Marine litter at the seafloor comprises different materials. Plastic is the most frequent material of marine litter found at the seafloor of the Baltic Sea (55,6%). "Abandoned, lost, discarded or otherwise lost fishing gear" (ALDFG) is a subgroup of plastic litter with special importance for environmental assessment because it has a defined source and may pose a health risk to animals. With the data provided, marine litter at the seafloor of the Baltic Sea was quantified and characterized with special regard to fishery as source. 72 litter items (LI) were collected within fishery catches by bottom trawling during three cruises in 2020 and 2021. The data were used to quantify litter at the seafloor of the Baltic Sea (9.2 LI/km²) including 2.2 LI/km² ALDFG and 0.4 LI/km² fishery nets. We conclude that fishery is an important source of litter and ALDFG represent a considerable share of marine litter with 22.2%.
Data includes the measured environmental concentrations (MEC) of the summer copper (Cu) concentration in the German Bight from 1986 to 2021 (MUDAB database, https://geoportal.bafg.de/MUDABAnwendung/), including sampling points coordinates, year of sampling and Cu concentration. Additionally the Hazard quotient (HQ) is provided by dividing the MEC with the predicted no effect concentration (PNEC), defined as EC10 estimates from Crassostrea gigas embryos exposed for 48 h at 18°C and LC10 estimates from C. gigas larvae exposed for 24 h at 24°C, divided by an assessment factor (AF) of 5.
As part of PhytOakmeter (www.phytoakmeter.de), time-domain transmission, soil moisture and -temperature sensors with custom-made logger systems were used to measure time series of soil state variables. The aim of these investigations was to provide data on environmental properties used in a cross-disciplinary approach. The measurement device consisted of two sensors at three different depths. The dataset contains the values of time (UTC), relative permittivity, soil moisture (in % vol) derived from permittivity and soil temperature (in °C). Determination of soil moisture was done using the formula of Topp et al. (1980). As sensors, the SMT100 soil moisture sensors with integrated temperature measurement were used. All sensors were installed within the upper 50cm below ground. The exact depths for each sensor are listed in the dataset and parameter comment.
Multibeam data were collected with RV Polarstern along the route of cruise PS142 and data acquisition was continuously monitored during the survey. Multibeam sonar system was Teledyne/Atlas Hydrosweep DS3. SVPs were retrieved from CTD data and synthetic profiles from World Ocean Atlas 18. SVPs were processed with HydrOffice SoundSpeedManager (https://www.hydroffice.org/soundspeed/main) and extended with World Ocean Atlas 18 (https://www.ncei.noaa.gov/archive/accession/NCEI-WOA18). SVP data were applied during acquisition. Multibeam data are unprocessed and may contain outliers and blunders and should not be used for grid calculations and charting projects without further editing. The raw multibeam sonar data in Teledyne Reson multibeam processing format (.s7k) were recorded with Teledyne PDS software. Raw data files can be processed using software packages like CARIS HIPS/SIPS. For updated vessel configuration files check further details.
Multibeam data were collected with RV Polarstern along the route of cruise PS151 and data acquisition was almost continuously monitored during the survey. Multibeam sonar system was Teledyne/Atlas Hydrosweep DS3. SVPs were retrieved from CTD data and synthetic profiles from World Ocean Atlas 23. SVPs were processed with HydrOffice SoundSpeedManager (https://www.hydroffice.org/soundspeed/main) and extended with World Ocean Atlas 23 (https://www.ncei.noaa.gov/archive/accession/NCEI-WOA23). SVP data were applied during acquisition. Multibeam data are unprocessed and may contain outliers and blunders and should not be used for grid calculations and charting projects without further editing. The raw multibeam sonar data in Teledyne Reson multibeam processing format (.s7k) were recorded with Teledyne PDS software. Raw data files can be processed using software packages like CARIS HIPS/SIPS. For updated vessel configuration files check further details.
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.
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).
Rewetting peatlands is an important measure to reduce greenhouse gas (GHG) emissions. However, after rewetting, the areas are highly heterogeneous in terms of GHG exchange, which depends on water level and source, vegetation, previous use, and duration of rewetting. These challenging conditions require new technologies that go beyond discrete sampling. Here we present data from two autonomous lander platforms deployed at the sediment-water interface (bottom lander) of a shallow coastal peatland (approx. 1 m water depth) that was rewetted by brackish water from the Baltic Sea, thus becoming part of the coastal water through a permanent connection. These landers were equipped with six commercially available state-of-the-art sensors, and temporal high-resolution measurements of physico-chemical variables, including partial pressures of carbon dioxide (CO2) and methane (CH4), were made. The resolution of the field data ranged from 10 seconds to 120 minutes and was obtained for partial pressure of CO2 (Contros HydroC-CO2) and CH4 (Contros HydroC-CH4), temperature, salinity, pressure (water depth), oxygen (O2) (CTD-O2 with SBE-37SMP-ODO), the concentrations of phosphate (SBE HydroCycle PO4), nitrate (SBE SUNA V2), chlorophyll a and the turbidity (both with SBE-FLNTUSB ECO) as stationary measurements at two different locations in close proximity. The CTD and oxygen measurements provide exact water depth data for the respective lander locations. In the other data sets (e.g., CO2 measurements) rounded data are inserted instead of the exact depth data, which is 0.6 m for lander_1 and 0.9 m for lander_2. SUNA raw data are provided for completeness. However, we found them of insufficient quality to estimate nitrate concentrations due to interferences and biofouling. The deployment and recovery of the landers, and thus the measurements, took place between 02 June 2021 and 09 August 2021, and the sensors were operated under permanent wired power supply and a centralized timestamp. The sensors were maintained and cleaned bi-weekly. Results show considerable temporal fluctuations expressed as multi-day, diurnal, and event-based variability, with spatial differences caused by biologically-dominated variables.
The Arctic PASSION Polar Monthly Mean IST data set (AP-MMIST) is a combined surface temperature product covering open ocean, marginal ice zone and closed sea ice areas, represented by Sea Surface Temperatures (SST), Marginal Ice Zone Temperatures (MIZT) and sea Ice Surface Temperatures (IST). Beside ocean and sea ice the data set also includes surface temperatures from the Greenland and Antarctic ice sheets. AP-MMIST has been jointly developed and produced by Arctic PASSION WP-1 and the Sea Ice Thematic Assembly Centre (Sea Ice TAC) under the Copernicus Climate Change Service (C3S - service contract: 2022/C3S2_312b_MOi_SC1). The AP-MMIST is a monthly averaged temperature product based on the C3S daily IST CDR and ICDR level 3 data. The daily mean C3S IST data set is a resampled and averaged daily mean IST product using Global Area Coverage - Advanced Very High-Resolution Radiometer (AVHRR) IST level 2 data as input. The level 2 and 3 CDR and ICDR data records are described in Algorithm Theoretical Baseline Document (Eastwood et al., 2023). The surface temperature retrieval algorithm used to produce the basic level 2 product is a traditional split window algorithm using two Thermal InfraRed (TIR) channels to compensate for atmosphere and angular emissivity dependency. This is described in the Algorithm Theoretical Baseline Document (Eastwood et al., 2023). The level 1 TIR input data set is the full data record from the AVHRR on-board NOAA satellite platforms since 1982, as well as AVHRR records on-board Metop satellites since 2006. The product output format is NetCDF with standard attributes, following CF convention to the degree possible. The monthly data are divided into 2 monthly files, one for each hemisphere, SH and NH.
High resolution radar data (lmax) of Boostedt
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