Assessing a Fluorescence Spectroscopy Method for In-Situ Microbial Drinking Water Quality

Abstract

Waterborne disease is a significant contributor to the global burden of disease, in particular among high-risk populations in developing nations. State-of-the-art methods for the enumeration of microbial pathogens in drinking water sources have important limitations, including high initial cost, 24-48 hour delays in results, high staffing and facility requirements, and training requirements which all become especially problematic in the developing nation context.A number of alternative approaches to microbial water quality testing have been proposed, with the goal of decreasing the required testing time, decreasing overall costs, leveraging appropriate technology approaches, or improving sensitivity or specificity of the water quality testing method. One approach that may offer solutions to some of these limitations involves the deployment of sensor networks using fluorescent spectroscopy to detect intrinsic protein fluorescence in water samples as a proxy for microbial activity. In recent years, a number of researchers have found significant and meaningful correlations between indicator bacteria species and the protein fluorescence of drinking water samples. Additionally, advances in the semiconductor industry could be used to drive down the cost of such sensors. This technology may also be extensible to other water quality parameters, including dissolved organic matter or the presence of fluorescent pollutants.In this thesis, a literature review describes the fundamentals of fluorescence spectroscopy, historical and recent work regarding the fluorescence of the amino acid tryptophan and associated bacterial fluorescence, possible mechanisms for this ii association, and potential applications of this technology for drinking water quality monitoring and waste water process control. Extensibility of the technology is also discussed.Next, experimental methodology in reproduction of similar results is described.Samples were taken from seven (7) iv Acknowledgements

Possibilities of Real Time Monitoring of Micropollutants in Wastewater Using Laser-Induced Raman & Fluorescence Spectroscopy (LIRFS) and Artificial Intelligence (AI)

“…Differentiating the extraction points shows that the correlation is significantly higher for the effluent samples (R 2 = 0.95) than for the Considering all samples, the coefficient of determination is R 2 = 0.75. This result is largely in line with the literature values [94,95]. Differentiating the extraction points shows that the correlation is significantly higher for the effluent samples (R 2 = 0.95) than for the influent samples (R 2 = 0.19).…”

“…Considering all samples, the coefficient of determination is R 2 = 0.75. This result is largely in line with the literature values [94,95]. Differentiating the extraction points shows that the correlation is significantly higher for the effluent samples (R 2 = 0.95) than for the Considering all samples, the coefficient of determination is R 2 = 0.75.…”

“…The evaluation of these in a literature-published hypothesis revealed a correlation between the tryptophan-like peak and DOC, which was another focus of the current investigation. According to [94], tryptophan is especially useful as a reporter for conformation changes in proteins, since several protein changes can result in predictable changes in tryptophan fluorescence in a sample [94]. On the other Regarding online wastewater monitoring, another issue is the evaluation of the assumed correlation between the sum parameter DOC and the fluorescence intensity in the biological treatment stage [91][92][93].…”