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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).

WISE Water Framework Directive Database

The WISE Water Framework Directive database contains data from the River Basin Management Plans reported by EU Members States, Iceland, Norway and the United Kingdom according to article 13 of the Water Framework Directive (WFD). The database includes information about surface water bodies (number and size, water body category, ecological status or potential, chemical status, significant pressures and impacts, and exemptions) and about groundwater bodies (number and size, quantitative status, chemical status, significant pressures and impacts, and exemptions). The information is presented by country, river basin district (RBD) and river basin district sub-unit (where applicable).

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.

Industrial Reporting under the Industrial Emissions Directive 2010/75/EU and European Pollutant Release and Transfer Register Regulation (EC) No 166/2006 Ver 12.0 Mar. 2025 (Spatial data)

This metadata refers to the geospatial dataset representing the status of the EEA Industrial Reporting database as of 10 March 2025 (version 14). The release and emissions data cover the period 2007-2023 as result of the data reported under the E-PRTR facilities, 2017-2023 for IED installations and WI/co-WIs, and 2016-2023 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.

GTS Bulletin: ISND79 AMDW - Observational data (Binary coded) - BUFR (details are described in the abstract)

The ISND79 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISN): Synoptic observations from fixed land stations at non-standard time (i.e. 01, 02, 04, 05, ... UTC) A2 (D): 90°E - 0° northern hemisphere (Remarks from Volume-C: NATIONAL AUTOMATIC SYNOP)

Member States' use of revenues from the auctioning of EU ETS allowances, 2020-2024

This metadata overs the dataset containing information on how EU Member States spend the revenues from auctioning EU ETS emission allowances in one calendar year. More information on the EU Emissions Trading System (EU ETS) can be found here. The revenues from the auctioning of these allowances represent an increasing income source for Member States. This data is being collected under Article 19 of the Governance Regulation. The Regulation’s aim is to help the EU reach its 2030 climate and energy targets by setting common rules for planning, reporting and monitoring. The Regulation also ensures that EU planning and reporting are synchronised with the ambition cycles under the Paris Agreement. Reporting is mandatory for EU Member States. Some information is only mandatory to report if the data is available.

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.

Tree Species - Sentinel-2 - Germany, 2016

The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2016 at a spatial resolution of 10 meters. The map depicts the distribution of ten tree species groups derived from multi-temporal optical Sentinel-2 data. The input features explicitly incorporate phenological information to capture seasonal vegetation dynamics relevant for species discrimination. A total of over 100,000 training and test samples were compiled from publicly accessible sources, including urban tree inventories, Google Earth Pro, Google Street View, and field observations. The final product was created by majority-voting on annual XGBoost Sentinel-2 tree species classifications (2016–2024) and filtering with forest structure data. If no clear majority vote was achieved, the class uncertain was assigned. The Tree Species Germany 2016 product achieves an overall F1-score of 0.95. For the dominant species pine, spruce, beech, and oak, class-wise F1-scores range from 0.92 to 0.99, while F1-scores for other widespread species such as birch, alder, larch, Douglas fir, fir, and other deciduous species range from 0.85 to 0.96. The product provides a consistent, high-resolution, and up-to-date representation of tree species distribution across Germany. Its transferable, cost-efficient, and repeatable methodology enables reliable large-scale forest monitoring and offers a valuable basis for assessing spatial patterns and temporal changes in forest composition in the context of ongoing climatic and environmental dynamics.

Global optimized REVEALS reconstruction of past vegetation cover for taxonomically harmonized pollen data sets

This data set presents the reconstructed vegetation cover for 3083 sites based on harmonized pollen data from the data set LegacyPollen 2.0 (https://doi.pangaea.de/10.1594/PANGAEA.965907) and optimized RPP values. 1115 sites are located in North America, 1435 in Europe, and 533 in Asia. Sugita's REVEALS model (2007) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by taking into account taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were also calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal. In this optimized reconstruction, relative pollen productivity estimates for the ten most common taxa were first optimized by using reconstructed tree cover from modern pollen samples and LANDSAT remotely sensed tree cover (Townshend 2016) for North America, Europe, and Asia. Values for non-optimized taxa for relative pollen productivity and fall speed were taken from the synthesis from Wiezcorek and Herzschuh (2020). The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with optimized reconstructed vegetation cover for all Europe, North America and Asia. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.

GTS Bulletin: SMVX01 EDZW - Surface data (details are described in the abstract)

The SMVX01 TTAAii Data Designators decode as: T1 (S): Surface data T1T2 (SM): Main synoptic hour (Remarks from Volume-C: SHIP)

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