The diploma thesis deals with the determination of sources of polycyclic aromatic hydrocarbons (PAH) and the changes in the PAH concentrations during the last 11 years, from 2006 to 2016. The data were sampled at National Atmospheric Observatory in Košetice, a representative station for the Central European Region. Multidimensional statistical methods as Positive Matrix Factorization (PMF), conditional bivariate probability function (CBPF), and Potential Source Contribution Function (PSCF) were used for data analyses. In the first part, the changes in concentrations of the four specific PAH, Benzo(a)pyrene (BaP), Fluoranthene (FLA), the sums of all the PAH (SUMA), and the Toxical Equivalent (TEQ) was studied. The highest concentration of all four specific PAH was detected at the beginning of the studied period. The immission limit for BaP was not exceeded. Statistically significant decreasing trend for BaP, TEQ, and SUMA PAH was identified. Second part of the thesis studied the PAH source apportionment. The study proved that the station was strongly influenced by the local domestic heating on one hand, and long-distance transportation from the west, and specifically from the northwest on the other hand. The influence of long-distance transport has an increasing trend over time, vice-versa for the...

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Texas is the second largest state in U.S.A. based on geographical area, population and the economy. It is home to several large coastal urban areas with major industries and infrastructure supporting the fossil-fuel based energy sector. Most of the major cities on the state have been impacted by significant air pollution events over the past decade. Studies conducted in the southern coastal region of TX have identified long range transport as a major contributor of particulate matter (PM) pollution along with local emissions. Biomass burns, secondary sulfates and diesel emissions sources are comprise as the dominant mass of PM2.5 have been noted to be formed by the long range transport biomass from Central America. Thus, the primary objective of this study was to identify and quantify local as well as regional sources contributing to the PM pollution in the coastal area of Brownsville located along the Gulf of Mexico. Source apportionment techniques such as principal component analysis (PCA) and positive matrix factorization (PMF) were employed on the air quality monitoring data to identify and quantify local and regional sources affecting this coastal region. As a supplement to the PMF and PCA, conditional probability function (CPF) analysis and potential source contribution function (PSCF) analysis were employed to characterize the meteorological influences for PM events. PCA identified an optimal solution of 6 sources affecting the coastal area of Brownsville, while PMF resolved 8 sources for the same area. Biomass comingled with sea salt was identified to be the dominant contributor from the PCA analysis with 30.2% of the apportioned PM mass in Brownsville, meanwhile PMF account secondary sulfates I & II with 27.6%. the other common sources identified included, biomass burning, crustal dust, secondary sulfate, oil combustion, mobile sources and miscellaneous traffic sources.

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L'objectif de cette thèse est le développement et la validation d'un modèle numérique de la dynamique des particules en mélange externe et résolu en taille. Afin de suivre plusieurs compositions chimiques par classe de tailles, une nouvelle approche est présentée dans laquelle la composition chimique des particules est elle-même discrétisée suivant la fraction d'un ou plusieurs des constituants chimiques (e.g. suie, sulfate). Cette approche a pour but de mieux simuler l'évolution d'une population de particules à l'échelle locale et de particulariser des compositions chimiques typiques de certaines sources. Dans l'atmosphère, les particules interagissent essentiellement entre elles et avec les polluants gazeux par coagulation et condensation/évaporation. La première partie de la thèse a été consacrée à l'élaboration du modèle pour la coagulation, processus physique qui s'avère le plus complexe à modéliser selon notre approche du mélange externe. Dans un premier temps, les équations de la coagulation en mélange externe sont présentées et discrétisées suivant un nombre arbitraire de classe de tailles et de compositions chimiques. Plusieurs simulations numériques ont ensuite été effectuées avec ce modèle sur un même cas d'étude, en utilisant deux, trois et quatre composants chimiques. On vérifie à chaque fois que les résultats de la simulation numérique en mélange externe sont cohérents avec ceux du mélange interne du cas d'étude. Les résultats de ces simulations permettent d'apprécier l'effet de mélange de la coagulation qui produit, à partir de particules monocomposées, des particules bicomposées et tricomposées. Étant donné la complexité croissante d'un tel modèle, une attention toute particulière a été portée à l'implémentation numérique et à l'optimisation des algorithmes choisis. L'extension de cette approche à la condensation/évaporation constitue le prochain développement de ce modèle, nous en posons les bases théoriques en annexe. S'il existe aujourd'hui des données de mesure résolues en taille (SMPS), il n'y en a pas encore qui puissent être réellement validantes pour ce modèle de mélange externe, c'est-à-dire qui distinguent quantitativement plusieurs compositions chimiques par classe de taille. Aussi, dans la seconde partie de la thèse, nous avons envisagé le protocole d'une expérience en chambre permettant de mettre en évidence le mélange par coagulation de deux populations de particules de compositions différentes et d'apporter des données validantes pour le modèle développé. Deux séries d'expériences ont été menées, la première dans la chambre de grand volume CESAM et la seconde, dans le réacteur de petit volume de l'INERIS. La première série a mis en évidence l'homococagulation de chaque distribution polydispersée prise séparément et dans une moindre mesure, l'hétérocoagulation des deux distributions de nature différentes (NaBr et KBr) entre elles. La seconde série a montré la possibilité d'observer simultanément deux distributions monodispersées de particules de compositions différentes (CaSO4 et KBr), prérequis pour ce cas. Au final, les résultats de mesure se sont avérés insuffisants pour produire des données validantes pour le modèle, à cause du trop grand écart-type des distributions polydispersées dans la chambre de grand volume et à cause du dépôt au paroi qui domine dans le réacteur de petit volume. Des analyses au microscope électronique ont cependant attesté de la présence de particules issues de la coagulation entre les deux natures. A la suite des différentes expériences menées, nous revenons sur le protocole envisagé et proposons quelques pistes d'améliorations / The objective of this thesis is the development and validation of a numerical size resolved and externally mixed model of the particle dynamics. In order to trace several chemical compositions for each size class, a new approach is presented in which the particle chemical composition is itself discretized according to the mass fraction of one or several of its components (e.g. soot, sulfate). This approach aims to improve the simulation of the particle population evolution at local scale and to emphasize chemical compositions which are specific to some sources. In atmosphere, particles interacts essentially between themselves and gaseous pollutants through coagulation and condensation/evaporation. The first part of this thesis is dedicated to the model development for the coagulation process, which happens to be the most complex to model with our external mixing approach. First, coagulation equations in external mixing were set up and discretized with an arbitrary number of size and chemical composition classes. Several numerical simulations were then performed with this model according to the same case 6 study, using two, three and four chemical components. We checked each time that the simulation results in external mixing agreed well with those of the case study internal mixing. The results of these simulations are useful to understand how coagulation mix particles and produces, from monocomposed ones, bicomposed and tricomposed particles. Given the growing complexity of such a model, the numerical implementation has been carried out with carefullness and algorithms have been optimized. The extension of this approach to condensation/evaporation is the next development step of this model, the theoretical basis are adressed in appendix. Size resolved particle measurements (SMPS) do exist nowadays, but truely suitable data to validate the external mixing model still lack, that is to say measurements which would quantitatively distinguish several chemical compositions per size class. That is why, in the second part of this thesis, we considered the protocol of a chamber experiment allowing to highlight the mixing by coagulation of two particle populations with distinct compositions and to bring validating data for the model developed. Two series of experiments were conducted, the first one with the CESAM large volume chamber and the second, with the small reactor of INERIS. The first serie underlined the homocoagulation of each polydispersed distribution taken separately and to a lower extent, the heterocoagulation of the two distributions of different kinds (NaBr et KBr) between themselves. The second serie showed the possibility to observe simultaneously two monodispersed distributions of particles with different compositions (CaSO4 et KBr), which was required in this case. Finally, measurement results happened to be insufficiant to produce validating data for the model, because of the great deviation of polydispersed distributions in the large volume chamber and because of the dominating wall losses in the small reactor. However, some microscope electronic analysis showed evidences of particles produced from coagulation between both kind of particles. Further to these experiments, we come back to the planed protocol and propose some improvements

A year-long study was conducted in Pinal County, Arizona to characterize fine and coarse particulate matter as a means of furthering our understanding of ambient concentrations and composition in rural, arid environments. Detailed measurement of ambient fine and coarse mass, ion, metal, and carbon concentrations at one-in-six day resolution was conducted at three sites from February 2009 to February 2010. Detailed organic carbon speciation was collected at 5-week resolution. A series of samples representing native soil, agricultural soil, road dust, and cattle feed lot material was collected, resuspended in the laboratory, and analyzed to provide a chemical source profile for each soil type yielding insights into unique source signatures. Observations within the chemical speciation data and subsequent modeling analysis show a strong impact from local sources at the Cowtown site where mass concentrations are highest. Source apportionment results confirm the significant impact from the cattle feedlot adjacent to the site. Chemical analysis of ambient particles and local feedlot material shows the presence of chemical marker species including phosphate which is unique to this source. Fugitive dust is a significant contributor to ambient particulate matter concentrations at all monitoring locations. Seasonal observations show higher concentrations during tilling and harvesting indicating the large role agricultural sources play on particle concentrations in this area. Chemical characterization and modeling show that re-entrained road dust is a significant factor. Fine particle modeling results indicate that concentrations are influenced significantly by motor vehicles including impacts from direct emissions including brake wear and indirect emissions including resuspended road dust. A significant fraction is also associated with crustal sources while about 5 g/m3 appears to be transported into the region from beyond the air shed. Detailed analysis of the local monsoon season indicates that monsoon rains serve to clean the atmosphere resulting in a marked decrease in ambient coarse mass and resulted in a period where local coarse PM concentrations measured at all sites became more uniform. The monsoon season also featured localized high wind events which severely increased coarse PM concentrations and often caused exceedences of the PM National Ambient Air Quality Standard.

A year-long study was conducted in Pinal County, Arizona to characterize fine and coarse particulate matter as a means of furthering our understanding of ambient concentrations and composition in rural, arid environments. Detailed measurement of ambient fine and coarse mass, ion, metal, and carbon concentrations at one-in-six day resolution was conducted at three sites from February 2009 to February 2010. Detailed organic carbon speciation was collected at 5-week resolution. A series of samples representing native soil, agricultural soil, road dust, and cattle feed lot material was collected, resuspended in the laboratory, and analyzed to provide a chemical source profile for each soil type yielding insights into unique source signatures. Observations within the chemical speciation data and subsequent modeling analysis show a strong impact from local sources at the Cowtown site where mass concentrations are highest. Source apportionment results confirm the significant impact from the cattle feedlot adjacent to the site. Chemical analysis of ambient particles and local feedlot material shows the presence of chemical marker species including phosphate which is unique to this source. Fugitive dust is a significant contributor to ambient particulate matter concentrations at all monitoring locations. Seasonal observations show higher concentrations during tilling and harvesting indicating the large role agricultural sources play on particle concentrations in this area. Chemical characterization and modeling show that re-entrained road dust is a significant factor. Fine particle modeling results indicate that concentrations are influenced significantly by motor vehicles including impacts from direct emissions including brake wear and indirect emissions including resuspended road dust. A significant fraction is also associated with crustal sources while about 5 g/m3 appears to be transported into the region from beyond the air shed. Detailed analysis of the local monsoon season indicates that monsoon rains serve to clean the atmosphere resulting in a marked decrease in ambient coarse mass and resulted in a period where local coarse PM concentrations measured at all sites became more uniform. The monsoon season also featured localized high wind events which severely increased coarse PM concentrations and often caused exceedences of the PM National Ambient Air Quality Standard.

Fine particulate matter (PM2.5) has been associated with adverse effects on human health, but whether specific components of PM2.5 are responsible for specific health effects is still under investigation. The complex chemical composition of PM2.5 and issues such as multi-component interactions, spatial variability and sampling/instrument error further complicates this analysis. A complementary approach to examining species-specific associations is to assess associations between health outcomes and sources contributing to PM2.5, which can provide critical information to regulators to tighten controls on sources that contribute most to adverse health effects and allows for better multi-pollutant epidemiologic analyses, as the number of source-categories is typically far less than the number of PM2.5 species. This study develops and evaluates various air quality modeling approaches for determining daily source contributions to ambient PM2.5. Results from long-term air quality simulations using an emissions-based model (Models-3/CMAQ - Community Multiscale Air-Quality model) were evaluated in terms of the model's ability to simulate short-term (e.g., daily) variability in concentrations of PM2.5 components. To examine source-specific health outcomes, an extended PM2.5 source-apportionment model, CMB-LGO (Chemical Mass Balance incorporating the Lipschitz Global Optimizer) was developed and compared with results based on other approaches such as CMB, PMF (Positive Matrix Factorization), and Models-3/CMAQ in terms of simulating the daily variability of source impacts. Based on findings from spatial and temporal analyses of tracer concentrations and source impacts, PM2.5 source-apportionment results from CMB-LGO and PMF were applied in a health-study for the Atlanta area. Despite methodological differences and uncertainties in the apportionment process, good agreement was observed between the CMB-LGO and PMF based risk ratios, indicating to the usefulness of applying apportionment methods in health studies.

This study investigated the source attribution of ship emissions to atmospheric particulate matter with a median aerodynamic diameter less than, or equal to 2.5 micron (PM2.5) in the port city of Halifax, Nova Scotia, Canada. The USEPA PMF model successfully determined the following sources with the average mass (percentage) contribution: Sea salt 0.147 µg m-3 (5.3%), Surface dust 0.23 µg m-3 (8.3%), LRT Secondary (ammonium sulfate) 0.085 µg m-3 (3.1%), LRT Secondary (nitrate and sulfate) 0.107 µg m-3 (3.9%), Ship emissions 0.182 µg m-3 (6.6%), and Vehicles and re-suspended gypsum 2.015 µg m-3 (72.8%). A good correlation was achieved between PM2.5 total mass predicted and observed with R2 = 0.83, bias = -0.23, and RMSE = 0.09 µg m-3. In addition, a 2.5 times (60%) reduction in sulfate was estimated, when compared to 2006-2008 Government data in Halifax.

Dallas is the third largest growing industrialized city in the state of Texas. the prevailing air quality here is highly influenced by the industrialization and particulate matter 2.5µm (PM2.5) has been found to be one of the main pollutants in this region. Exposure to PM2.5 in elevated levels could cause respiratory problems and other health issues, some of which could be fatal. the current study dealt with the quantification and analysis of the sources of emission of PM2.5 and an emission inventory for PM2.5 was assessed. 24-hour average samples of PM2.5 were collected at two monitoring sites under the Texas Commission on Environmental Quality (TCEQ) in Dallas, Dallas convention Centre (CAMS 312) and Dallas Hinton sites (CAMS 60). the data was collected from January 2003 to December 2009 and by using two positive matrix models PMF 2 and EPA PMF the PM2.5 source were identified. 9 sources were identified from CAMS 312 of which secondary sulfate (31% by PMF2 and 26% by EPA PMF) was found to be one of the major sources. Data from CAMS 60 enabled the identification of 8 sources by PMF2 and 9 by EPA PMF. These data also confirmed secondary sulfate (35% by PMF2 and 34% by EPA PMF) as the major source. to substantiate the sources identified, conditional probability function (CPF) was used. the influence of long range transport pollutants such as biomass burns from Mexico and Central America was found to be influencing the region of study and was assessed with the help of potential source contribution function (PSCF) analysis. Weekend/weekday and seasonal analyses were useful in understanding the behavioral pattern of pollutants. Also an inter comparison of the model results were performed and EPA PMF results was found to be more robust and accurate than PMF 2 results.