Atmospheric aerosol particles play an important role in global climate change, via direct and indirect radiative forcing. Elemental carbon (EC) and nitrate are important contributors to anthropogenic aerosol radiative forcing over Europe, since they strongly absorb and/or scatter solar radiation, respectively. However, the evaluation of their climate effects remains highly uncertain. Improvements on the simulation of particle number/mass size distribution (PSD) in modelling will help us to refine model assessments of climate change. The simulations were performed over Europe with a fully online-coupled regional air quality model (WRF-Chem) for the time period of September 10-20th, 2013. Measurements in the HOPE-Melpitz campaign and other datasets in Europe were adopted to evaluate the model uncertainties. The meteorological conditions were well reproduced by the simulations. However, a remarkable overestimation of coarse mode PSD was found in the simulations. The overestimation was mainly contributed by EC, sodium nitrate and sea salt (SSA), stemming from the inadequate emission of EC and SSA. The EC inventory overestimates EC point sources in Germany and the fractions of coarse mode EC emissions in Eastern Europe and Russia. Allocating too much EC emission into the coarse mode could shorten EC lifetime and reduce its long-range transport, thus partly (~20-40%) explaining the underestimation of EC in Germany, when air masses came from eastern direction in previous studies. Furthermore, WRF-Chem overestimated coarse mode SSA mass concentrations by factors of about 8-20 over northwestern and central Europe in this study, due to the shortcoming of its emission scheme. This could facilitate the coarse mode sodium nitrate formation and lead to ~140% overestimation of coarse mode nitrate. Under such circumstances, nitric acid was exhausted, and fine mode ammonium nitrate formation was inhibited. The overestimated SSA shaped the PSD of nitrate towards larger sizes, which might influence the optical properties, lifetime and climate effect of nitrate accordingly. A transport mechanism would broaden the influence of SSA on nitrate PSD to central Europe, where a considerable amount of nitrate precursors and ammonium nitrate is present.:Table of Contents List of Figures List of Tables Abbreviations 1. Introduction 1.1 Particle size distribution 1.2 Elemental carbon particle size distribution simulation 1.3 Chemical pathways for particulate nitrate 1.4 Influence of sea salt on nitrate particle mass size distribution 1.5 Objectives 2. Methodology 2.1. WRF-Chem model 2.1.1. General description 2.1.2. Model configuration 2.1.3 Anthropogenic source emissions 2.1.4 Natural source emissions 2.2 HOPE-Melpitz campaign 2.3 GUAN network over Germany 2.4 Other datasets 3. Results and Discussion 3.1 First publication 3.1.1 Evaluation of the size segregation of elemental carbon (EC) emission in Europe: influence on the simulation of EC long-range transportation 3.1.2 Supporting information 3.2 Second publication 3.2.1 Sea salt emission, transport and influence on size-segregated nitrate simulation: a case study in northwestern Europe by WRF-Chem 3.2.2 Supporting information 4. Summary and Conclusions 5. Outlook Appendix A Bibliography Acknowledgements

Air pollution is the main environmental health issues that affects all the regions and causes millions premature deaths every year. In order to take any preventive measures, we need the ability to predict pollution level and air quality. This task is conventionally solved using deterministic models. However, those models fail to capture complex non-linear dependencies in erratic data. Lately machine learning models gained popularity as a very promising alternative to deterministic models. The purpose of this thesis is to conduct a comparative study between ChemicalTransport Model (WRF-Chem) and a Statistical Model built from machine learning algorithms in order to understand which one is advantageous predicting the air quality and the meteorological conditions using data from Cuenca, Ecuador. The study aims to compare the two methods and conclude on which of them is better in forecasting the concentration of fine particulate matter (PM2.5) in an urban complex terrain. I concluded that even though WRF-Chem has the biggest advantage of forecasting all the data of interest for broader time horizon machine learning algorithms provide better accuracy for middle-term period. Machine learning models also require much less computational power but lack ability to predict meteorological conditions along with pollution level.

The purpose of the study was to conduct documented research on two of the recently designed teaching methods of high school chemistry, the Chemical Education Material Study (CHEM Study) and the Chemical Bond Approach (CBA). An attempt was made to answer certain questions concerning differences in the two methods.

Direct injection spark ignition (DISI) engines are the next generation of gasoline fuelled engines. Their greater fuel economy and reduced CO2 emissions compared with port fuel injection (PFI) engines has led to their popularity. However, DISI engines produce a greater number of particulate matter (PM) emissions than PFI engines. Concern over the health effects of PM emissions, and forthcoming European legislation to regulate them from gasoline powered vehicles has led to an increased interest in the study of PM formation, measurement, and characterisation. A model was developed by Aikawa et al, the PM index, correlating PM emissions with fuel composition. PM emissions are thought to be linked both to the vapour pressure (VP) and the double bond equivalent (DBE) of the components of the fuel. However, there was no independent control of these parameters and the study was undertaken on a PFI engine. In this thesis, experiments have been conducted to validate this model and extend it, as the PN index, to DISI engines. Fuels have been designed using Raoult’s law and UNIFAC (with careful consideration of octane number) such that the DBE and VP of the fuel mix could be varied independently. The design of the fuels was such that the component parts would co-evaporate upon injection into the cylinder, ensuring a homogeneous mixture of the components at the point of ignition. The PN index has been tested on a single cylinder engine, at a matrix of test points, using these model fuels, and their PM emissions have been analysed using a Cambustion DMS500. The results show that the PN index is followed closely using model fuels, provided that these model fuels contain a ‘light-end’ (in this case 5 % v/v n-pentane). Imaging of in-cylinder evaporation and in-cylinder measurement of hydrocarbons shows how the composition of model fuels affects their PM emissions. The PN index has also been tested using commercial fuels on a single cylinder engine and a Jaguar V8 engine; the results again show that the PN index is also an excellent predictor of PN emissions for market fuels from both of these engines. PN emissions have been evaluated from two fuels representing the EU5 reference fuel specification, developed using the PN index to give a difference in PM emissions. Testing these fuels on both a single cylinder engine and a Jaguar V8 engine has shown up to a factor of three variation in observed PN emissions. This has important implications for forthcoming European emissions legislation. The results of these tests were fed into the recommendations for the EU6 reference fuel specification. The PN index has also been investigated in a Jaguar V6 engine with five different fuels with a spread of calculated PN indices over a simulated NEDC. Here the PN emissions have been measured using two PN, and one PM instrument and the results compared. The results show that the trends of the PN index are followed, but not as closely as predicted. Detailed analysis shows that this discrepancy is due to other effects, for example cold start, dominating the PN emissions in certain phases. PN emissions have been measured from a highly boosted engine at a variety of operating points using 14 different fuels. It has been shown that for a large variety of engine operating parameters PN emissions from highly boosted engines behave as expected. When changing the fuels, the results show that a variation of over three orders of magnitude can be observed. The predictions of the PN index are inconclusive however, with further work suggested to fully evaluate the PN index on highly boosted engines.

The increasing demand for the domestic refrigeration system urges the development of greener form of refrigeration. The eighty-year-old single pressure absorption refrigeration system invented by Albert Einstein and Leo Szilard is attractive as it has no mechanical moving parts and can be driven by heat alone. However, the literature on either the refrigeration system or its components is scarce. The bubble pump is the crucial component of the refrigeration system, but it is poorly understood as its mass flow rate cannot be readily predicted. Two new time correlations in the mass flow rate prediction are presented to increase the accuracy when heat losses occur in the bubble pump. These time correlations are verified with the experimental results. When either the heat input or submergence ratio increases, the accuracy of the prediction increases. The percentage of error for the high heat input or submergence ratio is within ±10%. Working conditions and system dimension have a direct influence to the bubble pump performance. For instance, the bubble pump experimental results show that the mass flow rate of the bubble pump increases when either the submergence ratio or the concentration of ammonia increases. However, the performance of the bubble pump drops when the tube diameter or the system pressure increases. The Einstein refrigeration system has only been rebuilt once since it invention. In order to redesign and rebuilt a practical Einstein refrigeration system, some challenges are revealed. With the combination of the good features of the designs of Einstein and Delano, a new prototype has been rebuilt and tested. The practical results obtained from the five experimental setups are the first set of experimental result that has ever been presented. The highest cooling capacity and coefficient of performance (COP) obtained are 5 W and 0.04 respectively.

TITLE: The Representation of the "New Woman" on the works of the authors in the Weimarer Republic SUMMARY: The following thesis will give an overview about the political, social and cultural Situation on the time of the Weimarer Republic. The main emphasis gives a report on the concept of "New Woman"; the new social and literary woman type. The analysis on selected works of Irmgard Keun and Vicki Baum will throw light on the figure of this "New Woman". KEYWORDS: Weimarer Republic, "Neue Sachlichkeit", "New Woman", Irmgard Keun: Gilgi - eine von uns (1931), Vicki Baum: Stud. chem. Helene Willfüer (1928)

The Models-3/Community Multi-scale Air Quality modeling system (CMAQ), coupled with Goddard Institute for Space Studies (GISS) atmospheric General Circulation Model (GCM), fifth Generation Mesoscale Model system (MM5), and Goddard Earth Observing System-CHEMistry (GEOS-Chem), was used to simulate atmospheric concentration of ozone and particulate matter over the continental United States 12-km and 36-km (CONUS) domains at year 2000 and year 2050. In the study, GISS GCM model outputs interfaced with MM5 were utilized to supply the current and future meteorological conditions for CMAQ. The conventional CMAQ profile initial and boundary conditions were replaced by time-varied and layer-varied GEOS-Chem outputs. The future emission concentrations were estimated using year 2000 based emissions with emission projections suggested by the IPCC A1B scenario. Multi-scenario statistical analyses were performed to investigate the effects of climate change and change of anthropogenic emissions toward 2050. The composite effects of these changes were broken down into individual effects and analyzed on three distinct regions (i.e., Midwest, Northeast and Southeast). The results of CMAQ hourly and 8-hour average concentrations indicate the maximum ozone concentration in the Midwest is increased slightly from year 2000 to year 2050, as a result of increasing average and maximum temperatures by 2 to 3 degrees Kelvin. In converse, there is an observed reduction of surface ozone concentration in the Southeast caused by the decrease in solar radiation. For the emission reduction scenario, the decline of anthropogenic emissions causes reductions of both ozone and PM2.5 for all regions. The emission reduction has compensated the effect of increasing temperature. The overall change on the maximum daily 8-hr ozone and average PM2.5 concentrations in year 2050 were estimated to be 10% and 40% less than the values in year 2000, respectively. The modeling results indicates the effect of emissions reduction has greater impact than the effect of climate change.

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In this study, the effect of a passive trapped-vortex cell on lift to drag (L/D) ratio of an FFA-W3-301 airfoil is studied. The upper surface of the airfoil was modified to incorporate a cavity defined by seven parameters. The L/D ratio of the airfoil is modeled using a radial basis function metamodel. This model is used to find the optimal design parameter values that give the highest L/D. The numerical results indicate that the L/D ratio is most sensitive to the position on an airfoil’s upper surface at which the cavity starts, the position of the end point of the cavity, and the vertical distance of the cavity end point relative to the airfoil surface. The L/D ratio can be improved by locating the cavity start point at the point of separation for a particular angle of attack. The optimal cavity shape (o19_aXX) is also tested for a NACA0024 airfoil.

Yes / Inhibitory GABAB receptors (GABABRs) can down-regulate most excitatory synapses in the CNS by reducing postsynaptic excitability. Functional GABABRs are heterodimers of GABAB1 and GABAB2 subunits and here we show that the trafficking and surface expression of GABABRs is differentially regulated by synaptic or pathophysiological activation of NMDA receptors (NMDARs). Activation of synaptic NMDARs using a chemLTP protocol increases GABABR recycling and surface expression. In contrast, excitotoxic global activation of synaptic and extrasynaptic NMDARs by bath application of NMDA causes the loss of surface GABABRs. Intriguingly, exposing neurons to extreme metabolic stress using oxygen/glucose deprivation (OGD) increases GABAB1 but decreases GABAB2 surface expression. The increase in surface GABAB1 involves enhanced recycling and is blocked by the NMDAR antagonist AP5. The decrease in surface GABAB2 is also blocked by AP5 and by inhibiting degradation pathways. These results indicate that NMDAR activity is critical in GABABR trafficking and function and that the individual subunits can be separately controlled to regulate neuronal responsiveness and survival. / BBSRC, MRC and the European Research Council