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Peña, Sanchez Carlos Alberto. "Quantification of Anthropogenic and Natural Sources of Fine Particles in Houston, Texas Using Positive Matrix Factorization." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc149652/.
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Texas, due to its geographical area, population, and economy is home to a variety of industrialized areas that have significant air quality problems. These urban areas are affected by elevated levels of fine particulate matter (PM2.5). The primary objective of this study was to identify and quantify local and regional sources of air pollution affecting the city of Houston, Texas. Positive Matrix Factorization (PMF) techniques were applied to observational datasets from two urban air quality monitoring sites in Houston from 2003 through 2008 in order to apportion sources of pollutants affecting the study region. Data from 68 species for Aldine and 91 for Deer Park were collected, evaluated, and revised to create concentration and uncertainty input files for the PMF2 and EPA PMF (PMF3) source apportionment models. A 11-sources solution for Aldine and 10-sources for Deer Park were identified as the optimal solutions with both models. The dominant contributors of fine particulate matter in these sites were found to be biomass burnings (2%-8.9%), secondary sulfates I (21.3%-7.6%) and II (38.8%-22.2%), crustal dust (8.9%-10.9%), industrial activities (10.9%-4.2%), traffic (23.1%-15.6%), secondary nitrates (4.4%-5.5%), fresh (1%-1.6%) and aged(5.1%-4.6%) sea salt and refineries (1.3%-0.6%), representing a strong case to confirm the high influence of local activities from the industrial area and the ship channel around the Houston channel. Additionally, potential source contribution function (PSCF) and conditional probability function (CPF) analyses were performed to identify local and regional source-rich areas affecting this urban airshed during the study period. Similarly, seasonal variations and patterns of the apportioned sources were also studied in detail.
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Ciani, Renato. "Um estudo de sensibilidade da fatoração PMF - Positive Matrix Factorization - em relação às medidas de incerteza das variáveis." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-07092017-165948/.
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A fatoração PMF - Positive Matrix Factorization - é um método de resolução de problemas em que variáveis observadas conjuntamente são modeladas como a combinação linear de fatores potenciais, representada pela multiplicação de duas matrizes. Este método tem sido utilizado principalmente em áreas de estudo em que as variáveis observadas são sempre não negativas, e quando é aplicada uma modelagem fatorial ao problema. Assume-se a premissa de que são resultantes da multiplicação de duas matrizes com entradas não negativas, ou seja, os fatores potenciais, e os poderadores da combinação linear são desconhecidos, e têm valores não negativos. Neste método além da possibilidade de restringir a busca dos valores das matrizes da fatoração a valores não negativos, também é possível incluir a medida de incerteza relacionada a cada observação no processo de obtenção da fatoração como um modo de reduzir o efeito indesejado que valores outliers podem causar no resultado. Neste trabalho é feito um estudo de sensibilidade da fatoração PMF em relação a algumas medidas de incertezas presentes na literatura, utilizando o software EPA PMF 5.0 com ME-2. Para realizar este estudo foi desenvolvida uma metodologia de simulação de base de dados a partir de perfis de fontes emissoras conhecidas incluindo valores outliers, e aplicação sequencial da fatoração PMF com o software ME-2 nas bases de dados simuladas.The PMF factorization - Positive Matrix Factorization - is a problem solving method in which jointly observed variables are modeled as a linear combination of potential factors, represented by the multiplication of two matrices. This method has been used primarily in study areas in which the observed variables are always non negative, and when it is applied a factor modeling in the problem. It is made the assumption that the variables in study come from the two matrices multiplication both having non negative components, i.e., the potential factors, and the linear combination values are unknown, and all of them have non negative values. In this method, besides the possibility of constraining the search of the matrix factorization values on non negative values, it is also possible to include the uncertainty measure related to each observation on factorization process as a way to reduce the undesired effect which outliers can cause to the outcome. This paper presents a study of the sensitivity of the factorization PMF over some uncertainties measures present in literature, using EMP PMF 5.0 with ME-2 software. To carry out this study was developed a methodology of database simulation from known emitting sources profiles including outliers values, and a sequential application of PMF factorization with ME-2 software in simulated databases.
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Scerri, Mark. "The use of Positive Matrix Factorization (PMF) in source apportionment of ambient aerosol in the Central Mediterranean." Phd thesis, Digilabs srls, 2019. https://tuprints.ulb.tu-darmstadt.de/9172/13/Mark%20Scerri%20Cumulative%20thesis%20copy%20Signed.pdf.
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Positive Matrix Factorization (PMF) is a widely used receptor modelling technique in order to determine the nature and contribution of the different aerosol sources modulating ambient levels of particulate matter at a receptor. This cumulative thesis together with the papers included within, reports the results of three source apportionment exercises: a) the isolation of the natural contribution to PM10 levels at a rural background site in Malta; b) the estimation of the contributions of the sources driving PM2.5 levels at a traffic hotspot in Malta and c) a methodological investigation of how PMF can be used on a smaller dataset using samples taken from an agricultural area in Apulia, South eastern Italy.
The study on the magnitude of the natural contribution to PM10 involved a sampling campaign at a rural background station in Għarb, Gozo (one of the islands in the Maltese archipelago). This sampling campaign resulted in the collection 224 samples, which were subsequently characterised by inductively coupled plasma mass spectrometry (ICP – MS) and ion chromatography (IC) respectively for, their metallic and ionic content. The use of data resulting from this analysis with PMF resulted in the isolation of the two natural sources expected to be of relevance to Malta (marine aerosol and Saharan dust) as well as in the estimation of their apportionment. PMF also resolved three additional sources: a local crustal source, and two secondary inorganic aerosol components (one rich in nitrate and the other rich in sulfate). The natural sources jointly accounted for approximately 39% of the measured PM10, which is at the upper end of the 0.5 – 58% range determined by previous studies for natural contributions in Europe.
A total of 180 membranes sampled throughout 2016 were used in the study on the sources of PM2.5 at a traffic site. These membranes were analysed for: elemental concentrations (using X-ray fluorescence spectroscopy, XRF); ionic content (using IC) and for black carbon – BC (using an optical method). The use of this chemical database with PMF resulted in the isolation of 7 aerosol sources, 4 of which were common to the exercise carried out on PM10 at the rural background site (all the sources except for the local crustal source). The additional three sources isolated at this site were traffic, shipping and fireworks. The isolation of the latter component is itself an interesting result, because it shows that a seasonal activity such as the letting of fireworks during the summer village feasts affects the annual levels of PM2.5. Additionally, this component probably has an effect on human health due to its chemical composition. This work will also provide evidence-based information to the policy makers on the emission reductions required in order for the PM2.5 levels to be compliant with the annual air quality guideline issued by the World Health Organization.
Finally, a fundamental methodological investigation on how PMF can be used on a small dataset was carried out. This study is based on 29 PM10 and 33 PM2.5 samples collected from a rural area in Apulia, Italy. PMF did not work correctly when the datasets for the two different fractions were used separately. The datasets were therefore aggregated into a single chemical database of 62 samples and this was then used with PMF. A 5-factor model, which exhibited a fairly good rotational stability was the result of this modelling exercise. This was subsequently further improved through the imposition of constraints based on the chemical constitution of the aerosol sources affecting this receptor, which is made possible by the new features included in the United States Environment Protection Agency PMF version 5. Given the size of the dataset the, the uncertainties in the solution returned by PMF were fully characterised using all the error estimation methodologies included in this version of PMF. Additionally, the results of the PMF modelling were validated against those returned by two other models, Constrained Weighted Non-negative Matrix Factorization (CW – NMF) and Chemical Mass Balance (CMB) as well as through the use of other statistical parameters. These results essentially confirm the validity of the model returned by PMF and indicate that the latter model extracted all the information about the aerosol sources affecting the receptor from the speciation data.
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Lingwall, Jeff W. "Bayesian and Positive Matrix Factorization approaches to pollution source apportionment /." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1295.pdf.
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Scerri, Mark [Verfasser], Stephan [Akademischer Betreuer] Weinbruch, and Konrad [Akademischer Betreuer] Kandler. "The use of Positive Matrix Factorization (PMF) in source apportionment of ambient aerosol in the Central Mediterranean / Mark Scerri ; Stephan Weinbruch, Konrad Kandler." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2019. http://d-nb.info/1199006483/34.
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Oroumiyeh, Farzan. "Temporal Interpolation Modeling of Cincinnati’s Central Air Quality Monitoring Data for Use in Epidemiologic Studies: PM2.5 Source Apportionment using Positive Matrix Factorization (PMF)." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504800976355814.
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Srivastava, Deepchandra. "Improving the discrimination of primary and secondary sources of organic aerosol : use of molecular markers and different approaches." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0055/document.
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Les aérosols organiques (AO), issus de nombreuses sources et de différents processus atmosphériques, ont un impact significatif sur la qualité de l’air et le changement climatique. L’objectif de ce travail de thèse était d’acquérir une meilleure connaissance de l’origine des AO par l’utilisation de marqueurs organiques moléculaires au sein de modèles source-récepteur de type positive matrix factorization (PMF). Ce travail expérimental était basé sur deux campagnes de prélèvements réalisées à Grenoble (site urbain) au cours de l’année 2013 et dans la région parisienne (site péri-urbain du SIRTA, 25 km au sud-ouest de Paris) lors d’un intense épisode de pollution aux particules (PM) en Mars 2015. Une caractérisation chimique étendue (de 139 à 216 espèces quantifiées) a été réalisée et l’utilisation de marqueurs moléculaires primaires et secondaires clés dans la PMF a permis de déconvoluer de 9 à 11 sources différentes de PM10 (Grenoble et SIRTA, de façon respective) incluant aussi bien des sources classiques (combustion de biomasse, trafic, poussières, sels de mer, nitrate et espèces inorganiques secondaires) que des sources non communément résolues telles que AO biogéniques primaires (spores fongiques et débris de plantes), AO secondaires (AOS) biogéniques (marin, oxydation de l’isoprène) et AOS anthropiques (oxydation des hydrocarbures aromatiques polycycliques (HAP) et/ou des composés phénoliques). En outre, le jeu de données obtenu pour la région parisienne à partir de prélèvements sur des pas de temps courts (4h) a permis d’obtenir une meilleure compréhension des profils diurnes et des processus chimiques impliquées. Ces résultats ont été comparés à ceux issus d’autres techniques de mesures (en temps réel, ACSM (aerosol chemical speciation monitor) et analyse AMS (aerosol mass spectrometer) en différée) et/ou d’autres méthodes de traitement de données (méthodes traceur EC (elemental carbon) et traceur AOS). Un bon accord a été obtenu entre toutes les méthodes en termes de séparation des fractions primaires et secondaires. Cependant, et quelle que soit l’approche utilisée, la moitié de la masse d’AOS n’était toujours pas complètement décrite. Ainsi, une nouvelle approche d’étude des sources de l’AO a été développée en combinant les mesures en temps réel (ACSM) et celles sur filtres (marqueurs moléculaires organiques) et en utilisant un script de synchronisation des données. L’analyse PMF combinée a été réalisée sur la matrice de données unifiée. 10 facteurs AO, incluant 4 profils chimiques différents en lien avec la combustion de biomasse, ont été mis en évidence. Par rapport aux approches conventionnelles, cette nouvelle méthodologie a permis d’obtenir une meilleure compréhension des processus atmosphériques liés aux différentes sources d’AOOrganic aerosols (OAs), originating from a wide variety of sources and atmospheric processes, have strong impacts on air quality and climate change. The present PhD thesis aimed to get a better understanding of OA origins using specific organic molecular markers together with their input into source-receptor model such as positive matrix factorization (PMF). This experimental work was based on two field campaigns, conducted in Grenoble (urban site) over the 2013 year and in the Paris region (suburban site of SIRTA, 25 km southwest of Paris) during an intense PM pollution event in March 2015. Following an extended chemical characterization (from 139 to 216 species quantified), the use of key primary and secondary organic molecular markers within the standard filter-based PMF model allowed to deconvolve 9 and 11 PM10 sources (Grenoble and SIRTA, respectively). These included common ones (biomass burning, traffic, dust, sea salt, secondary inorganics and nitrate), as well as uncommon resolved sources such as primary biogenic OA (fungal spores and plant debris), biogenic secondary AO (SOA) (marine, isoprene oxidation) and anthropogenic SOA (polycyclic aromatic hydrocarbons (PAHs) and/or phenolic compounds oxidation). In addition, high time-resolution filter dataset (4h-timebase) available for the Paris region also illustrated a better understanding of the diurnal profiles and the involved chemical processes. These results could be compared to outputs from other measurement techniques (online ACSM (aerosol chemical speciation monitor), offline AMS (aerosol mass spectrometer) analyses), and/or to other data treatment methodologies (EC (elemental carbon) tracer method and SOA tracer method). A good agreement was obtained between all the methods in terms of separation between primary and secondary OA fractions. Nevertheless, and whatever the method used, still about half of the SOA mass was not fully described. Therefore, a novel OA source apportionment approach has finally been developed by combining online (ACSM) and offline (organic molecular markers) measurements and using a time synchronization script. This combined PMF analysis was performed on the unified matrix. It revealed 10 OA factors, including 4 different biomass burning-related chemical profiles. Compared to conventional approaches, this new methodology provided a more comprehensive description of the atmospheric processes related to the different OA sources
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Dufresne, Marvin. "Sources et déterminants des composés organiques volatils à Marseille." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Lille Douai, 2022. http://www.theses.fr/2022MTLD0007.
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Les Composés organiques volatils (COV) dont les hydrocarbures non méthaniques (HCNM) ont un rôle clé dans la chimie atmosphérique en tant que précurseurs de polluants secondaires tels que l’ozone (O3) et les aérosols organiques secondaires (AOS). Pourtant, les connaissances sur les émissions des HCNM restent insuffisantes provoquant de fortes incertitudes associées aux inventaires d’émissions et par conséquent sur les modèles de chimie-transport (CTM), essentiels pour la mise en place de politique de qualité de l’air efficace. Ce manque d’information est d’autant plus critique sur le bassin Méditerranéen, région particulièrement marquée par la pollution atmosphérique et le changement climatique. Dans le but d’apporter des connaissances nouvelles sur les sources et déterminants des COV sur cette région, une campagne d’observation de 18 mois a été menée de mars 2019 à août 2020 à Marseille. Elle a permis l’obtention d’une base de données unique de 70 composés hydrocarbonés pour l’étude de l’évolution de la composition en HCNM de l’atmosphère de Marseille. L’analyse des observations à l’aide du modèle source-récepteur PMF (Positive Matrix Factorization) a permis de déterminer huit sources majeures pour les composés mesurés. Le trafic routier est le premier émetteur de ces composés à Marseille pour toutes les saisons contribuant à 40 % des concentrations alors que le chauffage domestique contribue à 20 % en hiver. Une baisse marquée des émissions en HCNM dues au trafic routier a été constatée au printemps 2020 associée au confinement pour la crise sanitaire du COVID-19. Une source industrielle a été identifiée comme fortement émettrice de xylènes, espèces à fort impact potentiel sur la formation d’AOS. Enfin, les inventaires d’émissions à différentes échelles ont été comparés entre eux et avec l’évaluation issue des observations pour la zone d’étude. Il apparaît une forte variabilité sur les émissions en COV totaux mais une très bonne concordance pour les émissions en COV du trafic routier. Cette comparaison a montré que la spéciation chimique des sources d’émissions en COV est significativement plus élevée pour les inventaires dans le cas des HCNM issues de combustion (alcènes et aromatiques) ce qui est possiblement dû à une surestimation du chauffage résidentiel suivant les saisons. En outre, l’étude a montré une différence de composition chimique pour le trafic routier entre l’inventaire d’émission local et les observationsVolatil Organic Compounds (VOC) are key species because of their role as precursors of secondary pollutants such as ozone (O3) and secondary organic aerosols (SOA). However, the knowledge on VOC emissions remains insufficient, leading to high uncertainties on emission inventories and consequently on chemistry-transport models (CTM) which are crucial for the successful implementation of efficient air quality policies. This lack of information is all the more critical in the Mediterranean basin since this region is particularly affected by air pollution and climate change. In order to provide new knowledge on the sources and factors controlling VOC in this region, an 18-months field campaign took place from March 2019 to August 2020 in Marseille. It allowed to obtain a unique database of 70 non-methane hydrocarbon (NMHC) compounds for the study of the evolution of the VOC composition of the atmosphere of Marseille. The analysis of observations using the source-receptor model PMF (Positive Matrix Factorization), allowed to determine eight major NMHC emission sources for the measured compounds. Road traffic is the main emitter of these compounds in Marseille in all the seasons contributing to 40% of concentrations whereas residential heating contributes to 20% in winter. A sharp decrease of the NMHC emissions due to road traffic has been observed in Spring 2020 associated to the lockdown due to the sanitary crisis of Covid-19. An industrial source has been identified as high emitter of xylenes, species with a high potential on SOA formation. Global, regional and local emission inventories were compared to each other with the observations in the Marseille area. A high variability on the total VOC emissions but a very good agreement on the VOC emissions from road traffic. This comparison showed the chemical speciation of VOC emission sources is significantly higher for the inventories in the case of HCNM emitted by combustion (alkenes and aromatics) possibly due to an overestimation of residential heating. In addition, the study showed a difference in chemical composition for road traffic between the local emission inventory and observations
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Chevrier, Florie. "Chauffage au bois et qualité de l’air en Vallée de l’Arve : définition d’un système de surveillance et impact d’une politique de rénovation du parc des appareils anciens." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAU020/document.
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La combustion de la biomasse est l’une des sources majoritaires de particules atmosphériques en périodes hivernales dans les vallées alpines, et particulièrement en vallée de l’Arve où des dépassements des seuils européens sont très régulièrement observés. Ceci a conduit à la mise en place d’un large programme de remplacement des dispositifs de chauffage au bois les moins performants dans le cadre d’une des actions du Plan de Protection de l’Atmosphère, le Fond Air Bois. Le projet DECOMBIO (DÉconvolution de la contribution de la COMbustion de la BIOmasse aux PM10 dans la vallée de l’Arve) a ainsi été mis en place en octobre 2013 afin de mesurer l’impact de cette politique de rénovation des appareils de chauffage au bois sur la qualité de l’air. C’est dans ce programme que s’inscrivent ces travaux de thèse dont l’objectif principal est de valider les méthodologies mises en place en routine pour permettre une déconvolution rapide de la combustion de la biomasse et mettre en relation les éventuels changements observés avec les avancées des remplacements de dispositifs de chauffage au bois domestiques.Pour mener à bien ce travail, trois sites, représentant les différentes situations de la vallée de l’Arve, ont été instrumentés (Marnaz, Passy et Chamonix) afin de suivre en continu, et tout au long du projet DECOMBIO, l’évolution des concentrations atmosphériques du Black Carbon (BC) et des traceurs moléculaires permettant de distinguer la contribution de la combustion de la biomasse des autres types de combustion. Un important jeu de données a été acquis entre novembre 2013 et octobre 2014 grâce à des prélèvements réguliers sur filtre permettant une caractérisation très fine de la composition chimique des particules atmosphériques. L’utilisation de l’approche statistique « Positive Matrix Factorization » (PMF) a permis de mieux appréhender les différentes sources entrant en jeu dans les émissions de particules au sein de cette vallée avec notamment un intérêt particulier pour les émissions de la combustion de la biomasse. Le développement de cette méthodologie d’attribution et de quantification des sources de particules basé sur l’utilisation de traceurs organiques spécifiques, de contraintes particulières appliquées à ce modèle et de données de déconvolution de la matière carbonée constitue une avancée importante dans la définition des facteurs sources issus de ce modèle.Les méthodologies développées au cours de ce travail, permettant une amélioration des connaissances et des contributions des sources, constituent donc des outils directement utilisables par les Associations Agréées de Surveillance de la Qualité de l’Air (AASQA), notamment pour l’évaluation quantitative des mesures prises pour améliorer la qualité de l’air dans le cadre de Plans de Protection de l’Atmosphère, entre autres celui de la vallée de l’ArveBiomass burning is one of the major sources of atmospheric particles during wintertime in Alpine valleys, and more especially in the Arve valley where exceedances of the European regulated limit value are regularly observed. This situation led to the establishment of an important program of replacement of old wood stoves with new ones as part of an action of an Atmospheric Protection Plan (APP), the “Fonds Air Bois”. The research program DECOMBIO (“DÉconvolution de la contribution de la COMbustion de la BIOmasse aux PM10 dans la vallée de l’Arve”) has been set up in October 2013 to estimate the impact of this wood stoves renewal policy on air quality. This thesis works be incorporated within this program and have for main objective to validate methodologies used in routine to enable a fast deconvolution of the biomass burning source and to compare any observed changes with progress of wood stove changeout.To complete this work, three sites, representing the different situations of the Arve valley, were instrumented (Marnaz, Passy and Chamonix) to monitor the continuing evolution of atmospheric concentrations of Black Carbon (BC) and molecular markers enabling to distinguish between the biomass burning contribution and that of other types of combustion. A large dataset was acquired between November 2013 and October 2014 thanks to regular filter samples enabling a vast chemical characterization of PM10. The use of statistical analysis “Positive Matrix Factorization” (PMF) has led to an enhanced appreciation of particle emission sources within this valley with a focus on biomass burning emissions. The development of this methodology of identification and source apportionment based on the use of specific organic markers, specific constraints and data from carbonaceous matter deconvolution is an important progress in definition of factors from this model.The developed methodologies during this work, enabling an improvement of knowledges and source apportionment, are tools directly usable by French Accredited Associations for Air Quality Monitoring, especially for the quantitative assessment of actions introduced to improve air quality as part of Atmospheric Protection Plans, for example the one in the Arve valley
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Shaltanis, Jennifer Lynn Hehl. "Source apportionment of Spokane fine fraction air pollution using the Spokane health effects database and positive matrix factorization." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Dissertations/Fall2006/j_shaltanis_112606.pdf.
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Lingwall, Jeff William. "Bayesian and Positive Matrix Factorization approaches to pollution source apportionment." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/430.
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The use of Positive Matrix Factorization (PMF) in pollution source apportionment (PSA) is examined and illustrated. A study of its settings is conducted in order to optimize them in the context of PSA. The use of a priori information in PMF is examined, in the form of target factor profiles and pulling profile elements to zero. A Bayesian model using lognormal prior distributions for source profiles and source contributions is fit and examined.
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Comero, S. "SOURCE IDENTIFICATION OF ENVIRONMENTAL POLLUTANTS USING CHEMICAL ANALYSIS AND POSITIVE MATRIX FACTORIZATION." Doctoral thesis, Università degli Studi di Milano, 2012. http://hdl.handle.net/2434/169980.
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Multivariate modeling techniques are successfully used in different areas of environmental research because of their ability to process large data sets. The main objective of their application lies in the determination of data structures and hidden information which account for the data set variability.
This thesis work seeks to explore the application of the positive matrix factorization (PMF) technique to different geochemical data sets on three spatial scales: local, pan-regional and pan-European. In particular, we focus on PMF identification of pollutants/contamination sources (e.g., anthropogenic and natural pollution) and chemical/physical processes (e.g., mineralization, weathering and corrosion) characterizing the data sets under examination.
PMF analysis was carried out on four data sets with different spatial scale:
at local scale, geochemical characteristics of soil samples at the abandoned Coren del Cucì mine dump were examined. A GIS-based approach was also combined with PMF results for a better source resolution. Five factors were determined: (i) two geo-morphological backgrounds characteristic of the area outside the dump; (ii) a source of mineralization situated inside the waste disposal area; and (iii) two different geochemical anomaly zones;
at a national level, eleven alpine lakes site in the Northern Italy were considered. X-ray fluorescence analyses on lake sediments were evaluated by PMF. Four interpretable mineralogical/chemical features were identified: (i) phosphate and sulphur source; (ii) carbonates; (iii) silicates; and (iv) heavy metal-bearing minerals. Also, to properly modify input information, a new PMF factor was determined, explaining a possible Pb contamination source;
in the pan-regional context, sediments of the Danube River basin, which cover an area of 817.000 km2, flowing through nine European countries, were analysed. The objective was to draw out information about the natural vs. anthropogenic origin of heavy metals and to determine the role of tributaries. Three factors were identified: (i) a carbonate component characterized by Ca and Mg; (ii) an alumino-silicate component dominated by Si and Al content and the presence of some metals attributed to natural processes; (iii) an anthropogenic source identified by Hg, S, P and some heavy metals load. Considering only the tributaries input, an additional source probably attributed to the use of fertilizers in agriculture was determined;
finally, a pan-European data set comprising sewage sludge from European waste water treatment plants was obtained. The final objective was to link the silver content to the increasingly use of silver nanoparticles in a variety of house-hold and personal care products. Here, method validation procedure was applied to the measured elements in order to compute correct uncertainties to be used in PMF application. The four resulting factors could be described by: (i) copper dissolution from water pipe lines; (ii) engineered silver nanoparticles load; (iii) anthropogenic influence suggested by the presence of different metals; and (iv) iron variation due to the use of this element for phosphorus removal in sewage sludge.
These studies provide first evidence that PMF could be successfully applied to geochemical data sets at different spatial scale.
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Groetzner, Patrick Hermann [Verfasser], and Mirjam [Akademischer Betreuer] Dür. "A Method for Completely Positive and Nonnegative Matrix Factorization / Patrick Hermann Groetzner ; Betreuer: Mirjam Dür." Trier : Universität Trier, 2018. http://d-nb.info/1197807918/34.
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Groetzner, Patrick [Verfasser], and Mirjam [Akademischer Betreuer] Dür. "A Method for Completely Positive and Nonnegative Matrix Factorization / Patrick Hermann Groetzner ; Betreuer: Mirjam Dür." Trier : Universität Trier, 2018. http://d-nb.info/1197807918/34.
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Sundqvist, Kristina. "Sources of dioxins and other POPs to the marine environment : Identification and apportionment using pattern analysis and receptor modeling." Doctoral thesis, Umeå universitet, Kemi, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-22266.
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In the studies underlying this thesis, various source tracing techniques were applied to environmental samples from the Baltic region. Comprehensive sampling and analysis of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) in surface sediments in Swedish coastal and offshore areas resulted in a unique data set for this region. Nearly 150 samples of surface sediments were analyzed for all tetra- to octa-chlorinated PCDD/Fs. The levels showed large spatial variability with hotspots in several coastal regions. Neither Sweden nor the EU has introduced guideline values for PCDD/Fs in sediment, but comparisons to available guidelines and quality standards from other countries indicate that large areas of primarily coastal sediments may constitute a risk to marine organisms. Multivariate pattern analysis techniques and receptor models, such as Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF), were used to trace sources. These analyses suggested that three to six source types can explain most of the observed pattern variations found in the sediment samples. Atmospheric deposition was suggested as the most important source to offshore areas, thus confirming earlier estimates. However, spatial differences indicated a larger fraction of local/regional atmospheric sources, characterized by PCDFs, in the south. This was indicated by the identification of several patterns of atmospheric origin. In coastal areas, the influence of direct emission sources was larger, and among these, chlorophenol used for wood preservation and emissions from pulp/paper production and other wood related industry appeared to be most important. The historic emissions connected to processes involving chemical reactions with chlorine (e.g. pulp bleaching) were found to be of less importance except at some coastal sites. The analysis of PCDD/Fs in Baltic herring also revealed spatial variations in the levels and pollution patterns along the coast. The geographical match against areas with elevated sediment levels indicated that transfer from sediments via water to organisms was one possible explanation. Fugacity, a concept used to predict the net transport direction between environmental matrices, was used to explore the gas exchange of hexachlorocyclohexanes (HCHs) and polychlorinated biphenyls (PCBs) between air and water. These estimates suggested that, in the Kattegat Sea, the gaseous exchange of HCHs primarily resulted in net deposition while PCBs were net volatilized under certain environmental conditions. The study also indicated that, while the air concentrations of both PCBs and γ-HCH are mostly dependent upon the origin of the air mass, the fluctuations in α-HCH were primarily influenced by seasonal changes.
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Holm, Klaus Herman. "Assessment of Atlanta’s PM [subscript 2.5] source profiles using principle component analysis and positive matrix factorization." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/20751.
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Demircioglu, Filiz. "Application Of Two Receptor Models For The Investigation Of Sites Contaminated With Polychlorinated Biphenyls: Positive Matrix Factorization And Chemical Mass Balance." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612190/index.pdf.
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This study examines the application of two receptor models, namely Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB), on the investigation of sites contaminated with PCBs. Both models are typically used for apportionment of pollution sources in atmospheric pollution studies, however have gained popularity in the last decade on the investigation of PCBs in soil/sediments. The aim of the study is four-fold(i) to identify the status of PCB pollution in Lake Eymir area via sampling and analysis of PCBs in collected soil/sediment samples, (ii) to modify the CMB model software in terms of efficiency and user-friendliness (iii) to apply the CMB model to Lake Eymir area PCB data for apportionment of the sources as well as to gather preliminary information regarding degradation of PCBs by considering the history of pollution in the area (iv) to explore the use of PMF for both source apportionment and investigation of fate of PCBs in the environment via use of Monte-Carlo simulated artificial data sets. Total PCB concentrations (Aroclor based) were found to be in the range of below detection limit to 76.3 ng/g dw with a median of. 1.7 ng/g dw for samples collected from the channel between Lake Mogan and Lake Eymir. Application of the CMB model yield contribution of highly chlorinated PCB mixtures (Aroclor 1254 and Aroclor 1260
typically used in transformers) as sources. The modified CMB model software provided user more efficient and user friendly working environment. Two uncertainty equations, developed and existing in literature, were found to be effective for better resolution of sources by the PMF model.
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Hemann, Joshua G. "Assessing Positive Matrix Factorization model fit: A new method to estimate uncertainty and bias in factor contributions at the daily time scale." Connect to online resource, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1447682.
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Thornhill, Dwight Anthony Corey. "Air Quality in Mexico City: Spatial and Temporal Variations of Particulate Polycyclic Aromatic Hydrocarbons and Source Apportionment of Gasoline-Versus-Diesel Vehicle Emissions." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/34421.
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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
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Deshpande, Seemantini R. "Evaluation of PM2.5 Components and Source Apportionment at a Rural Site in the Ohio River Valley Region." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1187123906.
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Kulkarni, Sarika. "Assessment of source-receptor relationships of aerosols: an integrated forward and backward modeling approach." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/392.
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This dissertation presents a scientific framework that facilitates enhanced understanding of aerosol source - receptor (S/R) relationships and their impact on the local, regional and global air quality by employing a complementary suite of modeling methods. The receptor - oriented Positive Matrix Factorization (PMF) technique is combined with Potential Source Contribution Function (PSCF), a trajectory ensemble model, to characterize sources influencing the aerosols measured at Gosan, Korea during spring 2001. It is found that the episodic dust events originating from desert regions in East Asia (EA) that mix with pollution along the transit path, have a significant and pervasive impact on the air quality of Gosan. The intercontinental and hemispheric transport of aerosols is analyzed by a series of emission perturbation simulations with the Sulfur Transport and dEposition Model (STEM), a regional scale Chemical Transport Model (CTM), evaluated with observations from the 2008 NASA ARCTAS field campaign. This modeling study shows that pollution transport from regions outside North America (NA) contributed ∼ 30 and 20% to NA sulfate and BC surface concentration. This study also identifies aerosols transported from Europe, NA and EA regions as significant contributors to springtime Arctic sulfate and BC. Trajectory ensemble models are combined with source region tagged tracer model output to identify the source regions and possible instances of quasi-lagrangian sampled air masses during the 2006 NASA INTEX-B field campaign. The impact of specific emission sectors from Asia during the INTEX-B period is studied with the STEM model, identifying residential sector as potential target for emission reduction to combat global warming. The output from the STEM model constrained with satellite derived aerosol optical depth and ground based measurements of single scattering albedo via an optimal interpolation assimilation scheme is combined with the PMF technique to characterize the seasonality and regional distribution of aerosols in Asia. This innovative analysis framework that combines the output from source - oriented chemical transport models with receptor models is shown to reduce the uncertainty in aerosol distributions, which in turn leads to better estimates of source - receptor relationships and impact assessments of aerosol radiative forcing and health effects due to air pollution.
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Santos, Luís Henrique Mendes dos. "O impacto das fontes de poluição na distribuição de tamanho em número e massa do material particulado atmosférico em São Paulo." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/14/14133/tde-27092018-224325/.
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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.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.
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Genc, Tokgoz D. Deniz. "Temporal Variation In Aerosol Composition At Northwestern Turkey." Phd thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615740/index.pdf.
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Daily aerosol samples (PM) were collected at a rural station, which is 5 km away from the Turkish-Bulgarian border between April 2006 and March 2008. Aerosol samples were analyzed for elements by ICPMS, ions by IC and black carbon by aethalometer to provide a multi-species aerosol data set, which can represent aerosol population for Northwestern Turkey and Eastern Europe. Average concentration of SO42-, NO3- and NH4+ was 5.8, 2.9 and 2.0 &mug m-3, respectively, while total aerosol mass was 66 &mu
g m-3. Seasonal variation of crustal species had maxima in summer, while most of the anthropogenic species had maxima in winter. Rainfall was found as the only local meteorological parameter affecting aerosols concentrations. The dominant sectors of air masses arriving the Northwestern Turkey were northeast in summer and west-northwest in winter. Air masses were classified into five clusters regarding their wind speed and direction. Most species indicated significant differences between clusters. The influence of forest fires in Ukraine and Russian Federation was identified by cluster analysis using soluble K as tracer. Source apportionment of PM was carried out by EPA PMF model and five sources were resolved. Crustal emissions were found to be the major contributor to PM (41%). The second largest source was distant anthropogenic sources with a contribution of 26%. Traffic was also a remarkable source with 16% contribution. Sea salt and stationary combustion sources accounted for 9% and 8% of PM, respectively. Potential source regions of resolved sources were determined by potential source contribution function (PSCF).
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Espina, Martin Pablo. "Determinants and sources of secondary inorganic aerosols in a rural area in Northern France." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Lille Douai, 2020. http://www.theses.fr/2020MTLD0007.
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Une campagne de mesure de la composition chimique des particules fines (PM2.5) et des gaz a été menée sur un site rural du nord de la France (le village de Caillouël-Crépigny), de mars 2018 à février 2019. Cette campagne longue, d’une durée de 1 an, a permis d’étudier les sources, la variabilité temporelle et les déterminants des gaz précurseurs et des aérosols, en se centrant sur les aérosols inorganiques secondaires (AIS), qui représentent la fraction la plus importante des PM2.5 dans cette région. Des mesures complémentaires ont été effectuées pendant des périodes de canicule à l’été 2018, qui ont permis de mieux étudier les liens entre Composés Organiques Volatils Biogéniques (BVOCs) et AIS dans un contexte de changement climatique.L’objectif de cette thèse est, au final, d’aider à mieux définir les stratégies de réduction de la pollution atmosphérique et de prévention des effets locaux du changement climatique.Ce travail de thèse s’est dérouléedans le cadre du Labex CaPPA et du programme multidisciplinaire de recherche CLIMIBIO, en collaboration avec Atmo Hauts-de-France, et a été soutenu par la région des Hauts-de-France et l’IMT Lille DouaiA monitoring campaign of the chemical composition of atmospheric fine particles (PM2.5) and gases was performed at a rural site (village of Caillouël-Crépigny) in the North of France, from March 2018 until February 2019. This 1-year long campaign allowed studying the sources, temporal variability and drivers of precursor gases and aerosol species, with a special focus on secondary inorganic aerosols (SIA), representing the largest fraction of PM2.5 in the region. Additional measurements were done during heat wave periods in summer 2018, in order to further study the relationship between Biogenic Volatile Organic Compounds (BVOCs) and SIA in the context of global change.The objective of this thesis is to help decision makers to consider possible strategies to reduce the environmental and health impacts of atmospheric pollution and the possible local effects of climate change.This thesis work was part of the Labex CaPPA and the multidisciplinary research project CPER CLIMIBIO, in collaboration with Atmo Hauts-de-France, and financially supported by the region Hauts-de-France and IMT Lille Douai
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Young, Dominique Emma. "Characterisation of the chemical properties and behaviour of aerosols in the urban environment." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/characterisation-of-the-chemical-properties-and-behaviour-of-aerosols-in-the-urban-environment(27de7e50-5069-40a0-b5cd-1370747f646a).html.
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Atmospheric aerosols have adverse effects on human health, air quality, and visibility and frequently result in severe pollution events, particularly in urban areas. However, the sources of aerosols and the processes governing their behaviour in the atmosphere, including those which lead to high concentrations, are not well understood thus limit our ability to accurately assess and forecast air quality. Presented here are the first long-term chemical composition measurements from an urban environment using an Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS). Organic aerosols (OA) were observed to account for a significant fraction (44%) of the total non-refractory submicron mass during 2012 at the urban background site in North Kensington, London, followed by nitrate (28%), sulphate (14%), ammonium (13%), and chloride (1%). The sources and components of OA were determined using Positive Matrix Factorisation (PMF) and attributed as hydrocarbon-like OA (HOA), cooking OA (COA), solid fuel OA (SFOA), type 1 oxygenated OA (OOA1), and type 2 oxygenated OA (OOA2), where HOA, COA, and SFOA were observed to be of equal importance across the year. The concentration of secondary OA increased during the summer yet the extent of oxidation, as defined by the oxygen content, showed no variability during the year. The main factors governing the diurnal, monthly, and seasonal trends observed in all organic and inorganic species were meteorological conditions, specific nature of the sources, and availability of precursors. Regional and transboundary pollution influenced total aerosol concentrations and high concentration events were observed to be governed by different factors depending on season. High-Resolution ToF-AMS measurements were used to further probe OA behaviour, where two SFOA factors were derived from PMF analysis in winter, which likely represent differences in burn conditions. In the summer an OA factor was identified, likely of primary origin, which was observed to be strongly associated with organic nitrates and anthropogenic emissions. This work uses instruments and techniques that have not previously been used in this way in an urban environment, where the results further the understanding of the chemical components of urban aerosols. Aerosol sources are likely to change in the future with increases in solid fuel burning as vehicular emissions decrease, with significant implications on air quality and health. Thus it is important to understand aerosol sources and behaviour in order to develop effective pollution abatement strategies.
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Isikdemir, Ozlem. "Investigation Of 8-year-long Composition Record In The Eastern Mediterranean Precipitation." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607064/index.pdf.
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Measurement of chemical composition of precipitation is important both to understand acidification of terrestrial and aquatic ecosystems and neutralization process in the atmosphere. Such data are scarce in the Mediterranean region. In this study, chemical composition of daily, wet-only, 387 number of rain water samples collected between 1991 and 1999 were investigated to determine levels, temporal variation and long-term trends in concentrations of major ions and trace elements between 1991 and 1999. Samples had already been collected and some of the analysis had been completed. The anions SO42-, NO3- and Cl- were analyzed by HPLC coupled with UV-VIS detector, NH4+ was analyzed by colorimetry and H+ ion was analyzed by pH meter. The major ions and trace metals were analyzed by using Atomic Absorption Spectrometry (AAS) and Graphite Furnace Atomic Absorption Spectrometry (GFAAS). In this study complete data set were generated by analyzing samples that had not been previously analyzed for major ions and trace elements with Inductively Coupled Plasma with Optical Emission Spectrometry (ICP-OES).
Statistical tools were used to determine the distribution of the pollutants. The rain water data tends to be log-normally distributed since data show large variations due to meteorological conditions, physical and chemical transformations and air mass transport patterns. The median pH of the rain water was found to be 5.29, which indicates that the rain water is not strongly acidic. This case is not a result of lacking of acidic compounds but rather indicates extended neutralization process in rain water. Eastern Mediterranean atmosphere is under the influence of three general source types: (1) anthropogenic sources, which are located to the north and northwest of the basin brings low pH values to the region (SO42-, NO3- ions)(2) a strong crustal source, which is dried and suspended local soil and air masses transported from North Africa transport which have high pH values (Ca2+, Al, Fe ions) and (3) a marine source, which is the Mediterranean Sea itself (Na+, Cl- ions). In the region, the main acid forming compounds are H2SO4 and HNO3 whereas
CaCO3 and NH3 are responsible for the neutralization process. To describe the level of pollutant concentrations and the factors that affect their variations in rain water
ion compositions, neutralization of acidity, short and long-term variability of ions and elements, their time trend analysis and wet deposition fluxes were investigated briefly. Positive matrix factorization (PMF) was used to determine components of ionic mass in the precipitation. In Antalya Station the rain water has five factors: free acidity factor, crustal factor, marine factor, NO3- factor and SO42- factor. Potential Source Contribution Function (PSCF) and trajectory statistics were used to determine source regions generating these components. NO3- has potential source regions of Western Mediterranean countries and North Africa, whereas SO42- has additional southeasterly trajectory components of Israel and south east of Turkey.
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Munzur, Basak. "Chemical Composition Of Atmospheric Particles In The Aegean Region." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609373/index.pdf.
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Daily aerosol samples were collected at the Çandarli which is located on Aegean coast of Turkey. A rural site was selected to monitor atmospheric pollution by long range transport. Sampling was performed in both summer and winter seasons, and in total 151 samples were obtained. Concentrations of elements in the samples were measured in order to identify sources and possible source locations of pollutants. Measured concentrations of trace elements at the Ç
andarli station were compared with those measured at various sites around the world and, also in Turkey. As a result of comparison, level of pollution at the Aegean Region was found to be lower than the Mediterranean Region and Black Sea Region. Air flow climatology at Ç
andarli was investigated in order to determine potential source regions for pollutants. Frequency of air flows from Russia and Western Europe are higher suggesting that emissions from these industrial regions affect the chemical composition of particulate matter. Besides these, it was concluded that contributions from Central and Eastern European countries are significantly high because of frequent air mass transport. Concentrations of elements measured at Ç
andarli station were found to show short and seasonal variations. Such variations in concentrations are explained by variations in the source strengths and transport patterns. Positive matrix factorization (PMF) was applied to determine sources of elements and contribution of sources to each element. This analysis revealed 5 sources, two local anthropogenic emissions factor, one soil factor, one sea salt factor and one long range transport factor. Distribution of Potential Source Contribution Function (PSCF) values showed that main sources of SO42- are observed in Bulgaria, Romania, Poland, Ukraine and central part of Aegean region.
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Yoruk, Ebru. "Composition Of Atmosphere At The Central Anatolia." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12604725/index.pdf.
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Concentrations of elements and ions measured in samples collected between February 1993 and December 2000 at a rural site in central Anatolia were investigated to evaluate the chemical composition of atmosphere at central Anatolia, to determine pollution level of the region, to study temporal variability of the pollutants and to investigate the sources and source regions of air pollutants in the region.
Level of pollution at central Anatolia was found to be lower than the pollution level at other European countries and Mediterranean and Black Sea regions of Turkey.
Enrichment factor calculations revealed that SO42-, Pb and Ca are highly enriched in the aerosolwhereas, soil component has dominating contribution on observed concentrations of V, Mg, Ca and K. SO42-/(SO2+SO42-) ratio observed in Ç
ubuk station indicates that contribution of distant sources is more important than the contribution of local sources on observed SO42- levels. SO42-/NO3- ratio calculations showed that Central Anatolia is receipt of SO42- from Eastern European countries. Positive Matrix Factorization (PMF) analysis revealed 6 source groups, namely motor vehicle source, mixed urban factor, long range transport factor, soil factor, NO3- factor and Cd factor. Distribution of Potential Source Contribution Function (PSCF) values showed that main source areas of SO42-, NH4+ and Cd are western parts of Turkey, Balkan countries, central and western Europe, central Russian Federation and north of Sweden and Finland
NO3- are the regions located around the Mediterranean Sea
and there is no very strong potential source area observed for NH3 and Pb.
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Krecl, Patricia. "Impact of residential wood combustion on urban air quality." Doctoral thesis, Stockholm : Department of Applied Environmental Science (ITM), Stockholm university, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7682.
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Dogan, Guray. "Comparison Of The Rural Atmosphere Aerosol Compositions At Different Parts Of Turkey." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12605844/index.pdf.
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Long term data generated at four rural stations are compared to determine similarities and differences in aerosol compositions and factors contributing to observed differences at different regions in Turkey. The stations used in this study are located at Mediterranean coast (20 km to the west of Antalya city), Black Sea coast (20 km to the east of Amasra town), Central Anatolia (Çubuk, Ankara) and Northeastern part of the Anatolian Plateau (at Mt. Uludag). Data used in comparisons were generated in previous studies. However, some re-analysis of data were also performed
(1) to improve the similarities of the parameters compared and (2) to be able to apply recently-developed methodologies to data sets. Data from Mediterranean and Black Sea stations were identical in terms of parameters measured and were suitable for extensive comparison. However, fewer parameters were measured at Ç
ubuk and Uludag stations, which limited the comparisons involving these two stations. Comparison included levels of major ions and elements, short-term and seasonal variations in concentrations, background (baseline) concentrations of elements, flow climatology of regions, correlations between elements, potential source areas affecting regions, and source types affecting chemical composition of particles. Comparison of levels of measured parameters in four regions showed that there are some differences in concentrations that arise from differences in the local characteristics of the sampling points. For example very high concentrations of elements such as Na and Cl in the Mediterranean region is attributed to closer proximity of the Antalya station to coast and not a general feature of the Mediterranean aerosol. There are also significant regional differences in the concentrations of measured elements and ions as well. Concentrations of anthropogenic elements are very similar at two coastal stations (Antalya and Amasra), but they are approximately a factor of two smaller at the two stations that are located on the Anatolian Plateau. This difference between coastal and high altitude plateau stations, which is common to all anthropogenic species, is attributed to different source regions and transport mechanisms influencing coastal regions and Anatolian Plateau. Some statistically significant differences were also observed in the temporal variations of elements and ions measured in different stations. The elements with crustal origin showed similar seasonal pattern at all stations, with higher concentrations in summer and lower concentrations in winter. This difference between summer and winter is attributed to suppression of re-suspension of crustal aerosol from wet or ice-covered surface soil in winter. Concentrations of anthropogenic elements, on the other hand, did not show a statistically significant seasonal trend at Amasra, Ç
ubuk and Uludag stations, but they have higher concentrations during summer months at the Antalya station. This difference between Mediterranean aerosol and aerosol at the Central and Northern Turkey is due to influence of more local sources on Ç
ubuk, Amasra and Uludag stations and domination of more distant source in determining aerosol composition at the Mediterranean region. A similar conclusion of strong influence of local sources on chemical composition of particles at the Central Anatolia was also suggested by the comparison of baseline concentrations in each station. General features in flow climatology (residence times of upper atmospheric air masses) in each region are found to be similar with more frequent flow from W, WNW, NW and NNW wind sectors. Since these are the sectors that include high emitting countries in Eastern and Western Europe and Russia, transport from these sectors are expected to bring pollution from both distant European countries and more local Balkan countries and western parts of Turkey. Flow climatology in stations showed small, but statistically significant, differences between summer and winter seasons. These variations suggested that the station at the Central Anatolia and Black Sea (Ç
ubuk Amasra and Uludag stations) are affected from sources located at the Western Europe in winter season and from sources located at the Eastern Europe in summer. Mediterranean aerosol, on the other hand, are affected from sources at the Western Europe and do not show any seasonal differences. This variation in flow climatology between summer and winter seasons (and lack of variation at the Mediterranean station) is supported by the seasonal variation (and lack of variation at the Mediterranean station) in SO42-/NO3- ratio measured at the stations. Potential source contribution function (PSCF) values are calculated for selected elements and ions in each station. Statistical significance of calculated PSCF values is tested using bootstrapping technique. Results showed that specific grids at Russia and at Balkan countries are common source regions affecting concentrations of anthropogenic elements at all four regions in Turkey. However, each station is also affected from specific source regions as well. Aerosol composition at the Anatolian Plateau are affected from sources closer to the sampling points whereas Mediterranean and Black Sea aerosol are affected from source regions that farther away from the receptors. It should be noted that the same conclusion is also reached in comparison of seasonal patterns and baseline concentrations at these stations. Types of sources affecting aerosol composition at Black Sea, Mediterranean and Central Anatolia are also compared. Source types affecting atmospheric composition in these regions were calculated using positive matrix factorization (PMF). The results showed that aerosol at the Black Sea, Central Anatolia and Mediterranean atmosphere consists of 8, 6 and 7 components, respectively. Two of these components, namely a crustal component and a long-range transport component are common in all three stations. The chemical compositions of these common components are shown to the same within 95% statistical significance interval. Three factors, namely a fertilizer factor, which is highly enriched in NH4+ ion, a sea salt component and an arsenic factor are common in the Mediterranean and Black Sea aerosol but not observed at the Central Anatolia. Other factors found in the regions are specific for that region.
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Ozturk, Fatma. "Investigation Of Short And Long Term Trends In The Eastern Mediterranean Aerosol Composition." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12610373/index.pdf.
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Approximately 2000 daily aerosol samples were collected at Antalya (30°34&
#900
30.54 E, 36°
47&
#8217
30.54N) on the Mediterranean coast of Turkey between 1993 and 2001. High volume PM10 sampler was used for the collection of samples on Whatman&
#8211
41 filters. Collected samples were analyzed by a combination of analytical techniques. Energy Dispersive X-Ray Fluorescence (EDXRF) and Inductively Coupled Plasma Mass Spectrometry (ICPMS) was used to measure trace element content of the collected samples from Li to U. Major ions, namely, SO42- and NO3-, were determined by employing Ion Chromatography (IC). Samples were analyzed in terms of their NH4+ contents by means of Colorimetry. Evaluation of short term trends of measured parameters have been shown that elements with marine and crustal origin are more episodic as compared to anthropogenic ones. Most of the parameters showed well defined seasonal cycles, for example, concentrations of crustal elements increased in summer season while winter concentrations of marine elements were considerably higher than associated values for summer. Seasonal Kendall statistic depicted that there was a decreasing trend for crustal elements such as Be, Co, Al, Na, Mg, K, Dy, Ho, Tm, Cs and Eu. Lead, As, Se and Ge were the anhtropogenic elements that decreasing trend was detected in the course of study period. Cluster and Residence time analysis were performed to find the origin of air masses arrving to Eastern Mediterranena Basin. It has been found that air masses reaching to our station resided more on Balkans and Eastern Europe. Positive Matrix Factorization (PMF) resolved eight factors influencing the chemical composition of Eastern Mediterranean aerosols as local dust, Saharan dust, oil combustion, coal combustion, crustal-anthropogenic mixed, sea salt, motor vehicle emission, and local Sb factor.
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Assefa, Anteneh. "Tracing and apportioning sources of dioxins using multivariate pattern recognition techniques." Doctoral thesis, Umeå universitet, Kemiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-102877.
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High levels of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in edible fish in the Baltic Sea have raised health concerns in the Baltic region and the rest of Europe. Thus, there are urgent needs to characterize sources in order to formulate effective mitigation strategies. The aim of this thesis is to contribute to a better understanding of past and present sources of PCDD/Fs in the Baltic Sea environment by exploring chemical fingerprints in sediments, air, and biota. The spatial and temporal patterns of PCDD/F distributions in the Baltic Sea during the 20th century were studied in Swedish coastal and offshore sediment cores. The results showed that PCDD/F levels peaked in 1975 (± 7 years) in coastal and 1991 (± 5 years) in offshore areas. The time trends of PCDD/Fs in the sediment cores also showed that environmental half-lives of these pollutants have been shorter in coastal than in offshore areas (15 ± 5 and 29 ± 14 years, respectively). Consequently, there have been remarkable recoveries in coastal areas, but slower recovery in offshore areas with 81 ± 12% and 38 ± 11% reductions from peak levels, respectively. Source-to-receptor multivariate modeling by Positive Matrix Factorization (PMF) showed that six types of PCDD/F sources are and have been important for the Baltic Sea environment: PCDD/Fs related to i) atmospheric background, ii) thermal processes, iii) manufacture and use of tetra-chlorophenol (TCP) and iv) penta-chlorophenol (PCP), v) industrial use of elementary chlo- rine and the chloralkali-process (Chl), and vi) hexa-CDD sources. The results showed that diffuse sources (i and ii) have consistently contributed >80% of the total amounts in the Southern Baltic Sea. In the Northern Baltic Sea, where the biota is most heavily contaminated, impacts of local sources (TCP, PCP and Chl) have been higher, contributing ca. 50% of total amounts. Among the six sources, only Thermal and chlorophenols (ii-iv) have had major impacts on biota. The impact of thermal sources has, however, been declining as shown from source apportioned time-trend data of PCDD/Fs in Baltic herring. In contrast, impacts of chlorophenol-associated sources generally increased, remained at steady-state or slowly decreased during 1990-2010, suggesting that these sources have substantially contributed to the persistently high levels of PCDD/Fs in Baltic biota. Atmospheric sources of PCDD/Fs for the Baltic region (Northern Europe) were also investigated, and specifically whether the inclusion of parallel measurements of metals in the analysis of air would help back-tracking sources. PCDD/Fs and metals in high-volume air samples from a rural field station near the shore of the central Baltic Sea were measured. The study focused on the winter season and air from the S and E sectors, as these samples showed elevated levels of PCDD/Fs, particularly PCDFs. Several metals were found to correlate significantly with the PCDFs. The wide range of candidate metals as source markers for PCDD/F emissions, and the lack of an up-to-date extensive compilation of source characteristics for metal emission from vari- ous sources, limited the use of the metals as source markers. The study was not able to pin-point primary PCDD/F sources for Baltic air, but it demonstrated a new promising approach for source tracing of air emissions. The best leads for back-tracking primary sources of atmospheric PCDD/Fs in Baltic air were seasonal trends and PCDD/F congener patterns, pointing at non-industrial related thermal sources related to heating. The non-localized natures of the sources raise challenges for managing the emissions and thus societal efforts are required to better control atmospheric emissions of PCDD/Fs.EcoChange
BalticPOPs
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Trindade, Camila Carnielli. "Avaliação do uso de diferentes modelos receptores com dados de PM2,5 : balanço químico de massa (BQM) e fatoração de matriz positiva (FMP)." reponame:Repositório Institucional da UFES, 2009. http://repositorio.ufes.br/handle/10/1932.
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A identificação de fontes para material particulado tem sido um tema de crescente interesse em todo o mundo para auxiliar a gestão da qualidade do ar. Esta classe de estudos é convencionalmente baseada no uso de modelos receptores, que identificam e quantificam as fontes responsáveis a partir da concentração do contaminante no receptor. Existe uma variedade de modelos receptores disponíveis na literatura, este trabalho compara os resultados dos modelos receptores balanço químico de massa (BQM) e fatoração de matriz positiva (FMP) para o banco de dados de PM2,5, da região de Brighton, Colorado, com o intuito de investigar as dificuldades na utilização de cada modelo, bem como suas vantagens e desvantagens. Inicialmente, já é conhecido que o modelo BQM tem a desvantagem de necessitar dos perfis das fontes, determinados experimentalmente, para ser aplicado e também tem limitações quando as fontes envolvidas são similares. Já o modelo FMP não requer os perfis de fontes, mas tem a desvantagem de precisar de elevada quantidade amostral da concentração do contaminante no receptor. Os resultados mostraram, baseados nas medidas de performance que os dois modelos foram aptos para reproduzir os dados do receptor com ajustes aceitáveis. Todavia, resultados diferentes se ajustaram a medidas de performance. O modelo BQM, utilizou 9 tipos de fontes e o modelo FMP encontrou apenas 6 tipos de fontes. Constatou-se com isso que o modelo FMP tem dificuldades em modelar fontes que aparecem ocasionalmente. As fontes sulfato de amônio, solos, veículos a diesel e nitrato de amônio tiverem boas correlações nos resultados dos dois modelos de contribuições de fontes. Os perfis de fontes utilizados no modelo BQM e resultados do modelo FMP que mais se assimilaram foram das fontes nitrato de amônio, solos, sulfato de amônio e combustão de madeira e ou/ veículos desregulados. Verificou-se no modelo FMP que as espécies não características de determinadas fontes aparecem nos resultados dos perfis das fontes, o que torna-se ainda mais complexo a identificação das fontes, requerendo elevado conhecimento sobre a composição de inúmeras fontes.
The identification of sources of particulate matter has been a topic of growing interest throughout the world to assist the air quality management. This class of studies is conventionally based on the use of receptor models, which identify and quantify the sources responsible from the concentration of the contaminant in the receptor. There are a variety of receptor models, this study compares the results of chemical mass balance (CMB) and positive matrix factorization (PMF) models for a database of PM2.5, for the region of Brighton, Colorado, with a view to investigate the difficulties in the use of each model, as well as its advantages and disadvantages. It is known that the CMB model has the disadvantage of requiring source profiles, determined experimentally, to be applied and also has limitations when the sources involved are similar. On the other hand, the PMF model does not require source profiles, it has the disadvantage to require a large amount sample, in receptor. The results showed, based on performance measures that both models were able to reproduce the data of the receptor with reasonable fit. However, different results were adjusted for performance measurements. The CMB model, used 9 types of sources and PMF model found only 6 types of sources, it was noted by that what the PMF model has difficulty in modeling sources that appear occasionally. The sources ammonium sulfate, soil, diesel vehicles and ammonium nitrate have good correlation in the results of the two model of sources apportionment. The source profiles used in the CMB model and results of the PMF model that present more similarities were of the sources ammonium nitrate, soil, ammonium sulfate and combustion of wood and/or smoker vehicles. It was verified what the PMF model does not separate well species in the source profiles, therefore becomes even more complex to identify the sources in the FMP model, requiring considerable knowledge about the composition of many sources. For the database used with similar sources, the lack of confidence in the results based only on receptors models for a final decision on the source apportionment.
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Mangin, Olivier. "Emergence de concepts multimodaux : de la perception de mouvements primitifs à l'ancrage de mots acoustiques." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0002/document.
Full textAbstract:
Cette thèse considère l'apprentissage de motifs récurrents dans la perception multimodale. Elle s'attache à développer des modèles robotiques de ces facultés telles qu'observées chez l'enfant, et elle s'inscrit en cela dans le domaine de la robotique développementale.Elle s'articule plus précisément autour de deux thèmes principaux qui sont d'une part la capacité d'enfants ou de robots à imiter et à comprendre le comportement d'humains, et d'autre part l'acquisition du langage. A leur intersection, nous examinons la question de la découverte par un agent en développement d'un répertoire de motifs primitifs dans son flux perceptuel. Nous spécifions ce problème et établissons son lien avec ceux de l'indétermination de la traduction décrit par Quine et de la séparation aveugle de source tels qu'étudiés en acoustique.Nous en étudions successivement quatre sous-problèmes et formulons une définition expérimentale de chacun. Des modèles d'agents résolvant ces problèmes sont également décrits et testés. Ils s'appuient particulièrement sur des techniques dites de sacs de mots, de factorisation de matrices et d'apprentissage par renforcement inverse. Nous approfondissons séparément les trois problèmes de l'apprentissage de sons élémentaires tels les phonèmes ou les mots, de mouvements basiques de danse et d'objectifs primaires composant des tâches motrices complexes. Pour finir nous étudions le problème de l'apprentissage d'éléments primitifs multimodaux, ce qui revient à résoudre simultanément plusieurs des problèmes précédents. Nous expliquons notamment en quoi cela fournit un modèle de l'ancrage de mots acoustiquesThis thesis focuses on learning recurring patterns in multimodal perception. For that purpose it develops cognitive systems that model the mechanisms providing such capabilities to infants; a methodology that fits into thefield of developmental robotics.More precisely, this thesis revolves around two main topics that are, on the one hand the ability of infants or robots to imitate and understand human behaviors, and on the other the acquisition of language. At the crossing of these topics, we study the question of the how a developmental cognitive agent can discover a dictionary of primitive patterns from its multimodal perceptual flow. We specify this problem and formulate its links with Quine's indetermination of translation and blind source separation, as studied in acoustics.We sequentially study four sub-problems and provide an experimental formulation of each of them. We then describe and test computational models of agents solving these problems. They are particularly based on bag-of-words techniques, matrix factorization algorithms, and inverse reinforcement learning approaches. We first go in depth into the three separate problems of learning primitive sounds, such as phonemes or words, learning primitive dance motions, and learning primitive objective that compose complex tasks. Finally we study the problem of learning multimodal primitive patterns, which corresponds to solve simultaneously several of the aforementioned problems. We also details how the last problems models acoustic words grounding
35
Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
Full textAbstract:
Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Jaeckels, Jeffrey Michael. "Positive matrix factorization (PMF) of carbonaceous aerosols for source apportionment and comparison to chemical mass balance (CMB) apportionment." 2007. http://catalog.hathitrust.org/api/volumes/oclc/153260239.html.
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薛獅宏. "Factorization of a spase positive definite symmetric matrix on vector computers." Thesis, 1990. http://ndltd.ncl.edu.tw/handle/73733882078184694141.
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Chen, Ya-Fang, and 陳雅芳. "Identification of PCDD/F Atmospheric Deposition and Emission Sources via Positive Matrix Factorization." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/87126262475139866128.
Full textAbstract:
碩士國立陽明大學
環境與職業衛生研究所
101
PCDDs (polychlorinated dibenzo-p-dioxins) and PCDFs (polychlorinated dibenzofurans) are commonly known as dioxin which has been listed as persistent organic pollutants (POPs). The 2,3,7,8-tetra-chlorodibenzo-p-dioxin is classified as a group 1 carcinogen by International Agency for Research on Cancer (IARC), and PCDD/Fs have been proven to induce biochemical and toxic responses in experimental animals. PCDD/Fs is emitted to atmosphere by anthropogenic activities and transport to anywhere through diffusion mechanism. Finally, the PCDD/Fs distributed in particles deposit to ground and that will be hazardous risks for human. Therefore, understanding the atmospheric deposition of PCDD/Fs and sources is important. The objective of this study is to monitor the atmospheric deposition of PCDD/Fs in urban area and industrial parks of northern, central and southern Taiwan, moreover, speculate the relative contribution of various emission sources by applying United States Environmental Protection Agency Positive Matrix Factorization (US EPA PMF) software to apportionment of PCDD/Fs in atmospheric depositions. Our measurements indicate that the atmospheric PCDD/F deposition fluxes were 0.74~6.85 pg I-TEQ/m2-day in urban area; furthermore, around 3.18~20.2, 9.30~38.9 and 4.26~21.0 pg I-TEQ/m2-day were measured in industrial parks of northern, central and southern Taiwan, respectively. The deposition flux (2.64±1.57 pg I-TEQ/m2-day, n=13) of PCDD/F measured in urban area was significantly lower than that observed in industrial park of northern (11.0±4.89 pg I-TEQ/m2-day, n=12), central (18.1±8.65 pg I-TEQ/m2-day, n=12) and southern (11.5±5.94 pg I-TEQ/m2-day, n=24) Taiwan. Moreover, the deposition flux of PCDD/Fs in industrial park of central Taiwan was the highest. According to the statistical results of PMF analysis, the major contributors of atmospheric PCDD/F depositions observed in urban area in northern Taiwan and industrial park of the northern, central, and southern Taiwan were long-range transport (50.2%), MSWI/IWI (54.9%), secondary copper smelting plant (37.9%) and electric arc furance (39.0%), respectively.
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Chen, Ching-Chun, and 陳景純. "Applying Positive Matrix Factorization to Identify Pollution Sources of Fine Particles in Forest Environments." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/87083184041311760085.
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碩士國立臺灣大學
環境衛生研究所
103
In recent years, problem of air pollution in Taiwan is worsening. Anthropogenic emissions are increasing, resulting in a lot of pollutants present in the atmosphere, including particulate matters. Expoures to the fine particles (PM2.5) with aerodynamic diameter less than 2.5 micron may cause adverse effect on human health, such as lung function impairment or respiratory-related diseases. In this study, PM2.5 were measured at the nursery in Xitou natural education area from September 2013 to July 2014. PM2.5 samples were collectd for 80 days and each sample covered 22 hours. The analysis results showed that the average PM2.5 concentration during day and night was 28.86 ± 7.02 µg/m3 and 19.12 ± 5.14 µg/m3 in Fall, respectively; the average of PM2.5 concentration is 19.16 ± 10.74 µg/m3 in winter, 26.33 ± 10.81 µg/m3 in spring and 11.52 ± 6.31 µg/m3 in summer. For PM2.5 compositions, sixteen elements (Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ba, Pb), organic carbon (OC), elemental carbon (EC) as well as concentrations of twelve inorganic ions (Na+, NH4+, K+, Mg2+, Ca2+, Cl−, NO2-, NO3−, PO43-, SO4=) were determined. The model of the positive matrix factorization (PMF) was applied to estimate pollution sources in this study. We assessed the best-fitted solution by evaluating the Q value, Maximum Individual Column Mean (IM), Maximum Individual Column Standard Deviation (IS), and Error Estimation (EE). Based on the resolved source profiles and source contribution, four sources were identified: Diesel/Secondary, Fuel-oil combustion/ Traffic, Sea salt transported and Biomass burning, while the largest contributors of PM2.5 were Diesel/Secondary pollution source (44%).
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Lee, Kun-Wei, and 李崑瑋. "Characterization of Metallic Elements and SourceApportionment of PM2.5 at Taichung Cityby Using Positive Matrix Factorization." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/65236649440962057592.
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碩士國立中興大學
環境工程學系所
102
In this study, PM2.5 aerosol samples were collected by using a dichotomous sampler in 2009 in the city of Taichung. Twenty-four hours sampling was conducted consecutively for 7 days during the end period every monthly. The samples were then further analyzed to determine the concentrations of 22 elements (Al, Fe, Na, Mg, K, Ca, Sr, Ba, Ti, Mn, Co, Ni, Cu, Zn, Mo, Cd, Sb, Pb, V, Cr, As and Se) by inductively coupled plasma mass spectrometry (ICP-MS). The average concentration of PM2.5 was found to be 32.6 ± 14.6 μg m-3. The results from the correlation matrix indicated the possible pollution sources were crustal elements, salt spray, biomass or coal fuel burning, fossil fuel or heavy oil combustion, vehicles or industries emission and Sb related sources. Also, the apportionments of the pollution sources were evaluated based on the measurements of the metallic elements and the collected data of SO42-, NO3- and NH4+ with positive matrix factorization (PMF). Totally seven source types were identified and their contributions were 15.6 % secondary ammonium sulfate, 14.6% secondary nitrate, 21.3 % vehicles emission with biomass or coal fuel burning, 16.5 % fossil fuel combustion, 10.5 % Sb-rich related pollution, 6.6 % metal processing and 7.6 % crust with salt spray. Similar results were also found by using principal component analysis (PCA) which indicated that the major five sources in Taichung were factor1─vehicles emission, secondary nitrate and Sb-rich, factor2─crust, factor3─heavy oil combustion and metal processing, factor4─biomass burning and factor5─secondary ammonium sulfate.
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Liang, Jyh-Feng, and 梁志鋒. "A Study On the Comparison Of Two Receptor Models:Chemical Mass Balance Model and Positive Matrix Factorization Model." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/94883354832951295833.
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碩士中興大學
環境工程學系所
94
Two receptor models, Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF), are applied to estimate the source contributions of TaChia area in this study. There are thirty three samples of PM2.5 and PM2.5~10 , respectively. And four samples are impacted by Asian Dust Storm. This research will analysis the source contribution of Asian Dust Storm by receptor model. CMB model is written by Matlab program language. Condition Index and π matrix are used to identify the collinearity of source profiles by CMB model. Their advantages are that collinearity of source profiles are defined definitely and source profiles can be chosen flexible. PMF model is used the EPA PMF 1.1 version developed by USEPA. The results of two models are compared. Vehicle emissions, vegetative burning, ammonium sulfate, ammonium nitrate, crustal materials, incinerator, oil-fired boiled are analyzed to the source contributions of PM2.5 by two receptor models. Vehicle emissions are the major source contributions of PM2.5, and it was estimated about 57 % and 35 % of PM2.5 by CMB model and PMF model. The second to fourth source contributions are vegetative burning, ammonium sulfate, ammonium nitrate, and they accounts for 44.3 % and 48.4 % of total source contributions to CMB model and PMF model, respectively. Six sources include vehicle emissions, crustal materials, marine spray, ammonium nitrate, incinerator, vegetative burning are resolved to the source contribution of PM2.5~10 by two receptor models. The results show that vehicle emission and crustal materials are primary and secondary source contributions of PM2.5~10. They accounts for 74 % and 61 % of total source contributions to PM2.5~10 according to the results obtained from CMB model and PMF model, respectively. Vehicle emissions estimated by CMB model are still 52 % of total source contribution higher than 35 % estimated by PMF model. The contribution of Asian dust storm is only resolved by CMB model, and it accounts for 3.4 % of total source contributions. Instead, PMF model can’t resolve the contribution of Asian dust storm. In conclusion, the major sources identified by the two receptor models are the same. The reason why high differences of contributions to vehicle emissions may be the source profile collected from the foreign area and it is not proper for the characteristics of vehicle emissions for TaChia area. Incinerator and crustal materials are low percentages of total contributions and their regression coefficient(r2) are low of the results between CMB model and PMF model. The reasons may be due to the incompleteness of profiles and a lack of local-specific profiles. In addition, a lack of samples to Asian dust storm, PMF model can’t resolve the source contribution of Asian dust storm.
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Gaoseb, Frans Otto. "Spectral factorization of matrices." Diss., 2020. http://hdl.handle.net/10500/26844.
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Abstract in EnglishThe research will analyze and compare the current research on the spectral factorization of non-singular and singular matrices. We show that a nonsingular non-scalar matrix A can be written as a product A = BC where the eigenvalues of B and C are arbitrarily prescribed subject to the condition that the product of the eigenvalues of B and C must be equal to the determinant of A. Further, B and C can be simultaneously triangularised as a lower and upper triangular matrix respectively. Singular matrices will be factorized in terms of nilpotent matrices and otherwise over an arbitrary or complex field in order to present an integrated and detailed report on the current state of research in this area. Applications related to unipotent, positive-definite, commutator, involutory and Hermitian factorization are studied for non-singular matrices, while applications related to positive-semidefinite matrices are investigated for singular matrices. We will consider the theorems found in Sourour [24] and Laffey [17] to show that a non-singular non-scalar matrix can be factorized spectrally. The same two articles will be used to show applications to unipotent, positive-definite and commutator factorization. Applications related to Hermitian factorization will be considered in [26]. Laffey [18] shows that a non-singular matrix A with det A = ±1 is a product of four involutions with certain conditions on the arbitrary field. To aid with this conclusion a thorough study is made of Hoffman [13], who shows that an invertible linear transformation T of a finite dimensional vector space over a field is a product of two involutions if and only if T is similar to T−1. Sourour shows in [24] that if A is an n × n matrix over an arbitrary field containing at least n + 2 elements and if det A = ±1, then A is the product of at most four involutions. We will review the work of Wu [29] and show that a singular matrix A of order n ≥ 2 over the complex field can be expressed as a product of two nilpotent matrices, where the rank of each of the factors is the same as A, except when A is a 2 × 2 nilpotent matrix of rank one. Nilpotent factorization of singular matrices over an arbitrary field will also be investigated. Laffey [17] shows that the result of Wu, which he established over the complex field, is also valid over an arbitrary field by making use of a special matrix factorization involving similarity to an LU factorization. His proof is based on an application of Fitting's Lemma to express, up to similarity, a singular matrix as a direct sum of a non-singular and nilpotent matrix, and then to write the non-singular component as a product of a lower and upper triangular matrix using a matrix factorization theorem of Sourour [24]. The main theorem by Sourour and Tang [26] will be investigated to highlight the necessary and sufficient conditions for a singular matrix to be written as a product of two matrices with prescribed eigenvalues. This result is used to prove applications related to positive-semidefinite matrices for singular matrices.
National Research Foundation of South Africa
Mathematical Sciences
M Sc. (Mathematics)
43
"On the separation of T Tauri star spectra using non-negative matrix factorization and Bayesian positive source separation." Thesis, 2010. http://hdl.handle.net/1911/62077.
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The objective of this study is to compare and evaluate Bayesian and deterministic methods of positive source separation of young star spectra. In the Bayesian approach, the proposed Bayesian Positive Source Separation (BPSS) method uses Gamma priors to enforce non-negativity in the source signals and mixing coefficients and a Markov Chain Monte Carlo (MCMC) algorithm, modified by suggesting simpler proposal distributions and randomly initializing the MCMC to correctly separate spectra. In the deterministic approach, two Non-negative Matrix Factorization (NNMF) algorithms, the multiplicative update rule algorithm and an alternating least squares algorithm, are used to separate the star spectra into sources. The BPSS and NNMF algorithms are applied to the field of Astrophysics by applying the source separation techniques to T Tauri star spectra, resulting in a successful decomposition of the spectra into their sources. These methods are for the first time being applied and evaluated in optical spectroscopy. The results show that, while both methods perform well, BPSS outperforms NNMF. The NNMF and BPSS algorithms improve upon the current methodology used in Astrophysics iu two important ways. First, they permit the identification of additional components of the spectra in addition to the photosphere and boundary layer which can be modeled with current methods. Second, by applying a statistical algorithm, the modeling of T Tauri stars becomes less subjective. These methods may be further extrapolated to model spectra from other types of stars or astrophysical phenomena.
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Toganassova, Dilyara. "SOURCE APPORTIONMENT OF PM2.5 SHIP EMISSIONS IN HALIFAX, NOVA SCOTIA, CANADA." 2013. http://hdl.handle.net/10222/21432.
Full textAbstract:
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.
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"Characterization of simple saccharides and other organic compounds in atmospheric particulate matter and source apportionment using positive matrix factorization." Thesis, 2010. http://hdl.handle.net/1911/62006.
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Ambient particulate matter samples were collected at various sites in Texas, Arizona, and Austria from 2005 to 2009 to characterize the organic compositions and local PM sources. The primary biologically derived carbon sources, specifically the atmospheric entrainment of soil and associated biota and primary biological aerosol particles (PBAPs), are major sources contributing to ambient PM. This dissertation work proposes simple saccharides as well-suited tracers to characterize the contribution to ambient PM from these primary biologically derived carbon sources.
Saccharide concentrations in ambient PM were determined from various locations and various seasons. Aerosol saccharide compounds displayed seasonal variations, inter-correlations, and size fractionations (fine vs. coarse) that were consistent between samples and that can be used to determine sources. The difference in aerosol saccharide concentrations and relative species abundances was reflective of different climate patterns and ecosystems. Selected saccharide compounds including an established marker (levoglucosan) and novel markers (glucose, sucrose, trehalose, mannitol, and arabitol) were used along with other markers to model the major source contributions to ambient PM using a positive matrix factorization (PMF) model. Major local PM sources were resolved at three Texas sites (San Augustine, Dallas, and Big Bend National Park) and one Arizona site (Higley), with two source factors enriched in the proposed novel saccharide markers that can be related to the primary biologically derived carbon sources. The contribution to PM from the saccharide-rich primary biological sources was estimated to range from 16% (remote area) to 36% (rural and suburban area) at the four sampling sites studied. Other PM sources identified by PMF included motor vehicles, secondary aerosol formation, meat cooking, biogenic wax, sea salt, crustal material, and road dust.
To further characterize the primary biologically derived carbon sources, different soil and source samples representing PBAPs (plants and spores) were collected at Higley (AZ) to study their saccharide compositions in particle sizes equivalent to PM2.5 and PM10. It was found that the total measured non-levoglucosan saccharide content relative to PM mass in ambient aerosols (0.2% on average in PM2.5 and 0.11% in PM10) was much higher than the soil samples (<0.02% in both PM2.5 and PM10) but much lower than in the PBAP source samples (2% on average in plant PBAP samples and 16% in spore PBAP samples). The measured PBAP samples contained a concentration of sucrose and glucose that is consistent with the saccharide-rich source profiles resolved from ambient aerosol data analyzed by PMF while the measured soil samples did not. This can be interpreted as confirmation that PBAPs are an important PM source in additional to soil and associate biota at Higley, AZ. However, the saccharide levels in the measured PBAP samples were several orders of magnitude higher than the PMF results, suggesting that the ambient aerosol samples are a combination of high saccharide concentration PBAPs and lower saccharide concentration soils at Higley, AZ.
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Chang, Jung-Chi, and 張容綺. "Application of Positive Matrix Factorization Model for Examining Spatial Variations of Exposure to PM2.5 with Different Height in Taipei Metropolis." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/13976572122842849668.
Full textAbstract:
碩士國立臺灣大學
環境衛生研究所
105
Exposure to air pollutants such as fine particle matter (PM2.5) has high association with acute or chronic adverse health effects. Spatial variations have been examined and applied to evaluate air pollutant exposure in residential area widely. However, most of the past studies which examined spatial variation only considered about horizontal aspect. The vertical variations have not been studied extensively. Examining the vertical variations in urban areas is essential to realize the source influences from different height. This study measured the vertical variations by sampling three categories of floors at typical buildings in Taipei metropolis. Five sampling buildings were selected by its environmental features, including different volume of traffic or the various surrounding objects such as viaduct or parking lots. The categorized floor-levels included low-level sampling site set from first to third floors, mid-level sampling sites set between the sixth and seventh floors, and high-level sampling sites set between the tenth and eleventh floors. PM2.5 samples were collected to analyze the mass concentrations, absorption coefficient and 16 elements concentrations in three seasons (summer, autumn and winter). Moreover, positive matrix factorization (PMF) model was utilized to estimate the sources influences of different floors. The PM2.5 mass concentration was obtained by weighing before and after the sample collection. The highest value was at low-level floor (15.59 μg/m3), followed by high-level floor (15.25 μg/m3) and mid-level floor (15.04 μg/m3). On the other hand, based on the resolved source profiles and source contribution, seven characterized sources were identified: Secondary aerosol/ long-range transport, Traffic related, Paint project, Oil combustion, Dust source, Cr-rich industry and one mixed source. The largest contributor was secondary aerosol/ long-range transport (48.71%) in this study. Most of the vertical trends had higher value at low- and high- level floor, but lowest value at mid-level floor with 10% relative error. The seasonal variations of source contributions were analyzed in this study which showed that the highest value occurred in winter mostly. The source of secondary aerosol/long-range transport contributed 21%, 20% and 59% and dust source contributed 12%, 30% and 58%, respectively, in summer, autumn and winter. Finally, the effect of sources emission at different floors and seasonal variations could be utilized as information for developing prevention strategies of air pollution.
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Wang, Fu-Ming, and 王富民. "A Study On The Comparison Of Different Collinearity In Source Profiles By Two Models: Chemical Mass Balance Model and Positive Matrix Factorization Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/40923560255277401158.
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Khoury, Maroun Clive. "Products of diagonalizable matrices." Diss., 2009. http://hdl.handle.net/10500/787.
Full textAbstract:
Chapter 1 reviews better-known factorization theorems of a square
matrix. For example, a square matrix over a field can be expressed
as a product of two symmetric matrices; thus square matrices over
real numbers can be factorized into two diagonalizable matrices.
Factorizing matrices over complex num hers into Hermitian matrices
is discussed. The chapter concludes with theorems that enable one to
prescribe the eigenvalues of the factors of a square matrix, with
some degree of freedom. Chapter 2 proves that a square matrix over
arbitrary fields (with one exception) can be expressed as a product
of two diagona lizab le matrices. The next two chapters consider
decomposition of singular matrices into Idempotent matrices, and of
nonsingutar matrices into Involutions. Chapter 5 studies
factorization of a comp 1 ex matrix into Positive-( semi )definite
matrices, emphasizing the least number of such factors requiredMathematical Sciences
M.Sc. (MATHEMATICS)
49
Khoury, Maroun Clive. "Products of diagonalizable matrices." Diss., 2002. http://hdl.handle.net/10500/17081.
Full textAbstract:
Chapter 1 reviews better-known factorization theorems of a square
matrix. For example, a square matrix over a field can be expressed
as a product of two symmetric matrices; thus square matrices over
real numbers can be factorized into two diagonalizable matrices.
Factorizing matrices over complex numbers into Hermitian matrices
is discussed. The chapter concludes with theorems that enable one to
prescribe the eigenvalues of the factors of a square matrix, with
some degree of freedom. Chapter 2 proves that a square matrix over
arbitrary fields (with one exception) can be expressed as a product
of two diagonalizable matrices. The next two chapters consider
decomposition of singular matrices into Idempotent matrices, and of
nonsingular matrices into Involutions. Chapter 5 studies
factorization of a complex matrix into Positive-(semi)definite
matrices, emphasizing the least number of such factors required.Mathematical Sciences
M. Sc. (Mathematics)
50
Thimmaiah, Devraj. "Využití velikostní distribuce a elementárního složení městského aerosolu pro odhadu hlavních zdrojů/procesů podmikronových Pražských aerosolu pomocí receptorové modelování metody-Bilinear Positive Matrix Factorization." Doctoral thesis, 2009. http://www.nusl.cz/ntk/nusl-274234.
Full textAbstract:
Thesis Summary In this study' the sourcesofambient aerosolsin th€ uÍbanatmosphereofPrague, Czech Republic are apportionedusing bilinear Positive Matrix Faďorization (PMF2). Prior to this worl limited use of PMF techniquehas b€ťÍ' ryplied to Prague aerosols while elsewherearoundthe world, it has beenaaively usedby aerosol scientiststo reap thebenefitsince its fint inÚoduction in tbevea 1993. ln the currentstudy,the combinď pctrte nmber size disributions and readily available gaseous concentration .láa $tÍE 'E.d b ryortioning winter sub.micron particle sources in the urbm atmospbc of hgr. Tlle anbient Particle Number Concentations (PNC) wereotxainedsing r Scmng Mobility Particle Sizer (SMPS) in the size rangebetweeÍr14.ó md 73ó.5 m (Btd9od dianaers) along with the ambient gaseous concentrationsof CO, SQ. l,io, ()O * ]\iQL q, CH4, and Non Methane Hydrocarbons(NMHC) at the reccprr sit< e xllqriped rooftop sampling station(at height about 25m above street leall 25E AsL) be|onging to th€ Institute for Environmentalstuďes, Cbates tJnngsal 0aoe.5ď 4, |7.46"N; longifude-l4o25' 14.92 E). It is situared insi& lb. rDncn$! borni:al garden (area 0.035 km2).The receptoÍsite is shie|dedfrom diÍcctsouccs ofpo|hrin and thereaÍeno streetcanyon conditionsthatmigbt affea Úr sr@ry cmúm The meteorological d-Í. coocÍnmg umd...