Acid Mine Drainage

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Acid Mine Drainage
CIVIL ENGINEERING - Acid Mine Drainage
Acid Mine Drainage (AMD) is a serious environmental problem resulting from oxidation reactions in
sulfidic rock, which are catalyzed by iron-oxidizing bacteria. In-situ source control is a promising
approach for inexpensive and sustainable remediation of AMD. Previous research in our lab
demonstrated that addition of organic carbon to acid generating rock stimulates the growth of
heterotrophic microorganisms, consuming oxygen and sequestering ferric iron, thus inhibiting pyrite
oxidation. This project takes the next steps in evaluating carbon addition as a viable strategy for
remediation of waste rock sites. The overall goal of the project is to develop a fundamental quantitative
understanding of the coupled biogeochemical processes involved in the pyrite oxidation cycle and the
carbon cycle, facilitating the evaluation and design of a sustainable remediation process. From the scale
of microbial colonies on pyrite grains to the complex unsaturated flow paths at the waste rock pile scale
(see Figure below) the research approach recognizes the multi-scale interactions that generate AMD,
and are important factors in remediation by carbon addition. A unique aspect of the research is the
incorporation of state-of-the-art understanding of the biogeochemical mechanisms involved in the
pyrite oxidation cycle into a pile-scale reactive transport model. Most previous models for reactive
transport in waste rock piles use semi-empirical representations of pyrite oxidation, disregarding both
microbial kinetics and oxidation of pyrite by Fe3+, whose importance has been firmly established in
small-scale geochemical studies. None of the previous models consider carbon cycling. The proposed
research combines experiments and modeling across a range of scales. Students have the opportunity to
carry out experiments in waste rock tanks to determine microbial and chemical reaction rates, diffusion
and advective transport processes and to work with computational models to predict acid generation
and remediation conditions.
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