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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).

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.

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.

Raw data of physical oceanography during RV HEINCKE cruise HE672

Raw physical oceanography data was acquired by a ship-based Seabird SBE911plus CTD-Rosette system onboard RV HEINCKE . The CTD was equipped with duplicate sensors for temperature (SBE3plus) and conductivity (SBE4) as well as one sensor for oxygen (SBE43). Additional sensors such as a WET Labs C-Star transmissometer, a WET Labs ECO-AFL fluorometer (FLRTD) and an altimeter (Teledyne Benthos PSA-916) were mounted to the CTD. The data was recorded using pre-cruise calibration coefficients. No correction, post-cruise calibration or quality control was applied. Processed profile data are available via the link below.

ADCP current measurements (1200 kHz) during RV SENCKENBERG cruise SE202208-2

Ocean velocities were collected by a Teledyne RDI 1200 kHz Workhorse Sentinel II ADCP that was mounted on RV SENCKENBERG during RV SENCKENBERG cruise SE202208-2. The transducer was located at 1.5 m below the water line. The instrument was operated in single-ping, broadband mode with bin size of 0.25 m and a blanking distance of 0.25 m. The velocity of the ship was calculated from position fixes obtained by the Global Positioning System (GPS) received at a Trimble SPS461 Modular GPS Heading Receiver. Heading was obtained both from the Trimble receiver and the internal ADCP gyro. Heading as well as pitch and roll data from ADCP's internal gyrocompass and the navigation data were used by the data acquisition software ViSea DAS (AquaVision®) internally to convert ADCP velocities into earth coordinates. Accuracy of the ADCP velocities mainly depends on the quality of the position fixes as well as Trimble receiver and internal ADCP heading data. Further errors stem from a misalignment of the transducer with RV SENCKENBERG's centerline.

GTS Bulletin: QEZG98 EDZW - Pictorial information regional (Binary coded) (details are described in the abstract)

The QEZG98 TTAAii Data Designators decode as: T1 (Q): Pictorial information regional (Binary coded) T1T2 (QE): Precipitation A2 (G): 18 hours forecast T1ii (Q98): Air priorities for the Earth's surface (Remarks from Volume-C: (COSEU) RR-type H+18,+24 (gpv))

GTS Bulletin: HVXX92 EDZW - Grid point information (GRIB) (details are described in the abstract)

The HVXX92 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HV): Northward wind component A1 (X): Global Area (area not definable) A2 (X): Not assigned T1ii (H92): 925 hPa (Remarks from Volume-C: H+ 66 (GLOBAL MODEL) WIND COMPONENT 925 HPA)

Global particulate organic carbon flux derived from Th-234: 13 ocean regions, 3 export depths

The 234Th–238U disequilibrium technique has been widely used to estimate the amount of particulate organic carbon (POC) exported from surface ocean layers to the deep sea. This method is based on determining 234Th fluxes from vertical 234Th–238U profiles in the water column and converting them into POC fluxes using POC/234Th ratios measured in sinking particles at a given calculation depth. We present here an extensive repository of POC fluxes, together with Th fluxes and POC/234Th ratios. Covering all the global ocean, classified in 13 regions, season and moment of the bloom and calculated at three different depths: i) a fixed depth (100 m) ii) the reference depth in the paper associated to the base of the euphotic zone iii) the 234Th–238U equilibrium depth. To ensure a compilation representative of the global ocean, the dataset were selected using the division areas proposed by the international network JETZON (Joint Exploration of the Twilight Zone Ocean Network); that agreed a division of the oceans in 13 regions based on their contrasted physics and biogeochemical characteristics. The stations from 234Th publications associated to each JETZON region were carefully selected according to their ability to represent regional environmental conditions. Furthermore, station selection was based on essential criteria such as data quality and accessibility, availability of time series, clear definition of export depth, measurements from established programs, e.g. GEOTRACES, and the presence of other additional relevant ancillary data. The data in the compilation are thus organized by region and include geographic coordinates, season, selected export depth, and other key factors (such as a description of the flux evaluation depth or the export depth zone). After 234Th–238U compilation, 234Th fluxes were calculated, when possible, at the three different depths, i), ii) and iii), under the assumption of steady-state conditions, following Le Moigne et al. 2013. Using POC/234Th ratios, POC fluxes are estimated from Th fluxes and both fluxes were included in the repository. POC/234Th ratios were chosen from pump samples, prioritizing particles larger than 53 μm when available. These ratios must be estimated at the flux calculation depth [i), ii) and iii)]. When they were not available at the calculation depth POC/234Th values were interpolated as described in the readme text file. The values of the ratios are included in the repository, specifying the depth at which they were determined and indicating whether they have been interpolated. Similarly, when 234Th, 238U concentrations were not available at the calculation depth, values were interpolated (see readme text file).

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.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Glücksburg, Germany from 1984 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

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