In-situ techniques for monitoring drinking water quality

Author(s):  
Inge Elfferich ◽  
Elizabeth Bagshaw ◽  
Rupert Perkins ◽  
Peter Kille ◽  
Sophie Straiton ◽  
...  

<p>Efficient management of drinking water quality is critical for the water supply, so effective monitoring of supply and storage systems is a priority. This project aims to predict the presence of Taste and Odour (T&O) compounds in drinking water reservoirs, using molecular analyses and smart in-situ monitoring systems. The most common T&O compounds, Geosmin and 2-MIB, are secondary metabolites that can be produced in waterbodies by cyanobacteria and actinomycetes and impact drinking water taste and odour. Although there is no evidence of related health risks, they can be perceived by humans at very low concentrations (5-10 ng/L) and the treatment process to remove them from drinking water is costly. Early assessment of T&O risk is crucial, but currently requires time-consuming and costly sampling as well as laboratory analysis which prevents real-time monitoring and a timely management response.</p><p>Cyanobacterial species responsible for T&O production can be monitored with eDNA techniques and potentially provide an early warning of T&O episodes. Moreover, detection of the genes that are responsible for T&O production within the DNA of the freshwater community can help to speed up analysis. We show that qPCR methods can target the Geosmin synthase gene (geoA) and that this correlates significantly with Geosmin concentrations >15 ng/L. Alternatively, in-situ sensors that can be deployed remotely and transmit data, can provide real-time monitoring for early warning and potentially predictive capacity. Commercially available sensors do not currently exist for T&O compounds, but they do for many other water quality parameters. We consider the analytes that could be effective for T&O warning systems, using a Welsh reservoir as an exemplar case. Assessment of nutrient dynamics suggests N and P ratios are critical, hence we evaluate the sensors that are available for these compounds and associated environmental controls on their behaviour. We present recommendations for the design of an in-situ monitoring programme and introduce the planned tests that will evaluate it.</p>

2017 ◽  
Vol 3 (5) ◽  
pp. 865-874 ◽  
Author(s):  
Zhiheng Xu ◽  
Wangchi Zhou ◽  
Qiuchen Dong ◽  
Yan Li ◽  
Dingyi Cai ◽  
...  

Drinking water quality along distribution systems is critical for public health.


Author(s):  
Srinivas Panguluri ◽  
Roy C. Haught ◽  
Craig L. Patterson ◽  
E. Radha Krishnan ◽  
John Hall

1996 ◽  
Vol 54 (5) ◽  
pp. 511-516 ◽  
Author(s):  
Robert E. Quick ◽  
Linda V. Venczel ◽  
Nancy H. Bean ◽  
Anita K. Highsmith ◽  
Erika H. De Hannover ◽  
...  

Fact Sheet ◽  
2011 ◽  
pp. 1-2 ◽  
Author(s):  
Brian A. Pellerin ◽  
Brian A. Bergamaschi ◽  
Peter S. Murdoch ◽  
Bryan D. Downing ◽  
John Franco Saraceno ◽  
...  

2017 ◽  
Vol 7 (1.1) ◽  
pp. 47 ◽  
Author(s):  
S. Kavi Priya ◽  
G. Shenbagalakshmi ◽  
T. Revathi

Drinking Water Distribution Systems facilitate to carry portable water from water resources such as reservoirs, river, and water tanks to industrial, commercial and residential consumers through complex buried pipe networks. Determining the consequences of a water contamination event is an important concern in the field of water systems security and in drinking water distribution systems. The proposed work is based on the development of low cost fuzzy based water quality monitoring system using wireless sensor networks which is capable of measuring physiochemical parameters of water quality such as pH, temperature, conductivity, oxidation reduction potential and turbidity. Based on selected parameters a sensing unit is developed along with several microsystems for analog signal conditioning, data aggregation, sensor data analysis and logging, and remote representation of data to the consumers. Finally, algorithms for fusing the real time data and decision making using fuzzy logic at local level are developed to assess the water contamination risk. Based on the water contamination level in the distribution pipeline the drinking water quality is classified as acceptable/reject/desirable. When the contamination is detected, the sensing unit with ZigBee sends signals to close the solenoid valve inside the pipeline to prevent the flow of contaminated water supply and it intimates the consumers about drinking water quality through mobile app. Experimental results indicate that this low cost real time water quality monitoring system acts as an ideal early warning system with best detection accuracy. The derived solution can also be applied to different IoT (Internet of Things) scenario such as smart cities, the city transport system etc.


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