Modelling of global crop production and resulting N2O emissions

Landwirtschaft spielt eine zentrale Rolle im Erdsystem. Sie trägt durch die Emission von CO2, CH4 und N2O zum Treibhauseffekt bei, kann Bodendegradation und Eutrophierung verursachen, regionale Wasserkreisläufe verändern und wird außerdem stark vom Klimawandel betroffen sein. Da all diese Prozesse durch die zugrunde liegenden Nährstoff- und Wasserflüsse eng miteinander verknüpft sind, sollten sie in einem konsistenten Modellansatz betrachtet werden. Dennoch haben Datenmangel und ungenügendes Prozessverständnis dies bis vor kurzem auf der globalen Skala verhindert. In dieser Arbeit wird die erste Version eines solchen konsistenten globalen Modellansatzes präsentiert, wobei der Schwerpunkt auf der Simulation landwirtschaftlicher Erträge und den resultierenden N2O-Emissionen liegt. Der Grund für diese Schwerpunktsetzung liegt darin, dass die korrekte Abbildung des Pflanzenwachstums eine essentielle Voraussetzung für die Simulation aller anderen Prozesse ist. Des weiteren sind aktuelle und potentielle landwirtschaftliche Erträge wichtige treibende Kräfte für Landnutzungsänderungen und werden stark vom Klimawandel betroffen sein. Den zweiten Schwerpunkt bildet die Abschätzung landwirtschaftlicher N2O-Emissionen, da bislang kein prozessbasiertes N2O-Modell auf der globalen Skala eingesetzt wurde. Als Grundlage für die globale Modellierung wurde das bestehende Agrarökosystemmodell Daycent gewählt. Neben der Schaffung der Simulationsumgebung wurden zunächst die benötigten globalen Datensätze für Bodenparameter, Klima und landwirtschaftliche Bewirtschaftung zusammengestellt. Da für Pflanzzeitpunkte bislang keine globale Datenbasis zur Verfügung steht, und diese sich mit dem Klimawandel ändern werden, wurde eine Routine zur Berechnung von Pflanzzeitpunkten entwickelt. Die Ergebnisse zeigen eine gute Übereinstimmung mit Anbaukalendern der FAO, die für einige Feldfrüchte und Länder verfügbar sind. Danach wurde das Daycent-Modell für die Ertragsberechnung von Weizen, Reis, Mais, Soja, Hirse, Hülsenfrüchten, Kartoffel, Cassava und Baumwolle parametrisiert und kalibriert. Die Simulationsergebnisse zeigen, dass Daycent die wichtigsten Klima-, Boden- und Bewirtschaftungseffekte auf die Ertragsbildung korrekt abbildet. Berechnete Länderdurchschnitte stimmen gut mit Daten der FAO überein (R2 = 0.66 für Weizen, Reis und Mais; R2 = 0.32 für Soja), und räumliche Ertragsmuster entsprechen weitgehend der beobachteten Verteilung von Feldfrüchten und subnationalen Statistiken. Vor der Modellierung landwirtschaftlicher N2O-Emissionen mit dem Daycent-Modell stand eine statistische Analyse von N2O-und NO-Emissionsmessungen aus natürlichen und landwirtschaftlichen Ökosystemen. Die als signifikant identifizierten Parameter für N2O (Düngemenge, Bodenkohlenstoffgehalt, Boden-pH, Textur, Feldfrucht, Düngersorte) und NO (Düngemenge, Bodenstickstoffgehalt, Klima) entsprechen weitgehend den Ergebnissen einer früheren Analyse. Für Emissionen aus Böden unter natürlicher Vegetation, für die es bislang keine solche statistische Untersuchung gab, haben Bodenkohlenstoffgehalt, Boden-pH, Lagerungsdichte, Drainierung und Vegetationstyp einen signifikanten Einfluss auf die N2O-Emissionen, während NO-Emissionen signifikant von Bodenkohlenstoffgehalt und Vegetationstyp abhängen. Basierend auf den daraus entwickelten statistischen Modellen betragen die globalen Emissionen aus Ackerböden 3.3 Tg N/y für N2O, und 1.4 Tg N/y für NO. Solche statistischen Modelle sind nützlich, um Abschätzungen und Unsicherheitsbereiche von N2O- und NO-Emissionen basierend auf einer Vielzahl von Messungen zu berechnen. Die Dynamik des Bodenstickstoffs, insbesondere beeinflusst durch Pflanzenwachstum, Klimawandel und Landnutzungsänderung, kann allerdings nur durch die Anwendung von prozessorientierten Modellen berücksichtigt werden. Zur Modellierung von N2O-Emissionen mit dem Daycent-Modell wurde zunächst dessen Spurengasmodul durch eine detailliertere Berechnung von Nitrifikation und Denitrifikation und die Berücksichtigung von Frost-Auftau-Emissionen weiterentwickelt. Diese überarbeitete Modellversion wurde dann an N2O-Emissionsmessungen unter verschiedenen Klimaten und Feldfrüchten getestet. Sowohl die Dynamik als auch die Gesamtsummen der N2O-Emissionen werden befriedigend abgebildet, wobei die Modelleffizienz für monatliche Mittelwerte zwischen 0.1 und 0.66 für die meisten Standorte liegt. Basierend auf der überarbeiteten Modellversion wurden die N2O-Emissionen für die zuvor parametrisierten Feldfrüchte berechnet. Emissionsraten und feldfruchtspezifische Unterschiede stimmen weitgehend mit Literaturangaben überein. Düngemittelinduzierte Emissionen, die momentan vom IPCC mit 1.25 +/- 1% der eingesetzten Düngemenge abgeschätzt werden, reichen von 0.77% (Reis) bis 2.76% (Mais). Die Summe der berechneten Emissionen aus landwirtschaftlichen Böden beträgt für die Mitte der 1990er Jahre 2.1 Tg N2O-N/y, was mit den Abschätzungen aus anderen Studien übereinstimmt.

Applications and modelling in mathematics teaching

The aim of this paper is a comprehensive presentation of some important basic and general aspects of the topic applications and modelling, with emphasis on the secondary school level. Owing to the review character of this paper, some overlap with the survey paper Blum and Niss (1989) for ICME-6 in Budapest is inevitable. The paper will consist of three parts. In part 1, I shall try to clarify some basic concepts and remind the reader of a few application and modelling examples suitable for teaching. In part 2, I shall formulate some general aims for mathematics instruction and, on that basis, summarise the most important arguments for and against applications and modelling in mathematics teaching. Finally, in part 3, I shall discuss some relevant instructional aspects resulting from the considerations in part 2.

Mathematical problem solving, modelling, applications, and links to other subjects

The paper will consist of three parts. In part I we shall present some background considerations which are necessary as a basis for what follows. We shall try to clarify some basic concepts and notions, and we shall collect the most important arguments (and related goals) in favour of problem solving, modelling and applications to other subjects in mathematics instruction. In the main part II we shall review the present state, recent trends, and prospective lines of development, both in empirical or theoretical research and in the practice of mathematics instruction and mathematics education, concerning problem solving, modelling, applications and relations to other subjects. In particular, we shall identify and discuss four major trends: a widened spectrum of arguments, an increased globality, an increased unification, and an extended use of computers. In the final part III we shall comment upon some important issues and problems related to our topic.

Mathematical modelling in mathematics education and instruction

This paper aims at giving a concise survey of the present state-of-the-art of mathematical modelling in mathematics education and instruction. It will consist of four parts. In part 1, some basic concepts relevant to the topic will be clarified and, in particular, mathematical modelling will be defined in a broad, comprehensive sense. Part 2 will review arguments for the inclusion of modelling in mathematics teaching at schools and universities, and identify certain schools of thought within mathematics education. Part 3 will describe the role of modelling in present mathematics curricula and in everyday teaching practice. Some obstacles for mathematical modelling in the classroom will be analysed, as well as the opportunities and risks of computer usage. In part 4, selected materials and resources for teaching mathematical modelling, developed in the last few years in America, Australia and Europe, will be presented. The examples will demonstrate many promising directions of development.

Applied mathematical problem solving, modelling, applications, and links to other subjects

The paper will consist of three parts. In part I we shall present some background considerations which are necessary as a basis for what follows. We shall try to clarify some basic concepts and notions, and we shall collect the most important arguments (and related goals) in favour of problem solving, modelling and applications to other subjects in mathematics instruction. In the main part II we shall review the present state, recent trends, and prospective lines of development, both in empirical or theoretical research and in the practice of mathematics instruction and mathematics education, concerning (applied) problem solving, modelling, applications and relations to other subjects. In particular, we shall identify and discuss four major trends: a widened spectrum of arguments, an increased globality, an increased unification, and an extended use of computers. In the final part III we shall comment upon some important issues and problems related to our topic.

Hybrid Power System Modelling - Simulation and Energy Management Unit Development

Weltweit leben mehr als 2 Milliarden Menschen in ländlichen Gebieten. Als Konzept für die elektrische Energieversorgung solcher Gebiete kommen dezentrale elektrische Energieversorgungseinheiten zum Einsatz, die lokal verfügbare erneuerbare Ressourcen nutzen. Stand der Technik bilden Einheiten, die auf PV-Diesel-Batterie System basieren. Die verwendeten Versorgungsskonzepte in Hybridsystemen sind durch den Einsatz von Batterien als Energiespeicher meist wenig zuverlässig und teuer. Diese Energiespeicher sind sehr aufwendig zu überwachen und schwerig zu entsorgen. Den Schwerpunkt dieser Arbeit bildet die Entwicklung eines neuen Hybridsystems mit einem Wasserreservoir als Energiespeicher. Dieses Konzept eignet sich für Bergregionen in Entwicklungsländern wie Nepal, wo z.B. neben der solaren Strahlung kleine Flüsse in großer Anzahl vorhanden sind. Das Hybridsystem verfügt über einen Synchrongenerator, der die Netzgrößen Frequenz und Spannung vorgibt und zusätzlich unterstützen PV und Windkraftanlage die Versorgung. Die Wasserkraftanlage soll den Anteil der erneuerbaren Energienutzung erhöhen. Die Erweiterung des Systems um ein Dieselaggregat soll die Zuverlässigkeit der Versorgung erhöhen. Das Hybridsystem inkl. der Batterien wird modelliert und simuliert. Anschließend werden die Simulations- und Messergebnisse verglichen, um eine Validierung des Modells zu erreichen. Die Regelungsstruktur ist aufgrund der hohen Anzahl an Systemen und Parametern sehr komplex. Sie wird mit dem Simulationstool Matlab/Simulink nachgebildet. Das Verhalten des Gesamtsystems wird unter verschiedene Lasten und unterschiedlichen meteorologischen Gegebenheiten untersucht. Ein weiterer Schwerpunkt dieser Arbeit ist die Entwicklung einer modularen Energiemanagementeinheit, die auf Basis der erneuerbaren Energieversorgung aufgebaut wird. Dabei stellt die Netzfrequenz eine wichtige Eingangsgröße für die Regelung dar. Sie gibt über die Wirkleistungsstatik die Leistungsänderung im Netz wider. Über diese Angabe und die meteorologischen Daten kann eine optimale wirtschaftliche Aufteilung der Energieversorgung berechnet und eine zuverlässige Versorgung gewährleistet werden. Abschließend wurde die entwickelte Energiemanagementeinheit hardwaretechnisch aufgebaut, sowie Sensoren, Anzeige- und Eingabeeinheit in die Hardware integriert. Die Algorithmen werden in einer höheren Programmiersprache umgesetzt. Die Simulationen unter verschiedenen meteorologischen und netztechnischen Gegebenheiten mit dem entwickelten Model eines Hybridsystems für die elektrische Energieversorgung haben gezeigt, dass das verwendete Konzept mit einem Wasserreservoir als Energiespeicher ökologisch und ökonomisch eine geeignete Lösung für Entwicklungsländer sein kann. Die hardwaretechnische Umsetzung des entwickelten Modells einer Energiemanagementeinheit hat seine sichere Funktion bei der praktischen Anwendung in einem Hybridsystem bestätigen können.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Quality Criteria for Enterprise Modelling in the context of networked Enterprises

The capability for collaboration is a key success factor for networked enterprises. The paper introduces a methodology supporting the application of Enterprise Modelling in order to improve the maturity for collaboration. The methodology considers the current status of maturity for interoperability for deducing the right modelling approach. The approach is combined with quality criteria of the models in order to guide the modelling process. Both the deducing approach and the quality criteria are related to the levels of interoperability proposed by the ATHENA Interoperability Framework.

Enterprise Modelling Approach based on Maturity and Business Scope perspectives

This paper introduces a framework that supports users to implement enterprise modelling within collaborative companies. These enterprise models are the basis for a holistic interoperability measurement and management methodology which will be presented in the second part of the paper. The discipline of enterprise modelling aims at capturing all dimensions of an enterprise in a simplified model. Thus enterprise models are the appropriate basis for managing collaborative enterprise as they reduce the complexity of interoperability problems. Therefore, a first objective of this paper is to present an approach that enables companies to get the most effect out of enterprise modelling in a collaborative environment based on the maturity of their organisation relative to modelling. Within this first step, the user will get recommendations e.g. for the correct modelling language as well as the right level of detail.

On Probabilistic Strategies for Robot Tasks

Robots must act purposefully and successfully in an uncertain world. Sensory information is inaccurate or noisy, actions may have a range of effects, and the robot's environment is only partially and imprecisely modeled. This thesis introduces active randomization by a robot, both in selecting actions to execute and in focusing on sensory information to interpret, as a basic tool for overcoming uncertainty. An example of randomization is given by the strategy of shaking a bin containing a part in order to orient the part in a desired stable state with some high probability. Another example consists of first using reliable sensory information to bring two parts close together, then relying on short random motions to actually mate the two parts, once the part motions lie below the available sensing resolution. Further examples include tapping parts that are tightly wedged, twirling gears before trying to mesh them, and vibrating parts to facilitate a mating operation.

Modelling the Somantic Electrical Response of Hippocampal Pyramidal Neurons

A modeling study of hippocampal pyramidal neurons is described. This study is based on simulations using HIPPO, a program which simulates the somatic electrical activity of these cells. HIPPO is based on a) descriptions of eleven non-linear conductances that have been either reported for this class of cell in the literature or postulated in the present study, and b) an approximation of the electrotonic structure of the cell that is derived in this thesis, based on data for the linear properties of these cells. HIPPO is used a) to integrate empirical data from a variety of sources on the electrical characteristics of this type of cell, b) to investigate the functional significance of the various elements that underly the electrical behavior, and c) to provide a tool for the electrophysiologist to supplement direct observation of these cells and provide a method of testing speculations regarding parameters that are not accessible.

Probabilistic Independence Networks for Hidden Markov Probability Models

Graphical techniques for modeling the dependencies of randomvariables have been explored in a variety of different areas includingstatistics, statistical physics, artificial intelligence, speech recognition, image processing, and genetics.Formalisms for manipulating these models have been developedrelatively independently in these research communities. In this paper weexplore hidden Markov models (HMMs) and related structures within the general framework of probabilistic independencenetworks (PINs). The paper contains a self-contained review of the basic principles of PINs.It is shown that the well-known forward-backward (F-B) and Viterbialgorithms for HMMs are special cases of more general inference algorithms forarbitrary PINs. Furthermore, the existence of inference and estimationalgorithms for more general graphical models provides a set of analysistools for HMM practitioners who wish to explore a richer class of HMMstructures.Examples of relatively complex models to handle sensorfusion and coarticulationin speech recognitionare introduced and treated within the graphical model framework toillustrate the advantages of the general approach.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of household expenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that try to add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spending excluding alcohol/tobacco similar for teetotal and non-teetotal households? In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than one component, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durables within the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small. While this analysis is based on around economic data, the ideas carry over to many other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Statistical evidences of cyclic changes in volcanic gas chemistry composition by inverse modelling

The identification of compositional changes in fumarolic gases of active and quiescent volcanoes is one of the most important targets in monitoring programs. From a general point of view, many systematic (often cyclic) and random processes control the chemistry of gas discharges, making difficult to produce a convincing mathematical-statistical modelling. Changes in the chemical composition of volcanic gases sampled at Vulcano Island (Aeolian Arc, Sicily, Italy) from eight different fumaroles located in the northern sector of the summit crater (La Fossa) have been analysed by considering their dependence from time in the period 2000-2007. Each intermediate chemical composition has been considered as potentially derived from the contribution of the two temporal extremes represented by the 2000 and 2007 samples, respectively, by using inverse modelling methodologies for compositional data. Data pertaining to fumaroles F5 and F27, located on the rim and in the inner part of La Fossa crater, respectively, have been used to achieve the proposed aim. The statistical approach has allowed us to highlight the presence of random and not random fluctuations, features useful to understand how the volcanic system works, opening new perspectives in sampling strategies and in the evaluation of the natural risk related to a quiescent volcano

Modelling of Mercury’s surface composition and remote detection from the orbit with the BepiColombo Mercury Planetary Orbiter

It can be assumed that the composition of Mercury’s thin gas envelope (exosphere) is related to the composition of the planets crustal materials. If this relationship is true, then inferences regarding the bulk chemistry of the planet might be made from a thorough exospheric study. The most vexing of all unsolved problems is the uncertainty in the source of each component. Historically, it has been believed that H and He come primarily from the solar wind, while Na and K originate from volatilized materials partitioned between Mercury’s crust and meteoritic impactors. The processes that eject atoms and molecules into the exosphere of Mercury are generally considered to be thermal vaporization, photonstimulated desorption (PSD), impact vaporization, and ion sputtering. Each of these processes has its own temporal and spatial dependence. The exosphere is strongly influenced by Mercury’s highly elliptical orbit and rapid orbital speed. As a consequence the surface undergoes large fluctuations in temperature and experiences differences of insolation with longitude. We will discuss these processes but focus more on the expected surface composition and solar wind particle sputtering which releases material like Ca and other elements from the surface minerals and discuss the relevance of composition modelling