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Access Type
WSU Access
Date of Award
January 2025
Degree Type
Dissertation
Degree Name
Ph.D.
Department
Civil and Environmental Engineering
First Advisor
Shawn P. McElmurry
Second Advisor
Nancy G. Love
Abstract
Cooling towers (CTs) are vital for industrial and commercial operations, playing a critical role in heat exchange systems. However, they also can present significant public health risks as hotspots for Legionella bacteria, the pathogens responsible for Legionnaires’ disease. Under favorable environmental and operational conditions, Legionella can proliferate in CTs and spread through aerosolized droplets, posing substantial risks to vulnerable populations. Despite advancements in monitoring technologies and microbial control strategies, current practices often struggle to predict and control Legionella colonization. Challenges include the inconsistent collection of data, methodological gaps, and limited integration of biologically relevant parameters. This dissertation aims to address these limitations by evaluating and improving Legionella monitoring methodologies through three interconnected objectives.
The first aim involved a retrospective analysis of over 70 CTs in Detroit, MI, monitored following the discovery of nearby legionellosis cases. Data from automated controllers and culture-based Legionella tests were analyzed to evaluate the predictive power of standard water quality parameters. Advanced statistical tools were applied to identify key factors influencing Legionella colonization but with limited statistical power. This highlighted the limitations of traditional data collection and monitoring practices that were investigated with a designed observational experiment.The second aim focused on a prospective case study applying a systematic approach to measure Legionella dynamics in six full-scale systems. To improve statistical power, the experiment performed weekly water quality testing, integrating supplemental parameters like free halogen, pH, and dissolved oxygen. Legionella quantification was performed using quantitative polymerase chain reaction (qPCR) alongside traditional culture methods. The effect of changes to the microbial control program on Legionella results were successfully identified due to the improved statistical quality of the prospective data.
The third aim synthesized findings into predictive models to enhance Legionella monitoring and risk assessment frameworks. Using tailored regression approaches, the prospective models significantly improved inferential and predictive capabilities compared to retrospective models. Additionally, the alignment of culture and qPCR data provided insights into reconciling standardized action thresholds.
By addressing critical gaps in current practices, this dissertation advances Legionella monitoring strategies, offering practical, data-driven tools to enhance public health outcomes and mitigate risks associated with CT systems.
Recommended Citation
Zarb, Audrey Rose, "Bridging Methodological Gaps In Legionella Monitoring Of Full-Scale Cooling Towers" (2025). Wayne State University Dissertations. 4249.
https://digitalcommons.wayne.edu/oa_dissertations/4249