987 resultados para spectrometry


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Capillary electrophoresis (CE) is a modern analytical technique, which is electrokinetic separation generated by high voltage and taken place inside the small capillaries. In this dissertation, several advanced capillary electrophoresis methods are presented using different approaches of CE and UV and mass spectrometry are utilized as the detection methods. ^ Capillary electrochromatography (CEC), as one of the CE modes, is a recent developed technique which is a hybrid of capillary electrophoresis and high performance liquid chromatography (HPLC). Capillary electrochromatography exhibits advantages of both techniques. In Chapter 2, monolithic capillary column are fabricated using in situ photoinitiation polymerization method. The column was then applied for the separation of six antidepressant compounds. ^ Meanwhile, a simple chiral separation method is developed and presented in Chapter 3. Beta cycodextrin was utilized to achieve the goal of chiral separation. Not only twelve cathinone analytes were separated, but also isomers of several analytes were enantiomerically separated. To better understand the molecular information on the analytes, the TOF-MS system was coupled with the CE. A sheath liquid and a partial filling technique (PFT) were employed to reduce the contamination of MS ionization source. Accurate molecular information was obtained. ^ It is necessary to propose, develop, and optimize new techniques that are suitable for trace-level analysis of samples in forensic, pharmaceutical, and environmental applications. Capillary electrophoresis (CE) was selected for this task, as it requires lower amounts of samples, it simplifies sample preparation, and it has the flexibility to perform separations of neutral and charged molecules as well as enantiomers. ^ Overall, the study demonstrates the versatility of capillary electrophoresis methods in forensic, pharmaceutical, and environmental applications.^

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A comprehensive forensic investigation of sensitive ecosystems in the Everglades Area is presented. Assessing the background levels of contamination in these ecosystems represents a vital resource to build up forensic evidence required to enforce future environmental crimes within the studied areas. This investigation presents the development and validation of a fractionation and isolation method for two families of herbicides commonly applied in the vicinity of the study area, including phenoxy acids like 2,4-D, MCPA, and silvex; as well as the most common triazine-based herbicides like atrazine, prometyne, simazine and related metabolites like DIA and DEA. Accelerated solvent extraction (ASE) and solid phase extraction (SPE) were used to isolate the analytes from abiotic matrices containing large amounts of organic material. Atmospheric-pressure ionization (API) with electrospray ionization in negative mode (ESP-), and Chemical Ionization in the positive mode (APCI+) were used to perform the characterization of the herbicides of interest.

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Thiosalt species are unstable, partially oxidized sulfur oxyanions formed in sulfur-rich environments but also during the flotation and milling of sulfidic minerals especially those containing pyrite (FeS₂) and pyrrhotite (Fe₍₁₋ₓ₎S, x = 0 to 0.2). Detecting and quantifying the major thiosalt species such as sulfate (SO₄²⁻), thiosulfate (S₂O₃²⁻), trithionate (S₃O₆²⁻), tetrathionate (S₄O₆²⁻) and higher polythionates (SₓO₆²⁻, where 3 ≤ x ≤ 10) in the milling process and in the treated tailings is important to understand how thiosalts are generated and provides insight into potential treatment. As these species are unstable, a fast and reliable analytical technique is required for their analysis. Three capillary zone electrophoresis (CZE) methods using indirect UV-vis detection were developed for the simultaneous separation and determination of five thiosalt anions: SO₄²⁻, S₂O₃²⁻, S₃O₆²⁻, S₄O₆²⁻ and S₅O₆²⁻. Both univariate and multivariate experimental design approaches were used to optimize the most critical factors (background electrolyte (BGE) and instrumental conditions) to achieve fast separation and quantitative analysis of the thiosalt species. The mathematically predicted responses for the multivariate experiments were in good agreement with the experimental results. Limits of detection (LODs) (S/N = 3) for the methods were between 0.09 and 0.34 μg/mL without a sample stacking technique and nearly four-fold increase in LODs with the application of field-amplified sample stacking. As direct analysis of thiosalts by mass spectrometry (MS) is limited by their low m/z values and detection in negative mode electrospray ionization (ESI), which is typically less sensitive than positive ESI, imidazolium-based (IP-L-Imid and IP-T-Imid) and phosphonium-based (IP-T-Phos) tricationic ion-pairing reagents were used to form stable high mass ions non-covalent +1 ion-pairs with these species for ESI-MS analysis and the association constants (Kassoc) determined for these ion-pairs. Kassoc values were between 6.85 × 10² M⁻¹ and 3.56 × 10⁵ M⁻¹ with the linear IP-L-Imid; 1.89 ×10³ M⁻¹ and 1.05 × 10⁵ M⁻¹ with the trigonal IP-T-Imid ion-pairs; and 7.51×10² M⁻¹ and 4.91× 10⁴ M⁻¹ with the trigonal IP-T-Phos ion-pairs. The highest formation constants were obtained for S₃O₆²⁻ and the imidazolium-based linear ion-pairing reagent (IP-L-Imid), whereas the lowest were for IP-L-Imid: SO₄²⁻ ion-pair.

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In this work, desorption/ionization mass spectrometry was employed for the analysis of sugars and small platform chemicals that are common intermediates in biomass transformation reactions. Specifically, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) mass spectrometric techniques were employed as alternatives to traditional chromatographic methods. Ionic liquid matrices (ILMs) were designed based on traditional solid MALDI matrices (2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA)) and 1,3-dialkylimidazolium ionic liquids ([BMIM]Cl, [EMIM]Cl, and [EMIM]OAc) that have been employed as reaction media for biomass transformation reactions such as the conversion of carbohydrates to valuable platform chemicals. Although two new ILMs were synthesized ([EMIM][DHB] and [EMIM][CHCA] from [EMIM]OAc), chloride-containing ILs did not react with matrices and resulted in mixtures of IL and matrix in solution. Compared to the parent solid matrices, much less matrix interference was observed in the low mass region of the mass spectrum (< 500 Da) using each of the IL-matrices. Furthermore, the formation of a true ILM (i.e. a new ion pair) does not appear to be necessary for analyte ionization. MALDI sample preparation techniques were optimized based on the compatibility with analyte, IL and matrix. ILMs and IL-matrix mixtures of DHB allowed for qualitative analysis of glucose, fructose, sucrose and N-acetyl-D-glucosamine. Analogous CHCA-containing ILMs did not result in appreciable analyte signals under similar conditions. Small platform compounds such as 5-hydroxymethylfurfural (HMF) and levulinic acid were not detected by direct analysis using MALDI-MS. Furthermore, sugar analyte signals were only detected at relatively high matrix:IL:analyte ratios (1:1:1) due to significant matrix and analyte suppression by the IL ions. Therefore, chemical modification of analytes with glycidyltrimethylammonium chloride (GTMA) was employed to extend this method to quantitative applications. Derivatization was accomplished in aqueous IL solutions with fair reaction efficiencies (36.9 – 48.4 % glucose conversion). Calibration curves of derivatized glucose-GTMA yielded good linearity in all solvent systems tested, with decreased % RSDs of analyte ion signals in IL solutions as compared to purely aqueous systems (1.2 – 7.2 % and 4.2 – 8.7 %, respectively). Derivatization resulted in a substantial increase in sensitivity for MALDI-MS analyses: glucose was reliably detected at IL:analyte ratios of 100:1 (as compared to 1:1 prior to derivatization). Screening of all test analytes resulted in appreciable analyte signals in MALDI-MS spectra, including both HMF and levulinic acid. Using appropriate internal standards, calibration curves were constructed and this method was employed for monitoring a model dehydration reaction of fructose to HMF in [BMIM]Cl. Calibration curves showed wide dynamic ranges (LOD – 100 ng fructose/μg [BMIM]Cl, LOD – 75 ng HMF/μg [BMIM]Cl) with correlation coefficients of 0.9973 (fructose) and 0.9931 (HMF). LODs were estimated from the calibration data to be 7.2 ng fructose/μg [BMIM]Cl and 7.5 ng HMF/μg [BMIM]Cl, however relatively high S/N ratios at these concentrations indicate that these values are likely overestimated. Application of this method allowed for the rapid acquisition of quantitative data without the need for prior separation of analyte and IL. Finally, small molecule platform chemicals HMF and levulinic acid were qualitatively analyzed by DESI-MS. Both HMF and levulinic acid were easily ionized and the corresponding molecular ions were easily detected in the presence of 10 – 100 times IL, without the need for chemical modification prior to analysis. DESI-MS analysis of ILs in positive and negative ion modes resulted in few ions in the low mass region, showing great potential for the analysis of small molecules in IL media.

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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

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Ambient wintertime background urban aerosol in Cork city, Ireland, was characterized using aerosol mass spectrometry. During the three-week measurement study in 2009, 93% of the ca. 1 350 000 single particles characterized by an Aerosol Time-of-Flight Mass Spectrometer (TSI ATOFMS) were classified into five organic-rich particle types, internally mixed to different proportions with elemental carbon (EC), sulphate and nitrate, while the remaining 7% was predominantly inorganic in nature. Non-refractory PM1 aerosol was characterized using a High Resolution Time-of-Flight Aerosol Mass Spectrometer (Aerodyne HR-ToF-AMS) and was also found to comprise organic aerosol as the most abundant species (62 %), followed by nitrate (15 %), sulphate (9 %) and ammonium (9 %), and chloride (5 %). Positive matrix factorization (PMF) was applied to the HR-ToF-AMS organic matrix, and a five-factor solution was found to describe the variance in the data well. Specifically, "hydrocarbon-like" organic aerosol (HOA) comprised 20% of the mass, "low-volatility" oxygenated organic aerosol (LV-OOA) comprised 18 %, "biomass burning" organic aerosol (BBOA) comprised 23 %, non-wood solid-fuel combustion "peat and coal" organic aerosol (PCOA) comprised 21 %, and finally a species type characterized by primary m/z peaks at 41 and 55, similar to previously reported "cooking" organic aerosol (COA), but possessing different diurnal variations to what would be expected for cooking activities, contributed 18 %. Correlations between the different particle types obtained by the two aerosol mass spectrometers are also discussed. Despite wood, coal and peat being minor fuel types used for domestic space heating in urban areas, their relatively low combustion efficiencies result in a significant contribution to PM1 aerosol mass (44% and 28% of the total organic aerosol mass and non-refractory total PM1, respectively).Ambient wintertime background urban aerosol in Cork city, Ireland, was characterized using aerosol mass spectrometry. During the three-week measurement study in 2009, 93% of the ca. 1 350 000 single particles characterized by an Aerosol Time-of-Flight Mass Spectrometer (TSI ATOFMS) were classified into five organic-rich particle types, internally mixed to different proportions with elemental carbon (EC), sulphate and nitrate, while the remaining 7% was predominantly inorganic in nature. Non-refractory PM1 aerosol was characterized using a High Resolution Time-of-Flight Aerosol Mass Spectrometer (Aerodyne HR-ToF-AMS) and was also found to comprise organic aerosol as the most abundant species (62 %), followed by nitrate (15 %), sulphate (9 %) and ammonium (9 %), and chloride (5 %). Positive matrix factorization (PMF) was applied to the HR-ToF-AMS organic matrix, and a five-factor solution was found to describe the variance in the data well. Specifically, "hydrocarbon-like" organic aerosol (HOA) comprised 20% of the mass, "low-volatility" oxygenated organic aerosol (LV-OOA) comprised 18 %, "biomass burning" organic aerosol (BBOA) comprised 23 %, non-wood solid-fuel combustion "peat and coal" organic aerosol (PCOA) comprised 21 %, and finally a species type characterized by primary m/z peaks at 41 and 55, similar to previously reported "cooking" organic aerosol (COA), but possessing different diurnal variations to what would be expected for cooking activities, contributed 18 %. Correlations between the different particle types obtained by the two aerosol mass spectrometers are also discussed. Despite wood, coal and peat being minor fuel types used for domestic space heating in urban areas, their relatively low combustion efficiencies result in a significant contribution to PM1 aerosol mass (44% and 28% of the total organic aerosol mass and non-refractory total PM1, respectively).

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An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed for the measurement of the size resolved chemical composition of single particles at a site in Cork Harbour, Ireland for three weeks in August 2008. The ATOFMS was co-located with a suite of semi-continuous instrumentation for the measurement of particle number, elemental carbon (EC), organic carbon (OC), sulfate and particulate matter smaller than 2.5 μm in diameter (PM2.5). The temporality of the ambient ATOFMS particle classes was subsequently used in conjunction with the semi-continuous measurements to apportion PM2.5 mass using positive matrix factorisation. The synergy of the single particle classification procedure and positive matrix factorisation allowed for the identification of six factors, corresponding to vehicular traffic, marine, long-range transport, various combustion, domestic solid fuel combustion and shipping traffic with estimated contributions to the measured PM2.5 mass of 23%, 14%, 13%, 11%, 5% and 1.5% respectively. Shipping traffic was found to contribute 18% of the measured particle number (20–600 nm mobility diameter), and thus may have important implications for human health considering the size and composition of ship exhaust particles. The positive matrix factorisation procedure enabled a more refined interpretation of the single particle results by providing source contributions to PM2.5 mass, while the single particle data enabled the identification of additional factors not possible with typical semi-continuous measurements, including local shipping traffic.

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Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

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The composition of atmospheric particles is an important factor in determining their impact on climate and health. In this study, an aerosol time-of-flight mass spectrometer (ATOFMS) was used to measure the chemical composition of ambient single particles at two contrasting locations – an industrial site in Dunkirk, France and a regional background site in Corsica. The ATOFMS data were combined with meteorological information and other particle measurements to determine the various sources of the particles observed at the sites. The particle classes detected in Dunkirk included carbonaceous species from fossil fuel combustion and biomass burning, metal-containing types from local industries and seasalt. Highest particle number concentrations and mass concentrations of PM2.5, black carbon, organics, nitrate, ammonium and several metallic species (Fe, Mn, Pb, Zn) were found during periods heavily influenced by local industry. Particles from a ferromanganese alloy manufacturing facility were identified by comparing ambient ATOFMS data with single particle mass spectra from industrial chimney filters and ores. Particles from a steelworks were identified based on comparison of the ambient data with previous studies. Based on these comparisons, the steelworks was identified as the dominant emitter of Fe-rich particles, while the ferromanganese alloy facility emitted Mn-rich particles. In Corsica, regional transport of carbonaceous particles from biomass burning and fossil fuel combustion was identified as the major source of particles in the Mediterranean background aerosol. Throughout the campaign the site was influenced by air masses altering the composition of particles detected. During North Atlantic air masses the site was heavily influenced by fresh sea salt. Regional stagnation was the most common type of air mass regime throughout the campaign and resulted in the accumulation of carbonaceous particles during certain periods. Mass concentrations were estimated for ATOFMS particle classes, and good agreement was found between the major carbonaceous classes and other quantitative measurements. Overall the results of this work serve to highlight the excellent ability of the ATOFMS technique in providing source-specific composition and mixing state information on atmospheric particles at high time resolution.