La surveillance de la qualité de l'air est actuellement effectuée avec des mesures de concentration et à partir d'outils de modélisation de la dispersion atmosphérique. Ces modèles numériques évaluent les concentrations des polluants avec une résolution spatio-temporelle plus fine que les mesures. Néanmoins, les estimations fournies par ces modèles sont moins précises que les mesures. Dans ce projet de recherche, nous avons étudié les approches de couplage d'échelles et d'assimilation de données pour améliorer les estimations fournies par le modèle de dispersion atmosphérique SIRANE, dédié à l'échelle urbaine. L'approche de couplage d'échelles consiste à déterminer les conditions aux limites d'une simulation à partir d'une autre simulation à plus grande échelle. Au cours de ce travail de thèse, nous avons analysé trois méthodes afin de coupler le modèle urbain SIRANE et le modèle à méso-échelle CHIMERE. Cette étude montre que ces méthodes permettent potentiellement d'estimer la qualité de l'air à l'échelle urbaine de manière plus satisfaisante que les modèles à méso-échelle (utilisés seuls). Cependant, elles n'améliorent pas forcément la modélisation des conditions aux limites d'une simulation à l'échelle urbaine et les estimations fournies par celles-ci. Cela est a priori lié au fait que les estimations fournies par le modèle CHIMERE ne sont pas suffisamment satisfaisantes sur notre cas d'étude. Il est néanmoins possible que ces méthodes améliorent les résultats à l'échelle urbaine en utilisant une simulation à l'échelle régionale de meilleure qualité. L'approche d'assimilation de données consiste à combiner les mesures et les données modélisées afin de déterminer la meilleure estimation de l'état d'un système. Durant cette thèse, nous avons étudié trois méthodes d'assimilation de données : la méthode de débiaisement, la méthode que nous avons nommée modulation de la contribution des sources et la méthode Best Linear Unbiased Estimator. Cette étude indique que ces méthodes permettent globalement d'améliorer les estimations fournies par le modèle SIRANE. L'étude de sensibilité vis-à-vis du nombre de mesures utilisées lors de l'assimilation de données indique qu'en général, plus ce nombre est élevé plus les résultats sont satisfaisants. Enfin, les résultats montrent que les performances statistiques associées à ces trois méthodes d'assimilation de données sont globalement comparables entre elles sur notre cas d'étude. / Air quality monitoring is currently carried out with concentration measurements and with atmospheric dispersion modeling tools. These numerical models evaluate pollutant concentrations with a finer spatio-temporal resolution than measurements. Nevertheless, the estimates provided by these models are less accurate than measurements. In this research project, we studied multiscale coupling and data assimilation approaches to improve the estimates provided by the SIRANE atmospheric dispersion model, dedicated to the urban scale. The multiscale coupling approach consists in determining the boundary conditions of a simulation from another simulation on a larger scale. In this thesis work, we analyzed three methods for coupling the SIRANE model with the CHIMERE mesoscale model. This study shows that these methods can potentially estimate the air quality at the urban scale more satisfactorily than the mesoscale models (used alone). However, they do not necessarily improve the modeling of the boundary conditions of a simulation at the urban scale and the estimates provided by them. This is a priori due to the fact that the estimates provided by the CHIMERE model are not sufficiently good on our case study. It is possible, however, that these methods improve the results at the urban scale by using a better simulation at the regional scale. The data assimilation approach consists of combining the measurements and the modelled data to determine the best estimate of the system state. During this thesis, we studied three data assimilation methods : the unbiased method, the method that we called source apportionment modulation, and the Best Linear Unbiased Estimator method. This study indicates that these methods generally improve the estimates provided by the SIRANE model. The sensitivity study on the number of measurements used during the data assimilation indicates that, in general, higher is this number, more satisfactory are the results. Finally, the results show that the statistical performances associated with these three data assimilation methods are globally comparable on our case study.

A percepção crescente da sociedade em relação aos perigos inerentes às instalações industriais que manipulam grandes inventários de substâncias perigosas faz com que a ferramenta análise quantitativa de risco ganhe importância na complexa discussão sobre a viabilidade destes empreendimentos, no intuito de promover a ocupação adequada do solo na área urbana e prevenir a ocorrência do chamado acidente maior. Contudo, para se chegar à expressão de risco de uma determinada instalação industrial deve-se aplicar um conjunto de técnicas e de modelos matemáticos, entre os quais estão os modelos de dispersão atmosférica, usados para se estimar a área afetada na vizinhança da mesma por liberações acidentais que levam à formação de nuvens de substâncias químicas na atmosfera. Em decorrência da complexidade inerente ao próprio processo de dispersão atmosférica, especialmente no que tange aos denominados gases densos, existe uma diversidade de modelos que podem ser aplicados no escopo da análise de risco, o que leva a seus usuários, naturalmente, ao questionamento sobre a suscetibilidade dos resultados finais ao tipo de modelagem adotada. Neste sentido, este trabalho estuda o processo de dispersão atmosférica de nuvens densas formadas em liberações acidentais, identificando as principais possibilidades de modelagem deste processo e, ao final, apresenta um estudo de caso demonstrando que diferentes modelagens desta dispersão, comumente empregadas em análise de risco de instalações industriais, podem produzir variações na estimativa do risco de uma mesma instalação e, portanto, influenciar as decisões baseadas em risco. / The concern of the society about the risks posed by activities that deal with hazardous substances has increased in an environment strongly industrialized and with high population density in view of the inherent potential hazards of them as well as the impact of recent accidental episodes, even though their benefits provided. In this context the quantitative risk analysis is presented as an essential tool to assess the risk of these activities and compose a complex discussion about its feasibility. Some of these accident scenarios may involve the formation of a hazardous product cloud and its subsequent air dispersion in the off-site region when an accidental released take place and one should apply the so-called atmospheric dispersion models for estimating the consequences of the releases. Due to the complexity involved in this atmospheric dispersion process, there is a wide variety of mathematical models that can be applied for estimating the offsite consequences of the accidental releases leading, naturally, to one wonder whether the final risk expression of a facility is susceptible to these differences. Often in the world of industrial use of hazardous materials, toxic or flammable there is a possibility that these accidental releases produce clouds that are denser than air, a situation that demands even more attention in terms of risk aspects involved. Then, this dissertation studies the process of atmospheric dispersion of heavier-than-air clouds produced after an accidental release, identifying the main ways of modelling the process and presents a case study comparing different dispersion models that demonstrates that the final expression of risk of a typical installation can be different when it is used different dispersion model in the process.

Cette thèse s'inscrit dans un projet de modélisation numérique de la dispersion atmosphérique de polluants à travers le code de mécanique des fluides numérique Code_Saturne. L'objectif est de pouvoir simuler la dispersion atmosphérique de polluants en environnement complexe, c'est-à-dire autour de centrales, sites industriels ou en milieu urbain. Dans ce contexte, nous nous concentrons sur la modélisation de la dispersion des polluants à micro-échelle, c'est-à-dire pour des distances de l'ordre de quelques mètres à quelques kilomètres et correspondant à des échelles de temps de l'ordre de quelques dizaines de secondes à quelques dizaines de minutes : on parle de modélisation en champ proche. L’approche suivie dans ces travaux de recherche suit une formulation hybride eulérienne/lagrangienne, où les champs dynamiques moyens relatifs au fluide porteur (pression, vitesse, température, turbulence) sont calculés via une approche eulérienne et sont ensuite fournis au solveur lagrangien. Ce type de formulation est couramment utilisé dans la littérature atmosphérique pour son efficacité numérique. Le modèle lagrangien stochastique considéré dans nos travaux est le Simplified Langevin Model (SLM), développé par Pope (1985,2000). Ce modèle appartient aux méthodes communément appelées méthodes PDF (Probability Density Function), et, à notre connaissance, n'a pas été exploité auparavant dans le contexte de la dispersion atmosphérique. Premièrement, nous montrons que le SLM respecte le critère dit de mélange homogène (Thomson, 1987). Ce critère, essentiel pour juger de la bonne qualité d'un modèle lagrangien stochastique, correspond au fait que si des particules sont initialement uniformément réparties dans un fluide incompressible, alors elles doivent le rester. Nous vérifions le bon respect du critère de mélange homogène pour trois cas de turbulence inhomogène représentatifs d'une large gamme d'applications pratiques : une couche de mélange, un canal plan infini, ainsi qu'un cas de type atmosphérique mettant en jeu un obstacle au sein d'une couche limite neutre. Nous montrons que le bon respect du critère de mélange homogène réside simplement en la bonne introduction du terme de gradient de pression en tant que terme de dérive moyen dans le modèle de Langevin (Pope, 1987; Minier et al., 2014; Bahlali et al., 2018c). Nous discutons parallèlement de l'importance de la consistance entre champs eulériens et lagrangiens dans le cadre de telles formulations hybrides eulériennes/lagrangiennes. Ensuite, nous validons le modèle dans le cas d'un rejet de polluant ponctuel et continu, en conditions de vent uniforme et turbulence homogène. Dans ces conditions, nous disposons en effet d'une solution analytique nous permettant une vérification précise. Nous observons que dans ce cas, le modèle lagrangien discrimine bien les deux différents régimes de diffusion de champ proche et champ lointain, ce qui n'est pas le cas d'un modèle eulérien à viscosité turbulente (Bahlali et al., 2018b).Enfin, nous travaillons sur la validation du modèle sur plusieurs campagnes expérimentales en atmosphère réelle, en tenant compte de la stratification thermique de l'atmosphère et de la présence de bâtiments. Le premier programme expérimental considéré dans nos travaux concerne le site du SIRTA (Site Instrumental de Recherche par Télédétection Atmosphérique), dans la banlieue sud de Paris, et met en jeu une stratification stable de la couche limite atmosphérique. La seconde campagne étudiée est l'expérience MUST (Mock Urban Setting Test). Réalisée aux Etats-Unis, dans le désert de l'Utah, cette expérience a pour but de représenter une ville idéalisée, au travers d'un ensemble de lignées de conteneurs. Deux rejets ont été simulés et analysés, respectivement en conditions d'atmosphère neutre et stable (Bahlali et al., 2018a) / This Ph.D. thesis is part of a project that aims at modeling pollutant atmospheric dispersion with the Computational Fluid Dynamics code Code_Saturne. The objective is to simulate atmospheric dispersion of pollutants in a complex environment, that is to say around power plants, industrial sites or in urban areas. In this context, the focus is on modeling the dispersion at micro-scale, that is for distances of the order of a few meters to a few kilometers and corresponding to time scales of the order of a few tens of seconds to a few tens of minutes: this is also called the near field area. The approach followed in this thesis follows a hybrid Eulerian/Lagrangian formulation, where the mean dynamical fields relative to the carrier fluid (pressure, velocity, temperature, turbulence) are calculated through an Eulerian approach and are then provided to the Lagrangian solver. This type of formulation is commonly used in the atmospheric literature for its numerical efficiency. The Lagrangian stochastic model considered in our work is the Simplified Langevin Model (SLM), developed by Pope (1985,2000). This model belongs to the methods commonly referred to as PDF (Probability Density Function) methods, and, to our knowledge, has not been used before in the context of atmospheric dispersion. First, we show that the SLM meets the so-called well-mixed criterion (Thomson, 1987). This criterion, essential for any Lagrangian stochastic model to be regarded as acceptable, corresponds to the fact that if particles are initially uniformly distributed in an incompressible fluid, then they must remain so. We check the good respect of the well-mixed criterion for three cases of inhomogeneous turbulence representative of a wide range of practical applications: a mixing layer, an infinite plane channel, and an atmospheric-like case involving an obstacle within a neutral boundary layer. We show that the good respect of the well-mixed criterion lies simply in the good introduction of the pressure gradient term as the mean drift term in the Langevin model (Pope, 1987; Minier et al., 2014; Bahlali et al., 2018c). Also, we discuss the importance of consistency between Eulerian and Lagrangian fields in the framework of such Eulerian/Lagrangian hybrid formulations. Then, we validate the model in the case of continuous point source pollutant dispersion, under uniform wind and homogeneous turbulence. In these conditions, there is an analytical solution allowing a precise verification. We observe that in this case, the Lagrangian model discriminates well the two different near- and far-field diffusion regimes, which is not the case for an Eulerian model based on the eddy-viscosity hypothesis (Bahlali et al., 2018b).Finally, we work on the validation of the model on several experimental campaigns in real atmosphere, taking into account atmospheric thermal stratification and the presence of buildings. The first experimental program considered in our work has been conducted on the `SIRTA' site (Site Instrumental de Recherche par Télédétection Atmosphérique), in the southern suburb of Paris, and involves a stably stratified surface layer. The second campaign studied is the MUST (Mock Urban Setting Test) experiment. Conducted in the United States, in Utah's desert, this experiment aims at representing an idealized city, through several ranges of containers. Two cases are simulated and analyzed, respectively corresponding to neutral and stable atmospheric stratifications (Bahlali et al., 2018a)

L’objectif de la thèse est d’effectuer l’analyse de sensibilité paramétrique du logiciel Phast de modélisation de la dispersion atmosphérique de gaz toxiques et/ou inflammables. La technique a consisté à coupler Phast et l’outil d’analyse de sensibilité SimLab, ce qui permet d’exécuter automatiquement un grand nombre de simulations en faisant varier l’ensemble des paramètres du modèle de façon simultanée. La méthode d’analyse de sensibilité globale choisie, E-FAST, est basée sur l’analyse de la variance des sorties du modèle pour le calcul des indices de sensibilité. Nous avons étudié des scénarios de rejet continus pour six produits différents (monoxyde d’azote, ammoniac, chlore, azote, n-hexane et fluorure d’hydrogène), sélectionnés pour couvrir une large gamme de caractéristiques physiques et de conditions de stockage. L’analyse du modèle de dispersion de Phast, Unified Dispersion Model, a été séparée en deux étapes : étape de « screening » avec pour but de comparer l’influence de l’ensemble des paramètres puis étude de l’influence globale des paramètres de modélisation, autres que les paramètres météo et du terme source, sur une plage large de valeurs. Pour chaque produit, nous avons décomposé les scénarios de base en sous-scénarios correspondant à des conditions de rejet différentes. Ce travail a notamment permis de classifier les paramètres du modèle selon leur degré d’influence sur la variabilité de différentes sorties et d’effectuer une analyse comparative par produit indiquant, pour des conditions de rejet données, quels paramètres sont les plus influents sur les sorties. Une étude complémentaire a consisté à effectuer une analyse de sensibilité locale de ces paramètres autour de leur valeur par défaut. / We have undertaken a parametric sensitivity analysis of the Phast software tool’s models for atmospheric dispersion of toxic and/or inflammable gases. We have coupled Phast with the sensitivity analysis tool SimLab, and have automated the execution of a large number of simulations while varying simultaneously selected model parameters. The global sensitivity analysis method used, E-FAST, is based on analysis of the variance of model outputs, and allows us to estimate sensitivity indices. We have studied continuous release scenarios for six different products (nitric oxide, ammonia, chlorine, nitrogen, n-hexane and hydrogen fluoride), which were chosen to cover a wide range of physical characteristics and storage conditions. Our analysis of Phast’s Unified Dispersion Model comprises two phases: a screening phase which allows the sensitivity of a wide range of parameters to be compared, followed by a phase focusing on the sensitivity of internal model parameters (excluding weather and source term variables), over a wide input range. For each product, we have broken down base-case scenarios into a number of sub-scenarios corresponding to different release conditions. This work has allowed us to rank model parameters according to their influence on the variability of a number of model outputs. It also includes a per-product comparative analysis indicating, for each release condition studied, which parameters have the most influence on the outputs. In the final part of the work, we have analyzed the local sensitivity of these parameters in a narrow range around their default values.

<p>The MIUU mesoscale model was further developed, in order to include information on large-scale atmospheric fields from global or regional atmospheric climate- and weather-prediction models. For this purpose, a new lateral boundary condition was developed and implemented into the model. The new lateral boundary condition is a combination of two existing conditions, namely the flow relaxation scheme and the tendency modification scheme.</p><p>Tests indicated that an optimum lateral boundary configuration would be obtained with moderate to strong flow relaxation at higher levels, small flow relaxation at lower levels (within the atmospheric boundary layer), upstream advection at the outermost 4 grid points, and 6% horizontal grid stretching starting at a substantial distance from the lateral boundaries. The flow relaxation coefficients should be specified carefully, in order to minimize the reflection of all kinds of waves at the lateral boundaries.</p><p>The summer thermal low in the mean-sea-level pressure field over North America is traditionally analyzed over the northern end of the Gulf of California. The position of this low is influenced by the application of the so-called plateau correction in obtaining mean-sea-level pressure values from highly elevated stations in North America. A model study indicated that the low should be located approximately 450 km to the north and somewhat to the east of the above location. </p><p>A statistical comparison of model results from two mesoscale models against upper-air and surface measurements from several sites was carried out. Statistical methods, however, give only an insufficient picture of overall model performance. A comparison between predicted and measured tracer concentrations could be used to better evaluate the overall performance of different models.</p><p>Sound propagation in the atmosphere was predicted in a mountain valley using a mesoscale atmospheric model together with a sound propagation model. This suggests that forecasts of sound propagation should be possible in future.</p>

The MIUU mesoscale model was further developed, in order to include information on large-scale atmospheric fields from global or regional atmospheric climate- and weather-prediction models. For this purpose, a new lateral boundary condition was developed and implemented into the model. The new lateral boundary condition is a combination of two existing conditions, namely the flow relaxation scheme and the tendency modification scheme. Tests indicated that an optimum lateral boundary configuration would be obtained with moderate to strong flow relaxation at higher levels, small flow relaxation at lower levels (within the atmospheric boundary layer), upstream advection at the outermost 4 grid points, and 6% horizontal grid stretching starting at a substantial distance from the lateral boundaries. The flow relaxation coefficients should be specified carefully, in order to minimize the reflection of all kinds of waves at the lateral boundaries. The summer thermal low in the mean-sea-level pressure field over North America is traditionally analyzed over the northern end of the Gulf of California. The position of this low is influenced by the application of the so-called plateau correction in obtaining mean-sea-level pressure values from highly elevated stations in North America. A model study indicated that the low should be located approximately 450 km to the north and somewhat to the east of the above location. A statistical comparison of model results from two mesoscale models against upper-air and surface measurements from several sites was carried out. Statistical methods, however, give only an insufficient picture of overall model performance. A comparison between predicted and measured tracer concentrations could be used to better evaluate the overall performance of different models. Sound propagation in the atmosphere was predicted in a mountain valley using a mesoscale atmospheric model together with a sound propagation model. This suggests that forecasts of sound propagation should be possible in future.

This work is a multi-scale effort to confront the rapidly evolving threat of biological weapons attacks through improved bioaerosol surveillance, detection, and response capabilities. The effects of bioaerosol release characteristics, transport in the atmospheric surface layer, and implications for bioaerosol sampler design and real-time detection were studied to develop risk assessment and modeling tools to enhance our ability to respond to biological weapons attacks. A simple convection-diffusion-sedimentation model was formulated and used to simulate atmospheric bioaerosol dispersion. Model predictions suggest particles smaller than 60 micrometers in aerodynamic diameter (AD) are likely to be transported several kilometers from the source. A five fold increase in effective mass collection rate, a significant bioaerosol detection advantage, is projected for samplers designed to collect particles larger than the traditional limit of 10 micrometers AD when such particles are present in the source distribution. A family of dynamically scaled wetted-wall bioaerosol sampling cyclones (WWC) was studied to provide bioaerosol sampling capability under various threat scenarios. The effects of sampling environment, i.e. air conditions, and air flow rate on liquid recovery rate and response time were systematically studied. The discovery of a critical liquid input rate parameter enabled the description of all data with self-similar relationships. Empirical correlations were then integrated into system control algorithms to maintain microfluidic liquid output rates ideally suited for advanced biological detection technologies. Autonomous ambient air sampling with an output rate of 25 microliters per minute was achieved with open-loop control. This liquid output rate corresponds to a concentration rate on the order of 2,000,000, a substantial increase with respect to other commercially available bioaerosol samplers. Modeling of the WWC was performed to investigate the underlying physics of liquid recovery. The set of conservative equations governing multiphase heat and mass transfer within the WWC were formulated and solved numerically. Approximate solutions were derived for the special cases of adiabatic and isothermal conditions. The heat and mass transfer models were then used to supplement empirical correlations. The resulting semi-empirical models offer enhanced control over liquid concentration factor and further enable the WWC to be deployed as an autonomous bioaerosol sampler. / text

This experimental study analyses the dynamics of concentration fluctuations in a passive plume emitted by a point source within the turbulent boundary layer. We aim to extend the popular study of Fackrell and Robins (1982) about concentration fluctuations and fluxes from point sources by including third and fourth moments of concentration. We also further inquire into the influence of source conditions, such as the source size, source elevation and emission velocity, on higher order concentration moments. The data set is completed by a detailed description of the velocity statistics within the TBL, with exhaustive information on both the temporal and spatial structure of the flow. The experimental data-set has been used to test two different modeling ap- proaches: an analytical meandering plume model (in one and in three dimen- sions) and a Lagrangian stochastic micro-mixing model.

Η ατμοσφαιρική ρύπανση επηρεάζει την δημόσια υγεία, το φυσικό οικοσύστημα και επιφέρει μεταβολές στις κλιματικές συνθήκες. Το πρόβλημα της αέριας ρύπανσης παρουσιάζεται εντονότερο σε αστικές περιοχές, όπου η συσσώρευση ανθρωπίνων δραστηριοτήτων οδηγεί κατά κανόνα σε αυξημένες εκπομπές αερίων. Κάτω από την επήρεια δυσμενών μετεωρολογικών συνθηκών, τα επίπεδα συγκεντρώσεων των ρύπων μπορούν να ξεπεράσουν τα όρια της Παγκόσμιας Οργάνωσης Υγείας. Για την αποτελεσματική αντιμετώπιση του προβλήματος είναι απαραίτητη η ανάλυση και η σωστή περιγραφή όλων των φαινομένων και παραγόντων που καθορίζουν τις σχέσεις πηγής – αποδέκτη και ατμοσφαιρικών ρύπων. Για το σκοπό αυτό ενδείκνυνται κυρίως μαθηματικά μοντέλα προσομοίωσης μετεωρολογικών φαινομένων και φαινομένων διασποράς και μετασχηματισμού ρύπων. Η έντονη ευαισθητοποίηση της κοινής γνώμης σε θέματα σχετικά με την προστασία του περιβάλλοντος αναγκάζει τις κυβερνήσεις των χωρών να επιβάλλουν την διερεύνηση των συνεπειών έργων και δραστηριοτήτων στο ατμοσφαιρικό περιβάλλον. Τα μοντέλα διασποράς ατμοσφαιρικών ρύπων είναι εύχρηστα εργαλεία που μπορούν να εκτιμήσουν συγκεντρώσεις ρύπων, έτσι ώστε αυτές να είναι αντιπροσωπευτικές στο χώρο και στον χρόνο. Οι μετρήσεις ρύπων με όργανα λαμβάνονται σε συγκεκριμένες θέσεις και ως εκ τούτου δεν είναι αντιπροσωπευτικές για μεγαλύτερες περιοχές. Μέσες τιμές ρύπων για μεγαλύτερες περιοχές υπολογίζονται εύκολα με μοντέλα ατμοσφαιρικής ρύπανσης. Σκοπός αυτής της εργασίας, είναι η πρόβλεψη των συγκεντρώσεων των ρύπων διοξειδίου του θείου SO2, ολικών οξειδίων του αζώτου NOx και της ποσοστιαίας κατανομής της συνεισφοράς των πηγών ρύπανσης στις συγκεντρώσεις των ρύπων που καταγράφονται στις θέσεις των αποδεκτών με την χρήση του λογισμικού AERMOD της Εταιρίας Περιβαλλοντικής Προστασίας (EPA) των ΗΠΑ. Το AERMOD χρησιμοποιεί γκαουσιανά μοντέλα διασποράς. Για τον σκοπό αυτό συγκεντρώνονται και χρησιμοποιούνται πολλά και διαφορετικού τύπου δεδομένα, όπως μετεωρολογικά, γεωγραφικά, κυκλοφορίας αυτοκινήτων και πλοίων, εκπομπές ρύπων κ.α. Επίσης γίνεται η υπόθεση, ότι οι μεγαλύτερες συνεισφορές στην ατμοσφαιρική ρύπανση της Πάτρας γίνονται από την κυκλοφορία των αυτοκινήτων, από τα πλοία του λιμανιού και τις κεντρικές θερμάνσεις των κατοικιών. Η πρόβλεψη που προκύπτει μετά από την επεξεργασία των παραπάνω δεδομένων από το πρόγραμμα AERMOD συγκρίνεται με τα διαθέσιμα αποτελέσματα των μετρήσεων για ατμοσφαιρικούς ρύπους από το Εργαστήριο Τεχνολογίας του Περιβάλλοντος, που έγιναν στην Πάτρα στο διάστημα από τις 13 Νοεμβρίου του 1997 έως τις 23 Ιανουαρίου του 1998, κατά τις πρωινές (8:30 – 9:30) και βραδινές ώρες (20:30 – 21:30) στα πλαίσια διπλωματικής εργασίας υπό την επίβλεψη του κ. Π. Γιαννόπουλου. Στο Κεφάλαιο 1 αναφέρονται γενικές πληροφορίες για την ατμοσφαιρική ρύπανση, την πόλη της Πάτρας, για τους σημαντικότερους ρύπους της ατμόσφαιρας, αλλά και το πώς τα μετεωρολογικά φαινόμενα επηρεάζουν την διασπορά των ρύπων. Στο 2ο Κεφάλαιο αναφέρονται γενικές πληροφορίες για τα σημαντικότερα μαθηματικά μοντέλα ατμοσφαιρικής διασποράς, ενώ στο 3ο κεφάλαιο γίνεται μία γενική περιγραφή του θεωρητικού υπόβαθρου του προγράμματος AERMOD και του Προγράμματος AERMET. Στο Κεφάλαιο 4 παρουσιάζονται τα γεωγραφικά και μετεωρολογικά δεδομένα, τα δεδομένα για τους φόρτους κυκλοφορίας των οχημάτων στην πόλη της Πάτρας αλλά και πληροφορίες για την κίνηση των πλοίων στο παλιό λιμάνι της Πάτρας. Στο 4ο κεφάλαιο παρουσιάζονται οι υπολογισμοί των εκπομπών των ρύπων από τα αυτοκίνητα, τα πλοία και τις κεντρικές θερμάνσεις των κατοικιών. Επίσης παρουσιάζεται η ποσοστιαία κατανομή των εκπομπών από τις πηγές ατμοσφαρικής ρύπανσης και η συνεισφορά της κάθε μιας στην ρύπανση της ατμόσφαιρας. Τέλος παρουσιάζονται οι προβλέψεις που προκύπτουν για τις συγκεντρώσεις των ρύπων στις θέσεις των αποδεκτών και η σύγκριση αυτών με τις μετρήσεις για ατμοσφαιρικούς ρύπους που είχαν γίνει από το Νοέμβριο του 97 έως τον Ιανουάριο του 98. Στο Κεφάλαιο 5 παρουσιάζονται τα συμπεράσματα της εργασίας. Σαν συμπέρασμα της εργασίας προκύπτει ότι τα γκαουσιανά μοντέλα ατμοσφαιρικής διασποράς είναι χρήσιμα εργαλεία για την βραχυπρόθεσμη πρόγνωση των επιπέδων ρύπανσης, την εκτίμηση της συνεισφοράς των επί μέρους πηγών στην ποιότητα του αέρα και τη βελτιστοποίηση των στρατηγικών αντιρρύπανσης. Επισημαίνεται ότι τα μοντέλα προσομοίωσης αποτελούν την μοναδική μεθοδολογία αναφορικά με την δυνατότητα εκτίμησης της συνεισφοράς των επιμέρους πηγών. Επίσης, από τα αποτελέσματα αυτής της εργασίας προκύπτουν χρήσιμα συμπεράσματα για την προέλευση της ατμοσφαιρικής ρύπανσης στην πόλη της Πάτρας, όπως το ότι το μεγαλύτερο ποσοστό της (65 – 76% για το SO2 και 85 – 92% για NOx) προέρχεται από την κυκλοφορία των οχημάτων, ενώ αξιοσημείωτα είναι και τα ποσοστά των ρύπων που προέρχονται από τις κεντρικές θερμάνσεις (17 – 29% για το SO2 και 7,5 – 14,2% για NOx). Επίσης από τα αποτελέσματα φαίνεται ότι τα ποσοστά των ΝΟx που προέρχονται από τα πλοία είναι πολύ μικρά (0,3% - 0,4%), ενώ αντίθετα τα αντίστοιχα ποσοστά του SO2 (6% – 7%) είναι αξιοσημείωτα. Τέλος, άξιο αναφοράς είναι ότι όπως προκύπτει από τις συγκεντρώσεις των ρύπων που προβλέπει το AERMOD, φαίνεται ότι σε μία ζώνη πλάτους 400 m γύρω από το λιμάνι το ποσοστό της συγκέντρωσης του SO2 είναι αυξημένο (8% – 9%). / Air pollution affects public health, natural ecosystem and bring changes in climatic conditions. The problem of air pollution are most marked in urban areas, where the accumulation of human activities should lead to increased greenhouse gases. Under the influence of adverse weather conditions, the concentration levels of pollutants can overcome the limits of the World Health Organization. For the effective address of this problem is necessary to analyze all phenomena and factors that define the relationship source - receptor and atmospheric pollutants. For this purpose are suitable mathematical models simulating weather patterns and phenomena of dispersion and transformation of pollutants. The intense public awareness on issues related to the protection of the environment forces governments to impose the investigation of the effects of projects to the atmosphere. The air pollutant dispersion models are handy tools that can estimate pollutant concentrations, so that they are representative in space and time. The measurements of pollutants with instruments done at specific locations and therefore they are not representative for larger areas. Mean values for pollutants at larger areas easily calculated with models of atmospheric pollution. The aim of this work is the prediction of pollutant concentrations of sulfur dioxide SO2, total nitrogen oxides NOx and the percentage distribution of the contribution of pollution sources in pollutant concentrations recorded at the locations of receptors with the use of the software AERMOD. AERMOD belongs to the Environmental Protection Company (EPA) in the USA. AERMOD uses Gaussian dispersion models. For this purpose collected and used many different types of data, such as meteorological, geographical, automobile traffic and ship emissions, etc. Also it is assumed that the greatest contributions to air pollution of Patras come from the circulation of cars, from the port's ships and from the heating installations. The prediction obtained after processing the above data from the AERMOD program comes in comparison with the available results of measurements of air pollutants from the Laboratory of Environmental Engineering, held in Patras in the period from 13 November 1997 until 23 January 1998 in the morning (8:30 - 9:30) and evening (20:30 - 21:30) in the thesis under the supervision of Mr. P. Giannopoulos. In Chapter 1 reported general information on air pollution, about the significant atmospheric pollutants, and how weather conditions affect the dispersion of pollutants. In the second chapter reported general information about the most important mathematical atmospheric dispersion models, while in the third chapter gives a general description for the theoretical background of the programs AERMOD and AERMET. In Chapter 4 presents the geographical and meteorological data, data on motor vehicle traffic volumes in the city of Patras and information on the movement of ships in the old harbor of Patras. In the fourth chapter presented calculations of emissions of pollutants from cars, ships and central heating of homes. Also in the fourth chapter reported the percentage distribution of emissions from sources of atmospheric pollution and contribution of each in the pollution. Finally in the fourth chapter presented the forecasts for the concentrations of pollutants in the positions of the receptors and compare them with measurements for atmospheric pollutants that were made from November 97 until January 98. In Chapter 5 presented the conclusions of the work. As a conclusion of this study shows that the Gaussian atmospheric dispersion models are useful tools for short-term forecasting of pollution levels, and for the assessment of the contribution of individual sources on air quality. Noted that the simulation models are the unique methodology regarding the possibility of assessing the contribution of individual sources. Also, from the results of this work resulting conclusions about the origin of air pollution in the city of Patras, such that the highest percentage (65 - 76% for SO2 and 85 to 92% for NOx) comes from traffic vehicles, while noteworthy are the percentages of pollutants from central heating (17 - 29% for SO2 and 7.5 to 14.2% for NOx). Also, from the results it appears that rates of NOx from ships are very small (0.3% - 0.4%), while the corresponding percentages of SO2 (6% - 7%) is remarkable. Finally, it is worth mentioning that as indicated by the concentrations of pollutants that AERMOD calculates , it seems that in a zone extending 400 m around the harbor, the percentage of the concentration of SO2 is increased (8% - 9%).

A percepção crescente da sociedade em relação aos perigos inerentes às instalações industriais que manipulam grandes inventários de substâncias perigosas faz com que a ferramenta análise quantitativa de risco ganhe importância na complexa discussão sobre a viabilidade destes empreendimentos, no intuito de promover a ocupação adequada do solo na área urbana e prevenir a ocorrência do chamado acidente maior. Contudo, para se chegar à expressão de risco de uma determinada instalação industrial deve-se aplicar um conjunto de técnicas e de modelos matemáticos, entre os quais estão os modelos de dispersão atmosférica, usados para se estimar a área afetada na vizinhança da mesma por liberações acidentais que levam à formação de nuvens de substâncias químicas na atmosfera. Em decorrência da complexidade inerente ao próprio processo de dispersão atmosférica, especialmente no que tange aos denominados gases densos, existe uma diversidade de modelos que podem ser aplicados no escopo da análise de risco, o que leva a seus usuários, naturalmente, ao questionamento sobre a suscetibilidade dos resultados finais ao tipo de modelagem adotada. Neste sentido, este trabalho estuda o processo de dispersão atmosférica de nuvens densas formadas em liberações acidentais, identificando as principais possibilidades de modelagem deste processo e, ao final, apresenta um estudo de caso demonstrando que diferentes modelagens desta dispersão, comumente empregadas em análise de risco de instalações industriais, podem produzir variações na estimativa do risco de uma mesma instalação e, portanto, influenciar as decisões baseadas em risco. / The concern of the society about the risks posed by activities that deal with hazardous substances has increased in an environment strongly industrialized and with high population density in view of the inherent potential hazards of them as well as the impact of recent accidental episodes, even though their benefits provided. In this context the quantitative risk analysis is presented as an essential tool to assess the risk of these activities and compose a complex discussion about its feasibility. Some of these accident scenarios may involve the formation of a hazardous product cloud and its subsequent air dispersion in the off-site region when an accidental released take place and one should apply the so-called atmospheric dispersion models for estimating the consequences of the releases. Due to the complexity involved in this atmospheric dispersion process, there is a wide variety of mathematical models that can be applied for estimating the offsite consequences of the accidental releases leading, naturally, to one wonder whether the final risk expression of a facility is susceptible to these differences. Often in the world of industrial use of hazardous materials, toxic or flammable there is a possibility that these accidental releases produce clouds that are denser than air, a situation that demands even more attention in terms of risk aspects involved. Then, this dissertation studies the process of atmospheric dispersion of heavier-than-air clouds produced after an accidental release, identifying the main ways of modelling the process and presents a case study comparing different dispersion models that demonstrates that the final expression of risk of a typical installation can be different when it is used different dispersion model in the process.