The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 2nd River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the above mentioned surface water bodies and groundwater bodies. The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. See also https://rod.eionet.europa.eu/obligations/766 for information on the Environmental Quality Standards Directive - Preliminary programmes of measures and supplementary monitoring. Where available, spatial data related to the 3rd RBMPs due in 2022 (hereafter WFD2022) was used to update the WFD2016 data. See https://rod.eionet.europa.eu/obligations/780 for further information on the WFD2022 reporting.
Wandernde Westwinde und warmes Tiefenwasser sind die treibenden Kräfte hinter dem zunehmenden Eismassenverlust in der Westantarktis. Zu diesem Ergebnis kommt ein internationales Geologenteam, dessen Studie am 5. Juli 2017 im Fachmagazin Nature erschienen ist. Die Wissenschaftler aus Deutschland, Großbritannien, Dänemark und Norwegen hatten mit Hilfe von Sedimentkernen das Zusammenspiel von Ozean und Eisströmen im Amundsenmeer für die zurückliegenden 11.000 Jahre rekonstruiert und deutliche Parallelen zwischen den aktuellen Ereignissen und großen Eisverlusten vor mehr als 7500 Jahren entdeckt. Die neuen Daten sollen nun helfen, die zukünftige Entwicklung des Westantarktischen Eisschildes besser vorherzusagen. Mit ihren neuen Erkenntnissen füllen die Wissenschaftler eine entscheidende Lücke in der Klima- und Eismodellierung. Für ihre Studie hatten die Wissenschaftler Sedimentkerne analysiert, die im Jahr 2010 auf einer Expedition des deutschen Forschungseisbrechers Polarstern in die Pine Island-Bucht des Amundsenmeeres geborgen worden waren. Die Bodenproben enthielten Überreste winziger Meeresorganismen, sogenannter Foraminiferen. Der geochemische Fingerabdruck ihrer Kalkschalen erlaubt Rückschlüsse auf die Umweltbedingungen zu Lebzeiten der Tiere. Auf diese Weise gelang es den Forschern, die Temperatur-, Strömungs- und Eisverhältnisse im Amundsenmeer für die zurückliegenden 11.000 Jahre zu rekonstruieren. Die in das Amundsenmeer mündenden Gletscher und Eisströme verlieren inzwischen so viel Eis, dass sie allein zehn Prozent des globalen Meeresspiegelanstieges verursachen. Weltweite Aufmerksamkeit erregen vor allem der Pine Island-Gletscher und der Thwaites-Gletscher. Beide haben ihr Fließtempo und ihre Rückzugsraten in den vergangenen Jahrzehnten enorm gesteigert. Zusammen genommen speichern die Eisströme der Region so viel Eis, dass sie im Falle ihres Abschmelzens den Meeresspiegel um 1,2 Meter ansteigen lassen könnten.
This metadata refers to the vector data covering 100 cities in Europe in 2021, for which Urban Heat Island modelling is available, the percentage of educational facilities that are located within the extent of urban heat island of 2 degrees Celsius or more than the regional average. The Urban Heat Island intensity exacerbates high temperatures in cities and thus may pose additional risks to human thermal comfort and health. Urban heat island (UHI) is an urban or metropolitan area that is significantly warmer than its surrounding rural areas due to human activities. The temperature difference is usually larger at night than during the day, and is most apparent when winds are weak. UHI is most noticeable during the summer and winter. The main cause of the UHI effect is from the modification of land surfaces. The data is included in the European Climate and Health Observatory: https://climate-adapt.eea.europa.eu/observatory. The European Climate and Health Observatory platform provides easy access to a wide range of relevant publications, tools, websites and other resources related to climate change and human health.
The raster dataset of urban heat island modelling shows the fine-scale (100m pixel size) temperature differences (in degrees Celsius °C) across 100 European cities, depending on the land use, soil sealing, anthropogenic heat flux, vegetation index and climatic variables such as wind speed and incoming solar radiation. In the framework of the Copernicus European Health contract for the Copernicus Climate Change Service (C3S), VITO provided 100m resolution hourly temperature data (2008-2017) for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). As the cities vary in size, so do the model domains. They have been defined with the intention to have a more or less constant ratio of urban vs. non-urban pixels (as defined in the CORINE land use map), with a maximum of 400 by 400 pixels (due to computational restraints). From this data set, the average urban heat island intensity is mapped for the summer season (JJA), which is the standard way of working in the scientific literature (e.g. Dosio, 2016). The UHI is calculated by subtracting the rural (non-water) spatial P10 temperature value from the average temperature map. The 100 European cities for the urban simulations were selected based on user requirements within the health community.
This vector dataset shows the Urban Heat Island (UHI) intensity (in degrees Celsius °C) for 100 European cities, based on their elevation above sea level, land use, soil sealing, vegetation index and anthropogenic heat flux. The Urban Heat Island intensity exacerbates high temperatures in cities and thus may pose additional risks to human thermal comfort and health. The UHI intensity is represented by spatial P90 (90th percentile) urban heat island intensity of a given city ("P90" field in the dataset). This indicator is calculated by subtracting the rural (non-water) spatial P10 (10th percentile) temperature value from the average, height-corrected (to exclude terrain effects), air temperature map. This indicator represents the specific exposure of single cities and due to the height correction will be comparable across Europe. The dataset has been created by VITO within the Copernicus Health contract for C3S and is based on UrbClim model (De Ridder et al. 2015). The 100 European cities for the urban simulations were selected based on user requirements within the health community.
This metadata refers to the vector data covering 100 cities in Europe in 2021, for which Urban Heat Island modelling is available, the percentage of healthcare services (hospitals) that are located within the extent of urban heat island of 2 degrees or more than the regional average. The Urban Heat Island intensity exacerbates high temperatures in cities and thus may pose additional risks to human thermal comfort and health. Urban heat island (UHI) is an urban or metropolitan area that is significantly warmer than its surrounding rural areas due to human activities. The temperature difference is usually larger at night than during the day, and is most apparent when winds are weak. UHI is most noticeable during the summer and winter. The main cause of the UHI effect is from the modification of land surfaces. The data is included in the European Climate and Health Observatory: https://climate-adapt.eea.europa.eu/observatory. The European Climate and Health Observatory platform provides easy access to a wide range of relevant publications, tools, websites and other resources related to climate change and human health.
This metadata refers to the vector dataset presenting, for NUTS3 regions, the average travel time to the nearest hospital in 2020. The data has been developed by Eurostat to measure how easily basic services can be reached by the resident population, based on spatial analyses of the location of healthcare facilities, combined with the road network. (note this could have been across a national border). The data is included in the European Climate and Health Observatory: https://climate-adapt.eea.europa.eu/observatory. The European Climate and Health Observatory platform provides easy access to a wide range of relevant publications, tools, websites and other resources related to climate change and human health.
This metadata refer to the dataset presenting the annual change in the estimated West Nile Virus transmission risk between 1950 and 2020 by country. The risk varies between 0 (no risk) and 1 (very high risk). This indicator uses machine learning models incorporating WNV reported cases and climate variables (temperature, precipitation) to estimate WNV transmission probability. West Nile virus is a climate-sensitive multi-host and multi-vector pathogen. Human infection is associated with severe disease risk and death. In the past few decades, European countries have had a large increase in the intensity, frequency, and geographical expansion of West Nile virus outbreaks. The 2018 outbreak has been the largest yet, with 11 European countries reporting 1584 locally acquired infections. Increasing ambient temperatures are increasing the vectorial capacity of the Culex mosquito vector, and thus increasing the outbreak probability.
The new urban sprawl metric, named "Weighted Urban Proliferation“ (WUP) is based on the following definition of urban sprawl: the more area is built over in a given landscape (amount of built-up area) and the more dispersed this built-up area is in the landscape (spatial configuration), and the higher the uptake of built-up area per inhabitant or job (lower utilisation intensity in the built-up area), the higher the degree of urban sprawl. Weighted Urban Proliferation (WUP) metric has three components: the percentage of built-up areas (PBA), the dispersion of the built-up areas (DIS), and land uptake per person (LUP).
The service contains information about the ecological status or potential of European surface water bodies, delineated for the 2nd River Basin Management Plans (RBMP) under the Water Framework Directive (WFD). The Quality Element status is the poorest of the known quality element status values per water body. For example, the nutrient conditions status (QE3-1-6) is based on the following two quality elements: Nitrogen conditions (QE3-1-6-1) and Phosphorus conditions (QE3-1-6-2). The ecological status or potential is presented for the following quality elements: QE1 - Biological quality elements; QE1-1 - Phytoplankton; QE1-2 - Other aquatic flora; QE1-2-1 - Macroalgae; QE1-2-2 - Angiosperms; QE1-2-3 - Macrophytes; QE1-2-4 - Phytobenthos; QE1-3 - Benthic invertebrates; QE1-4 - Fish; QE2 - Hydromorphological quality elements; QE2-1 - Hydrological or tidal regime; QE2-2 - River continuity conditions; QE2-3 - Morphological conditions; QE3 - Chemical and physico-chemical quality elements; QE3-1 - General parameters; QE3-1-1 - Transparency conditions; QE3-1-2 - Thermal conditions; QE3-1-3 - Oxygenation conditions; QE3-1-4 - Salinity conditions; QE3-1-5 - Acidification status; QE3-1-6 - Nutrient conditions; QE3-1-6-1 - Nitrogen conditions; QE3-1-6-2 - Phosphorus conditions; QE3-3 - River Basin Specific Pollutants. The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. Relevant concepts: Surface water body: Body of surface water means a discrete and significant element of surface water such as a lake, a reservoir, a stream, river or canal, part of a stream, river or canal, a transitional water or a stretch of coastal water. Surface water: Inland waters, except groundwater; transitional waters and coastal waters, except in respect of chemical status for which it shall also include territorial waters. Inland water: All standing or flowing water on the surface of the land, and all groundwater on the landward side of the baseline from which the breadth of territorial waters is measured. River: Body of inland water flowing for the most part on the surface of the land but which may flow underground for part of its course. Lake: Body of standing inland surface water. Transitional waters: Bodies of surface water in the vicinity of river mouths which are partly saline in character as a result of their proximity to coastal waters but which are substantially influenced by freshwater flows. Coastal water: Surface water on the landward side of a line, every point of which is at a distance of one nautical mile on the seaward side from the nearest point of the baseline from which the breadth of territorial waters is measured, extending where appropriate up to the outer limit of transitional waters.
| Origin | Count |
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| Bund | 573 |
| Europa | 162 |
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| Wissenschaft | 5 |
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| Förderprogramm | 282 |
| Messwerte | 2 |
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| unbekannt | 323 |
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| Keine | 276 |
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