661 research outputs found

    Aplicación de redes complejas a la descripción de la dinámica de contaminantes atmosféricos

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    Air pollution has been a major concern among environmental scientists due to its importance to public health. Among the different pollutants that can be found in the air, one can point out tropospheric ozone as one of the most studied ones in the recent years, due to the risk derived for living beings. As a result of the many factors involved in the creation and destruction of this gas, the analysis of its dynamics is quite complicated. Traditionally, conventional statistical methods have been employed, while in the last decades multifractal approaches have gained importance. This is due to their suitability describing systems with a great degree of variability. This thesis focuses on the evaluation and implementation of complex networks for the analysis of tropospheric O3 dynamics. The studies carried out are based on the Visibility Graph (VG) technique, which transforms time series into complex networks that inherit the properties of the first ones. In the first part, a combination of the VG and the multifractal Sand-Box (SB) algorithms is performed. By doing this, authors analyze the generalized fractal dimensions and the singularity spectra. Then, a comparison was made between these multifractal parameters and the quantities obtainable from the degree distribution of the resulting graphs. Regarding the second part of this thesis, the VG methodology was used on O3 time series from rural and urban stations, in order to retrieve the centrality parameters from the obtained networks. This way, degree, shortest path and betweenness are studied to support the use of this technique and find new information. Results show that this methodology can indeed differentiate between ozone measurements in urban and countryside environments, providing new insights about the dynamics. In the third and last part of this document, authors propose an alternative approach to the VG, called Sliding Visibility Graph (SVG). This new technique takes advantage of the fact that visibility adjacency matrices are mostly empty, since the bast majority of the nodes are not connected to each other. Thanks to this, it is possible to apply effectively a sliding window approach to lessen considerably the computation time, reducing one order the time efficiency (from O(N2) to O(N). This is especially convenient when dealing with very large time series. As the resulting network approximates the original VG, it has been evaluated how it converges to the VG case for different types of series, as there lies the actual interest of this tool. As expected, the SVG results converge quite rapidly to the exact values, especially for random and O3 concentration series.La contaminación atmosférica es uno de los principales problemas estudiados dentro de la ciencia ambiental, debido a su gran impacto en la salud pública. Entre los diferentes contaminantes que podemos encontrar en el aire, merece la pena destacar el ozono troposférico (O3) como uno de los más estudiados en los últimos años, debido al alto riesgo para los seres vivos. Como resultado de los numerosos factores implicados en la creación y destrucción de este gas, el análisis de sus dinámicas es bastante complejo. Tradicionalmente, se han usado métodos estadísticos convencionales, mientras que en las últimas décadas han ganado importancia las técnicas multifractales. Esto se debe a su adecuación para describir sistemas con un grado elevado de variabilidad. Esta tesis se centra en la evaluación e implementación de las redes complejas para el análisis de la dinámica del O3. Los estudios llevados a cabo se basan en el uso de la técnica del Grafo de Visibilidad (GV), que transforma series temporales en redes complejas que heredan propiedades de las primeras. En la primera parte, se utiliza una combinación del GV y del algoritmo multifractal Sand-Box (SB). Gracias a esto, es posible obtener las dimensiones fractales generalizadas y el espectro de singularidades. Por último, se ha realizado una comparación entre los parámetros multifractales y las cantidades obtenibles directamente a partir de la distribución del grado de los grafos resultantes. En cuanto a la segunda parte de esta tesis, el método del GV es usado en series temporales de O3 de estaciones rurales y urbanas, con la finalidad de obtener los parámetros de centralidad de las redes conseguidas. De este modo, el grado, el camino mínimo y la intermediación se estudian para refutar la aplicabilidad del GV y buscar nueva información. Los resultados muestran que en efecto esta metodología puede permitir diferenciar entre medidas de ozono en medios rurales y urbanos. En la tercera y última parte de este documento, los autores proponen un método alternativo al GV, llamado Grafo de Visibilidad Deslizante (GVD). Esta nueva técnica se aprovecha del hecho de que las matrices de adyacencia de los GV son prácticamente vacías, puesto que la mayoría de los vértices no están conectados entre sí. Gracias a ello, es posible aplicar de forma efectiva un algoritmo de ventana deslizante para reducir considerablemente el tiempo de cálculo, bajando en uno el orden de magnitud de la eficiencia (de O (N2) a O (N)). Esto es especialmente provechoso cuando se trata con series temporales muy grandes. Debido a que la red resultante aproxima al GV original, se ha evaluado cómo converge al segundo para diferentes tipos de series temporales, que es donde reside en interés real de esta herramienta. Como era de esperar, los resultados del GVD convergen rápidamente a los valores exactos, especialmente para series aleatorias y concentración de O3

    Existence of fractal behaviour in ozone time series

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    Fractal has received a wide attention and has been used in many areas such as meteorology, stock market and also in medical field. It can be viewed as an object which has similar appearance when viewed at different scales which are known as self-similar. Thus, the scale invariance and scaling properties of the time series may be explored using fractal techniques. The aim of this study is to investigate the presence of fractal behaviour in the ozone time series. The presence of fractal behaviour can lead to the possibility of implementing the fractal approach in order to examine the properties of a time series. In this study, the daily average of ozone concentration from six selected air monitoring stations with different types of backgrounds in Peninsular Malaysia are used. From the autocorrelation function (ACF) plot obtained for the six stations, the slow decay in ACF values indicates that self-similarity are present where it shows that the series is having the property of fractal behaviour. In this paper, the existence of fractal behaviour is investigated by using the power spectrum method and the empirical probability distribution function. The result shows that the daily average of ozone concentration exhibits fractal behaviour for all the six monitoring stations considered

    Multifractal characterisation of particulate matter (PM10) time series in the Caribbean basin using visibility graphs

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    Datos de investigación disponibles en: http://www.gwadair.frA good knowledge of pollutant time series behavior is fundamental to elaborate strategies and construct tools to protect human health. In Caribbean area, air quality is frequently deteriorated by the transport of African dust. In the literature, it is well known that exposure to particulate matter with an aerodynamic diameter of 10 μm or less (PM10) have many adverse health effects as respiratory and cardiovascular diseases. To our knowledge, no study has yet performed an analysis of PM10 time series using complex network framework. In this study, the so-called Visibility Graph (VG) method is used to describe PM10 dynamics in Guadeloupe archipelago with a database of 11 years. Firstly, the fractal nature of PM10 time series is highlighted using degree distribution for all data, low dust season (October to April) and high dust season (May to September). Thereafter, a profound description of PM10 time series dynamics is made using multifractal analysis through two approaches, i.e. Rényi and singularity spectra. Achieved results are consistent with PM10 behavior in the Caribbean basin. Both methods showed a higher multifractality degree during the low dust season. In addition, multifractal parameters exhibited that the low dust season has the higher recurrence and the lower uniformity degrees. Lastly, centrality measures (degree, closeness and betweenness) highlighted PM10 dynamics through the year with a decay of centrality values during the high dust season. To conclude, all these results clearly showed that VG is a robust tool to describe times series properties

    Laser induced fluorescence studies of dispersion by breaking waves

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    Background PM10 atmosphere: In the seek of a multifractal characterization using complex networks

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    In the literature, several epidemiological studies have already associated respiratory and cardiovascular diseases to acute exposure of mineral dust. However, frail people are also sensitive to chronic exposure to particulate matter with an aerodynamic diameter 10μm or less (PM10). Consequently, it is crucial to better understand PM10 fluctuations at all scales. This study investigates PM10 background atmosphere in the Caribbean area according to African dust seasonality with complex network framework. For that purpose, the regular Visibility Graph (VG) and the new Upside-Down Visibility Graph (UDVG) are used for a multifractal analysis. Firstly, concentration vs degree (v-k) plots highlighted that high degree values (hubs behavior) are related to the highest PM10 concentrations in VG while hubs is associated to the lowest concentrations in UDVG, i.e. probably the background atmosphere. Then, the degree distribution analysis showed that VG and UDVG difference is reduced for high dust season contrary to the low one. As regards the multifractal analysis, the multifractal degree is higher for the low season in VG while it is higher for the high season in UDVG. The degree distribution behavior and the opposite trend in multifractal degree for UDVG are due to the increase of PM10 background atmosphere during the high season, i.e. from May to September. To sum up, UDGV is an efficient tool to perform noise fluctuations analysis in environmental time series where low concentrations play an important role as wel

    Turbulent structure in environmental flows: effects of stratification and rotation

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    Several series of experiments in stratified and in rotating/stratified decaying flows after a grid is used to stir the two layer stable fluid brine and fresh water set up. We measure by comparing the gained potential energy with the available kinetic energy AKE, the relative efficiency of mixing. The experiments in stratified rotating flows with grid driven turbulence were both periodic (quasi stationary) and non-monotonic (decaying) forcing. This thesis compares experimental, numerical and field observations on the structure and Topology of the Stratified Rotating Flows as well as their decay, the horizontal spectra changes appreciable with slopes from 1.1 to 5, but vorticity and local circulation, and also the initial topology and forcing of the flow. A detailed study of the vorticity decay and vortex and energy structure has been performed, the new results show that neither stratified nor rotating flows exhibit pure 2D structures. The work parameterizes the role of the Richardson number and the Rossby number, both in the experiments and in the ocean visualizations is very important. The conditions of vortex decay show the effects of the internal waves in the decay turbulent conditions both for stratified and rotating flows. The parameter space (Re,Ri,Ro) has been used to interpret many previously disconnected explanations of the 2D-3D turbulent behaviour. The comparison of numerical simulations with experiments has allowed implementing new theoretical aspects of the interaction between waves and vortices finding the surprising and very interesting result that these interactions depend on the level of enstrophy. This also leads to new ways of using multifractal analysis ad intermittency in ocean environmental observations. A large collection of SAR images obtained from three European coastal areas were used for routine satellite analysis by SAR and other sensors, which seem very important to build seasonal databases of the dynamic conditions of ocean mixing. The topology of the basic flow is very important and in particular the topology of the vortices and their decay which depends on ambient factors such as wave activity, wind and currents. We find more realistic estimates of the spatial/temporal non-homogeneities (and intermittency obtained as spatial correlations of the turbulent dissipation); these values are used to parameterize the sea surface turbulence, as well as a laboratory experiments at a variety of scales. Using multi-fractal geometry as well, we can establish now a theoretical pattern for the turbulence behaviour that is reflected in the different descriptors. Vorticity evolution is smoother and different than that of scalar or tracer density. The correlation between the local Ri and the fractal dimension detected from energy or entropy is good. Using multi-fractal geometry we can also establish certain regions of higher local activity used to establish the geometry of the turbulence mixing that needs to be studied in detail when interpreting the complex balance between the direct 3D Kolmogorov type cascade and the Inverse 2D Kraichnan type cascade

    Joint multifractal analysis of air temperature, relative humidity and reference evapotranspiration in the middle zone of the Guadalquivir river valley

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    Previous works have analysed the relationship existing between reference evapotranspiration (ET0) and other climatic variables under a one-at-a-time perturbation condition. However, due to the physical relationships between these climatic variables is advisable to study their joint influence on ET0. The box-counting joint multifractal algorithm describes the relations between variables using relevant information extracted from the data singularities. This work investigated the use of this algorithm to describe the simultaneous behaviour of ET0, calculated by means of Penman–Monteith (PM) equation, and the two main climatic variables, relative humidity (RH) and air temperature (T), influencing on it in the middle zone of the Guadalquivir river valley, Andalusia, southern Spain. The studied cases were grouped according to the fractal dimension values, obtained from the global multifractal analysis, which were related to their probability of occurrence. The most likely cases were linked to smooth behaviour and weak dependence between variables, both circumstances were detected in the local multifractal analysis. For these cases, the rest of Penman Monteith (PM) equation variables, neither the T nor the RH, seemed to influence on ET0 determination, especially when low T values were involved. By contrast, the least frequent cases were those with variables showing high fluctuations and strong relationship between them. In these situations, when T is low, the ET0 is affected by the rest of PM equation variables. This fact confirmed T as main driver of ET0 because the higher T values the lesser influence of other climate variables on ET0. This condition could not be extended to RH because the variability in ET0 singularities was not significantly influenced by low or high values of this variable. These results show that the joint multifractal analysis can be regarded as a suitable tool for describing the complex relationship between ET0, T and RH, providing additional information to that derived from descriptive statistics. Although, joint multifractal analysis shows some limitations when it is applied to large number of variables, the results reported are promising and suggest the convenience of exploring the relationships between ET0 and other climatic variables not considered here with this framework such as wind speed and net radiation

    Breaking waves and the dispersion of surface films

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    Real-time pollen monitoring using digital holography

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    We present the first validation of the SwisensPoleno, currently the only operational automatic pollen mon-itoring system based on digital holography. The device pro-vides in-flight images of all coarse aerosols, and here wedevelop a two-step classification algorithm that uses theseimages to identify a range of pollen taxa. Deterministiccriteria based on the shape of the particle are applied toinitially distinguish between intact pollen grains and othercoarse particulate matter. This first level of discriminationidentifies pollen with an accuracy of 96 %. Thereafter, in-dividual pollen taxa are recognized using supervised learn-ing techniques. The algorithm is trained using data obtainedby inserting known pollen types into the device, and out ofeight pollen taxa six can be identified with an accuracy ofabove 90 %. In addition to the ability to correctly identifyaerosols, an automatic pollen monitoring system needs to beable to correctly determine particle concentrations. To fur-ther verify the device, controlled chamber experiments us-ing polystyrene latex beads were performed. This providedreference aerosols with traceable particle size and numberconcentrations in order to ensure particle size and samplingvolume were correctly characterized
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