| Accelerated In Situ Bioremediation |
Accelerated in situ bioremediation is where substrate or nutrients are added to an aquifer to stimulate the growth of a target consortium of bacteria. Usually the target bacteria are indigenous, however enriched cultures of bacteria (from other sites) that are highly efficient at degrading a particular contaminant can be introduced into the aquifer (termed bioaugmentation). Accelerated ISB is used where it is desired to increase the rate of contaminant biotransformation, which may be limited by lack of required nutrients, electron donor, or electron acceptor. The type of amendment required depends on the target metabolism for the contaminant of interest. Aerobic ISB may only require the addition of oxygen, while anaerobic ISB often requires the addition of both an electron donor (e.g., lactate, benzoate) as well as an electron acceptor (e.g., nitrate, sulfate). Chlorinated solvents, in particular, often require the addition of a carbon substrate to stimulate reductive dechlorination. The goal of accelerated ISB is to increase the biomass throughout the contaminated volume of aquifer, thereby achieving effective biodegradation of dissolved and sorbed contaminant.
Our state-of-the-art facilities enable pilot and full-scale experimentation in the laboratory and in the field. We can perform any tests necessary to generate the microbial and engineering parameters for designing in situ or ex situ bioremediation systems.
Battelle can perform any site characterization test required to implement in situ bioremediation.
In state-of-the-art test cells, we evaluate groundwater flow in porous media and devise optimal strategies for in situ nutrient delivery and biofouling control.
Through sophisticated computing strategies for designing in situ bioremediation systems, Battelle can integrate geological, biological, and environmental data to simulate and optimize bioremediation processes. We use simulations to identify critical parameters of contaminant destruction and nutrient injection, we can predict optimal field operation strategies.