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Predictive Modeling of Microcystin Concentrations in Drinking Water Treatment Systems Of Predictive Modeling of Microcystin Concentrations in Drinking Water Treatment Systems of Ohio and their Potential Health Effects Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By: Traven A. Wood, B.S. Graduate Program in Public Health The Ohio State University 2019 Thesis Committee: Mark H. Weir (Adviser) Jiyoung Lee Allison MacKay Copyright by Traven Aldin Wood 2019 Abstract Cyanobacteria present significant public health and engineering challenges due to their expansive growth and potential synthesis of microcystins in surface waters that are used as a drinking water source. Eutrophication of surface waters coupled with favorable climatic conditions can create ideal growth environments for these organisms to develop what is known as a cyanobacterial harmful algal bloom (cHAB). Development of methods to predict the presence and impact of microcystins in drinking water treatment systems is a complex process due to system uncertainties. This research developed two predictive models, first to estimate microcystin concentrations at a water treatment intake, second, to estimate the risks of finished water detections after treatment and resultant health effects to consumers. The first model uses qPCR data to adjust phycocyanin measurements to improve predictive linear regression relationships. Cyanobacterial 16S rRNA and mcy genes provide a quantitative means of measuring and detecting potentially toxic genera/speciess of a cHAB. Phycocyanin is a preferred predictive tool because it can be measured in real-time, but the drawback is that it cannot distinguish between toxic genera/speciess of a bloom. Therefore, it was hypothesized that genus specific ratios using qPCR data could be used to adjust phycocyanin measurements, making them more specific to the proportion of the bloom that is producing toxin. Data was obtained from a water treatment plant (WTP) intake at Tappan Lake, Ohio, a drinking water source for the Village of Cadiz. Using Pearson correlations and linear regressive analysis, it was found that adjusted phycocyanin, based on Planktothrix 16S and Planktothrix mcyE gene abundance ratios, exhibits improved correlation with microcystins. Furthermore, the analysis demonstrated the practicality of the adjustment in turning negative correlations between phycocyanin and microcystins to positive. More data from other water systems are needed to validate the findings ii of this study. The second model utilizes a stochastic method to model the risk of microcystin finished water detections after water treatment. Data needed for such a model include initial and finished water toxin detections, removal efficiencies of various treatment processes, and exposure data related to a consumer. Three different methods for modelling the health status of a bloom in order to determine the intra- to extracellular (E/I) ratio of initial toxin concentrations were explored. Then, water treatment characteristics specific to the 2014 Toledo Water Crisis (TWC) were modeled to obtain estimated finished water detections. Finally, health risks were estimated using a hazard quotient based on finished water detections and exposure scenarios. Risk estimates for children were greater than adults and present throughout the crisis. This model produced accurate predictive outputs that are consistent with conditions observed during the 2014 TWC. Furthermore, this model presents a novel method of assigning E/I ratios to initial microcystin concentrations, which is useful for assessing and predicting WTP resiliency amidst a changing bloom. Together, these models can serve as an innovative way of predicting microcystins from intake to tap. iii Acknowledgements Thank you to my fiancé and family for their encouragement and support through my academic journey. Thanks to Dr. Ruth Briland, Ohio Environmental Protection Agency; Donna Francy, United States Geological Survey (USGS); and members of the Tappan Lake Nutrient Reduction Initiative for data sharing. Most of all, a special thanks to Dr. Mark Weir for his mentorship, as well as Dr. Jiyoung Lee and Dr. Allison MacKay for their guidance and expertise. iv Vita May 2013 …………………………………………………………………….. Miller High School August 2017 ………………………………………. B.S. Environmental Health, Ohio University May-August 2017 ………Environmental Health Technician, Licking County Health Department May-September 2018 ………………………. …………………… Ohio EPA Internship Program January 2019-Present …………………Graduate Research Associate, The Ohio State University 2018 …………………… Lemeshow Student Excellence Scholarship, The Ohio State University Fields of Study Major Field: Public Health Specialization: Environmental Health Sciences v Table of Contents Abstract ........................................................................................................................................... ii Acknowledgements ........................................................................................................................ iv Vita .................................................................................................................................................. v List of Figures ................................................................................................................................. x List of Tables ................................................................................................................................. xi Chapter 1: Introduction to Microcystins and their Impact .............................................................. 1 1.1 Cyanobacteria and Cyanotoxins ............................................................................................ 1 1.2 Microcystin-Producing Genera ............................................................................................. 2 1.3 Dominant vs. Mixed Blooms ................................................................................................ 7 1.4 Microcystin Synthesis ........................................................................................................... 9 1.4.1 Microcystin Synthetase ................................................................................................... 9 1.4.2 Factors that affect Microcystin Synthesis ..................................................................... 10 1.4.3 Extracellular vs. Intracellular Toxin ............................................................................. 14 1.5 Monitoring Methods ............................................................................................................ 15 1.5.1 Microcystin Methods of Detection ............................................................................... 15 1.5.2 Quantitative Polymerase Chain Reaction (qPCR) ........................................................ 16 1.5.3 mcy Genes and Toxic Blooms ...................................................................................... 18 1.5.4 Phycocyanin and Chlorophyll-a ................................................................................... 23 1.6 Public Health Implications .................................................................................................. 28 vi 1.6.1 Exposure Matrices ........................................................................................................ 28 1.6.2 Human Health Effects .................................................................................................. 29 1.6.3 Toxicity and Exposure Values ...................................................................................... 31 1.7 Drinking Water Treatment Processes .................................................................................. 33 1.7.1 Intracellular Toxin Removal ......................................................................................... 34 1.7.2 Extracellular Toxin Removal ........................................................................................ 36 1.7.3 Microcystin Drinking Water Guidelines ...................................................................... 39 1.8 Modeling and Statistical Methods ....................................................................................... 40 1.8.1 Quantitative Microbial Risk Assessment Framework .................................................. 40 1.8.2 Stochastic Models ......................................................................................................... 42 1.8.3 Monte Carlo Simulation ............................................................................................... 42 1.8.4 Wilcoxon Ranked Sums Test ....................................................................................... 44 Chapter 2. Phycocyanin Adjustment Model using qPCR Data .................................................... 46 2.1 Introduction ......................................................................................................................... 46 2.2 Methods ............................................................................................................................... 47 2.2.1 2016 Data ...................................................................................................................... 48 2.2.2 2017 Data ...................................................................................................................... 50 2.2.3 Data Analysis ...............................................................................................................
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