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2001 Winning Research Project

Preventing Upsets, Ensuring Optimal Treatment  

A sudden, subtle change in wastewater influent goes unnoticed until biological treatment processes degrade or fail. Effluent is released that has not been fully treated. An operator’s worst nightmare could then ensue: health risks, fines, newspaper articles, public inquiries. How can plant operators avoid this disaster? How can they react to change before it affects the plant’s biological processes? Operators need a “radar” to detect upsets.

Biological treatment processes in wastewater plants are often exposed to rapid changes (upsets) in incoming wastewater. Activated sludge systems, currently the most widely used type of biological treatment, depend on a healthy population of bacteria to maintain acceptable effluent quality. Upsets can interfere with, even damage, the treatment process, as the bacterial population responds to differences in influent. When this occurs, permit levels may be exceeded, resulting in environmental damage and costly fines; treatment facilities may need to be adjusted or overhauled, resulting in lost time and money.

In order to avoid such undesirable events, operators must make quick adjustments when upsets occur. Unfortunately, operators are often forced to react to changes, rather than taking proactive steps as a result of changing influent quality. And there is little solid research that describes the effect of rapid changes in wastewater characteristics on the treatment process. In the absence of such cause-and-effect knowledge, operators often cannot determine what actions to take in order to mitigate upsets.

Nancy Love’s research has sought to establish the cause-and-effect relationship to better understand how changes in influent wastewater affect the biological treatment process. Her work has focused on identifying the predominant biochemical, chemical, and/or physical causes that link source (wastewater) and effect (change in treatment process).

Love believes that stress responses controlled at the molecular/cellular level play a significant role in defining how biological treatment processes perform at the macroscopic level. Understanding these molecular activities could lead to development of monitoring strategies or warning devices that could alert operators to incipient upsets. Early warning of upsets could allow for preventative action that would minimize or eliminate all the negative consequences of upset.

Love’s past research on molecular-level stress responses in activated sludge cultures has demonstrated methods of quickly detecting the rapid induction of specific stress proteins in activated sludge cultures. Her research team has also investigated a stress response that links the influx of toxic chemicals to deflocculation in activated sludge; similar effects have been demonstrated in biofilm biological treatment systems. The team is currently working with the National Institute for Standards and Technology to develop a low-cost, plastic biosensor that detects stress-response inducing chemicals. Testing of the device on real wastewaters is complete and the project team continues to optimize its design.

Love’s research plan builds on past research efforts and uses cutting-edge technology to bring about a solution. Understanding molecular-level responses to upsets in biological treatment systems will lead to understanding of source-cause-effect relationships. By looking at stress responses, specifically those controlled by proteins, and by applying state of the art analytical technologies for protein separation and identification, Love is seeking to develop a protein array that can be used to detect the presence or absence of key, stress-indicating proteins that link source and effect. Ongoing research with molecular imprinted polymers (plastic antibodies) will be integrated into this work in an effort to develop environmentally robust protein fingerprinting sensors for field application.

The end result? At least the first step in creating the “radar” that operators need, the early warning system to detect upsets and prevent the nightmare of process breakdown.

 


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