<div>Determination of the chemical composition of liquid transportation fuels emerged as a novel and important field of study after the introduction of advanced analytical instruments, which are capable of very detailed chemical analyses of complex mixtures. Aviation fuels make up a crucial portion of liquid transportation fuels. There are several significant challenges in the field of aviation fuels, including the development of optimal analytical methods for the determination of the chemical compositions of the fuels, fuel properties measurements, and correlations between fuel properties and chemical composition. This dissertation explores possible correlations between fuel chemical composition and its properties and proposes novel approaches. First, a detailed description of a method for the determination of the detailed chemical composition of all middle distillate fuels (diesel and aviation fuels) is presented. Second, the density was correlated to fuel composition. Additionally, the approach of measuring the density, the hydrogen content, and the carbon content via a GC×GC-FID was introduced. Lastly, it was discovered that minute differences in chemical composition can influence fuel properties. This finding is described in the last chapter, where three HEFA samples were investigated. </div>

Dissolved organic matter (DOM), one of the most complex naturally occurring mixtures, plays a central role in the biogeochemistry and the photochemistry of natural waters. A complete understanding of the environmental role of DOM will come only from the elucidation of the relationship between its structure and function. This thesis presents new work on the separation, characterization, and reactivity of DOM in rainwater, freshwater, and seawater. A new separation technique based on counterbalance capillary electrophoresis was developed for the separation of Suwannee River NOM. A comparative study of the organic content of rainwater was accomplished using nuclear magnetic resonance (NMR) with spectral database matching ,Fourier transform ion cyclotron mass spectrometry (FT-ICR-MS), and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC-TOFMS). Three complementary, non-overlapping datasets identified of over 400 compounds. Analysis of the FT-ICR-MS data using van Krevelen diagrams and the carbon oxidation state showed variation in the elemental composition and molecular size. Over 50% of the compounds identified in this study were known components of secondary organic aerosol (SOA) and volatile organic carbon (VOCs). Dissolved organic matter (DOM) plays a central role in the photochemistry of natural waters through the production of reactive oxygen species and the triplet excited state of DOM (3DOM*). These reactive species are central to the reactivity, transport, and fate of both natural and anthropogenic chemicals in the environment. Laser flash photolysis (LFP) was used to demonstrate that particulate organic matter (POM) generates a triplet excited state species (3POM*). LFP of seawater from the Pacific Ocean and the Bermuda Atlantic Time Series Station detected similar excited state species from surface to 4535m. Metal speciation has been implicated in the photochemistry of natural waters. Copper immobilized metal affinity chromatography (IMAC) of seawater and freshwater isolated a low and a high affinity fraction that generated excited state transients. Excitation-emission matrix spectroscopy showed that while the seawater fractions were autochthonous, freshwater fractions enriched in chromophoric DOM (CDOM), were allochthonous. The discovery of these different classes of compounds in freshwater and seawater has important implications both for the mineralization of DOM and the removal of xenobiotics in the aquatic environment.

Dissolved organic matter (DOM), one of the most complex naturally occurring mixtures, plays a central role in the biogeochemistry and the photochemistry of natural waters. A complete understanding of the environmental role of DOM will come only from the elucidation of the relationship between its structure and function. This thesis presents new work on the separation, characterization, and reactivity of DOM in rainwater, freshwater, and seawater. A new separation technique based on counterbalance capillary electrophoresis was developed for the separation of Suwannee River NOM. A comparative study of the organic content of rainwater was accomplished using nuclear magnetic resonance (NMR) with spectral database matching ,Fourier transform ion cyclotron mass spectrometry (FT-ICR-MS), and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC-TOFMS). Three complementary, non-overlapping datasets identified of over 400 compounds. Analysis of the FT-ICR-MS data using van Krevelen diagrams and the carbon oxidation state showed variation in the elemental composition and molecular size. Over 50% of the compounds identified in this study were known components of secondary organic aerosol (SOA) and volatile organic carbon (VOCs). Dissolved organic matter (DOM) plays a central role in the photochemistry of natural waters through the production of reactive oxygen species and the triplet excited state of DOM (3DOM*). These reactive species are central to the reactivity, transport, and fate of both natural and anthropogenic chemicals in the environment. Laser flash photolysis (LFP) was used to demonstrate that particulate organic matter (POM) generates a triplet excited state species (3POM*). LFP of seawater from the Pacific Ocean and the Bermuda Atlantic Time Series Station detected similar excited state species from surface to 4535m. Metal speciation has been implicated in the photochemistry of natural waters. Copper immobilized metal affinity chromatography (IMAC) of seawater and freshwater isolated a low and a high affinity fraction that generated excited state transients. Excitation-emission matrix spectroscopy showed that while the seawater fractions were autochthonous, freshwater fractions enriched in chromophoric DOM (CDOM), were allochthonous. The discovery of these different classes of compounds in freshwater and seawater has important implications both for the mineralization of DOM and the removal of xenobiotics in the aquatic environment.

Tuberculosis (TB) is one of the deadliest infectious diseases of our time, with 1.4 million deaths globally, recorded in 2010 (3800 deaths a day) by the World Health Organization (WHO). Currently, South Africa ranks third on the 2011 list of 22 high-burden TB countries in the world and it was estimated that each active-TB person could potentially infect 10–15 people annually. The WHO additionally reported that in the year 2009, 87% of all TB patients worldwide were successfully treated, with a treatment success rate of 74% reported for South Africa. Despite this however, non-adherence to anti-TB treatment is still a major issue, due to it resulting in a global increased prevalence of drug resistant TB and subsequently TB treatment failure. Treatment failure is thought to be caused by a number of factors, however, it still remains largely misunderstood. One aspect of this, that isn't clearly addressed in the literature, is the underlying variation in each patient, resulting in his/her varying reaction to the drug regimen, and hence it’s varying efficacy from one patient to the next. Furthermore, little is known about the underlying variation of the host to the primary TB infection or response to the TB disease state, and how some patients have more effective mechanisms for eliminating the infection, or recovering from the disease. Considering this, a metabolomics research study using GC×GC-TOFMS was conducted, in order to identify potential metabolite markers which may be used to better characterise the underlining mechanisms associated with poor treatment outcomes (treatment failure). The first aim was to evaluate the accuracy and efficiency of the methodology used, as well as to determine the capability and accuracy of the analyst to perform these methods. In order to evaluate the GCxGC-TOFMS analytical repeatability, one QC sample was extracted and injected repeatedly (6 times) onto the GC×GC-TOFMS. Similarly, the analyst's repeatability for performing the organic acid extraction and analyses was also determined, using 10 identical QC samples, which were extracted and injected separately. CV values were subsequently calculated from the collected and processed data as a measure of this. Of all the compounds detected from the 6 QC sample repeats used for GCxGC-TOFMS repeatability, 95.59% fell below a 50% CV value, and 93,7% of all the compounds analysed for analyst repeatability had a CV < 50. Subsequently, using the above metabolomics approach, in addition to a wide variety of univariate and multivariate statistical methods, two patient outcome groups were compared. A sample group cured from TB after 6 months of treatment was compared vs a sample group where treatment failed after the 6 month period. Using urine collected from these two patient groups at various time points, the following metabolomics comparisons where made: 1) at time of diagnosis, before any anti-TB treatment was administrated, 2) during the course of treatment, in order to determine any variance in these groups due to a varying response to the anti-TB drugs, 3) over the duration of the entire 6 months treatment regimen, in order to determine if differences exist between the two groups over time. A clear natural differentiation between the cured and failed outcome groups were obtained at time of diagnosis, and a total of 39 metabolites markers were subsequently identified. These metabolites were classified according to their various origins, and included (1) those associated with the presence of M. tuberculosis bacteria, (2) those resulting from an altered host metabolism due to the TB infection, and (3) metabolites of various exogenous origins. The detailed interpretation of these metabolites suggests that a possible underlying RCD or some sort of mitochondrial dysfunction may be present in the treatment failure group, which may also be induced through an external stimulus, such as alcohol consumption. We hypothesise that this may possibly result in a far greater severity to M. tuberculosis infection in this group, subsequently causing a reduced capacity for a successful treatment outcome, also considering the critical role of the mitochondria in the metabolism of anti-TB drugs. Furthermore, 20 metabolite markers were identified when comparing the two outcome groups during the treatment phase of this metabolomics investigation. A vast majority of these 20 metabolites were also identified as markers for time 0 (time of diagnosis). Additionally, metabolites associated with anti-TB drug induced side effects, were also found to be comparatively increased in the treatment failure group, indicative of more pronounced liver damage, accompanied by metabolites characteristic of a MADD metabolite profile, due to a deficient electron transport flavoprotein, confirming previous experiments done in rats. These side effects have also previously been implicated as a major contributor of poor treatment compliance, and ultimately treatment failure. Lastly, 35 metabolite markers were identified by time dependent statistical analysis and represented those metabolites best describing the variation between the treatment outcome groups over the entire study duration (from diagnosis, to week 26). This time dependent statistical analysis identified markers, using an alternative statistical approach, and confirmed previous findings and added in a better characterisation of treatment failure. Considering the above, we successfully applied a metabolomics approach for identifying metabolites which could ultimately aid in the prediction and monitoring of treatment outcomes. This additionally led to a better understanding and or characterisation of the phenomenon known as treatment failure, as well as the underlying mechanisms related to this occurrence. / MSc (Biochemistry), North-West University, Potchefstroom Campus, 2013

Tuberculosis (TB) is one of the deadliest infectious diseases of our time, with 1.4 million deaths globally, recorded in 2010 (3800 deaths a day) by the World Health Organization (WHO). Currently, South Africa ranks third on the 2011 list of 22 high-burden TB countries in the world and it was estimated that each active-TB person could potentially infect 10–15 people annually. The WHO additionally reported that in the year 2009, 87% of all TB patients worldwide were successfully treated, with a treatment success rate of 74% reported for South Africa. Despite this however, non-adherence to anti-TB treatment is still a major issue, due to it resulting in a global increased prevalence of drug resistant TB and subsequently TB treatment failure. Treatment failure is thought to be caused by a number of factors, however, it still remains largely misunderstood. One aspect of this, that isn't clearly addressed in the literature, is the underlying variation in each patient, resulting in his/her varying reaction to the drug regimen, and hence it’s varying efficacy from one patient to the next. Furthermore, little is known about the underlying variation of the host to the primary TB infection or response to the TB disease state, and how some patients have more effective mechanisms for eliminating the infection, or recovering from the disease. Considering this, a metabolomics research study using GC×GC-TOFMS was conducted, in order to identify potential metabolite markers which may be used to better characterise the underlining mechanisms associated with poor treatment outcomes (treatment failure). The first aim was to evaluate the accuracy and efficiency of the methodology used, as well as to determine the capability and accuracy of the analyst to perform these methods. In order to evaluate the GCxGC-TOFMS analytical repeatability, one QC sample was extracted and injected repeatedly (6 times) onto the GC×GC-TOFMS. Similarly, the analyst's repeatability for performing the organic acid extraction and analyses was also determined, using 10 identical QC samples, which were extracted and injected separately. CV values were subsequently calculated from the collected and processed data as a measure of this. Of all the compounds detected from the 6 QC sample repeats used for GCxGC-TOFMS repeatability, 95.59% fell below a 50% CV value, and 93,7% of all the compounds analysed for analyst repeatability had a CV < 50. Subsequently, using the above metabolomics approach, in addition to a wide variety of univariate and multivariate statistical methods, two patient outcome groups were compared. A sample group cured from TB after 6 months of treatment was compared vs a sample group where treatment failed after the 6 month period. Using urine collected from these two patient groups at various time points, the following metabolomics comparisons where made: 1) at time of diagnosis, before any anti-TB treatment was administrated, 2) during the course of treatment, in order to determine any variance in these groups due to a varying response to the anti-TB drugs, 3) over the duration of the entire 6 months treatment regimen, in order to determine if differences exist between the two groups over time. A clear natural differentiation between the cured and failed outcome groups were obtained at time of diagnosis, and a total of 39 metabolites markers were subsequently identified. These metabolites were classified according to their various origins, and included (1) those associated with the presence of M. tuberculosis bacteria, (2) those resulting from an altered host metabolism due to the TB infection, and (3) metabolites of various exogenous origins. The detailed interpretation of these metabolites suggests that a possible underlying RCD or some sort of mitochondrial dysfunction may be present in the treatment failure group, which may also be induced through an external stimulus, such as alcohol consumption. We hypothesise that this may possibly result in a far greater severity to M. tuberculosis infection in this group, subsequently causing a reduced capacity for a successful treatment outcome, also considering the critical role of the mitochondria in the metabolism of anti-TB drugs. Furthermore, 20 metabolite markers were identified when comparing the two outcome groups during the treatment phase of this metabolomics investigation. A vast majority of these 20 metabolites were also identified as markers for time 0 (time of diagnosis). Additionally, metabolites associated with anti-TB drug induced side effects, were also found to be comparatively increased in the treatment failure group, indicative of more pronounced liver damage, accompanied by metabolites characteristic of a MADD metabolite profile, due to a deficient electron transport flavoprotein, confirming previous experiments done in rats. These side effects have also previously been implicated as a major contributor of poor treatment compliance, and ultimately treatment failure. Lastly, 35 metabolite markers were identified by time dependent statistical analysis and represented those metabolites best describing the variation between the treatment outcome groups over the entire study duration (from diagnosis, to week 26). This time dependent statistical analysis identified markers, using an alternative statistical approach, and confirmed previous findings and added in a better characterisation of treatment failure. Considering the above, we successfully applied a metabolomics approach for identifying metabolites which could ultimately aid in the prediction and monitoring of treatment outcomes. This additionally led to a better understanding and or characterisation of the phenomenon known as treatment failure, as well as the underlying mechanisms related to this occurrence. / MSc (Biochemistry), North-West University, Potchefstroom Campus, 2013

<p>Aviation fuels are complex mixtures that mostly consist of a wide range of different hydrocarbons but also contain small amounts of heteroatom-containing compounds. Different fuels can have very different physical and chemical properties (e.g., storage and thermal stabilities are influenced by the heteroatom-containing compounds), with some performing better as fuels than others. To address this situation, correlations need to be developed between the chemical composition of fuels and their properties. This requires that the chemical compounds in fuels are correctly characterized, which is challenging. Because of the large number and many different types of organic compounds present in fuels, separation of these compounds by using techniques such as one- (GC) and -two-dimensional gas chromatography (GC×GC) is necessary before mass spectrometric characterization. Furthermore, analysis using traditional electron ionization (EI) mass spectrometry is hampered by excessive fragmentation that often leads to complete absence of a stable molecular radical cation, thus preventing the determination of the molecular weight (MW) of the analyte. To explore alternative methods, GC coupled with methane chemical ionization (CI) triple quadrupole mass spectrometry and GC×GC coupled with methane CI time-of-flight high-resolution mass spectrometry, both in the positive-ion mode, were tested. While both chromatographic techniques separate volatile organic chemicals via boiling point and intermolecular forces, GC×GC methods incorporate a greater level of separation by taking advantage of secondary column of different polarity. This additional level of separation can help separate overlapping compounds that would be impossible in GC. What comes to mass spectrometry analysis, methane CI was found to be more predictable and “softer” than the traditionally employed EI. Several ions revealing the MW of the analyte, e.g., M+•, [M+H-H2]+, and/or [M+H]+, were generated for almost every compound studied with some associated fragmentation. These fragmentation patterns provided invaluable structural information. When combined with the number of carbon atoms in the diagnostic ions, double bond and ring equivalent (DBRE) values, and elemental compositions, all obtained from highly accurate mass measurements performed using the time-of-flight mass spectrometer (but not the quadrupole), the classification of the compounds was possible. In some instances, even the unambiguous identification of individual compounds in aviation fuels was possible.</p>

<p>Crude oil is a mixture of hydrocarbons so complex that it is predicted to comprise as many compounds as there are genes in the human genome. Developing methods to not only recover crude oil from the ground but also to convert crude oil into desirable products is challenging due to its complex nature. Thus, the petroleum industry relies heavily on analytical techniques to characterize the oil in reservoirs prior to enhanced oil recovery efforts and to evaluate the chemical compositions of their crude oil based products. Mass spectrometry (MS) is the only analytical technique that has the potential to provide elemental composition as well as structural information for the individual compounds that comprise petroleum samples. The continuous development of ionization techniques and mass analyzers, and other instrumentation advances, have primed mass spectrometry as the go-to analytical technique for providing solutions to problems faced by the petroleum industry. The research discussed in this dissertation can be divided into three parts: developing novel mass spectrometry-based methods to characterize mixtures of saturated hydrocarbons in petroleum products (Chapters 3 and 5), exploring the cause of fragmentation of saturated hydrocarbons upon atmospheric pressure chemical ionization to improve the analysis of samples containing these compounds (Chapter 4), and developing a better understanding of the chemical composition of crude oil that tightly binds to reservoir surfaces to improve chemically enhanced oil recovery (Chapter 6). </p>