Keywords
drinking water; QMRA; decision support; water safety
Start Date
15-9-2020 6:20 PM
End Date
15-9-2020 6:40 PM
Abstract
Quantitative Microbiological Risk Analysis (QMRA) is a probabilistic approach performed to assess the microbiological safety of drinking water. Reported values in the literature are used for quantifying the removal of certain pathogens along the drinking water treatment process, but this has some limitations when evaluating real-time operation. Firstly, instability or failures in drinking water treatment plants (DWTPs) can severely affect the risk of drinking water, even in short-time events. Secondly, in the framework of climate change and water scarcity, non-conventional water sources such as recycled wastewater can play a key role in integrating water supply strategies, but this can lead to increase the pathogen load in DWTP influent water. The objective of this study is to develop a framework for a QMRA-based key performance indicator (KPI) that can act as an early-warning system in DWTPs. According to historical data and process knowledge, logarithmic reduction values were prescribed to coagulation/flocculation and rapid filtration processes from a range provided by previous literature. Finally, two scenarios were considered to validate the use of the developed KPI at a surface water DWTP. It was shown that when source water presented Cryptosporidium concentrations typical from peak events, the DWTP scheme was only effective when the treatment units accomplished a minimum degree of efficiency. In front of alternative water sources like a tertiary effluent from a wastewater treatment plant, it was shown that an additional separation process would be needed for a major degree of robustness in operating the DTWP. The developed framework can be implemented in commercial software for DWTPs monitoring and communicates risk of actual operation conditions in visual manner through a traffic light KPI.
Adapting the QMRA framework for a real-time decision support at DWTP
Quantitative Microbiological Risk Analysis (QMRA) is a probabilistic approach performed to assess the microbiological safety of drinking water. Reported values in the literature are used for quantifying the removal of certain pathogens along the drinking water treatment process, but this has some limitations when evaluating real-time operation. Firstly, instability or failures in drinking water treatment plants (DWTPs) can severely affect the risk of drinking water, even in short-time events. Secondly, in the framework of climate change and water scarcity, non-conventional water sources such as recycled wastewater can play a key role in integrating water supply strategies, but this can lead to increase the pathogen load in DWTP influent water. The objective of this study is to develop a framework for a QMRA-based key performance indicator (KPI) that can act as an early-warning system in DWTPs. According to historical data and process knowledge, logarithmic reduction values were prescribed to coagulation/flocculation and rapid filtration processes from a range provided by previous literature. Finally, two scenarios were considered to validate the use of the developed KPI at a surface water DWTP. It was shown that when source water presented Cryptosporidium concentrations typical from peak events, the DWTP scheme was only effective when the treatment units accomplished a minimum degree of efficiency. In front of alternative water sources like a tertiary effluent from a wastewater treatment plant, it was shown that an additional separation process would be needed for a major degree of robustness in operating the DTWP. The developed framework can be implemented in commercial software for DWTPs monitoring and communicates risk of actual operation conditions in visual manner through a traffic light KPI.
Stream and Session
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