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Automated monitoring of organic and bacterial drinking water constitution via PARAFAC fluorescence spectroscopy and flow cytometry
Citation Link: https://doi.org/10.15480/882.14887
Publikationstyp
Doctoral Thesis
Date Issued
2025
Sprache
English
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2025-02-12
TORE-DOI
First published in
Number in series
11
Citation
Institut für Wasserressourcen und Wasserversorgung 11: (2025)
Ensuring high drinking water quality is of major public health concern, protecting consumers from harmful consequences. One relevant concern about drinking water quality is the content of dissolved organic matter (DOM) which can be related to source water quality and treatment needs. Additionally, the bacterial constitution is crucial to monitor evolving changes in time and respond appropriately. However, DOM characterizing methods are a compromise between analytical effort, time and data quality while bacterial methods such as cultivation are labor-intensive, time-consuming and difficult to adapt to online measurements. Therefore, developing an automated monitoring system that quickly and consistently analyzes water quality data with high detail is vital.
This work examines the application of parallel factor analysis (PARAFAC) fluorescence spectroscopy to characterize DOM content and flow cytometry to monitor the presence of bacteria in drinking water. The specific research objectives of this work were mainly to further develop, combine and automate, and test both methods in real-world applications.
Using PARAFAC fluorescence spectroscopy, DOM compositions of investigated drinking waters, originating from groundwater in Northern Germany, were described through a respective fluorescence score of six compounds (C1–C6). Additionally, the total cell count (TCC) and the proportion of high nucleic acid cells (%HNA) were determined via flow cytometry describing the bacterial constitution. Scenarios of water quality changes were simulated in the laboratory by spiking one specific drinking water with increasing amounts of water samples of varying water quality. Water quality could be described by generating parameter-specific baselines defining their thresholds. Strongly deviating waters, e.g., wastewater effluent and rainwater, were identified in lower volume proportions than less strongly deviating waters. Regarding sensitivity, C1–C3 and TCC were the most performant for detecting water quality changes, e.g., due to a contamination event.
Automation of both methods required hardware and software extensions and development. Sampling, data analysis, evaluation, and visualization were the automation objects addressed in this work. In the context of near real-time drinking water analysis, the time required from sampling to data visualization was reduced to less than 15 minutes.
In pilot plant trials utilizing a model drinking water distribution system, combined methods were tested to detect water quality changes in a flowing system. Tests were performed to simulate events of water quality change. The combined system provided characteristic fingerprints of flowing water and detected sudden changes. 300 m behind the injection point, continuous induction of wastewater effluent and rainwater could be detected under appropriate conditions. In a large-scale measurement campaign, a three-component PARAFAC model (c1–c3) was proven to characterize groundwater DOM individually and can be applied to estimate humic substances concentrations in groundwater.
In conclusion, it can be stated that PARAFAC fluorescence spectroscopy in conjunction with flow cytometry represents a rapid and powerful system for the comprehensive characterization of DOM and the presence of bacteria in both drinking water and groundwater. The continuous and automatic monitoring of the emphasized parameters enables to recognize even minor deviations in water characteristics.
This work examines the application of parallel factor analysis (PARAFAC) fluorescence spectroscopy to characterize DOM content and flow cytometry to monitor the presence of bacteria in drinking water. The specific research objectives of this work were mainly to further develop, combine and automate, and test both methods in real-world applications.
Using PARAFAC fluorescence spectroscopy, DOM compositions of investigated drinking waters, originating from groundwater in Northern Germany, were described through a respective fluorescence score of six compounds (C1–C6). Additionally, the total cell count (TCC) and the proportion of high nucleic acid cells (%HNA) were determined via flow cytometry describing the bacterial constitution. Scenarios of water quality changes were simulated in the laboratory by spiking one specific drinking water with increasing amounts of water samples of varying water quality. Water quality could be described by generating parameter-specific baselines defining their thresholds. Strongly deviating waters, e.g., wastewater effluent and rainwater, were identified in lower volume proportions than less strongly deviating waters. Regarding sensitivity, C1–C3 and TCC were the most performant for detecting water quality changes, e.g., due to a contamination event.
Automation of both methods required hardware and software extensions and development. Sampling, data analysis, evaluation, and visualization were the automation objects addressed in this work. In the context of near real-time drinking water analysis, the time required from sampling to data visualization was reduced to less than 15 minutes.
In pilot plant trials utilizing a model drinking water distribution system, combined methods were tested to detect water quality changes in a flowing system. Tests were performed to simulate events of water quality change. The combined system provided characteristic fingerprints of flowing water and detected sudden changes. 300 m behind the injection point, continuous induction of wastewater effluent and rainwater could be detected under appropriate conditions. In a large-scale measurement campaign, a three-component PARAFAC model (c1–c3) was proven to characterize groundwater DOM individually and can be applied to estimate humic substances concentrations in groundwater.
In conclusion, it can be stated that PARAFAC fluorescence spectroscopy in conjunction with flow cytometry represents a rapid and powerful system for the comprehensive characterization of DOM and the presence of bacteria in both drinking water and groundwater. The continuous and automatic monitoring of the emphasized parameters enables to recognize even minor deviations in water characteristics.
Subjects
drinking water quality
flow cytometry
dissolved organic matter (DOM)
PARAFAC
fluorescence spectroscopy
real-time monitoring
DDC Class
628.1: Water Supply Systems
Funding Organisations
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Schuster_Jonas_Automated-Monitoring-of-Organic-and-Bacterial-Drinking-Water-Constitution-via-PARAFAC-Fluorescence-Spectroscopy-and-Flow-Cytometry.pdf
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