Here, we examine the ecosystem ramifications of changes in sediment-dwelling invertebrate bioturbation behaviour—a key process mediating nutrient cycling—associated with nearfuture environmental conditions (+ 1.5 °C, 550 ppm [pCO2]) for species from polar regions experiencing rapid rates of climate change. This dataset is included in the OA-ICC data compilation maintained in the framework of the IAEA Ocean Acidification International Coordination Centre (see https://oa-icc.ipsl.fr). Original data were downloaded from Polar Data Centre (see Source) by the OA-ICC data curator. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2024) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2024-07-11.
This data set presents the reconstructed vegetation cover for 1451 European sites based on harmonized pollen data from the data set LegacyPollen 2.0 and optimized RPP values. Sugita's REVEALS model (2007) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by taking into account taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were also calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal and forest cover was reconstructed. In this optimized reconstruction, relative pollen productivity estimates for the ten most common taxa were first optimized by using reconstructed tree cover from modern pollen samples and LANDSAT remotely sensed tree cover (Sexton et al. 2013) for Europe. Values for non-optimized taxa for relative pollen productivity and fall speed were taken from the synthesis from Wiezcorek and Herzschuh (2020). The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with optimized reconstructed vegetation cover for all records in Europe. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.
Die traceless materials GmbH ist ein Bioökonomie Start-up Unternehmen, das im Jahr 2020 als Ausgründung der TU Hamburg hervorgegangen ist. Das Hauptgeschäftsfeld stellt die Entwicklung und Produktion des traceless Materials (rückstandslos biologisch abbaubares Material) für den Kunststoffverarbeitungsmarkt dar. Erklärtes Ziel ist, einen messbaren Beitrag zur Lösung der weltweiten Verschmutzung durch Kunststoffe zu leisten. Die traceless materials GmbH stellt mittels eines innovativen Verfahrens ein Material her, welches vergleichbare Eigenschaften wie Kunststoff besitzt. Es handelt sich dabei aber um eine neuartige Materialkategorie. Konventioneller Kunststoff wird in einem synthetischen Verfahren und zum Großteil aus fossilen Rohstoffen hergestellt. Der Rohstoff in diesem Projekt hingegen sind pflanzliche Reststoffe, welche nach der Extraktion der natürlichen Polymere noch als Futtermittel oder zur energetischen Verwertung genutzt werden können. Im Vorhaben soll eine Demonstrationsanlage mit einer Kapazität von mehreren Tausend Tonnen pro Jahr errichtet und betrieben werden. Im Herstellungsprozess des traceless Materials wird als Rohstoff ein pflanzlicher Reststoff verwendet, der als Nebenprodukt der industriellen Getreideverarbeitung anfällt. Mit einem zum Patent angemeldeten Verfahren werden daraus natürliche Polymere extrahiert und zu einem Granulat verarbeitet. Dieses Granulat kann mit gängigen Technologien der Kunststoffverarbeitung zu verschiedenen Produktanwendungen weiterverarbeitet werden, beispielsweise im Spritzguss oder der Extrusion. Das hergestellte Material könnte z.B. zur Herstellung von Einwegverpackungen und -produkten, welche leicht in die Umwelt gelangen oder sich nicht recyceln lassen, eingesetzt werden und so zur Verbrauchsminderung fossiler Rohstoffe beitragen. Damit soll auch die Umweltverschmutzung zurückgehen, da das Material sich rückstandslos abbaut und nicht schädlich für Flora und Fauna ist, wenn es unsachgemäß in der Umwelt entsorgt werden sollte. Produkte, die aus dem Material hergestellt werden, sind entweder über den Restmüll oder bei Verpackungen über den gelben Sack/die gelbe Tonne/Wertstofftonne zu entsorgen. In beiden Fällen werden sie energetisch verwertet, da der Marktanteil für eine sortenreine Sammlung und mechanisches Recycling derzeit zu gering ist. Eine Entsorgung über die Bioabfallsammlung ist nicht zulässig, auch wenn das Material zertifiziert gartenkompostierbar ist. Bei einer Kompostierung würde auch der energetische Nutzen verloren gehen. Bei einer jährlichen Produktionskapazität von mehreren Tausend Tonnen können nicht nur substantiell CO 2 -Emissionen und fossile Energieträger, sondern auch Wasser und Landressourcen eingespart werden. Das Verfahren ist für eine Vielzahl von Unternehmen der Chemie- und Kunststoffindustrie übertragbar. Da das Material auf den gängigen Anlagen der kunststoffverarbeitenden Industrie eingesetzt werden kann, ist eine Übertragbarkeit ohne (hohen) Aufwand möglich. Weiterhin wird an der Übertragbarkeit dieses Verfahrens der Polymerextraktion auf andere Reststoffe von Getreide geforscht. Branche: Chemische und pharmazeutische Erzeugnisse, Gummi- und Kunststoffwaren Umweltbereich: Ressourcen Fördernehmer: traceless materials GmbH Bundesland: Hamburg Laufzeit: seit 2023 Status: Laufend
This data publication contains maps resulting from spatial prioritisations conducted for the iAtlantic D5.3 report on Systematic Conservation Planning of the wider Atlantic Ocean based on results generated by the iAtlantic project. The maps were produced using the prioritizr R package (Hanson et al. 2023), which identifies priority areas for achieving specific conservation goals while minimising costs. The various prioritisations were developed to address multiple research questions related to: (1) identifying priority areas for conservation and restoration, (2) transboundary conservation, (3) climate-smart conservation planning, and (4) protecting 30% of the Atlantic Ocean, including 10% under strict protection. The results are organised into subfolders based on the research questions addressed and further categorised into data-rich and data-poor regions, along with aggregate results for each region. Further, the results are organised into subfolders representing multiple scenarios executed using various cost layers, including area-based, Global Fishing Watch (GFW, 2023) benthic, GFW total fishing, Global Fisheries Landings (GFL, Watson 2019) v4.0 benthic, and GFL v4.0 total landings. Each map filename provides descriptive information about the executed scenario.
<p>Im Pilotprojekt <a href="https://www.ki-ideenwerkstatt.de/unterstuetzung-materialien/pilotprojekte/toxfox-mithilfe-von-ki-inhaltsstoffe-scannen/"><em>ToxFox</em></a> wurde 2024/25 gemeinsam mit dem <a href="https://www.bund.net/">BUND</a> eine KI-basierte OCR-Lösung (englisch: optical character recognition, Bild zu Text) entwickelt. Hierbei wird via FastAPI-Webanwendung ein per Smartphonekamera aufgenommens Bild der Informationstextes der Inhaltsstoffe auf Verpackung eines Produktes erfasst und anschließend eine Liste der gefundenen Schadstoffe nach INCI zurückgegeben. INCI steht für die Internationale Nomenklatur für kosmetische Inhaltsstoffe. Bisher musste für diesen Prozess der Barcode der Produkte gescannt werden. Mit der OCR-Lösung sollen u.a. Fehler korrigiert werden, die durch veraltete, auf Barcodes enthaltene Informationen entstehen oder sich durch eine Umbenennung der Chemikalien durch die Industrie ergeben könnten.</p>
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).
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).
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).
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).
This dataset provides carbonate chemistry and hydrological measurements supporting the analysis of the stability of alkalinity and carbon transport potential in the Elbe Estuary, northern Germany. It includes (1) results from laboratory incubation experiments using water samples from the Elbe conducted in 2023, (2) historical water chemistry monitoring records from multiple stations, and (3) monthly flow discharge measurements from the Neu Darchau gauging station. Experimental data were collected from the experiments varying salinity and seasonal conditions, and parameters measured include pH, temperature, and total alkalinity. Major ion concentrations (Na+, K+, Ca2+, Mg2+, Cl-, SO42-) were reconstructed from stoichiometry. The saturation states of calcite and aragonite, as well as pCO2, were calculated using the phreeqpython geochemical package. Historical data, covering carbonate chemistry and major ions at several stations and over multiple years, were collected from digitized sources and FGG Elbe. Together, this dataset facilitates the investigation of long-term trends in the carbonate system and carbon transport in the land ocean transition zone of the Elbe River.
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