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6,170 results for “Europeans”
European Mean Target Achievement (MTA) Indicator
<p>The EU MTA indicator is one way of assessing the benefits of protected area expansions using information of covered species distributions. It can be interpreted as the average number of species or habitats that are adequately (indicated through a target) conserved by conservation areas (Natura 2000 and/or CDDA sites) within the European union.</p> <p>This repository contains the created MTA indicator values created from an intersection of the Natura2000 and CDDA databases with the sensitive Article 12 and 17 reporting data.</p> <p><strong>Filename explanation: </strong></p> <p>MTA_{target}_{scale}_{directive}_{biodiversity}_{version}.csv</p> <table> <tbody> <tr> <td>target</td> <td>Which target was used for calculations. Currently: 'loglinear'</td> </tr> <tr> <td>scale</td> <td>Which datasets from the reporting was used. Supported currently are EU and MS</td> </tr> <tr> <td>directive</td> <td>Subset either for 'All' species and habitats, or just 'Art12' or 'Art17' data</td> </tr> <tr> <td>biodiversity</td> <td>Subset either for 'All', 'species' or 'habitats' respectively</td> </tr> <tr> <td>version</td> <td>A unique version number for each upload identical with the Zotero version.</td> </tr> </tbody> </table> <p> </p> <p>For further information and a detailed factsheet can be found on the online dashboard here:<br><a title="Online dashboard" href="https://martin-jung.github.io/EUMTA/dashboard.html">https://martin-jung.github.io/EUMTA/dashboard.html</a> </p> <p>---</p> <p>* The MTA indicator calculation and the creation of this dashboard contributes to WP7 of the NaturaConnect project. The information here is provided free of charge and the project takes no responsibility for errors or misuse.</p>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Croatia
<p>This dataset contains TSE surveillance results in cattle, sheep, goats, cervids and other species, and genotyping in sheep, pursuant to Regulation (EC) 999/2001.</p> <p><strong>Reporting authorities contributing to each data collection</strong>:</p> <ul> <li>TSE_2023_HR: Ministry of Agriculture (MPS)</li> <li>TSE_2022_HR: Ministry of Agriculture (MPS)</li> <li>TSE_2021_HR: Ministry of Agriculture (MPS)</li> <li>TSE_2020_HR: Ministry of Agriculture (MPS)</li> <li>TSE_2019_HR: Ministry of Agriculture (MPS)</li> </ul>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Austria
<p>This dataset contains TSE surveillance results in cattle, sheep, goats, cervids and other species, and genotyping in sheep, pursuant to Regulation (EC) 999/2001.</p> <p><strong>Reporting authorities contributing to each data collection</strong>:</p> <ul> <li>TSE_2023_AT: Austrian Agency for Health and Food Safety (AGES)</li> <li>TSE_2022_AT: Austrian Agency for Health and Food Safety (AGES)</li> <li>TSE_2021_AT: Austrian Agency for Health and Food Safety (AGES)</li> <li>TSE_2020_AT: Austrian Agency for Health and Food Safety (AGES)</li> <li>TSE_2019_AT: Austrian Agency for Health and Food Safety (AGES)</li> </ul>
DuneFront deliverable D4.1 - Physical boundary conditions over European coasts
<p>The European project DuneFront (<a href="https://dunefront.eu">https://dunefront.eu</a>, <a href="https://cordis.europa.eu/project/id/101135410">https://cordis.europa.eu/project/id/101135410</a>) is working to improve coastal protection across Europe by using Nature-based Solutions (NbS), such as Dune-Dike hybrids (DD-hybrids), to defend coastlines from extreme weather and rising sea levels. Within this project, this “Physical Boundary Conditions” deliverable focuses on collecting and mapping key physical boundary conditions that affect the effectiveness of these solutions. The aim was to create a consistent, Europe-wide, high-quality dataset that helps understand how DD-hybrids are, and will be, affected by waves, tides, weather patterns, and climate change. </p> <p>The dataset is made of 5 geopackage files, each duplicated in csv format for accessibility. See the deliverable report (pdf) for detailed information on each file, use notes, and literature references. We explicitly recommend the use of the gpkg files over csv for any GIS application, for reasons that are detailed in the report.</p>
European Truck Parking Locations
<p><strong>### KAMO Update (v04)</strong></p> <p>This updated dataset comprises <em>N=13,323</em> real-world truck parking locations across Europe (EU-27, EFTA, and the UK), filtered for location alongside the TEN-T network. Locations origintate from from the previously published (<em>N=19,713</em>) and unpublished (<em>N=32,251</em>) locations and additional sources to refine and enhance the dataset. Documenation and methods are provided in the attached documentation. KAMO and Fraunhofer ISI does not assume any liability for completeness, correctness and accuracy of the information. </p> <p>This dataset aims to support in identifying attractive, real-world charging infrastructure locations in Europe, facilitating the planning of national and European charging networks to boost e-truck diffusion and promote sustainable road freight transport. It benefits scientists, industry players, grid operators, and public authorities by providing precise local information as well as insights for infrastructure planning, energy demand modeling, and deployment along key transport corridors (TEN-T network) as prescribed per the EU's Alternative Fuels Infrastructure Regulation (AFIR).</p> <p>We have incorporated feedback from stakeholders compared to the previously published version. The update shall:</p> <blockquote> <p>Add missing locations and increase TEN-T coverage</p> <p>Supplement planning information</p> <p>Allow conclusions on the attractiveness of locations</p> </blockquote> <p>We recommend using this location data as input (or candidate locations) for coverage or optimization algorithms to identify a highly condensed set of optimal / most attractive locations. More information is available upon request.</p> <p>More information is available upon request. </p> <p><strong>### Older versions (v01-v03)</strong></p> <p>This geospatial dataset comprises N=19,713 real-world truck parking locations across Europe (EU-27, EFTA, and the UK). Data origintated from various sources including OpenStreetMap and commercial truck routing / geocoding software to identify publicly accessible and truck-certified parking locations. Using geospatial clustering helped to condense the dataset and reduce redundancies. Refining and enhancing the dataset involved supplementary datasets and several filters to obtain the final subset. Accordingly, GPS coordinates may not match exact locations but should be considered as reference point for detailed local analyses of ambient conditions and truck accessibility. Coverage and completeness varies among countries. Fraunhofer ISI does not assume any liability for completeness, correctness and accuracy of the information. </p> <p>This dataset plays a pivotal role in identifying viable real-world locations for future alternative infrastructure sites for heavy-duty trucks, thereby acting as a crucial resource in promoting low-carbon road freight transport facilitated by electrified truck fleets. Infrastructure sites may comprise charging infrastructure for battery-electric trucks and hydrogen refuelling stations (HRS) for fuel-cell electric or hydrogen combustion trucks. Consequently, it can serve as a valuable asset for research in traffic science, future energy systems, and alternative truck powertrains. Its value extends to assisting industry stakeholders such as Charge Point Operators (CPOs), truck manufacturers, and grid network operators but also public authorities in aligning their efforts towards the deployment of alternative infrastructure.</p>
RivFISH - An European database on fish species presence across river basins
<p>The RivFISH database aggregates the available data on freshwater-dependent fish presence in Europe, validated at the river basin level and considering taxonomical synonyms for species names, thus allowing for a maximization of data usage and robustness. This database also promotes interoperability with other datasets, including the IUCN Red List of Threatened Species, FishBase and the Catchment Characterisation and Modelling (CCM2) – River and Catchment Database v2.1. It is, as far as the authors know, the most up-to-date and comprehensive database on the presence of freshwater-dependent fish species for European river basins. The structure of the database is also prepared to deal with future alterations in species taxonomy, as well as new records of species occurrence in river basins.</p>
Data from: Functional structure of European forest beetle communities is enhanced by rare species
<p>From article abstract:</p> <p><a href="https://doi.org/10.1016/j.biocon.2022.109491">https://doi.org/10.1016/j.biocon.2022.109491</a></p> <p><strong>ABSTRACT</strong></p> <p>Biodiverse communities have been shown to sustain high levels of multifunctionality and thus a loss of species likely negatively impacts ecosystem functions. For most taxa, however, the roles of individual species are poorly known. Rare species, often the most likely to go extinct, may have unique traits leading to unique functional roles. Alternatively, rare species may be functionally redundant, such that their loss would not disrupt ecosystem functions. We quantified the functional role of rare species by using capture records of wood-living (saproxylic) beetle species, combined with recent databases of their morphological and ecological traits, from three regions in central and northern Europe. Using a rarity index based on species’ local abundance, geographic range, and habitat breadth, we used local and regional species removal simulations to examine the contributions of both the rarest and the most common beetle species to three measures of community functional structure: functional richness, functional specialization, and functional originality. In both regional species pools and local communities, all three of these measures declined more rapidly when rare species were removed than under common (or random) species removal scenarios. These consistent patterns across scales and among several forest types give evidence that rare species provide unique functional contributions, and that their loss may disproportionately impact ecosystem functions. This implies that conservation measures targeting rare and endangered species, such as preserving intact forests with dead wood and mature trees, can provide broader ecosystem-level benefits. Experimental research linking functional structure to ecosystem processes should be prioritized to increase our understanding of the functional consequences of species loss and to develop more effective conservation strategies.</p> <p> </p> <p><strong>DATASET DESCRIPTION</strong></p> <p>This dataset includes a) beetle capture information and b) beetle trait information from three countries: 1) Norway, 2) Finland, and 3) Germany. </p> <p> </p> <p><strong>FILES</strong></p> <p><strong>readme.txt</strong> -- this has the information from this description section</p> <p><strong>Norway_traits.csv</strong>, <strong>Finland_traits.csv</strong>, <strong>Germany_traits.csv</strong> -- these are the trait files, including all species</p> <p><strong>Norway_sites.species.csv</strong>, <strong>Finland_sites.species.csv</strong>, <strong>Germany_sites.species.csv</strong> -- this has species (rows) by sites (columns); values are the number of beetles caught (for number of traps, dates, and other site covariates, see related dataset: <a href="https://doi.org/10.5061/dryad.tmpg4f50b">https://doi.org/10.5061/dryad.tmpg4f50b</a> and manuscript: <a href="https://doi.org/10.1111/jbi.14272">https://doi.org/10.1111/jbi.14272</a>). Species names follow GBIF taxonomic backbone.</p> <p><strong>Traits_METADATA.csv</strong> -- this has information on all the fields in the trait data</p> <p> </p>
Data and code for the manuscript "From white to green: Snow cover loss and increased vegetation productivity in the European Alps"
<p>Data and code used for the manuscript "From white to green: Snow cover loss and increased vegetation productivity in the European Alps" by Rumpf et al., submitted December 2021 to Science</p> <p>See file ReadMe.txt for a description of the content and the original publication for further explanations.</p> <p>You are free to use these data and code for scientific purposes but are obliged to cite the above-mentioned publication.<br> For further questions, contact sabine.rumpf@unibas.ch</p>
Lake mask and distance to land dataset of 2024 lakes for the European Space Agency Climate Change Initiative Lakes v2
<p>This dataset contains the distance to land and the lake identifiers as a global netcdf file for all the water pixels at 1km (1/120 deg) lat/lon resolution of 2024 lakes distributed globally. It contains also the list of lakes as a csv file with information such as the lake center as defined in [1], and the coordinate of a box to easily locate the like in the global netcd file. The mask excludes islands on lakes and it has been derived from the GloboLakes high resolution limnology dataset [2]. The dateset have been further harmonized with the lake maximum extent lake polygons by PML [3]. The lake list with the plot of the mask and the polygons is available as a html file accessible also from the lake website at the University of Reading: http://www.laketemp.net/home_CCI/LMPolygons.php</p> <p>This dataset accompanies the <strong>ESA CCI Lakes v2 dataset</strong> [4].</p> <p> </p> <p>[1] Carrea, L.; Embury, O.; Merchant, C.J. (2015): High-resolution datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates - Geoscience Data Journal, 2 (2). pp. 83-97. ISSN 2049-6060 doi: https://doi.org/10.1002/gdj3.32</p> <p>[2] Carrea, L.; Embury, O.; Merchant, C.J. (2015): GloboLakes: high-resolution global limnology dataset v1. Centre for Environmental Data Analysis. doi:10.5285/6be871bc-9572-4345-bb9a-2c42d9d85ceb. <a href="http://dx.doi.org/10.5285/6be871bc-9572-4345-bb9a-2c42d9d85ceb">http://dx.doi.org/10.5285/6be871bc-9572-4345-bb9a-2c42d9d85ceb</a></p> <p>[3] Simis, S.; Mata, A.; Selmes, N.; Carrea, L. (2021) Lake polygons dataset accompanying Calimnos v1.4.0 and ESA CCI Lakes Climate Research Data Package v2.0. zenodo https://doi.org/10.5281/zenodo.4899250</p> <p>[4] Carrea, L.; Crétaux, J.-F.; Liu, X.; Wu, Y.; Bergé-Nguyen, M.; Calmettes, B.; Duguay, C.; Jiang, D.; Merchant, C.J.; Mueller, D.; Selmes, N.; Simis, S.; Spyrakos, E.; Stelzer, K.; Warren, M.; Yesou, H.; Zhang, D. (2022): ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 2.0.1. NERC EDS Centre for Environmental Data Analysis <a href="https://catalogue.ceda.ac.uk/uuid/03c935c6890c4b2ebf4aae4d84cd9472">https://catalogue.ceda.ac.uk/uuid/03c935c6890c4b2ebf4aae4d84cd9472</a></p>
Distribution and habitat suitability maps for Central European steppe plants
<p>This dataset contains distribution maps for Central European steppe plants and coordinates of species occurrence points used by Divíšek et al. (2022) to calibrate habitat suitability models. These models were projected onto past climates and the resulting habitat suitability maps for 10 periods since the Last Glacial Maximum (LGM) are also included. These maps were further used as input data for simulations of species migration from climatically suitable areas in the LGM to identify those that may have served as a source for colonisation of the species' current ranges. For each species, we present maps of climatically suitable areas during the LGM and mid-Holocene (for the latter period, only areas accessible from the LGM are shown), as well as maps of the "source areas" from which the species may have colonised the regions occupied today.</p>
European_bird_dispersal: v1.0.3-Edispersal
<p><strong>Standardised empirical dispersal kernels emphasise the pervasiveness of long-distance dispersal in European birds </strong></p> <p>ABSTRACT:</p> <ol> <li>Dispersal is a key life-history trait for most species and is essential to ensure connectivity and gene flow between populations and facilitate population viability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis. </li> <li>Here we introduce a statistical framework to estimate standardised dispersal kernels from biased data. Based on this, we compare empirical dispersal kernels for European breeding birds considering age (average dispersal; natal, before first breeding; and breeding dispersal, between subsequent breeding attempts) and sex (females and males) and test whether different dispersal properties are phylogenetically conserved. </li> <li>We standardised and analysed data from an extensive volunteer-based bird ring-recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the different age and sex-specific dispersal kernels for each bird species. </li> <li>The dispersal movements of the 234 European bird species analysed were statistically best explained by heavy-tailed kernels, meaning that while most individuals disperse over short distances, long-distance dispersal is a prevalent phenomenon in almost all bird species. The phylogenetic signal in both median and long dispersal distances estimated from the best-fitted kernel was low (Pagel’s λ < 0.25), while it reached high values (Pagel’s λ >0.7) when comparing dispersal distance estimates for fat-tailed dispersal kernels. As expected in birds, natal dispersal was on average 5 km greater than breeding dispersal, but sex-biased dispersal was not detected.</li> <li>Our robust analytical framework allows sound use of widely available mark-recapture data in standardised dispersal estimates. We found strong evidence that long-distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events. </li> </ol> <p><strong>Content</strong></p> <ul> <li>The workflow for estimating dispersal kernels from ring-recovery data for all of Europe</li> <li>The code to develop the dispersal kernels with ring-recovery data. </li> <li>Dispersal distances for European birds: <a href="/api/files/0afdcc68-9a21-4e61-b8ff-9eb74f3c0d70/Table_S14_ species_dispersal_distances_v1_0_2.csv?versionId=1e3c628b-88c0-4b20-aad7-a5bf06e21bec">Table_S14_ species_dispersal_distances_v1_0_2.csv</a></li> <li>Dispersal kernel parameters for European birds: <a href="/api/files/0afdcc68-9a21-4e61-b8ff-9eb74f3c0d70/Table_S13_species_dispersal_parameters_v1_0_2.csv?versionId=195bd982-9d5e-47a1-b7d8-cf5a101f3603">Table_S13_species_dispersal_parameters_v1_0_2.csv</a></li> </ul>
Simulated Photon-Matter interaction of 3fs 4.96 keV European XFEL pulses with 2NIP
<p>Simulated photon-matter interaction trajectories for x-ray pulses from SASE1 beamline at European XFEL with a protein (pdb entry 2NIP).</p> <p>Input: https://dx.doi.org/10.5281/zenodo.884873 (WPG coherent wavefront propagation)</p> <p>Simulation Code: The PMI simulation was run with the code XMDYN, x-ray cross sections and transitions rates were calculated with XATOM. Both codes are developed at Center for Free Electron Laser Science, Theory Division, DESY, Hamburg, Germany.</p>
WPGed XPD 3fs, 4.96 keV pulses European XFEL SASE1 SPB-SFX
<p>Propagated pulses of 3 fs duration and 4.96 keV photon energy.</p> <p>Input (XFEL source): (per XPD https://in.xfel.eu/xpd) [https://dx.doi.org/10.5281/zenodo.855301]</p> <p>Simulation code: WPG</p>
Regional Datasets for Air Quality Monitoring in European Cities
<p>The primary environmental health threat in the WHO European Region is air pollution, impacting the daily health and well-being of its citizens significantly. To effectively understand the impact, and dynamics of air quality a detailed investigation of different environmental, weather, and land cover indices is appropriate. To this end, this paper introduces three European cities’ spatiotemporal datasets, customized for air pollution monitoring at a regional level. The datasets are composed of major air quality, weather measurements and land use information. The duration is approximately from 2020 to 2023 with an hourly temporal resolution and a spatial resolution of 0.005◦. The temporal and spatiotemporal datasets are publicly released aiming to provide a solid foundation for researchers, analysts, and practitioners to conduct in-depth analyses of air pollution dynamics.</p>
Supplementary material for 'Revealing patterns of nocturnal migration using the European weather radar network'
<p>This package contains data, filters and visualizations from <a href="https://doi.org/10.1111/ecog.04003">Nilsson and Dokter et al. (2019)</a>.</p> <p><strong>Files</strong></p> <p><strong>radar_metadata.csv</strong>: Metadata for the 84 European radars considered for this study. Includes radar code (<code>odim_code</code> = <code>country</code> + <code>odim_code_3char</code> and alternative radar code <code>vp_radar</code>), radar site location (<code>location</code>, <code>latitude</code>, <code>longitude</code>), radar site elevation (<code>site_altitude_asl</code> in meters above sea level) and radar altitude range used in this study (<code>min_height_cut_asl</code> and <code>max_height_cut_asl</code> in meters above sea level).</p> <p><strong>vp.zip</strong>: Vertical profiles of birds (vp) data, processed from the radar volume data following procedures described by Dokter et al. (2011), using the vol2bird algorithm in the R package bioRad. Zip file includes vp data for the 84 European radars considered for this study from September 19 to October 9, 2016 (21 days). This time period is characterized by strong passerine migration throughout Europe. Files are organized in radar (= <code>odim_code</code>), date and hour directories and follow the <a href="https://github.com/adokter/vol2bird/wiki/ODIM-bird-profile-format-specification">ODIM bird profile format specification</a>. Data can be read with the <a href="https://github.com/adokter/bioRad/">R package bioRad</a>.</p> <p><strong>vp_processing_settings.yaml</strong>: Data selection setting for this study, based on data quality criteria. File lists for each radar the altitudes to include (<code>include_heights</code>), time periods to exclude (<code>exclude_datetimes</code>) and reasons for exclusion (comments). 70 of the 84 radars were retained after filtering.</p> <p><strong>vp_processed_70_radars_20160919_20161009.csv</strong>: Processed vp data for 70 radars. Is the result of processing <code>vp.zip</code> with <code>vp_processing_settings.yaml</code> and <code>radar_metadata.csv</code> using <a href="https://doi.org/10.5281/zenodo.1173544">vp-processing</a> (Desmet & Nilsson 2018). Note: includes all timestamps: day and night & those marked for exclusion (marked in <code>exclusion_reason</code>). This data file forms the basis for analysis in the study.</p> <p>Headers are:</p> <ul> <li><code>radar_id</code>: odim_code of the radar</li> <li><code>datetime</code>: timestamp</li> <li><code>HGHT</code>: lower altitude of altitude bin (m above sea level)</li> <li><code>u</code>: bird ground speed towards east (m/s)</li> <li><code>v</code>: bird ground speed towards north (m/s)</li> <li><code>dens</code>: bird density (birds/km3)</li> <li><code>dd</code>: bird flight direction (degrees from north)</li> <li><code>ff</code>: bird ground speed (m/s)</li> <li><code>DBZH</code>: reflectivity factor (dBZ) in horizontal polarisation</li> <li><code>mtr</code>: migration traffic rate (birds/km/h)</li> <li><code>day_night</code>: timestamp occurs during <code>day</code> or <code>night</code> (based on sunrise/sunset)</li> <li><code>date_of_sunset</code>: date at sunset, with night timestamps between midnight and sunrise belonging to the previous date</li> <li><code>exclusion_reason</code>: reason timestamp is excluded in vp_processing_settings.yaml (if applicable). Excluded timestamps have <code>NA</code> values for <code>u</code>, <code>v</code>, <code>dens</code>, <code>dd</code>, <code>ff</code>, <code>DBZH</code>, and <code>mtr</code>.</li> </ul> <p><strong>vp_flowviz.csv:</strong> Input data for visualizations. Is the result of processing <code>vp_processed_70_radars_20160919_20161009.csv</code> using <code>vp-to-flowviz.Rmd</code> in <a href="https://doi.org/10.5281/zenodo.1173544">vp-processing</a> (Desmet & Nilsson 2018). Aggregates data in hourly bins for 200-2000m (<code>altitude_band</code> = 1) and above (<code>altitude_band</code> = 2). Only altitude band 1 is used in visualizations.</p> <p><strong>flowviz.mov:</strong> Screencast of <code>vp_flowviz.csv</code> visualized with <a href="https://doi.org/10.5281/zenodo.57472">Bird migration flow visualization v2</a> (Desmet et al. 2016, Shamoun-Baranes et al. 2016). The visualization extrapolates the migration over the entire sampling range (cropped in the screencast due to technical limitations and thus excluding the Bulgarian radar), not taking topography or water bodies into account, and shows the ground speed (length of arrows) and direction of migration over time. Note that density is not shown: low density movements can therefore appear as strong as high density movements when ground speeds are similar.</p> <p><strong>cartoviz.mov:</strong> Screencast of <code>vp_flowviz.csv</code> visualized as an interactive map with <a href="https://carto.com">CARTO</a>. Visualization shows migration density (size of circles) and mean direction (colour) over time. The interactive map is available at <a href="https://inbo.carto.com/u/lifewatch/builder/8685140f-8d8c-4d06-9e1e-25d051d43748/embed">https://inbo.carto.com/u/lifewatch/builder/8685140f-8d8c-4d06-9e1e-25d051d43748/embed</a>.</p>
An acoustically isolated European starling song library
<p>A dataset of song collected from 14 European starlings individually recorded in acoustically isolated chambers. Each folder contains vocalizations for one bird.</p> <p>These data were used for the publication, "<em>Parallels in the sequential organization of birdsong and human speech</em>". Nature Communications (2019). If you use this dataset, please cite this publication and this repository.</p> <p>Work supported by NSF Graduate Research Fellowship 2017216247 to TS and an NIH R56DC016408 to TQG.</p>
Projected fresh water use from the European energy sector on NUTS2 level by 2050 following EU Energy Reference Scenario 2016
<p>The dataset contains projections of fresh water withdrawal and consumption from the European energy sector on NUTS2 level by 2050 following EU Energy Reference Scenario 2016.</p> <p>The energy sector in this scope includes energy production (production of coal, oil and gas) and energy transformation in oil refineries and power plants (nuclear, solid fuels, oil, gas, biomass and geothermal).</p> <p>The information in provided on NUTS 2 level following the NUTS2 2013 definition.</p> <p>The dataset is explained in more detail in the report <a href="https://ec.europa.eu/jrc/en/publication/projected-fresh-water-use-european-energy-sector">Projected fresh water use from the European energy sector</a>.</p>
S54 | EFSAPRI | European Food Safety Authority Priority Substances
<p>This is the dataset associated with list S54 EFSAPRI on the NORMAN Suspect List Exchange:</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p>
A European aerosol phenomenology – 9: LIGHT ABSORPTION PROPERTIES OF CARBONACEOUS AEROSOL PARTICLES ACROSS SURFACE EUROPE
<p>Carbonaceous aerosols (CA), composed of black carbon (BC) and organic aerosols (OA), exert an important role on the climate system through their interaction with solar radiation. Light absorption properties of CA particles are of special interest due to their important contribution to global and regional warming. Among atmospheric particulate matter (PM), BC and the absorbing components of OA (or brown carbon, BrC) are characterized by the highest absorption efficiency but their role in the current climate change, especially that of BrC, is still uncertain. Here we present the absorption properties of BC and BrC PM at 44 sites across Europe using aethalometer data collected at different types of environment (6 traffic (TR), 16 urban (UB), 7 suburban (SUB), 10 regional background (RB) and 5 mountain (M) sites). The absorption Ångström exponent (AAE) method was used to assign total measured absorption to the contributions of BC (bAbs,BC) and BrC (bAbs,BrC) to total absorption (bAbs). The results showed a clear dependence of the absorption coefficients bAbs, bAbs,BC and bAbs,BrC on station settings as follows: TR > UB > SUB > RB > M, even if significant exceptions were observed. The relative contribution of bAbs,BrC to bAbs (%AbsBrC) at 370 nm was on average lower at traffic sites (11-20%) reaching at some SUB and RB sites median annual values that accounted for more than 30% and 10% of the absorption at 370 and 660 nm, respectively. The median AAE of CA particles was correspondingly low at TR sites (1.1-1.2) where internal combustion engines dominated the CA mass concentration. Low AAE were also observed at some remote RB and M sites, likely due to the lack of proximity from BrC sources or lack of sufficiently strong secondary processes resulting in BrC. On average, AAE was lower in Western Europe (<1.3) compared to Eastern Europe (>1.3), likely due to a more extensive use of coal and biomass burning in eastern countries. The median AAE of BrC PM (AAEBrC) showed a wide range of values, from 2.5 to 6, with no clear relationship with station background or region. Assessing the seasonal variability revealed, overall, an increase of bAbs, bAbs,BC, bAbs,BrC in winter, which was attributed to meteorological conditions and more heating related emissions. Accordingly, bAbs,BrC exhibited a stronger increase than bAbs,BC, resulting in higher AAE and %AbsBrC during the winter season. The diel cycles differed between bAbs,BC and bAbs,BrC, with bAbs,BC showing the bimodal peaks during the morning and evening rush hours, whereas bAbs,BrC, together with %AbsBrC, AAE and AAEBrC, peaked at night. Decade-long trend analysis performed for a subset of stations across Europe revealed a decrease of bAbs, driven by declining bAbs,BC, whereas, overall, bAbs,BrC, %AbsBrC and AAE increased with time. This strongly implies an efficient reduction of BC mass concentrations from traffic sources in Europe and a less effective reduction of emissions from BrC sources. The observed increasing trends of AAE reflected a progressive change in the chemical composition of CA particles driven by a relative increase/decrease of BrC/BC content in CA with time.</p>
From waste to value: Recovering critical raw materials from urban mines in the European Union and the United States
<p><strong>Submitted data was used to write an article: </strong>Jędrusiak, R., Bielowicz, B., Drobniak, A., 2023, From waste to value: Recovering critical raw materials from urban mines in the European Union and the United States, Mineral Resource Management 39 (3), 43-63. <a href="https://doi.org/10.24425/gsm.2023.147557">https://doi.org/10.24425/gsm.2023.147557</a></p> <p> </p> <p><strong>Funding acknowledgments: </strong>Agnieszka Drobniak contribution comes from the support of the Polish National Agency for Academic Exchange within the Polish Returns Programme (BPN/PPO/2021/1/00005/DEC/1), and the National Science Center, Poland (2022/01/1/ST10/00024). This research was funded by the Ministry of Science and Higher Education of Poland (subsidies no. 16.16.140.315).</p> <p> </p> <p><strong>Article Abstract: </strong>Modern human consumption, rapid urbanization and further increases in the world’s population lead to the demand for more goods and materials. However, after utilization, only some of these materials are recovered or recycled, many are discarded due to a lack of implemented recovery technologies and regulations, or due to the content of contaminants. Moreover, many of the potentially recoverable materials are deposited in landfills or shipped to less developed countries for disposal where they can cause environmental contamination. The new approach to waste management follows the hierarchy of waste prevention. First, waste is prepared for reuse and repair without the need for treatment processes, or it is recycled. If this is not possible, the waste is incinerated with energy recovery, or failing that, it is disposed of in landfills. This waste hierarchy has become one of the key factors in the transformation of a linear economy into a circular economy. Particularly noteworthy is waste containing raw materials of significant economic importance, especially those of a high supply risk due to the level of concentration in another country and import dependence. These critical raw materials (CRM) are an inherent part of our modern, technology-driven life. They are essential to national security and the economic development of every country. Their use is drastically increasing, and with it, the need to assure their reliable and unrestricted access along with lowering the environmental impact from their production and extraction. Currently, scientists and industry direct a lot of effort into finding new supplies of these materials, not only from traditional sources in nature but also from new sources like anthropogenic waste. The purpose of this study is to present the raw material potential which remains mostly unused in residues from municipal waste incineration in regions with highly developed economies – the United States and the European Union. These economies have shortages of their own raw material extraction capacity due to high levels of consumption and insufficient amounts of raw-material content in natural resources.</p>
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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