Air quality forecasts are of great value since several pollutants in our environment effect both human health, global climate, vegetation, crop yields, animals, materials and acidification of forests and lakes. Air-quality forecasts help to make people aware of the presence and the quantity of pollutants, and give them a chance to protect themselves, their business and the Earth. Many different air-quality models are in daily use all over the world, providing citizens with forecasts of air quality and warnings of unhealthy air quality if recommended highest concentrations are exceeded. This study adapts the WRF meteorological model (Weather research and Forecasting model) to be a driver of the CMAQ air-quality model (models-3 Community Multiscale Air Quality model). Forecasts of ozone and nitrogen dioxide concentrations from this coupled WRF/CMAQ modelling system are tested against observed data during a four-day period in May, 2006. The Lower Fraser Valley study area is a fertile valley surrounded by mountain chains in southwest British Columbia, Canada. The valley stretches from the Pacific coast eastwards towards the Rocky Mountains. This valley hosts more than 2 million people and it is west Canada’s fastest growing region. The Lower Fraser Valley holds a big city, Vancouver, several suburbs, numerous industries and a widespread agricultural production. During the analysed four-day period in May, a synoptic high-pressure built over the region, favoring high concentrations of pollutants as ozone and nitrogen dioxide. The created WRF/CMAQ model forecasted an acceptable magnitude of nitrogen dioxide but the daily variations are not recreated properly by the model. The WRF/CMAQ model forecasts the daily variation of ozone in a satisfying way, but the forecasted concentrations are overestimated by between 20 and 30 ppb throughout the study. Factors that could contribute to the elevated ozone concentrations were investigated, and it was found that the weather forecasting model WRF was not generating fully reliable meteorological values, which in turn hurt the air-quality forecasts. As the WRF model usually is a good weather forecasting model, the short spin-up time for the model could be a probable cause for its poor performance. / Prognoser över luftkvaliteten är mycket värdefulla, då flera luftföroreningar i vår närmiljö påverkar människans hälsa, det globala klimatet, vegetation, djur, material och bidrar till försurning av skog och vattendrag. Luftkvalitetsprognoser gör människan mer medveten om närvaron av luftföroreningar och i vilken mängd de finns. De ger människan en chans att vidta skyddsåtgärder för att skydda sig själv, sitt eventuella levebröd, och Jorden. Många olika luftkvalitetsmodeller används idag dagligdags över hela världen och förser invånare med prognoser för luftkvaliteten och varningar om koncentrationerna av föroreningar överstiger rekommenderade värden. I denna studie används väderprognosmodellen WRF (Weather Research and Forecasting model) för att driva luftkvalitetsmodellen CMAQ (models-3 Community Multiscale Air Quality model). Prognoser av ozon- och kvävedioxidhalterna i luften från den kopplade WRF/CMAQ modellen analyseras mot observerade data under en fyra dagars period i maj, 2006. Studieområdet Lower Fraser Valley är en bördig dalgång som är omgiven av bergskedjor i sydvästra British Columbia, Kanada. Dalen sträcker sig från Stilla havskusten och österut mot Klippiga bergen. I denna dalgång bor mer än 2 miljoner människor och det är västra Kanadas snabbast växande region. Lower Fraser Valley rymmer en storstad, Vancouver, flera förorter, många industrier och även stora jordbruksområden. Den fyra dagars period i maj som analyseras karaktäriseras av ett högtrycksbetonat synoptiskt väderläge med lokala variationer, vilka tillsammans är gynnsamma för att uppmäta höga koncentrationer av luftföroreningar som ozon och kvävedioxid. Den skapade WRF/CMAQ modellen prognostiserar godtagbar magnitud hos kvävedioxid men den dagliga variationen återskapas inte av modellen. Modellen prognostiserar den dagliga variationen av ozonkoncentration på ett tillfredsställande sätt, men storleksmässigt ligger koncentrationerna en faktor 20-30 ppb för högt rakt av under hela studien. Kringliggande faktorer som kan påverka koncentrationen ozon studeras närmare och det framkommer att den meteorologiska prognosmodellen WRF inte genererar fullt tillförlitliga värden för en rättvisande luftkvalitetsprognos. Då WRF modellen vanligtvis är en bra prognosmodell kan den korta initialiseringstiden för modellen vara en trolig orsak till dess otillräckliga prestation.

Die Veröffentlichung analysiert die Ursachen der NO2-Belastung in Sachsen und prognostiziert deren Entwicklung. Die aktualisierte Version des Handbuchs der Emissionsfaktoren des Straßenverkehrs (HBEFA 3.1) ist eine der Datengrundlagen. Hauptverursacher von NO2-Grenzwertüberschreitungen in sächsischen Städten ist der Kfz-Verkehr. Die sächsischen Daten von Verkehrsstationen im Zeitraum von 1995 bis 2009 bestätigen den bundesweit abnehmenden Trend. An hoch belasteten Straßen sind weitere dauerhafte und/oder temporäre Maßnahmen erforderlich, um den NO2-Grenzwert bis spätestens 2015 einzuhalten. Die Erneuerung der Kfz-Flotte reicht dafür nicht aus. Als sofort wirkende Maßnahme hat auch unter Berücksichtigung des neuen HBEFA 3.1 die Umweltzone ihre Berechtigung. Die Festlegung von wirksamen Maßnahmen erfordert eine individuelle Planung.

In today’s world, where air pollution has become a ubiquitous problem, city air is normally monitored. Such monitoring can produce large amounts of data, and this enables the development of statistical and machine learning techniques for modeling and forecasting air quality. However, the complex nature of air pollution makes such data a challenge to fully utilize. To this end, machine learning methods, especially deep neural networks, have in recent years emerged as a promising technology for more accurate predictions of air pollution levels, and the research problem in this work is; To capture and model the complex dynamics of air pollution with machine learning methods, with an emphasis on deep neural networks. Connected to the research problem is the research question; How can machine learning, in particular deep neural networks, be used to forecast air pollution levels and pollution peaks? An emphasis is put on pollution peaks, as these are the episodes when existing forecasting models tend to give the largest prediction errors. In this work, historical data from air monitoring sensors were utilized to train several neural network architectures, as well as a more straightforward multiple linear regression model, for forecasting background levels of nitrogen dioxide in the center of Stockholm. Several evaluation metrics showed that the neural network models outperformed the multiple linear regression model, however, none of the models had the desired structure of the forecast errors, and all models failed to successfully capture sudden pollution peaks. Nevertheless, the results point to an advantage for the more complex neural network models, and further advances in the field of machine learning, together with higher resolution data, have the potential to improve air quality forecasts even more and cross conventional forecasting limits.

Unexpectedly high concentrations of NO₂ have been noted in stack emissions from industrial gas turbines. NO₂ formation appears to occur through the so called "HO₂ mechanism II in which NO combines with HO₂ to produce NO₂ and OH. In this study, the formation of NO₂ was investigated through computer modeling and experimental testing. Computer modeling utilized the CHEMKIN chemical kinetics program and a subset of a previously published C-H-O-N system mechanism. Experimental work was conducted using a high pressure flow reactor designed and built in the course of the study. The effects of pressure, temperature, and the presence of a NO₂ promoting hydrocarbon, methane, were investigated. It was discovered that as pressure increased from 1 atm. to 8.5 atm., the rate and amount of NO converted to NO₂ also increased. There also appeared to be a temperature "window" between approximately 800 and 1000 K in which NO to NO₂ conversion readily occurred. The presence of methane was seen to enhance NO conversion to NO₂, and a ratio of [CH₄]/[NO] was found to be a useful parameter in predicting NO₂ formation. Significant NO conversion to NO₂ was noted for [CH₄]/[NO] > 1 at the hydrocarbon injection point. Experimental results validated those trends obtained from modeling with a modified C-H-O-N mechanism. / Master of Science

Reactions of strongly oxidizing pollutants with unsaturated hydrocarbon surfaces are important to many areas of scientific interest. For example, reactions of unsaturated hydrocarbons on the surface of tropospheric aerosols could have a great effect on the oxidizing capacity of the troposphere while the reaction products could be involved in the formation of clouds and smog. These reactions are also important in understanding the toxic effect inhalation of these pollutants have on the pulmonary surfactant of the lung, the only amicable air-water interface of the body. The fatty acids of this surfactant are as much as 30% unsaturated, and exposure to oxidizing pollutant is known to alter both the composition and function of the surfactant. Understanding the reaction mechanism will further the knowledge of how this toxicity occurs. While the reactions of strongly oxidizing pollutants, such as ozone and nitrogen dioxide, with alkenes in the gas and solution phases are well known, the interfacial reaction mechanisms of these species is not fully understood. The goal of this study is to determine the reaction mechanism when an unsaturated hydrocarbon monolayer at the gas-surface interface is exposed to gas phase nitrogen dioxide. An olefin-terminated thiol was synthesized and a self-assembled monolayer on Au(111) made and characterized using Reflection-Absorption Infrared Spectroscopy (RAIRS). This unsaturated surface was then exposed to NO2 at a pressure of 1x10-4 mbar in a UHV (Ultrahigh Vacuum) chamber. Time-resolved RAIRS was preformed in situ to monitor the reaction during exposure. X-ray Photoelectron Spectroscopy and RAIRS determined the surface reaction product as an aldehyde. While the mechanism can not be precisely determined, two mechanisms involving either the hydrogen abstraction or radical addition of the NO2 to yield an aldehyde are proposed. / Master of Science

No description available.

The health impacts of urban air pollution are a growing concern in our rapidly urbanizing world. Urban air pollutants show high intra-urban spatial variability linked to urban land use and land cover (LULC). This correlation of air pollutants with LULC is widely recognized; LULC data is an integral input into a wide range of models, especially land use regression models developed by epidemiologists to study the impact of air pollution on human health. Given the demonstrated links between LULC and urban air pollution, and between urban air pollution and health, an interesting question arises: what is the potential of LULC modifications to mitigate the health impacts of urban air pollution? In this dissertation we assess the potential of LULC modifications to mitigate the health impacts of NO2, a respiratory irritant and strong marker for combustion-related air pollution, in the Portland-Vancouver metropolitan area in northwestern USA. We begin by measuring summer and winter NO2 in the area using a spatially dense network of passive NO2 samplers. We next develop an annual average model for NO2 based on the observational data, using random forest -- for the first time in the realm of urban air pollution -- to disentangle the effects of highly correlated LULC variables on ambient NO2 concentrations. We apply this random forest (LURF) model to a 200m spatial grid covering the study area, and use this 200m LURF model to quantify the effect of different urban land use categories on ambient concentrations of NO2. Using the changes in ambient NO2 concentrations resulting from land use modifications as input to BenMAP (a health benefits assessment tool form the US EPA), we assess the NO2-related health impact associated with each land use category and its modifications. We demonstrate how the LURF model can be used to assess the respiratory health benefits of competing land use modifications, including city-wide and local-scale mitigation strategies based on modifying tree canopy and vehicle miles traveled (VMT). Planting trees is a common land cover modification strategy undertaken by cities to reduce air pollution. Statistical models such as LUR and LURF demonstrate a correlation between tree cover and reduced air pollution, but they cannot demonstrate causation. Hence, we run the atmospheric chemistry and transport model CMAQ to examine to what extent the dry deposition mechanism can explain the reduction of NO2 which statistical models associate with tree canopy. Results from our research indicate that even though the Portland-Vancouver area is in compliance with the US EPA NO2 standards, ambient concentrations of NO2 still create an annual health burden of at least $40 million USD. Our model suggests that NO2 associated with high intensity development and VMT may be creating an annual health burden of $7 million and $3.3 million USD respectively. Existing tree canopy, on the other hand, is associated with an annual health benefit of $1.4 million USD. LULC modifications can mitigate some fraction of this health burden. A 2% increase in tree canopy across the study area may reduce incidence rates of asthma exacerbation by as much as 7%. We also find that increasing tree canopy is a more effective strategy than reducing VMT in terms of mitigating the health burden of NO2. CMAQ indicates that the amount of NO2 removed by dry deposition is an order of magnitude smaller than that predicted by our statistical model. About one-third of the difference can be explained by the lower NO2 values predicted by CMAQ, and one-third may be attributable to parameterization of stomatal uptake.

Fung, Kit Ching. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 134-144). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Some appendixes in Chinese.

Mgr. Martina Nádherná PhD. Thesis Applications of ionic liquids in electrolytes for amperometric gas sensors and Li-ion batteries SUMMARY The dissertation presents the results of preparation and characterisation of new aprotic electrolytes based on ionic liquids for the solid-state electrochemical gas sensors and for the electrochemical energy storage devices - secondary lithium-ion batteries. In the part dealing with the solid-state amperometric sensor for NO2 research was aimed at development of new solid electrolyte. This electrolyte is developed as a system of ionic liquid embedded in the structure of a polymer, when the ionic liquid joints the properties of a solvent and a dissolved salt. The electrolyte therefore does not contain any volatile component and is long-term chemically and electrochemically stable. Several series of electrolytes were prepared with different polymers or macromonomers and imidazolium-based ionic liquids. The composition, especially the polymer-IL ratio was optimized. The electrolytes were successfully tested in a solid-state NO2 sensor with a gold minigrid serving as the indicating electrode. The research included the determination of basic electrochemical parameters and study of the sensor behaviour under different conditions. The influence of atmosphere humidity,...

Introdução: A poluição do ar é resultado de complexas interações que envolvem emissões de poluentes atmosféricos e que sabidamente causam consequências negativas para a saúde humana. De acordo com alguns estudos, a exposição à poluição, durante a gestação, pode afetar o peso ao nascimento, contudo, não há ainda conhecimento sedimentado sobre as janelas críticas de exposição à poluição durante a gestação e quais os efeitos no crescimento fetal e no fluxo placentário. Objetivos: Visando investigar, mais profundamente, o impacto da poluição na vida intrauterina, o objetivo deste estudo foi avaliar a influência da exposição à poluição, nos três trimestres da gestação, no crescimento fetal e na hemodinâmica feto-placentária avaliados no terceiro trimestre da gestação. Métodos: Foi realizado um estudo prospectivo com 386 gestantes, na cidade de São Paulo, intitulado ProcriAR. Os poluentes dióxido de nitrogênio (NO2) e ozônio (O3) foram medidos durante cada trimestre da gestação por meio da utilização de amostradores passivos individuais. No terceiro trimestre, foi realizada ultrassonografia fetal na qual foram avaliados: o diâmetro biparietal, a circunferência craniana, a circunferência abdominal, o comprimento do fêmur, o peso fetal, o índice de líquido amniótico e os índices de pulsatilidade (IP) de sonograma das artérias umbilical, cerebral média e uterinas. Foi realizada análise multivariada, controlada por idade materna, no momento da concepção, índice de massa corporal (IMC), paridade, tabagismo, consumo de álcool, cor, nível de escolaridade, estado civil, idade gestacional no momento do exame e sexo fetal. Resultados: Menor circunferência cefálica foi associada com a exposição ao O3 no primeiro trimestre (p = 0,012; beta = -0,005; intervalo de confiança de 95% (IC 95%), - 0,008, -0,001), e maior circunferência cefálica foi associada com a exposição ao NO2 no primeiro trimestre (p = 0,033; beta = 2,5 x 10-4; IC 95%, 2 x 10-5, 4,8 x 10-4). A exposição ao O3 no segundo trimestre foi associada a maiores valores de IP da artéria umbilical (p = 0,006; beta = 0,018; IC 95%, 0,005, 0,030), porém a exposição ao O3 no terceiro trimestre foi associada a menores valores de IP da umbilical (p = 0,004; beta = - 0,022; IC 95%, -0,037, - 0,007). Conclusão: Nossos resultados sugerem que, no ambiente de São Paulo, o O3 pode interferir no crescimento do polo cefálico e na resistência vascular placentária / Background: Air pollution may influence fetal growth and placental flow according to trimester-specific exposure. Objectives: To determine the influence of maternal air pollution exposure during each trimester of pregnancy on fetal growth and fetoplacental hemodynamics. Methods: ProcriAR, a prospective cohort study of 386 pregnant women, was conducted in the city of São Paulo. Nitrogen dioxide (NO2) and ozone (O3) were measured during each trimester using passive personal monitors. In trimester 3, we evaluated the biparietal diameter, head circumference, abdominal circumference, femur length, fetal weight, amniotic fluid index and Doppler velocimetry data of the umbilical, middle cerebral and uterine arteries. Multivariate analysis was performed, controlling for maternal age at conception, body mass index, parity, smoking, alcohol consumption, race, highest education level completed, and marital status and the fetus\'s gestational age and sex. Results: Reduced head circumference was associated with O3 exposure in trimester 1 (p = 0.012; beta = -0.005; 95% confidence interval (CI), -0.008, -0.001), and increased head circumference was associated with NO2 exposure in trimester 1 (p = 0.033; beta = 2.5 x 10-4; 95% CI, 2 x 10-5, 4.8 x 10-4). Exposure to O3 during the second and third trimesters was associated with higher (p = 0.006; beta = 0.018; 95% CI, 0.005, 0.030) and lower (p = 0.004; beta = -0.022; 95% CI, -0.037, -0.007) umbilical artery pulsatility values, respectively. Conclusion: Our results suggest that in the environment of São Paulo, O3 may interfere with fetal growth and vascular resistance