4.7 Article

On-line detection of Escherichia coli intrusion in a pilot-scale drinking water distribution system

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 198, Issue -, Pages 384-392

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2017.04.090

Keywords

Bacterial contamination; Drinking water distribution; On-line measurement; Water quality monitoring

Funding

  1. Finnish Agency for Technology and Innovation (TEKES) [968/31/08]
  2. Olvi Foundation [201400025]
  3. Kuopio Water

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Improvements in microbial drinking water quality monitoring are needed for the better control of drinking water distribution systems and for public health protection. Conventional water quality monitoring programmes are not always able to detect a microbial contamination of drinking water. In the drinking water production chain, in addition to the vulnerability of source waters, the distribution networks are prone to contamination. In this study, a pilot-scale drinking-water distribution network with an on-line monitoring system was utilized for detecting bacterial intrusion. During the experimental Escherichia coli intrusions, the contaminant was measured by applying a set of on-line sensors for electric conductivity (EC), pH, temperature (T), turbidity,UV-absorbance at 254 nm (UVAS SC) and with a device for particle counting. Monitored parameters were compared with the measured E. coli counts using the integral calculations of the detected peaks. EC measurement gave the strongest signal compared with the measured baseline during the E. coli intrusion. Integral calculations showed that the peaks in the EC, pH, T, turbidity and UVAS SC data were detected corresponding to the time predicted. However, the pH and temperature peaks detected were barely above the measured baseline and could easily be mixed with the background noise. The results indicate that on-line monitoring can be utilized for the rapid detection of microbial contaminants in the drinking water distribution system although the peak interpretation has to be performed carefully to avoid being mixed up with normal variations in the measurement data. (C) 2017 Elsevier Ltd. All rights reserved.

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