Graduate Theses & Dissertations

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Equilibria and distribution models of ionizing organic chemical contaminants in environmental systems
Ionizing organic chemicals are recognized as constituting a large fraction of the organic chemicals of commerce. Many governments internationally are engaged in the time-consuming and expensive task of chemical risk assessment for the protection of human and environmental health. There are standard models that are consistently used to supplement experimental and monitoring data in such assessments of non-ionizing organics by both government regulators and industry stakeholders. No such standard models exist for ionizing organics. Equilibrium distribution models, the foundational equations within multimedia environmental fate models for non-ionizing organics, were developed for the standard series of biphasic systems: air-water, particle-water, air-particle and organic-aqueous phases within living tissue. Multiple chemical species due to the ionization reaction were considered for each system. It was confirmed that, under select conditions, the properties of the neutral parent are sufficient to predict the overall distribution of the organic chemical. Complications due to biotransformation and paucity of identifiable equilibrium distribution data for ionizing organics limited the development of the model for living tissues. However, the equilibrium distributions of ionizing organics within this biotic system were shown to correlate with the abiotic sediment-water system. This suggests that the model developed for particle-water systems should be adaptable to the biotic system as model input and test data become available. Observational data for soil- and sediment- water systems, i.e., particle-water systems, allowed the development of a primarily non-empirical distribution equation for mono-protic acids; this model was almost entirely theoretically derived. The theoretical approach to model development allowed a quantitative assessment of the role of the neutral ion pair, resulting from the complexation of the organic anion with metal cations. To demonstrate the model's potential usefulness in governmental screening risk assessments, it was applied to a broad range of mono-protic organics including drugs and pesticides using standard property estimation software and generic inputs. The order-of-magnitude agreement between prediction and observation typical of the existing models of non-ionizing organics was generally achieved for the chemicals tested. The model was sensitive to the octanol-water partition coefficient of the most populous species. No calibration set was used in the development of any of the models presented. Author Keywords: bioconcentration, chemical equilibrium, environmental modelling, ionizing organic, sorption
Influence of nitrogen deposition on the vegetation community of Irish oak woodlands
In this study, the influence of N deposition on the vegetation community of semi-natural oak woodlands in Ireland was assessed through national and regional scale analysis of forest plot data. At both scales, Canonical Correspondence Analysis suggested that N deposition was a predictor of community composition, although site-specific soil characteristics were the strongest predictors of the species dataset. Threshold Indicator Taxon Analysis suggested that the vegetation community demonstrated the most change at 13.2 kg N ha-1 yr-1. While this change point falls within the current recommended critical load range for nutrient nitrogen for acidophilous oak dominated woodlands (10 to 15 kg N ha-1 yr-1), it is notable that 23% of species recorded had individual change points below this range, and could potentially be lost from this habitat if deposition increases. The results from this study suggest that, for acidophilous oak woodlands, habitat conservation policies should be unified with N emission reduction policies. Author Keywords: community composition, critical load, nitrogen depositioin, oak woodland, species richness, Taxon Indicator Threshold Analysis
Novel Silica Sol-Gel Passive Sampler for Mercury Monitoring in Aqueous Systems
A novel passive sampler for mercury monitoring was prepared using organosilica sol-gel materials. It comprises a binding layer with thiol groups for mercury complexation and a porous diffusive layer through which mercury can diffuse and arrive at the binding layer. Our study demonstrated that this new sampler follows the principle of passive sampling. The mass of mercury accumulated in the binding layer depends linearly on the mercury concentration in solution, the sampling rate and the exposure time. A typical sol-gel sampler is characterized by a diffusive layer of 1.2 &mum, in which mercury ions diffuse with a coefficient of D = 0.09~10-6 cm2/s. The capacity for mercury uptake is approximately 0.64 &mug/cm2. Mercury diffusion and binding in the passive sampler are independent of the type of mercury-chloride complex. Its sampling rate increases with increasing water turbulence and decreases with increasing DOM amount. The field trial of sol-gel sampler in Miller Creek shows the concentration gained from the sol-gel passive sampler is slightly lower than that from the spot sampling. Author Keywords:
SPATIAL AND TEMPORAL GENETIC STRUCTURE OF WOLVERINE POPULATIONS
Habitat loss and fragmentation can disrupt population connectivity, resulting in small, isolated populations and low genetic variability. Understanding connectivity patterns in space and time is critical in conservation and management planning, especially for wide-ranging species in northern latitudes where habitats are becoming increasingly fragmented. Wolverines (Gulo gulo) share similar life history traits observed in large-sized carnivores, and their low resiliency to disturbances limits wolverine persistence in modified or fragmented landscapes - making them a good indicator species for habitat connectivity. In this thesis, I used neutral microsatellite and mitochondrial DNA markers to investigate genetic connectivity patterns of wolverines for different temporal and spatial scales. Population genetic analyses of individuals from North America suggested wolverines west of James Bay in Canada are structured into two contemporary genetic clusters: an extant cluster at the eastern periphery of Manitoba and Ontario, and a northwestern core cluster. Haplotypic composition, however, suggested longstanding differences between the extant eastern periphery and northwestern core clusters. Phylogeographic analyses across the wolverine's Holarctic distribution supported a postglacial expansion from a glacial refugium near Beringia. Although Approximate Bayesian computations suggested a west-to-east stepping-stone divergence pattern across North America, a mismatch distribution indicated a historic bottleneck event approximately 400 generations ago likely influenced present-day patterns of haplotype distribution. I also used an individual-based genetic distance measure to identify landscape features potentially influencing pairwise genetic distances of wolverines in Manitoba and Ontario. Road density and mean spring snow cover were positively associated with genetic distances. Road density was associated with female genetic distance, while spring snow cover variance was associated with male genetic distance. My findings suggest that northward expanding anthropogenic disturbances have the potential to affect genetic connectivity. Overall, my findings suggest that (1) peripheral populations can harbour genetic variants not observed in core populations - increasing species genetic diversity; (2) historic bottlenecks can alter the genetic signature of glacial refugia, resulting in a disjunct distribution of unique genetic variants among contemporary populations; (3) increased temporal resolution of the individual-based genetic distance measure can help identify landscape features associated with genetic connectivity within a population, which may disrupt landscape connectivity. Author Keywords: conservation genetics, Holarctic species, landscape genetics, peripheral population, phylogeography, wolverine
SPAF-network with Saturating Pretraining Neurons
In this work, various aspects of neural networks, pre-trained with denoising autoencoders (DAE) are explored. To saturate neurons more quickly for feature learning in DAE, an activation function that offers higher gradients is introduced. Moreover, the introduction of sparsity functions applied to the hidden layer representations is studied. More importantly, a technique that swaps the activation functions of fully trained DAE to logistic functions is studied, networks trained using this technique are reffered to as SPAF-networks. For evaluation, the popular MNIST dataset as well as all \(3\) sub-datasets of the Chars74k dataset are used for classification purposes. The SPAF-network is also analyzed for the features it learns with a logistic, ReLU and a custom activation function. Lastly future roadmap is proposed for enhancements to the SPAF-network. Author Keywords: Artificial Neural Network, AutoEncoder, Machine Learning, Neural Networks, SPAF network, Unsupervised Learning
Modelling Submerged Coastal Environments
Built upon remote sensing and GIS littoral zone characterization methodologies of the past decade, a series of loosely coupled models aimed to test, compare and synthesize multi-beam SONAR (MBES), Airborne LiDAR Bathymetry (ALB), and satellite based optical data sets in the Gulf of St. Lawrence, Canada, eco-region. Bathymetry and relative intensity metrics for the MBES and ALB data sets were run through a quantitative and qualitative comparison, which included outputs from the Benthic Terrain Modeller (BTM) tool. Substrate classification based on relative intensities of respective data sets and textural indices generated using grey level co-occurrence matrices (GLCM) were investigated. A spatial modelling framework built in ArcGISTM for the derivation of bathymetric data sets from optical satellite imagery was also tested for proof of concept and validation. Where possible, efficiencies and semi-automation for repeatable testing was achieved using ArcGISTM ModelBuilder. The findings from this study could assist future decision makers in the field of coastal management and hydrographic studies. Keywords: Seafloor terrain characterization, Benthic Terrain Modeller (BTM), Multi-beam SONAR, Airborne LiDAR Bathymetry, Satellite Derived Bathymetry, ArcGISTM ModelBuilder, Textural analysis, Substrate classification Author Keywords:
Novel Functional Materials From Renewable Lipids
Vegetable oils represent an ideal and renewable feedstock for the synthesis of a variety of functional materials. However, without financial incentive or unique applications motivating a switch, commercial products continue to be manufactured from petrochemical resources. Two different families of high value, functional materials synthesized from vegetable oils were studied. These materials demonstrate superior and unique performance to comparable petrochemical analogues currently on the market. In the first approach, 3 amphiphilic thermoplastic polytriazoles with differing lipophilic segment lengths were synthesized in a polymerization process without solvents or catalysts. Investigation of monomer structure influence on the resultant functional behaviour of these polymers found distinctive odd/even behaviour reliant on the number of carbon atoms in the monomers. Higher concentrations of triazole groups, due to shorter CH2 chains in the monomeric dialkynes, resulted in more brittle polymers, displaying higher tensile strengths but reduced elongation to break characteristics. These polymers had similar properties to commercial petroleum derived thermoplastics. One polymer demonstrated self-assembled surface microstructuring, and displayed hydrophobic properties. Antimicrobial efficacy of the polymers were tested by applying concentrated bacterial solutions to the surfaces, and near complete inhibition was demonstrated after 4 hours. Scanning electron microscope images of killed bacteria showed extensive membrane damage, consistent with the observed impact of other amphiphilic compounds in literature. These polytriazoles are suited for applications in medical devices and implants, where major concerns over antibiotic resistance are prevalent. In the second approach, a series of symmetric, saturated diester phase change materials (PCMs) were also synthesized with superior latent heat values compared to commercial petrochemical analogues. These diesters exhibit melting temperatures between 39 °C and 77 °C, with latent heats greater than 220 J/g; much greater than paraffin waxes, which are currently the industry standard. Assessment of the trends between differing monomer lengths, in terms of number of CH2 groups of the 24 diesters synthesized exhibited structure/function dependencies in latent heat values and phase change temperatures, providing an understanding of the influence of each monomer on PCM thermal properties. A synthetic procedure was developed to produce these PCMs from a low value biodiesel feedstock. Application of these PCMs in the thermoregulation of hot beverages was demonstrated using a representative diester. This PCM cooled a freshly brewed hot beverage to a desired temperature within 1 minute, compared to 18 minutes required for the control. Furthermore, the PCM kept the beverage within the desired temperature range for 235 minutes, 40 % longer than the control. Author Keywords: Antimicrobial Surface, Click Chemistry, Green Chemistry, Phase Change Material, Polytriazole, Renewable
Smote and Performance Measures for Machine Learning Applied to Real-Time Bidding
In the context of Real-Time Bidding (RTB) the machine learning problems of imbalanced classes and model selection are investigated. Synthetic Minority Oversampling Technique (SMOTE) is commonly used to combat imbalanced classes but a shortcoming is identified. Use of a distance threshold is identified as a solution and testing in a live RTB environment shows significant improvement. For model selection, the statistical measure Critical Success Index (CSI) is modified to add emphasis on recall. This new measure (CSI-R) is empirically compared with other measures such as accuracy, lift, efficiency, true skill score, Heidke's skill score and Gilbert's skill score. In all cases CSI-R is shown to provide better application to the RTB industry. Author Keywords: imbalanced classes, machine learning, online advertising, performance measures, real-time bidding, SMOTE
Mitigating Cold Flow Problems of Biodiesel
The present thesis explores the cold flow properties of biodiesel and the effect of vegetable oil derived compounds on the crystallization path as well as the mechanisms at play at different stages and length scales. Model systems including triacylglycerol (TAG) oils and their derivatives, and a polymer were tested with biodiesel. The goal was to acquire the fundamental knowledge that would help design cold flow improver (CFI) additives that would address effectively and simultaneously the flow problems of biodiesel, particularly the cloud point (CP) and pour point (PP). The compounds were revealed to be fundamentally vegetable oil crystallization modifiers (VOCM) and the polymer was confirmed to be a pour point depressant (PPD). The results obtained with the VOCMs indicate that two cis-unsaturated moieties combined with a trans-/saturated fatty acid is a critical structural architecture for depressing the crystallization onset by a mechanism wherein while the straight chain promotes a first packing with the linear saturated FAMEs, the kinked moieties prevent further crystallization. The study of model binary systems made of a VOCM and a saturated FAME with DSC, XRD and PLM provided a complete phase diagram including the thermal transformation lines, crystal structure and microstructure that impact the phase composition along the different crystallization stages, and elicited the competing effects of molecular mass, chain length mismatch and isomerism. The liquid-solid boundary is discussed in light of a simple thermodynamic model based on the Hildebrand equation and pair interactions. In order to test for synergies, the PP and CP of a biodiesel (Soy1500) supplemented with several VOCM and PLMA binary cocktails were measured using a specially designed method inspired by ASTM standards. The results were impressive, the combination of additives depressed CP and PP better than any single additive. The PLM and DSC results suggest that the cocktail additives are most effective when the right molecular structure and optimal concentration are provided. The cocktail mixture achieves then tiny crystals that are prevented from aggregating for an extended temperature range. The results of the study can be directly used for the design of functional and economical CFI from vegetable oils and their derivatives. Author Keywords: Biodiesel, Microstructure, Polymorphism, Pour point depressants, Triacylglycerol, Vegetable Oil Based Crystal Modifier
Novel Aliphatic Lipid-Based Diesters for use in Lubricant Formulations
Structure-property relationships are increasingly valued for the identification of specifically engineered materials with properties optimized for targeted application(s). In this work, linear and branched diesters for use in lubricant formulations are prepared from lipid-based oleochemicals and their structure-property relationships reported. It is shown that the branched diesters possess exceptional physical property profiles, including suppression of crystallization, and are superior alternatives for use in lubricant formulations. For the linear aliphatic diesters, both high and low temperature properties were predictable functions of total chain length, and both were differently influenced by the fatty acid versus diol chain length. Symmetry did not influence either, although thermal stability decreased and thermal transition temperatures increased with increasing saturation. All of the linear diesters demonstrated Newtonian flow behaviour. Viscosity was also predictable as a function of total chain length; any microstructural features due to structural effects were superseded by mass effects. Author Keywords: Crystallization, Phase behaviour, Rheology, Structure-Function, Thermogravimetric analysis, Vegetable Oils
Synthesis of Lipid Based Polyols from 1-butene Metathesized Palm Oil for Use in Polyurethane Foam Applications
This thesis explores the use of 1-butene cross metathesized palm oil (PMTAG) as a feedstock for preparation of polyols which can be used to prepare rigid and flexible polyurethane foams. PMTAG is advantageous over its precursor feedstock, palm oil, for synthesizing polyols, especially for the preparation of rigid foams, because of the reduction of dangling chain effects associated with the omega unsaturated fatty acids. 1-butene cross metathesis results in shortening of the unsaturated fatty acid moieties, with approximately half of the unsaturated fatty acids assuming terminal double bonds. It was shown that the associated terminal OH groups introduced through epoxidation and hydroxylation result in rigid foams with a compressive strength approximately 2.5 times higher than that of rigid foams from palm and soybean oil polyols. Up to 1.5 times improvement in the compressive strength value of the rigid foams from the PMTAG polyol was further obtained following dry and/or solvent assisted fractionation of PMTAG in order to reduce the dangling chain effects associated with the saturated components of the PMTAG. Flexible foams with excellent recovery was achieved from the polyols of PMTAG and the high olein fraction of PMTAG indicating that these bio-derived polyurethane foams may be suitable for flexible foam applications. PMTAG polyols with controlled OH values prepared via an optimized green solvent free synthetic strategy provided flexible foams with lower compressive strength and higher recovery; i.e., better flexible foam potential compared to the PMTAG derived foams with non-controlled OH values. Overall, this study has revealed that the dangling chain issues of vegetable oils can be addressed in part using appropriate chemical and physical modification techniques such as cross metathesis and fractionation, respectively. In fact, the rigidity and the compressive strength of the polyurethane foams were in very close agreement with the percentage of terminal hydroxyl and OH value of the polyol. The results obtained from the study can be used to convert PMTAG like materials into industrially valuable materials. Author Keywords: Compressive Strength, Cross Metathesis, Fractionation, Polyols, Polyurethane Foams, Vegetable Oils
Effect of Listing a Stock on the S&P 500 Index on the Stock’s Volatility
This paper investigates the effect of listing a stock on the S&P 500 Index on the stock’s volatility, using various econometrics models: GARCH and EGARCH. The study mainly addresses three issues; firstly, it analyzes stock volatility in two sub-periods, secondly, it determines whether the announcement can account for the fluctuations in the price of the stock, and finally, it investigates the change in the stock’s variance. After isolating the effects of external and industry shock by using the returns on the S&P 500 Index as a proxy, the author finds evidence of structural change in the volatility of stocks after that stock is added to the index. Additionally, the existence of a dominant symmetric effect, which captures the response of volatility to news, indicate that following the onset of including the stock on the index, information flowing into the market increased. However, the rate at which old news is captured in price falls. The empirical evidence also suggests that on average a stocks variance falls and that the announcement to list a stock on the index has little effect on the stock’s price. Author Keywords: EGARCH, GARCH, S&P 500 Index, Symmetric Effect, Volatility

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Graduate student theses produced at Trent University. You may also browse theses and dissertations by year, program, or author.

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