This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Water quality assessment is essential for maintaining healthy ecosystems and protecting human health. Data interrogation and exploratory data analysis techniques are used to analyze the spatial and temporal variability of water quality parameters, identifying correlations, and to better understand the factors that impacts microbial and chemical quality of water. The

Water quality assessment is essential for maintaining healthy ecosystems and protecting human health. Data interrogation and exploratory data analysis techniques are used to analyze the spatial and temporal variability of water quality parameters, identifying correlations, and to better understand the factors that impacts microbial and chemical quality of water. The seasonal dynamics of microbiome in surface waters were investigated to identify the factors driving these dynamics. Initial investigation analyzed two decades of regional water quality data from 20 various locations in Central Arizona, USA. Leveraging advanced data science techniques, the study uncovered correlations between crucial parameters, including dissolved organic carbon (DOC), ultraviolet absorbance (UVA), and specific ultraviolet absorbance (SUVA). These findings provide foundational insights into the dynamic of overall water quality. A comprehensive 12-month surface water sample collection and study was conducted to investigate potential bias in bacterial detection using EPA approved Membrane Filtration (MF) technique. The results underscore that while MF excels in recovering bacteria of public health significance, it exhibits biases, particularly against small and spore-forming bacteria and Archaea, such as Bacilli, Mollicutes, Methylacidiphilae, and Parvarchaea. This emphasizes the importance of complementing standard microbiology approaches to mitigate technological biases and enhance the accuracy of microbial water quality testing, especially for emerging pathogens. Furthermore, a complementary study of microbial dynamics within a model drinking water distribution systems (DWDSs) using treated water from the same source water as the above study. The influence of pipe material and water temperature on the microbiome and trace element composition was investigated. The research unveiled a preferential link between pipe material and trace elements, with water temperature significantly impacting the microbiome to a higher degree than the chemical composition of water. Notably, Legionellaceae and Mycobacteriaceae were found to be prevalent in warmer waters, highlighting the substantial influence of water temperature on the microbiome, surpassing that of pipe material. These studies provide comprehensive insights into the spatial and temporal variability of water quality parameters. Analyzing microbial data in depth is crucial in detecting bacterial species within a monitoring program for adjusting operational conditions to reduce the presence of microbial pathogens and enhance the quality of drinking water.
ContributorsAloraini, Saleh (Author) / Abbaszadegan, Morteza (Thesis advisor) / Fox, Peter (Committee member) / Perreault, Francois (Committee member) / Alum, Absar (Committee member) / Arizona State University (Publisher)
Created2023