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.
This study reports a precisely dated pollen record with a 20-year resolution from the varved sediments of Lake Mondsee in the north-eastern European Alps (47°49′N, 13°24′E, 481 m above sea level). The analysed part of core spans the interval between 1500 BCE and 500 CE and allows changes in vegetation composition in relation to climatic changes and human activities in the catchment to be inferred. Intervals of distinct but modest human impact are identified at ca. 1450-1220, 740-490 and 340-190 BCE and from 80 BCE to 180 CE. While the first two intervals are synchronous with prominent salt mining phases during the Bronze Age and Early Iron Age at the nearby UNESCO World Heritage Site of Hallstatt, the last two intervals fall within the Late Iron Age and Roman Imperial Era, respectively. Comparison with published records of extreme runoff events obtained from the same sediment core shows that human activities (including agriculture and logging) around Lake Mondsee were low during intervals of high flood frequency as indicated by a higher number of intercalated detrital event layers, but intensified during hydrologically stable intervals. Comparison of the pollen percentages of arboreal taxa with the stable oxygen isotope and potassium ion records of the NGRIP and GISP2 ice cores from Greenland reveals significant positive correlations for Fagus and negative correlations for Betula and Alnus. This underlines the sensitivity of vegetation around Lake Mondsee to temperature fluctuations in the North Atlantic as well as to moisture fluctuations controlled by changes in the intensity of the Siberian High and the North Atlantic Oscillation (NAO) regime.
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.
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")
Water isotopes (δ2H and δ18O) were analyzed in samples collected in lakes associated to major riverine systems in northeastern Germany throughout 2020. This sub-dataset is derived from water samples collected from lake shores. Samples were taken in March and July 2020 with a pipette from 40-60 cm depth below water surface and directly transferred into a measurement vial. Stable isotope analysis was conducted at IGB Berlin, using a Picarro L2130-i cavity ring-down spectrometer. The data give information about the seasonal isotope amplitude in the sampled lakes and about spatial isotope variability in different branches of the associated riverine systems.
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.
WMS zum Bebauungsplan 060 Steuerung Tierhaltungsanlagen Munderloh Urschrift im originären Datenformat
This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).
The structural polysaccharides cellulose and chitin of plants, fungi, and arthropods are major components of organic matter in agricultural soils. These biopolymers are carbon sources of soil microbial communities linked to soil redox processes. Soil aggregates of waterunsaturated soil form natural boundaries of oxic conditions outside and oxygen-limited conditions inside. These biogeochemical interfaces lead to a highly heterogeneous oxygen distribution on a millimetre scale. The effects and mechanisms of the toxicity of herbicides on biopolymer degrading communities in such highly compartmentalized soils have not been resolved. The proposed study is a continuation of a project funded within Priority Program 1315 'Biogeochemical Interfaces in Soil'. The preceding project resolved phylogenetic identities of known and novel prokaryotes linked to cellulose degradation under both oxic and anoxic conditions, and demonstrated that the acidic herbicides Bentazon and MCPA impair microbial processes involved in cellulose degradation. The proposed project will (I) identify chitin-degrading prokaryotes, fungi, and protists that are active in oxic and anoxic microzones, (II) determine the tolerance of various cellulolytic and chitinolytic taxa to Bentazon and MCPA, (III) characterize key chitin-degraders, and (IV) will quantitatively assess oxygen distribution in during biopolymer degradation in an agricultural soil. Central methods will include stable isotope probing, analyses of 16S rRNA, 18S rRNA, and chitinase genes, HPLC, GC, and oxygen sensing via analysis of fluorescence dyes.
Der Datensatz Agricultural And Aquaculture Facilities / Tierhaltungs- und Aufzuchtanlagen in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE View-Service (WMS-AF-TIERE) Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE Download-Service (WFS-AF-TIERE) 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. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute. Der Datensatz Agricultural And Aquaculture Facilities / Tierhaltungs- und Aufzuchtanlagen in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE View-Service (WMS-AF-TIERE) Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE Download-Service (WFS-AF-TIERE) 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. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute.
| Organisation | Count |
|---|---|
| Bund | 495 |
| Europa | 13 |
| Global | 1 |
| Kommune | 87 |
| Land | 361 |
| Weitere | 58 |
| Wissenschaft | 452 |
| Zivilgesellschaft | 10 |
| Type | Count |
|---|---|
| Agrarwirtschaft | 1 |
| Chemische Verbindung | 4 |
| Daten und Messstellen | 224 |
| Ereignis | 2 |
| Förderprogramm | 420 |
| Hochwertiger Datensatz | 1 |
| Software | 1 |
| Taxon | 33 |
| Text | 148 |
| Umweltprüfung | 167 |
| unbekannt | 208 |
| License | Count |
|---|---|
| Geschlossen | 302 |
| Offen | 838 |
| Unbekannt | 25 |
| Language | Count |
|---|---|
| Deutsch | 513 |
| Englisch | 692 |
| Resource type | Count |
|---|---|
| Archiv | 130 |
| Bild | 7 |
| Datei | 157 |
| Dokument | 174 |
| Keine | 506 |
| Unbekannt | 3 |
| Webdienst | 28 |
| Webseite | 241 |
| Topic | Count |
|---|---|
| Boden | 735 |
| Lebewesen und Lebensräume | 931 |
| Luft | 583 |
| Mensch und Umwelt | 1165 |
| Wasser | 716 |
| Weitere | 1070 |