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.
Tierhaltungsanlage In der Finkenstädt (Ursprungsplan) im Datenformat INSPIRE PLU Version 4.0.1
Additional reporting obligations in the area of energy efficiency' is a dataset reported by EU Member States and Contracting Parties of the Energy Community under the Governance Regulation. The dataset includes information on reasons why energy consumption is stable or growing per sector, floor area of government buildings not meeting energy performance requirements, number of energy audits carried out in large companies, applied national primary energy factor for electricity, number and floor area of new and renovated nearly zero-energy buildings (NZEB), and internet links to lists/interfaces of energy services.
Residence times is a key signature to characterize flow and transport at all temporal and spatial scales in different hydrological compartments. It is assumed that the spatial organisation of the landscape controls space-time organisation of the water cycle and related processes and hence the residence time. Combining flux and residence concentration data of natural tracers in water, stable isotopes, and artificial tracers will allow us to predict residence time and flow pathways in the different hydrological compartments as well as integrative for entire watersheds. We will investigate with different methods the fingerprint of hydrological processes found in the signal of isotopic composition and natural and artificial tracers of soil, ground and stream water in space and time. The temporal variability of isotopes in soil water, groundwater and stream water will be combined to benchmark transport and flow models and to derive a new functional form of short to long-term transit time distributions. The spatial patterns of stable isotopes in the saturated and unsaturated zone will be used to derive long-term flow pathways, mixing patterns and the proportion of evaporation to transpiration. Artificial tracer experiments using salt and electric resistivities will vizualize and quantify internal flow pathways in particular preferential flow pathways.
This dataset contains dissolved inorganic/organic carbon (DIC/DOC) concentrations, its stable isotope ratios (δ13CDIC/DOC), partial pressure of carbon dioxide in the water column pCO₂(aq) (pCO2(aq)) and area-integrated CO₂ emission rates derived from flux calculations (FCO2; g C d⁻¹), along with corresponding parameters (temperature, pH, calcium, bicarbonate) collected from the Danube River and its key tributaries during five seasonal sampling campaigns in 2023 and 2024. Water samples were collected using a weighted 2 L sampling bottle submerged 1–2 meters below the surface, with sampling conducted from the river center via bridges or passenger boats, and occasionally from the riverbank. In situ temperature measurements were taken with a multiparameter instrument (HQ40d, HACH™, Loveland, CO, USA). δ13ODIC/DOC was analyzed using a OI Analytical Aurora 1030W-IRMS. This dataset is providing valuable insights into carbon dynamics in a large river system and support investigations of biogeochemical cycling. It further can inform ecosystem management and conservation strategies under changing environmental conditions.
This dataset contains diel measurements of alkalinity, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), particulate organic carbon (POC), d18O values of dissolved oxygen, and calculated partial pressure of CO2 (pCO2), calculated CO2 fluxes, and calculated gas-transfer velocity (k600) from stream-water samples collected at three sites along the Wiesent karst headwater stream in northern Bavaria, Germany, between 21 and 22 August 2023. Measurements were conducted at 4 h intervals over a 24 h period to assess short-term variability in carbon and oxygen cycling and CO2 evasion.
During a 4-week measurement campaign (ISLAS2022) in March and April 2022, we collected a comprehensive dataset characterizing the atmospheric water vapour and precipitation isotope composition within weather systems in the European Arctic and sub-Arctic. Focusing on an area covering the Nordic Seas and Northern Scandinavia, stable water isotope measurements with cavity ring-down spectrometers (CRDS) were taken from a research aircraft stationed at Kiruna, Sweden; from a Research Vessel going from Tromsø to the western ice edge in Greenland, and from measurements at supersites at Andenes on the Lofoten archipelago, Abisko, and Kiruna. Water vapour and precipitation isotope measurements from different sites and platforms were complemented by additional instrumentation to characterize the atmospheric conditions. Advanced instrumentation included wind LIDAR, ground-based vertical-pointing rain radar, and aerosol measurements at Andenes, two-directional depolarising aerosol LIDAR and horizontal cloud RADAR on the aircraft. Controlled meteorological balloons were launched from Ny-Ålesund, Svalbard into cold-air outbreak conditions. Surface precipitation samples were collected from a surface network including Abisko, Andenes, Kiruna, Longyearbyen, Ny-Ålesund, Jan Mayen, Bjørnøya, Tarfala, Ålesund, and Bergen. Surface snow was repeatedly sampled along a detailed transect from Kiruna to Lofoten archipelago. Citizen science snow sampling contributed to distributed surface snow sampling in Northern Scandinavia. All stable water isotope measurements have been calibrated onto the VSMOW-SLAP scale. The data from the ISLAS2022 measurement campaign enables the comprehensive assessment of air mass transformation and water turnover during cold-air outbreak conditions using stable water isotopes as a constraint.
Soil cores for microbial, dissolved gas concentrations and isotopic analysis were taken using a Russian type peat corer (De Vleeschouwer et al. 2010) before and after rewetting. Each time, we took duplicates at stations 1-8 for this rather labor-intensive process and divided the core into four depth sections: surface, 5–20, 20–40 and 40–50 cm. Subsamples for dissolved gases and stable carbon isotope analyses were taken with tip-cut syringes with a distinct volume of 3 ml (Omnifix, Braun, Bad Arolsen, Germany) and immediately placed into NaCl-saturated vials (20 ml, Agilent Technologies, 5182-0837, Santa Clara, USA) leaving no headspace and closed gas-tight using rubber stoppers and metal crimpers (both: diameter 20 mm, Glasgerätebau Ochs, Bovenden, Germany).
This dataset contains dissolved oxygen (DO) concentrations, stable oxygen isotope ratios of DO (δ¹⁸ODO), particulate organic carbon (POC) concentrations, and respiration/photosynthesis (R/P) ratios, along with corresponding parameters (temperature, δ¹⁸OH2O, nitrate) collected from the Danube River and its key tributaries during five seasonal sampling campaigns in 2023 and 2024. Water samples were collected using a weighted 2 L sampling bottle submerged 1–2 meters below the surface, with sampling conducted from the river center via bridges or passenger boats, and occasionally from the riverbank. In situ temperature measurements were taken with a multiparameter instrument (HQ40d, HACH™, Loveland, CO, USA). δ¹⁸ODO was analyzed using a modified automated equilibration system (Gasbench II, ThermoFisher Scientific™) coupled to a DELTA V Advantage isotope ratio mass spectrometer (IRMS, ThermoFisher Scientific™). This dataset captures seasonal variations in DO dynamics and provides valuable insights into oxygen sources and sinks within the Danube River. The data support the study of biogeochemical cycling in large river systems and can inform ecosystem management and conservation strategies in the face of environmental and climate change.
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