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).
Die Stiftung Initiative Mehrweg hat erstmals im Jahr 2006 eine Studie zur Nachhaltigkeit von Verpackungssystemen für Obst- und Gemüsetransporte in Europa basierend auf einer Lebenszyklusanalyse in Auftrag gegeben, mit dem Ziel gebräuchliche Verpackungssysteme für Obst und Gemüse in Europa auf die mit ihrer Verwendung verbundenen Umweltauswirkungen zu untersuchen und miteinander zu vergleichen. Darüber hinaus sollten Erkenntnisse zu den Kosten und zu ausgewählten sozialen Faktoren gewonnen werden, um dem Aspekt der Nachhaltigkeit gerecht zu werden. Die Ergebnisse der ersten Studie wurden 2009 nochmals überprüft und aktualisiert. Die Studie wurde von der Abteilung Ganzheitliche Bilanzierung (GaBi) der Universität Stuttgart und der PE International erstellt. Es handelt sich bei der Untersuchung der ökologischen Auswirkungen um eine vergleichende Ökobilanz im Sinne der DIN EN ISO 14040 ff, was durch einen Critical Review bestätigt wurde. Die Ergebnisse zeigen deutliche ökologische und ökonomische Vorteile für die Mehrwegsysteme.
The objective of the project is to support the client for successful development of CDM projects in the agro-industry sector in Thailand. Sector for CDM project development is agro-industry with focus on starch factories. Starch industry is highly energy intensive and produces significant amounts of wastewater. Furthermore, as part of the Cassava processing, pulp is separated as organic waste. The projects aim to introduce biogas generation from organic waste in starch production and decrease the factories dependence on fossil fuels. The supported CDM projects consist of two components: methane avoidance and fuel switch of electricity from the grid and fossil fuels to renewable energy. The technical solutions included the treatment of wastewater and pulp from starch industry for biogas production. The generated biogas will be used for electricity and heat generation. The development of the projects as CDM projects enables co-financing of the investment via the carbon sales. Services provided: The support consisted of 3 packages: Revision of the PDD for biogas from wastewater project: Technical revision of the Project Design Document as a '3rd party'; Assessment and revision of the 'additionality of the project and emission reduction calculations; Development of the PDD for the pulp to energy biogas projects: Development of a project design document (PDD) according to the regulations of the Kyoto protocol; Assessment and demonstration of the 'additionality of CDM projects which use pulp from starch factories for biogas generation; Preparation of the study about the pulp in the starch factories in Thailand: Development of the concept for the study; Determination of methodology, approach and stakeholders for the study development.
Three research questions of the project: 1. What global, European and Swiss climate GHG-policies will follow after 2012 and what will be their performance in the long run (up to 2050)? 2. What policies will foster mitigation in the transportation and building and real estate sectors, how can they be made acceptable and what is the role of voluntary approaches? 3. What will be the economic impacts of climate change on tourism and what are the opportunities for mitigation and adaptation?
Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.In the frame of the proposal 'Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change' we advocate the development of fully coupled, process-oriented models that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes on the landscape scale. We will use the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behaviour and couple this to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.The objective of this proposal is therefore to quantify the global uncertainty of the coupled hydro-biogeochemical models and investigate the uncertainty chain from parameter uncertainty over forcing data uncertainty up the structural model uncertainty be setting up different combinations of CMF and LandscapeDNDC. A comprehensive work program has been developed structured in 4 work packages, that consist of (1) model set up, calibration and uncertainty assessment on site scale followed by (2) an application and uncertainty assessment of the coupled model structures on regional scale, (3) global change scenario analyses and finally (4) evaluating model results in an ensemble fashion.Last but not least, a further motivation of this proposal is to provide project results in a manner that they support planning and decision taking under uncertainty, as this proposal is part of the package proposal on 'Methodologies for dealing with uncertainties in landscape planning and related modelling'.
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 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.
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).
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