There is a growing debate among research and practice communities on adequate strategies that reduce consumer exposure to accidental microbial contaminations or deliberate attacks in drinking water distribution systems (DWDS). To limit the spread of disease in a contamination event, effective strategies are multi-barrier approaches that include prevention, detection, mitigation and source elimination.
Typically, early public health protection relies on the passive efficacy of a disinfectant residual. However, little is known on its real ability to successfully inactivate intruding pathogens in the DWDS before water reaches consumers. A second barrier is provided by rapid and adequate response to emergency scenarios.
To this aim, an automatic sensor system t o continuously monitor water quality in DWDS would be very important as an early detection system and for contamination source location identification to eliminate or isolate the source problems. First preliminary objective is the development of a general method that, through the use of water quality modelling, systematically and quantitatively measures the ability of a particular system operation design to reduce consumer exposure to hazardous contaminations in DWDS.
Second objective is to explicitly use t he vulnerability assessment scheme to compare and select alternative system operation designs that may preventively provide an improved barrier to protect consumers until a contamination event is detected and consequent action is taken. This scheme will al so allow for the evaluation of adequate mitigation strategies to be adopted once water quality problems have been detected.
Finally, a methodology and tool set will be developed to identify the optimal sensor layout that, from the one hand reduces consumer exposure risks to contaminations and from the other hand is able to provide valuable information to identify, at least statistically, network zones that may be the cause of water quality problems.
Fields of science
- medical and health scienceshealth sciencespublic health
- engineering and technologyenvironmental engineeringwater treatment processesdrinking water treatment processes
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorssmart sensors
- natural sciencesearth and related environmental scienceshydrology
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