The formation of biogeochemical interfaces in soils is controlled, among other factors, by the type of particle surfaces present and the assemblage of organic matter and mineral particles. Therefore, the formation and maturation of interfaces is studied with artificial soils which are produced in long-term biogeochemical laboratory incubation experiments (3, 6, 12, 18 months. Clay minerals, iron oxides and charcoal are used as major model components controlling the formation of interfaces because they exhibit high surface area and microporosity. Soil interface characteristics have been analyzed by several groups involved in the priority program for formation of organo-mineral interfaces, sorptive and thermal interface properties, microbial community structure and function. Already after 6 months of incubation, the artificial soils exhibited different properties in relation to their composition. A unique dataset evolves on the development and the dynamics of interfaces in soil in the different projects contributing to this experiment. An integrated analysis based on a conceptual model and multivariate statistics will help to understand overall processes leading to the biogeochemical properties of interfaces in soil, that are the basis for their functions in ecosystems. Therefore, we propose to establish an integrative project for the evaluation of data obtained and for publication of synergistic work, which will bring the results to a higher level of understanding.
EAGER is a core group of international scientists trying to improve and harmonize national ammonia emission inventory calculations. Through the exchange they strive to continuously improve their respective N flux models. Six N-flow models used to calculate NH3 emissions from agriculture for inventories and policy implementation in UK, DK, NL, DE, CH were compared using standard activity data sets. For liquid manure the results were well comparable. For solid manure larger differences indicated greater uncertainties. In a third WP a survey on punlished and unpulished experimental data on emissions from solid manure was therfore conducted. Project goal: EAGER aims at achieving a detailed overview of the present best available inventory techniques, compiling and harmonizing the available knowledge on emission factors (EF) and initiating a new generation of NH3 emission inventories. Results: EAGER is a core group of international scientists trying to improve and harmonize national ammonia emission inventory calculations. Through the exchange they strive to continuously improve their respective N flux models
The major aim of CARCINOGENOMICS is to develop in vitro methods for assessing the carcinogenic potential of compounds, as an alternative to current rodent bioassays for genotoxicity and carcinogenicity. The major goal is to develop a battery of mechanism-based in vitro tests accounting for various modes of carcinogenic action. These tests will be designed to cover major target organs for carcinogenic action e.g. the liver, the lung, and the kidney. The novel assays will be based on the application of 'omics' technologies (i.e. genome-wide transcriptomics as well as metabonomics) to robust in vitro systems (rat/human), thereby also exploring stem cell technology, to generate 'omic' responses from a well-defined set of model compounds causing genotoxicity and carcinogenicity. Phenotypic markers for genotoxic and carcinogenic events will be assessed for the purpose of anchoring gene expression modulations, metabolic profiles and mechanism pathways. Through extensive biostatistics, literature mining, and analysis of molecular-expression datasets, differential genetic pathways will be identified capable of predicting mechanisms of chemical carcinogenesis in vivo. Furthermore, generated transcriptomic and metabonomic data will be integrated into a holistic understanding of systems biology, and applied to build an iterative in silico model of chemical carcinogenesis. Subsequently, predictive gene expression profiles, typically consisting of some 150-250 genes, will be loaded onto high throughput dedicated DNA-chips, thus accelerating the analysis of transcriptomic responses by a factor of 100. It is expected that the outcome of this project will generate a platform enabling the investigation of large numbers of compounds for their genotoxic and carcinogenic potential, as envisaged under the REACH initiative. This will contribute to speeding the identification of potential harmful substances to man, while lowering costs and reducing animal tests. Prime Contractor: Maastricht, University, Health Risk Analysis and Toxicology (Grat); Maastricht, Nederland.
Accurate assessment of the aquatic impact of organic contaminants relies heavily on quantifying the principal degradation processes responsible for their removal. It is increasingly understood that oxidation processes play a significant and complicated role in the degradation of many contaminants in aquatic systems. The goals of the proposed project are threefold: 1. To assess three distinct computational approaches for their ability to accurate predict oxidation reaction barriers for a suite of organic compounds. These methods will be validated against existing databases of experimental measurements and high-level theoretical benchmarks. 2. To extend the existing database of measured rate constants describing organic contaminant oxidation by important oxidations in aquatic systems, for a limited number of test pollutants, using previously validated experimental protocols. 3. To further test the validity of the kinetic models for describing the rates of oxidations of organic contaminants in natural waters, using the combined data set of newly measured rate constants and both measured and newly computed oxidation barrier free energy data. In the proposed project, we will test both existing and newly developed quantum chemical models to predict the oxidation rates of several target contaminant families. The approaches developed here are expected to enable the future screening of other contaminants for their reactivity with oxidants in aquatic environments. This has important implications for the fate and impact of organic contaminants in natural surface waters, water and wastewater treatment facilities, and remediation efforts at highly contaminated sites.
An estimate of sediment transport rates in alluvial rivers is important in the context of erosion, sedimentation, flood control, long-term morphological assessment, etc. Extensive research during the last decades has produced a plethora of sediment transport models. Sediment transport is complex and often subject to semi-empirical or empirical treatment. Most of the sediment transport functions are based on simplified assumptions that the rate of sediment transport could be determined by one or two dominant factors, such as water discharge, average flow velocity, energy slope, and shear stress (Yang, 1996). In many practical situations prediction errors of these models are observed to be high.An alternative approach is to use data driven modelling, which is especially attractive for modelling processes about which adequate knowledge of the physics is limited, like in the case of sediment transport. Over the last decade fuzzy rule-based models have been introduced in engineering as a powerful alternative modelling tool. The fuzzy rule-based approach introduced by Zadeh (1965) is being widely utilized in various fields of engineering. It is a qualitative modelling scheme in which the system behaviour is described using a natural language (Sugeno & Yasukawa, 1993). This research focuses on the applicability of a data-driven fuzzy rule-based modelling approach in estimating sediment transport rates. It also aims at the comparison of the results of the fuzzy rule-based model with the results of other commonly utilized sediment transport functions.A number of variables play important roles in determining sediment transport capacity. These variables are: flow depth, particle fall velocity, particle diameter, flow velocity, energy or water surface slope, shear velocity, shear stress, fluid density, sediment density, stream power, unit stream power, and discharge. Additionally; size, shape, and unit weight of bed composition; morphology of bed forms and availability of sediment from source area affect sediment transport capacity. The most significant factors affecting sediment transport capacity will be identified and used for constructing a fuzzy model. The fuzzy model identification is usually carried out in two steps: (1) determining the number of fuzzy rules and their associated membership functions and (2) optimizing the fuzzy model. The fuzzy logic toolbox in MATLAB will be used for performing the fuzzy modelling.A general fuzzy system has the components of fuzzification, fuzzy rule base, fuzzy output engine, and defuzzification. Fuzzification converts each piece of input data to degrees of membership by a look-up in one or more several membership functions. Intuition, fuzzy clustering, neural networks, genetic algorithms, and inductive reasoning can be among many ways to assign membership values or functions to fuzzy variables...
Soil moisture - the water stored in soil within reach of the plants - is a crucial parameter for a large number of applications. Consequently, the field of microwave remote sensing of soil moisture has been an important research topic since the 1970s. But only in the last few years significant progress towards operational soil moisture services has been made. This progress became possible due to advances in sensor technology and new algorithmic approaches. With the improved algorithms it has been possible to derive soil moisture from existing operational microwave sensors. The first global soil moisture dataset derived from ERS-1/2 scatterometer measurements was released in 2002. The first near-real-time operational soil moisture service was started by EUMETSAT in May 2008 based on METOP ASCAT, which is the successor instrument of the ERS-1/2 scatterometer. Austria has made important contributions to these developments. The algorithms for retrieving soil moisture from the C-band scatterometers on board of ERS-1/2 and METOP have been developed by the Vienna University of Technology (TU Wien). Within EUMETSAT's Satellite Application Facility in Support to Operational Hydrology and Water Management (Hydrology SAF) the Austrian meteorological service (ZAMG) coordinates the soil moisture activities and is responsible for building up operational services for value-added METOP ASCAT soil moisture products. The overall goal of the proposed project is to advance the use of soil moisture services based on METOP ASCAT and complementary satellite systems, most importantly SMOS and ENVISAT ASAR, by extending the Hydrology SAF products to Africa and Australia, carrying out extensive calibration and validation (Cal/Val) activities and by developing novel water hazards applications. The considered applications are weather forecasting, drought and yield monitoring, hydrologic prediction, epidemiological modelling, climate change, desertification monitoring and societal risks assessment. A project of comparable thematic focus and breath has not been proposed before. It is expected that the interdisciplinary cooperation of specialists from different fields will lead to important scientific innovations that will promote a wide use of satellite technology in water hazards applications.
Satellite measurements strongly contribute to the understanding of the processes related to stratospheric ozone loss, e.g. by global and long term monitoring of ozone and its depleting substances. For instance, measurements performed in limb geometry by SCIAMACHY on ENVISAT largely improved the knowledge about the vertical distribution of species like BrO and OClO only recently. However, there are still important open questions, like e.g. the chlorine activation processes on different kinds of aerosols and polar stratospheric clouds. Also, the role of very short lived species in the stratospheric bromine budget or the effects of a possible enhancement of the Brewer-Dobson circulation are not fully understood.Globally, the vertical distribution of ozone depleting species varies significantly in space and time due to solar illumination, atmospheric chemistry and transport. Especially strong gradients occur near the twilight zone or across stratospheric transport barriers (polar vortex boundary, subtropical transport barriers). These regions are of particular importance for chemistry and transport of the lower stratosphere and upper troposphere, since they separate air masses on large scales but also enable exchange between them.Standard 1-D profile retrievals, which assume horizontal homogeneity, result in large systematic biases due to neglecting the effect of horizontal gradients on the measurement. We propose to develop, improve and apply a tomographic profile retrieval algorithm, which optimally combines the information provided by the SCIAMACHY limb and nadir measurements. An improved global dataset of 3D stratospheric profiles for NO2, BrO and OClO for the 10 years of the SCIAMACHY mission (2002-2012) will be developed, compared to atmospheric chemistry simulations and applied to selected questions of atmospheric science. The dataset developed in this project will be very useful for investigating the complex interplay of stratospheric chemistry and transport processes, and will help to reduce the uncertainties in the distribution of ozone depleting species, in particular for regions with large horizontal inhomogeneity.
Working group 7 (Agriculture) under the European Climate Change Programme has so far mainly dealt with mitigation potentials of GHG. A thorough integrated economic and environmental assessment in the area of agriculture and sinks has not yet been carried out. In order to support the international negotiation process and for the development of good policies the Integrated Sink Enhancement Assessment (INSEA) project's objective is to develop an analytical tool to assess economic and environmental effects for enhancing carbon sinks in agriculture and forestry. The approach is centered on spatially explicit databases that will allow the calculation of 'cost-landscapes' taking on an engineering approach to integrated costs computation of additional sink enhancement measures and negative emission technologies. The various model structures will be applied to detailed European data sets and less detailed global data sets assessing the marginal abatement cost and long-term scenarios of sink enhancement measures. Concise policy conclusions from the modeling exercise will aim at supporting the implementation of the Kyoto Protocol commitments as well as post Kyoto negotiations. In the proposal we advocate a spatially explicit approach that is motivated by the fact that LULUCF activities are by their very nature spatial entities and aggregate non-spatial treatment could, according to our experience, lead to serious biases in the assessment. Furthermore, we propose not only a simple and easily tractable static and deterministic approach for cost calculations, but also more comprehensive, dynamic, and uncertainty (risk)-based treatments. We believe that such a multidimensional approach is necessary since ecosystems are more complicated and complex in their responses and therefore robustness and consistency across a variety of decision rules will guarantee sustainable management of this natural resource.
The HGF Alliance 'Remote Sensing and Earth System Dynamics' aims at the development and evaluation of novel bio/geo-physical information products derived from data acquired by a new generation of remote sensing satellites; and their integration in Earth system models for improving understanding and modelling ability of global environmental processes and ecosystem change. The Earth system comprises a multitude of processes that are intimately meshed through complex interactions. In times of accelerated global change, the understanding and quantification of these processes is of primary importance. Spaceborne remote sensing sensors are predestined to produce bio-geo-information products on a global scale. The upcoming generation of spaceborne remote sensing configurations will be able to provide global data sets and products with unprecedented spatial and temporal resolution in the context of a consistent and systematic observation strategy. The integration of these data sets in existing environmental and climate science components will allow a new global view of the Earth system and its dynamics, initiating a performance leap in ecosystem and climate change modelling.
The investigation of high-silica rhyolitic rocks collected in the recent ICDP drilling from the Snake River Plain (SRP) volcanic province (western United States) as well as rocks from the adjacent rhyolitic complexes offers a unique opportunity to track the evolution of magma storage conditions in time and space in the 'Yellowstone hotspot' intracontinental volcanic province. The application of various geothermometers which can be used to determine pre-eruptive temperatures show a general trend indicating a general decrease of temperature over the last 16 Ma. However, the depth (or pressure) of the magma chambers is difficult to constrain and remains mainly unknown because the mineral assemblage in the rhyolitic systems is not suitable for geobarometry. As an alternative to mineral compositions, the silica content of rhyolitic melts can be used to constrain pressure, provided that the silicate melts have cotectic compositions (melts coexisting with quartz and feldspar), which is the case for most SRP rhyolites. From studies in synthetic systems, it is well known that the silica content of cotectic melts decreases with increasing pressure and that it may be used as barometer in pressure ranges of ca 1000 - 50 MPa. However, the evolution of silica content with pressure is not calibrated for natural systems containing up to 2 wtProzent Cao and 4 wtProzent FeO. In this study, we plan to determine the role of pressure on the silica content of cotectic melts compositions relevant for SRP compositions. The experimental data are crucial to interpret the natural glass compositions (matrix glass and glass inclusions) analyzed in the ICDP core samples and will be used to extract quantitative information on the depth of magma storage prior to eruption. The dataset obtained from various eruptive events (samples from ICDP drillings and other SRP rhyolites) will be used to check if there is an evolution of the depth of magma storage over the lifetime of the 'Yellowstone hotspot' in the last 16 Ma and if there is a correlation between the pre-eruptive pressure, the volume of erupted material, the temperature (or differentiation level) and the water activity of magmas. This study will be conducted in close cooperation with other U.S. groups who are in charge of the analysis of ICDP rhyolitic samples. It is emphasized that the experimental database obtained in this project can also be applied to other case studies (high silica rhyolites, A-type granites).
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