Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Looking for orders of magnitude : five essays in trade and the environment and economic geography

General Summary Although the chapters of this thesis address a variety of issues, the principal aim is common: test economic ideas in an international economic context. The intention has been to supply empirical findings using the largest suitable data sets and making use of the most appropriate empirical techniques. This thesis can roughly be divided into two parts: the first one, corresponding to the first two chapters, investigates the link between trade and the environment, the second one, the last three chapters, is related to economic geography issues. Environmental problems are omnipresent in the daily press nowadays and one of the arguments put forward is that globalisation causes severe environmental problems through the reallocation of investments and production to countries with less stringent environmental regulations. A measure of the amplitude of this undesirable effect is provided in the first part. The third and the fourth chapters explore the productivity effects of agglomeration. The computed spillover effects between different sectors indicate how cluster-formation might be productivity enhancing. The last chapter is not about how to better understand the world but how to measure it and it was just a great pleasure to work on it. "The Economist" writes every week about the impressive population and economic growth observed in China and India, and everybody agrees that the world's center of gravity has shifted. But by how much and how fast did it shift? An answer is given in the last part, which proposes a global measure for the location of world production and allows to visualize our results in Google Earth. A short summary of each of the five chapters is provided below. The first chapter, entitled "Unraveling the World-Wide Pollution-Haven Effect" investigates the relative strength of the pollution haven effect (PH, comparative advantage in dirty products due to differences in environmental regulation) and the factor endowment effect (FE, comparative advantage in dirty, capital intensive products due to differences in endowments). We compute the pollution content of imports using the IPPS coefficients (for three pollutants, namely biological oxygen demand, sulphur dioxide and toxic pollution intensity for all manufacturing sectors) provided by the World Bank and use a gravity-type framework to isolate the two above mentioned effects. Our study covers 48 countries that can be classified into 29 Southern and 19 Northern countries and uses the lead content of gasoline as proxy for environmental stringency. For North-South trade we find significant PH and FE effects going in the expected, opposite directions and being of similar magnitude. However, when looking at world trade, the effects become very small because of the high North-North trade share, where we have no a priori expectations about the signs of these effects. Therefore popular fears about the trade effects of differences in environmental regulations might by exaggerated. The second chapter is entitled "Is trade bad for the Environment? Decomposing worldwide SO2 emissions, 1990-2000". First we construct a novel and large database containing reasonable estimates of SO2 emission intensities per unit labor that vary across countries, periods and manufacturing sectors. Then we use these original data (covering 31 developed and 31 developing countries) to decompose the worldwide SO2 emissions into the three well known dynamic effects (scale, technique and composition effect). We find that the positive scale (+9,5%) and the negative technique (-12.5%) effect are the main driving forces of emission changes. Composition effects between countries and sectors are smaller, both negative and of similar magnitude (-3.5% each). Given that trade matters via the composition effects this means that trade reduces total emissions. We next construct, in a first experiment, a hypothetical world where no trade happens, i.e. each country produces its imports at home and does no longer produce its exports. The difference between the actual and this no-trade world allows us (under the omission of price effects) to compute a static first-order trade effect. The latter now increases total world emissions because it allows, on average, dirty countries to specialize in dirty products. However, this effect is smaller (3.5%) in 2000 than in 1990 (10%), in line with the negative dynamic composition effect identified in the previous exercise. We then propose a second experiment, comparing effective emissions with the maximum or minimum possible level of SO2 emissions. These hypothetical levels of emissions are obtained by reallocating labour accordingly across sectors within each country (under the country-employment and the world industry-production constraints). Using linear programming techniques, we show that emissions are reduced by 90% with respect to the worst case, but that they could still be reduced further by another 80% if emissions were to be minimized. The findings from this chapter go together with those from chapter one in the sense that trade-induced composition effect do not seem to be the main source of pollution, at least in the recent past. Going now to the economic geography part of this thesis, the third chapter, entitled "A Dynamic Model with Sectoral Agglomeration Effects" consists of a short note that derives the theoretical model estimated in the fourth chapter. The derivation is directly based on the multi-regional framework by Ciccone (2002) but extends it in order to include sectoral disaggregation and a temporal dimension. This allows us formally to write present productivity as a function of past productivity and other contemporaneous and past control variables. The fourth chapter entitled "Sectoral Agglomeration Effects in a Panel of European Regions" takes the final equation derived in chapter three to the data. We investigate the empirical link between density and labour productivity based on regional data (245 NUTS-2 regions over the period 1980-2003). Using dynamic panel techniques allows us to control for the possible endogeneity of density and for region specific effects. We find a positive long run elasticity of density with respect to labour productivity of about 13%. When using data at the sectoral level it seems that positive cross-sector and negative own-sector externalities are present in manufacturing while financial services display strong positive own-sector effects. The fifth and last chapter entitled "Is the World's Economic Center of Gravity Already in Asia?" computes the world economic, demographic and geographic center of gravity for 1975-2004 and compares them. Based on data for the largest cities in the world and using the physical concept of center of mass, we find that the world's economic center of gravity is still located in Europe, even though there is a clear shift towards Asia. To sum up, this thesis makes three main contributions. First, it provides new estimates of orders of magnitudes for the role of trade in the globalisation and environment debate. Second, it computes reliable and disaggregated elasticities for the effect of density on labour productivity in European regions. Third, it allows us, in a geometrically rigorous way, to track the path of the world's economic center of gravity.

Enhanced biodegradation of hexachlorocyclohexane (HCH) in contaminated soils via inoculation with Sphingobium indicum B90A.

Soil pollution with hexachlorocyclohexane (HCH) has caused serious environmental problems. Here we describe the targeted degradation of all HCH isomers by applying the aerobic bacterium Sphingobium indicum B90A. In particular, we examined possibilities for large-scale cultivation of strain B90A, tested immobilization, storage and inoculation procedures, and determined the survival and HCH-degradation activity of inoculated cells in soil. Optimal growth of strain B90A was achieved in glucose-containing mineral medium and up to 65% culturability could be maintained after 60 days storage at 30 degrees C by mixing cells with sterile dry corncob powder. B90A biomass produced in water supplemented with sugarcane molasses and immobilized on corncob powder retained 15-20% culturability after 30 days storage at 30 degrees C, whereas full culturability was maintained when cells were stored frozen at -20 degrees C. On the contrary, cells stored on corncob degraded gamma-HCH faster than those that had been stored frozen, with between 15 and 85% of gamma-HCH disappearance in microcosms within 20 h at 30 degrees C. Soil microcosm tests at 25 degrees C confirmed complete mineralization of [(14)C]-gamma-HCH by corncob-immobilized strain B90A. Experiments conducted in small pits and at an HCH-contaminated agricultural site resulted in between 85 and 95% HCH degradation by strain B90A applied via corncob, depending on the type of HCH isomer and even at residual HCH concentrations. Up to 20% of the inoculated B90A cells survived under field conditions after 8 days and could be traced among other soil microorganisms by a combination of natural antibiotic resistance properties, unique pigmentation and PCR amplification of the linA genes. Neither the addition of corncob nor of corncob immobilized B90A did measurably change the microbial community structure as determined by T-RFLP analysis. Overall, these results indicate that on-site aerobic bioremediation of HCH exploiting the biodegradation activity of S. indicum B90A cells stored on corncob powder is a promising technology.

Asphalt Resurfacing Structural Research, HR-556, Construction Report, 1995

Discarded tires present major disposal and environmental problems. One method of recycling tires is to use finely ground rubber from tires in asphalt cement concrete (ACC). This process has been researched in Iowa since 1991. There are currently eight projects being researched. This project involved using crumb rubber modifier (CRM) in ACC using a dry process. This project is located on US 63 in Howard County. It involved 17 test sections. There were five test sections using 20 lb of CRM per ton, four test sections using 10 lb of CRM per ton and eight test sections using a conventional mix. Not only were different mixes used, but the overlay was also placed in various thicknesses ranging from 2 in. to 8 in. (5 cm to 20 cm). The project was completed in August 1994. The project construction went well with only minor problems. This report contains information about procedures and tests that were completed and those that will be completed. Evaluation on the project will continue for five years.

Efficiency of five biosolids to supply nitrogen and phosphorus to ryegrass

Biosolids have been considered satisfactory to supply crops and plant nutrients. The ideal biosolids application rate should result in high crop yields and nutrient uptake, and leave low concentrations of nutrients in soils to avoid environmental problems. The objective of this study was to estimate the capacity of five biosolids to supply N and P to ryegrass (Lolium perenne) after a single application of either fertilizers or biosolids to a Spodosol and an Oxisol. Results showed that 6% - 36% of N and 3% - 7% of P applied as biosolids were recovered in plants grown on the Spodosol, while the range on the Oxisol was 26%-75% for N and 1.2%-3.7% for phosphorus. Biosolids' efficiency on supplying N and P to plants was similar to fertilizer on the Spodosol, but on the Oxisol it refrained to 65%-67% fertilizer's efficiency. After a single application of biosolids followed by six consecutive harvests, 25%-94% of the N and 93%-99% of the P were not used by plants and remain in the soils.

Estudi de la contaminació per nitrats a les aigües subterrànies de Catalunya: l'Alt Penedès, el Baix Camp, el Baix Empordà, el Baix Penedès, la Garrotxa, el Maresme, Osona, el Pla de l'Estany, la Segarra, el Segrià, el Tarragonès i l'Urgell

La contaminació per nitrats de les aigües subterrànies és un dels problemes mediambientals i de salut pública que més afecten els nostres aqüífers. És per això que un dels eixos del nostre estudi és fer la màxima difusió de l’estat de la qualitat de l’aigua dels aqüífers de diferents àrees de Catalunya. En el present estudi es tracta la contaminació per nitrats a les aigües de 945 punts de mostreig (sobretot d’aigua procedent de pous, d’algunes mines i d’algunes fonts) de Catalunya, situats en 12 comarques diferents, totes elles amb algun o una gran part dels seus municipis englobats en una zona vulnerable. D’aquests punts de mostreig s’ha fet un recull de dades de la concentració de nitrats des de l’any 2003 fins el 2012 per tal d’estudiar-ne l’evolució i la incidència de la pluviometria, així com conèixer en quines comarques les variables externes: superfície agrària útil (SAU), explotacions agràries i cabana porcina i bovina poden haver incidit directament en la contaminació. També s’estudia fins a quin punt, aquest deteriorament, ha afectat la mineralització de l’aigua o afecta a llocs d’aigües més mineralitzades. A partir dels resultats obtinguts s’ha arribat a les conclusions que la concentració mitjana de nitrats a les aigües subterrànies en la majoria de comarques estudiades és elevada, superior als 50 mg/l que estableix la normativa vigent; que ha tendit a l’estabilitat en els últims deu anys; que afecta llocs d’aigües molt mineralitzades i que la pluviometria incideix notablement en la concentració de nitrats. S’ha observat que les variables externes superfície agrària útil (SAU), explotacions agràries i cabana porcina i bovina incideixen directament en la contaminació, excepte al Maresme. Finalment es presenten diferents usos alternatius als de l’aigua de consum per aquestes aigües contaminades amb nitrats i que han posat en pràctica diferents municipis de les comarques estudiades.

Fate of the herbicide glyphosate and its metabolite AMPA in soils and their transfer to surface waters: A multi-scale approach in the Lavaux vineyards, western Switzerland

The use of herbicides in agriculture may lead to environmental problems, such as surface water pollution, with a potential risk for aquatic organisms. The herbicide glyphosate is the most used active ingredient in the world and in Switzerland. In the Lavaux vineyards it is nearly the only molecule applied. This work aimed at studying its fate in soils and its transfer to surface waters, using a multi-scale approach: from molecular (10-9 m) and microscopic scales (10-6 m), to macroscopic (m) and landscape ones (103 m). First of all, an analytical method was developed for the trace level quantification of this widely used herbicide and its main by-product, aminomethylphosphonic acid (AMPA). Due to their polar nature, their derivatization with 9-fluorenylmethyl chloroformate (FMOC-Cl) was done prior to their concentration and purification by solid phase extraction. They were then analyzed by ultra performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). The method was tested in different aqueous matrices with spiking tests and validated for the matrix effect correction in relevant environmental samples. Calibration curves established between 10 and 1000ng/l showed r2 values above 0.989, mean recoveries varied between 86 and 133% and limits of detection and quantification of the method were as low as 5 and 10ng/l respectively. At the parcel scale, two parcels of the Lavaux vineyard area, located near the Lutrive River at 6km to the east of Lausanne, were monitored to assess to which extent glyphosate and AMPA were retained in the soil or exported to surface waters. They were equipped at their bottom with porous ceramic cups and runoff collectors, which allowed retrieving water samples for the growing seasons 2010 and 2011. Results revealed that the mobility of glyphosate and AMPA in the unsaturated zone was likely driven by the precipitation regime and the soil characteristics, such as slope, porosity structure and layer permeability discrepancy. Elevated glyphosate and AMPA concentrations were measured at 60 and 80 cm depth at parcel bottoms, suggesting their infiltration in the upper parts of the parcels and the presence of preferential flow in the studied parcels. Indeed, the succession of rainy days induced the gradual saturation of the soil porosity, leading to rapid infiltration through macropores, as well as surface runoff formation. Furthermore, the presence of more impervious weathered marls at 100 cm depth induced throughflows, the importance of which for the lateral transport of the herbicide molecules was determined by the slope steepness. Important rainfall events (>10 mm/day) were clearly exporting molecules from the soil top layer, as indicated by important concentrations in runoff samples. A mass balance showed that total loss (10-20%) mainly occurred through surface runoff (96%) and, to a minor extent, by throughflows in soils (4%), with subsequent exfiltration to surface waters. Observations made in the Lutrive River revealed interesting details of glyphosate and AMPA dynamics in urbanized landscapes, such as the Lavaux vineyards. Indeed, besides their physical and chemical properties, herbicide dynamics at the catchment level strongly depend on application rates, precipitation regime, land use and also on the presence of drains or constructed channels. Elevated concentrations, up to 4970 ng/l, observed just after the application, confirmed the diffuse export of these compounds from the vineyard area by surface runoff during main rain events. From April to September 2011, a total load of 7.1 kg was calculated, with 85% coming from vineyards and minor urban sources and 15% from arable crops. Small vineyard surfaces could generate high concentrations of herbicides and contribute considerably to the total load calculated at the outlet, due to their steep slopes (~10%). The extrapolated total amount transferred yearly from the Lavaux vineyards to the Lake of Geneva was of 190kg. At the molecular scale, the possible involvement of dissolved organic matter (DOM) in glyphosate and copper transport was studied using UV/Vis fluorescence spectroscopy. Combined with parallel factor (PARAFAC) analysis, this technique allowed characterizing DOM of soil and surface water samples from the studied vineyard area. Glyphosate concentrations were linked to the fulvic-like spectroscopic signature of DOM in soil water samples, as well as to copper, suggesting the formation of ternary complexes. In surface water samples, its concentrations were also correlated to copper ones, but not in a significant way to the fulvic-like signature. Quenching experiments with standards confirmed field tendencies in the laboratory, with a stronger decrease in fluorescence intensity for fulvic-like fluorophore than for more aromatic ones. Lastly, based on maximum concentrations measured in the river, an environmental risk for these compounds was assessed, using laboratory tests and ecotoxicity data from the literature. In our case and with the methodology applied, the risk towards aquatic species was found negligible (RF<1).

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Evaluation of Recycled Rubber in Asphalt Concrete, HR-330, Construction Report, 1991

Discarded tires present major disposal and environmental problems. The recycling of those tires in asphalt cement concrete is what this research deals with. The Iowa DOT and the University of Northern Iowa (UNI) are evaluating the use of discarded tires in asphalt rubber cement and rubber chip mixes. The project is located on US 61 between Blue Grass and Muscatine in Muscatine County. It contains four rubberized asphalt sections and control sections. One section consists of reacted rubber asphalt cement used in both the binder and surface courses, and one section, both lanes, contains a rubber chip mix. The reacted rubber asphalt and the rubber chip mixes were laid in July 1991. The project construction went well with a few problems of shoving and cracking of the mat. This report contains information about procedures and tests that were run and those that will be run. It also has a cost comparison since this is a major concern with the use of asphalt rubber. Evaluation of this project will continue for five years. Three more research projects containing rubberized asphalt were constructed in 1991 and another is to be constructed in 1992.

Venäjälle suuntautuva tavaraliikenne ja sen ympäristöhaittojen minimointi

Tavaranvaihto Suomen itärajalla on aina ollut hyvin vilkasta. Neuvostoliiton romahtamisen jälkeen kauppaan tuli hetkellisesti erittäin syvä notkahdus, joka kääntyi voimakkaaksi nousuksi lähestyttäessä 1990-luvun puoliväliä. Pelkän vientikaupan oheen tuli välityskauppaa, sekä transitoliikennettä, jolla on ollut huomattavaa paikallista vaikutusta Kaakkois-Suomen työllisyyteen, sekä kuljetusalalle maanlaajuisestikin. Venäjän devalvaatio elokuussa 1998 romahdutti, sekä kaupan, että transitoliikenteen, mutta on sittemmin kääntynyt uuteen nousuun. Koko Venäjän tulevaisuus ja sitä kautta maamme itärajan liikennemäärät ovat varsin vaikeasti ennustettavissa, mutta todennäköisintä on Venäjän talouskasvun jatkuminen, jonka hyödyntämisessä ja tukemisessa myös Suomen tulisi olla. Liikennemäärien kasvu on aiheuttanut paikallisia ympäristöongelmia myös Suomen puolella rajaa. Ongelmat ovat kasaantuneet rajanylityspaikoille Nuijamaalle ja Vaalimaalle valtavien rekkajonojen myötä. Paikallisten asukkaiden elämän helpottamiseksi olisi valtiovallan pyrittävä kehittämään rajanylityspaikkoja, joista erityisesti Nuijamaa on käynyt jo kauan sitten liian pieneksi. Tekninen kehitys pienentää yksittäisen auton aiheuttamaa kuormitusta luonnolle, mutta liikennemäärien kasvu aiheuttaa kasaantuvia paikallisia ongelmia. Olemme toistaiseksi Suomessa EU:n itärajalla. Viron ja muiden Baltian maiden liittymiseen saakka, ja maantieteellisessä erityisasemassa koko unionin alueella. Samalla Suomen olisi muistettava, että meidän itärajalla on toistaiseksi maailman suurin elintasokuilu ja eurooppalainen vastakkain asettelu: EU vastaan Venäjä, länsi vastaan itä.

Recursos litosféricos y medio ambiente

This paper focuses that geological resources is an essential need in the development of the society and specially of the developing countries. Taking into account the processes and environmental problems related to mining exploitation, these activities should be performed in a environment concordance. For these reason al1 the available environmental techniques and tools for a responsible exploitation of resources should be used.

Gas-phase photocatalytic oxidation of volatile organic compounds

Substances emitted into the atmosphere by human activities in urban and industrial areas cause environmental problems such as air quality degradation, respiratory diseases, climate change, global warming, and stratospheric ozone depletion. Volatile organic compounds (VOCs) are major air pollutants, emitted largely by industry, transportation and households. Many VOCs are toxic, and some are considered to be carcinogenic, mutagenic, or teratogenic. A wide spectrum of VOCs is readily oxidized photocatalytically. Photocatalytic oxidation (PCO) over titanium dioxide may present a potential alternative to air treatment strategies currently in use, such as adsorption and thermal treatment, due to its advantageous activity under ambient conditions, although higher but still mild temperatures may also be applied. The objective of the present research was to disclose routes of chemical reactions, estimate the kinetics and the sensitivity of gas-phase PCO to reaction conditions in respect of air pollutants containing heteroatoms in their molecules. Deactivation of the photocatalyst and restoration of its activity was also taken under consideration to assess the practical possibility of the application of PCO to the treatment of air polluted with VOCs. UV-irradiated titanium dioxide was selected as a photocatalyst for its chemical inertness, non-toxic character and low cost. In the present work Degussa P25 TiO2 photocatalyst was mostly used. In transient studies platinized TiO2 was also studied. The experimental research into PCO of following VOCs was undertaken: - methyl tert-butyl ether (MTBE) as the basic oxygenated motor fuel additive and, thus, a major non-biodegradable pollutant of groundwater; - tert-butyl alcohol (TBA) as the primary product of MTBE hydrolysis and PCO; - ethyl mercaptan (ethanethiol) as one of the reduced sulphur pungent air pollutants in the pulp-and-paper industry; - methylamine (MA) and dimethylamine (DMA) as the amino compounds often emitted by various industries. The PCO of VOCs was studied using a continuous-flow mode. The PCO of MTBE and TBA was also studied by transient mode, in which carbon dioxide, water, and acetone were identified as the main gas-phase products. The volatile products of thermal catalytic oxidation (TCO) of MTBE included 2-methyl-1-propene (2-MP), carbon monoxide, carbon dioxide and water; TBA decomposed to 2-MP and water. Continuous PCO of 4 TBA proceeded faster in humid air than dry air. MTBE oxidation, however, was less sensitive to humidity. The TiO2 catalyst was stable during continuous PCO of MTBE and TBA above 373 K, but gradually lost activity below 373 K; the catalyst could be regenerated by UV irradiation in the absence of gas-phase VOCs. Sulphur dioxide, carbon monoxide, carbon dioxide and water were identified as ultimate products of PCO of ethanethiol. Acetic acid was identified as a photocatalytic oxidation by-product. The limits of ethanethiol concentration and temperature, at which the reactor performance was stable for indefinite time, were established. The apparent reaction kinetics appeared to be independent of the reaction temperature within the studied limits, 373 to 453 K. The catalyst was completely and irreversibly deactivated with ethanethiol TCO. Volatile PCO products of MA included ammonia, nitrogen dioxide, nitrous oxide, carbon dioxide and water. Formamide was observed among DMA PCO products together with others similar to the ones of MA. TCO for both substances resulted in the formation of ammonia, hydrogen cyanide, carbon monoxide, carbon dioxide and water. No deactivation of the photocatalyst during the multiple long-run experiments was observed at the concentrations and temperatures used in the study. PCO of MA was also studied in the aqueous phase. Maximum efficiency was achieved in an alkaline media, where MA exhibited high fugitivity. Two mechanisms of aqueous PCO – decomposition to formate and ammonia, and oxidation of organic nitrogen directly to nitrite - lead ultimately to carbon dioxide, water, ammonia and nitrate: formate and nitrite were observed as intermediates. A part of the ammonia formed in the reaction was oxidized to nitrite and nitrate. This finding helped in better understanding of the gasphase PCO pathways. The PCO kinetic data for VOCs fitted well to the monomolecular Langmuir- Hinshelwood (L-H) model, whereas TCO kinetic behaviour matched the first order process for volatile amines and the L-H model for others. It should be noted that both LH and the first order equations were only the data fit, not the real description of the reaction kinetics. The dependence of the kinetic constants on temperature was established in the form of an Arrhenius equation.

Assessment of Coastal Bird Populations and Habitats on the Finnish Coast of the Baltic Sea: Implications for Monitoring and Management

Coastal birds are an integral part of coastal ecosystems, which nowadays are subject to severe environmental pressures. Effective measures for the management and conservation of seabirds and their habitats call for insight into their population processes and the factors affecting their distribution and abundance. Central to national and international management and conservation measures is the availability of accurate data and information on bird populations, as well as on environmental trends and on measures taken to solve environmental problems. In this thesis I address different aspects of the occurrence, abundance, population trends and breeding success of waterbirds breeding on the Finnish coast of the Baltic Sea, and discuss the implications of the results for seabird monitoring, management and conservation. In addition, I assess the position and prospects of coastal bird monitoring data, in the processing and dissemination of biodiversity data and information in accordance with the Convention on Biological Diversity (CBD) and other national and international commitments. I show that important factors for seabird habitat selection are island area and elevation, water depth, shore openness, and the composition of island cover habitats. Habitat preferences are species-specific, with certain similarities within species groups. The occurrence of the colonial Arctic Tern (Sterna paradisaea) is partly affected by different habitat characteristics than its abundance. Using long-term bird monitoring data, I show that eutrophication and winter severity have reduced the populations of several Finnish seabird species. A major demographic factor through which environmental changes influence bird populations is breeding success. Breeding success can function as a more rapid indicator of sublethal environmental impacts than population trends, particularly for long-lived and slowbreeding species, and should therefore be included in coastal bird monitoring schemes. Among my target species, local breeding success can be shown to affect the populations of the Mallard (Anas platyrhynchos), the Eider (Somateria mollissima) and the Goosander (Mergus merganser) after a time lag corresponding to their species-specific recruitment age. For some of the target species, the number of individuals in late summer can be used as an easier and more cost-effective indicator of breeding success than brood counts. My results highlight that the interpretation and application of habitat and population studies require solid background knowledge of the ecology of the target species. In addition, the special characteristics of coastal birds, their habitats, and coastal bird monitoring data have to be considered in the assessment of their distribution and population trends. According to the results, the relationships between the occurrence, abundance and population trends of coastal birds and environmental factors can be quantitatively assessed using multivariate modelling and model selection. Spatial data sets widely available in Finland can be utilised in the calculation of several variables that are relevant to the habitat selection of Finnish coastal species. Concerning some habitat characteristics field work is still required, due to a lack of remotely sensed data or the low resolution of readily available data in relation to the fine scale of the habitat patches in the archipelago. While long-term data sets exist for water quality and weather, the lack of data concerning for instance the food resources of birds hampers more detailed studies of environmental effects on bird populations. Intensive studies of coastal bird species in different archipelago areas should be encouraged. The provision and free delivery of high-quality coastal data concerning bird populations and their habitats would greatly increase the capability of ecological modelling, as well as the management and conservation of coastal environments and communities. International initiatives that promote open spatial data infrastructures and sharing are therefore highly regarded. To function effectively, international information networks, such as the biodiversity Clearing House Mechanism (CHM) under the CBD, need to be rooted at regional and local levels. Attention should also be paid to the processing of data for higher levels of the information hierarchy, so that data are synthesized and developed into high-quality knowledge applicable to management and conservation.