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Schwefeldioxid Brunsbüttel, Cuxhavener Straße 1-Stunden Mittelwert 2026

Um die Gesundheit der Menschen und die Vegetation vor den Einflüssen zu hoher Luftschadstoffbelastungen zu schützen, wird die Luftqualität laufend untersucht und nach gesetzlichen Vorschriften beurteilt. Dafür betreibt das Landesamt für Umwelt (LfU) in Schleswig-Holstein ein Netz aus Messstationen, an denen mit unterschiedlichen Methoden Luftschadstoffe gemessen werden. Die Messdaten aus Schleswig-Holstein und viele zusätzliche Informationen zu den Messungen werden an das Umweltbundesamt weiter geleitet und von dort gemeinsam mit den Daten aller Bundesländer an die Europäische Kommission gemeldet. Alle aktuell veröffentlichten Daten sind als ***vorläufig*** einzustufen, da sie zu Ihrer schnellen Information zunächst automatisch auf Gültigkeit geprüft werden. Vor der abschließenden Bewertung und Beurteilung der Luftqualität findet später eine mehrstufige Prüfung nach gesetzlichen Vorgaben statt. Bei den CSV-Dateien „fehlt“ am Tag der Umstellung von Normalzeit (MEZ) auf Sommerzeit (MESZ) die 3-Uhr-Messung, am Tag der Umstellung von Sommer- auf Normalzeit gibt es hingegen zwei 3-Uhr-Messungen. Die JSON-Dateien sind von dieser Problematik nicht betroffen, hier wird durchgängig Normalzeit verwendet. [Informationen zur Messstation](https://www.schleswig-holstein.de/DE/Fachinhalte/L/luftqualitaet/Messstationen/BrunsbuettelCux.html)

Schulstammdaten und Schülerzahlen der Hamburger Schulen

Für jede Schule und ggf. ihre Zweigstellen werden dargestellt: - Adresse (Straße, Hausnummer, PLZ, Ort, Geoposition) - Kontaktdaten (Telefon, E-Mail-Funktionspostfach, Fax, Homepage) - Schulmerkmale (Schulnummer, Zweigstelle ja/nein, Schulform nach Haushaltskapitel, Erwachsenenbildung ja/nein, Telefonnummer der Schulaufsicht, zugehöriger ReBBZ-Standort) - Zahl der Schüler

Continuous meteorological observations at DynaCom automatic weather station, Spiekeroog, Germany, 2025-01 to 2025-12

Data presented here were collected between January 2025 to December 2025 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Meteorological data were collected near the experimental setup, with a locally installed weather station located approximately 500m north of the southern shoreline. The weather station system used here was a ClimaSensor US 4.920x.00.00x that was pre-calibrated by the manufacturer (Adolf Thies GmbH & Co. KG, D-Göttingen). Data were recorded and saved within the Processcontrol Weather (c) -4H- JENA engineering GmbH (v20.1.0.1 2020) software in a sampling interval of 1 min, with an averaging time of 10 s. Date and time were given in UTC and the position was derived from the internal GPS system. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2024b). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Continuous current observations near DynaCom experimental islands in the back-barrier tidal flat, Spiekeroog, Germany, 2019-11 to 2023-09

Data presented here were collected between November 2019 to September 2023 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) involving the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were established in the back-barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog (Germany). A recording current meter (RCM; SEAGUARD® Recording Current Meter, Aanderaa Data Instruments AS, Bergen/Norway) was installed in the back-barrier tidal flat near the experimental islands. The sensor was bottom-mounted in a shallow tidal creek (0.59 m NHN) using a steel girder buried in the sediment, which caused the sensor to be exposed during low tide. All low-tide data have been removed from the dataset. The system was equipped with a ZPulse Doppler Current Sensor (DCS), a conductivity sensor, an oxygen optode, and two analogue sensors for chlorophyll-a and turbidity (16445). All sensors were pre-calibrated by the manufacturer. Recorded data were internally logged until readout with the SeaGuard Studio software (V1.5.23). Salinity was derived in the SeaGuard Studio software using temperature-dependent, nonlinear seawater conductivity compensation following the Practical Salinity Scale (PSS-78). Subsequent data processing was done using MATLAB (R2024b). Turbidity and chlorophyll-a data were excluded from the final dataset, as the recorded signals show implausible values and did not pass quality-control criteria. Post-processing and quality control included (a) the removal of low tide data, data covering maintenance activities, and data affected by biofouling, (b) the removal of implausible values, c) an outlier detection using the Hampel filter method, and (d) visual checks. Identified outlier were removed and synchronously removed across all associated parameters of the respective sensor.

Oxygen consumption rate, organic carbon and grain size data for intertidal sediments and oxygen concentration of pore waters data of Spiekeroog Island North Beach, May 2022 to April 2023

The permeable sandy sediments of beach aquifers receive a high input of electron acceptors, such as oxygen (O2), as well as fresh organic matter through seawater infiltration, driving the biogeochemical turnover in the subterranean estuary. Here, we experimentally determined seasonal sedimentary O2 consumption rates of intertidal sediments along a transect in the seawater infiltration zone at Spiekeroog Island North Beach, Germany, and present the data together with measurements of organic carbon and grain sizes, oxygen concentration of pore waters and beach topography. The samples were taken down to 1 m depth during two-monthly sampling campaigns from May 2022 to April 2023. Preliminary investigations of O2 consumption rates took place in in March, June and August 2017. Sediment and porewater sampling procedures were carried out as described by Massmann et al. (2023). O2 consumption rates were determined in slurry incubations of the retrieved sediments using gas tight vials (Labco Exetainer® 12 ml) equipped with O2 sensor spots (Pyroscience, OXSP5). Incubations were carried out in the dark at in situ temperatures, and vials were mounted on a rotating wheel to mimic porewater advection. The sediment's total organic carbon content was determined in a CS analyser (Eltra CS 800). Additionally, the fine fraction of the sediment was washed out and the organic carbon content of the fine sediments was measured in a CHNSO analyser (Hekatech Euro EA). The grain size distribution of the sediments was detemined using dynamic image analysis (Sympatec QICPIC). The O2 concentration in the pore water along the transect was measured immediately after the sample was taken using a flow-through oxygen optode (Pyroscience, OXFTC). The data was collected to investigate the impact of seasonal inputs and filtration efficiency on the O2 consumption during seawater infiltration into the permeable sands of beach aquifers.

Organic parameters obtained from Metzingen core

The total carbon (TC), total organic carbon (TOC), and total sulfur (TS) were determined using a LECO CS-230 system (Laboratory Equipment Corporation). Samples were heated up to 2000 °C under an oxygen atmosphere and an infrared detector subsequently measured the amount of produced CO₂ and SO₂. TOC was measured the same way after removing inorganic carbonates using 10 % HCl solution at 80 °C. Rock-Eval Pyrolyses were performed on a Rock-Eval-6 analyser (Vinci Technologies) using up to 180 mg initial sample material and a standard program (Espitalié et al., 1977; Lafargue et al., 1998), starting isothermal with 300°C for 3 min, succeeded by a heating rate of 25°C/min up to 650°C. Standard deviations for hydrogen indices (HI) and Tmax values are ± 5 % and ± 2°C, respectively.

Organic parameters obtained from Röttingen core

The total carbon (TC), total organic carbon (TOC), and total sulfur (TS) were determined using a LECO CS-230 system (Laboratory Equipment Corporation). Samples were heated up to 2000 °C under an oxygen atmosphere and an infrared detector subsequently measured the amount of produced CO₂ and SO₂. TOC was measured the same way after removing inorganic carbonates using 10 % HCl solution at 80 °C. Rock-Eval Pyrolyses were performed on a Rock-Eval-6 analyser (Vinci Technologies) using up to 180 mg initial sample material and a standard program (Espitalié et al., 1977; Lafargue et al., 1998), starting isothermal with 300°C for 3 min, succeeded by a heating rate of 25°C/min up to 650°C. Standard deviations for hydrogen indices (HI) and Tmax values are ± 5 % and ± 2°C, respectively.

Continuous salinity observations at station BEFmate_I3pio, 2017-04 to 2017-12

Data presented here were collected between April 2017 to December 2017 in the BEFmate project (Biodiversity - Ecosystem Functioning across marine and terrestrial ecosystems) of the Universities of Oldenburg and Göttingen and the Nationalparkverwaltung Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were established in the back-barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog (Germany). Salinity at different elevation zones was measured using conductivity loggers deployed in dip wells within experimental islands as well as in the saltmarsh enclosed plots. Measurements were obtained using HOBO U24 Conductivity Logger U24-002-C (Onset Computer Corporation, Bourne, MA/USA). All devices were pre-calibrated by the manufacturer. Logged data were retrieved in the field using a Hobo Underwater Shuttle (U-DTW-1) and were read out with the HOBOware Pro (V3.7.28) software. Salinity was derived in HOBOware Pro using temperature-dependent, nonlinear seawater conductivity compensation following the Practical Salinity Scale (PSS-78). Subsequent data processing was done using MATLAB (R2024b). Post-processing and quality control included (a) the removal of data covering maintenance activities, (b) the removal of implausible values using fixe thresholds (salinity > 40 psu and < 5 psu; temperature > 35 °C and < -5 °C), c) an outlier detection using the Hampel filter method, and (d) visual checks. Identified outliers were removed and synchronously removed across all associated parameters (temperature and salinity).

Continuous salinity observations at station BEFmate_S3pio, 2017-04 to 2017-12

Data presented here were collected between April 2017 to December 2017 in the BEFmate project (Biodiversity - Ecosystem Functioning across marine and terrestrial ecosystems) of the Universities of Oldenburg and Göttingen and the Nationalparkverwaltung Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were established in the back-barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog (Germany). Salinity at different elevation zones was measured using conductivity loggers deployed in dip wells within experimental islands as well as in the saltmarsh enclosed plots. Measurements were obtained using HOBO U24 Conductivity Logger U24-002-C (Onset Computer Corporation, Bourne, MA/USA). All devices were pre-calibrated by the manufacturer. Logged data were retrieved in the field using a Hobo Underwater Shuttle (U-DTW-1) and were read out with the HOBOware Pro (V3.7.28) software. Salinity was derived in HOBOware Pro using temperature-dependent, nonlinear seawater conductivity compensation following the Practical Salinity Scale (PSS-78). Subsequent data processing was done using MATLAB (R2024b). Post-processing and quality control included (a) the removal of data covering maintenance activities, (b) the removal of implausible values using fixe thresholds (salinity > 40 psu and < 5 psu; temperature > 35 °C and < -5 °C), c) an outlier detection using the Hampel filter method, and (d) visual checks. Identified outliers were removed and synchronously removed across all associated parameters (temperature and salinity).

Continuous salinity observations at station BEFmate_S3pio, 2019-03 to 2023-09

Data presented here were collected between 2019-03 and 2023-09 at station BEFmate_S3pio within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) involving the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were established in the back-barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog (Germany). Salinity at different elevation zones was measured using conductivity loggers deployed in dip wells within experimental islands as well as in the saltmarsh enclosed plots. Measurements were obtained using HOBO U24 Conductivity Logger U24-002-C (Onset Computer Corporation, Bourne, MA/USA). All devices were pre-calibrated by the manufacturer. Logged data were retrieved in the field using a Hobo Underwater Shuttle (U-DTW-1) and were read out with the HOBOware Pro (V3.7.28) software. Salinity was derived in HOBOware Pro using temperature-dependent, nonlinear seawater conductivity compensation following the Practical Salinity Scale (PSS-78). Subsequent data processing was done using MATLAB (R2024b). Post-processing and quality control included (a) the removal of data covering maintenance activities, (b) the removal of implausible values using fixe thresholds (salinity > 40 psu and < 5 psu; temperature > 35 °C and < -5 °C), c) an outlier detection using the Hampel filter method, and (d) visual checks. Identified outliers were removed and synchronously removed across all associated parameters (temperature and salinity).

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