<p>Испитивано је хроматографско понашање (хроматографска липофилност) 29 стероидних једињења (триазола и тетразола, толуенсулфонилхидразида, диона, нитрила и динитрила) од потенцијалног биомедицинског значаја, испитивано је помоћу течне хроматографије високих перформанси на обрнутим фазама, применом две стационарне и две мобилне фазе. Липофилност, изражена преко ретенционог параметра logk, моделована је QSRR приступом. Формирани линеарни и нелинеарни модели омогућили су испитивање односа између ретенционих параметара и in silico молекулских дескриптора, који су израчунати на основу структуре испитиваних једињења. Добра предиктивна моћ формираних модела, добијених за калибрациони сет, потврђена је и применом екстерног тест сета и валидационог сета. Предиктивна моћ формираних модела потврђује могућност њиховог коришћења за предвиђање липофилности нових, структурно сличних, једињења. Примењене су и класификационе хемометријске методе (анализа главних компоненти и хијерархијска кластер анализа) како би се уочиле сличности и разлика између једињења. Поред тога, представљена је in vitro анализа антимикробног потенцијала испитиваних стероидних једињења према Staphylococcus aureus, Escherichia coli и Candida albicans. Два једињења, са епоксидном групом у положају 4,5, испољила су бактериостатски ефекат према S. aureus. Такође, приказана је докинг анализа одабраних испитиваних једињења са антипролиферативном активношћу према ћелијама андроген-рецептор негативног канцера простате (AR-нег. PC-3). На основу визуелизације оптималних положаја и анализе постојећих интеракција, идентификовано је једињење са највећим потенцијалом као инхибитор хуманог цитохрома P450 CYP17A1.</p> / <p>Ispitivano je hromatografsko ponašanje (hromatografska lipofilnost) 29 steroidnih jedinjenja (triazola i tetrazola, toluensulfonilhidrazida, diona, nitrila i dinitrila) od potencijalnog biomedicinskog značaja, ispitivano je pomoću tečne hromatografije visokih performansi na obrnutim fazama, primenom dve stacionarne i dve mobilne faze. Lipofilnost, izražena preko retencionog parametra logk, modelovana je QSRR pristupom. Formirani linearni i nelinearni modeli omogućili su ispitivanje odnosa između retencionih parametara i in silico molekulskih deskriptora, koji su izračunati na osnovu strukture ispitivanih jedinjenja. Dobra prediktivna moć formiranih modela, dobijenih za kalibracioni set, potvrđena je i primenom eksternog test seta i validacionog seta. Prediktivna moć formiranih modela potvrđuje mogućnost njihovog korišćenja za predviđanje lipofilnosti novih, strukturno sličnih, jedinjenja. Primenjene su i klasifikacione hemometrijske metode (analiza glavnih komponenti i hijerarhijska klaster analiza) kako bi se uočile sličnosti i razlika između jedinjenja. Pored toga, predstavljena je in vitro analiza antimikrobnog potencijala ispitivanih steroidnih jedinjenja prema Staphylococcus aureus, Escherichia coli i Candida albicans. Dva jedinjenja, sa epoksidnom grupom u položaju 4,5, ispoljila su bakteriostatski efekat prema S. aureus. Takođe, prikazana je doking analiza odabranih ispitivanih jedinjenja sa antiproliferativnom aktivnošću prema ćelijama androgen-receptor negativnog kancera prostate (AR-neg. PC-3). Na osnovu vizuelizacije optimalnih položaja i analize postojećih interakcija, identifikovano je jedinjenje sa najvećim potencijalom kao inhibitor humanog citohroma P450 CYP17A1.</p> / <p>Chromatographic behavior (chromatographic lipophilicity) of 29 steroid compounds (triazole and tetrazole, toluenesulfonylhydrazide, dione, dinitrile and nitrile) with potential biomedical importance was investigated by reversed-phases high-performance liquid chromatography using two stationary and two mobile phases. The lipophilicity expressed through the retention parameter logk was modeled using QSRR approach. Formed linear and non-linear models enabled the study of the relationship between the retention parameters and in silico molecular descriptors calculated from the structure of the investigated compounds. Good predictive power of the established models obtained for the calibration set was confirmed by the application of an external test set and validation set. The predictive power of the established model confirms the possibility of their use for lipophilicity prediction of new, structurally similar compounds. The classification chemometric methods (principal components analysis and hierarchical cluster analysis) were applied in order to recognize the similarities and differences between the compounds. Тhis dissertation presents the in vitro analysis of the antimicrobial potentials of the investigated steroid compounds against Staphylococcus aureus, Escherichia coli and Candida albicans. Two compounds, with epoxy group in the position 4,5, exhibited bacteriostatic effect against S. aureus. The docking analysis of selected test compounds with antiproliferative activity toward cells of androgen receptor-negative prostate cancer (AR-neg. PC-3) is showed. Based on the optimal position visualization and analysis of existing interactions a compound with the most promising potential as human cytochrome P450 CYP17A1 inhibitor is idetified.</p>

<p>Technology has become increasingly more prevalent in all aspects of society since the age of the computer. The United States Military has successfully integrated the powerful processing capabilities of computers to increase the proficiency and lethality of its Soldiers, Sailors, Marines, and Airmen. However, this increased lethality comes at risk due to the inherent vulnerabilities of computer systems to spyware, malware, and counterfeit components. Inspired by the ability of canines to seek out and find electronic devices, this research sought methods to characterize components by their “scent” using precise analytical tools. Using these tools, this thesis sought to develop and utilize non-invasive methods to show proof-of-concept for electronic device classification by volatile compounds unique to different types of components. The findings of this research proved that electronic components that vary by age, origin, type, or manufacturer emit different volatile compounds available for detection using modern two-dimensional gas chromatography and solid-phase microextraction technologies. If developed further, the methods used in this research have the potential for application in the United States Department of Defense to ensure that all electronic components installed in their systems are authentic, come from a trusted source, and can be relied upon in even the most stressful operating conditions.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / Clear coats have been part of automotive field paint finishes for several decades. Originally a layer of paint with no pigment, they have evolved into a protective layer important to the appearance and longevity of the vehicle's finish. These clear coats have been studied previously using infrared spectroscopy and other spectroscopic techniques. Previous studies focused on either all the layers of an automobile finish or on chemometric analysis of clear coats using other analytical techniques. For this study, chemometric analysis was performed on preprocessed spectra averaged from five separate samples. Samples were analyzed on a Thermo-Nicolet Nexus 670 connected to a Continuμm™ FT-IR microscope. Two unsupervised chemometric techniques, Agglomerative Hierarchical Clustering (AHC) and Principal Component Analysis (PCA), were used to evaluate the data set. Discriminant analysis, a supervised technique, was evaluated using several known qualifiers; these included cluster group from AHC, make, model, and year. Although discriminant analysis confirmed the AHC and PCA results, no correlation to make, model, or year was indicated.

Tato doktorská práce je zaměřena na vývoj algoritmu ke zpracování dat naměřených zařízením pro spektrometrii laserem indukovaného plazmatu (angl. LIBS). Zařízení LIBS s tímto algoritmem by mělo být následně schopno provést třídění vzorků a kvantitativní analýzu analytu in-situ a v reálném čase. Celá experimentální část této práce byla provedena ve Spolkovém institutu pro materiálový výzku a testování (něm. BAM) v Berlíně, SRN, kde byl sestaven elementární LIBS systém. Souběžně s experimentílní prací byl vytvořen přehled literárních zdrojů s cílem podat ucelený pohled na problematiku chemometrických metod používaných k analýze LIBS měření. Použití chemometrických metod pro analýzu dat získaných pomocí LIBS měření je obecně doporučováno především tehdy, jsou-li analyzovány vzorky s komplexní matricí. Vývoj algoritmu byl zaměřen na kvantitativní analýzu a třídění vyvřelých hornin na základě měření pomocí LIBS aparatury. Sada vzorků naměřených použitím metody LIBS sestávala z certifikovaných referenčních materiálů a vzorků hornin shromážděných přímo na nalezištích mědi v Íránu. Vzorky z Íránu byly následně na místě roztříděny zkušeným geologem a množství mědi v daných vzorcích bylo změřeno na Univerzitě v Clausthalu, SRN. Výsledné kalibrační křivky byly silně nelineární, přestože byly sestaveny i z měření referenčních vzorků. Kalibrační křivku bylo možné rozložit na několik dílčích tak, že závislost intenzity měděné čáry na množství mědi se nacházela v jiném trendu pro jednotlivé druhy hornin. Rozdělení kalibrační křivky je zpravidla přisuzováno tzv. matričnímu jevu, který silně ovlivňuje měření metodou LIBS. Jinými slovy, pokud určujeme množství analytu ve vzorcích s různou matricí, je výsledná kalibrační křivka sestavená pouze z jedné proměnné (intenzity zvolené spektrální čáry analytu) nepřesná. Navíc, normalizace takto vytvořených kalibračních křivek k intenzitě spektrální čáry matrčního prvku nevedla k výraznému zlepšení linearity. Je obecně nemožné vybrat spektrální čáru jednoho matričního prvku pokud jsou analyzovány prvky s komplexním složením matric. Chemometrické metody, jmenovitě regrese hlavních komponent (angl. PCR) a regrese metodou nejmenších čtverců (angl. PLSR), byly použity v multivariační kvantitatvní analýze, tj. za použití více proměnných/spektrálních čar analytu a matričních prvků. Je potřeba brát v potaz, že PCR a PLSR mohou vyvážit matriční jev pouze do určité míry. Dále byly vzorky úspěšně roztříděny pomocí analýzy hlavních komponent (angl. PCA) a Kohonenových map na základě složení matričních prvků (v anglické literatuře se objevuje termín ‚spectral fingerprint‘) Na základě teorie a experimentálních měření byl navržen algoritmus pro spolehlivé třídění a kvantifikaci neznámých vzorků. Tato studie by měla přispět ke zpracování dat naměřených in-situ přístrojem pro dálkovou LIBS analýzu. Tento přístroj je v současnosti vyvíjen v Brně na Vysokém učení technickém. Toto zařízení bude nenahraditelné při kvantifikaci a klasifikaci vzorků pouze tehdy, pokud bude použito zároveň s chemometrickými metodami a knihovnami dat. Pro tyto účely byla již naměřena a testována část knihoven dat v zaměření na aplikaci metody LIBS do těžebního průmyslu.

<p dir="ltr">Condition-based maintenance is a proactive maintenance strategy that prevents failures or diminished functionality in process systems through proper monitoring and management of process conditions. Despite being considered a mature maintenance management strategy in various industries, condition-based maintenance remains underutilized in pharmaceutical manufacturing. This situation needs to change, especially as the pharmaceutical industry continues to shift from batch to continuous manufacturing, where the implementation of CBM as a maintenance strategy assumes a greater importance.</p><p dir="ltr">This dissertation focused on addressing the challenges of implementing CBM in a continuous drug product manufacturing system. These challenges stem from the unique aspects of pharmaceutical drug product manufacturing, which includes the peculiar behavior of particulate materials and the evolutionary nature of pharmaceutical process development. The proposed solutions to address these challenges revolve around an innovative framework for the practical development of condition monitoring systems. Overall, this framework enables the incorporation of limited process knowledge in creating condition monitoring systems, which has the desired effect of empowering data-driven machine learning models.</p><p dir="ltr">A key feature of this framework is a formalized method to represent the process condition, which is usually vaguely defined in literature. This representation allows the proper mapping of preexisting condition monitoring systems, and the segmentation of the entire process condition model into smaller modules that have more manageable condition monitoring problems. Because this representation methodology is based on probabilistic graphical modelling, the smaller modules can then be holistically integrated via their probabilistic relationships, allowing the robust operation of the resulting condition monitoring system and the process it monitors.</p><p dir="ltr">Breaking down the process condition model into smaller segments is crucial for introducing novel fault detection capabilities, which enhances model prediction transparency and ensures prediction acceptance by a human operator. In this work, a methodology based on prediction probabilities was introduced for developing condition monitoring systems with novel fault detection capabilities. This approach relies on high-performing machine learning models capable of consistently classifying all the initially known conditions in the fault library with a high degree of certainty. Simplifying the condition monitoring problem through modularization facilitates this, as machine learning models tend to perform better on simpler systems. Performance indices were proposed to evaluate the novel fault detection capabilities of machine learning models, and a formal approach to managing novel faults was introduced.</p><p dir="ltr">Another benefit of modularization is the identification of condition monitoring blind spots. Applying it to the RC led to sensor development projects such as the virtual sensor for measuring granule flowability. This sensor concept was demonstrated successfully by using a data-driven model to predict granule flowability based on size and shape distribution measurements. With proper model selection and feature extraction guided by domain expertise, the resulting sensor achieved the best prediction performance reported in literature for granule flowability.</p><p dir="ltr">As a demonstration exercise in examining newly discovered faults, this work investigated a roll compaction phenomenon that is usually concealed from observation due to equipment design. This phenomenon results in the ribbon splitting along its thickness as it comes out of the rolls. In this work, important aspects of ribbon splitting were elucidated, particularly its predictability based on RC parameters and the composition of the powder blend used to form the ribbon. These findings have positive ramifications for the condition monitoring of the RC, as correspondence with industrial practitioners suggests that a split ribbon is desirable in some cases, despite being generally regarded as undesirable in the limited literature available on the subject.</p><p dir="ltr">Finally, this framework was primarily developed for the pharmaceutical dry granulation line, which consists of particle-based systems with a moderate level of complexity. However, it was also demonstrated to be feasible for the Tennessee Eastman Process (TEP), a more complex liquid-gas process system with a greater number of process faults, variables, and unit operations. Applying the framework resulted in machine learning models that yielded one of the best fault detection performances reported in literature for the TEP, while also introducing additional capabilities not yet normally reported in literature, such as fault diagnosis and novel fault detection.</p>

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In the production of paper, the quality of the pulp is an important factor both for the productivity and for the final quality. Reliable real-time measurements of pulp quality are therefore needed. One way is to use acoustic or vibration sensors that give information-rich signals and place the sensors at suitable locations in a pulp production line. However, these sensors are not selective for the pulp properties of interest. Therefore, advanced signal processing and multivariate calibration are essential tools. The current work has been focused on the development of calibration routes for extraction of information from acoustic sensors and on signal processing algorithms for enhancing the information-selectivity for a specific pulp property or class of properties. Multivariate analysis methods like Principal Components Analysis (PCA), Partial Least Squares (PLS) and Orthogonal Signal Correction (OSC) have been used for visualization and calibration. Signal processing methods like Fast Fourier Transform (FFT), Fast Wavelet Transform (FWT) and Continuous Wavelet Transform (CWT) have been used in the development of novel signal processing algorithms for extraction of information from vibrationacoustic sensors. It is shown that use of OSC combined with PLS for prediction of Canadian Standard Freeness (CSF) using FFT-spectra produced from vibration data on a Thermo Mechanical Pulping (TMP) process gives lower prediction errors and a more parsimonious model than PLS alone. The combination of FFT and PLS was also used for monitoring of beating of kraft pulp and for screen monitoring. When using regular FFT-spectra on process acoustic data the obtained information tend to overlap. To circumvent this two new signal processing methods were developed: Wavelet Transform Multi Resolution Spectra (WT-MRS) and Continuous Wavelet Transform Fibre Length Extraction (CWT-FLE). Applying WT-MRS gave PLS-models that were more parsimonious with lower prediction error for CSF than using regular FFT-Spectra. For a Medium Consistency (MC) pulp stream WT-MRS gave predictions errors comparable to the reference methods for CSF and Brightness. The CWT-FLE method was validated against a commercial fibre length analyzer and good agreement was obtained. The CWT-FLE-curves could therefore be used instead of other fibre distribution curves for process control. Further, the CWT-FLE curves were used for PLS modelling of tensile strength and optical parameters with good results. In addition to the mentioned results a comprehensive overview of technologies used with acoustic sensors and related applications has been performed. / Vid framställning av pappersprodukter är kvaliteten på massan en viktig faktor för produktiviteten och kvalitén på slutresultatet. Det är därför viktigt att ha tillgång till tillförlitliga mätningar av massakvalitet i realtid. En möjlighet är att använda akustik- eller vibrationssensorer i lämpliga positioner vid enhetsoperationer i massaprocessen. Selektiviteten hos dessa mätningar är emellertid relativt låg i synnerhet om mätningarna är passiva. Därför krävs avancerad signalbehandling och multivariat kalibrering. Det nu presenterade arbetet har varit fokuserat på kalibreringsmetoder för extraktion av information ur akustiska mätningar samt på algoritmer för signalbehandling som kan ge förbättrad informationsselektivitet. Multivariata metoder som Principal Component Analysis (PCA), Partial Least Squares (PLS) and Orthogonal Signal Correction (OSC) har använts för visualisering och kalibrering. Signalbehandlingsmetoderna Fast Fourier Transform (FFT), Fast Wavelet Transform (FWT) och Continuous Wavelet Transform (CWT) har använts i utvecklingen av nydanande metoder för signalbehandling anpassade till att extrahera information ur signaler från vibrations/akustiska sensorer. En kombination av OSC och PLS applicerade på FFT-spektra från raffineringen i en Termo Mechnaical Pulping (TMP) process ger lägre prediktionsfel för Canadian Standard Freeness (CSF) än enbart PLS. Kombinationen av FFT och PLS har vidare använts för monitorering av malning av sulfatmassa och monitorering av silning. Ordinära FFT-spektra av t.ex. vibrationssignaler är delvis överlappande. För att komma runt detta har två signalbehandlingsmetoder utvecklats, Wavelet Transform Multi Resolution Spectra (WT-MRS) baserat på kombinationen av FWT och FFT samt Continuous Wavelet Transform Fibre Length Extraction (CWT-FLE) baserat på CWT. Tillämpning av WT-MRS gav enklare PLS-modeller med lägre prediktionsfel för CSF jämfört med att använda normala FFT-spektra. I en annan tillämpning på en massaström med relativt hög koncentration (Medium Consistency, MC) kunde prediktioner för CSF samt ljushet erhållas med prediktionsfel jämförbart med referensmetodernas fel. Metoden CWT-FLE validerades mot en kommersiell fiberlängdsmätare med god överensstämmelse. CWT-FLE-kurvorna skulle därför kunna användas i stället för andra fiberdistributionskurvor för processtyrning. Vidare användes CWT-FLE kurvor för PLS modellering av dragstyrka samt optiska egenskaper med goda resultat. Utöver de nämnda resultaten har en omfattande litteratursammanställning gjorts över området och relaterade applikationer. / QC 20100629

Submitted by Biblioteca de Pós-Graduação em Geoquímica BGQ (bgq@ndc.uff.br) on 2016-05-02T17:58:54Z No. of bitstreams: 1 GALLOTTA_30_06_14.pdf: 62695484 bytes, checksum: 33335ee3affc2bcffb11fc10caf9ae3f (MD5) / Made available in DSpace on 2016-05-02T17:58:54Z (GMT). No. of bitstreams: 1 GALLOTTA_30_06_14.pdf: 62695484 bytes, checksum: 33335ee3affc2bcffb11fc10caf9ae3f (MD5) / Universidade Federal Fluminense. Instituto de Química. Programa de Pós-Graduação em Geociências-Geoquímica. Niterói, RJ / Os hidrocarbonetos presentes no ambiente consistem em misturas complexas de compostos derivados de múltiplas fontes. Os combustíveis fósseis representam a principal contribuição, devido à taxa e escala espacial, em que o petróleo tem sido usado como fonte de energia e matéria-prima para a indústria química. O objetivo deste estudo foi avaliar os níveis de concentração e identificar fontes de hidrocarbonetos na Bacia do Alto Iguaçu e, em especial, na área de influência da Refinaria Presidente Getúlio Vargas (REPAR). Além dos fatores de poluição crônica, a área de estudo foi alvo de um derrame acidental de petróleo em julho de 2000. Diversos indicadores em diferentes compartimentos ambientais (água superficial, sedimento, solo e água subterrânea) foram avaliados na fase pós-derrame e no monitoramento ambiental ao longo de várias campanhas por mais de uma década. Os esforços de avaliação foram concentrados nos seguintes indicadores: os nalcanos, os alcanos isoprenoides, os hidrocarbonetos policíclicos aromáticos (HPA), os biomarcadores de petróleo e ainda o total de hidrocarbonetos de petróleo (THP). Os resultados identificaram como principal aporte de matéria orgânica para as águas superficiais dos rios Barigüi e Iguaçu, os fluxos materiais originados em região a montante do acidente, refletindo a contribuição antropogênica crônica da cidade de Curitiba. Em 2007 e 2008, as concentrações de THP e HPA nas águas superficiais e sedimentos dos rios Barigüi e Iguaçu refletem uma expressiva melhoria nas condições desses rios em relação a 2000. Na área interna da refinaria (Ponto Zero), observou-se uma nítida diminuição (atenuação) natural das concentrações de THP no solo em todas as profundidades dos perfis amostrados ao longo do tempo nos Banhados 1 e 4 e, em particular, uma diminuição importante das concentrações entre 2004 e 2007. Para a identificação das fontes de hidrocarbonetos foram utilizadas razões diagnósticas e quimiometria. As razões diagnósticas calculadas a partir de concentrações de HPA sugeriram que, na maioria dos sedimentos dos Rios Barigüi e Iguaçu coletados nas campanhas de 2000 e 2001, a fonte petrogênica é a principal. Somente na estação a montante do acidente no Rio Barigüi, a fonte pirolítica predominou nestas duas campanhas. As razões diagnósticas que apresentaram maior eficiência na identificação de fontes de hidrocarbonetos nos sedimentos dos rios Barigüi e Iguaçu foram: ΣC1-Fenantrenos/Fenantreno; e (ΣHPA parentais de 3-6 anéis)/(Σ5 séries de HPA alquilados). A identificação de fontes através de razões diagnósticas calculadas a partir de áreas e alturas de picos cromatográficos demonstrou sua aplicabilidade verificando a relação entre os compostos encontrados em amostras de solo da área interna da refinaria com a amostra de petróleo derramado no acidente, após quase uma década da ocorrência do vazamento. A identificação de fontes através método de quimiométrico baseado na análise de componentes principais (ACP) de seções pré-processadas e combinadas dos Cromatogramas de Íons Selecionados (CIS) mostrou que as amostras mais contaminadas estão na área interna da refinaria. Essas amostras apresentam um padrão de distribuição petrogênica e diferentes graus de intemperismo. As amostras da área externa à refinaria (Guajuvira, General Lúcio e Balsa Nova) são menos ou não contaminadas e/ou contém uma mistura de contribuições diagenéticas, pirolíticas e petrogênicas onde predominam diferentes proporções. Os locais mais distantes da atividade industrial (Balsa Nova) contem, como esperado, os níveis mais baixos de contaminação por HPA. Os resultados de biomarcadores demonstraram que não há evidências para concluir que as amostras da área externa à refinaria e o óleo Cusiana vazado tenham a mesma origem. Os resultados ao longo dos rios Barigüi e Iguaçu e do Ponto Zero demonstraram que as ações de emergência para a contenção do óleo foram adequadas para os rios, e que a contaminação decorrente do derrame ficou predominantemente contida no Ponto Zero e diminuiu significativamente após uma década. / Hydrocarbons present in the environment consist of complex mixtures of compounds derived from multiple sources. The main contribution lies on fossil fuel inputs due to the rate and spatial scale by which petroleum has been used as an energy source and chemical feedstock. The aim of this study was to assess the concentration levels and identify sources of hydrocarbons in the Upper Iguaçu Watershed and, in particular, in the area of influence of the President Getulio Vargas Refinery (REPAR). In addition to the factors of chronic pollution, the study area was the scenario of an acute accidental oil spill in July 2000. Numerous indicators in different environmental compartments (surface water, sediment, soil and groundwater) were assessed in the post spill phase and during the environmental monitoring programs over the course of several campaigns for more than a decade. Assessment efforts were concentrated on the following indicators: n-alkanes, alkanes isoprenoids, polycyclic aromatic hydrocarbons (PAH), petroleum biomarkers and total petroleum hydrocarbons (TPH). The results identified as the main contribution of organic matter to surface waters of the Barigüi and Iguaçu Rivers the materials flows originated in the region upstream of the accident, reflecting chronic anthropogenic contribution of the city of Curitiba. In 2007 and 2008, the TPH and PAH concentrations in surface waters and sediments of the Barigüi and Iguaçu Rivers revealed a significant improvement in the conditions of these rivers when compared with 2000. Inside the refinery area (Point Zero), it was observed a clear natural decrease (attenuation) of the concentrations of TPH in the soil at all depths sampled over time in Marshes 1 and 4 and, in particular, an important decrease of concentrations between 2004 and 2007. Diagnostic ratios and chemometrics were used to identity hydrocarbon sources. The diagnostic ratios calculated from the concentrations of PAH suggested that, in the majority of sediments from the Barigüi and Iguaçu Rivers collected in 2000 and 2001 campaigns, the main source is petrogenic. Only in the station upstream the accident in the Barigüi River, the pyrolytic source predominated in these two campaigns. The diagnostic ratios that presented higher efficiency in identifying sources of hydrocarbons in sediments of the Barigüi and Iguaçu Rivers were: ΣC1- Phenantrenes/Phenanthrene; and (Σ3-6 rings parental PAH)/(Σ5 alkylated PAH series). The source identification through diagnostic ratios calculated from heights and areas of chromatographic peaks demonstrated its applicability establishing a relationship between the compounds found in soil samples of the internal area of the refinery and the sample of the oil spilled in the accident, after nearly a decade of occurrence of the spillage. The source identification through chemometric method based on principal components analysis (PCA) of preprocessed and combined sections of Selected Ion Chromatograms (SIC) showed that the most contaminated samples are inside the refinery area. These samples present a petrogenic pattern and different weathering degrees. Samples from outside the refinery area (Guajuvira, General Lúcio e Balsa Nova) are either less or not contaminated, and/or contain mixtures of diagenetic, pyrogenic and petrogenic inputs where different proportions predominate. The locations farthest away from industrial activity (Balsa Nova) contain, as expected, the lowest levels of PAH contamination. The biomarkers results do not show any evidences to conclude positive matches between the samples from outside the refinery area and the spilled Cusiana oil. The results along Barigüi and Iguaçu rivers and Point Zero demonstrated that emergency actions to contain the oil were appropriate for the rivers, and that the contamination resulting from the spill was mostly contained in the Point Zero and decreased significantly after one decade

Anthropogenic emissions into the troposphere can impact air quality, leading to poorer health outcomes in the affected areas. Volatile organic compounds (VOCs) are a group of chemical compounds, including some which are toxic, that are precursors in the formation of ground-level ozone and secondary organic aerosols. VOCs have a variety of sources, and the distribution of atmospheric VOCs differs significantly over time and space. Historically, the large number of chemical species present at low concentrations (parts-per-trillion to parts-per-billion by volume) have made VOCs difficult to measure in ambient air. However, with improvements in analytical instrumentation, these measurements are becoming more common place. Direct mass spectrometry (MS), such as membrane introduction mass spectrometry (MIMS) and proton-transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) facilitate real-time, continuous measurements of VOCs in air, with full scan mass spectral data capturing changes in chemical composition with high temporal resolution. Operated on-road, mobilized direct MS has been used for quantitative mapping of VOCs at the neighborhood scale, but identifying VOC sources based on the observed mixture of molecules in the full scan MS dataset has yet to be explored. This dissertation describes the use of chemometric techniques to interrogate full scan MS data, and the progression from discriminating VOC samples of known chemical composition based on full scan MIMS data through to the apportionment of VOC sources measured continuously with a PTR-ToF-MS system operating in a moving vehicle. Lab‐constructed VOC samples of known chemical composition and concentration demonstrated the use of principal component analysis (PCA) to discriminate, and k-nearest neighbours to classify, samples based on normalized full scan MIMS data. Furthermore, multivariate curve resolution-alternating least squares (MCR-ALS) was used to resolve mixtures into molecular component contributions. PCA was also used to discriminate ‘real-world’ VOC mixtures (e.g., woodsmoke VOCs, headspace above aqueous hydrocarbon samples) of unknown chemical composition measured by MIMS. Using vehicle mounted MIMS and PTR-ToF-MS systems, full scan MS data of ambient atmospheric VOCs were collected and PCA was applied to the normalized full scan MS data. A supervised analysis performed PCA on samples collected near known VOC sources, while an unsupervised analysis using PCA followed by cluster analysis was used to identify groups in a continuous, time series PTR-ToF-MS dataset measured between Nanaimo and Crofton, British Columbia (BC). In both the supervised and unsupervised analysis, samples impacted by emissions from different sources (e.g., internal combustion engines, sawmills, composting facilities, pulp mills) were discriminated. With PCA, samples were discriminated based on differences in the observed full scan MS data, however real-world samples are often impacted by multiple VOC sources. MCR-weighted ALS (MCR-WALS) was applied to the continuous, time series PTR-ToF-MS data from three field campaigns on Vancouver Island, BC for source apportionment. Variable selection based on signal-to-noise ratios was used to reduce the mass list while retaining the observed m/z that capture changes in the mixture of VOCs measured, improving model results, and reducing computation time. Both point (e.g., anthropogenic hydrocarbon emissions, pulp mill emissions) and diffuse (e.g., VOCs from forest fire smoke) VOC sources were identified in the data, and were apportioned to determine their contributions to the measured samples. The data analyzed captured fine scale changes in the ambient VOCs present in the air, and geospatial maps of each individual source, and of the source apportionment were used to visualize the distribution of VOC sources across the sampling area. This work represents the first use of MCR-WALS to identify and apportion ambient VOC sources based on continuous PTR-ToF-MS data measured from a moving vehicle. The methods described can be applied to larger scale field campaigns for the source apportionment of VOCs across multiple days to capture diurnal and seasonal variations. Identifying spatial and temporal trends in the sources of VOCs at the regional scale can help to identify pollution ‘hot spots’ and inform evidence-based public policy for improving air quality. / Graduate / 2022-08-17