Online microbial fingerprinting for quality management of drinking water: Full-scale event detection

Online characterization of bacterial processes in drinking water systems

“…The decrease in bacterial cell concentration at the network location during the period of 25-26 August 2019 could be attributed to higher water consumption in the network. Other studies reported that higher variations in total cell numbers in the network can be affected by environmental factors such as water temperature, water consumption, residual chlorine concentration, and stagnation time 1,4,13 . The regrowth of bacterial cells and biofilms in DWDSs can cause higher total cell numbers in the network due to the reduced residual chlorine concentration through the distribution pipelines.…”

“…Drinking water quality guidelines protect public health by applying limits on concentrations of contaminants in drinking water. Bacterial growth in drinking water distribution systems (DWDSs) can lead to failure in meeting water quality guidelines, deterioration of the aesthetics of the water, and might be linked with an increased risk of diseases 1 . The microbial water quality in DWDSs can deteriorate if a suitable growth environment exists 2 .…”

Computational Surveillance of Microbial Water Quality With Online Flow Cytometry

“…Transforming multivariate fingerprinting features into a process control signal is a new area of research, with contributions from Props et al (2018) and Favere et al (2020). In this work, our FP algorithm of choice was PB since it is fast to compute, it intrinsically adapts to any FCM distribution, and it is applicable to dimensions higher than 2.…”

“…In that context, flow cytometry (FCM) has emerged as a powerful and robust tool which allows for high-temporal-resolution monitoring (Egli and Stefan, 2015;Van Nevel et al, 2017b;Safford and Bischel, 2018). Several studies have been conducted on drinking water plants, as well as groundwater used for drinking water supply, to show the additional insights that are gained on the dynamics of the microbial communities compared to traditional cultivation methods (Cheswick et al, 2019;Kantor et al, 2019;Favere et al, 2020). The basic principle of flow cytometry measurements is the detection and counting of suspended particles present in a water samples by passing them one by one through a laser beam.…”

“…Koch et al (2014) identified microbial differences in electroactive biofilms grown under different substrate conditions using multiple fingerprint calculation approaches, and Props et al (2018) applied a cluster analysis on fingerprinting features to differentiate between natural freshwater microbial communities. In contrast, a recent study has developed an online processing method that was shown to be effective in drinking water quality monitoring (Favere et al, 2020). Based on flow cytometric fingerprints, Favere et al used the Bray-Curtis dissimilarity to detect drastic microbial water changes in the incoming and exiting water streams of a water tower.…”