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Waterbase - Biology, 2024

Waterbase serves as the EEA’s central database for managing and disseminating data regarding the status and quality of Europe's rivers, lakes, groundwater bodies, transitional, coastal, and marine waters. It also includes information on the quantity of Europe’s water resources and the emissions from point and diffuse sources of pollution into surface waters. Specifically, Waterbase - Biology focuses on biology data from rivers, lakes, transitional and coastal waters collected annually through the Water Information System for Europe (WISE) – State of Environment (SoE) reporting framework. The data are expected to be collected within monitoring programs defined under the Water Framework Directive (WFD) and used in the classification of the ecological status or potential of rivers, lakes, transitional and coastal water bodies. These datasets provide harmonised, quality-assured biological monitoring data reported by EEA member and cooperating countries, as Ecological Quality Ratios (EQRs) from all surface water categories (rivers, lakes, transitional and coastal waters).

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).

Project OTC-Genomics: Environmental and microbial time series data from the Warnow estuary and the Baltic Sea coast

Estuaries and coasts are characterized by ecological dynamics that bridge the boundary between habitats, such as fresh and marine water bodies or the open sea and the land. Because of this, these ecosystems harbor ecosystem functions that shaped human history. At the same time, they display distinct dynamics on large and small temporal and spatial scales, impeding their study. Within the framework of the OTC-Genomics project, we compiled a data set describing the community composition as well as abiotic state of an estuary and the coastal region close to it with unprecedented spatio-temporal resolution. We sampled fifteen locations in a weekly to twice weekly rhythm for a year across the Warnow river estuary and the Baltic Sea coast. From those samples, we measured temperature, salinity, and the concentrations of Chlorophyll a, phosphate, nitrate, and nitrite (physico-chemical data); we sequenced the 16S and 18S rRNA gene to explore taxonomic community composition (sequencing data and bioinformatic processing workflow); we quantified cell abundances via flow cytometry (flow cytometry data); and we measured organic trace substances in the water (organic pollutants data). Processed data products are further available on figshare.

Industrial Emissions Directive 2010/75/EU and European Pollutant Release and Transfer Register Regulation (EC) No 166/2006 - ver. 15.0 Dec. 2025 (Tabular data)

This metadata refers to the geospatial dataset representing the status of the EEA Industrial Reporting database as of 15 December 2025 (version 15). The release and emissions data cover the period 2007-2024 as result of the data reported under the E-PRTR facilities, 2017-2024 for IED installations and WI/co-WIs, and 2016-2024 for LCPs. These data are reported to EEA under Industrial Emissions Directive (IED) 2010/75/EU Commission Implementing Decision 2018/1135 and the European Pollutant Release and Transfer Register (E-PRTR) Regulation (EC) No 166/2006 Commission Implementing Decision 2019/1741. The dataset brings together data formerly reported separately under E-PRTR Regulation Art.7 and under IED Art.72. Additional reporting requirements under the IED are also included.

SWIM Water Extent - Sentinel-1/2 - Daily

SWIM Water Extent is a global surface water product at 10 m pixel spacing based on Sentinel-1/2 data. The collection contains binary layers indicating open surface water for each Sentinel-1/2 scene. Clouds and cloud shadows are removed using ukis-csmask (see: https://github.com/dlr-eoc/ukis-csmask ) and are represented as NoData. The water extent extraction is based on convolutional neural networks (CNN). For further information, please see the following publications: https://doi.org/10.1016/j.rse.2019.05.022 and https://doi.org/10.3390/rs11192330

INSPIRE: Geoscientific Map of Germany 1:2,000,000 - Geology (GK2000 Geologie)

The GK2000 Geologie (INSPIRE) represents the surface geology of Germany on a scale of 1:2,000,000. According to the Data Specification on Geology (D2.8.II.4_v3.0) the content of the geological map is stored in three INSPIRE-compliant GML files: GK2000_Geology_GeologicUnit.gml contains the geologic units, GK2000_Geology_GeologicStructure.gml comprises the faults and GK2000_Geology_GeomorphologicFeature.gml represents the marginal position of the ice shield as well as the impact craters Nördlinger Ries and Steinheimer Becken. The GML files together with a Readme.txt file are provided in ZIP format (GK2000_Geologie-INSPIRE.zip). The Readme.text file (German/English) contains detailed information on the GML files content. Data transformation was proceeded by using the INSPIRE Solution Pack for FME according to the INSPIRE requirements.

Kilimanjaro Glaciers (East Africa)

The Tropical Glaciology Group's research on Kilimanjaro started in 2002 and is in progress. Central aspects of our research plan are: 1) Development of the working hypothesis: From a synopsis of (i) proxy data indicating changes in East African climate since ca. 1850, (ii) 20th century instrumental data (temperature and precipitation), and (iii) the observations and interpretations made during two periods of fieldwork (June 2001 and July 2002) a scenario of modern glacier retreat on Kibo is reconstructed. This scenario offers the working hypothesis for our project. 2) Impact of local climate on the glaciers: This goal involves micrometeorological measurements on the glaciers, and the application of collected data to full glacier energy and mass balance models. These models quantify the impact of local climate on a glacier, based on pure physical system knowledge. Our models are validated by measured mass loss and surface temperature. 3) Latest Extent of the Kilimanjaro glaciers: Here, a satellite image was analyzed to derive the surface area and spatial distribution of glaciers on Kilimanjaro in February 2003. To validate this approach, an aerial flight was conducted in July 2005. 4) Linking local climate to large-scale circulation: As glacier behavior on Kilimanjaro, a totally free-standing mountain, is likely to reflect changes in larger-scale climate, this goal explores the large-scale climate mechanisms driving local Kilimanjaro climate. Well known large-scale forcings of east African climate are sea surface temperature variations in the Pacific and, more important, in the Indian Ocean. 5) Regional modification of large-scale circulation: The regional precipitation response in East Africa due to large-scale forcing is not adequately resolved in a global climate model as used in 4). Thus, mesoscale model experiments with the numerical atmospheric model RAMS will be conducted within this goal. They are thought to reveal the modification of atmospheric flow by the Kilimanjaro massif on a regional scale. 6) Practical aspects: Based on micro- and mesoscale results, (i) how much water is provided by glaciers, (ii) providing future projections of glacier behavior as basis for economic and societal studies (practical part), e.g., for studies on the impact of vanishing glaciers on Kibo's touristic appeal, and (iii) which impact does deforestation on the Kilimanjaro slopes have on summit climate? Referring to item 2), two new automatic weather stations have been installed in February 2005. They complete a station operated by Massachusetts University on the surface of the Northern Icefield since 2000.

GTS Bulletin: IUPD43 EDZW - Observational data (Binary coded) - BUFR (details are described in the abstract)

The IUPD43 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IU): Upper air T1T2A1 (IUP): Profilers A2 (D): 90°E - 0° northern hemisphere(The bulletin collects reports from stations: 10169;Rostock (ROS);) (Remarks from Volume-C: DUAL-POLARIZATION RADAR DATA OF ROSTOCK)

GTS Bulletin: PAGJ51 EDZW - Pictorial information (Binary coded) (details are described in the abstract)

The PAGJ51 TTAAii Data Designators decode as: T1 (P): Pictorial information (Binary coded) T1T2 (PA): Radar data (The bulletin collects reports from stations: 10410;Essen-Bredeney;) (Remarks from Volume-C: RADAR SWEEPS DATA, 10 ELEVATION ANGELS)

GTS Bulletin: PAGF51 EDZW - Pictorial information (Binary coded) (details are described in the abstract)

The PAGF51 TTAAii Data Designators decode as: T1 (P): Pictorial information (Binary coded) T1T2 (PA): Radar data (The bulletin collects reports from stations: 10410;Essen-Bredeney;) (Remarks from Volume-C: RADAR SWEEPS DATA, 10 ELEVATION ANGELS)

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