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GISCO - Nomenclature of Territorial Units for Statistics 2021 (NUTS 2021), May 2021

The 'GISCO NUTS 2021' data set represents the NUTS 2021 regulation and statistical regions by means of multipart polygon, polyline and point topology. The NUTS geographical information is completed by attribute tables and a set of cartographic help lines to better visualize multipart polygonal regions. The NUTS nomenclature is a hierarchical classification of statistical regions defined by Eurostat. The NUTS classification subdivides the EU economic territory into 3 statistical levels. The NUTS 2021 classification has been established through the Commission Delegated Regulation 2019/1755, which entered into force on 8th August 2019 and applies from 1st January 2021. A non official NUTS-like classification has been defined for the EFTA countries and the candidate countries. At present, six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are maintained in the GISCO geodatabase. The polygon and boundary classes delineate the regions, while the points provide an anchor for each region. Associated tables contain basic information such as the name of the region. The public data set will be available at 1M, 3M, 10M, 20M, 60M, while the full data set at 100K is restricted. The data set covers EU Member States, EFTA countries, EU candidate countries and the UK. Following the departure of the UK from the European Union, the UK is no longer flagged as an EU Member State but retains its place in the NUTS and statistical regions data set. This dataset (NUTS_2021) is derived from the EuroBoundary Map 2020 (EBM2020) from Eurogeographics as well as GISCO NUTS 2016 (from Türkiye). The list of NUTS2021 codes including changes with respect to NUTS2016 is available on https://ec.europa.eu/eurostat/documents/345175/629341/NUTS2021.xlsx. The public metadata for NUTS 2021 released by Eurostat is available here: https://gisco-services.ec.europa.eu/distribution/v2/nuts/nuts-2021-metadata.xml. This revision (May 2021) includes minor changes in the dataset such as (see https://gisco-services.ec.europa.eu/distribution/v2/nuts/nuts-2021-release-notes.txt): * 2020-10-05 Point snapping is disabled in all datasets, number of decimals increased for 01M datasets. * 2020-11-18 Inclusion of Jan Mayen and Svalbard in to Norways Statistical Regions. Amendment to Serbia NUTS BN line status. * 2020-12-05 Fixed broken utf-8 encoding. * 2021-03-15 Added LAU 2011,2012,2013,2014,2015,2020 * 2021-04-26 Fixed country labels 2001, 2006 (incorrect Kosovo coordinates) IMPORTANT NOTE: Additional information, including the conditions of use and acknowledgement notice is included in the document provided with the dataset "GISCO NUTS 2021 Additional Information.pdf". Public access to this data set is restricted due to intellectual property rights. It shall only be used internally by the EEA, its ETCs and subcontractors working on behalf of the EEA. This metadata has been slightly adapted from the original metadata information provided by Eurostat (European Commission) and is to be used only for internal EEA purposes. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview.

Climate related hazards

This series refers to datasets related to the potential occurrence of a climate-induced physical event or trend that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, ecosystems and environmental resources. It includes datasets on flooding, drought, urban heat island and heatwaves, extreme temperatures and precipitations, fire danger as well as climate suitability for vectors of infectious diseases. The datasets are part of the European Climate Adaptation Platform (Climate-ADAPT) accessible here: https://climate-adapt.eea.europa.eu/

Model Output Statistics for LINTON-ON-OUSE (03266)

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

Noise data reported under Environmental Noise Directive (END)

The datasets includes 1) the noise exposure data, 2) the noise contours data, 3) razterized noise contours data and 4) potential quiet areas all under the terms of the Environmental Noise Directive (END). Data covers the EEA32 member countries and the United Kingdom (excluding Turkey for the third round of noise mapping in 2017).

Quantitative und qualitative Bewertung unterschiedlicher Systeme für die Erfassung von Altpapier

Tendenzen am internationalen Altpapiermarkt lassen befürchten, dass die zukünftig von der europäischen Papierindustrie benötigten Altpapiermengen nicht in der erforderlichen Menge und in der gewohnten Qualität zur Verfügung stehen und dass sich diese Entwicklung negativ auf die Wirtschaftlichkeit des Altpapiereinsatzes auswirkt. Vor diesem Hintergrund gewinnt die Erschließung nationaler Reserven für das Aufkommen an Altpapier in den Ländern der Europäischen Gemeinschaft einen höheren Stellenwert. Während in Deutschland mit 75 Prozent die weltweit höchste Rücklaufquote von Altpapier erreicht wurde, liegt diese Kennziffer in Ländern mit einem hohen Papierverbrauch wie Großbritannien, Italien, Frankreich und Spanien derzeit lediglich zwischen 47 und 54 Prozent. Durch die Einführung geeigneter Sammelsysteme kann sowohl Einfluss auf die Menge als auch auf Qualitätsparameter des erfassten Altpapiers genommen werden. Dies trägt zur Senkung der Sortierkosten bei. Ziel des Projektes ist eine Leistungsbewertung von Systemen zur Erfassung von Altpapieren aus haushaltnahen Anfallstellen in Deutschland. Durch die Projektbearbeitung werden Kennziffern für die realisierbaren Erfassungsmengen und die stoffliche Zusammensetzung der erfassten Altpapiere (grafische Altpapiere, sonstige Altpapiere, papierfremde Bestandteile) in Abhängigkeit von der Besiedlungsstruktur der Entsorgungsgebiete ermittelt und miteinander verglichen. Weiterhin wird untersucht, ob Sammelsystem und Besiedlungsstruktur unterschiedliche Einflüsse auf ausgewählte technologische Gebrauchswerteigenschaften der erfassten Altpapiere ausüben. Die Effizienz der Erfassungssysteme und die Qualität des dort erfassten Altpapiers werden bewertet. Daraus können Empfehlungen für Steigerungsmöglichkeiten abgeleitet werden.

Economic/Climate Recovery Scorecards

As global leaders head to the G20 summit to consider solutions to the current global economic crisis, a new report prepared by Ecofys and Germanwatch for WWF and E3G reveals that many of the economic recovery packages being discussed are a missed opportunity in terms of stimulating a green recovery, and actually run the risk of locking the world into a high-carbon future. The report provides the most detailed and comprehensive analysis to date of the proposed 'stimulus' packages of five key countries - France, Germany, Italy, the UK and the US - as well as the package agreed by the European Union as a whole.

Waterbase - UWWTD: Urban Waste Water Treatment Directive – reported data

The Urban Waste Water Treatment Directive concerns the collection, treatment and discharge of urban waste water and the treatment and discharge of waste water from certain industrial sectors. The objective of the Directive is to protect the environment from the adverse effects of the above mentioned waste water discharges. This series contains time series of spatial and tabular data covering Agglomerations, Discharge Points, and Treatment Plants.

Microbial community composition in fresh water at different stations

Fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes was used to investigate the phylogenetic composition of bacterioplankton communities in several freshwater and marine samples. An average of about 50% of the cells were detected by probes for the domains Bacteria and Archaea. Cells were concentrated from water samples (1 to 100 ml) on white polycarbonate filters (diameter, 47 mm; pore size, 0.2 mm; type GTTP 4700 [Millipore, Eschborn, Germany]) by applying a vacuum of <25 kPa. They were subsequently fixed by covering the filter with 3 ml of a freshly prepared, phosphate-buffered saline (pH 7.2)-4% paraformaldehyde (Sigma, Deisenhofen, Germany) solution for 30 min at room temperature. Airdried filters are ready for hybridization and can be stored at 220°C or room temperature for several months without showing apparent changes. Probes BET42a, GAM42a, and PLA886 were used with competitor oligonucleotides as described previously amongst others in Manz et al., (1992; doi:10.1016/S0723-2020(11)80121-9). The filters were transferred to a vial containing 50 ml of prewarmed (48°C) washing solution (70 mM NaCl, 20 mM Tris-HCl [pH 7.4], 5 mM EDTA, 0.01% sodium dodecyl sulfate) and incubated freely floating without shaking at 48°C for 15 min. The filter sections were dried on Whatman 3M paper (Whatman Ltd., Maidstone, United Kingdom) and covered with 50 ml of DAPI solution (1 mg/ml in distilled water filtered through at 0.2-mm filter) for 5 min at room temperature in the dark. For each sample and probe, more than 500 cells were enumerated; for the DAPI examination, more than 1,500 cells were counted per sample. All probe-specific cell counts are presented as the percentage of cells visualized by DAPI. The mean abundances and standard deviations were calculated from the counts of 10 to 20 randomly chosen fields on each filter section. All counts were corrected by subtracting the counts obtained with the negative control NON338. Mean and standard deviation were calculated from the counts of 10 to 20 randomly chosen fields on each filter section.

Geographic Information System of the European Commission (GISCO)

This metadata refers to the whole content of GISCO reference database, which contains both public datasets (also available for the general public through http://ec.europa.eu/eurostat/web/gisco/geodata) and datasets to be used only internally by the EEA (typically, but not only, GISCO datasets at 1:100k).

WISE WFD Protected Areas under the Water Framework Directive

The WISE WFD protected areas data set contains the location of areas which have been designated as requiring special protection of their surface water and groundwater, or for the conservation of habitats and species directly depending on water, including economically significant aquatic species (e.g. shellfish). According to the Article 6 of the Water Framework Directive (WFD, Directive 2000/60/EC), Member States shall ensure the establishment of a register of all areas lying within each River Basin District which have been designated as requiring special protection under specific Community legislation for the protection of their surface water and groundwater, or for the conservation of habitats and species directly depending on water, including the protection of Natura 2000 sites and economically significant aquatic species (e.g. shellfish).

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