abstract: Population growth and fresh water depletion challenge drinking water utilities. Surface water quality is impacted significantly by climate variability, human activities, and extreme events like natural disasters. Dissolved organic carbon (DOC) is an important water quality index and the precursor of disinfection by-products (DBPs) that varies with both hydrologic and anthropogenic factors. Granular activated carbon (GAC) is a best available technology for utilities to meet Stage 2 D/DBP rule compliance and to remove contaminants of emerging concern (CECs) (e.g., pharmaceutical, personal care products (PCPs), etc.). Utilities can operate GAC with more efficient and flexible strategies with the understanding of organic occurrence in source water and a model capable predicting DOC occurrence. In this dissertation, it was found that DOC loading significantly correlated with spring runoff and was intensified by dry-duration antecedent to first flush. Dynamic modeling based on reservoir management (e.g., pump-back operation) was established to simulate the DOC transport in the reservoir system. Additionally, summer water recreational activities were found to raise the level of PCPs, especially skin-applied products, in raw waters. GAC was examined in this dissertation for both carbonaceous and emerging nitrogenous DBP (N-DBP) precursors (i.e., dissolved organic nitrogen (DON)) removal. Based on the experimental findings, GAC preferentially removes UV254-absorbing material, and DOC is preferentially removed over DON which may be composed primarily of hydrophilic organic and results in the low affinity for adsorption by GAC. The presence of organic nitrogen can elevate the toxicity of DBPs by forming N-DBPs, and this could be a major drawback for facilities considering installation of a GAC adsorber owing to the poor removal efficiency of DON by GAC. A modeling approach was established for predicting DOC and DON breakthrough during GAC operation. However, installation of GAC adsorber is a burden for utilities with respect to operational and maintenance cost. It is common for utilities to regenerate saturated GAC in order to save the cost of purchasing fresh GAC. The traditional thermal regeneration technology for saturated GAC is an energy intensive process requiring high temperature of incineration. Additionally, small water treatment sites usually ship saturated GAC to specialized facilities for regeneration increasing the already significant carbon footprint of thermal regeneration. An innovative GAC regeneration technique was investigated in this dissertation for the feasibility as on-site water treatment process. Virgin GAC was first saturated by organic contaminant then regenerated in-situ by iron oxide nanocatalysts mixed with hydrogen peroxide. At least 70 % of adsorption capacity of GAC can be regenerated repeatedly for experiments using modeling compound (phenol) or natural organic matter (Suwannee River humic acid). The regeneration efficiency increases with increasing adsorbate concentration. Used-iron nanocatalysts can be recovered repeatedly without significant loss of catalytic ability. This in-situ regeneration technique provides cost and energy efficient solution for water utilities considering GAC installation. Overall, patterns were found for DOC and CEC variations in drinking water sources. Increasing concentrations of bulk (DOC and DON) and/or trace organics challenge GAC operation in utilities that have limited numbers of bed-volume treated before regeneration is required. In-situ regeneration using iron nanocatalysts and hydrogen peroxide provides utilities an alternative energy-efficient operation mode when considering installation of GAC adsorber. / Dissertation/Thesis / Ph.D. Civil and Environmental Engineering 2012

The objective of the study was to compare the trihalomethanes (THMs) produced from ferrate with hypochlorite and to determine how different the THM production would be for a given degree of disinfection (3 log reduction in Heterotrophic Plate Count (HPC)). Different water samples were collected from Lake Claire, Atlantic Ocean, and secondary effluent from an advanced wastewater treatment plant. THM formation was determined using a standard assay over 7 days at room temperature. In addition samples were tested for Total Coliform Escherichia coli (TC/E.coli), and heterotrophic bacteria using HPC by spreadplating on R2A agar. Dissolved organic carbon (DOC) was measured as well. Dosages of 2, 5, and 10 ppm of hypochlorite and ferrate were used for Lake Claire and Atlantic Ocean water, while 1, 2, and 5 ppm dosages were used for wastewater treatment effluent. Ferrate resulted in 48.3% ± 11.2% less THM produced for the same level of disinfection (i.e. approximately 3 logs reduction in HPC). Oxidation of DOC was relatively small with a 6.1 to 11.6 % decrease in DOC being observed for ferrate doses from 2 to 10 mg/L. Free chlorine oxidation of DOC was negligible.

N-Nitrosamines are an emerging group of disinfection byproducts characterized by high carcinogenic risks at ng/L levels and by their frequent detection in water and wastewater treatment systems in the U.S. and other parts of the world. The overall goal of this research is to achieve a better understanding of the roles of common nitrosamine precursors in leading to N-nitrosamine formation in water and wastewater treatment systems. The specific objectives of this research are: (a) To probe the mechanisms of nitrosamine formation from commonly employed water treatment polymers, particularly polyDADMACs, during ozonation, (b) To evaluate the role of dithiocarbamate compounds as nitrosamine precursors in reaction with common water disinfection oxidants, and (c) To investigate the potential enhancement effect of activated carbons (AC) to promote transformation of amines to nitrosamines and identify the involved reaction mechanism. Results of this research show that, upon ozonation, polyDADMACs may yield N-nitrosodimethylamine (NDMA) at levels up to two orders of magnitude higher than current advisory guidelines for NDMA. Radical pathways may be responsible for the degradation of the quaternary ammonium ring groups in polyDADMACs to release of dimethylamine (DMA). Detection of significant amounts of nitrite after ozonation of polyDADMACs and DMA suggests the potential role of nitrosation pathway in NDMA formation. Study results also reveal dithiocarbamates as potent nitrosamine precursors with significant nitrosamine yields upon ozonation and monochloramination. Identification and quantification of reaction products suggest nitrosation and chlorinated-UDMH oxidation as primary reaction mechanisms in nitrosamine formation from ozonation and monochloramination of dithiocarbamates compounds, respectively. This research also demonstrates that many commercial AC materials may catalyze transformation of secondary amines to yield trace levels of N-nitrosamines under ambient aerobic conditions. This is a novel discovery with far-reaching implications because of the widespread usage of AC materials in numerous analytical and environmental applications. The study results show that the properties of AC materials and reaction conditions play a crucial role in the catalyzed nitrosamine formation and should be carefully selected to minimize analytical errors and undesirable nitrosamine formation in water samples. Overall, the mechanistic information obtained in this research will be useful for the water industry and research communities to develop more effective strategies to control undesirable nitrosamine formation in water and wastewater treatment systems and thus better protect the public health.

DNA-binding proteins (DBPs) such as repair proteins, DNA polymerases, re- combinases, transcription factors, etc. manifest diverse stochastic behaviours dependent on physiological conditions inside the cell. Now that multiple independent in vitro studies have extensively characterised different aspects of the biochemistry of DBPs, computational and mathematical tools that would be able to integrate this information into a coherent framework are in huge demand, especially when attempting a transition to in vivo characterisation of these systems. ChIP-Seq is the method commonly used to study DBPs in vivo. This method generates high resolution sequencing data { population scale readout of the activity of DBPs on the DNA. The mathematical tools available for the analysis of this type of data are at the moment very restrictive in their ability to extract mechanistic and quantitative details on the activity of DBPs. The main trouble that researchers experience when analysing such population scale sequencing data is effectively disentangling complexity in these data, since the observed output often combines diverse outcomes of multiple unsynchronised processes reflecting biomolecular variability. Although being a static snapshot ChIP-Seq can be effectively utilised as a readout for the dynamics of DBPs in vivo. This thesis features a new approach to ChIP-Seq analysis { namely accessing the concealed details of the dynamic behaviour of DBPs on DNA using probabilistic modelling, statistical inference and numerical optimisation. In order to achieve this I propose to integrate previously acquired assumptions about the behaviour of DBPs into a Markov- Chain model which would allow to take into account their intrinsic stochasticity. By incorporating this model into a statistical model of data acquisition, the experimentally observed output can be simulated and then compared to in vivo data to reverse engineer the stochastic activity of DBPs on the DNA. Conventional tools normally employ simple empirical models where the parameters have no link with the mechanistic reality of the process under scrutiny. This thesis marks the transition from qualitative analysis to mechanistic modelling in an attempt to make the most of the high resolution sequencing data. It is also worth noting that from a computer science point of view DBPs are of great interest since they are able to perform stochastic computation on DNA by responding in a probabilistic manner to the patterns encoded in the DNA. The theoretical framework proposed here allows to quantitatively characterise complex responses of these molecular machines to the sequence features.

A new technique for sample preparation and trace analysis of organic pollutants in water using mixed-phase thin film (MPTF) devices, combined with direct thermal desorption, cold trapping, gas chromatography-mass spectrometry (GC-MS) is presented for the first time. Two novel analytical devices, Carboxen/polydimethylsiloxane (CAR/PDMS) and polydimethylsiloxane/divinylbenzene (PDMS/DVB) TF samplers were fabricated using spin coating technique and glass wool fabric mesh as substrate. The samplers were easily tailored in size and shape by cutting tools. Good durability and flat-shape stability were observed during extractions and stirring in water. The latter characteristic obviates the need for an extra framed holder for rapid thin film microextraction (TFME) and makes the samplers more robust and user-friendly. The analytical performance of the MPTF devices was satisfactorily illustrated and compared with those of solid phase microextraction (SPME) fibers and PDMS thin film membrane using water samples spiked with seven N–nitrosamines (NAs), known as disinfection by-products (DBPs) in drinking water. Marked enhancement of extraction efficiencies (typically more than one order of magnitude) for the N-nitrosamines, including the hydrophilic ones, was obtained with the MPTF devices under generally pre-equilibrium conditions, compared to the SPME fibers and PDMS thin film membrane. The analytical results obtained in this study, including linearity, repeatability and detection levels at low ng/L for the tested compounds, indicate that the new thin film devices are promising for rapid sampling and sample preparation of trace levels of polar organic pollutants in water with sensitivities higher than SPME fibers and with a wide application range typical of mixed-phase coatings. The user-friendly format and robustness of the novel devices are also advantageous for on-site applications, which is the ultimate use of thin film samplers. Moreover, the thin film fabrication approach developed in this study offers the possibility of making other novel samplers with PDMS or different absorptive polymers such as polyacrylate (PA) and polyethylene glycol (PEG) as particle-free, or as particle-loaded thin films with a variety of adsorptive solid particles. In another development in the course of this research, the performance and accuracy of the SPME fiber approach for sample preparation of selected DBPs were demonstrated and compared with the conventional liquid-liquid extraction (LLE) method by real drinking water samples analysis in collaboration with Health Canada. Four regulated trihalomethanes (THMs) and seven other DBPs known as priority by-products, including four haloacetonitriles, two haloketones and chloropicrin, were analyzed in real samples during two separate comparative studies. In each study, duplicate samples from several water treatment and distribution systems in Canada, collected and stabilized under the same protocol, were analyzed in parallel by two independent labs; in the University of Waterloo by an optimized headspace SPME-GC-MS and in Health Canada by a LLE-GC-ECD (electron capture detection) method equivalent to EPA 551.1. The values for the concentration of the analytes in the samples obtained by the two methods were in good agreement with each other in majority of the cases indicating that SPME affords the promise of a dependable sample preparation technique for rapid DBPs analysis. In particular, it was shown that the SPME fiber approach combined with GC-MS is a fast reliable alternative to the LLE-GC-ECD (EPA 551.1) method for analysis of the regulated THMs in the concentration ranges that are typical and relevant for drinking water samples.

Disinfectants in drinking water can interact with natural organic matter (NOM) to form disinfection by-products (DBPs). Halogenated furanones (including MX and MCA) are a group of emerging DBPs that can account for a significant amount of the total mutagenicity found in drinking water. Source water characteristics and NOM removal capabilities of coagulation can greatly influence the formation of DBPs. This project examines the effects of bench scale coagulation and chlorination tests on NOM removal, DBP formation, and genotoxicity. NOM was characterized using liquid chromatography-organic carbon detection (LC-OCD). Experiments with Ottawa River, Otonabee River, and Lake Simcoe waters show that DBPs decreased with increases in coagulant dosage, due to the removal of NOM during coagulation. DBP formation and speciation was then compared with NOM content to identify specific fractions that contribute to the formation of these DBPs. Genotoxicity was directly linked to MX presence in chlorinated waters.

Les méthodes de Monte Carlo par chaînes de Markov (MCMC) utilisent généralement des chaînes de Markov réversibles. Jusqu’à récemment, une grande partie de la recherche théorique sur les chaînes de Markov concernait ce type de chaînes, notamment les théorèmes de Peskun (1973) et de Tierney (1998) qui permettent d’ordonner les variances asymptotiques de deux estimateurs issus de chaînes réversibles différentes. Dans ce mémoire nous analysons des algorithmes simulants des chaînes qui ne respectent pas cette condition. Nous parlons alors de chaînes non réversibles. Expérimentalement, ces chaînes produisent souvent des estimateurs avec une variance asymptotique plus faible et/ou une convergence plus rapide. Nous présentons deux algorithmes, soit l’algorithme de marche aléatoire guidée (GRW) par Gustafson (1998) et l’algorithme de discrete bouncy particle sampler (DBPS) par Sherlock et Thiery (2017). Pour ces deux algorithmes, nous comparons expérimentalement la variance asymptotique d’un estimateur avec la variance asymptotique en utilisant l’algorithme de Metropolis-Hastings. Récemment, un cadre théorique a été introduit par Andrieu et Livingstone (2019) pour ordonner les variances asymptotiques d’une certaine classe de chaînes non réversibles. Nous présentons leur analyse de GRW. De plus, nous montrons que le DBPS est inclus dans ce cadre théorique. Nous démontrons que la variance asymptotique d’un estimateur peut théoriquement diminuer en ajoutant des propositions à cet algorithme. Finalement, nous proposons deux modifications au DBPS. Tout au long du mémoire, nous serons intéressés par des chaînes issues de propositions déterministes. Nous montrons comment construire l’algorithme du delayed rejection avec des fonctions déterministes et son équivalent dans le cadre de Andrieu et Livingstone (2019). / Markov chain Monte Carlo (MCMC) methods commonly use chains that respect the detailed balance condition. These chains are called reversible. Most of the theory developed for MCMC evolves around those particular chains. Peskun (1973) and Tierney (1998) provided useful theorems on the ordering of the asymptotic variances for two estimators produced by two different reversible chains. In this thesis, we are interested in non-reversible chains, which are chains that don’t respect the detailed balance condition. We present algorithms that simulate non-reversible chains, mainly the Guided Random Walk (GRW) by Gustafson (1998) and the Discrete Bouncy Particle Sampler (DBPS) by Sherlock and Thiery (2017). For both algorithms, we compare the asymptotic variance of estimators with the ones produced by the Metropolis- Hastings algorithm. We present a recent theoretical framework introduced by Andrieu and Livingstone (2019) and their analysis of the GRW. We then show that the DBPS is part of this framework and present an analysis on the asymptotic variance of estimators. Their main theorem can provide an ordering of the asymptotic variances of two estimators resulting from nonreversible chains. We show that an estimator could have a lower asymptotic variance by adding propositions to the DBPS. We then present empirical results of a modified DBPS. Through the thesis we will mostly be interested in chains that are produced by deterministic proposals. We show a general construction of the delayed rejection algorithm using deterministic proposals and one possible equivalent for non-reversible chains.

Historically, chlorination has been widely utilized as a primary and secondary disinfectant in municipal water supplies. Although chlorine disinfection is effective in inactivating pathogenic microbes, the use of chlorine creates the unintentional formation of regulated chemicals. On January 4, 2006, the United States Environmental Protection Agency (EPA) promulgated the Stage 2 Disinfectants/Disinfection by-product rule (DBPR) that focuses on public health protection by limiting exposure to four trihalomethanes (THM) and five haloacetic acids (HAA5), formed when chlorine is used for microbial pathogen control. This thesis examines post-aeration TTHM formation when employing spray-aeration processes to remove semi-volatile TTHMs from chlorinated potable water supplies. A bench scale air stripping unit was designed, constructed and operated to evaluate spray aeration for the removal of the four regulated trihalomethane (THM) species from potable drinking water including bromodichloromethane, bromoform, dibromochloromethane, chloroform. The study was conducted using finished bulk water samples collected from two different water treatment facilities (WTFs) located in Oviedo and Babson Park, Florida. Both treatment plants treat groundwater; however, Oviedo's Mitchell Hammock WTF (MHWTF) supply wells contain dissolved organic carbon and bromide DBP precursors whereas the Babson Park WTF #2 (BPWTF2) supply well contains dissolved organic carbon DBP precursors but is absent of bromide precursor. Three treatment scenarios were studied to monitor impacts on total trihalomethane (TTHM) removal and post-treatment (post-aeration) TTHM formation potential, including 1) no treatment (non-aerated control samples), 2) spray aeration via specially fabricated GridBee® nozzle for laboratory-scale applications, 3) spray aeration via a commercially available manufactured BETE® nozzle used for full-scale applications. Select water quality parameters, chlorine residual, and total trihalomethane concentrations were monitored throughout the study. The GridBee® spray nozzle resulted in TTHM removals ranging from 45.2 ± 3.3% for the BPWTF2 samples, and 37.7 ± 3.1% for the MHWTF samples. The BETE® spray nozzle removed 54.7±3.9% and 48.1±6.6% of total trihalomethanes for the Babson Park and Mitchell Hammock WTF samples, respectively. The lower percent removals at the MHWTF are attributed to the detectable presence of bromide and subsequent formation of hypobromous acid in the samples. Post spray aeration TTHM formation potentials were monitored and it was found that the MHWTF experienced significantly higher formation potentials, once again due to the presence of hypobromous acid which led to increases in overall TTHM formation over time in comparison with the Babson Park WTF #2 TTHM formation samples. In addition, chlorine residuals were maintained post spray aeration treatment, and initial chlorine residual and trihalomethane concentrations did not significantly impact overall spray nozzle performance. Among other findings, it was concluded that spray nozzle aeration is a feasible option for the Babson Park WTF #2 for TTHM compliance. For Oviedo's Mitchell Hammock WTF spray aeration was successful in removing TTHMs, however it was not effective in maintaining DBP rule compliance due to the excessive nature of DBP formation in the water samples. This study was not intended to serve as an assessment of varying nozzle technologies; rather, the focus was on the application of spray aerators for TTHM removal and post-formation in drinking water systems.

No description available.