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METOP GOME-2 - Ozone (O3) - Global

Gridded Level 3 ozone column densities derived from the Metop/GOME-2-instruments. In the stratosphere – where the majority of the total O3 amount is located - O3 plays an vital role for the UV protection. In the troposphere O3 is generated by chemical processes caused by natural and anthropogenic emission of NO2 and volatile organic components (VOCs) (e.g. HCHO). Direct exposure to O3 is harmfull for humans and our environment. The total O3 column is retrieved from GOME solar back-scattered measurements in the uv wavelength region 325-335nm [using the DOAS method]. To determine the AMF an iterative process is applied, the assumed profile depends on the latitude, month, but also on the total column. The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

METOP GOME-2 - Tropospheric Nitrogen Dioxide (NO2) - Global

Gridded Level 3 tropospheric NO2 column densities derived from the Metop/GOME-2-instruments. In the troposphere NO2 is a short-lived atmospheric constituent caused by combustion processes, e.g. fossil fuel consumption or biomass buring or by lightning. NO2 plays an important role in the formation of ozone. The total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region around 440nm [using the DOAS method]. To derive tropospheric NO2 columns, the estimated stratospheric component is substracted from the total column. In addition, an air mass factor based on monthly climatological NO2 profiles is considered. The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

Forstliche Versuchsflächen des Landes Brandenburg (WFS gesamt+fachbezogene Layer)

Das Landeskompetenzzentrum Forst Eberswalde verwaltet Daten von fast 1000 im ganzen Land Brandenburg verteilten Versuchen mit über 3000 häufig sehr langfristig bearbeiteter Einzelflächen (teilweise seit 1870), von denen mehr als 1000 Flächen noch unter aktueller Beobachtung stehen. Die Digitalisierung der Lageskizzen älterer Flächen erfolgte 2013-2014. Neue Flächen werden mit Hilfe von GPS geografisch verortet. Die Daten werden in einer Datenbank der langfristigen forstlichen Versuchsflächen des Landes Brandenburg verwaltet. Der WFS-Dienst enthält 52 abrufbare Layer zu den forstliche Versuchsflächen des Landes Brandenburg: die Gesamtmenge aller Flächen sowie gefiltert nach einzelnen fachbezogenen Parametern.

Abundance and biomass of macrofauna in the German Bight from 2016 to 2019

The long-term ecological research benthic monitoring comprises four representative permanent stations (SSd, Slt, FSd and WB) that have been sampled countinuously since 1969. The four stations are representative for the different benthic communities in the German Bight. Inter-annual variability and possible long-term trends were analysed based on spring-time samples since 1969. Earlier datasets have been published in the publication series https://doi.org/10.1594/PANGAEA.667646. Macrozoobenthos of soft-bottom benthic community was collected by van-Veen grabs. This dataset contains the continuation of this time series with the samples collected in spring between 2016 and 2019 each year in the North Sea, German Bight. Data for each campaign comprise four stations in the German Bight, sampled by grab samples (infauna). Biodiversity data of species include abundance (count data) and biomass (wet mass, g) per sample.

LTER Benthos – German Bight: Long-term ecological research of benthos in the German Bight (2001 et seq)

The long-term ecological research benthic monitoring comprises four representative permanent stations (SSd, Slt, FSd and WB) that have been sampled continuously in spring since 1969. The four stations are representative for the different benthic communities in the German Bight. Inter-annual variability and possible long-term trends were analysed based on spring-time samples since 1969. Macrozoobenthos of soft-bottom benthic community was collected by van-Veen grabs. Data for each campaign comprise four stations in the German Bight, sampled by grab samples (infauna). Biodiversity data of species include abundance (count data) and biomass (wet mass, g) per sample. The data is also available in a PostgreSQL-based data warehouse that can be accessed and queried through an open-access frontend web service at https://critterbase.awi.de/benosis by searching for the data sets "LTER_Benthos". Earlier datasets covering the years 1969-2000 have been published in the publication series https://doi.org/10.1594/PANGAEA.667646.

METOP GOME-2 - Cloud Optical Thickness (COT) - Global

Gridded Level 3 cloud optical thickness derived from Metop/GOME observations. Cloud physical properties (cloud fraction, cloud top height, cloud optical thickness) are derived from GOME/GOME-2 observations using the OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/ The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

Boden-Dauerbeobachtung im Land Brandenburg View-Service (WMS-LFU-BDF)

Der INSPIRE View Service beinhaltet die Standorte zu den Messstellen der Boden-Dauerbeobachtungsflächen im Land Brandenburg. Die Boden-Dauerbeobachtung ist ein Instrument zur langfristigen Überwachung von Veränderungen des Zustandes und der Funktionen des Bodens im Sinne des Bundes-Bodenschutzgesetzes bzw. weiterer untergesetzlicher Regelwerke. Die Boden-Dauerbeobachtung ist dabei nicht isoliert, sondern als zentrales Element einer integrierten Umwelt-Beobachtung zu betrachten. Ziele der Boden- Dauerbeobachtung sowohl brandenburgspezifisch als auch bundesweit sind a) die Erfassung des aktuellen Zustandes der Böden, b) die langfristige Überwachung von Bodenveränderungen und c) die Ableitung von Prognosen für die zukünftige Entwicklung der Böden. Als Sachdaten sind neben der Bezeichnung der Boden-Dauerbeobachtungsfläche auch Angaben zur Nutzungsart, der naturräumlichen Haupt-Einheitsgruppe, dem Bodenausgangsgestein, dem Bodentyp, der Bodenart des Oberbodens sowie der Kategorie für deren Auswahl hinterlegt. Aggregierte und qualitätsgeprüfte Messdaten werden zu einem späteren Zeitpunkt ergänzt. Hinweis: Die Lage der Standorte wurde auf ganze km gerundet und entspricht daher nicht der tatsächlichen Lage der Boden-Dauerbeobachtungsflächen.

Immissionsökologische Dauerbeobachtungsstationen zum Monitoring von Schadstoffen aus der Luft

An den immissionsökologischen Dauerbeobachtungsstationen werden ganzjährig im regelmäßigen Zyklus (28-Tage) mit verschiedenen Messeinrichtungen Parameter zum Monitoring von Schadstoffen aus der Luft erfasst. Zum Monitoring eutrophierender und versauernder Einträge sind elektrisch gekühlte Niederschlagssammler (Elektrisch gekühlter Bulk, Wet only) sowie Passivsammler für die Ermittlung gasförmiger Ammoniak- und NO2-Konzentrationen installiert. Der Eintrag von Metallen wird über die Sammlung des Staubniederschlags (Bergerhoff-Methode) ermittelt. Von Mai bis November wird mit Methoden des aktiven Biomonitorings die Wirkung von Stoffeinträgen auf Pflanzen ermittelt. Die Wirkung des atmogenen Eintrags von Metallen auf Pflanzen wird mit der standardisierten Graskultur erhoben, die Wirkung organischer Schadstoffe (Dioxine/Furane, PAK, PCB) wird mit standardisierten Graskulturen und Grünkohl ermittelt. Messdaten sind gegen Bereitstellungsgebühr bei der Datenstelle des LfU erhältlich.

BAM1 antibody (fucoidan) analysis during 24-days of incubations in mesocosm experiments with brown algae

Six mesocosm experiments with specimens of Fucales or Laminariales were conducted across six georegions (3 mesocosms with brown algae, 3 mesocosms without brown algae). Incubations lasted 24 days, followed by a year-long monitoring of incubation water. During the first 12 days, brown algae were maintained in mesocosms adjacent to control mesocosms, with 1 L of water sampled every second day. Half of the mesocosm water was replaced with fresh seawater after each sampling. Environmental conditions and primary productivity of specimens was recorded during the incubation. After 12 days, specimens were removed and incubation continued for another 12 days, maintaing the same sampling routine. At the end of the 24 day- incubation period, long-term monitoring was set-up with 6-10L of incubation water in two different conditions: one exposed to a controlled light cycle at 20°C, the second set in darkness at 4°C with added nutrients (40 µM NO3- and 3µM PO43-). Additional water samples were collected along transects extending from near-shore brown algae poplulations. Water samples were filtered over pre-combusted GFF filters (450°C, 4.5h), and both the filtrate and filters were analysed for dissolved organic carbon (DOC), particulate organic carbon (POC). Fucoidan was quantified in dissolved (>1kDa) fraction and surface active fraction (SAF) (> 1kDa and negative charged fraction purified with anion exchange chromatography) fractions through monosaccharide quantification after acid-hydrolysis (100°C, 24h) using HPAEC-PAD, according to Engel and Händel, 2011. Intact polysaccharides were detected using structure-sensitive monoclonal antibodies (Torode et al., 2015; Vidal-Melgosa et al., 2021). Microbial cells were quantified using DAPI-cell staining and counting. Semi-quantitative measurements of particulate fucoidan were performed via acid hydrolysis of GFF filter pieces, followed by monosaccharide analysis via HPAEC-PAD. Sedimented particles to bottom of mesocosms were scooped out on day 24 for monosaccharide analysis and BAM1 antibody binding specific to fucoidan.

Microbial cell abundance quantified via DAPI-cell counting during mesocosm experiments with brown algae

Six mesocosm experiments with specimens of Fucales or Laminariales were conducted across six georegions (3 mesocosms with brown algae, 3 mesocosms without brown algae). Incubations lasted 24 days, followed by a year-long monitoring of incubation water. During the first 12 days, brown algae were maintained in mesocosms adjacent to control mesocosms, with 1 L of water sampled every second day. Half of the mesocosm water was replaced with fresh seawater after each sampling. Environmental conditions and primary productivity of specimens was recorded during the incubation. After 12 days, specimens were removed and incubation continued for another 12 days, maintaing the same sampling routine. At the end of the 24 day- incubation period, long-term monitoring was set-up with 6-10L of incubation water in two different conditions: one exposed to a controlled light cycle at 20°C, the second set in darkness at 4°C with added nutrients (40 µM NO3- and 3µM PO43-). Additional water samples were collected along transects extending from near-shore brown algae poplulations. Water samples were filtered over pre-combusted GFF filters (450°C, 4.5h), and both the filtrate and filters were analysed for dissolved organic carbon (DOC), particulate organic carbon (POC). Fucoidan was quantified in dissolved (>1kDa) fraction and surface active fraction (SAF) (> 1kDa and negative charged fraction purified with anion exchange chromatography) fractions through monosaccharide quantification after acid-hydrolysis (100°C, 24h) using HPAEC-PAD, according to Engel and Händel, 2011. Intact polysaccharides were detected using structure-sensitive monoclonal antibodies (Torode et al., 2015; Vidal-Melgosa et al., 2021). Microbial cells were quantified using DAPI-cell staining and counting. Semi-quantitative measurements of particulate fucoidan were performed via acid hydrolysis of GFF filter pieces, followed by monosaccharide analysis via HPAEC-PAD. Sedimented particles to bottom of mesocosms were scooped out on day 24 for monosaccharide analysis and BAM1 antibody binding specific to fucoidan.

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