Entwicklung der Luftqualität 1989 bis 2009: NOx-, SO2-, Feinstaub-Emissionen auf Grundlage eines 1x1km Rasters
Das Projekt "Forest management in the Earth system" wird/wurde gefördert durch: Deutsche Forschungsgemeinschaft. Es wird/wurde ausgeführt durch: Max-Planck-Institut für Meteorologie.The majority of the worlds forests has undergone some form of management, such as clear-cut or thinning. This management has direct relevance for global climate: Studies estimate that forest management emissions add a third to those from deforestation, while enhanced productivity in managed forests increases the capacity of the terrestrial biosphere to act as a sink for carbon dioxide emissions. However, uncertainties in the assessment of these fluxes are large. Moreover, forests influence climate also by altering the energy and water balance of the land surface. In many regions of historical deforestation, such biogeophysical effects have substantially counteracted warming due to carbon dioxide emissions. However, the effect of management on biogeophysical effects is largely unknown beyond local case studies. While the effects of climate on forest productivity is well established in forestry models, the effects of forest management on climate is less understood. Closing this feedback cycle is crucial to understand the driving forces behind past climate changes to be able to predict future climate responses and thus the required effort to adapt to it or avert it. To investigate the role of forest management in the climate system I propose to integrate a forest management module into a comprehensive Earth system model. The resulting model will be able to simultaneously address both directions of the interactions between climate and the managed land surface. My proposed work includes model development and implementation for key forest management processes, determining the growth and stock of living biomass, soil carbon cycle, and biophysical land surface properties. With this unique tool I will be able to improve estimates of terrestrial carbon source and sink terms and to assess the susceptibility of past and future climate to combined carbon cycle and biophysical effects of forest management. Furthermore, representing feedbacks between forest management and climate in a global climate model could advance efforts to combat climate change. Changes in forest management are inevitable to adapt to future climate change. In this process, is it possible to identify win-win strategies for which local management changes do not only help adaptation, but at the same time mitigate global warming by presenting favorable effects on climate? The proposed work opens a range of long-term research paths, with the aim of strengthening the climate perspective in the economic considerations of forest management and helping to improve local decisionmaking with respect to adaptation and mitigation.
Das Projekt "Forscherguppe (FOR) 1536: INTERNANO: Mobility, aging and functioning of engineered inorganic nanoparticles at the aquatic-terrestrial interface, Aging of engineered inorganic nanoparticles in surface waters" wird/wurde gefördert durch: Deutsche Forschungsgemeinschaft. Es wird/wurde ausgeführt durch: Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Institut für Umweltwissenschaften.When released into surface waters, engineered inorganic nanoparticles (EINP) can be subject to multiple transformations. The objectives of MASK are to understand under which conditions EINP in aquatic systems will attach to suspended matter, under which conditions and in which time scale EINP are coated by NOM present in freshwater systems, how these coated colloidal particles are stabilized in the aquatic system and to which extent the aquatic aging processes are reversible. Homo-aggregation, coating changes, biological interactions and hetero-aggregation are hypothesized as key processes governing EINP aging in water bodies. In process orientated laboratory incubation experiments (50 ml to 6 l) with increasing complexity, MASK unravels the relevance and the interplay of inorganic colloids, aquagenic and pedogenic organic matter and solution physicochemistry for stability of EINP. These systems will successively approach situations in real waters. MASK thus provides information on EINP fluxes in the aquatic compartment, their time scales, reversibility and relative relevance. EINP will be analysed by standard light scattering techniques, ICP-MS, ESEM/EDX, WetSTEM and AFM. A method coupling hydrodynamic radius chromatography (HDC) with ICPMS recently developed by K. Tiede for nAg0 will be optimized and developed for further EINP analysis, MASK is further responsible for the virtual subproject ANALYSIS, the development and optimization of joint research unit methods of EINP analysis, sample preparation and sample storage, the exchange of methods and coordinates the joint analyses and the central EINP database.
Das Projekt "Methodologies for dealing with uncertainties in landscape planning and related modeling; Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change" wird/wurde gefördert durch: Deutsche Forschungsgemeinschaft. Es wird/wurde ausgeführt durch: Universität Gießen, Institut für Landschaftsökologie und Ressourcenmanagement, Professur für Landschafts-, Wasser- und Stoffhaushalt.Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.In the frame of the proposal 'Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change' we advocate the development of fully coupled, process-oriented models that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes on the landscape scale. We will use the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behaviour and couple this to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.The objective of this proposal is therefore to quantify the global uncertainty of the coupled hydro-biogeochemical models and investigate the uncertainty chain from parameter uncertainty over forcing data uncertainty up the structural model uncertainty be setting up different combinations of CMF and LandscapeDNDC. A comprehensive work program has been developed structured in 4 work packages, that consist of (1) model set up, calibration and uncertainty assessment on site scale followed by (2) an application and uncertainty assessment of the coupled model structures on regional scale, (3) global change scenario analyses and finally (4) evaluating model results in an ensemble fashion.Last but not least, a further motivation of this proposal is to provide project results in a manner that they support planning and decision taking under uncertainty, as this proposal is part of the package proposal on 'Methodologies for dealing with uncertainties in landscape planning and related modelling'.
Das Projekt "Forschergruppe (FOR) 986: Structural Change in Agriculture, How should Model Linkages be designed to analyze the Effects of Global Agricultural Trade Liberalization at the Farm Level?" wird/wurde gefördert durch: Deutsche Forschungsgemeinschaft. Es wird/wurde ausgeführt durch: Johann Heinrich von Thünen-Institut Bundesforschungsinstitut für Ländliche Räume, Wald und Fischerei, Institut für Betriebswirtschaft.In the last decades agricultural policy has gained increasingly in complexity. Nowadays it influences the food and agricultural sector from the global market down to the farm level. Widespread research questions, like the impact of the WTO negotiations on the farm structure, most often require comprehensive modeling frameworks. Thus, different types of models are utilized according to their comparative advantages and combined in a strategically useful way to more accurately represent micro and macro aspects of the food and agricultural sector. Consequently, in recent years we have seen an increase in the development and application of model linkages. Given this background, the overall objective of this subproject is a systematic sensitivity analysis of model linkages that gradually involves more and more characteristics of the linkage and the corresponding transfer of results between models. In addition, the project aims to answer the following specific question: How does structural change at the farm level influence aggregate supply and technical progress? Under which conditions is it possible to derive macro-relationships from micro-relationships? How does the aggregation level influence the model results and how can possible problems be overcome? This procedure is used to quantify the effects and to derive conditions for optimal interaction of the connected models. The analysis is based on the general equilibrium model GTAP (Global Trade Analysis Project) and the farm group model FARMIS (Farm Modelling Information System) which are employed in conjunction to analyze the effects of WTO negotiations on the farm level.
Das Projekt "Development of an integrated forest carbon monitoring system with field sampling and remote sensing for tropical forests in Indonesia" wird/wurde gefördert durch: Deutsche Forschungsgemeinschaft. Es wird/wurde ausgeführt durch: Universität Göttingen, Burckhardt-Institut, Abteilung Waldinventur und Fernerkundung.Forests play a relevant role in mitigation of climate change. A major issue, however, is the scientifically well founded, transparent and verifyable monitoring of achievements in forest carbon sequestration through reduction of deforestation and forest degradation, and through fostering sustainable forest management. Monitoring is particularly difficult in diverse and inaccessible humid tropical forest areas. The proposed research will contribute to the improvement of forest carbon monitoring under the challenging conditions of humid tropical forests. Sample based field observations and model based biomass predictions will be linked to area-wide satellite remote sensing imagery (RapidEye) and to strip samples of LiDAR imagery. Techniques of linking these data sources will be further developed and analysed with respect to (1) precision of carbon estimation and (2) accuracy of carbon regionalization. The proposed project implies research on methodological improvements of both sample based forest inventories (resampling techniques for biomass, imputation of non-response) and remote sensing application to forest monitoring (regionalization, sample based application of LiDAR data). At the core of this research is the analysis of the error variance components that each data source brings into the system. Such error analysis will allow identifying optimal resource allocation for the efficient improvement of forest carbon monitoring systems.
Emissionswerte PM10 und PM2,5
Emissionswerte NOx
Emissionswerte SO2
Darstellung aller Stationen und Messwerte der BLUME-, RUBIS- und Passivsammler-Messnetze seit 1975 sowie ausgewählter langjährig betriebener Berliner Klimastationen
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