Water Online

January 2017

Water Innovations gives Water and Wastewater Engineers and end-users a venue to find project solutions and source valuable product information. We aim to educate the engineering and operations community on important issues and trends.

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efficiency of the biological hazards during each process in the WWTP can be studied. Typical pollutants are defined for treated discharge quality assessment, including biochemical oxygen demand (BOD), chemical oxygen demand (COD), nitrogen, phosphorus, oil and grease, suspended solids, and coliform bacteria. The overall treatment procedure of a WWTP is divided into three different types: physical treatment (primary treatment), biological treatment (secondary treatment), and chemical treatment (tertiary treatment or disinfection). Based on the function of each treatment process, the pollutants are linked to one or several treatment processes for removal or inactivation. In the fault tree analysis, the quality risk assessment of each pollutant is analyzed separately, and the overall quality risk assessment of the WWTP is determined based on the results of each part. For the quality risk assessment of each pollutant, three main conditions are considered: the treatment process failure, the facility monitoring system failure, and the effluent quality test sensor failure. The treatment process failure mainly considers the mechanical failure of the treatment equipment and other causes (e.g., insufficient or excessive chlorine, insufficient contact time). The monitoring system failure indicates the failure of the monitoring equipment that is used for fault detection and diagnosis in each treatment process (e.g., the supervisory control and data acquisition [SCADA] system). Effluent quality test sensor failure means the failure of sensors that are used for effluent water quality tests. A set of effluent water quality risk metrics can be defined and calculated by the software tool, including the Probability of Excessive Suspended Solids; Probability of Excessive Oil and Grease; Probability of Excessive BOD, Nitrogen, Phosphorus; Probability of Excessive COD and Coliform Bacteria; Failure Probability of WWTP Effluent Quality Test Sensor; and Probability of Unsatisfied Effluent Quality. More planners and regulators rely on risk-based decision making. This unique, versatile software tool is believed to be a useful addition to the existing asset management tools in the current market for facilitating informed decisions on risk reduction in the evolving wastewater sector. n Acknowledgment This project was supported by National Science Foundation Industry/ University Cooperative Research Center on Water Equipment & Policy located at University of Wisconsin-Milwaukee and Marquette University. wateronline.com n Water Innovations 27 RISKANALYSIS Dr. Lingfeng Wang, Ph.D., is an associate professor in the Department of Electrical Engineering and Computer Science at the University of Wisconsin-Milwaukee, where he directs the Research Laboratory of Trustworthy Cyber-Physical Systems and Infrastructures. His research is focused on addressing challenging issues on reliability, cyberse- curity, and resiliency for contemporary critical infrastructures (e.g., drinking water distribution networks and wastewater reclamation facilities) from the perspectives of cyber-physical systems and water- energy nexus. Email: l.f.wang@ieee.org About The Author

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