Influence of the environment on behavior patterns of laying hens kept in cages

The aim of this paper is to verify the correlation between environmental indicators and behaviors expressed by laying hens kept in cages. The birds react to a severe environment through their behaviors, end the behaviors can be monitored to identify the birds' welfare conditions. The behaviors birds display ere the result of stress caused by the combination of environmental temperature, relative humidity, radiant heat, and air speed (environmental temperature being the most important). In order to check the influence of the environment, an experiment was carried out on a commercial poultry farm, located in the city of Bastos. The study was initiated in March 2007, during four non-consecutive weeks. The birds' behaviors were recorded using video, by cameras installed in the cages. The birds behaviors were identified and noted for the frequency of occurrence for each bird, and the average duration of each behavior (in seconds), using video samples of 15 minutes recorded from 1 PM to 4 PM. The environmental variables collected were: air temperature, concentration of ammonia, relative air humidity, velocity of the air, noise, roof temperature, and light intensity. The observed behaviors were: opening wings, stretching, threatening, ruffling feathers, drinking water, aggressive pecking, eating, running, lying down, stretching head out of the cage, preening, mounting and prostrating. Principal Components Analysis was used to determine associations between the behavior variables and environmental variables described above. In this experiment, there were no significant correlations between behavioral variables and environmental variables.

Interações entre o ambiente físico, uso e cobertura da terra e as características físicas e químicas no canal fluvial: a bacia hidrográfica do rio Santo Anastácio, Oeste Paulista (Dez. 2009 – Dez. 2010)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

História natural de Hypsiboas prasinus (Anura: Hylidae) na Serra do Japi, município de Jundiaí, São Paulo, Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudo de Simuliidae (Diptera : Nematocera) e seus criadouros em igarapés do município de Santo Antônio do Tauá, estado do Pará, Brasil

Considerando a grande importância dos simulídeos (piuns e borrachudos) do ponto de vista bio-ecológico, médico e veterinário, desenvolveu-se este estudo sobre as espécies do gênero Simulium que se criam em igarapés do município de Santo Antônio do Tauá, Estado do Pará, Brasil. Os estudos foram desenvolvidos pelas seguintes metodologias: observações diretas dos criadouros nos igarapés; instalação de criadouros artificiais para a colonização por simulídeos; análise das freqüências de picadas em pessoas durante o dia; coletas e amostragens da entomofauna associada aos habitats aquáticos; amostragens qualitativas e quantitativas da vegetação nos criadouros; análises físico-químicas da água dos igarapés e criadouros; análises de fatores climáticos locais; e morfometria das larvas para a determinação do número de estádios larvais de Simulium quadrifidum. Estudou-se a entomofauna aquática e a respectiva abundância relativa de Simuliidae em dois igarapés. As espécies Simulium perflavum,Simulium quadrifidum, Simulium incrustaium e Simulium goeldii foram coletadas. As formas imaturas de Simulium perflavum foram as predominantes em ambientes perturbados com águas claras. Simulium quadrifidum foi predominante em ambientes com pouca alteração, de águas pretas, com baixos teores de nutrientes. Simulium incrustatum foi mais abundante em ambientes arbustivos e somente em águas claras. Simulium goeldii foi registrada apenas em áreas de matas primárias (com pouca alteração) e mais abundante em águas pretas. Os fatores que mais interferiram na colonização natural dos substratos artificiais por Simuliidae foram as constantes oscilações no nível d'água durante o período quando em que substratos ficaram expostos nos igarapés. A entomofauna aquática apresentou-se abundante no período seco. Constatou-se pela primeira vez a antropofilia da espécie Simulium incrustatum no Pará. Esta espécie mostrou dois picos diários de freqüência de picadas em voluntários, um pela manhã e outro à tarde. Houve diferenças significativas na freqüência de picadas entre áreas com tipos diferentes de vegetação nos mesmos períodos, e alta correlação negativa com a temperatura do ar, apenas na área de capoeira e no período seco. Determinou-se, pela primeira vez, o número de estádios larvais de Simulium quadrifidum e registrou-se a ovipostura de suas fêmeas somente pela parte da tarde, às 16:30h. Novos registros de predadores de adultos de simulídeos foram acrescentados.

Poluição atmosférica e paisagem urbana no município de São Paulo

This paper proposes an analysis of two major polluting elements of the atmosphere of São Paulo city, carbon monoxide (CO) and sulfur dioxide (SO2). This study was performed through analysis of data on the quality of air, by means of published reports and records obtained by experiment using measuring rate monitor for CO2. Atmospheric data were collected and sorted. From this work it was possible to identify the concentration of carbon dioxide in the center of São Paulo on September 14, 2012 using the infrared gas analyzer (IRGA). From the ratios of carbon monoxide and sulfur dioxide spatially analyzed could identify major emitters by comparing records of pollutants and their origin. The analysis makes it possible to map the intensity of air pollution in urban areas, identifying the polluting elements, their issuers and thereby contributes to the current understanding of atmospheric features, bringing a geographical spatial analysis of air pollutants in São Paulo, contributing to awareness of vulnerabilities, enabling a useful tool for planning and maintenance of the urban environment related public policies

Calling activity and vocal repertoire of hypsiboas prasinus (Anura, Hylidae), a treefrog from the Atlantic Forest of Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Gestão integrada de resíduos sólidos urbanos nos municípios da UGRHI- 14 Alto Paranapanema: interfaces concretas e potencialidades

Pós-graduação em Geografia - FCT

Desenvolvimento de uma rede de sensores sem fio aplicada no monitoramento da variabilidade térmica em casas de vegetação

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modulation Techniques for Multi-Phase Converters and Control Strategies for Multi-Phase Electric Drives

The ever-increasing spread of automation in industry puts the electrical engineer in a central role as a promoter of technological development in a sector such as the use of electricity, which is the basis of all the machinery and productive processes. Moreover the spread of drives for motor control and static converters with structures ever more complex, places the electrical engineer to face new challenges whose solution has as critical elements in the implementation of digital control techniques with the requirements of inexpensiveness and efficiency of the final product. The successfully application of solutions using non-conventional static converters awake an increasing interest in science and industry due to the promising opportunities. However, in the same time, new problems emerge whose solution is still under study and debate in the scientific community During the Ph.D. course several themes have been developed that, while obtaining the recent and growing interest of scientific community, have much space for the development of research activity and for industrial applications. The first area of research is related to the control of three phase induction motors with high dynamic performance and the sensorless control in the high speed range. The management of the operation of induction machine without position or speed sensors awakes interest in the industrial world due to the increased reliability and robustness of this solution combined with a lower cost of production and purchase of this technology compared to the others available in the market. During this dissertation control techniques will be proposed which are able to exploit the total dc link voltage and at the same time capable to exploit the maximum torque capability in whole speed range with good dynamic performance. The proposed solution preserves the simplicity of tuning of the regulators. Furthermore, in order to validate the effectiveness of presented solution, it is assessed in terms of performance and complexity and compared to two other algorithm presented in literature. The feasibility of the proposed algorithm is also tested on induction motor drive fed by a matrix converter. Another important research area is connected to the development of technology for vehicular applications. In this field the dynamic performances and the low power consumption is one of most important goals for an effective algorithm. Towards this direction, a control scheme for induction motor that integrates within a coherent solution some of the features that are commonly required to an electric vehicle drive is presented. The main features of the proposed control scheme are the capability to exploit the maximum torque in the whole speed range, a weak dependence on the motor parameters, a good robustness against the variations of the dc-link voltage and, whenever possible, the maximum efficiency. The second part of this dissertation is dedicated to the multi-phase systems. This technology, in fact, is characterized by a number of issues worthy of investigation that make it competitive with other technologies already on the market. Multiphase systems, allow to redistribute power at a higher number of phases, thus making possible the construction of electronic converters which otherwise would be very difficult to achieve due to the limits of present power electronics. Multiphase drives have an intrinsic reliability given by the possibility that a fault of a phase, caused by the possible failure of a component of the converter, can be solved without inefficiency of the machine or application of a pulsating torque. The control of the magnetic field spatial harmonics in the air-gap with order higher than one allows to reduce torque noise and to obtain high torque density motor and multi-motor applications. In one of the next chapters a control scheme able to increase the motor torque by adding a third harmonic component to the air-gap magnetic field will be presented. Above the base speed the control system reduces the motor flux in such a way to ensure the maximum torque capability. The presented analysis considers the drive constrains and shows how these limits modify the motor performance. The multi-motor applications are described by a well-defined number of multiphase machines, having series connected stator windings, with an opportune permutation of the phases these machines can be independently controlled with a single multi-phase inverter. In this dissertation this solution will be presented and an electric drive consisting of two five-phase PM tubular actuators fed by a single five-phase inverter will be presented. Finally the modulation strategies for a multi-phase inverter will be illustrated. The problem of the space vector modulation of multiphase inverters with an odd number of phases is solved in different way. An algorithmic approach and a look-up table solution will be proposed. The inverter output voltage capability will be investigated, showing that the proposed modulation strategy is able to fully exploit the dc input voltage either in sinusoidal or non-sinusoidal operating conditions. All this aspects are considered in the next chapters. In particular, Chapter 1 summarizes the mathematical model of induction motor. The Chapter 2 is a brief state of art on three-phase inverter. Chapter 3 proposes a stator flux vector control for a three- phase induction machine and compares this solution with two other algorithms presented in literature. Furthermore, in the same chapter, a complete electric drive based on matrix converter is presented. In Chapter 4 a control strategy suitable for electric vehicles is illustrated. Chapter 5 describes the mathematical model of multi-phase induction machines whereas chapter 6 analyzes the multi-phase inverter and its modulation strategies. Chapter 7 discusses the minimization of the power losses in IGBT multi-phase inverters with carrier-based pulse width modulation. In Chapter 8 an extended stator flux vector control for a seven-phase induction motor is presented. Chapter 9 concerns the high torque density applications and in Chapter 10 different fault tolerant control strategies are analyzed. Finally, the last chapter presents a positioning multi-motor drive consisting of two PM tubular five-phase actuators fed by a single five-phase inverter.

Entwicklung und Anwendung von mobilen Messstrategien und Analysemethoden zur Untersuchung urbanen Aerosols

Seit Anbeginn der Menschheitsgeschichte beeinflussen die Menschen ihre Umwelt. Durch anthropogene Emissionen ändert sich die Zusammensetzung der Atmosphäre, was einen zunehmenden Einfluss unter anderem auf die Atmosphärenchemie, die Gesundheit von Mensch, Flora und Fauna und das Klima hat. Die steigende Anzahl riesiger, wachsender Metropolen geht einher mit einer räumlichen Konzentration der Emission von Luftschadstoffen, was vor allem einen Einfluss auf die Luftqualität der windabwärts gelegenen ruralen Regionen hat. In dieser Doktorarbeit wurde im Rahmen des MEGAPOLI-Projektes die Abluftfahne der Megastadt Paris unter Anwendung des mobilen Aerosolforschungslabors MoLa untersucht. Dieses ist mit modernen, zeitlich hochauflösenden Instrumenten zur Messung der chemischen Zusammensetzung und Größenverteilung der Aerosolpartikel sowie einiger Spurengase ausgestattet. Es wurden mobile Messstrategien entwickelt und angewendet, die besonders geeignet zur Charakterisierung urbaner Emissionen sind. Querschnittsmessfahrten durch die Abluftfahne und atmosphärische Hintergrundluftmassen erlaubten sowohl die Bestimmung der Struktur und Homogenität der Abluftfahne als auch die Berechnung des Beitrags der urbanen Emissionen zur Gesamtbelastung der Atmosphäre. Quasi-Lagrange’sche Radialmessfahrten dienten der Erkundung der räumlichen Erstreckung der Abluftfahne sowie auftretender Transformationsprozesse der advehierten Luftschadstoffe. In Kombination mit Modellierungen konnte die Struktur der Abluftfahne vertieft untersucht werden. Flexible stationäre Messungen ergänzten den Datensatz und ließen zudem Vergleichsmessungen mit anderen Messstationen zu. Die Daten einer ortsfesten Messstation wurden zusätzlich verwendet, um die Alterung des organischen Partikelanteils zu beschreiben. Die Analyse der mobilen Messdaten erforderte die Entwicklung einer neuen Methode zur Bereinigung des Datensatzes von lokalen Störeinflüssen. Des Weiteren wurden die Möglichkeiten, Grenzen und Fehler bei der Anwendung komplexer Analyseprogramme zur Berechnung des O/C-Verhältnisses der Partikel sowie der Klassifizierung der Aerosolorganik untersucht. Eine Validierung verschiedener Methoden zur Bestimmung der Luftmassenherkunft war für die Auswertung ebenfalls notwendig. Die detaillierte Untersuchung der Abluftfahne von Paris ergab, dass diese sich anhand der Erhöhung der Konzentrationen von Indikatoren für unprozessierte Luftverschmutzung im Vergleich zu Hintergrundwerten identifizieren lässt. Ihre eher homogene Struktur kann zumeist durch eine Gauß-Form im Querschnitt mit einem exponentiellen Abfall der unprozessierten Schadstoffkonzentrationen mit zunehmender Distanz zur Stadt beschrieben werden. Hierfür ist hauptsächlich die turbulente Vermischung mit Umgebungsluftmassen verantwortlich. Es konnte nachgewiesen werden, dass in der advehierten Abluftfahne eine deutliche Oxidation der Aerosolorganik im Sommer stattfindet; im Winter hingegen ließ sich dieser Prozess während der durchgeführten Messungen nicht beobachten. In beiden Jahreszeiten setzt sich die Abluftfahne hauptsächlich aus Ruß und organischen Partikelkomponenten im PM1-Größenbereich zusammen, wobei die Quellen Verkehr und Kochen sowie zusätzlich Heizen in der kalten Jahreszeit dominieren. Die PM1-Partikelmasse erhöhte sich durch die urbanen Emissionen im Vergleich zum Hintergrundwert im Sommer in der Abluftfahne im Mittel um 30% und im Winter um 10%. Besonders starke Erhöhungen ließen sich für Polyaromaten beobachten, wo im Sommer eine mittlere Zunahme von 194% und im Winter von 131% vorlag. Jahreszeitliche Unterschiede waren ebenso in der Größenverteilung der Partikel der Abluftfahne zu finden, wo im Winter im Gegensatz zum Sommer keine zusätzlichen nukleierten kleinen Partikel, sondern nur durch Kondensation und Koagulation angewachsene Partikel zwischen etwa 10nm und 200nm auftraten. Die Spurengaskonzentrationen unterschieden sich ebenfalls, da chemische Reaktionen temperatur- und mitunter strahlungsabhängig sind. Weitere Anwendungsmöglichkeiten des MoLa wurden bei einer Überführungsfahrt von Deutschland an die spanische Atlantikküste demonstriert, woraus eine Kartierung der Luftqualität entlang der Fahrtroute resultierte. Es zeigte sich, dass hauptsächlich urbane Ballungszentren von unprozessierten Luftschadstoffen betroffen sind, advehierte gealterte Substanzen jedoch jede Region beeinflussen können. Die Untersuchung der Luftqualität an Standorten mit unterschiedlicher Exposition bezüglich anthropogener Quellen erweiterte diese Aussage um einen Einblick in die Variation der Luftqualität, abhängig unter anderem von der Wetterlage und der Nähe zu Emissionsquellen. Damit konnte gezeigt werden, dass sich die entwickelten Messstrategien und Analysemethoden nicht nur zur Untersuchung der Abluftfahne einer Großstadt, sondern auch auf verschiedene andere wissenschaftliche und umweltmesstechnische Fragestellungen anwenden lassen.

Micropreparative isoelectric focusing protein separation in a suspended drop

IEF protein binary separations were performed in a 12-μL drop suspended between two palladium electrodes, using pH gradients created by electrolysis of simple buffers at low voltages (1.5-5 V). The dynamics of pH gradient formation and protein separation were investigated by computer simulation and experimentally via digital video microscope imaging in the presence and absence of pH indicator solution. Albumin, ferritin, myoglobin, and cytochrome c were used as model proteins. A drop containing 2.4 μg of each protein was applied, electrophoresed, and allowed to evaporate until it splits to produce two fractions that were recovered by rinsing the electrodes with a few microliters of buffer. Analysis by gel electrophoresis revealed that anode and cathode fractions were depleted from high pI and low pI proteins, respectively, whereas proteins with intermediate pI values were recovered in both fractions. Comparable data were obtained with diluted bovine serum that was fortified with myoglobin and cytochrome c.

Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Aplicación de técnicas de inteligencia artificial a la predicción de contaminantes atmosféricos

Abstract Air pollution is a big threat and a phenomenon that has a specific impact on human health, in addition, changes that occur in the chemical composition of the atmosphere can change the weather and cause acid rain or ozone destruction. Those are phenomena of global importance. The World Health Organization (WHO) considerates air pollution as one of the most important global priorities. Salamanca, Gto., Mexico has been ranked as one of the most polluted cities in this country. The industry of the area led to a major economic development and rapid population growth in the second half of the twentieth century. The impact in the air quality is important and significant efforts have been made to measure the concentrations of pollutants. The main pollution sources are locally based plants in the chemical and power generation sectors. The registered concerning pollutants are Sulphur Dioxide (SO2) and particles on the order of ∼10 micrometers or less (PM10). The prediction in the concentration of those pollutants can be a powerful tool in order to take preventive measures such as the reduction of emissions and alerting the affected population. In this PhD thesis we propose a model to predict concentrations of pollutants SO2 and PM10 for each monitoring booth in the Atmospheric Monitoring Network Salamanca (REDMAS - for its spanish acronym). The proposed models consider the use of meteorological variables as factors influencing the concentration of pollutants. The information used along this work is the current real data from REDMAS. In the proposed model, Artificial Neural Networks (ANN) combined with clustering algorithms are used. The type of ANN used is the Multilayer Perceptron with a hidden layer, using separate structures for the prediction of each pollutant. The meteorological variables used for prediction were: Wind Direction (WD), wind speed (WS), Temperature (T) and relative humidity (RH). Clustering algorithms, K-means and Fuzzy C-means, are used to find relationships between air pollutants and weather variables under consideration, which are added as input of the RNA. Those relationships provide information to the ANN in order to obtain the prediction of the pollutants. The results of the model proposed in this work are compared with the results of a multivariate linear regression and multilayer perceptron neural network. The evaluation of the prediction is calculated with the mean absolute error, the root mean square error, the correlation coefficient and the index of agreement. The results show the importance of meteorological variables in the prediction of the concentration of the pollutants SO2 and PM10 in the city of Salamanca, Gto., Mexico. The results show that the proposed model perform better than multivariate linear regression and multilayer perceptron neural network. The models implemented for each monitoring booth have the ability to make predictions of air quality that can be used in a system of real-time forecasting and human health impact analysis. Among the main results of the development of this thesis we can cite: A model based on artificial neural network combined with clustering algorithms for prediction with a hour ahead of the concentration of each pollutant (SO2 and PM10) is proposed. A different model was designed for each pollutant and for each of the three monitoring booths of the REDMAS. A model to predict the average of pollutant concentration in the next 24 hours of pollutants SO2 and PM10 is proposed, based on artificial neural network combined with clustering algorithms. Model was designed for each booth of the REDMAS and each pollutant separately. Resumen La contaminación atmosférica es una amenaza aguda, constituye un fenómeno que tiene particular incidencia sobre la salud del hombre. Los cambios que se producen en la composición química de la atmósfera pueden cambiar el clima, producir lluvia ácida o destruir el ozono, fenómenos todos ellos de una gran importancia global. La Organización Mundial de la Salud (OMS) considera la contaminación atmosférica como una de las más importantes prioridades mundiales. Salamanca, Gto., México; ha sido catalogada como una de las ciudades más contaminadas en este país. La industria de la zona propició un importante desarrollo económico y un crecimiento acelerado de la población en la segunda mitad del siglo XX. Las afectaciones en el aire son graves y se han hecho importantes esfuerzos por medir las concentraciones de los contaminantes. Las principales fuentes de contaminación son fuentes fijas como industrias químicas y de generación eléctrica. Los contaminantes que se han registrado como preocupantes son el Bióxido de Azufre (SO2) y las Partículas Menores a 10 micrómetros (PM10). La predicción de las concentraciones de estos contaminantes puede ser una potente herramienta que permita tomar medidas preventivas como reducción de emisiones a la atmósfera y alertar a la población afectada. En la presente tesis doctoral se propone un modelo de predicción de concentraci ón de los contaminantes más críticos SO2 y PM10 para cada caseta de monitorización de la Red de Monitorización Atmosférica de Salamanca (REDMAS). Los modelos propuestos plantean el uso de las variables meteorol ógicas como factores que influyen en la concentración de los contaminantes. La información utilizada durante el desarrollo de este trabajo corresponde a datos reales obtenidos de la REDMAS. En el Modelo Propuesto (MP) se aplican Redes Neuronales Artificiales (RNA) combinadas con algoritmos de agrupamiento. La RNA utilizada es el Perceptrón Multicapa con una capa oculta, utilizando estructuras independientes para la predicción de cada contaminante. Las variables meteorológicas disponibles para realizar la predicción fueron: Dirección de Viento (DV), Velocidad de Viento (VV), Temperatura (T) y Humedad Relativa (HR). Los algoritmos de agrupamiento K-means y Fuzzy C-means son utilizados para encontrar relaciones existentes entre los contaminantes atmosféricos en estudio y las variables meteorológicas. Dichas relaciones aportan información a las RNA para obtener la predicción de los contaminantes, la cual es agregada como entrada de las RNA. Los resultados del modelo propuesto en este trabajo son comparados con los resultados de una Regresión Lineal Multivariable (RLM) y un Perceptrón Multicapa (MLP). La evaluación de la predicción se realiza con el Error Medio Absoluto, la Raíz del Error Cuadrático Medio, el coeficiente de correlación y el índice de acuerdo. Los resultados obtenidos muestran la importancia de las variables meteorológicas en la predicción de la concentración de los contaminantes SO2 y PM10 en la ciudad de Salamanca, Gto., México. Los resultados muestran que el MP predice mejor la concentración de los contaminantes SO2 y PM10 que los modelos RLM y MLP. Los modelos implementados para cada caseta de monitorizaci ón tienen la capacidad para realizar predicciones de calidad del aire, estos modelos pueden ser implementados en un sistema que permita realizar la predicción en tiempo real y analizar el impacto en la salud de la población. Entre los principales resultados obtenidos del desarrollo de esta tesis podemos citar: Se propone un modelo basado en una red neuronal artificial combinado con algoritmos de agrupamiento para la predicción con una hora de anticipaci ón de la concentración de cada contaminante (SO2 y PM10). Se diseñó un modelo diferente para cada contaminante y para cada una de las tres casetas de monitorización de la REDMAS. Se propone un modelo de predicción del promedio de la concentración de las próximas 24 horas de los contaminantes SO2 y PM10, basado en una red neuronal artificial combinado con algoritmos de agrupamiento. Se diseñó un modelo para cada caseta de monitorización de la REDMAS y para cada contaminante por separado.

Localización óptima de una planta de bioetanol a partir de tubérculos de pataca (Helianthus tuberosus l.) en la Cuenca del Duero

El objetivo del presente trabajo es determinar la localización óptima de una planta de producción de 30.000 m3/año de bioetanol a partir de tubérculos de pataca (Helianthus tuberosus L.) cultivada en regadío, en tierras de barbecho de la Cuenca Hidrográfica del Duero (CH Duero). Inicialmente se elaboró, a partir de datos bibliográficos, un modelo de producción de pataca en base a una ecuación de regresión que relaciona datos experimentales de rendimientos de variedades tardías con variables agroclimáticas. Así se obtuvo una función de producción basada en la cantidad de agua disponible (precipitación efectiva + dosis de riego) y en la radiación global acumulada en el periodo brotación‐senescencia del cultivo. A continuación se estima la superficie potencial de cultivo de pataca en la CH Duero a partir de la superficie arable en regadío cartografiada por el Sistema de Ocupación del Suelo (SIOSE), a la cual se le aplican, en base a los requerimientos del cultivo, unas restricciones climáticas, edafológicas, topográficas y logísticas mediante el uso de Sistemas de Información Geográfica (SIG). La proporción de superficie de regadío restringida se cuantifica a escala municipal con el fin de calcular la superficie de barbecho en regadío apta para el cultivo de pataca. A partir de las bases de datos georreferenciadas de precipitación, radiación global, y la dotación de agua para el riego de cultivos no específicos establecida en el Plan Hidrológico de la Cuenca del Duero a escala comarcal, se estimó la producción potencial de tubérculos de pataca sobre la superficie de barbecho de regadío según el modelo de producción elaborado. Así, en las 53.360 ha de barbecho en regadío aptas para el cultivo de pataca se podrían producir 3,8 Mt de tubérculos al año (80 % de humedad) (761.156 t ms/año) de los que se podría obtener 304.462 m3/año de bioetanol, considerando un rendimiento en la transformación de 12,5 kg mf/l de etanol. Se estiman los costes de las labores de cultivo de pataca así como los costes de la logística de suministro a una planta de transformación considerando una distancia media de transporte de 25 km, en base a las hojas de cálculo de utilización de aperos y maquinaria agrícola oficiales del Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA). Considerando el balance de costes asociados a la producción de bioetanol (costes de transformación, distribución y transporte del producto, costes estructurales de la planta, ahorro de costes por la utilización de las vinazas generadas en el proceso como fertilizante y un beneficio industrial), se ha estimado que el coste de producción de bioetanol a partir de tubérculos de pataca asciende a 61,03 c€/l. Se calculan los beneficios fiscales para el Estado por el cultivo de 5.522 ha de pataca que suministren la materia prima necesaria para una planta de bioetanol de 30.000 m3/año, en concepto de cotizaciones a la Seguridad Social de los trabajadores, impuestos sobre el valor añadido de los productos consumidos, impuesto sobre sociedades y ahorro de las prestaciones por desempleo. Se obtuvieron unos beneficios fiscales de 10,25 c€ por litro de bioetanol producido. El coste de producción de bioetanol depende del rendimiento de tubérculos por hectárea y de la distancia de transporte desde las zonas de producción de la materia prima hasta la planta. Se calculó la distancia máxima de transporte para que el precio de coste del bioetanol producido sea competitivo con el precio de mercado del bioetanol. Como resultado se determinó que el precio del bioetanol (incluido un beneficio industrial del 15%) de la planta sería igual o inferior al precio de venta en el mercado (66,35 c€/l) con una distancia máxima de transporte de 25 km y un rendimiento mínimo del cultivo de 60,1 t mf/ha. Una vez conocido el área de influencia de la planta según la distancia de transporte máxima, se determinó la localización óptima de la planta de producción de bioetanol mediante un proceso de ubicación‐asignación realizado con SIG. Para ello se analizan los puntos candidatos a la ubicación de la planta según el cumplimiento de unos requerimientos técnicos establecidos (distancia a fuentes de suministro eléctrico y de recursos hídricos, distancia a estaciones de ferrocarril, distancia a núcleos urbanos y existencia de Espacios Naturales Protegidos) que minimizan la distancia de transporte maximizando la cantidad de biomasa disponible según la producción potencial estimada anteriormente. Por último, la superficie destinada al cultivo de pataca en el área de influencia de la planta se determina en base a un patrón de distribución del cultivo alrededor de una agroindustria. Dicho patrón se ha obtenido a partir del análisis del grado de ocupación del cultivo de la remolacha en función de la distancia de transporte a la planta azucarera de Miranda de Ebro (Burgos). El patrón resultante muestra que la relación entre el grado de ocupación del suelo por el cultivo y la distancia de transporte a la planta siguen una ecuación logística. La localización óptima que se ha obtenido mediante la metodología descrita se ubica en el municipio leonés de El Burgo Ranero, donde la producción potencial de tubérculos de pataca en la superficie de barbecho situada en un radio de acción de 25 km es de 375.665 t mf/año, superando las 375.000 t mf requeridas anualmente por la planta de bioetanol. ABSTRACT Jerusalem artichoke (Helianthus tuberosus L.) is a harsh crop with a high potential for biomass production. Its main use is related to bioethanol production from the carbohydrates, inulin mainly, accumulated in its tubers at the end of the crop cycle. The aerial biomass could be used as solid biofuel to provide energy to the bioethanol production process. Therefore, Jerusalem artichoke is a promising crop as feedstock for biofuel production in order to achieve the biofuels consumption objectives established by the Government of Spain (PER 2011‐2020 and RDL 4/2013) and the European Union (Directive 2009/28/EC). This work aims at the determination of the optimal location for a 30,000 m3/year bioethanol production plant from Jerusalem artichoke tubers in the Duero river basin. With this purpose, a crop production model was developed by means of a regression equation that relates experimental yield data of late Jerusalem artichoke varieties with pedo‐climatic parameters from a bibliographic data matrix. The resulting crop production model was based on the crop water availability (including effective rainfall and irrigation water supplied) and on global radiation accumulated in the crop emergence‐senescence period. The crop potential cultivation area for Jerusalem artichoke in the Duero basin was estimated using the georeferenced irrigated arable land from the “Sistema de Ocupación del Suelo” (SIOSE) of Spain. Climatic, soil, slope and logistic restrictions were considered by means of Geographic Information Systems (GIS). The limited potential growing area was then applied to a municipality scale in order to calculate the amount of fallow land suitable for Jerusalem artichoke production. Rainfall and global radiation georeferenced layers as well as data of irrigation water supply for crop production (established within the Duero Hydrologic Plan) were use to estimate the potential production of Jerusalem artichoke tubers in the suitable fallow land according to the crop production model. As a result of this estimation, there are 53,360 ha of fallow land suitable for Jerusalem artichoke production in the Duero basin, where 3.8 M t fm/year could be produced. Considering a bioethanol processing yield of 12.5 kg mf per liter of bioethanol, the above mentioned tuber potential production could be processed in 304,462 m3/year of bioethanol. The Jerusalem crop production costs and the logistic supply costs (considering an average transport distance of 25 km) were estimated according to official agricultural machinery cost calculation sheets of the Minister of Agriculture of Spain (MAGRAMA). The bioethanol production cost from Jerusalem artichoke tubers was calculated considering bioethanol processing, transport and structural costs, industrial profits as well as plant cost savings from the use of vinasses as fertilizer. The resulting bioetanol production cost from Jerusalem artichoke tubers was 61.03 c€/l. Additionally, revenues for the state coffers regarding Social Security contributions, added value taxes of consumed raw materials, corporation tax and unemployment benefit savings due to the cultivation of 5,522 ha of Jerusalem artichoke for the 30.000 m3/year bioethanol plant supply were calculated. The calculated revenues amounted to 10.25 c€/l. Bioethanol production cost and consequently the bioethanol plant economic viability are strongly related to the crop yield as well as to road transport distance from feedstock production areas to the processing plant. The previously estimated bioethanol production cost was compared to the bioethanol market price in order to determine the maximum supply transport distance and the minimum crop yield to reach the bioethanol plant economic viability. The results showed that the proposed plant would be economically viable at a maximum transport distance of 25 km and at a crop yield not less than 60.1 t fm/ha. By means of a GIS location‐allocation analysis, the optimal bioethanol plant location was determined. Suitable candidates were detected according to several plant technical requirements (distance to power and water supply sources, distance to freight station, and distance to urban areas and to Natural Protected Areas). The optimal bioethanol plant location must minimize the supply transport distance whereas it maximizes the amount of available biomass according to the previously estimated biomass potential production. Lastly, the agricultural area around the bioethanol plant finally dedicated to Jerusalem artichoke cultivation was planned according to a crop distribution model. The crop distribution model was established from the analysis of the relation between the sugar beet (Beta vulgaris L.) cropping area and the road transport distance from the sugar processing plant of Miranda de Ebro (Burgos, North of Spain). The optimal location was situated in the municipality of ‘El Burgo Ranero’ in the province of León. The potential production of Jerusalem artichoke tubers in the fallow land within 25 km distance from the plant location was 375,665 t fm/year, which exceeds the amount of biomass yearly required by the bioethanol plant.