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Conductivity-Temperature-Depth (CTD) profiles with auxiliary sensor data from Norwegian Polar Institute cruise Arctic Ocean 2023 - 2 from north of Svalbard, across the shelf slope, and into the deep Nansen Basin of the Arctic Ocean between 10-29 August 2023. Three stations - 182, 216, and 221 - were part of the A-DBO (https://arcticpassion.eu/adbo/) network. The dataset includes profiles of sensor temperature, conductivity, uncalibrated dissolved oxygen, chlorophyll fluorescence, colored dissolved organic matter (CDOM) fluorescence (voltage only), beam attenuation, and calculated practical salinity (EOS-80). Profile data are from down casts only and available in a 1 decibar vertical resolution (i.e. averaged into 1-decibar bins). Chlorophyll fluorescence was calibrated against sample bottles using linear regression through the origin, excluding values larger than 8 mg/m3 (Figure 1 in summary_CTD_AO-II-2023_CTD.pdf). The salinity was verified against sample bottle salinities (Figure 2 in summary_CTD_AO-II-2023_CTD.pdf). Additionally, parameters for temperature, conductivity, salinity, chlorophyll, and beam attenuation are provided for the sampled bottle depths (named NISKIN_*).
The data are contained in a single, self-documenting netCDF file. Profile data are organized in arrays with one column per cast and one row per pressure bin (BIN_*). Data corresponding to the bottle depths are organized similarly, with one column per cast and one row per Niskin bottle. For stations 179-192 and 215-221 a rosette with 24 bottles was used and for stations 193, 195-214 a rosette with 12 Niskin bottles. For the latter, maximum of 12 topmost rows in the array are filled. 1-dimensional metadata such as time and position are organized in a row-vector with one value per cast. All variables have the same number of columns, equal to the total number of CTD casts. For more information on the sampling routines, please refer to the AO-II-2023 cruise report (https://hdl.handle.net/11250/3114227). The CTD post-cruise processing included the removal of salinity spikes. The primary conductivity sensor was of better quality than the secondary sensor and data from the primary sensors were selected to be included.
The data has been collected during the Seasonal Pelagic Monitoring in Kongsfjorden from 2019 (ongoing). The dataset contains mesozooplankton occurrence. It has been sampled using a WP2 Closing Net, HydroBios 57 cm with a mesh size 180 µm. All specimens are identified to the lowest taxonomical level and the occurrence is given for a specific species and stage or size group as organismQuantity (ind/m3). Biomass (dry mass mg/m3) can be calculating using biomass conversion factor in the zooplanktonMaster file.
Sampling method:
The mesozooplankton has been sampled weekly at the station in the middle of the fjord outside Ny-Ålesund (Kb3) from May to August with less frequent sampling in July and August. In addition, a transect from the glacier front to the fjord moth including the stations Kb8, Kb5, Kb3 and Kb1, was sampled one to four times every season. All samples were collected using a WP2 net, HydroBios 57 cm with a mesh-size 180 µm with a closing device at three depth layers (0-50 m, 50-100m and 100-bottom). Samples were concentrated over a sieve of 180 um and preserved in 4 % formaldehyde free from acid.
Analyse method:
All samples have been analysed at the Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under a stereomicroscope equipped with an ocular micrometer, according to standard procedures (Harris et al. 2000). Small-sized zooplankters (most of Copepoda, juvenile stages of Pteropoda, Euphausiacea, Ostracoda, Amphipoda and Chaetognatha) were identified and counted in sub-samples obtained from the fixed sample volume by automatic pipette (approximately 500 individuals). Large zooplankters (big Copepoda, Pteropoda, Euphausiacea, Ostracoda, Amphipoda, Decapoda, Appendicularia, Chaetognatha, and Pisces larvae) were sorted out and identified from the whole sample. Representatives of Calanus spp. were identified at the species level based on morphology and prosome lengths of individual copepodid stages (Kwasniewski et al. 2003).
Data structure:
The data follows Darwin Core nomenclature as far as possible but also includes variables not supported by Darwin Core. All information about the sampling such as eventDate, latitude, longitude, depts, etc. is located in the event file while the result such as scientificName, lifeStage, occurrence etc. are found in the occurrence file. The result file also contains some of the main event info.
Header name index - events
- expedition: project name (or abbreviation of name) and year
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- fieldNumber: sample ID (e.g. ZOT-001)
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. MultiNet 200 µm
- maximumDepthInMeters: bottom depth of the sampled layer
- minimumDepthInMeters: top depth of the sampled layer
- sampleType: description of the sample type according to a standard list
- fieldSplit: info about whether the sample is splitted. If the sample was split in 2 then fieldSplit = 2
- initialSampleVolume: The volume of water filtered through the plankton net. (initialSampleVolume = (netOpeningArea * (maximumDepthInMeters – minimumDepthInMeters)/field Split), WP2 opening area: 3.14*(0.57/2)^2=0.255m2
- recordedBy: name of the person who took the samples
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- analysedFraction: fraction of the sampled volume that is examined for organism counted
- individualCount: the number of individuals present in the analysed volume (see extra information below)
- phylum, class, order, family, genus & taxonKey-LSID: Taxonomical information for given species according to Worms
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Calanus finmarchicus).
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the Identification.
- lifeStage: the age class, life stage, or life form/morph of the organism.
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in mm.
- organismRemark: indicates whether it is mesozooplankton, macrozooplankton, rare species
- identificationRemarks: a free text field for adding information relevant to the analysis. Used to indicate the speciemen that were dead. When nothing was remarked they were alive.
- identifiedBy: person who did the lab-analyse
- sampleSizeValue: the sample volume used to calculate the organismQuantity (sampleSizeValue 0 initialSampleVolume *analysedFraction)
- sampleSizeUnit: m3
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: ind/m3
Additional information for some of the fields
individualCount: The number of (all) organisms found in the sample examined
- for “mesozooplankton”, the number of mesozooplankton (medium size zooplankton organisms) encountered in all sub-samples
- for “macrozooplankton”, the number of macrozooplankton (large size zooplankton organisms, total length > 5 mm) encountered, identified in the entire sample
- for “rare” zooplankton, we only enter information about the finding of “rare” zooplankton in the database template, and its absolute number (“organismQuantity”) is not estimated
Funding:
The Seasonal Pelagic Monitoring is funded by the Norwegian Polar Institute
This dataset contains results from water column samples collected during Kongsfjorden and Rijpfjorden (MOSJ and ICE cruises) from the years 2011 to 2020. All samples are collected from Niskin bottles from the CTD rosette of the ship. The data is from the transect from the glacier front to the Fram Strait in Kongsfjorden and from the inner glacier front in the inner part of the fjord across the shelf break.
Samples were filled directly from the Niskin bottle into new or acid-washed 20 ml scintillation vials and added with 0.2 ml (200 μl) of Triklormethan for spectrophotometry (Merck no. 2447.0500). The samples were stored in a fridge temperature. Samples for ammonium were also collected and analysed immediately on board, with the method of Solorzano (1969). The following nutrients; nitrite (NO2-), nitrate (NO3-), phosphate (PO43-) and silicate (SiO44-) are measured spectrophotometrically at 540, 540, 810 and 810 nm, respectively, on a modified Alpkem Flow Solution IV autoanalyzer or a modified Scalar autoanalyser (Bendschneider & Robinson 1952 RFA Methodology).
Measurement of nitrite
The method is based on that nitrite reacts colorimetrically with aromatic amin and forms a diazonium ion in acidic medium. The diazonium ion connects to a new aromatic amine and forms an azo. The absorption of the color is measured spectrophotometrically at 540 nm on a modified Alpkem Flow Solution IV autoanalyzer or a modified scalar autoanalyzer (Bendschneider & Robinson 1952 RFA Methodology). The detection limit for nitrites is 0.06 microM (Scalar) and 0.05 microM (Alpkem) and is significant to the second decimal place.
Measurement of nitrate
The method is based on the nitrate is reduced to nitrite (NO2-) by means of cadmium in the presence of copper ions. Then forming NO2- a diazonium ion with an aromatic amine in an acidic environment, which is diverted to a new aromatic amine and an azo dye is formed. Absorption of the color is measured spectrophotometrically at 540 nm on a modified Alpkem Flow Solution IV autoanalyser or a modified scalar autoanalyser (Bendschneider & Robinson 1952 RFA Methodology). The amount of nitrate is calculated as the difference between total reduced nitrite (this method) and NO2 measured without cadmium reduction (see Method U3_3 above). The detection limit for nitrate is 0.4 microM (Scalar) and 0.5 microM (Alpkem) and is significant to the first decimal place.
Measurement of phosphate (PO43-)
The method is based on the phosphate reacts with molybdate to form phosphomolybdate in acid medium (pH < 1) providing a yellow dye. This dye is reduced by ascorbic acid to a blue dye, and absorbance is measured spectrophotometrically at 810 nm on a modified Alpkem Flow Solution IV autoanalyzer or a modified Scalar autoanalyzer (Grashoff 1965). The detection limit for phosphate is 0.06 microM (Scalar and Alpkem) and is significant to the second decimal place.
Measurements of silicate
The method is based on the silicate reacts with molybdate to form a silikomolybdat (yellow dye) in an acidic environment (pH = 1.5-2). Oxalic acid is added to the silikomolybdat which then is reduced with ascorbic acid. The result is a blue compound which is measured spectrophotometrically at 810 nm on a modified Alpkem Flow Solution IV autoanalyser or a modified Scalar autoanalyzer (Grashoff 1965). The detection limit for silicate is 0.7 microM (Scalar) and 0.4 microM (Alpkem) and is significant to the first decimal place.
Chlorophyll
Chlorophyll samples were collected on 25-mm GF/F filters (Whatman), extracted in 100% methanol for 12 h at 5°C on board the ship and measured fluorometrically with an Trilogy Turner Fluorometer (Turner Design, Inc.). Phaeopigments were measured by fluorescence after acidification with 5% HCl. Calibration of the fluorometer was carried out following the JGOFS protocol 35 (Knap et al., 1996).
Data structure:
The data follows Darwin Core nomenclature as far as possible but also includes variables that aren’t supported by Darwin Core. The data includes event parameters and result parameters.
Event parameters:
- expedition: cruise number for R/V Kronprins Haakon
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- fieldNumber: human-readable sample ID (e.g. ZNUT-001)eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. MultiNet 200 µm
- samplingDepthInMeters: bottom depth of the sampled layer
Result parameters:
- PO4 [mmol/m3]: Concentration of phosphate as mmol per m3
- NO2 [mmol/m3]: Concentration of nitrite as mmol per m3
- NO3 [mmol/m3]: Concentration of nitrate as mmol per m3
- Si [mmol/m3]: Concentration of silicate as mmol per m3
- NH4 [mmol/m3]: Concentration of ammonium as mmol per m3
- BSi [µg/L]: Concentration of biogenic silica as µg per litre
- chlorophyll a [mg/m3]: Concentration of chlorophyll a as mmol per m3
- phaeophytin [mg/m3]: Concentration of phaeophytinas mmol per m3
- PON [µg/L]: Concentration of particulate organic nitrogen in µg per litre
- POC [µg/L]: : Concentration of particulate organic carbon in µg per litre
- PON [µmol/L]: Concentration of particulate organic nitrogen as µ mol per litre
- POC [µmol/L]: Concentration of particulate organic carbon as µ mol per litre
References
- Bendschneider, K. & Robinson, R.I. (1952), A new Spectrophotometric method for the determination of nitrite in Seawater. J. Mar. Res. 2: 87-96.
- Grasshoff, K. (1965), On the Automatic Determination of Phosphate, Silicate and Fluoride in Seawater. ICES Hydrographic Committee Report No. 129.
- Knap, A., Michaels, A., Close, A., Ducklow, H. & Dickson A. (1996), Measurement of Chlorophyll a and Phaeopigments by fluorometric analysis. JGOFS report 19: 118-122.
- RFA Methodology, Nitrate+nitrite Nitrogen, A303-S170 Revision 6-89. ALPKEM, a division of OI Analytical, College Station, Texas
- Solorzano, L. (1969), Determination of ammonia in natural waters by the phenolhypochlorite method. Limnol Oceanogr. 14:799.
The data has been collected during the monitoring cruise (NPI, Transekttokt) in Kong Håkon VII Hav from 2021 until today. The sampling covers a transect from the ice shelf across the shelf break into the deep ocean at approximately 6° East but also includes other opportunistic stations in the area. The samples were collected using a 12-Niksin-bottle SBE32 carousel water sampler equipped with CTD (conductivity-temperature-depth; SBE91+ system).
TT21: Transekttokt 2021 from December 31, 2020 to January 14, 2021 on cargo vessel CV Malik Arctica
Samples for the analysis of macronutrients (nitrate, nitrite, ammonium, phosphate, and silicic acid) were fixed with 200 µL of chloroform and refrigerated at 4 °C (for analysis at Vrije Universiteit) or sterile filtered (0.2 µm) and stored –20 °C in the dark (for analysis at UiT). Samples from 2021 were analysis at the Vrije Universiteit, Brussels, Belgium using a QuAAtro Autoanalyzer and the spectrophotometric method described by Grasshof et al. (1983). Samples from 2022 onward were analysed at UiT The Arctic University of Norway. At UiT macronutrient concentrations were measured in triplicate using a QuAAtro39 Continuous Segmented Flow Analyzer (Seal Analytics, Germany) and standard colorimetric methods (e.g., Hydes et al., 2010 ) using the protocols No. Q-068-05 Rev. 12 for nitrate (NO3; detection limit = 0.02 µmol L-1), No. Q-068-05 Rev. 12 for nitrite (NO2; detection limit = 0.07 µmol L-1), No. Q-064-05 Rev. 8 for phosphate (PO4; detection limit = 0.01 µmol L-1), and No. Q-066-05 Rev. 5 for silicate (dSi; detection limit = 0.07 µmol L-1). Analysis of macronutrient concentration data was done using the AACE software (SEAL Analytical, Germany). Reference standards of nutrient concentrations in seawater (Ocean Scientific International, LTD., United Kingdom) were used to verify instrument calibration.
Method ratio of stable oxygen isotopes in seawater (δ18O)
Samples for δ18O were stored at 4 °C in the dark until measurement with a Perspective (Nu Instrument, Ametek) isotope ratio mass spectrometer coupled to a Gas Bench system in the AMGC laboratory at the Vrije Universiteit, Brussels, Belgium (Epstein and Mayeda, 1953; Harmon, 1961). All samples for δ18O were standardized against V-SMOW, and the standard deviation of the δ18O analyses was 0.1‰.
Method Chlorophyll a
Samples for Chlorophyll a were filtered through 0.7 µm GF/F filters (GE Healthcare, Little Chalfont, UK) under low vacuum pressure (approximately −30 kPa), extracted with 100% methanol for approximately 24 hours, and stored at 4 °C in dark conditions (Holm-Hansen and Riemann, 1978). The pigment concentration, including phaeopigments, was measured with a Turner Trilogy Fluorometer (Turner Design, Inc.), which had been calibrated with Chl a standards from Turner Designs (Sunnyvale, California) prior to the cruise following the JGOFS protocol 35 (Knap et al., 1996).
Method particulate organic carbon (POC) and nitrogen (PON)
Samples for POC and PON analyses were filtered through pre-combusted 25mm Whatman 0.7 µm GF/F filters (GE Healthcare, Little Chalfont, UK) under low vacuum pressure (approximately −30 kPa; Moran et al., 1999). Samples for POC and PON were stored at −20 °C during shipment, then prepared for analysis by drying at 60 °C and acidifying in fuming hydrochloric acid. POC and PON concentrations were measured with a coupled element analyzer mass spectrometer (Europa Scientific, ANCA-MS 20-20 15N/13C) at the Tvärminne Zoological Station, Finland. All readings were blank-corrected.
Data structure:
The data is following Darwin Core nomenclature as far as possible but also includes variables that aren’t supported by Darwin Core.
Header name index
Event parameters
- expedition: cruise number for C/V Silver Arctic, C/V Malik Arctica or another vessel
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- gearType: the gear used to take the sample e.g. MultiNet 200 µm
- maximumDepthInMeters: sampling depth
- fieldNumber: human-readable sample ID (e.g. ZNUT-001)eventRemarks: comments or remarks about the event (free text field)
- sampleRemark: info about the sample
Result parameters
Nutrients
- fieldNumber: sample ID
- NO2 [mmol/m3]
- NO3 [mmol/m3]
- NH4 [mmol/m3]
- PO4 [mmol/m3]
- Si [mmol/m3]
- Epstein, S, Mayeda, T. 1953. Varation of O18 content of waters from natural sources. Geochimica et Cosmochimica Acta 4(5):213–224. doi: 10.1016/0016-7037(53)90051-9.
- Grasshoff, K. (1965), On the Automatic Determination of Phosphate, Silicate and Fluoride in Seawater. ICES Hydrographic Committee Report No. 129.
- Harmon, C. 1961. Isotopic variations in meteoric waters. Science 133(3465): 1702–1703. doi: 10.1126/science.133.3465.1702.
- Holm-Hansen, O, Riemann, B. (1978). Chlorophyll a Determination: Improvements in Methodology. Oikos 30(3): 438–447. doi:10.2307/3543338.
- Knap, A., Michaels, A., Close, A., Ducklow, H. & Dickson A. (1996), Measurement of Chlorophyll a and Phaeopigments by fluorometric analysis. JGOFS report 19: 118-122.
- Moran, SB, Charette, MA, Pike, SM, Wicklund, CA. (1999). Differences in seawater particulate organic carbon concentration in samples collected using small- and large-volume methods: the importance of DOC adsportion to the filter blank. Marine Chemistry 67(1–2): 33–42. doi: 10.1016/S0304-4203(99)00047-X.
Datasets from Paulsen et al. (in prep) Emergent patterns between NDVI and plant biomass, summer temperature and tundra disturbance in a new time series from the high Arctic. Arctic Science. The datasets are part of the larger COAT vegetation monitoring in Svalbard (P.I. Virve Ravolainen).
Two datasets with biomass, summer temperature and disturbance, NDVI from drone and Sentinel-2 in plots (plot-level, 0.5 x 0.5 m) and within monitoring sites (site-level, 30 m diameter circle).
- loc/locality: Location of monitoring sites (adv=Adventdalen, bro=Brøggerhalvøya, sas=Sassendalen)
- site_id: the unique id of each monitoring site
- plot_id: the unique id of each plot within each monitoring site
- habitat: dry = dryas ridge habitat , mos = moss tundra habitat
- Drone NDVI (10 cm spatial resolution, NDVI captured with sequoia camera on fixed-wing eBeex drone)
- Sentinel-2 NDVI (10 m spatial resolution, Sentinel-2 L2A)
- Total biomass (total_biomass): total vascular plant biomass of main plant groups and species in grams per square meter
- Growing degree days (GDD): accumulated temperature above 1 degree C until ground sampling day for that monitoring site.
- Winter damage (winter_damage): Recordings of winter-damaged shrubs in plots on a scale from 1-8 (or mean per site).
- Biotic crust (biotic_crust): Recordings of biotic crust in plots on a scale from 1-12 (or mean per site).
- Goose grubbing (light_grubbing, severe_grubbing): Recordings of presence or absence of goose disturbance in plots (0=no goose grubbing, 1=light goose grubbing, 2=severe goose grubbing). On site-level it is the total number of plots for each category.
This dataset contains results of dissolved inorganic carbon (DIC) from seawater column samples collected in Kongsfjorden (between 78°50’ and 79°04’N and 11°20’ and 12°30’E) and West-Spitsbergen shelf (Svalbard) during three years in July/August 2015-2017 as part of the annual MOSJ (Monitoring of Svalbard and Jan Mayen) summer cruises using R/V Lance. Vertical profiles of salinity and temperature and water samples for DIC were collected using a ship-board CTD probe attached to a Rosette-sampler with 12-Niskin bottles (SBE911 plus, Sea Bird Electronics, Bellevue, WA, United States). The CTD was calibrated by Sea Bird Electronics annually before each sampling season. DIC was measured after the cruises at the Institute of Marine Research (IMR Tromsø, Norway) using gas extraction of acidified samples followed by coulometric titration and photometric detection using a Versatile Instrument for the Determination of Titration carbonate (VINDTA 3D, Marianda, Germany). Replicate measurements of Certified Reference Material (CRM, provided by A. G. Dickson, Scripps Institution of Oceanography, United States) ensured the precision and accuracy of the measurements, which was better ±2 μmol kg−1 for DIC. References: Dickson, A. G., Sabine, C. L., and Christian, J. R. (2007). Guide to best practices for ocean CO2 measurements. chap. 4, pp. 23–78, PICES Spec. Publ., 3.
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2024-02-23T00:00:00Z
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Abstract:
Main greenhouse gases and carbon_monoxide at Birkenes II. These measurements are gathered as a part of the following projects NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), methane in air (mole_fraction_of_methane_in_air), methane in air (mole_fraction_of_methane_in_air), water_vapor in air (mole_fraction_of_water_vapor_in_air), water_vapor in air (mole_fraction_of_water_vapor_in_air)
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2024-02-13T00:00:00Z
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Abstract:
Ozone at Zeppelin mountain (Ny-Ålesund). These measurements are gathered as a part of the following projects EMEP_NRT, GAW-WDCRG_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: ozone in air (mole_fraction_of_ozone_in_air), ozone in air (mass_concentration_of_ozone_in_air)
Institutions: DE60L, Technical University Munich and Helmholtz Center Munich, ZAUM, Centre of Allergy & Environment, Biedersteinerstrasse 29, 80802, Munich, Germany, DE60L, Technical University Munich and Helmholtz Center Munich, ZAUM, Centre of Allergy & Environment, Biedersteinerstrasse 29, 80802, Munich, Germany
Last metadata update: 2024-03-27T00:00:00Z
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Abstract:
Bioaerosols at Zugspitze-Schneefernerhaus. These measurements are gathered as a part of the following projects AutoPollen_NRT, SYLVA_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: pollen_abies in aerosol, pollen_abies in aerosol, pollen_acer in aerosol, pollen_acer in aerosol, pollen_aesculus in aerosol, pollen_aesculus in aerosol, pollen_alnus in aerosol, pollen_alnus in aerosol, pollen_ambrosia in aerosol, pollen_ambrosia in aerosol, pollen_artemisia in aerosol, pollen_artemisia in aerosol, pollen_asteraceae in aerosol, pollen_asteraceae in aerosol, pollen_betula in aerosol, pollen_betula in aerosol, pollen_brassica in aerosol, pollen_brassica in aerosol, pollen_carpinus in aerosol, pollen_carpinus in aerosol, pollen_castanea in aerosol, pollen_castanea in aerosol, pollen_chenopodium in aerosol, pollen_chenopodium in aerosol, pollen_corylus in aerosol, pollen_corylus in aerosol, pollen_cruciferae in aerosol, pollen_cruciferae in aerosol, pollen_cyperaceae in aerosol, pollen_cyperaceae in aerosol, pollen_erica in aerosol, pollen_erica in aerosol, pollen_fagus in aerosol, pollen_fagus in aerosol, pollen_fraxinus in aerosol, pollen_fraxinus in aerosol, pollen_galium in aerosol, pollen_galium in aerosol, pollen_humulus in aerosol, pollen_humulus in aerosol, pollen_impatiens in aerosol, pollen_impatiens in aerosol, pollen_juglans in aerosol, pollen_juglans in aerosol, pollen_juniperus in aerosol, pollen_juniperus in aerosol, pollen_larix in aerosol, pollen_larix in aerosol, pollen_parietaria in aerosol, pollen_parietaria in aerosol, pollen_picea in aerosol, pollen_picea in aerosol, pollen_pinaceae in aerosol, pollen_pinaceae in aerosol, pollen_plantago in aerosol, pollen_plantago in aerosol, pollen_platanus in aerosol, pollen_platanus in aerosol, pollen_poaceae in aerosol, pollen_poaceae in aerosol, pollen_populus in aerosol, pollen_populus in aerosol, pollen_quercus in aerosol, pollen_quercus in aerosol, pollen_quercus_ilex in aerosol, pollen_quercus_ilex in aerosol, pollen_rumex in aerosol, pollen_rumex in aerosol, pollen_salix in aerosol, pollen_salix in aerosol, pollen_sambucus in aerosol, pollen_sambucus in aerosol, pollen_secale in aerosol, pollen_secale in aerosol, pollen_solidago in aerosol, pollen_solidago in aerosol, pollen_taraxacum in aerosol, pollen_taraxacum in aerosol, pollen_taxus in aerosol, pollen_taxus in aerosol, pollen_tilia in aerosol, pollen_tilia in aerosol, pollen_triticum in aerosol, pollen_triticum in aerosol, pollen_ulmus in aerosol, pollen_ulmus in aerosol, pollen_urticaceae in aerosol, pollen_urticaceae in aerosol, pollen_zea_mays in aerosol, pollen_zea_mays in aerosol, spores_fungi in aerosol, spores_fungi in aerosol, spores_fungi_alternaria in aerosol, spores_fungi_alternaria in aerosol
Institutions: US06L, National Oceanic and Atmospheric Administration, NOAA/ESRL/GMD, Earth System Research Laboratory, Global Monitoring Division, 325 Broadway, CO 80305-3, Boulder, U.S.A., US06L, National Oceanic and Atmospheric Administration, NOAA/ESRL/GMD, Earth System Research Laboratory, Global Monitoring Division, 325 Broadway, CO 80305-3, Boulder, U.S.A.
Last metadata update: 2024-02-24T00:00:00Z
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Abstract:
Aerosol_optical_depth at Penn State (SURFRAD). These measurements are gathered as a part of the following projects GAW-WDCA, NOAA-ESRL and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: aerosol_optical_depth in aerosol (atmosphere_optical_thickness_due_to_ambient_aerosol_particles), aerosol_optical_depth in aerosol (atmosphere_optical_thickness_due_to_ambient_aerosol_particles), aerosol_optical_depth in aerosol (atmosphere_optical_thickness_due_to_ambient_aerosol_particles)
Institutions: SE01L, Swedish Environmental Research Institute, IVL, P.O.Box 47086, S-402 58 GÖTEBORG, Sweden, SE01L, Swedish Environmental Research Institute, IVL, P.O.Box 47086, S-402 58 GÖTEBORG, Sweden
Last metadata update: 2024-03-22T00:00:00Z
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Abstract:
Heavy metals at Bredkälen. These measurements are gathered as a part of the following projects AMAP, EMEP, HELCOM and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: arsenic in precip (mass_concentration_of_arsenic_in_precipitation), cadmium in precip (mass_concentration_of_cadmium_in_precipitation), chromium in precip (mass_concentration_of_chromium_in_precipitation), cobalt in precip (mass_concentration_of_cobalt_in_precipitation), copper in precip (mass_concentration_of_copper_in_precipitation), lead in precip (mass_concentration_of_lead_in_precipitation), manganese in precip (mass_concentration_of_manganese_in_precipitation), nickel in precip (mass_concentration_of_nickel_in_precipitation), vanadium in precip (mass_concentration_of_vanadium_in_precipitation), zinc in precip (mass_concentration_of_zinc_in_precipitation)
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2024-02-12T00:00:00Z
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Abstract:
Main greenhouse gases and carbon_monoxide at Zeppelin mountain (Ny-Ålesund). These measurements are gathered as a part of the following projects EMEP_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), methane in air (mole_fraction_of_methane_in_air), methane in air (mole_fraction_of_methane_in_air)
Aerosol_absorption_coefficient at Alert. These measurements are gathered as a part of the following projects GAW-WDCA, NOAA-ESRL and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: aerosol_absorption_coefficient in pm10, aerosol_absorption_coefficient in pm10, aerosol_absorption_coefficient in pm10
Institutions: FR07L, Institut Mines Telecom Lille Douai, IMT Lille Douai, SAGE department, 941 rue Charles Bourseul, CS 10838, 59508, Douai, France, FR07L, Institut Mines Telecom Lille Douai, IMT Lille Douai, SAGE department, 941 rue Charles Bourseul, CS 10838, 59508, Douai, France
Last metadata update: 2024-02-26T00:00:00Z
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Abstract:
Meteorology at Le Casset. These measurements are gathered as a part of the following projects EMEP and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: pressure in met (air_pressure), relative_humidity in met (relative_humidity), temperature in met (air_temperature), wind_direction in met (wind_from_direction), wind_speed in met (wind_speed)
Institutions: FR07L, Institut Mines Telecom Lille Douai, IMT Lille Douai, SAGE department, 941 rue Charles Bourseul, CS 10838, 59508, Douai, France, FR07L, Institut Mines Telecom Lille Douai, IMT Lille Douai, SAGE department, 941 rue Charles Bourseul, CS 10838, 59508, Douai, France
Last metadata update: 2024-02-26T00:00:00Z
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Abstract:
Meteorology at Saint-Nazaire-le-Désert. These measurements are gathered as a part of the following projects EMEP and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: relative_humidity in met (relative_humidity), temperature in met (air_temperature)