http://lod.bco-dmo.org/id/dataset/810032
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2020-04-27
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Global reconstruction of surface oceanic N2O disequilibrium and its associated flux
2020-04-27
publication
2020-04-27
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2020-05-01
publication
https://doi.org/10.26008/1912/bco-dmo.810032.1
Daniele Bianchi
University of California-Los Angeles
principalInvestigator
Simon Yang
University of California-Los Angeles
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Bianchi, D., Yang, S. (2020) Global reconstruction of surface oceanic N2O disequilibrium and its associated flux. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2020-04-27 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.810032.1 [access date]
Global reconstruction of surface oceanic N2O disequilibrium and its associated flux Dataset Description: <p>Global reconstruction of surface oceanic N2O disequilibrium and its associated flux. The dataset includes 3 files:<br />
(1) <strong>surfocean-n2o-compilation.csv</strong>: available as a .csv/.tsv&nbsp;file via the "Get Data" button on the BCO-DMO landing page. A global compilation of observed surface ocean nitrous oxide pressure, concentration, mixing ratio measurements and their implied nitrous oxide disequilibrium used to train the supervised learning algorithm. Also attached as a .mat file (<strong>surfocean-n2o-compilation.mat</strong>) under "Data Files".<br />
(2) <strong>dn2o-mapped-Yang2020.nc</strong>: available under "Data Files". Predicted N2O disequilibrium.<br />
(3) <strong>n2oFlux-Yang2020.nc</strong>: available under "Data Files". The predicted ocean to atmosphere N2O flux.</p>
<p>This dataset contains a compilation of data from multiple sources. A list of all datasets and the associated information, including cruise name, is included in the associated Supplemental File, "SuppCruiseTable_dec11.xlsx".</p> Methods and Sampling: <p>We compiled surface (0m-12m depth) marine N2O concentrations and partial pressures measurements from a variety of sources. The core of the data is sourced from the MEMENTO database (Kock&nbsp;&amp; Bange, 2015). We complement MEMENTO with additional published N2O measurements from the literature, and unpublished N2O measurements from 16 additional cruises (see Supplemental File "SuppCruiseTable_dec11.xlsx"), including 11 cruises from the Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP). We do not perform any further quality control of the N2O data from published sources besides that performed by the individual contributors and the MEMENTO database administrators (Kock&nbsp;&amp; Bange, 2015). A description of the quality control performed on new unpublished N2O data is reported as footnotes to the annotations labeled as qc1**, qc2**, or qc3** (see "SuppCruiseTable_dec11.xlsx"). We convert each marine N2O measurement to XwN2O (the N2O mixing ratio in seawater, in units of ppb) using, when needed, the N2O solubility coefficient (Weiss &amp; Price, 1980). The coefficient is calculated using co-measured temperature, and salinity, as well as sea level pressure from the ERA5 reanalysis (Copernicus Climate Change Service, 2017), at the time (month and year), and location of the measurement. If the measurement time is not available in the ERA5 reanalysis prediction, we instead use the climatological atmospheric pressure at sea level, calculated from the monthly predictions for the years from 1979 through 2018. We then calculated N2O disequilibrium as DN2O = XwN2O − XaN2O, where XaN2O is the atmospheric N2O mixing ratio estimated by linear interpolation of NOAA’s flask measurement dataset (Hall&nbsp;et al., 2007) at the time and latitude of each marine N2O measurement.;</p>
<p>To convert sparse observations to a global climatology, we trained 100 ensembles of regressions trees (Random Forests) to predict DN2O based on its relationship to well-sampled physical and biogeochemical predictors. We note that, while the prediction of N2O disequilibrium is done in mixing ratio units (ppb), the results are reported in the more commonly used pressure units (natm): pN2O = XN2O . P, where P is the climatological atmospheric pressure at sea level in atm, predicted by ERA5, included as part of the relevant data file for easy conversion. (see Data File: dn2o-mapped-Yang2020.nc).&nbsp;</p>
<p>We calculate the N2O air-sea flux using two wind-speed dependent parameterizations: an updated version of a commonly-used quadratic formulation (Wanninkhof, 1992; Wanninkhof, 2014) and a recent formulation that explicitly accounts for the effect of bubble-mediated fluxes (Liang et al., 2013). We apply each parameterization to two high-resolution wind products (Copernicus Climate Change Service, 2017;&nbsp;Wentz et al., 2015), yielding four permutations of the piston velocity. In total, we obtain an ensemble of 400 global N2O air-sea flux estimates, from which we calculate a mean and uncertainty range (see Data File: n2oFlux-Yang2020.nc).</p>
<p><strong>Sampling and analytical prodcedures:</strong><br />
The data is compiled from multiple sources, published and unpublished.&nbsp; Refer to the associated Supplemental File "SuppCruiseTable_dec11.xlsx"&nbsp;for a detailed description of sampling and analytical methods associated with new data and references associated with published data. "qc" refers to "qualtiy control and methods"; see related references and descriptions in the Supplemental File.</p>
<p><strong>GOSHIP (qc1): </strong>N2O was measured using shipboard gas chromatography-electron capture detection (GC-ECD) using analytical techniques modified from those described in Bullister and Wisegarver (2008). N2O was purged from 200 mL seawater samples using N2 carrier gas and trapped onto a trap that included MS5A held at -60°C. The trap was subsequently heated to 175°C to release N2O, which was further separated and purified via two precolumns before being quantified using electron capture detection. (The carrier gas for the N2O analyses was a 95%Ar/5% CH4 mix) The analytical system was calibrated frequently using internal standards of known N2O compositions or standards from Working Group no. 143 of the Scientific Committee on Oceanic Research (SCOR) (Wilson et al. 2018). Concentrations of N2O in seawater samples and gas standards are reported relative to the SIO98 calibration scale.</p>
<p><strong>SPOT (qc3): </strong>Dissolved N2O concentrations were measured using a headspace equilibration method modified from Laperriere et al. (2019). A 30-mL ultra-high purity N2 headspace was introduced into 160 mL seawater samples using a 30-mL syringe with a second empty 30-mL syringe inserted into the septum to collect displaced sample water. Each headspace was overpressured with 10 mL of ultra high purity N2 to minimize atmospheric contamination. Samples were analyzed on an SRI 8610 Greenhouse Gas Monitoring Gas Chromatograph (GC) equipped with an electron capture detector (ECD), dual HayeSep D packed columns, and a 1-mL sample loop (SRI Instruments, Torrance, California, USA). Ultra-high purity N2 gas was used as the carrier with the sample loop kept at 60 °C and the column oven kept at 100 °C. Two certified standards, 0.1 ppm and 1 ppm N2O (Matheson Tri-Gas) were used for daily calibration using a linear calibration scheme.</p>
<p><strong>Others (qc2):</strong> N2O concentrations were measured with a GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer (CF-IRMS) as described in Bourbonnais et al. (2017). Briefly, seawater was pumped from sample bottles and completely extracted using a gas-extractor continuously sparged with He. N2O was then concentrated and purified in a purge-trap system. CO2 and H2O were removed with chemical and cryogenic traps. N2O was cryofocused with liquid N2 traps and passed through a gas chromatography (GC) column before IRMS analysis. N2O concentrations were calculated from relative peak heights between the samples and seawater standards of known N2O concentration equilibrated with the atmosphere at 5C and 20C. Equilibrium surface N2O concentrations were calculated based on the global mean atmospheric N2O dry mole fraction at the time of the cruise. The data were inter calibrated with samples also measured using purge-trap gas extraction systems coupled with either a GC-Electron Capture Detector (ECD) or a GC-quadrupole mass spectrometer (Fenwick et al., 2017) when available (e.g., P18 GO-SHIP, ArcticNet 2017 expedition) and yielded comparable N2O concentrations (generally less than 5% difference).</p>
<p>The data is compiled from multiple sources, published and unpublished. Refer to the Supplemental File, "SuppCruiseTable_dec11.xlsx", for a detailed description of sampling and analytical methods associated with new data and references associated with published data.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1847687 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1847687
completed
Daniele Bianchi
University of California-Los Angeles
310-825-6936
UCLA Atmospheric & Oceanic Sciences Box 951565
Los Angeles
CA
90095
USA
dbianchi@atmos.ucla.edu
pointOfContact
Simon Yang
University of California-Los Angeles
310-825-6936
520 Portola Plaza 7127 Math Sciences
Los Angeles
CA
90095
USA
simon.yang.ch@gmail.com
pointOfContact
asNeeded
Dataset Version: 1
Unknown
cruise
date
year
month
day
latitude
longitude
depth
n2o_ppb
n2o_nM
dn2o_ppb
atmPressure
temperature
salinity
Shipboard gas chromatography-electron capture detection
GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer
theme
None, User defined
cruise name
date
year
month of year
day of month
latitude
longitude
depth
Nitrous Oxide
barometric pressure
water temperature at measurement depth
salinity
featureType
BCO-DMO Standard Parameters
Gas Chromatograph
Isotope-ratio Mass Spectrometer
instrument
BCO-DMO Standard Instruments
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
CAREER: Multiple Scales of Nitrogen Cycle in Oxygen Minimum Zones
https://osprey.bco-dmo.org/project/809665
CAREER: Multiple Scales of Nitrogen Cycle in Oxygen Minimum Zones
<p><em>NSF Award Abstract:</em><br />
The nitrogen cycle in the ocean is key to ocean productivity, carbon storage, and emissions of nitrous oxide, a potent greenhouse gas, to the atmosphere. The chemical processes that connect nitrogen species in the ocean are sensitive to the amount of oxygen dissolved in seawater. These reactions become more intense within oxygen minimum zones, areas of the ocean with little or no dissolved oxygen. Oxygen minimum zones are affected by currents that range in scale from hundreds to less than few kilometers. These currents create microhabitats where nitrogen cycling and nitrous oxide emissions are higher. This project investigates the interaction between small-scale ocean circulation, oxygen availability, and the nitrogen cycle. It uses a series of increasingly finer-scale numerical simulations of the Pacific Ocean, where two of the largest oxygen minimum zones are found. These simulations provide information about nitrogen transformations and nitrous oxide emissions on timescales from less than one year to several decades, and spatial scales from a few kilometers to the basin scale. This research will increase our ability to simulate and predict ocean responses to natural and human disturbances, with implications for society. The educational component of the project establishes a series of ocean-going chemical oceanography activities for approximately 100 undergraduate students at the University of California at Los Angeles each year. The field trips involve half-day cruises in the Santa Monica Bay, where students sample a variety of biogeochemical properties. Observations collected during the field trips will be used as a resource in classroom activities and student research projects. The field trips and educational materials offer opportunities to explore cutting-edge questions in ocean biogeochemistry, increase student interest in ocean sciences and access to research, and enhance student learning and self-efficacy, ultimately promoting retention in oceanography and STEM.</p>
<p>Oxygen minimum zones host major nitrogen transformations, including denitrification, anammox, and nitrous oxide production, which are essential for biogeochemistry and climate. These reactions are strongly partitioned along oxygen gradients in the suboxic range, making them sensitive to ventilation and chemical heterogeneity driven by variable ocean currents. However, the nature of this sensitivity is poorly understood. The objective of this project is to test the hypothesis that physical circulation at scales from tens of kilometers (mesoscale) to less than one kilometer (submesoscale) is critical in shaping these nitrogen cycle transformations. To test the hypothesis and investigate its implications, we will optimize a new model of the nitrogen cycle against a range of recent observations, and implement it in a realistic three-dimensional hydrodynamic-biogeochemical model. We will adopt a nesting strategy to downscale a Pacific-wide historical simulation to a series of regional domains at resolutions down to few kilometers or less, resolving the oxygen minimum zone boundaries and their fine-scale variability. By analyzing these model solutions, we will: (1) constrain the sensitivity of the microbial nitrogen cycle to oxygen, ventilation, and chemical heterogeneity; (2) in light of this sensitivity, quantify the role of mesoscale and submesoscale processes in shaping nitrogen transformations and transport across oxygen minimum zone boundaries; and (3) investigate the response of the nitrogen cycle to climate variability, in particular fixed-nitrogen losses and nitrous oxide emissions to the atmosphere.</p>
Multiple Scales of Nitrogen Cycle in the Ocean
largerWorkCitation
project
eng; USA
oceans
-180
180
-77.177
88.3943333
1971-06-09
2018-06-04
Global
0
BCO-DMO catalogue of parameters from Global reconstruction of surface oceanic N2O disequilibrium and its associated flux
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/810105.rdf
Name: cruise
Units: unitless
Description: <p>Cruise name</p>
http://lod.bco-dmo.org/id/dataset-parameter/810106.rdf
Name: date
Units: unitless
Description: <p>Date; format: YYYY-MM-DD</p>
http://lod.bco-dmo.org/id/dataset-parameter/810107.rdf
Name: year
Units: unitless
Description: <p>Measurement year; format: YYYY</p>
http://lod.bco-dmo.org/id/dataset-parameter/810108.rdf
Name: month
Units: unitless
Description: <p>Measurement month; format: MM</p>
http://lod.bco-dmo.org/id/dataset-parameter/810109.rdf
Name: day
Units: unitless
Description: <p>Measurement day; format: DD</p>
http://lod.bco-dmo.org/id/dataset-parameter/810110.rdf
Name: latitude
Units: degrees North
Description: <p>Measurement latitude</p>
http://lod.bco-dmo.org/id/dataset-parameter/810111.rdf
Name: longitude
Units: degrees East
Description: <p>Measurement longitude</p>
http://lod.bco-dmo.org/id/dataset-parameter/810112.rdf
Name: depth
Units: meters (positive down)
Description: <p>Measurement depth</p>
http://lod.bco-dmo.org/id/dataset-parameter/810113.rdf
Name: n2o_ppb
Units: ppb
Description: <p>Ocean n2o mixing ratio</p>
http://lod.bco-dmo.org/id/dataset-parameter/810114.rdf
Name: n2o_nM
Units: nmol/L
Description: <p>Ocean n2o mixing ratio</p>
http://lod.bco-dmo.org/id/dataset-parameter/810115.rdf
Name: dn2o_ppb
Units: ppb
Description: <p>Estimated n2o disequilibrium</p>
http://lod.bco-dmo.org/id/dataset-parameter/810116.rdf
Name: atmPressure
Units: atm
Description: <p>Sea level pressure estimated at observed time and location</p>
http://lod.bco-dmo.org/id/dataset-parameter/810117.rdf
Name: temperature
Units: degrees Celsius
Description: <p>Co-measured temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/810118.rdf
Name: salinity
Units: g/kg
Description: <p>Co-measured salinity (or estimated from climatology if absent)</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
375341667
https://darchive.mblwhoilibrary.org/bitstream/1912/25729/1/n2oFlux-Yang2020.nc
download
10383037
https://darchive.mblwhoilibrary.org/bitstream/1912/25729/2/n2oDataYang2020PNAS.mat
download
178944231
https://darchive.mblwhoilibrary.org/bitstream/1912/25729/3/dn2o-mapped-Yang2020.nc
download
20028058
https://darchive.mblwhoilibrary.org/bitstream/1912/25729/4/dataset-810032_n2o-global-reconstruction__v1.tsv
download
https://doi.org/10.26008/1912/bco-dmo.810032.1
download
onLine
dataset
<p>We compiled surface (0m-12m depth) marine N2O concentrations and partial pressures measurements from a variety of sources. The core of the data is sourced from the MEMENTO database (Kock&nbsp;&amp; Bange, 2015). We complement MEMENTO with additional published N2O measurements from the literature, and unpublished N2O measurements from 16 additional cruises (see Supplemental File "SuppCruiseTable_dec11.xlsx"), including 11 cruises from the Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP). We do not perform any further quality control of the N2O data from published sources besides that performed by the individual contributors and the MEMENTO database administrators (Kock&nbsp;&amp; Bange, 2015). A description of the quality control performed on new unpublished N2O data is reported as footnotes to the annotations labeled as qc1**, qc2**, or qc3** (see "SuppCruiseTable_dec11.xlsx"). We convert each marine N2O measurement to XwN2O (the N2O mixing ratio in seawater, in units of ppb) using, when needed, the N2O solubility coefficient (Weiss &amp; Price, 1980). The coefficient is calculated using co-measured temperature, and salinity, as well as sea level pressure from the ERA5 reanalysis (Copernicus Climate Change Service, 2017), at the time (month and year), and location of the measurement. If the measurement time is not available in the ERA5 reanalysis prediction, we instead use the climatological atmospheric pressure at sea level, calculated from the monthly predictions for the years from 1979 through 2018. We then calculated N2O disequilibrium as DN2O = XwN2O − XaN2O, where XaN2O is the atmospheric N2O mixing ratio estimated by linear interpolation of NOAA’s flask measurement dataset (Hall&nbsp;et al., 2007) at the time and latitude of each marine N2O measurement.;</p>
<p>To convert sparse observations to a global climatology, we trained 100 ensembles of regressions trees (Random Forests) to predict DN2O based on its relationship to well-sampled physical and biogeochemical predictors. We note that, while the prediction of N2O disequilibrium is done in mixing ratio units (ppb), the results are reported in the more commonly used pressure units (natm): pN2O = XN2O . P, where P is the climatological atmospheric pressure at sea level in atm, predicted by ERA5, included as part of the relevant data file for easy conversion. (see Data File: dn2o-mapped-Yang2020.nc).&nbsp;</p>
<p>We calculate the N2O air-sea flux using two wind-speed dependent parameterizations: an updated version of a commonly-used quadratic formulation (Wanninkhof, 1992; Wanninkhof, 2014) and a recent formulation that explicitly accounts for the effect of bubble-mediated fluxes (Liang et al., 2013). We apply each parameterization to two high-resolution wind products (Copernicus Climate Change Service, 2017;&nbsp;Wentz et al., 2015), yielding four permutations of the piston velocity. In total, we obtain an ensemble of 400 global N2O air-sea flux estimates, from which we calculate a mean and uncertainty range (see Data File: n2oFlux-Yang2020.nc).</p>
<p><strong>Sampling and analytical prodcedures:</strong><br />
The data is compiled from multiple sources, published and unpublished.&nbsp; Refer to the associated Supplemental File "SuppCruiseTable_dec11.xlsx"&nbsp;for a detailed description of sampling and analytical methods associated with new data and references associated with published data. "qc" refers to "qualtiy control and methods"; see related references and descriptions in the Supplemental File.</p>
<p><strong>GOSHIP (qc1): </strong>N2O was measured using shipboard gas chromatography-electron capture detection (GC-ECD) using analytical techniques modified from those described in Bullister and Wisegarver (2008). N2O was purged from 200 mL seawater samples using N2 carrier gas and trapped onto a trap that included MS5A held at -60°C. The trap was subsequently heated to 175°C to release N2O, which was further separated and purified via two precolumns before being quantified using electron capture detection. (The carrier gas for the N2O analyses was a 95%Ar/5% CH4 mix) The analytical system was calibrated frequently using internal standards of known N2O compositions or standards from Working Group no. 143 of the Scientific Committee on Oceanic Research (SCOR) (Wilson et al. 2018). Concentrations of N2O in seawater samples and gas standards are reported relative to the SIO98 calibration scale.</p>
<p><strong>SPOT (qc3): </strong>Dissolved N2O concentrations were measured using a headspace equilibration method modified from Laperriere et al. (2019). A 30-mL ultra-high purity N2 headspace was introduced into 160 mL seawater samples using a 30-mL syringe with a second empty 30-mL syringe inserted into the septum to collect displaced sample water. Each headspace was overpressured with 10 mL of ultra high purity N2 to minimize atmospheric contamination. Samples were analyzed on an SRI 8610 Greenhouse Gas Monitoring Gas Chromatograph (GC) equipped with an electron capture detector (ECD), dual HayeSep D packed columns, and a 1-mL sample loop (SRI Instruments, Torrance, California, USA). Ultra-high purity N2 gas was used as the carrier with the sample loop kept at 60 °C and the column oven kept at 100 °C. Two certified standards, 0.1 ppm and 1 ppm N2O (Matheson Tri-Gas) were used for daily calibration using a linear calibration scheme.</p>
<p><strong>Others (qc2):</strong> N2O concentrations were measured with a GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer (CF-IRMS) as described in Bourbonnais et al. (2017). Briefly, seawater was pumped from sample bottles and completely extracted using a gas-extractor continuously sparged with He. N2O was then concentrated and purified in a purge-trap system. CO2 and H2O were removed with chemical and cryogenic traps. N2O was cryofocused with liquid N2 traps and passed through a gas chromatography (GC) column before IRMS analysis. N2O concentrations were calculated from relative peak heights between the samples and seawater standards of known N2O concentration equilibrated with the atmosphere at 5C and 20C. Equilibrium surface N2O concentrations were calculated based on the global mean atmospheric N2O dry mole fraction at the time of the cruise. The data were inter calibrated with samples also measured using purge-trap gas extraction systems coupled with either a GC-Electron Capture Detector (ECD) or a GC-quadrupole mass spectrometer (Fenwick et al., 2017) when available (e.g., P18 GO-SHIP, ArcticNet 2017 expedition) and yielded comparable N2O concentrations (generally less than 5% difference).</p>
<p>The data is compiled from multiple sources, published and unpublished. Refer to the Supplemental File, "SuppCruiseTable_dec11.xlsx", for a detailed description of sampling and analytical methods associated with new data and references associated with published data.</p>
Specified by the Principal Investigator(s)
<p><strong>Data Processing:</strong><br />
The N2O disequilibrium at the location of each measurement is estimated following: _DXN2O = XN2O_ocean − XN2O_atm. Here, XN2O_ocean is the ocean-side N2O measurement converted to mixing ratios, and XN2O_ atm is the atmospheric N2O mixing ratio estimated by interpolating the National Oceanic and Atmospheric Administration atmospheric N2O flask dataset at the latitude and time of the oceanic measurements.</p>
<p><strong>BCO-DMO Processing</strong>:<br />
added "date" column as YYYY-MM-DD.</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Shipboard gas chromatography-electron capture detection
Shipboard gas chromatography-electron capture detection
PI Supplied Instrument Name: Shipboard gas chromatography-electron capture detection PI Supplied Instrument Description:GOSHIP: Shipboard gas chromatography-electron capture detection (GC-ECD)
SPOT: SRI 8610 Greenhouse Gas Monitoring Gas Chromatograph (GC) equipped with an electron capture detector (ECD), dual HayeSep D packed columns, and a 1-mL sample loop (SRI Instruments, Torrance, California, USA). Instrument Name: Gas Chromatograph Instrument Short Name:Gas Chromatograph Instrument Description: Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC) Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB02/
GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer
GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer
PI Supplied Instrument Name: GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer PI Supplied Instrument Description:Others (see qc2): GV IsoPrime Continuous Flow Isotope-Ratio Mass Spectrometer (CF-IRMS) Instrument Name: Isotope-ratio Mass Spectrometer Instrument Short Name:IR Mass Spec; IRMS Instrument Description: The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer). Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB16/