New insights into drinking water treatment, storage and distribution systems using Flow Cytometry.

dc.contributor.advisorHassard, Francis
dc.contributor.advisorJarvis, Peter
dc.contributor.authorPalazzo, Francesca
dc.date.accessioned2024-05-15T12:58:36Z
dc.date.available2024-05-15T12:58:36Z
dc.date.issued2022-09
dc.descriptionJarvis, Peter - Associate Supervisoren_UK
dc.description.abstractExcessive microbial regrowth in drinking water distribution systems (DWDS) signifies compromised biostability. In chlorinated DWDS, diminished chlorine residual and substantially elevated water age or transit times can pose risks to water safety. This study delves into microbial community dynamics within DWDS by analysing samples from 119 service reservoirs and 41 water towers across various water sources for six months (March-September 2021). Using Flow Cytometry (FCM) to directly measure microbial populations, surface water exhibited 4-10 times higher microbial loading compared to groundwater and mixed sources. Among these sites, two distinct microbial water quality compliance events (detection of culturable coliform bacteria) were identified through FCM data, each presenting different microbial trends. Factors influencing regrowth in DWDS, notably water age and free chlorine, were scrutinized. Elevated intact cell counts were noted with chlorine levels <0.50 mg/L and water ages surpassing 4 days. Multiple linear regression highlighted temperature as the prime factor affecting cell counts variability in surface and mixed waters. For groundwaters, water age was significant, likely due to decreased disinfectant residuals and minimal treatment of these sources. The Bray-Curtis similarity index, derived from FCM fingerprints, emerged as a potential metric for detecting biological instability in drinking water microbiomes. The findings underscore the necessity of optimally managed DWDS and emphasize the significance of maintaining chlorine levels, especially at higher water ages and temperatures – particularly relevant considering climate change. Through FCM and its fingerprint analysis, a more detailed view of DWDS dynamics is attainable, promoting possibility for enhanced system control. The implications of this research offering potential for safeguarding public health, ensuring consistent water quality, and pathways for more resilient and sustainable water distribution practices. As a prospective direction for future research, machine learning models could be developed to predict and classify microbial community dynamics in DWDS using the rich dataset provided by FCM fingerprints.en_UK
dc.description.coursenameMSc by Research in Wateren_UK
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21623
dc.language.isoen_UKen_UK
dc.publisherCranfield Universityen_UK
dc.publisher.departmentSWEEen_UK
dc.rights© Cranfield University, 2022. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.en_UK
dc.subjectFlow cytometryen_UK
dc.subjectdrinking wateren_UK
dc.subjectservice reservoiren_UK
dc.subjectwater toweren_UK
dc.subjectwater ageen_UK
dc.subjectfingerprint analysisen_UK
dc.titleNew insights into drinking water treatment, storage and distribution systems using Flow Cytometry.en_UK
dc.typeThesis or dissertationen_UK
dc.type.qualificationlevelMastersen_UK
dc.type.qualificationnameMResen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Palazzo_F_2022.pdf
Size:
1.11 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description: