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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Laurencelle, Marc; Surdyk, Nicolas; Glavan, Matjaž; Hansen, Birgitte; +3 Authors

    A database has been developed and delivered during the FAIRWAY project. This database was developed as a response to the need to harmonize datasets and assessment methods related to pressure and state indicators for water quality in the EU member states, in order to compare and assess indicators using a harmonized approach. The dataset that is made available here provides two files: a public version* of the Excel database, which contains all "tabular" (non-GIS) data related to the 13 case studies that was gathered for the purposes of FAIRWAY's Monitoring & Indicators research theme. It is structured as one "data sheet" and one "summary sheet" per case study. The data sheets contain various parameters (ideally time-dependent data series i.e. time series) that were used, wherever possible, to compute relevant Agri-drinking water quality indicators (ADWIs) such as "nitrogen budget" (a compound Pressure indicator) or "lag time" (a statistically-inferred Link indicator). a ZIP folder containing all GIS data gathered for the FAIRWAY's Monitoring & Indicators research theme. The GIS files are grouped in subfolders, by case study, and then by keywords describing the nature of the spatial data. The Excel database contains near 385,000 rows of data from the 13 case study sites, with more than 65 parameters and more than 500 sub-parameters. The dataset also contains spatial information in a GIS-data zipped folder. The spatial mapping information can be made visible using basic QGIS project files (.qgz), so that GIS data from each case study can be explored. The indicators database can be used in several ways. It may be used to explore data or to calculate additional indicators. Depending of the case studies��� interests, the most commonly available State indicators are about nitrate and pesticides concentrations in water. From a practical point of view based on its actual content, the database may notably be used to explore statistical relations (or Links) between related Pressure and State indicators. This database can also be used as a spatial mapping portal for other usages. For more information on the database, follow this link. * Note that this is a public version of the database, which means that all confidential data was removed from the data sheets. This is the PUBLIC version of the database, where all confidential data has been removed from the Excel-file data sheets.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO; Sygma
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO; Sygma
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Schewe, Ingo;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    PANGAEA
    Dataset . 2013
    Data sources: B2FIND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
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      PANGAEA
      Dataset . 2013
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Fink, Hiske G; Wienberg, Claudia; Hebbeln, Dierk; McGregor, Helen V; +3 Authors

    Continuous sedimentary records from an eastern Mediterranean cold-water coral ecosystem thriving in intermediate water depths (~600 m) reveal a temporary extinction of cold-water corals during the Early to Mid Holocene from 11.4-5.9 cal kyr BP. Benthic foraminiferal assemblage analysis shows low-oxygen conditions of 2 ml l**-1 during the same period, compared to bottom-water oxygen values of 4-5 ml l**-1 before and after the coral-free interval. The timing of the corals' demise coincides with the sapropel S1 event, during which the deep eastern Mediterranean basin turned anoxic. Our results show that during the sapropel S1 event low oxygen conditions extended to the rather shallow depths of our study site in the Ionian Sea and caused the cold-water corals temporary extinction. This first evidence for the sensitivity of cold-water corals to low oceanic oxygen contents suggests that the projected expansion of tropical oxygen minimum zones resulting from global change will threaten cold-water coral ecosystems in low latitudes in the same way that ocean acidification will do in the higher latitudes.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2012
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2012
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Tsanis, Ioannis; Seiradakis, Konstantinos; Sarchani, Sofia; Panagea, Ioanna S; +2 Authors

    Underlying data of soil measurements and analysis by TUC team for the publication ���The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment��� https://doi.org/10.3390/land10090964 from the SoilCare project study sites in Crete. Abstract: The risk of erosion is particularly high in Mediterranean areas, especially in areas that are subject to a not so effective agricultural management���or with some omissions���, land abandonment or wildfires. Soils on Crete are under imminent threat of desertification, characterized by loss of vegetation, water erosion, and subsequently, loss of soil. Several large-scale studies have estimated average soil erosion on the island between 6 and 8 Mg/ha/year, but more localized investigations assess soil losses one order of magnitude higher. An experiment initiated in 2017, under the framework of the SoilCare H2020 EU project, aimed to evaluate the effect of different management practices on the soil erosion. The experiment was set up in control versus treatment experimental design including different sets of treatments, targeting the most important cultivations on Crete (olive orchards, vineyards, fruit orchards). The minimum-to-no tillage practice was adopted as an erosion mitigation practice for the olive orchard study site, while for the vineyard site, the cover crop practice was used. For the fruit orchard field, the crop-type change procedure (orange to avocado) was used. The experiment demonstrated that soil-improving cropping techniques have an important impact on soil erosion, and as a result, on soil water conservation that is of primary importance, especially for the Mediterranean dry regions. The demonstration of the findings is of practical use to most stakeholders, especially those that live and work with the local land.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO; Sygma
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO; Sygma
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; +17 Authors

    We present a map of arable land (both utilized and abandoned) together with a validation data set for eight countries of the former Soviet Union (fSU), namely Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine. The map has a spatial resolution of 10 arc-seconds and represents the year 2010. The map is based on the integration of a number of existing maps and a training data set collected using visual interpretation of very high resolution (VHR) imagery. The map can be used for carbon modelling, assessment of land use, land use change and evaluation of agriculture potential. An additional validation data set was collected through visual interpretation of VHR imagery by trained experts, and can be used for validation of other maps from this region. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. Supplement to: Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcantara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Deppermann, Andre; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen (2018): Spatial distribution of arable and abandoned land across former Soviet Union Countries. Scientific Data, 5, 180056

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    PANGAEA
    Dataset . 2017
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2017
      Data sources: B2FIND
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    Authors: Sarigiannis, Dimosthenis;

    This dataset is operationally produced by the atmospheric dispersion models applied in ICARUS and contains data stored in two main subfolders as follows: 1) Folder “Air quality data of Representative days” which includes air quality data for the Representative days (RD) which were estimated by the EUROCORDEX climate data. This data has been derived from the application of a nesting approach at the urban scale of the Eulerian WRF/WRF-Chem model in the 9 pilot cities addressed in ICARUS i.e. Thessaloniki, Athens, Roskilde/Copenhagen, Basel, Brno, Milan, Madrid, Ljubljana and Stuttgart. On the urban scale, nine (9) nests with dimensions 2x2km have been used consisting of 42x42 grid cells each. Daily concentrations were produced and stored for NO2, O3, PM10, PM2.5. Data are stored in various subfolders named according to the city to which they are referring to and in further subfolders named according to the policy/measure assessed. Within these subfolders the filename convention is the following: Domain/date of the RD. 2) The “GHG” folder which includes GHGs (CO2 and CH4) concentration data calculated for each ICARUS city under the BaU emission scenario. The filename conventions is the following: Cityname.csv

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Fosså, Jan Helge; Kutti, Tina; Bergstad, Odd Aksel; Knutsen, Tor; +4 Authors
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    PANGAEA
    Dataset . 2011
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2011
      Data sources: B2FIND
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    Authors: Malo Rosemeier; Gregor Basters; Alexandros Antoniou;

    Title: Benefits of subcomponent over full-scale blade testing elaborated on a trailing-edge bond line design validation Authors: Malo Rosemeier, Gregor Basters, and Alexandros Antoniou Affiliation: Division Structural Components, Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems, Am Seedeich 45, 27572 Bremerhaven, Germany The following data used for the study is provided: data_blade.zip contains input data for fusedwind-dev (https://github.com/FUSED-Wind/fusedwind-dev) of the DTU10MW blade. data_becas.zip contains input/ output data obtained for/ from BECAS with BECASWrapper (https://gitlab.windenergy.dtu.dk/HAWTOpt2/BECASWrapper). data_rfoil.zip contains polars obtained from Rfoil. data_feproc.zip contains the ANSYS APDL models obtained with FEPROCWrapper (https://gitlab.iwes.fraunhofer.de/git/bdt/FEPROCWrapper). *.sqlite data bases contain all results data which can be accessed with the `post.py` script. result_plots.zip contain the results generated by the `post.py` script. For further details see the manuscript. We acknowledge the support of the European Commission's Seventh Framework Programme within the IRPWind project (609795) and the support within the Future Concept Fatigue Strength of Rotor Blades project granted by the German Federal Ministry for Economic Affairs and Energy (BMWi) (0325939) and the Senator for Health, Environment and Consumer Protection of the Free Hanseatic City of Bremen within the ERDF programme Bremen 2014-2020 (201/PF_IWES_Zukunftskonzept_Betriebsfestigkeit_Rotorblätter_Phase I).

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    ZENODO
    Dataset . 2018
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2018
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2018
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2018
      License: CC BY
      Data sources: Datacite
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    Authors: Mas, Virginie;

    The data set describes biogeochemical composition of sediment samples from the Var turbidite system.

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    PANGAEA
    Dataset . 2012
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2012
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Schmid, Dorothea;

    The dataset includes data on future activity-emission factor matrices for all the ICARUS participating cities and for the classical air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, CO, SO2, BC and OC), GHGs (CO2, CO, N2O, CH4), heavy metals, PAHs and dioxins, relevant to the years 2015, 2020 and 2030. A detailed description of the structure of the DB can be found in deliverable D2.2 freely downloadable from the ICARUS website. Additionally, bottom-up activity data and emission factors are combined to sectoral emission grids (1x1 km) for each city. The sites targeted cover all the ICARUS pilot cities. The data are available in MS-Access format (accdb) to maximise the interoperability for use with a variety of analytical software. The sectoral emission grids are provided in standard GIS vector format (shp).

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO; Sygma
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO; Sygma
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Laurencelle, Marc; Surdyk, Nicolas; Glavan, Matjaž; Hansen, Birgitte; +3 Authors

    A database has been developed and delivered during the FAIRWAY project. This database was developed as a response to the need to harmonize datasets and assessment methods related to pressure and state indicators for water quality in the EU member states, in order to compare and assess indicators using a harmonized approach. The dataset that is made available here provides two files: a public version* of the Excel database, which contains all "tabular" (non-GIS) data related to the 13 case studies that was gathered for the purposes of FAIRWAY's Monitoring & Indicators research theme. It is structured as one "data sheet" and one "summary sheet" per case study. The data sheets contain various parameters (ideally time-dependent data series i.e. time series) that were used, wherever possible, to compute relevant Agri-drinking water quality indicators (ADWIs) such as "nitrogen budget" (a compound Pressure indicator) or "lag time" (a statistically-inferred Link indicator). a ZIP folder containing all GIS data gathered for the FAIRWAY's Monitoring & Indicators research theme. The GIS files are grouped in subfolders, by case study, and then by keywords describing the nature of the spatial data. The Excel database contains near 385,000 rows of data from the 13 case study sites, with more than 65 parameters and more than 500 sub-parameters. The dataset also contains spatial information in a GIS-data zipped folder. The spatial mapping information can be made visible using basic QGIS project files (.qgz), so that GIS data from each case study can be explored. The indicators database can be used in several ways. It may be used to explore data or to calculate additional indicators. Depending of the case studies��� interests, the most commonly available State indicators are about nitrate and pesticides concentrations in water. From a practical point of view based on its actual content, the database may notably be used to explore statistical relations (or Links) between related Pressure and State indicators. This database can also be used as a spatial mapping portal for other usages. For more information on the database, follow this link. * Note that this is a public version of the database, which means that all confidential data was removed from the data sheets. This is the PUBLIC version of the database, where all confidential data has been removed from the Excel-file data sheets.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Schewe, Ingo;
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    PANGAEA
    Dataset . 2013
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2013
      Data sources: B2FIND
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    Authors: Fink, Hiske G; Wienberg, Claudia; Hebbeln, Dierk; McGregor, Helen V; +3 Authors

    Continuous sedimentary records from an eastern Mediterranean cold-water coral ecosystem thriving in intermediate water depths (~600 m) reveal a temporary extinction of cold-water corals during the Early to Mid Holocene from 11.4-5.9 cal kyr BP. Benthic foraminiferal assemblage analysis shows low-oxygen conditions of 2 ml l**-1 during the same period, compared to bottom-water oxygen values of 4-5 ml l**-1 before and after the coral-free interval. The timing of the corals' demise coincides with the sapropel S1 event, during which the deep eastern Mediterranean basin turned anoxic. Our results show that during the sapropel S1 event low oxygen conditions extended to the rather shallow depths of our study site in the Ionian Sea and caused the cold-water corals temporary extinction. This first evidence for the sensitivity of cold-water corals to low oceanic oxygen contents suggests that the projected expansion of tropical oxygen minimum zones resulting from global change will threaten cold-water coral ecosystems in low latitudes in the same way that ocean acidification will do in the higher latitudes.

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    PANGAEA
    Dataset . 2012
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2012
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Tsanis, Ioannis; Seiradakis, Konstantinos; Sarchani, Sofia; Panagea, Ioanna S; +2 Authors

    Underlying data of soil measurements and analysis by TUC team for the publication ���The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment��� https://doi.org/10.3390/land10090964 from the SoilCare project study sites in Crete. Abstract: The risk of erosion is particularly high in Mediterranean areas, especially in areas that are subject to a not so effective agricultural management���or with some omissions���, land abandonment or wildfires. Soils on Crete are under imminent threat of desertification, characterized by loss of vegetation, water erosion, and subsequently, loss of soil. Several large-scale studies have estimated average soil erosion on the island between 6 and 8 Mg/ha/year, but more localized investigations assess soil losses one order of magnitude higher. An experiment initiated in 2017, under the framework of the SoilCare H2020 EU project, aimed to evaluate the effect of different management practices on the soil erosion. The experiment was set up in control versus treatment experimental design including different sets of treatments, targeting the most important cultivations on Crete (olive orchards, vineyards, fruit orchards). The minimum-to-no tillage practice was adopted as an erosion mitigation practice for the olive orchard study site, while for the vineyard site, the cover crop practice was used. For the fruit orchard field, the crop-type change procedure (orange to avocado) was used. The experiment demonstrated that soil-improving cropping techniques have an important impact on soil erosion, and as a result, on soil water conservation that is of primary importance, especially for the Mediterranean dry regions. The demonstration of the findings is of practical use to most stakeholders, especially those that live and work with the local land.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; +17 Authors

    We present a map of arable land (both utilized and abandoned) together with a validation data set for eight countries of the former Soviet Union (fSU), namely Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine. The map has a spatial resolution of 10 arc-seconds and represents the year 2010. The map is based on the integration of a number of existing maps and a training data set collected using visual interpretation of very high resolution (VHR) imagery. The map can be used for carbon modelling, assessment of land use, land use change and evaluation of agriculture potential. An additional validation data set was collected through visual interpretation of VHR imagery by trained experts, and can be used for validation of other maps from this region. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. Supplement to: Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcantara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Deppermann, Andre; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen (2018): Spatial distribution of arable and abandoned land across former Soviet Union Countries. Scientific Data, 5, 180056

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    PANGAEA
    Dataset . 2017
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2017
      Data sources: B2FIND
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    Authors: Sarigiannis, Dimosthenis;

    This dataset is operationally produced by the atmospheric dispersion models applied in ICARUS and contains data stored in two main subfolders as follows: 1) Folder “Air quality data of Representative days” which includes air quality data for the Representative days (RD) which were estimated by the EUROCORDEX climate data. This data has been derived from the application of a nesting approach at the urban scale of the Eulerian WRF/WRF-Chem model in the 9 pilot cities addressed in ICARUS i.e. Thessaloniki, Athens, Roskilde/Copenhagen, Basel, Brno, Milan, Madrid, Ljubljana and Stuttgart. On the urban scale, nine (9) nests with dimensions 2x2km have been used consisting of 42x42 grid cells each. Daily concentrations were produced and stored for NO2, O3, PM10, PM2.5. Data are stored in various subfolders named according to the city to which they are referring to and in further subfolders named according to the policy/measure assessed. Within these subfolders the filename convention is the following: Domain/date of the RD. 2) The “GHG” folder which includes GHGs (CO2 and CH4) concentration data calculated for each ICARUS city under the BaU emission scenario. The filename conventions is the following: Cityname.csv

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO; Sygma
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO; Sygma
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    Authors: Fosså, Jan Helge; Kutti, Tina; Bergstad, Odd Aksel; Knutsen, Tor; +4 Authors
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    PANGAEA
    Dataset . 2011
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2011
      Data sources: B2FIND
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    Authors: Malo Rosemeier; Gregor Basters; Alexandros Antoniou;

    Title: Benefits of subcomponent over full-scale blade testing elaborated on a trailing-edge bond line design validation Authors: Malo Rosemeier, Gregor Basters, and Alexandros Antoniou Affiliation: Division Structural Components, Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems, Am Seedeich 45, 27572 Bremerhaven, Germany The following data used for the study is provided: data_blade.zip contains input data for fusedwind-dev (https://github.com/FUSED-Wind/fusedwind-dev) of the DTU10MW blade. data_becas.zip contains input/ output data obtained for/ from BECAS with BECASWrapper (https://gitlab.windenergy.dtu.dk/HAWTOpt2/BECASWrapper). data_rfoil.zip contains polars obtained from Rfoil. data_feproc.zip contains the ANSYS APDL models obtained with FEPROCWrapper (https://gitlab.iwes.fraunhofer.de/git/bdt/FEPROCWrapper). *.sqlite data bases contain all results data which can be accessed with the `post.py` script. result_plots.zip contain the results generated by the `post.py` script. For further details see the manuscript. We acknowledge the support of the European Commission's Seventh Framework Programme within the IRPWind project (609795) and the support within the Future Concept Fatigue Strength of Rotor Blades project granted by the German Federal Ministry for Economic Affairs and Energy (BMWi) (0325939) and the Senator for Health, Environment and Consumer Protection of the Free Hanseatic City of Bremen within the ERDF programme Bremen 2014-2020 (201/PF_IWES_Zukunftskonzept_Betriebsfestigkeit_Rotorblätter_Phase I).

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2018
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2018
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2018
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2018
      License: CC BY
      Data sources: Datacite
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    Authors: Mas, Virginie;

    The data set describes biogeochemical composition of sediment samples from the Var turbidite system.

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    PANGAEA
    Dataset . 2012
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2012
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Schmid, Dorothea;

    The dataset includes data on future activity-emission factor matrices for all the ICARUS participating cities and for the classical air pollutants (NH3, NMVOC, NOX, PM10, PM2.5, CO, SO2, BC and OC), GHGs (CO2, CO, N2O, CH4), heavy metals, PAHs and dioxins, relevant to the years 2015, 2020 and 2030. A detailed description of the structure of the DB can be found in deliverable D2.2 freely downloadable from the ICARUS website. Additionally, bottom-up activity data and emission factors are combined to sectoral emission grids (1x1 km) for each city. The sites targeted cover all the ICARUS pilot cities. The data are available in MS-Access format (accdb) to maximise the interoperability for use with a variety of analytical software. The sectoral emission grids are provided in standard GIS vector format (shp).

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO; Sygma
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO; Sygma
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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