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Average travel time to the nearest hospital in minutes – excluding hospitals in potential flood-prone areas, 2020

This metadata refers to the vector dataset presenting, for NUTS3 regions, the average travel time to the nearest hospital in 2020, excluding hospitals located in the EEA potential flood-prone areas (https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/28c36420-c31b-440e-80c5-8064696f3517). 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 and the location of hospitals in the EEA potential flood-prone areas. Note that the accessibility could have been calculated 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.

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/

Exposure to climate hazards

This series refers to datasets related to the presence of people; livelihoods; species or ecosystems; environmental functions, services, and resources; infrastructure; or economic, social, or cultural assets in places and settings that could be adversely affected by climate hazards, including flooding, wildfires and urban heat island effects. The datasets are part of the European Climate Adaptation Platform (Climate-ADAPT) accessible here: https://climate-adapt.eea.europa.eu/

Bathing Water Directive - Status of bathing water

The EU Bathing Waters Directive requires Member States to identify popular bathing places in fresh and coastal waters and monitor them for indicators of microbiological pollution (and other substances) throughout the bathing season which runs from May to September

Air Quality Health Risk Assessments (NUTS3 and countries)

This data set presents health risk calculation of exposure to three main pollutants (PM2.5, NO2 and O3) and information on PM10 concentrations at NUTS3, country and city levels. In addition, average and population weighted average concentration values are available in the data set for PM10, PM2.5, NO2 and O3 (SOMO35). The calculations are made for years 2005 to 2020. The concentrations data are taken from the ETC/ATNI interpolated maps (ETC/ATNI Eionet Reports 1/2020/ and 1/2021 and references therein). The methodology is as described in ETC/ATNI Eionet Report 10/2021, aggregating at country level.

Nuklearmedizinische Entwicklung

Im Institut fuer Medizin (IME) erfolgt die Untersuchung des Verhaltens von Spurenelementkonzentrationen in menschlichen Koerperfluessigkeiten in Antwort auf unterschiedliche Belastungen (koerperliche Arbeit, Ernaehrung, Medikamente) unter besonderer Beruecksichtigung spezieller Organleistungen wie z.B. Bauchspeicheldruese, zur Verbesserung der klinischen Diagnostik. - Messung der genetisch bedingten und umweltbedingten Spurenelementkonzentrationsaenderungen in Saeugetierorganen und Korrelation zu verschiedenen Erkrankungen.

Climatic suitability index modelling for tiger mosquito (Aedes albopictus)

This raster dataset provides the modelling of the climate suitability index values (0-100%) for tiger mosquito (Aedes albopictus) for European cities. Aedes Albopictus has become a common occurrence in Southern Europe and transmits diseases such as Zika, dengue and chikungunya. The climatic suitability for tiger mosquito depends on factors such as sufficient amounts of rainfall, high summer temperatures and mild winters. Climate change is anticipated to further facilitate the spread of tiger mosquitoes across Europe by changing temperature and precipitation patterns, thereby increasing the suitable habitat.

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).

Climatic suitability index modelling for tiger mosquito (Aedes albopictus) 2008-2009, Jan. 2020

This raster dataset provides the modelling of the climate suitability index values (0-100%) for tiger mosquito (Aedes albopictus) for 100 European cities for the years 2008-2009, with a resolution of 100 m. Aedes Albopictus has become a common occurrence in Southern Europe and transmits diseases such as Zika, dengue and chikungunya. The climatic suitability for tiger mosquito depends on factors such as sufficient amounts of rainfall, high summer temperatures and mild winters. Climate change is anticipated to further facilitate the spread of tiger mosquitoes across Europe by changing temperature and precipitation patterns, thereby increasing the suitable habitat. In the framework of the Copernicus Climate Change Service (C3S) SIS European Health, VITO has provided to the Climate Data Store 100m resolution hourly temperature data for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). From this dataset, this climate suitability dataset has been generated based on annual precipitation and the average temperature in January and during the summer period (months June, July and August) for the years 2008-2009, following the methodology by European Centre for Disease Prevention and Control (ECDC, 2009). The 100 European cities for the urban simulations were selected based on user requirements within the health community.

Urban Morphological Zones Changes 1990-2000 (vector) - version 16, Jun. 2013

Changes between UMZs in 1990 and UMZs in 2000 using CLC version 16. Most changes are Positive changes, understood as areas of urban sprawl (i.e. new UMZ areas between 1990 and 2000), while negative changes describe the reduction of a certain UMZ between 1990 and 2000 (warning: some negative changes might be due to different interpretations between 1990-2000).

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