows that leverage existing water quality monitoring, geological, seasonal, and mineralogical information, followed by applying statistical calculations and geochemical modeling to identify contaminant-sources and transport mechanisms to surface waters. This body of work shows the value of quantitative automated mineralogy data and how this data set can be used as an initial, quick, cost-effective tool to predict the water-contamination threats of mining mineral deposits. Additionally, I show the value of newly-developed workflows, integrating published water quality monitoring data in conjunction with quantitative mineralogical data, statistical considerations, and thermodynamic models to establish watershed-specific geochemical processes and seasonal controls on metal(loid) mobility from mining. The workflow is applied to case studies on specific watersheds in the state of Arequipa in southern Peru with contrasting water quality characteristics to identify contaminant sources and rock types that are directly responsible for acid generation or acid neutralization in mining active regions.
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