In this study, atmospheric levels and sources of VOCs at Aliaga industrial area was investigated. For this, VOC concentrations were measured at two monitoring stations through winter and summer campaigns in 2005 and 2006. Sampling stations were located in downtown Aliaga and downwind of industrial facilities, approximately 500 m to the south east of Horozgedigi village. After the summer sampling, another temporary station was installed in between PETKIM and T&Uuml / PRAS, named as T&Uuml / PRAS Station to generate T&Uuml / PRAS and PETKIM profiles. More than 50 species were measured in all stations. In all stations, toluene has the highest contribution to total VOC concentration. Toluene is followed by m,p-xylene and benzene. While higher concentrations of traffic related VOCs were measured at Aliaga station, VOCs from industrial solvents and industrial processes were higher at Horozgedigi station. The concentration levels in Aliaga and Horozgedigi are found to be comparable to the other industrial regions reported in the literature. Investigation of episodes, diurnal variations of VOCs and meteorological parameters showed that PETKIM and T&Uuml / PRAS emissions affect the concentrations levels at Horozgedigi and Aliaga stations. Source profiles of PETKIM and T&Uuml / PRAS are determined by using the T&Uuml / PRAS station data set. 2-methyl-hexane, benzene and 2,2,3-tri-methyl-butane+2,3-di-methyl-pentane are found to be good markers of PETKIM emissions. Ten different VOC sources were identified in the region. These were gasoline exhaust, diesel exhaust, natural gas use, gasoline evaporation, industrial emissions-1, natural gas construction, non-industrial solvent use, industrial emissions-2, PETKIM emissions, and mixed emissions from PETKIM and shipbreaking facilities.

In recent years, the air quality of Kinmen-Xiamen region has deteriorated gradually, and PM10 was always the worst air quality indicator. Particularly, high PM10 concentration has been observed in spring and winter. The objective of this study was to characterize the chemical properties of atmospheric aerosol particles sampled at Xiamen Bay located at the west coast of Taiwan Strait by sampling atmospheric particles and using chemical mass balance (CMB) receptor model for source apportionment, which indicated the difference of background and episode periods. Furthermore, this study applied HYSPLIT model to figure out the transportation routes of polluted air mass by backward trajectory. Seven particulate matter (PM) sampling sites at Xiamen Bay, three sites at Kinmen Island and four sites at metro Xiamen, were selected for this particular study. Particulate matter sampling included regular and intensive sampling. Intensive sampling was conducted to collect PM2.5 and PM2.5-10 with dichotomous samplers in the spring and winter of 2008 and 2009, while regular sampling was conducted to collect PM10 with high-volume samplers twice a month since March 2008. Results from PM sampling indicated that atmospheric particles had a tendency to accumulate in Xiamen Bay all year round, particularly in spring and winter. Five sampling sites inside the Xiamen Bay had relatively higher PM concentration than two sampling sites outside the Xiamen Bay. It suggested that local emission at the Xiamen Bay was superior to long-range transportation from the Northeastern Monson. A superimposition phenomenon was regularly observed during the episodes at Xiamen Bay. The most abundant water-soluble ionic species of PM were SO42-, NO3-, and NH4+ at Xiamen Bay, the major chemical species of PM were secondary aerosols (i.e. (NH4)2SO4 and NH4NO3). Crustal elements (e.g. Ca, Mg, Fe, and Al) and anthropogenic elements (e.g. Zn and Pb) dominated the chemical species of particles. Backward trajectory results indicated that polluted air mass originated from Asian continent moved directly to Kinmen-Xiamen region in winter and spring, while air mass originated from the southwestern and southeastern ocean did not pass polluted region in summer, which result in better air quality of Kinmen-Xiamen region in summer than those in winter and spring. Results from CMB receptor modeling showed that the major sources of atmospheric PM10 at Kinmen-Xiamen region were soil dust, secondary aerosol, petroleum industry, motor vehicle exhanst, iron and steel industry, cement industry, Diesel vehicle exhanst marine aersols, and vegetative burning. The stationary sources were the major contributor accounting for approximately 50% of PM10 in Kinmen. It suggested that atmospheric particles were mainly originated from cross-boundary transport rather than local emission sources since there are no such kinds of industrial factories in Kinmen.

Both long-term and short-term exposure to fine particulate matter (PM2.5) has been shown to increase the rate of respiratory and cardiovascular illness, premature death, and hospital admissions from respiratory causes. It is important to understand what contributes to ambient PM2.5 level to establish effective regulation, and air quality model can provide guidance based on the best scientific understanding available. However, PM2.5 simulations in air quality models have often found performance less than desirable, particularly for organic carbon levels. Here, some of major shortcomings of current air quality model will be addressed and improved by using CMAQ, receptor models, and regression analysis. Detailed source apportionment of PM2.5 performed using the CMAQ-tracer method suggests that wood combustion and mobile sources are the largest sources of PM2.5, followed by meat cooking and industrial processes. Biases in emission estimates are investigated using tracer species, such as organic molecular markers and trace metals that are used in receptor models. Comparison of simulated and observed tracer species shows some consistent discrepancies, which enables us to quantify biases in emissions and improve CMAQ simulations. Secondary organic aerosol (SOA) is another topic that is investigated. CMAQ studies on organic aerosol usually underestimate organic carbon with larger than a 50% bias. Formation of aged aerosol from multigenerational semi-volatile organic carbon is added to CMAQ, significantly improving performance of organic aerosol simulations.

Pollution studies have sought to understand the relationships between adverse health effects and harmful exposures. Many environmental health studies are predicated on the idea that each exposure has both acute and long term health effects that need to be accurately mapped. Considerable work has been done linking air pollution to deleterious health outcomes but the underlying biological pathways and contributing sources remain difficult to identify. There are many statistical issues that arise in the exploration of these longitudinal study designs such as understanding pathways of effects, addressing missing data, and assessing the health effects of multipollutant mixtures. To this end this dissertation aims to address the afore mentioned statistical issues. Our first contribution investigates the mechanistic pathways between air pollutants and measures of cardiac electrical instability. The methods from chapter 1 propose a path analysis that would allow for the estimation of health effects according to multiple paths using structural equation models. Our second contribution recognizes that panel studies suffer from attrition over time and the loss of data can affect the analysis. Methods from Chapter 2 extend current regression calibration approaches by imputing missing data through the use of moving averages and assumed correlation structures. Our last contribution explores the use of factor analysis and two-stage hierarchical regression which are two commonly used approaches in the analysis of multipollutant mixtures. The methods from Chapter 3 attempt to compare the performance of these two existing methodologies for estimating health effects from multipollutant sources.

Atmospheric aerosols have been shown to have a significant impact on air quality and health in urban environments. Organic aerosols (OA) are one of the main constituents of submicron particulate matter. They are composed of thousands of different chemical species, which makes it challenging to identify and quantify their sources. OA sources have been previously studied; however quantitative knowledge of aerosol composition and their processes in urban environments is still limited. The results presented here investigate OA, their chemical composition and sources as well as their interaction with gases. On-line measurements of species in the particle and the gas phase were performed both from field-based and laboratory studies. Aerosol Mass Spectrometers (AMS) were used together with the Chemical Ionisation Mass Spectrometer (CIMS) and the Filter Inlet for Gases and AEROsols (FIGAERO). Two ambient datasets were analysed to develop methods for source apportionment, using the Multilinear Engine (ME-2), in order to gain new insights into aerosol sources in Manchester and London. Long-term measurements in London allowed the opportunity to perform seasonal analysis of OA sources and look into the relationship of hydrogen-like OA (HOA) and heavy- and light-duty diesel emissions. The seasonal analysis provided information about OA sources that was not possible to observe on the long-term analysis. During Bonfire Night in Manchester, with high aerosol concentrations, particularly biomass burning OA (BBOA), it was possible to identify particulate organic oxides of nitrogen (PON), with further identification of primary and secondary PON and their light absorbing properties. Through laboratory work, new insights into cooking organic aerosols (COA) were gained, a higher relative ion efficiency (RIEOA) value of around 3.3 for OA-AMS compared with the typical RIEOA of 1.4 was determined, which implies COA concentrations are overestimated when using the RIEOA value of 1.4. Dilution showed to have a significant effect on food cooking experiments, increasing both the gas/particle ratios and the O:C ratios. The data generated in this work, OA-AMS mass spectra and markers from both gas and particle phase identified with FIGAERO-CIMS, provide significant information that will contribute to the improvement of source apportionment in future studies. This work investigates OA, with a focus on primary organic aerosols originated from anthropogenic activities. These scientific findings increase our understanding of OA sources and can help to improve inventories and models as well as to develop plans and policies to mitigate the air pollution in urban environments.

Les hydrocarbures aromatiques polycycliques (HAP) sont des composés organiques présents dans l’ensemble des compartiments environnementaux. Dans l’atmosphère, leurs sources sont à la fois naturelles (feux de biomasse, éruptions volcaniques) et anthropiques (industrie, transport, chauffage résidentiel). Une fois émis, sous forme gazeuse ou adsorbés à la surface de particules atmosphériques, les HAP sont susceptibles d’être impliqués dans des processus physico-chimiques tels que la photodégradation et/ou des réactions d’oxydation avec différentes espèces radicalaires. Du fait de leur toxicité avérée, ces composés font l’objet de différentes réglementations, législations françaises et européennes. Concernant le compartiment atmosphérique, seul le benzo(a)pyrène présente aujourd’hui des seuils d’émission à respecter. Afin de faire évoluer ces textes et de mettre en place des mesures de réduction d’émissions, diverses approches ont été développées dans le but de différencier leurs sources dans l’atmosphère. L’approche moléculaire, basée sur les profils moléculaires et les rapports de concentrations, permet d’apporter des informations quant à leurs origines. En revanche, elle souffre de biais induits par les conditions de formation des HAP (température, conditions environnementales…) et par les processus physico-chimiques dans lesquels ils sont impliqués. L’objectif principal de ce travail est de mettre en place une méthodologie de traçage de sources des HAP particulaires par une approche isotopique. Le développement du protocole analytique a été réalisé pour déterminer la composition isotopique moléculaire des HAP particulaires par GC/C/IRMS. Il a été montré que la réactivité des HAP sous l’action d’oxydants (O3, NO2, OH) et/ou de la lumière solaire n’induisait pas de variation significative de la composition isotopique moléculaire des HAP. Cette méthodologie a ainsi pu être appliquée sur des échantillons naturels, prélevés sur des sites caractérisés par des sources spécifiques. Il a été montré que les 13C/12C des HAP, en complément de données moléculaires, permettent de différencier les origines de ces composés. Par exemple, les caractéristiques moléculaires et isotopiques de HAP issus de la combustion de plusieurs espèces de bois d’origine méditerranéenne ont été déterminées en appliquant cette méthodologie à des échantillons collectés directement à l’émission. Enfin, dans le cadre de l’étude de la pollution et de ses impacts dans le Bassin d’Arcachon, les apports atmosphériques en HAP ont été mesurés par l’approche moléculaire couplée à d’autres outils (rétrotrajectoires, oxydants, roses des vents…) afin de compléter le diagnostic environnemental. / Polycyclic Aromatic Hydrocarbons (PAH) are carcinogenic compounds, present in all the compartments of the Environment. In the atmosphere, their sources are both from natural (biomass burning, volcanic emissions...) and anthropogenic (transport, industry, residential heating...) origins. Once emitted in the atmosphere, PAH are distributed between the gaseous or particulate phases and may be involved in different physico-chemical processes such as photodegradation, radical-initiated oxidations... Due to their carcinogenicity, PAH emissions are nowadays subjected to various regulations from France and more largely, European Union. In the atmosphere, benzo(a)pyrene has been selected as representative of the PAHs because of its high toxicity. In order to improve regulations involving emission reductions, several methodologies have been developed to perform source apportionment. The most commonly used in the literature is the molecular approach, based on molecular profiles and particular ratios. Nevertheless, conditions of PAH formation and physico-chemical processes affect these characteristic values. The main objective of this work was to develop a new methodology of particulate-PAH source tracking based on the molecular isotopic composition. The development of analytical procedure was performed to determine 13C/12C of PAHs by GC/C/IRMS. The study of the impact of PAH reactivity in the presence of O3, NO2, OH and/or solar radiations shows that no significant isotopic fractionation is induced on their isotopic compositions. Molecular isotopic approach was applied on natural particles, collected at different specific sites: 13C/12C of PAHs and molecular data allow differentiating particulate-PAH sources. Therefore, determinations of molecular and isotopic characteristics have been undertaken by applying this methodology on particulate-PAHs emitted during the combustion of fifteen Mediterranean woods. Finally, molecular approach coupled with different parameters (back-trajectories, oxidant concentrations, wind roses...) enables to measure the levels of PAH concentrations in the atmosphere in order to evaluate their impacts as a source of pollution in the Arcachon Bay.

No description available.

This research uses Bayesian analysis of fluorescence spectroscopy results to determine if wastewater from the Heber Valley Special Service District (HVSSD) lagoons in Midway, UT has seeped into the adjacent Provo River. This flow cannot be directly measured, but it is possible to use fluorescence spectroscopy to determine if there is seepage into the river.Fluorescence spectroscopy results of water samples obtained from HVSSD lagoons and from upstream and downstream in the Provo River were used to conduct this statistical analysis. The fluorescence 'fingerprints' for the upstream and lagoon samples were used to deconvolute the two sources in a downstream sample in a manner similar to the tools and methods discussed in the literature and used for source apportionment of air pollutants. The Bayesian statistical method employed presents a novel way of conducting source apportionment and identifying the existence of pollution.This research demonstrates that coupling fluorescence spectroscopy with Bayesian statistical methods allows researchers to determine the degree to which a water source has been contaminated by a pollution source. This research has applications in determining the affect sanitary wastewater lagoons and other lagoons have on an adjacent river due to groundwater seepage. The method used can be applied in scenarios where direct collection of hydrogeologic data is not possible. This research demonstrates that the Bayesian chemical mass balance model presented is a viable method of performing source apportionment.

The expanding urbanisation, growing population, and industrial development are threatening global surface water quality. With increasing concern about surface-water quality, it is crucial to deeply understand the evolution of surface-water quality problems and comprehensively de-termine its fundamental driving forces. In this Dissertation, systematic work on the mechanisms of water pollution with trace elements has been carried out in three steps: i) to identify the sources contributing to surface water pollution by receptor-based models, ii) to determine the factors dominating the pollution risk transmission from sources to surface water by a source-based model, and iii) to capture the primary driving forces to the spatiotemporal variation in surface water pollution by Bayesian-based approaches. The following specific topics were ad-dressed based on five publications: a) The temporal trends of trace metal pollution in the surface water were characterised by the Mann-Kendall test and the Generalised Additive Model. b) The primary source contributors to the long-term trace metal pollution in a river system were determined by the Self-organised Map, Positive Matrix Factorization receptor model, and Bayesian multivariate receptor model. The distributions of the source contributions to trace metal pollution were estimated. c) The risk transmission of trace pollutants in the surface water was estimated by a source-based dynamic model. The sensitivities of the risk to human activities, characteristics of wastewater treatment plants, and river flow regimes were evaluated. d) The contributions of hydro-chemical factors, climate impact, and sampling methods to water pollution and data uncertainty were analysed by the Wavelet Analysis and Bayesian Net-work. Both the models’ accuracy and robustness were evaluated by statistical analysis. The methods and results provided herein could improve the standard of statistical rigour and support the authorities’ decision-making.

The Mexico City Metropolitan Area (MCMA) is one of the largest cities in the world, and as with many megacities worldwide, it experiences serious air quality and pollution problems, especially with ozone and particulate matter. Ozone levels exceed the health-based standard, which is equivalent to the U.S. standard, on approximately 80% of all days, and concentrations of particulate matter 10 μm and smaller (PM10) exceed the standard on more than 40% of all days in most years. Particulate polycyclic aromatic hydrocarbons (PAHs) are a class of semi-volatile compounds that are formed during combustion and many of these compounds are known or suspected carcinogens. Recent studies on PAHs in Mexico City indicate that very high concentrations have been observed there and may pose a serious health hazard. The first part of this thesis describes results from the Megacities Initiative: Local and Regional Observations (MILAGRO) study in Mexico City in March 2006. During this field campaign, we measured PAH and aerosol active surface area (AS) concentrations at six different locations throughout the city using the Aerodyne Mobile Laboratory (AML). The different sites encompassed a mix of residential, commercial, industrial, and undeveloped land use. The goals of this research were to describe spatial and temporal patterns in PAH and AS concentrations, to gain insight into sources of PAHs, and to quantify the relationships between PAHs and other pollutants. We observed that the highest measurements were generally found at sites with dense traffic networks. Also, PAH concentrations varied considerably in space. An important implication of this result is that for risk assessment studies, a single monitoring site will not adequately represent an individual's exposure. Source identification and apportionment are essential for developing effective control strategies to improve air quality and therefore reduce the health impacts associated with fine particulate matter and PAHs. However, very few studies have separated gasoline- versus diesel-powered vehicle emissions under a variety of on-road driving conditions. The second part of this thesis focuses on distinguishing between the two types of engine emissions within the MCMA using positive matrix factorization (PMF) receptor modeling. The Aerodyne Mobile Laboratory drove throughout the MCMA in March 2006 and measured on-road concentrations of a large suite of gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitric oxide (NO), benzene (C6H6), formaldehyde (HCHO), ammonia (NH3), fine particulate matter (PM2.5), PAHs, and black carbon (BC). These pollutant species served as the input data for the receptor model. Fuel-based emission factors and annual emissions within Mexico City were then calculated from the source profiles of the PMF model and fuel sales data. We found that gasoline-powered vehicles were responsible for 90% of mobile source CO emissions and 85% of VOCs, while diesel-powered vehicles accounted for almost all of NO emissions (99.98%). Furthermore, the annual emissions estimates for CO and VOC were lower than estimated during the MCMA-2003 field campaign. The number of megacities is expected to grow dramatically in the coming decades. As one of the world's largest megacities, Mexico City serves as a model for studying air quality problems in highly populated, extremely polluted environments. The results of this work can be used by policy makers to improve air quality and reduce related health risks in Mexico City and other megacities. / Master of Science