The main goal of this thesis was to study plasma generated by surface discharge and its application in volatile organic compound destruction. Introduction of this thesis deals with the issue of volatile organic compound. The term of volatile organic compound was defined and explained. Summary of the most important sources of volatile organic compound emissions and possible technics for their elimination was presented. This thesis drew attention on negative aspects of volatile organic compounds on human organism and on the whole environment. The problems of surface discharge and its possible application in various branches are known only few years therefore construction of plasma reactor itself was the first independent step of this work. The plasma reactor was consisted of electrode, which was created from the series of metal stripes each other separated by dielectric barrier. On the surface of the electrode, discharge was regulated and distributed. For the reason of technical limits experiment time was limited up to one minute. The experimental part describes reactor for surface discharge and other parts of apparatus in which degradation volatile organic compound was carried out. Nitrogen was used as carrier gas and it was mixed with air before entering into the reactor. Samples of compounds after degradation process were taken from reactor for the subsequent analysis. Analysis of the products proceeded in a gas chromatogram linked to mass spectrometer. The decomposition products were adsorbed in the SPME filaments or in sorption tubes. The decomposition products were analysed also through the mean of Testo 350 M/XL. This apparatus provided the information on the concentration of small molecules such as CO, H2, NO, NO2 and CxHy Hexane, cyclohexane and xylene were used as VOC examples. Analysis of GC-MS showed decomposition products of hexane, cyclohexane and xylene. The decomposition products were especially various alcohols, ketones, aldehydes and benzene compounds. The apparatus Testo 350 M/XL was unable to detect any CxHy, only large quantity of NO2. This thesis was further focused on possible factors which could have an influence on degradation of compounds, for example input power or different flow of oxygen. It was found that increasing power declined the removal efficiency. The maximum removal efficiency was 87 % for degradation of hexane at the lowest input power. Next part of this thesis was focused on diagnostics of plasma generated in the surface discharge form. The optical emission spectroscopy has been chosen as the best method for plasma characterisation. By this method, various important discharge parameters can be determined, e.g. vibration and rotation temperature. The obtained numeric value of rotation temperature was 840±80 K and vibration temperature was 1880±140 K. The obtained results may be used as a fundament for further study of VOC decomposition in surface discharge.

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Black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) are two atmospheric pollutants produced by motor vehicles using carbonaceous fuels. As a part of the Mexico City Project, measurements of BC, PPAHs and many other gas- and particle-phase emissions were measured in Mexico City using a mobile laboratory during the Mexico City Metropolitan Area field campaign in April 2003 (MCMA-2003). The main goal of this research is to estimate emissions of BC and particulate PAHs (PPAHs) for Mexico City's vehicle fleet. The emissions of gas-phase pollutants such as carbon monoxide (CO), total nitrogen oxides (NOy) and volatile organic compounds (VOC) are also estimated. The mobile lab has previously been used to chase vehicles and measure their emissions, but analysis has traditionally focused on determining emission factors of individual vehicles associated with specific chasing events. The laboratory continuously samples ambient air from an inlet at the front of the van, and it is always "seeing" exhaust plumes from the vehicles around it while driving through traffic. We have developed an algorithm that automatically identifies the exhaust plume measurement points, which are then used as the basis for calculation of emission factors. In the nearly 90 hours of on-road sampling during the field campaign, we have identified ~30,000 exhaust measurement points. The large sample size enables us to estimate fleet-average emission factors and thus the emission inventory. Motor vehicles are estimated to emit annually 1,960 tons of BC, 56.2 tons of PPAHs, 1,320,000 tons of CO, 125,000 tons of NOy and 2440 tons of VOCs. The spatial and temporal patterns of BC and PPAHs in different locations with in MCMA are also studied. / Master of Science

This thesis describes the investigation of three aspects of the formation of secondary organic aerosol (SOA): * Aerosol formation from mixed precursors * Global modelling of SOA formation * Modelling of dynamics of SOA formation based on empirical data collected from smog chamber experiments. The formation and growth processes of secondary organic aerosol were investigated using smog chamber experimentation and modelling techniques to gain a better understanding of the application of SOA yield values in modelling both SOA mass and dynamics. Published SOA yields from a range of volatile organic compounds (VOCs) are used to model SOA mass on a local, regional or global scale, based on the assumption that the SOA yield of a mixture is the sum of the yields of the components. Experimental investigations into SOA yield from mixtures of VOC revealed potential uncertainties that would result from applying these yields to systems containing multiple VOCs. SOA formation in systems of toluene or m-xylene, compared with systems of these VOCs and propene, have shown that the introduction of propene (which has a zero SOA yield) to smog chamber photo-oxidations of toluene or m-xylene delays the formation and suppresses the overall yield of SOA from 450 to 90 µg m-3 ppm-1 for the toluene system and from 325 to 125 µg m-3 ppm-1 for the mvxylene system compared with systems of individual species without propene. The SOA partitioning yield data also indicates that partitioning of species to existing aerosol is suppressed in the mixed systems. Gas-phase modelling of these experiments showed that potential SOA species were expected to be formed sooner due to the increased system reactivity provided by propene. The observed delay in SOA nucleation, similar consumption rates of toluene and m-xylene in both the single and mixed systems and the gas-phase modelling results suggest that the addition of propene to hydrocarbon SOA systems modifies the gas-phase chemistry leading to the formation of potential SOA species from toluene and m-xylene. This result calls into question the bulk and partitioning yield values that have been published for pure substances as well as the validity of applying individual VOC yields to VOC mixture. Application of SOA yields to the global scale provides estimates of annual global SOA formation, global contributions from various VOCs and regional SOA distributions. Two SOA modules, using bulk and partitioning yield methods, were added to a global atmospheric chemical transport model, MOZART-2. The bulk yield method, representing the maximum possible global SOA burden, gave an annual production of 24.5 Tg of SOA, which is slightly lower than previous estimates (30 - 270 Tg yr-1). The partitioning method, which gives a more realistic estimate of SOA formation, produced 15.3 Tg yr-1; the biogenic fraction (13.6 Tg yr-1) compares to a previous estimate of biogenic SOA of 18.5 Tg yr-1 and 2.5 to 44 Tg yr- 1 using the partitioning method. Anthropogenic SOA contributions of 1.1 Tg yr-1 from MOZART-2 compared to recent estimates of 0.05 -2.62 Tg yr-1. SOA production was found to be dependent on oxidant availability and VOC emissions in South America and Asia. The partitioning method produced significantly less SOA due to limited availability of OC. Thepartitioning method also produced a peak SOA concentration of 10 µg m-3 over South America in September and showed that SOA is at maximum production for most of the year in Asia and Europe. The two SOA formation methods also provides data to analyse the restrictions to SOA formation in particular regions, based on the maximum amount of SOA able to form (bulk yield method) and the more realistic partitioning estimate from the same region. Limitations to SOA formation in a particular region can be attributed to deficiencies in OC availability or VOC oxidant concentrations. Comparisons to limited observational and modelled data suggest that the MOZART-2 SOA model provides a good representation of global averaged SOA. SOA mass concentrations, predicted by models such as MOZART-2, can be used in part to model the dynamics of an SOA population (e.g. size of particles, number concentrations etc.). Aerosol properties such as size and number concentration can then be used to estimate their effect on climate and health. The explicit representation of the processes that affect aerosol dynamics, such as nucleation, condensation, evaporation and coagulation can be complex and use significant computational resources. Simplification of the discrete coagulation equation and empirical coagulation coefficients for continuum and non-continuum regime diffusion kinetics provided a simplified method of coagulation capable of predicting the evolution of inert sodium chloride aerosol in chamber experiments. A variable coagulation coefficient (linked to the mean particle number concentration of each experiment) was developed. This method is an empirical surrogate for the standard coefficient corrections applied to Brownian based diffusion in the continuum regime to account for the different kinetic effects within the transition and free molecular diffusion regimes. This method removes the need for calculating individual coefficients for each particle interaction. Estimates of modeluncertainty show that within uncertainty limits the model provides a good representation of experimental data. Correlation and index of agreement (IOA) calculations revealed good statistical agreement between modelled and experimental. Some experiments showed degrees of coagulation under prediction using the variable coefficient technique. Investigations into the effect of aerosol type and size, temperature and humidity may be necessary to refine the variable coefficient calculation technique. The model showed little sensitivity to model time step and is capable of high resolution representation of the aerosol. Mass concentration is conserved within the model whereas some error due to numerical diffusion within the number concentrations results from the bin sectioning technique used. The simplicity of this sectioning method over other methods and the minimal effect of numerical diffusion establishes a simplified method of modelling relative to the high resolution of the aerosol distribution the model achieves. It is suggested that the efficiency improvements introduced by the approaches used in developing this model provide an efficient ultra-fine coagulation modelling for atmospheric models. A semi-empirical model for SOA dynamics (SPLAT) incorporating coagulation, nucleation, condensation and evaporation was developed. The aim of the model and the development process was to predict, with high resolution and minimal computational expense, the formation and growth of SOA given a SOA mass input as a function of time. The average size distribution profile from chamber experimental data was used as part of the nucleation module. This technique provided an alternative method of representing the particle distribution compared to those models that assume a single diameter of nucleated particle or a fixed log-normal mode for the entire evolution of SOA. All SPLAT simulations assume organic nucleation events within the experiments modelled, although it is stilluncertain whether they occur in the atmosphere. The modelled nucleation events have produced a single nucleation burst, a result of immediate domination of condensation as soon as nucleation occurs. This deficiency is likely to be a result of the assumption of free molecular diffusion for condensation. The rate of condensation, calculated at every time step, is based on the aerosol size distributed surface area and the particle-size-dependent saturation mass concentrations. The SPLAT coagulation module was a version of the model developed in Chapter 6. Comparisons between experimental and modelled data showed good agreement. These comparisons revealed the shortcomings in the nucleation module while a statistical analysis of the modelled and experimental data has shown SPLAT to be effective in modelling a range of SOA systems. The complexity introduced in modelling aerosol dynamics in high resolution is offset in SPLAT by efficiency improvements due to the insensitivity of the model to time step size and simplified methods of bin sectioning, nucleation, coagulation, condensation and evaporation. Published SOA yields can be applied to predict SOA mass at local, regional or global scales. Although previously unreported uncertainties in these yields have been shown to exist, the MOZART-2 global chemical transport model has shown that SOA mass concentration can be predicted with reasonable quality, considering the scale of the model and limited observational data. These global scale SOA mass predictions can be used purely for global burden and occurrence, or as the input for modelling the dynamics of an aerosol population, which is significant for estimating an aerosol population's effect on climate change and health. SOA mass concentrations from chamber experiments were used as input to a SOA dynamics model. This model (SPLAT) then predicted the evolution of particle number concentrations and size within these experiments based on this mass input. Application of the dynamics model to the output of the MOZART-2 model could then provide a comprehensive global scale SOA modelling package.

In this research, a proton exchange membrane fuel cell (PEMFC) sensor was investigated for specific detection of volatile organic compounds (VOCs) for point-of-care (POC) diagnosis of the physiological conditions of humans. A PEMFC is an electrochemical transducer that converts chemical energy into electrical energy. A Redox reaction takes place at its electrodes whereas the volatile biomolecules (e.g. ethanol) are oxidized at the anode and ambient oxygen is reduced at the cathode. The compounds which were the focus of this investigation were ethanol (C2H5OH) and isoflurane (C3H2ClF5O), but theoretically, the sensor is not limited to only those VOCs given proper calibration. Detection in biosensing, which needs to be carried out in a controlled system, becomes complex in a multivariate environment. Major limitations of all types of biosensors would include poor selectivity, drifting, overlapping, and degradation of signals. Specific detection of VOCs in multi-dimensional environments is also a challenge in fuel cell sensing. Humidity, temperature, and the presence of other analytes interfere with the functionality of the fuel cell and provide false readings. Hence, accurate and precise quantification of VOC(s) and calibration are the major challenges when using PEMFC biosensor. To resolve this problem, a statistical model was derived for the calibration of PEMFC employing multivariate analysis, such as the “Principal Component Regression (PCR)” method for the sensing of VOC(s). PCR can correlate larger data sets and provides an accurate fitting between a known and an unknown data set. PCR improves calibration for multivariate conditions as compared to the overlapping signals obtained when using linear (univariate) regression models. Results show that this biosensor investigated has a 75% accuracy improvement over the commercial alcohol breathalyzer used in this study when detecting ethanol. When detecting isoflurane, this sensor has an average deviation in the steady-state response of ~14.29% from the gold-standard infrared spectroscopy system used in hospital operating theaters. The significance of this research lies in its versatility in dealing with the existing challenge of the accuracy and precision of the calibration of the PEMFC sensor. Also, this research may improve the diagnosis of several diseases through the detection of concerned biomarkers.