An Evaluation of Carbon Concentrations Associted with Biodiesel Particulate Matter in an Underground Metal Mine

Exposure to diesel particulate matter from diesel exhaust has been shown to have adverse health effects in humans. In 2012 The International Agency for Research on Cancer classified diesel exhaust as a group 1 know human carcinogen. Because of the associated health effects, there has been a strong push to reduce the amount of diesel exhaust present in the mining industry. Biodiesel is one to the more common and promising control options used to reduce the amount of diesel particulate matter that is generated during fuel combustion. The use of biodiesel over petroleum diesel has been shown to reduce not only particulate matter, but hydro carbon and carbon monoxide mass emissions as well. Personal and area samples were collected at an underground metal mine in the northwestern United States to evaluate the current blend of B70 biodiesel. The objective of this research was to evaluate the carbon levels associated with diesel particulate matter generated from the combustion of a B70 biodiesel. Data was also compared to past studies on which diesel particulate matter from petroleum diesel was evaluated. Samples were taken on four separate four day campaigns between March and October of 2014. Area samples were taken from 7 different areas in the mine and personal samples were taken from a 20 person cohort. The equipment used for sampling was compliant with the NIOSH 5040 method. Statistical analysis of the results was done using Minitab 17 software. The statistical analysis showed that the total carbon concentrations from biodiesel were well below the MSHA exposure limit. Results also showed that organic/elemental carbon ratios were consistent with past studies as the concentrations of organic carbon were significantly higher than those of elemental carbon.

Modern Computational Chemistry Methods for Prediction of Ground- and Excited-State Properties in Open-Shell Systems

The main goal of the research presented in this work is to provide some important insights about computational modeling of open-shell species. Such projects are: the investigation of the size-extensivity error in Equation-of-Motion Coupled Cluster methods, the analysis of the Long-Range corrected scheme in predicting UV-Vis spectra of Cu(II) complexes with the 4-imidazole acetate and its ethylated derivative, and the exploration of the importance of choosing a proper basis set for the description of systems such as the lithium monoxide anion. The most significant findings of this research are: (i) The contribution of the left operator to the size-extensivity error of the CR-EOMCC(2,3) approach, (ii) The cause of d-d shifts when varying the range-separation parameter and the amount of the exact exchange arising from the imbalanced treatment of localized vs. delocalized orbitals via the "tuned" CAM-B3LYP* functional, (iii) The proper acidity trend of the first-row hydrides and their lithiated analogs that may be reversed if the basis sets are not correctly selected.

MODELING AND EXPERIMENTAL SETUP OF AN HCCI ENGINE

For the past three decades the automotive industry is facing two main conflicting challenges to improve fuel economy and meet emissions standards. This has driven the engineers and researchers around the world to develop engines and powertrain which can meet these two daunting challenges. Focusing on the internal combustion engines there are very few options to enhance their performance beyond the current standards without increasing the price considerably. The Homogeneous Charge Compression Ignition (HCCI) engine technology is one of the combustion techniques which has the potential to partially meet the current critical challenges including CAFE standards and stringent EPA emissions standards. HCCI works on very lean mixtures compared to current SI engines, resulting in very low combustion temperatures and ultra-low NOx emissions. These engines when controlled accurately result in ultra-low soot formation. On the other hand HCCI engines face a problem of high unburnt hydrocarbon and carbon monoxide emissions. This technology also faces acute combustion controls problem, which if not dealt properly with yields highly unfavorable operating conditions and exhaust emissions. This thesis contains two main parts. One part deals in developing an HCCI experimental setup and the other focusses on developing a grey box modelling technique to control HCCI exhaust gas emissions. The experimental part gives the complete details on modification made on the stock engine to run in HCCI mode. This part also comprises details and specifications of all the sensors, actuators and other auxiliary parts attached to the conventional SI engine in order to run and monitor the engine in SI mode and future SI-HCCI mode switching studies. In the latter part around 600 data points from two different HCCI setups for two different engines are studied. A grey-box model for emission prediction is developed. The grey box model is trained with the use of 75% data and the remaining data is used for validation purpose. An average of 70% increase in accuracy for predicting engine performance is found while using the grey-box over an empirical (black box) model during this study. The grey-box model provides a solution for the difficulty faced for real time control of an HCCI engine. The grey-box model in this thesis is the first study in literature to develop a control oriented model for predicting HCCI engine emissions for control.

Mechanisms of Chloroperoxidase-catalyzed Enantioselective Reactions as Probed by Site-directed Mutagenesis and Isotopic Labeling

Chloroperoxidase (CPO) is a heme-containing glycoprotein secreted by the marine fungus Caldariomyces fumago. Chloroperoxidase contains one ferriprotoporphyrin IX prosthetic group per molecule and catalyzes a variety of reactions, such as halogenation, peroxidation and epoxidation. The versatile catalytic activities of CPO coupled with the increasing demands for chiral synthesis have attracted an escalating interest in understanding the mechanistic and structural properties of this enzyme. In order to better understand the mechanisms of CPO-catalyzed enantioselective reactions and to fine-tune the catalytic properties of chloroperoxidase, asparagine 74 (N74) located in the narrow substrate access channel of CPO was replaced by a bulky, nonpolar valine and a polar glutamine using site-directed mutagenesis. The CPO N74 mutants displayed significantly enhanced activity toward nonpolar substrates compared to wild-type CPO as a result of changes in space and polarity of the heme distal environment. More interestingly, N74 mutants showed dramatically decreased chlorination and catalase activity but significantly enhanced epoxidation activity as a consequence of improved kinetic perfection introduced by the mutation as reflected by the favorable changes in kcat and kcat/KM of these reactions. It is also noted that the N74V mutant is capable of decomposing cyanide, the most notorious poison for many hemoproteins, as judged by the unique binding behavior of N74V with potassium cyanide. Histidine 105 (H105) was replaced by a nonpolar amino acid alanine using site-directed mutagenesis. The CPO H105 mutant (H105A) displayed dramatically decreased chlorination and catalase activity possibly because of the decreased polarity in the heme distal environment and loss of the hydrogen bonds between histidine 105 and glutamic acid 183. However, significantly increased enantioselectivity was observed for the epoxidation of bulky styrene derivatives. Furthermore, my study provides strong evidence for the proposed histidine/cysteine ligand switch in chloroperoxidase, providing experimental support for the structure of the 420-nm absorption maximum for a number of carbon monoxide complexes of heme-thiolate proteins. For the NMR study, [dCPO(heme)] was produced using 90% deuterated growth medium with excess heme precursors and [dCPO(Phe)] was grown in the same highly deuterated medium that had been supplemented with excess natural phenylalanine. To make complete heme proton assignments, NMR spectroscopy has been performed for high-resolution structural characterization of [dCPO(heme)] and [dCPO(Phe)] to achieve unambiguous and complete heme proton assignments, which also allows important amino acids close to the heme active center to be determined.

Suicide among young people and adults in Ireland: method characteristics, toxicological analysis and substance abuse histories compared

Objective: Information on factors associated with suicide among young individuals in Ireland is limited. The aim of this study was to identify socio-demographic characteristics and circumstances of death associated with age among individuals who died by suicide. Methods: The study examined 121 consecutive suicides (2007–2012) occurring in the southern eastern part of Ireland (Cork city and county). Data were obtained from coroners, family informants, and health care professionals. A comparison was made between 15-24-year-old and 25-34-year-old individuals. Socio-demographic characteristics of the deceased, methods of suicide, history of alcohol and drug abuse, and findings from toxicological analysis of blood and urine samples taken at post mortem were included. Pearson’s χ2 tests and binary logistic regression analysis were performed. Results: Alcohol and/or drugs were detected through toxicological analysis for the majority of the total sample (79.5%), which did not differentiate between 15-24-year-old and 25-34-year-old individuals (74.1% and 86.2% respectively). Compared to 25-34-year-old individuals, 15-24-year-old individuals were more likely to engage in suicide by hanging (88.5%). Younger individuals were less likely to die by intentional drug overdose and carbon monoxide poisoning compared to older individuals. Younger individuals who died between Saturday and Monday were more likely to have had alcohol before dying. Substance abuse histories were similar in the two age groups. Conclusion: Based on this research it is recommended that strategies to reduce substance abuse be applied among 25-34-year-old individuals at risk of suicide. The wide use of hanging in young people should be taken into consideration for future means restriction strategies.

Mt. Bachelor Observatory 2015 data

The Mt. Bachelor Observatory (MBO) is a high altitude atmospheric research station that is located at the Mt. Bachelor ski area in Central Oregon. The observatory was started by Prof. Dan Jaffe in 2004. Over this time, his time at UW has made observations of ozone, carbon monoxide, mercury, nitrogen oxides, particulate matter and other atmospheric constituents. The data for 2015 are reported in this dataset. MBO coordinates (summit building): Latitude: 43.9775 N Longitude: 121.6861 W Elevation: 2.74 km asl

Caracterización paraclínica de trabajadores con patologías respiratorias de un centro de referencia neumológico, Bucaramanga, 2014-2016

Introducción: La enfermedad respiratoria ocupacional es causada por la exposición a diferentes agentes en el trabajo. Las pruebas objetivas realizadas en sospecha de enfermedad respiratoria de origen laboral, son importantes herramientas que permiten realizar un adecuado diagnóstico, una detección precoz de la enfermedad respiratoria ocupacional, disminuye el progreso rápido de la patología, la morbilidad de los trabajadores y el impacto negativo sobre su futuro laboral. Objetivo: Caracterizar las pruebas paraclínicas de las patologías respiratorias de trabajadores, en un centro de referencia neumológico de Bucaramanga año 2014-2016. Materiales y métodos: Se realizó un estudio descriptivo retrospectivo con datos secundarios de 96 trabajadores que laboran en diferentes actividades económicas. Se incluyeron variables sociodemográficas, laborales, ayudas imagenológicas y pruebas de función pulmonar, realizando 3 grupos de acuerdo a su patología que fueron: Asma, síndrome de disfunción reactiva de la vía aérea y neumoconiosis. En el análisis estadístico se emplearon medidas de tendencia central y dispersión. Resultados: De los 96 trabajadores 84.4% son hombres, las actividades económicas más frecuentes fueron la industria del petróleo y gas en un 27.1% y trabajadores en materiales de construcción en un 19.8%. En la caracterización paraclínica por grupo de patología, para asma predominó la obstrucción en la espirometría (46.9%) y los volúmenes pulmonares con atrapamiento aéreo (95.5%), en RADS (síndrome de disfunción de vías aéreas reactivas) los volúmenes pulmonares con atrapamiento aéreo (77%) y en las neumoconiosis para Rx de tórax (90.3%) y Tac de tórax (100%) reportaron alteraciones parenquimatosas, espirometría con obstrucción (54.8%) y volúmenes pulmonares con atrapamiento aéreo (62.5 %).Discusión y Conclusiones: Las ocupaciones de mayor riesgo para desarrollo de neumopatías de origen ocupacional fuero, , son la minería y construcción y para asma la agricultura y manufacturas. Para asma se evidenció que no hay significancia diagnóstica para estudios imagenológicos pero sí para las pruebas de función pulmonar. Para neumoconiosis el estudio imagenológico es el de mayor importancia ya que en las radiografías se presentan cambios incluso mucho antes de la afectación de la función pulmonar. Para RADS se concluyó que la realización de un test de provocación con metacolina sería el Gold estándar para el diagnóstico. Las pruebas de función respiratoria son de vital importancia para determinar la enfermedad ocupacional en trabajadores expuestos para vigilancia y detección precoz, es conveniente la realización de protocolos para la evaluación y diagnóstico de la enfermedad respiratoria de origen ocupacional. Palabras claves: Neumoconiosis, asma ocupacional, función pulmonar, radiografía de tórax, ocupación, Colombia.

ICE Emissions Estimation through Machine-learning techniques to support real-world R&D experiments

The emissions estimation, both during homologation and standard driving, is one of the new challenges that automotive industries have to face. The new European and American regulation will allow a lower and lower quantity of Carbon Monoxide emission and will require that all the vehicles have to be able to monitor their own pollutants production. Since numerical models are too computationally expensive and approximated, new solutions based on Machine Learning are replacing standard techniques. In this project we considered a real V12 Internal Combustion Engine to propose a novel approach pushing Random Forests to generate meaningful prediction also in extreme cases (extrapolation, very high frequency peaks, noisy instrumentation etc.). The present work proposes also a data preprocessing pipeline for strongly unbalanced datasets and a reinterpretation of the regression problem as a classification problem in a logarithmic quantized domain. Results have been evaluated for two different models representing a pure interpolation scenario (more standard) and an extrapolation scenario, to test the out of bounds robustness of the model. The employed metrics take into account different aspects which can affect the homologation procedure, so the final analysis will focus on combining all the specific performances together to obtain the overall conclusions.