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Lynntech, Inc.

Superfund Research Program

Real-time Monitoring of Bioremediation

Project Leader: G. Duncan Hitchens
Grant Number: R43ES017570
Funding Period: Phase I: September 2009 August 2010

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Summary

The Specific Aims of Phase I are to implement a suitable electrochemical sensor design and evaluate its functionality as a biofilm monitor. The focus will be on devising a sensor that has the potential to be manufactured as a low cost item. The sensor function will be evaluated in an artificial soil environment, using microorganisms that play a significant role in the anaerobic remediation of contaminated soil and groundwater. Functionality will be established by correlating the sensor output to changes in the environment and to the biodegradation rates of representative soil and groundwater contaminants.

Researchers will study a fundamentally different method to monitor microbial activity using an electrochemical cell where the anodic potential is controlled using a reference electrode. A wide variety of amperometric and voltammetric techniques can then be applied (Bard & Faulkner 2001). researchers will gain considerably by being able to obtain electrochemical information that directly relates to the bacterial metabolic activity, by excluding voltage effects occurring in the other parts of the electrochemical circuit. This will provide for example, a direct insight into the response to amendments made to the soil to stimulate biological activity. Additionally, with this method researchers will have the ability to obtain electrochemical (voltage vs. current) profiles of metallic and other reactive species in the biofilm environment providing a completely new information into the functioning of a subsurface biofilm in real time.

Heavy metal contamination of subsurface environments such as soil, sediment, and groundwater is a worldwide threat to human health. Lynntech is proposing to develop a sensor to provide real-time monitoring of heavy metal bioremediation leading to more effective and less costly methods of removing heavy metal contamination from subsurface environments.

Since the industrial revolution, pollution of subsurface environments by heavy metals has increased substantially from anthropogenic sources such as industrial effluents, military munitions manufacturing, and mining activities. Heavy metals cannot be degraded and therefore accumulate in soils, sediments, and groundwater, posing significant health risks to plants, animals, and humans. Because of the threat to the environment and human health, major efforts are underway to develop remediation strategies to treat heavy metal contaminated soil and groundwater. Bioremediation is rapidly gaining popularity as a less expensive alternative to tradition “pump and treat” methods of remediating heavy metal contaminated soils. Although bioremediation relies the natural interaction of microorganisms with heavy metals, its successful use is highly dependent on the complex interactions between microorganisms, hydrological transport, abiotic chemical species, nutrient availability, etc. This complexity makes it extremely difficult to model, design, or implement effective bioremediation strategies. Bioremediation is further complicated by biogeochemical heterogeneity both site-to-site and spatially and temporally within a site. A number of ex situ analytical processes are available to provide information that can help assess bioremediation but the sheer complexity and heterogeneity of the processes involved seriously limit their usefulness.

In order for rapid advances and cost reductions to occur in the use of bioremediation, real-time monitoring of relevant parameters in situ in the subsurface are needed. Lynntech proposes to develop a microbial biosensor that provides highly relevant, real-time information needed to efficiently implement bioremediation strategies. The proposed sensor utilizes microorganisms directly involved in bioremediation that are native to the contaminated site of interest and acts as a real-time gauge of bioremediation activity. Combining a network of these sensors with traditional analytical methods permits the mapping of bioremediation with an unprecedented level of accuracy and relevance and will be critical to understanding and ultimately controlling the complex biogeochemical processes involved in bioremediation. Successful development of these sensors will provide a means to rapidly develop and optimize site-specific bioremediation strategies that are more effective and far less costly than current approaches.

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