Dissertations / Theses on the topic 'Carbon particulate emission'

Indoor air quality is a growing concern in the world. People spend a considerable amount of time in indoor environments such as homes, workplaces, shopping malls, stores, and so on. Indoor sources like incense and candle burning, cooking contribute a significant amount of indoor air pollutants such as particulate matter, carbon monoxide (CO), volatile organic compounds. Exposure to these kinds of pollutants can result in adverse health effects. The purpose of this research is to determine the particulate matter and carbon monoxide emission factors (EFs) from incense stick burning. A test chamber with a rectangular exhaust duct, a fan to exhaust air with pollutants in it, and pollutant sensors were used to achieve the project goals. Several experiments were performed with different cases/scenarios to accurately estimate the EFs and several test runs were conducted for each case to test the repeatability of the results. The CO, PM2.5 (mass), PM2.5 (number), PM10 (mass), PM10 (number) EFs developed in this research are between 110-120 mg/g of incense, 2.5-3 mg/g of incense, 800-1100 #particles/µg of incense, 32-33 mg/g of incense, 1200-1400 #particles/µg of incense respectively.

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 Cityâ 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 â seeingâ 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.<br>Master of Science

Air quality management strategies in the US are developed largely from estimates of emissions, some highly uncertain, rather than actual measurements. Improved knowledge based on measurements of real-world emissions is needed to increase the effectiveness of these strategies. Consequently, the objectives of this research were to (1) quantify relationships among urban emissions sources, land use, and demographics, (2) determine the spatial and temporal variability of emissions, and (3) evaluate the accuracy of official emissions estimates. These objectives guided three field campaigns that employed a unique mobile laboratory equipped to measure pollutant fluxes by eddy covariance. The first campaign, conducted in Norfolk, Virginia, represented the first time fluxes of nitrogen oxides (NOx) were measured by eddy covariance in an urban environment. Fluxes agreed to within 10% of estimates in the National Emissions Inventory (NEI), but were three times higher than those of an inventory used for air quality modeling and planning. Additionally, measured fluxes were correlated with road density and increased development. The second campaign took place in the Tijuana-San Diego border region. Distinct spatial differences in fluxes of carbon dioxide (CO2), NOx, and particles were revealed across four sampling locations with the lowest fluxes occurring in a residential neighborhood and the highest ones at a port of entry characterized by heavy motor vehicle traffic. Additionally, observed emissions of NOx and carbon monoxide were significantly higher than those in emissions inventories, suggesting the need for further refinement of the inventories. The third campaign focused on emissions at a regional airport in Roanoke, Virginia. NOx and particle number emissions indices (EIs) were calculated for aircraft, in terms of grams of pollutant emitted per kilogram of fuel burned. Observed NOx EIs were ~20% lower than those in an international databank. NOx EIs from takeoffs were significantly higher than those from taxiing, but relative differences for particle EIs were mixed. Observed NOx fluxes at the airport agreed to within 25% of estimates derived from the NEI. The results of this research will provide greater knowledge of urban impacts to air quality and will improve associated management strategies through increased accuracy of official emissions estimates.<br>Ph. D.

This investigation aims to enhance the regeneration performance of a diesel particulate filter. This is achieved by introducing various chemical components to the regeneration process, which are representative of what can be generated ‘on board’ a vehicle using an exhaust gas fuel reformer. By researching the effects of introducing such components using a periodic injection cycle the aim is to reduce the volume of ‘reformates’ required to assist in proficient diesel particulate filter regeneration. As a result, this study also aims to support future work in the development of exhaust gas fuel reformer design for DPF aftertreatment applications. All experiments were performed using a Ford Puma 2.0 litre diesel engine. A test rig was constructed and installed that featured a mini diesel particulate filter housed within a tubular furnace. Exhaust gas could be sampled directly from the exhaust manifold and fed through the DPF. Exhaust gas measurements were taken both pre and post DPF using a FTIR spectrometer. It was shown that the regeneration process could be supported substantially by the introduction of hydrogen. Similar properties were also demonstrated when introducing a hydrogen-carbon monoxide mixture. The introduction of these species allowed for the regeneration process to be implemented at filter temperatures substantially lower than the passive regeneration temperature. Furthermore, by introducing these simulated reformates using a periodic injection strategy, it was evident that similar benefits to the regeneration process could be attained with significantly less volumes of simulated reformates. In an attempt to effectively utilise the carbon monoxide generated during hydrogen production by an exhaust gas fuel reformer, this study defined an optimised hydrogen/carbon monoxide mixture ratio of 60% (v/v) hydrogen balanced with carbon monoxide. At this optimised mixture ratio, the filter demonstrated the highest regeneration efficiency of all ratios tested. Such data could be utilised in future work in the development of fuel reformer design.

Diesel Particulate Matter (DPM) and coal dust samples were characterised using Raman microscopy, X-ray Photoelectron Spectroscopy (XPS), Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), Thermo-Gravimetric Analysis (TGA), X-ray Fluorescence (XRF) spectrometry and Scanning electron Microscopy. The sp2/sp3 carbon bonding ratios for DPM and coal dust were determined as 6.1 and 0.7, respectively, from XPS. Principal Component Analysis (PCA) was successfully implemented as a tool for distinguishing between the very similar DPM and coal dust Raman spectra, with over 99% of the variance contained in the first principal component. DPM and coal dust mixtures with known compositions were produced. Raman instrumental parameters were systematically optimised by varying the objective lenses, acquisition times and laser powers, to improve spectral and obtain the most reproducible integrated spectral areas. A rotation stage was developed and employed to spin the specimens during analysis, resulting in a larger sampling area. This resulted in a more representative sampling regime for the heterogeneous specimens and a considerable improvement in the reproducibility of integrated spectral areas. The error in the integrated spectral areas of 10 replicate spectra of different mixtures ranged from 5-22% before implementation of the rotating stage and was notably reduced to 2 -6% due to the action of spinning. Raman spectra of mixtures were used to construct a Partial Least Squares (PLS) model. The R2 values for the DPM and coal dust were 0.865 and 0.763, respectively. The differential bum-off of volatile organics during the Raman analysis due to localised heating from the laser hindered the ability to gain highly reproducible spectra and thus markedly affected the PLS model. A method development stage aimed at improving the R2 values was applied to the samples. This involved heat-treating the specimens to 625°C in an inert nitrogen atmosphere, before the Raman analysis. The resultant PLS model, after heat-treatment, dramatically improved the R2 values such that the DPM and coal dust were 0.974 and 0.907, respectively. This model was used to predict the composition of a test sample with known amounts of DPM and coal dust. The concentrations predicted by the model were 166 ± 3.9pg for the DPM and 68 ± 7.8jxg for the coal dust. The model slightly overestimated the amount of DPM present in the sample but gave a large underestimation of the coal dust content. The diagnostics of the model were investigated and recommendations for the improvement of future models were given.

Aerosol emissions from diesel combustion and other activities in rail yards can affect the health of urban populations. Fine particulate (PM[subscript 2.5]) concentrations near the Inman and Tilford rail yards in Atlanta, Georgia, are the highest measured in the state. The rail yard complex is surrounded by homes, schools, businesses and other industries. The impact of the aerosol emissions from these rail yards on local concentrations of PM[subscript 2.5] was quantified. Specifically, black carbon and PM[subscript 2.5] fuel-based emission factors from the rail yards were estimated by carbon balance using high time-resolution monitoring, a BC and PM[subscript 2.5] emissions inventory was estimated and dispersion modeling was applied to assess the impact of the rail yard activities on local air quality and the cost and benefits of upgrading locomotive engines with cleaner technologies was assessed. Further, baseline information that will allow a later evaluation of the improvement of local air quality as locomotives operating in the rail yards are upgraded was generated, and a composition profile of the rail yard aerosols was developed using chemical speciation techniques. These results found that activities from locomotives in the Inman and Tilford Rail yards lead to and an average emission factor of 6.0 ± 0.5 g of PM[subscript 2.5] per gallon of fuel and are responsible for increases in annual average concentrations of approximately 1.3 µg/m³ of PM[subscript 2.5] as far as 1 km from the perimeter of the rail yard complex. Approximately 11.7 tons of BC and 26 tons of PM[subscript 2.5] per year were emitted from the rail yards in 2011. The rail yards were found to be important sources of hydrocarbon-like organic aerosols (HOA) and black carbon from fuel (BCf). Upgrading the engines at the rail yards would decrease PM[subscript 2.5] emissions by about 9 t/year, reducing PM[subscript 2.5] concentrations around 0.5±0.1 µg/m³ as far as 1 km from the perimeter of the rail yard complex and producing monetized health benefits of approximately 24 million dollars per year.

La compréhension du rôle des aérosols atmosphériques dans le fonctionnement du système terre-atmosphère est limitée par les incertitudes sur leur répartition spatiale, leur composition et leurs sources. Si leurs impacts sur le changement climatique et l’environnement peuvent être évalués grâce aux modèles de chimie-transport, ces incertitudes en limitent la précision. Les observations satellitaires ont la capacité de fournir à l’échelle globale des informations précises sur un certain nombre de paramètres « aérosols » mais elles sont limitées par les conditions nuageuses, la périodicité des orbites et par le contenu en information, c’est-à-dire le type de paramètres que l’on peut retrouver suivant la nature de ces observations. Une approche prometteuse consiste à améliorer les champs d’émission des modèles en utilisant le principe de la modélisation inverse. Dans cette étude, nous avons conçu une méthode de restitution simultanée des sources d’émission de poussières désertiques, de carbone suie et de carbone organique à partir des produits satellitaires (POLDER/PARASOL) dérivés en utilisant l’algorithme GRASP, conjointement à une modélisation inverse du modèle GEOS-Chem. Cela nous a permis de créer une base de données d’émissions globales d’aérosols sur la période 2006 – 2011. Des simulations réalisées avec les modèles directs GEOS-Chem et GEOS-5/GOCART utilisant cette base de données montrent bien entendu un bon accord avec des observations POLDER mais aussi une nette amélioration de la modélisation de l’aérosol à l’échelle globale lorsque l’on compare les sorties à des mesures indépendantes du réseau AERONET ou à d’autres mesures spatiales (MODIS, MISR, OMI)<br>Understanding of the role that atmospheric aerosol play in the Earth-atmosphere system is limited by uncertainties in aerosol distribution, composition and sources. Thus, accurate chemical transport model simulation systems are crucial needed to analyse and predict atmospheric aerosols and their impacts on climate change and environment. Satellite observations have ability to provide an extensive spatial coverage and accurate aerosol products, however, are constrained by clear-sky condition, global coverage orbit cycle and information content. One of the most promising approaches is to reduce model uncertainty by improving the aerosol emission fields (i.e., model input) by means of inverse modeling relying on satellite observations as a constrain. In this study, we designed a method of simultaneous retrievals of desert dust, black carbon and organic carbon aerosol emission sources using aerosol data obtained from GRASP algorithm applied to POLDER/PARASOL satellite observations, and relying on the GEOS-Chem inverse modeling framework. Then, a satellite-based global aerosol emission database (2006-2011) has been developed. This aerosol emission database has been further evaluated by utilization in GEOS-Chem and GEOS-5/GOCART models. The model posterior simulation of aerosol properties employing the retrieved emissions shows a better agreement than the model prior simulation; it is true for not only fitted PARASOL products, but also for completely independent measurements from ground-based AERONET and satellites aerosol products (e.g., MODIS, MISR, OMI). The results suggest that the satellite-based aerosol emission database improves overall global aerosol modeling

Overall, particulate matter (PM) and household air pollution are at the root of 2.9 million deaths annually. One of the sources of particulate matter is biomass burning (BB) smoke. These particles can be formed by natural fires, prescribe agriculture fires, and as a result of burning fuel for cooking and heating houses. BB smoke particles can have various health effect and environmental impacts depending on a number of factors. Altering ozone refraction, they can act as cloud condensation nuclei. Health risks associated with these particle have been studied for long. Pulmonary, heart, carcinogen (especially due to compounds like Poly Aromatic Hydrocarbons (PAH). First and foremost, the nature of the fuel has a direct impact on the composition of the particulate matter and gaseous particles formed as the combustion products. Woody, Grass, or leafy fuels have been found to be composed of different compounds with different mass fractions. For example, cellulose content in wood is higher than other types of biomass fuel. As a results, it is logical to seek similar compound ending up in the particulate matter. The scale and intensity of the fire is the other influential factor. Although the effect of natural wildfire (bushfire) smoke particles would not be as direct and immediate as those evolving from the fuel burnt in household uses, long term effect of exposure to these particles spreading within the atmosphere month and even years after the fire has happened should not be overlooked. Besides, in very close vicinities to the fires, in fresh smoke less than minutes old, there always exist high number of finer particles which are health-wise of more concern compared to larger particle (as these finer particles penetrate into lower parts of the respiratory system through diffusion). Weather conditions, like elevation, wind speed, humidity, and sunlight are also influential factors in the formation of these particles. The other crucial factor is the phase of burning, i.e. Ignition, flaming, mixed state, and smouldering. Numerous studies have investigated the effect of these conditions on the size distribution, number concentration and physiochemical properties of smoke particles. PM properties of BB smoke have been investigated all around the globe for different biomass types and different burning conditions. Black carbon (BC) and organic carbon (OC) content of the PM are the most documented investigated items as they contributes to the high mass percentage of the PM. Other ubiquitous PM components include anhydrosugars, alcohols, PAHs, acids, water soluble ions, and trace elements. Gaseous particles resulted from BB carry with them sulphur oxides (SOx) and nitrogen oxides (NOx), volatile and semi volatile organic compounds. Each of these compounds and materials are known to have serious health and climate impacts. Numerous studies have used different devices and technologies to investigate the effect of fuel type and amount, and phase of burning and operational mode on different properties of fresh and aged smokes in case of small scale controlled or laboratory burns, massive natural wildfires, or air-forced cook stove gasifiers. In Australia, despite contributing to more than 7% of biomass burning emissions annually, there are quite a few exhaustive studies on the properties of bushfire particles. The importance of research redoubles considering the mega-fires taking place in Australia 2019-2020 which ravaged an estimate of 19 million hectares. This study is aimed to make a contribution in filling this gap and finding novel ideas in order to investigate different factors influencing Australian local vegetation fires which could potentially effect the environment and human health. Three journal articles are published based on this study, parts of which are used in different sections throughout this report. Citations are made in the beginning of the main relevant chapters. Abstract summaries are presented briefly here: First paper: Under controlled laboratory settings and small scale fires of vegetation collected from Toohey forest, it was found that leaves classification burn with flaming dominant phases producing intense black smoke which is consisted of larger particles as opposed to more smouldering-dominant burning of the branch and grass classifications releasing white smoke emissions which contain finer particles. Elemental analysis detected nine main elements in all three classifications and in three size fractions of smoke particulate matter samples (from 14.1μm to below 2.5μm). Potassium, a biomarker, was the most prevalent element among the samples followed by sulphur. Less abundant elements were found to be Na, Al, Mg, Zn, Si, Ca, and Fe. Second paper: Particle size distribution in biomass smoke was observed for different burning phases, including flaming and smouldering, during the combustion of nine common South Queensland Australian vegetation representatives. Smoke particles generated during smouldering phase of combustions were found to be coarser as compared to flaming aerosols for all hard species. In contrast, for leafy species this trend was inversed. In addition, the combustion process was investigated over the entire duration of burning by acquiring every second data for all nine species. Particles were separately characterised in two categories: fine particles (diameter below 200nm), and course particles with the diameter larger than 200nm. It was found that fine particles contribute to more than 90 percent of the total fresh smoke particles for all investigated species. Third paper: smoke samples were collected during prescribed fire burns conducted between May 2018 and August 2019across different regions in Toohey forest, Queensland, Australia. Particle size/mass distribution as well as size-segregated elemental content were measured and the results were compared against the values obtained from the combustion of similar vegetation mixture under controlled laboratory settings. It was found that the concentration levels of coarse particles (sizes above 1 μm) were higher during field burn events, whereas the contributions of PM1 (smaller than 1 μm) was higher in case of laboratory burns. Following elemental analysis of different size classes of smoke particles (<0.96μm, 0.96-2.5μm, and >2.5μm) confirmed the presence of eight elements in both laboratory and field cases (Na, K, Mg, Ca, Zn, Al, Fe, S), however, levels of Ca, Mg, Al, and S were noticeably higher in prescribed fire results. Observed discrepancies between field and laboratory data could be attributed to the effect of top soil and duff layers present in prescribed fires/natural wildfires and absence thereof in the laboratory burns, which reveals the influential role of the aforementioned layers on the overall air quality status across bushfires-affected areas.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Eng & Built Env<br>Science, Environment, Engineering and Technology<br>Full Text

Transport, whose intensity year by year increase, has assuredly influence on air quality. This issue solution will be focused especially on localities burden with transport in urban areas. The contribution of transport to increased values of air pollution will be evaluated with regards to meteorological conditions. Background stations from Czech Hydrometeorological Institute categorization will be chosen such as comparative sites. Pollutants emitted from traffic such as particulate matter, nitrogen oxides and carbon monoxide will be observed except meteorological conditions.

Diversos estudos tiveram como objetivo determinar e caracterizar o aerossol atmosférico na cidade de São Paulo, quanto a seu tamanho e composição química, bem como encontrar as suas fontes emissoras e contribuições em massa para a região estudada. A coleta dos constituintes atmosféricos foi realizada na estação de amostragem do Laboratório de Análises dos Processos Atmosféricos (LAPAt) do Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG) da Universidade de São Paulo (USP), localizada na zona oeste da cidade de São Paulo, geograficamente em 23°3334 S e 46°4400 O. O experimento foi realizado de 15 de agosto a 16 de setembro de 2016. Foram realizadas coletas de material particulado para análise da concentração em massa de sua fração fina inalável e composição química. A distribuição de tamanho para massa de material particulado foi determinada através da coleta com um impactador em cascata. A distribuição de tamanho para número foi obtida a partir de medidas com um Scanning Mobility Particle Sampler (SMPS) com o cálculo da concentração número de partículas (PNC) para o intervalo de 9 a 450 nm de diâmetro. Para estudar as relações entre os gases presentes na região amostrada com a radiação ultravioleta e com o PNC utilizamos os valores horários de concentrações dos gases (O3, NO, NO2 e NOX) e UV medidos na Rede Telemétrica da CETESB (Companhia de Tecnologia Ambiental do Estado de São Paulo). Os filtros coletados foram analisados pela técnica de Fluorescência de Raios-X dispersivo em energia (EDX). As concentrações de Black Carbon (BC) foram obtidas por refletância. Para a determinação das fontes de material particulado fino (MP2,5) foram utilizados os seguintes modelos receptores: Análise de Componentes Principais (ACP) e Fatoração de Matriz Positiva (FMP). Para análise de dispersão do poluente, utilizamos dados meteorológicos da estação climatológica do IAG situada no Parque do Estado. A concentração média de MP2,5 foi de 18,6 (±12,5) g/m³ e a concentração média de BC foi de 1,9 (±1,5) g/m³. As principais fontes encontradas, por ambos modelos receptores ACP e FMP, foram: veículos pesados (a diesel), veículos leves, queima de biomassa, ressuspensão de poeira de solo, pavimentos e construção, processos secundários e misturas de fontes. Os elementos-traço foram definidos em diferentes modas de tamanho: Al, Ca, Si e Ti com picos nas modas de acumulação, traçadores de ressuspensão de pavimento; Fe, Mn, P, K e Cr com picos na fração mais grossa da moda de acumulação, traçadores de emissões veiculares e queima de biomassa. Cu, Zn, Br, Pb, S e BC apresentam picos na fração mais fina da moda de acumulação, traçadores de emissões veiculares e queima de biomassa.<br>Several studies aimed to determine and characterize the atmospheric aerosol in the city of São Paulo, not only to its size and chemical composition, but as well as to find its emitting sources and mass contributions in the studied area. The atmospheric constituents were collected at the Laboratório de Análise dos Processos Atmosféricos (LAPAt) of the Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG) of the University of São Paulo (USP), located in the western zone of the city of São Paulo Paulo, geographically at 23°33\'34\"S and 46°44\'00\" W. The experiment was conducted from August 15 to September 16 of 2016. Samples of particulate matter were collected to analyze the mass concentration and chemical composition of its inhalable fine fraction. The particulate mass size distribution was determined through the collection with a cascade impactor. The number size distribution was obtained from measurements with a Scanning Mobility Particle Sampler (SMPS) with the calculated number of particle concentration (PNC) for the range of 9 to 450 nm of the diameter. In order to study the relationships among the compounds present in the region and the PNC, we used the hourly values of the gaseous concentrations (O3, NO, NO2 and NOx) and UV measured in CETESB\'s Air Quality Telemetric Network in the State of São Paulo. The sampled filters were analyzed by the energy dispersive X-ray Fluorescence (EDX) technique to determine the elemental composition. The concentrations of Black Carbon (BC) were obtained by reflectance analysis. In order to determine the sources of fine particulate matter (PM2.5), the following Receptors Models were used: Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF). For air pollution dispersion analysis, we used meteorological data from the IAG climatological station located in the Southeast of the city. The mean MP2.5 concentration was 18.6 (± 12.5) g/m³ and the mean concentration of BC was 1.9 (± 1.5) g/m³ for the sampling period. The main sources found by both ACP and PMF models were heavy-duty vehicles (diesel), light-duty vehicles, biomass burning, resuspension of soil dust, pavements and construction, secondary processes and mixed sources. The trace elements were defined at different size distributions: Al, Ca, Si and Ti with peaks in accumulation fraction (related to pavement resuspension tracers); Fe, Mn, P, K and Cr with peaks in the largest fraction of accumulation mode, characteristic of vehicular emissions tracer and biomass burning. Cu, Zn, Br, Pb, S and BC presented peaks in the finer fraction of the accumulation mode, related to vehicle emissions tracer and biomass burning.

Population exposure to traffic pollution is a rapidly developing, multi-disciplinary scientific field. While the link between long-term exposure and respiratory issues is well-established, there are probable links to a number of more serious health effects, which are still not fully understood. In the interests of protecting human health, it is prudent that we take a cautionary approach and actively seek to reduce exposure levels, especially in the home environment where people spend a significant portion of their time. In many large cities, a substantial number of homes are situated on land immediately adjacent to busy freeways and other heavily-trafficked roads. Characterising exposures of local residents is incredibly challenging but necessary for advancing epidemiological understandings. While existing studies are plentiful, the results are mixed and generally not transferable to other urban areas due to the localised nature of the built environment and meteorological influences. This thesis aimed to employ a variety of methods to develop a holistic understanding of the influence of traffic emissions on near-highway residents' exposure in two communities of South Auckland, New Zealand, where Annual Average Daily Traffic (AADT) is as high as 122,000 vehicles. First, ultrafine particles (UFPs), nitrogen oxides (NOx), carbon monoxide (CO) and particulate matter ≤ 10 μm (PM₁₀) were continuously monitored using a series of fixed stations at different distances from the highways, over several months during the winters of 2010 and 2011. Emissions modelling output (based on traffic composition), was used within a dispersion model to compare modelled concentrations with monitored levels. In addition, community census meshblock units were mapped by level of social deprivation in order to assess potential inequities in highway emissions exposure. The second layer of local air quality investigation involved using a bicycle platform to systematically measure concentrations of UFPs, CO and PM₁₀ using the entire street-grid network throughout each community. This was done forty times - five times at four times of day (07:00, 12:00, 17:00 and 22:00), for each study area, with the aim of mapping the diurnal fluctuation of microspatial variation in concentrations. Using global positioning system (GPS) data and geographical information system (GIS) software, spatially-resolved pollutant levels were pooled by time of day and the median values mapped, providing a visualisation of the spatial extent of the influence of emissions from the highways compared to minor roads. The third layer involved using data from multiple ambient monitors, both within the local areas and around the city, to simulate fifty-four residents' personal exposure for the month of June, 2010. This required collecting timeactivity information which was carried out by door-to-door surveying. The time-activity data were transformed into microenvironment and activity codes reflecting residents movements across a typical week, which were then run through the US-EPA's Air Pollution Exposure Model (APEX). APEX is a probabilistic population exposure model for which the user sets numerous microenvironmental parameters such as Air Exchange Rates (AERs) and infiltration factors, which are used in combination with air pollutant concentrations, meteorological, and geospatial data, to calculate individuals' exposures. Simulated exposure outputs were grouped by residents' occupations and their home addresses were artificially placed at varying distances from the highways. The effects of residential proximity to the highway, occupation, work destination and commute distance were explored using a Generalised Linear Model (GLM). Surveyed residents were also asked a series of Likert-type, ordered response questions relating to their perceptions and understandings of the potential impacts of living near a significant emissions source. Their response scores were explored as a function of proximity to the highway using multivariate linear regression. This formed the final layer of this investigation into air quality throughout these South Auckland communities of Otahuhu and Mangere Bridge. Results show that concentrations of primary traffic pollutants (UFPs, NOx, CO) are elevated by 41 - 64% within the roadside corridor compared to setback distances approximately 150 m away and that the spatial extent of UFPs can reach up to 650 m downwind early in the morning and late in the evening. Further, social deprivation mapping revealed that 100% of all census meshblocks within 150 m either side of both highways are at the extreme end of the deprivation index (NZDep levels 8 - 10). Simulations for residents dispersed across the community of Otahuhu estimated daily NOx and CO exposure would increase by 32 and 37% (p<0.001) if they lived immediately downwind of the highway. If they were to shift 100 m further downwind, daily exposure would decline by 56 - 70% (p<0.001). The difference in individuals' exposure levels by occupation varied across the same distance by a factor of eight (p<0.05), with unemployed or retired persons the most exposed due to having more free time to spend outdoors at home (recreation, gardening, etc.). Those working in ventilated offices were the least exposed, even though ambient concentrations - likely due to a strong urban street canyon effect - were higher than the nearest highway monitor (5 m downwind) by 25 - 30% for NOx and CO, respectively. Inverse linear relationships were identified for distance from highway and measures of concern for health impacts, as well as for noise (p<0.05). Positive linear relationships were identified for distance from highway and ratings of both outdoor and indoor air quality (p<0.05). Measures of level of income had no conclusive statistically significant effect on perceptions (p>0.05). The main findings within this thesis demonstrate that those living within the highway corridor are disproportionately exposed to elevated long-term average concentrations of toxic air pollutants which may impact on physical health. While the socioeconomic characteristics could also heighten susceptibility to potential health impacts in these areas, certain activity patterns can help mitigate exposure. This thesis has also shown that there may be quantifiable psychological benefits of a separation buffer of at least 100 m alongside major highways. These results enhance a very limited knowledge base on the impacts of near-roadway pollution in New Zealand. Furthermore, the results lend additional support to the international literature which is working to reduce residential exposures and population exposure disparities through better policies and improved environmental planning. Where possible, the placement of sensitive population groups within highway corridors, e.g. retirement homes, social housing complexes, schools and childcare centres, should be avoided.

Face à l'urgence climatique, l’efficacité énergétique et la réduction des émissions polluantes est devenue une priorité pour l'industrie aéronautique. La précision de la modélisation des phénomènes physicochimiques joue un rôle critique dans qualité de la prédiction des émissions de suie et des gaz à effet de serre par les chambres de combustion. Dans ce contexte, des méthodes d’apprentissage profond sont utilisées pour construire des modélisations avancées des émissions de particules. Une méthode automatisée de réduction et d’optimisation de la cinétique chimique d’un combustible aéronautique réel est dans un premier temps appliquée à la simulation aux grandes échelles pour la prédiction des émissions de monoxyde de carbone. Ensuite, des réseaux de neurones sont entraînés pour simuler le comportement dynamique des suies dans la chambre de combustion et prédire la distribution de taille des particules émises<br>With the climate change emergency, pollutant and fuel consumption reductions are now a priority for aircraft industries. In combustion chambers, the chemistry and soot modeling are critical to correctly quantify engines soot particles and greenhouse gases emissions. This thesis aimed at improving aircraft numerical pollutant tools, in terms of computational cost and prediction level, for engines high fidelity simulations. It was achieved by enhancing chemistry reduction tools, allowing to predict CO emissions of an aircraft engines at affordable cost for the industry. Next, a novel closure model for unresolved terms in the LES filtered transport equations is developed, based on neural networks (NN), to propose a better flame modeling. Then, an original soot model for engine high fidelity simulations is presented, also based on NN. This new model is applied to a one-dimensional premixed sooted flame, and finally to an industrial combustion chamber LES with measured soot comparison

Les mesures ont ete faites, pres du sol, dans une region accidentee (4**(o)s-1**(o)e) de 1978 a 1984. L'aerosol est surtout constitue de composes du carbone, et sa distribution dimensionnelle est formee de 3 modes dont le plus important est centre vers 0,1 micron. Les variations et la composante submicronique sont interpretees en termes de formation et d'evolution des particules et de melanges dans l'atmosphere. Les plus petits noyaux sont formes a partir de gaz emis par la biosphere, principalement au cours de reactions photochimiques. Pendant les heures ensoleillees, la production totale est estimee a 1,8. 10**(5) cm**(-2). S**(-1). 70% des particules formees restent alors dans les vallees, mais sous le couvert forestier la production est faible, et les concentrations augmentent, en fin d'apres-midi, lorsque les melanges amenent les particules formees, le jour, en altitude

碩士<br>國立雲林科技大學<br>環境與安全衛生工程系碩士班<br>100<br>Various biomass open burnings included clearing agricultural wastes and burning joss papers commonly appeared in Taiwan. A controlled burning chamber was utilized to examine burning aerosol derived from corn stoves, miscanthus, bamboo, and two kinds of joss paper (waste paper, bamboo material). Characteristics of particle sizes, gaseous pollutants (CO, CO2), water-soluble ions, and anhydrosugars constituents have been investigated. The results have shown that differences of CO2 emission from various biomass species were limited; and the emission of CO from corn stover presented a highest value in species. The particle-size emission from all species of burning mainly distributed in PM2.5 particle, meantime, the emission concentration in fine particle obviously was influenced by the combustion efficiency of biomass burning. Levoglucosan is a major constituent of three anhydrosugars (above 90%) in the study. The ratios of Levo/Manno in three particle sizes displayed no significantly difference, but the variation of ratios was apparently in among of biomass species. Furthermore, joss paper showed a high value of Levo/PM2.5 (31.4%) rather than common plant burnings did. The emissions of major ions from plant burnings (such as corn stover, miscanthus, and bamboo) were K+, Cl -, and SO42-. The distribution of ions was highly related with the composition of materials and the process of manufacturing. The results shown a high amount of emissions (PM2.5, CO2 and CO) derived from corn stover, and which is preciously concerned. PM of Joss paper made by bamboo emitted a less emissions comparing to that of paper made by waste paper. This investigation regarding characteristics of various biomass emissions is helpful to reveal some useful information to atmospheric researches.