O uso de drogas estimulantes por motoristas é reconhecidamente responsável por um aumento significativo na quantidade de acidentes nas estradas e rodovias. A própria exigência do trabalho muitas vezes acaba direcionando-os para a busca de algo que lhes proporcione maior estado de vigília e atenção nas estradas. Com base na importante correlação entre a profissão e o uso de substâncias anfetamínicas, foi proposta uma metodologia analítica para a determinação de anfetamina, metanfetamina, 3,4 metilenodioxianfetamina, 3,4 metilenodioximetanfetamina e 3,4 metilenodioxietilanfetamina em amostras de saliva através de técnica de extração líquido-líquido e análise por cromatografia em fase gasosa acoplada a espectrometria de massas (GC-MS). Para o desenvolvimento do método foi utilizado 1 mL de saliva, extração líquido-líquido com o solvente acetato de etila, derivatização com anidrido heptafluorobutírico (HFBA) e detecção com GC-MS. A metodologia foi validada e demonstrou linearidade de 10 a 400 ng/mL de saliva para todos os compostos. Os limites de detecção estabelecidos se encontraram entre 2,5 ng/mL e 7,5 ng/mL, enquanto os de quantificação foram de 10 ng/mL para todos os compostos. A exatidão apresentou valores entre 93,8% e 108,3%, a precisão intra-ensaio valores entre 4,05% e 9,34% e a precisão inter-ensaio valores entre 5,28% e 9,90%. A metodologia validada foi aplicada em amostras de saliva de caminhoneiros que trafegavam na região da cidade de Roseira SP em um evento de atendimento ao público promovido pela Sest/Senat (Serviço Social do Transporte/ Serviço Nacional de Aprendizagem do Transporte) em parceria com a Polícia Rodoviária Federal. Duas amostras de saliva de um total de 40 amostras analisadas apresentaram resultado positivo para anfetamina. / The use of stimulants by professional drivers is known as an increasing risk of accidents on the roads. The type of work itself induces the drivers to look out for something that provides better state of alertness and reduced sleep. Based on this important correlation between the occupation and use of stimulants, an analytical methodology was proposed for the determination of amphetamine, methamphetamine, and their methylenedioxy derivatives 3,4 methylenedioxyamphetamine, 3-4 methylenedioxymethamphetamine and 3,4 methylenedioxyethylamphetamine on oral fluid samples using solvent extraction and gas chromatography coupled with mass spectrum for detection and quantification of these analytes. The developed methodology used 1 mL of oral fluid, liquid-liquid extraction, heptafluorobutyric anhydride and gas chromatography-mass spectrometry for the detection and quantification. The methodology was validated and showed good linearity within the limits of 10 ng/mL and 400 ng/mL of oral fluid. The limits of detection were between 2.5 ng/mL and 7.5 ng/mL, while the limits of quantification were 10 ng/mL for all analytes. The accuracy showed values between 93.8% e 108.3%, the intra-assay precision between 4.05% e 9.34% and the inter-assay precision between 5.28% e 9.90%. The validated methodology was tested in oral fluid samples collected from truck drivers near the city of Roseira São Paulo during an event of health assistance fomented by SEST/SENAT in partnership with Federal Police. It was collected 40 saliva samples and two of them presented positive result for amphetamine.

In this work our driving motivation is to develop mathematically robust and computationally efficient algorithms that will help chemists towards their goal of pattern matching. Environmental chemistry today broadly faces difficult computational and interpretational challenges for vast and ever-increasing data repositories. A driving factor behind these challenges are little known intricate relationships between constituent analytes that constitute complex mixtures spanning a range of target and non-target compounds. While the end of goal of different environment applications are diverse, computationally speaking, many data interpretation bottlenecks arise from lack of efficient algorithms and robust mathematical frameworks to identify, cluster and interpret compound peaks. There is a compelling need for compound-cognizant quantitative interpretation that accounts for the full informational range of gas chromatographic (and mass spectrometric) datasets. Traditional target-oriented analysis focus only on the dominant compounds of the chemical mixture, and thus are agnostic of the contribution of unknown non-target analytes. On the other extreme, statistical methods prevalent in chemometric interpretation ignore compound identity altogether and consider only the multivariate data statistics, and thus are agnostic of intrinsic relationships between the well-known target and unknown target analytes. Thus, both schools of thought (target-based or statistical) in current-day chemical data analysis and interpretation fall short of quantifying the complex interaction between major and minor compound peaks in molecular mixtures commonly encountered in environmental toxin studies. Such interesting insights would not be revealed via these standard techniques unless a deeper analysis of these patterns be taken into account in a quantitative mathematical framework that is at once compound-cognizant and comprehensive in its coverage of all peaks, major and minor. This thesis aims to meet this grand challenge using a combination of signal processing, pattern recognition and data engineering techniques. We focus on petroleum biomarker analysis and polychlorinated biphenyl (PCB) congener studies in human breastmilk as our target applications. We propose a novel approach to chemical data analytics and interpretation that bridges the gap between target-cognizant traditional analysis from environmental chemistry with compound-agnostic computational methods in chemometric data engineering. Specically, we propose computational methods for target-cognizant data analytics that also account for local unknown analytes allied to the established target peaks. The key intuition behind our methods are based on the underlying topography of the gas chromatigraphic landscape, and we extend recent peak mapping methods as well as propose novel peak clustering and peak neighborhood allocation methods to achieve our data analytic aims. Data-driven results based on a multitude of environmental applications are presented.

Until present, many researchers relied on the conventional plug flow dispersion models to analyse the concentration profiles obtained from the tracer injection experiments to evaluate the dispersion coefficients in packed beds. The Fickian concept in the limit of long time duration is assumed to be applicable and it implies that the mean-square displacement of the tracer profile is constant with time and the concentration profile is Gaussian. There were very few studies on identifying the conditions under which this assumption is valid and delineate the range of applicability of the existing plug flow dispersion models. If the time scales of a tracer injection experiment are not sufficient for a tracer to traverse the bed radius and sample the velocity variations, this could give rise to persisting non-Fickian transients where the mean-square displacement of the tracer profile is not constant with time and the concentration profile deviates from the normal Gaussian distribution. These transients cannot be predicted by the conventional plug dispersion models. An extended axial non-Fickian macroscopic dispersion model is derived to describe the transient development of a solute tracer when injected into a fluid flowing through a cylindrical packed bed or empty tube and some non-Fickian effects in the dispersion process. The flow profile in beds packed with uniform particles exhibits radial non-uniformity due to the oscillatory variation in porosity because of the wall confinement (wall effect). Compared with the axial plug flow dispersion model, the extended model contains time-dependent coefficients such as the transient axial dispersion coefficient and higher order derivatives (higher than second order) of the cross-sectionally averaged concentration. Including them provides some insight on non-Fickian transport in the dispersion process. The model provides time criteria on the basis that the effelongitudinal dispersion coefficient in the packed bed reaches its asymptotic value and the non-Fickian transients will die out. Some experimental conditions in the literature were checked by these criteria and found to be either marginally satisfied, or not satisfied at all, which indicates that the Fickian concept is not valid. The model results for tracer dispersion in cylindrical packed beds show that the longitudinal dispersion coefficient converges to its asymptotic value on a time scale proportional to R2/(DT) where R is the column radius and (DT) is the area averaged lateral dispersion coefficient. The extended model encouraged study of the consequences of the additional dispersion terms in other applications such as the pulse spread in the field of capillary column inverse gas chromatography (CCIGC). CCIGC is used to evaluate the solute-polymer diffusion coefficient Dp and the partition coefficient K at infinite dilute conditions. The tube geometry in CCIGC is more complex than the conventional Taylor dispersion problem due to the polymer coating on the inside of the capillary wall. The extended CCIGC model presented in this study has advantages over the previous models by including the effects of Taylor dispersion and higher order derivatives of the pulse area-averaged concentration. Taylor dispersion effect causes more pulse spread in the longitudinal direction and by not including it in the CCIGC regression models may cause a significant error in the measured Dp values. The extended CCIGC model provides for the first time criteria on capillary dimensions for the transient coefficients (multiplying the second and higher order derivatives) to become constant and for the non-Fickian effects associated with the higher order derivatives to be neglected. Model results show that Taylor dispersion effect has a significant effect on the elution profiles at high values of Dp and/or low values of gas diffusion coefficients Dg and it can be used to increase the sensitivity range of the previous CCIGC models at extremely low and high Dp values.

Thesis (M.Sc. (Nutrition))--North-West University, Potchefstroom Campus, 2007.

Thesis (M. Sc.)(Chemistry)--University of Pretoria, 2005. / Includes summaries in English and Afrikaans. Includes bibliographical references. Available on the Internet via the World Wide Web.

The biggest limitation to conventional gas chromatography (GC) is limited peak capacity, making the analysis of complex mixtures a difficult or even impossible task. Comprehensive two-dimensional gas chromatography (GC×GC) significantly increases peak capacity and resolution, improves sensitivity and generates structured 3D chromatograms. This is achieved by connecting two columns coated with different stationary phases through a special interface (modulator). The interface samples the first column effluent and periodically injects fractions of this material, as narrow injection pulses, onto the second column for further separation. Commercial instruments achieve this with cryogenic agents. Since this expensive approach permits only in-laboratory analysis, the development of simple, economical and field-capable GC×GC systems is in demand. This report summarizes the fundamentals governing GC×GC separations and a brief history of technological advances in the field. It also documents the construction of a simple interface, devoid of moving parts and cryogenic consumables, and hence highly suitable for field analysis and monitoring applications. Evaluation of the interface suggests on-par performance with more complicated cryogenic modulators. GC×GC separations of technical mixtures of fatty acid methyl esters (FAMEs), common environmental pollutants (EPA 8270), polychlorinated biphenyls (PCBs), pesticides (toxaphene), as well as selected essential oils and major distillation fractions of crude oil indicate very good performance. Most notably, the interface prototype was applied for the first ever time-resolved on-site analysis of the semivolatile organic fraction of urban air particulate matter (PM2.5).

The biggest limitation to conventional gas chromatography (GC) is limited peak capacity, making the analysis of complex mixtures a difficult or even impossible task. Comprehensive two-dimensional gas chromatography (GC×GC) significantly increases peak capacity and resolution, improves sensitivity and generates structured 3D chromatograms. This is achieved by connecting two columns coated with different stationary phases through a special interface (modulator). The interface samples the first column effluent and periodically injects fractions of this material, as narrow injection pulses, onto the second column for further separation. Commercial instruments achieve this with cryogenic agents. Since this expensive approach permits only in-laboratory analysis, the development of simple, economical and field-capable GC×GC systems is in demand. This report summarizes the fundamentals governing GC×GC separations and a brief history of technological advances in the field. It also documents the construction of a simple interface, devoid of moving parts and cryogenic consumables, and hence highly suitable for field analysis and monitoring applications. Evaluation of the interface suggests on-par performance with more complicated cryogenic modulators. GC×GC separations of technical mixtures of fatty acid methyl esters (FAMEs), common environmental pollutants (EPA 8270), polychlorinated biphenyls (PCBs), pesticides (toxaphene), as well as selected essential oils and major distillation fractions of crude oil indicate very good performance. Most notably, the interface prototype was applied for the first ever time-resolved on-site analysis of the semivolatile organic fraction of urban air particulate matter (PM2.5).

Air is one of the most important resources in the world and is essential for life. With the development of industry, air pollution is becoming a severe problem. Air Pollution not only affects the quality of the air we breathe; it also impacts the land and the water. Volatile organic compounds (VOCs), which can cause short-term and long-term health problems, are found as contaminants in both indoor air and the environment. Therefore, it is necessary to develop accurate and convenient sampling methods to determine VOCs at trace levels in both community and occupational environment. The focus of this project is to develop the needle trap devices (NTDs) with appropriate sorbents and employ them to do air samplings by diffusive or active sampling mode. For diffusive sampling, the NTD with sorbent Carboxen1000 was developed to monitor benzene, toluene, ethylbenzene and o-xylene (BTEX) in the air, coupled with GC-MS. The factors such as sorbent strength, response time, face velocity, temperature and pressure, relative humidity and sampling duration were investigated. Method validations were done both in the laboratory and in field. The results demonstrate that the NTD with Carboxen1000 is a successful diffusive sampler for monitoring Time-weighted average (TWA) concentrations of BTEX. On the other hand, the NTD with divinylbenzene (DVB) coupled with GC-MS by thermal desorption was developed for sampling and analysis of volatile thiols. The factors such as sorbent strength, desorption efficiency were investigated. The applications, such as vegetable analysis and field sampling analysis, indicate that the NTD with sorbent DVB is a successful active sampler for determine volatile thiols in food and air samples.

Air is one of the most important resources in the world and is essential for life. With the development of industry, air pollution is becoming a severe problem. Air Pollution not only affects the quality of the air we breathe; it also impacts the land and the water. Volatile organic compounds (VOCs), which can cause short-term and long-term health problems, are found as contaminants in both indoor air and the environment. Therefore, it is necessary to develop accurate and convenient sampling methods to determine VOCs at trace levels in both community and occupational environment. The focus of this project is to develop the needle trap devices (NTDs) with appropriate sorbents and employ them to do air samplings by diffusive or active sampling mode. For diffusive sampling, the NTD with sorbent Carboxen1000 was developed to monitor benzene, toluene, ethylbenzene and o-xylene (BTEX) in the air, coupled with GC-MS. The factors such as sorbent strength, response time, face velocity, temperature and pressure, relative humidity and sampling duration were investigated. Method validations were done both in the laboratory and in field. The results demonstrate that the NTD with Carboxen1000 is a successful diffusive sampler for monitoring Time-weighted average (TWA) concentrations of BTEX. On the other hand, the NTD with divinylbenzene (DVB) coupled with GC-MS by thermal desorption was developed for sampling and analysis of volatile thiols. The factors such as sorbent strength, desorption efficiency were investigated. The applications, such as vegetable analysis and field sampling analysis, indicate that the NTD with sorbent DVB is a successful active sampler for determine volatile thiols in food and air samples.

No description available.