Simulating Biogeochemical Transport And Flow Processes In Acid Mine Drainage To Optimize Bioremediation
Pandey, Sachin 1 ; Yacob, Tesfayohanes 2 ; Silverstein, JoAnn 3 ; Rajaram, Harihar 4 ; Tasker, Travis 5 ; Minchow, Kristina 6 ; Basta, Jelena 7
1 University of Colorado
2 University of Colorado
3 University of Colorado
4 University of Colorado
5 Allegheny College
6 University of Colorado
7 Boulder High School
Acid mine drainage (AMD) has significant deleterious impacts on natural water quality, and it is often difficult to predict using traditional methods (Kuipers et. al, 2006). In-situ bioremediation is being investigated to inhibit the oxidation of sulfidic minerals catalyzed by iron oxidizing bacteria. Addition of organic carbon may stimulate heterotrophic bacterial communities to compete for oxygen, the limiting reagent. Current computational models of AMD rarely account for biogeochemical interactions and fail to model fate and transport of organic carbon, a critical component of bioremediation. I am developing a rigorous reactive transport model that considers these complexities to simulate both AMD generation and inhibition. We are using experimental results to calibrate the model, and hope to evaluate carbon dosing and application frequency effects on biostimulation.
Tracer experiments in waste-rock columns were conducted to determine transport parameters (Fig. 1). Optimization of a dual domain (mobile/immobile) convection diffusion model using CXTFIT 2.1 (Toride et al., 1999) provided the best fit (R2 = 0.986), indicating solute exchange between macropores and rock matrices. Calculated values of porewater velocity, dispersion coefficient, and ratio of mobile water content to total water content were 0.50 cm/min, 17 cm2/min, and 0.29, respectively. Heterotrophs release soluble microbial growth products (SMPs) capable of complexing free Fe(III), which also inhibits AMD (Marchand and Silverstein, 2002). We are estimating bulk equilibrium binding constants for different SMPs using the method of least squares after testing the approach with a well-known biological chelator, Deferoxamine Mesylate (DFO). The DFO model using the optimized K (1015.7) was less than the literature value (1031) but behaved similiarly. The results of these parameterizations will be implemented using PFLOTRAN, a parallelized reactive transport model. I plan to modify PFLOTRAN by coupling microbial dynamics and single-rock scale elements to the existing pile-scale process capabilities.
Kuipers, J. R., A.S. Maest, K.A. MacHardy, and G. Lawson, 2006, Comparison of Predicted and Actual Water Quality at Hardrock Mines: The reliability of predictions in Environmental Impact statements. Kuipers & Associates, MT USA 59703.
Marchand, Eric A and JoAnn Silverstein, 2002, The Influence of Heterotrophic Microbial Growth on Biological Oxidation of Pyrite. Environmental Science and Technology, v. 36, p. 5483-5490.
Toride, N., F.J. Leij and M.T. van Genuchten, 1999, The CXTFIT Code for Estimating Transport Parameters from Laboratory or Field Tracer Experiments, Version 2.1. Research Report No. 137, U.S. Salinity Laboratory and U.S. Department of Agriculture. Riverside, California.