The increasing atmospheric concentration of greenhouse gases (GHG) has direct consequences on humans and threatens the sustainability of natural and managed ecosystems. The European Union has set high targets for reducing their emissions by 80‐95% of the 1990 levels by 2050 and is working progressively to achieve these reductions. Legumes are an important group of crop species as they have the potential to reduce N2O emissions. Biogeochemical modelling can provide a valuable tool to explore options for mitigating GHG emissions and especially N2O from European agriculture by simulating novel legume based rotations. UK‐DNDC is a process based, biogeochemical model that can be used towards that goal. The model was tested for various regions in Europe and showed that it can simulate the N dynamics within crop rotations across a range of pedoclimatic zones. It is a useful tool in 1) identifying where and when high emissions occur, 2) highlighting the effects of the management practices on emissions and 3) exploring the impact of alternative managements on emissions. New rotations, which include legumes, have been proposed in order to assess the sustainability of the legumes in European agriculture and the effect that they will have on N2O production. Five regions in Europe, namely Sweden, Germany, Italy, Scotland and Romania, were selected in order to test the differences between legume based rotations and non‐legume based. These regions represent a wide range of pedo‐climatic zones in Europe. In most case studies, legumes showed that they can make an important contribution to mitigating N2O emissions. However, there were cases in which legumes enhanced the production of N2O. Modelling can help to understand system dynamics and it can also help to explore mitigation options for European agriculture in terms of N2O production. An important element of environmental modelling is to understand the uncertainty and sensitivity of model parameters in relation to the model outputs. The sensitivity testing of the model showed that clay content, initial soil organic carbon content and atmospheric background CO2 concentration are three key input parameters Nitrous oxide emissions were one of the results that showed great uncertainty in all the analyses. That highlights the challenges of the modelling activity for accurate N2O simulations in a dynamic ecosystem.

Die Dissertation beschäftigt sich mit den Auswirkungen des Klimawandels auf europäische Agrarmärkte im Jahre 2050, unter besonderer Berücksichtigung der Getreide- und Ölsaatenmärkte. Dazu werden die klimabedingten Änderungen der Pflanzenproduktivität des Vegetationsmodells LPJmL, welche auf fünf unterschiedlichen Klimamodellprojektionen basieren, in das Marktmodell ESIM implementiert. ESIM ist ein partielles Gleichgewichtsmodell, welches explizit Agrarmärkte der einzelnen EU-Mitgliedsstaaten simuliert. Zur Berücksichtigung der Unsicherheiten die der Klima-Einfluss-Modellierung zugrunde liegt, werden in dieser Arbeit zwei Ansätze berücksichtigt. Zunächst wird, mittels Gauss-Quadraturen, Stochastizitätin das Marktmodell implementiert, um die Unsicherheit bezüglich klimawandelbedingter steigender Ertragsvariabilität, zu berücksichtigen. Die zweite Methode verwendet die fünf individuellen Produktivitätsänderungen aus dem Vegetationsmodell, woraufhin eine Verteilung der Ergebnisse generiert wird. Darüber hinaus wird das Anpassungsverhalten der Landwirte in das Marktmodell integriert. Dies wird mittels der durch den Klimawandel veänderten Profitabilität der Ackerpflanzen berücksichtigt. Die Ergebnisse weisen darauf hin, dass die Pflanzenproduktivität innerhalb der EU, zumindest bis zum Jahre 2050, weitestgehend positiv vom Klimawandel beeinflusst wird. Die Stärke der Auswirkungen variiert jedoch stark zwischen den einzelnen Ackerpflanzen und Ländern, welche von den zugrundeliegenden Annahmen und Emissionszenarien abhängen. Diese Arbeit leistet einen Beitrag zur aktuellen Klimawandeldiskussion indem sie potentielle Schäden und Nutzen des Klimawandels auf den globalen und den europäischen Agrarsektor quantifizert. Darüber hinaus liefern die stochastische Simulation, sowie die multiplen Simualtionsläufe, ein realistisches Spektrum künftiger potentieller Auswirkungen des Klimawandels. / This study aims to assess potential economic effects of climate change on European agricultural markets at member state level by 2050, focusing on cereal and oilseed markets. The future scenarios include social as well as economic developments derived from two potential emission scenarios. In this modelling framework, crop simulation results of crop productivity changes from the dynamic vegetation model LPJmL, which are based on five individual climate projections, serve as inputs which are administered as a supply shock to the European Simulation Model (ESIM). ESIM is a partial equilibrium model depicting the agricultural sector of the EU in substantial detail. Changes in yields, production quantity and crop prices by the year 2050 are simulated. In order to account for the uncertainty inherent in climate impact assessments, two approaches are considered in this thesis. First, in order to account for climate change increased yield variability, stochasticity is implemented in ESIM, using the method of Gaussian Quadratures. The second method uses the five individual LPJmL outputs to generate a distribution of results. Further, a closely connected purpose of this study is to consider climate change induced adaptation of farmers to changes in the relative profitability of crops. Simulation results indicate, that agricultural productivity in most European countries is positively affected by climate change, at least until the year 2050. However, the degree of impacts vary among crop categories and countries and are also dependent on scenario assumptions. This thesis contributes to the current discussion about climate change impacts by quantifying the potential damages and benefits that may arise from climate change on EU member state level, as well as globally. Further, the stochastic and multiple simulation results based on different future climate and emission projections deliver a more realistic spectrum of potential impacts.