In the Earth, the dynamo action is strongly linked to core freezing. There is a solid inner core, the growth of which provides a buoyancy flux that drives the dynamo. The buoyancy in this case derives from a difference in composition between the solid inner core and the fluid outer core. In planetary bodies smaller than the Earth, however, this core differentiation process may differ - Fe may precipitate at the core-mantle boundary (CMB) rather than in the center and may fall as iron snow and initially remelt with greater depth. A chemical stable sedimentation zone develops that comprises with time the entire core - at that time a solid inner core starts to grow. The dynamics of this system is not well understood and also whether it can generate a magnetic field or not. The Jovian moon Ganymede, which shows a present-day magnetic dipole field, is a candidate for which such a scenario has been suggested. We plan to study this Fe-snow regime with both a numerical and experimental approach. In the numerical study, we use a 2D/3D thermo-chemical convection model that considers crystallization and sinking of iron crystals together with the dynamics of the liquid core phase (for the 3D case the influence of the rotation of the Fe snow process is further studied).The numerical calculations will be complemented by two series of experiments: (1) investigations in metal alloys by means of X-ray radioscopy, and (2) measurements in transparent analogues by optical techniques. The experiments will examine typical features of the iron snow regime. On the one hand they will serve as a tool to validate the numerical approach and on the other hand they will yield important insight into sub-processes of the iron snow regime, which cannot be accessed within the numerical approach due to their complexity.
Background Society aims for a pollutant-free environment, reflected in initiatives under the European Green Deal, which seek to reduce hazardous substances and promote safe, sustainable chemical use. Comprehensive exposure data are needed to identify sources, understand mixtures and eliminate sources of chemical pollution. High-resolution mass spectrometry non-target screening (HRMS NTS) is increasingly used in environmental regulatory context to chemically characterise the environment as completely as possible and retrospectively screen for known and emerging substances. Results This study provides use cases for monitoring and chemicals management with data from the German NTSPortal, a database and visualisation tool for HRMS NTS data from surface water and suspended particulate matter of major German rivers. Its internal spectral library enables substance identification comparable to standardised target analysis, supporting regulatory acceptance of HRMS NTS data for prioritisation and mixture assessment. To demonstrate its potential to research and regulation, we characterised the spatial and temporal distribution of riverine chemical mixtures and present selected use cases relevant to EU environmental, emission, and chemical legislation. Despite pronounced spatial variability, mixture composition based on presence–absence data remained stable over time, with 855 of 1721 substances detected at least once and 247 occurring ubiquitously. Declining trends for regulated substances such as carbendazim and climbazole illustrate the effectiveness of regulatory measures. Overall, the results showed that NTS data repositories can help overcome fragmented exposure information and enable more consistent use of monitoring data across policy areas, including evaluation of the revised Urban Waste Water Treatment Directive and One Health concepts. Conclusions Data from the German NTSPortal enabled a multi-matrix and temporal characterisation of riverine chemical mixtures, revealing both stable mixture compositions over time and persistent, catchment-specific substances. These data facilitated high-resolution mixture assessments across space and time, alongside trend analyses that meet regulatory needs in environmental monitoring and chemical risk assessment. Further temporal, spatial, chemical and matrix-spanning expansion of HRMS NTS repositories will enhance their value for environmental monitoring programmes. Strengthening interoperability, implementing FAIR data principles, and developing advanced tools for prioritisation, quantification and toxicity prediction, including AI-based approaches, will be crucial to fully realise the regulatory potential of NTS portals in the future. © The Author(s) 2026.
In recent years science has taken an increased interest in mineralization processes in tropical soils in particular under minimal tillage operations. Plant litter quality and management strongly affect mineralization-nitrification processes in soil and hence the fate of nitrogen in ecosystems and the environment. Plant secondary metabolites like lignin and polyphenols are poorly degradable and interact with proteins (protein binding capacity) and hence protect them from microbial attack. Nitrification, a microbiological process, directly and indirectly influences the efficiency of recovery of N in the vegetation as well as the loss of N (through denitrification and leaching) causing environmental pollution to water bodies and contributes to global warming (e.g. the greenhouse gas N2O is emitted as a by-product of nitrification and denitrification). Nitrifiers comprise a relatively narrow species diversity (at least as known to date) and are generally thought to be sensitive to low soil pH and stress. Despite these properties nitrification occurs in acid tropical soils with high levels of aluminium and manganese. Thus the main objective of the project will be the identification of micro-organisms and mechanisms responsible for mineralization-nitrification processes in acid tropical soils and the influence of long-term litter input of different chemical qualities and minimal tillage options. The project will include the use of stable isotopes (15N, 13C), mass spectrometry, gas chromatography (CO2, N2O), biochemical methods (PLFA) and molecular biology (16s rRNA., PCR, DGGE)
Cloud samples for the isotopic analysis were collected in the framework of the Hill Cap Cloud Thuringia 2010 (HCCT-2010) campaign on Schmücke (50° 39'N/ 10° 46'E, 937 m a.s.l.; Germany) in September and October 2010 with a three-stage Caltech Active Strand Cloudwater Collector (CASCC) during 13 different cloud events with a temporal resolution of 1 to 3 hours. In a first step, we ensured that no additional fractionation occurred during sampling with the CASCC. The d values of the three sizes classes of the CASCC (4 µm to 16 µm, 16 µm to 22 µm and >22 µm) did not differ significantly, revealing that the cloud droplets of different sizes quickly equilibrate their delta value with the one of the surrounding vapor. delta values in the cloud droplets varied from -77 per mil to -15 per mil in d2H and from -12.1 per mil to -3.9 per mil in d18O and were fitted by d2H =7.8*d18O +13*10**-3. delta values decreased with temperature as well as towards the end of the campaign, representing a seasonal trend which is known from d values in precipitation. The deuterium excess of the cloud samples was generally higher than the Local Meteoric Water Line of the closest GNIP (Global Network of Isotopes in Precipitation) station. Rain decreases its deuterium excess during falling through an unsaturated air column, while the cloud droplets conserve the deuterium excess of the initial evaporation and thus have been found to be a good indicator for the airmass source region: higher deuterium excess was measured for polar air masses and lower deuterium excess for Mediterranean air masses. Changes in d values during one cloud event were up to 3.6 per mil (d2H) and 0.23 per mil (d18O), except for frontal passages, which were associated with increases of ~6 per mil per hour (d2H) and ~0.6 per mil per hour (d18O). Using a box model, we showed that the influence of condensation only was able to explain the variation in the isotope signal of two cloud passages. Consequently, we deduced that the water vapor "feeding" the cloud advected the measured changes. A trajectory analysis and moisture source diagnostic revealed that it is very likely that the variations were either related to rain out along the trajectories or to meteorological changes in the moisture source region. This was the first study using stable water isotopologues in cloud water manifesting their potential in the context of atmospheric water vapor circulation.
This dataset contains laboratory-measured alkalinity, dissolved inorganic and organic carbon concentrations, δ13C values of DIC and DOC, and calculated pCO2, CO2 fluxes, and k600 from stream water samples collected along the White Main headwater stream in northern Bavaria, Germany, from March 2023 to April 2024.
Der interoprable INSPIRE-Viewdienst (WMS) Agricultural and Aquaculture Facilities gibt einen Überblick über die Tierhaltungs- und Aufzuchtanlagen im Land Brandenburg. Der Datensatz umfasst Geflügel, Rinder, Kälber, Schweine und gemischte Bestände. Die Datenquelle ist das Anlageninformationssystem LIS-A. Gemäß der INSPIRE-Datenspezifikation Agricultural and Aquaculture Facilities (D2.8.III.9_v3.0) liegen die Inhalte INSPIRE-konform vor. Der WMS beinhaltet 2 Layer: AgriculturalHolding und Sites. Der Holding-Layer wird gem. INSPIRE-Vorgaben nach Wirstschaftszweigen (NACE-Kategorie "A") untergliedert in: - AF.GrowingOfPerennialCrops: Anbau mehrjähriger Pflanzen (NACE-Kategorie "A.01.2") - AF.AnimalProduction: Tierhaltung (NACE-Kategorie "A.01.4") - AF.MixedFarming: Gemischte Landwirtschaft (NACE-Kategorie "A.01.5")
Der Datenbestand beinhaltet die Punktdaten zu den betriebenen Tierhaltungsanlagen aus dem Anlageninformationssystem LIS-A. Die Angaben zu den Anlagen enthalten jeweils den Standort und die genehmigte Leistung.
Globally, agriculture covers 40% of the earth’s surface and food systems are responsible for one-third of humanity’s contribution to global climate change. Yet, smallholder and subsistence farmers are among the most vulnerable to climate change, with extreme weather events and related food price volatility affecting livelihoods, biodiversity, and food security at multiple scales. This project builds on transdisciplinary research on agroecological transitions in vulnerable farming communities in Canada, Germany, India and Brazil. We will examine the influence of agroecological networks (farming organizations, institutional actors, and consumer groups) in promoting the perennialization of agriculture to support climate adaptation (improving resilience in livelihoods and food security) and mitigation (increasing carbon sequestration). Perennialization of agriculture integrates annual and perennial crops and trees into the same farming system. Compared to annual cropping systems which currently dominate global agriculture and markets, perennial crops show promise for climate adaptation and mitigation because of their contributions to carbon sequestration in tree biomass and soil organic carbon, and their buffering effects against soil degradation, drought, and other forms of extreme weather and climate variability. From a social wellbeing perspective, agroforestry and other diversified perennial systems offer opportunities to adapt to climate change and escape poverty traps, including higher and more stable farm incomes, balanced agricultural labour across growing seasons, improved working conditions compared to more input-intensive forms of agriculture and improved nutrition and health. Using a participatory action research approach, this project will use a novel methodology to test the relationships between personal, political, and practical leverage points driving the adoption of agroforestry and other practices supporting agricultural perennialization. We will sample farms and organizations in each case study across a diversification gradient from low-diversity farming systems to perennial and agroforestry-based management systems. We will then use qualitative and quantitative methods to assess climate resilience outcomes and estimate the potential of scaling adoption of perennial and agroforestry practices. A cross-case synthesis will take local institutional, environmental, and relational contexts into account to inform decision-making.
For surface soils, the mechanisms controlling soil organic C turnover have been thoroughly investigated. The database on subsoil C dynamics, however, is scarce, although greater than 50 percent of SOC stocks are stored in deeper soil horizons. The transfer of results obtained from surface soil studies to deeper soil horizons is limited, because soil organic matter (SOM) in deeper soil layers is exposed to contrasting environmental conditions (e.g. more constant temperature and moisture regime, higher CO2 and lower O2 concentrations, increasing N and P limitation to C mineralization with soil depth) and differs in composition compared to SOM of the surface layer, which in turn entails differences in its decomposition. For a quantitative analysis of subsoil SOC dynamics, it is necessary to trace the origins of the soil organic compounds and the pathways of their transformations. Since SOM is composed of various C pools which turn over on different time scales, from hours to millennia, bulk measurements do not reflect the response of specific pools to both transient and long-term change and may significantly underestimate CO2 fluxes. More detailed information can be gained from the fractionation of subsoil SOM into different functional pools in combination with the use of stable and radioactive isotopes. Additionally, soil-respired CO2 isotopic signatures can be used to understand the role of environmental factors on the rate of SOM decomposition and the magnitude and source of CO2 fluxes. The aims of this study are to (i) determine CO2 production and subsoil C mineralization in situ, (ii) investigate the vertical distribution and origin of CO2 in the soil profile using 14CO2 and 13CO2 analyses in the Grinderwald, and to (iii) determine the effect of environmental controls (temperature, oxygen) on subsoil C turnover. We hypothesize that in-situ CO2 production in subsoils is mainly controlled by root distribution and activity and that CO2 produced in deeper soil depth derives to a large part from the mineralization of fresh root derived C inputs. Further, we hypothesize that a large part of the subsoil C is potentially degradable, but is mineralized slower compared with the surface soil due to possible temperature or oxygen limitation.
In hydrology, the relationship between water storage and flow is still fundamental in characterizing and modeling hydrological systems. However, this simplification neglects important aspects of the variability of the hydrological system, such as stable or instable states, tipping points, connectivity, etc. and influences the predictability of hydrological systems, both for extreme events as well as long-term changes. We still lack appropriate data to develop theory linking internal pattern dynamics and integral responses and therefore to identify functionally similar hydrological areas and link this to structural features. We plan to investigate the similarities and differences of the dynamic patterns of state variables and the integral response in replicas of distinct landscape units. A strategic and systematic monitoring network is planned in this project, which contributes the essential dynamic datasets to the research group to characterize EFUs and DFUs and thus significantly improving the usual approach of subdividing the landscape into static entities such as the traditional HRUs. The planned monitoring network is unique and highly innovative in its linkage of surface and subsurface observations and its spatial and temporal resolution and the centerpiece of CAOS.
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