Abstract
Geochemical modeling of precipitation reactions in the complex matrix of acid mine drainage is fundamental to understanding natural attenuation, lime treatment, and treatment procedures that separate constituents for potential reuse or recycling. The three main dissolved constituents in acid mine drainage are iron, aluminum, and sulfate. During the neutralization of acid mine drainage (AMD) by mixing with clean tributaries or by titration with a base such as sodium hydroxide or slaked lime, Ca(OH)2, iron precipitates at pH values of 2–3 if oxidized and aluminum precipitates at pH values of 4–5 and both processes buffer the pH during precipitation. Mixing processes were simulated using the ion-association model in the PHREEQC code. The results are sensitive to the solubility product constant (Ksp) used for the precipitating phases. A field example with data on discharge and water composition of AMD before and after mixing along with massive precipitation of an aluminum phase is simulated and shows that there is an optimal Ksp to give the best fit to the measured data. Best fit is defined when the predicted water composition after mixing and precipitation matches most closely the measured water chemistry. Slight adjustment to the proportion of stream discharges does not give a better fit.
Highlights
Geochemical modeling is often limited by lack of sufficient mineralogic and hydrologic data, lack of sufficient temporal and spatial data, and lack of sufficient understanding of complex processes that dictate water compositions [1]
The two acid mine drainage (AMD) sample compositions were obtained from the Leviathan Mine data set [15] and the Berkeley Pit data set [16], and a spreadsheet provided by the Montana Bureau of Mines and Geology
The first important result is that the amount of portlandite needed to neutralize this water to a pH near 7 is about 21 mmoles, which is substantially less than the 68 mmoles of base needed to neutralize the Leviathan Mine water
Summary
Geochemical modeling is often limited by lack of sufficient mineralogic and hydrologic data, lack of sufficient temporal and spatial data, and lack of sufficient understanding of complex processes that dictate water compositions [1]. Substantial progress has been made over the last century and sophisticated codes use models to simulate mineral precipitation/dissolution, sorption, gas exchange, ionic strength effects, thermal effects, and transport [2]. Even with these advances, numerous assumptions must be made when applying these simulations to field conditions. Ferrihydrite, akagenéite, lepidocrocite, and goethite may co-precipitate during oxidation of dissolved ferrous iron. Mixtures of these minerals have been found associated with
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