M12 PM Remediation
Monday, 14 November 2005: 1:50 PM - 5:30 PM in 345-346

(KIN-1118-100556) Enhanced fuel biodegradation in a karst aquifer using a single-well injection.

King, L¹, Painter, R¹, Byl, T^{1, 2}, ¹ Tennessee State University, Nashville, TN, USA² USGS, Nashville, TN, USA

ABSTRACT- Microcosm studies indicate that anaerobic biodegradation of toluene is generally 50 times slower than aerobic biodegradation. Because of the potential for the rapid transport of dissolved contaminants in karst conduits, aerobic conditions are needed to enhance bioremediation. This study was divided into three phases. The objective of the first phase was to evaluate oxygen-release compounds (ORCs) to enhance fuel biodegradation by free-living bacteria found in karst aquifers. It was determined that 0.3% hydrogen peroxide resulted in the optimum enhanced fuel biodegradation by karst bacteria. The objective of the second phase was to develop a numerical method to quantify the rate of enhanced biodegradation using a single well for injection and monitoring. This was achieved by coupling the equation for residence-time distribution to a first-order rate of biodegradation and solving it using numerical differentiation. This approach was evaluated in a laboratory simulation using a single-well injection of H₂O₂ and NaCl (conservative tracer) into a 5-gallon carboy containing karst water with 100 ug/L toluene. There was close agreement between the predicted rate of toluene removal and the observed rate of removal in the experiment (18 percent), confirming the numerical approach. The objective of the third phase was to evaluate the approach in a field study. H₂O₂ and NaCl (100 gallons) were injected into a jet fuel-contaminated karst well and the same well was monitored for fuel concentration and geochemical constituents through time. The benzene and toluene concentrations in the well decreased at a rate similar to that predicted by the numerical model. This study demonstrated that the RTD-B approach can be used to quantify biodegradation in karst aquifers.

Key words: karst, bioremediation, predictive model