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Dataset Title:  Chemical composition of 'model' Primary Marine Aerosol (mPMA) and seawater
measured on R/V Endeavor EN589 during Sept. - Oct. 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_750917)
Range: longitude = -71.16 to -64.78°E, latitude = 35.04 to 41.4°N, time = 2016-09-18T09:55:00Z to 2016-10-14T14:37:00Z
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Campaign_Sequence_Number {
    Int16 _FillValue 32767;
    Int16 actual_range 26, 316;
    String bcodmo_name "sample";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Campaign sequence number corresponding to a given set of generator operating conditions as detailed in the companion file (EN589 Marine Aerosol Generator Operating Conditions).";
    String long_name "Campaign Sequence Number";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  Sample_Type {
    String bcodmo_name "sample_type";
    String description "Sample type:  Size-resolved mPMA sampled with a cascade impactor (CI); bulk mPMA sampled on a quartz filter (B); bulk mPMA sampled on a Teflon filter for photochemical manipulation experiments (P); or seawater (S).";
    String long_name "Sample Type";
    String units "unitless";
  }
  Sample_ID {
    Byte _FillValue 127;
    Byte actual_range 1, 33;
    String bcodmo_name "sample";
    String description "Sample ID number";
    String long_name "Sample ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  CI_50_Aerodynamic_Cut_Diam {
    String bcodmo_name "unknown";
    String description "Aerodynamic cut diameter for CI samples (µm at ambient relative humidity).";
    String long_name "CI 50 Aerodynamic Cut Diam";
    String units "micrometers";
  }
  S_Sample_Location {
    String bcodmo_name "unknown";
    String description "Location at which seawater was sampled (I denotes inlet to generator; O denotes outlet from generator).  Duplicate measurements at the same time and location are denoted by 'Dup'.";
    String long_name "S Sample Location";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 35.04, 41.4;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "general latitude of sampling; north is positive [added by BCO-DMO from supplemental doc]";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -71.16, -64.78;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "general longitude of sampling; east is positive [added by BCO-DMO from supplemental doc]";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4741925e+9, 1.47645582e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_Local";
    String description "Size-resolved and bulk mPMA sample start date and time or seawater sampling date and time; ISO 8601:2004E format.";
    String ioos_category "Time";
    String long_name "ISO Date Time Local Start";
    String source_name "ISO_DateTime_local_start";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  ISO_DateTime_local_end {
    String bcodmo_name "ISO_DateTime_Local";
    String description "Size-resolved and bulk mPMA sample stop date and time; ISO 8601:2004E format.";
    String long_name "ISO Date Time Local End";
    String units "unitless";
  }
  Cl {
    Float32 _FillValue NaN;
    Float32 actual_range 37.64, 593038.0;
    String bcodmo_name "chloride";
    String description "Cl- concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String long_name "CL";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  Br {
    Float32 _FillValue NaN;
    Float32 actual_range 0.05, 878.0;
    String bcodmo_name "bromides";
    String description "Br- concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String long_name "BR";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  SO4 {
    Float32 _FillValue NaN;
    Float32 actual_range 1.78, 30768.0;
    String bcodmo_name "SO4";
    String description "SO42- concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String long_name "SO4";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/SPHTMAXX/";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  Na {
    Float32 _FillValue NaN;
    Float32 actual_range 32.12, 508094.0;
    String bcodmo_name "Na";
    String description "Na+ concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  K {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 10305.0;
    String bcodmo_name "K";
    String description "K+ concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String long_name "K";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  Mg {
    Float32 _FillValue NaN;
    Float32 actual_range 2.88, 54581.0;
    String bcodmo_name "Mg";
    String description "Mg2+ concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String long_name "MG";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  Ca {
    Float32 _FillValue NaN;
    Float32 actual_range 0.07, 11080.0;
    String bcodmo_name "Ca";
    String description "Ca2+ concentration:  For mPMA in nmol m-3 air; for seawater in µM.";
    String long_name "Ca";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  OCwe {
    Float32 _FillValue NaN;
    Float32 actual_range 1.51, 66.59;
    String bcodmo_name "C_org";
    String description "Water-extractable organic carbon (OCwe) concentration for mPMA in nmol C m-3 air.";
    String long_name "OCwe";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOZX/";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  OCwe_STD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 2.88;
    String bcodmo_name "C_org";
    String description "OCwe precision for mPMA in nmol C m-3 air";
    String long_name "OCwe STD";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOZX/";
    String units "nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S";
  }
  Comments {
    String bcodmo_name "comment";
    String description "Comments";
    String long_name "Comments";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"The ionic data reported in this file were generated by William Keene
([wck@virginia.edu](\\\\\"mailto:wck@virginia.edu\\\\\")) and John Maben and the
OCwe data were generated by David Kieber
([djkieber@esf.edu](\\\\\"mailto:djkieber@esf.edu\\\\\")). Please direct any related
questions accordingly.
 
Sampling and Analytical Methods: Samples were collected on RV/Endeavor cruise
589. Locations, times, and conditions at the four hydrographic stations are
available under Supplemental Documentation. During some periods, size-resolved
mPMA was sampled from the generator\\u2019s headspace at 30 L min-1 with two
non-rotating Multi-Orifice Uniform Deposit Impactors (MOUDIs, [Marple et al.,
1991]) operated in parallel. Substrates and back filters from one impactor
were analyzed for major ions and those from the other impactor were analyzed
for water extractable organic carbon (OCwe). The aerodynamic cut diameters for
the impactor\\u2019s size fractions were 18, 10, 5.6, 3.2, 1.8, 1.0, 0.56,
0.32, and 0.18 \\u00b5m. Impactors were configured with precombusted 47-mm
diameter aluminum substrates and 37-mm diameter quartz backup filters.
 
During some periods, bulk mPMA was sampled in parallel at 30 L min-1 on two
precombusted 47-mm quartz filters, one of which was analyzed for major ions,
OCwe, and surfactants and the other for total OC and radiocarbon age.
 
During two periods, bulk mPMA was sampled in parallel at 30 L min-1 on two
90-mm Teflon filters. One sample was analyzed for major ions and OCwe and the
other was stored for photochemical manipulation experiments.
 
After recovery, samples of size-resolved and bulk mPMA for analysis of major
ions were transferred to precleaned 10-mL HDPE tubes, stored frozen,
subsequently extracted in 5 mL deionized water (DIW), and analyzed at the
University of Virginia (UVA) using a Dionex duel channel model ICS 3000 high-
performance ion chromatograph (IC). The anion channel was configured with
Thermo Scientific Dionex guard (IonPac AG 18: 4 x 50 mm) and analytical
separator (IonPac AS 18: 4 x 250mm) columns and electrolytically regenerated
suppressor (AERS 500: 4mm). The cation channel was configured Dionex Guard
(IonPac CG16: 5 x 50mm) and analytical separator (IonPac CG16: 5 x 250mm)
columns and a Thermo Scientific Dionex electrolytically regenerated suppressor
(CERS 500: 4mm).
 
Size-segregated mPMA sampled with cascade impactors and in bulk on quartz
filters for analysis of OCwe were transferred to precombusted 10-mL Pyrex
tubes, extracted immediately after recovery in 5 mL DIW, stored frozen, and
analyzed in triplicate with a Shimadzu Model TOC-V CSH carbon analyzer at the
State University of New York (SUNY).
 
Bulk mPMA sampled on Teflon filters were extracted immediately after recovery
in five sequential aliquots of DIW (total of 25 mL). Subsamples of extracts
were stored frozen on site and analyzed for major ions at UVA and for OCwe at
SUNY using methods described above.
 
Data for mPMA samples were corrected based on median concentrations of
analytes measured in dynamic handling blanks (N = 5 for impactor and 8 for
bulk samples) that were loaded and unloaded during the campaign and
subsequently processed and analyzed using procedures identical to those used
for samples.
 
Unfiltered seawater for analysis of major ions was sampled in precleaned 10-mL
HDPE tubes, stored frozen, and analyzed by IC at UVA.
 
Average detection limits (DLs) for mPMA analytes were estimated following
Keene et al. [1989, JGR] and are summarized (see Supplemental Documents)
 
Average precisions for inorganic mPMA analytes are estimated to be \\u00b14% of
the measured concentrations or \\u00b10.5*DLs, whichever are the greater
absolute values. Precisions for OCwe correspond to the standard deviations for
triplicate measurements.
 
Measured concentrations of all ionic constituents in seawater were
substantially higher than estimated DLs. Average precisions are approximately
\\u00b12% of the measured concentrations.
 
Refer to the following papers for additional details regarding the design and
operation of the marine aerosol generator, analytical methods, and data
quality.";
    String awards_0_award_nid "708309";
    String awards_0_award_number "OCE-1536608";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1536608";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String awards_1_award_nid "708317";
    String awards_1_award_number "OCE-1536605";
    String awards_1_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1536605";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Henrietta N Edmonds";
    String awards_1_program_manager_nid "51517";
    String awards_2_award_nid "708320";
    String awards_2_award_number "OCE-1536674";
    String awards_2_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1536674";
    String awards_2_funder_name "NSF Division of Ocean Sciences";
    String awards_2_funding_acronym "NSF OCE";
    String awards_2_funding_source_nid "355";
    String awards_2_program_manager "Henrietta N Edmonds";
    String awards_2_program_manager_nid "51517";
    String awards_3_award_nid "708323";
    String awards_3_award_number "OCE-1536597";
    String awards_3_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1536597";
    String awards_3_funder_name "NSF Division of Ocean Sciences";
    String awards_3_funding_acronym "NSF OCE";
    String awards_3_funding_source_nid "355";
    String awards_3_program_manager "Henrietta N Edmonds";
    String awards_3_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"EN589 Aerosol and Seawater Composition 
   PI: W. Keene (UVA) 
   version: 2018-12-31";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2018-12-05T19:26:56Z";
    String date_modified "2019-03-18T13:45:54Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.750917.1";
    Float64 Easternmost_Easting -64.78;
    Float64 geospatial_lat_max 41.4;
    Float64 geospatial_lat_min 35.04;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.78;
    Float64 geospatial_lon_min -71.16;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-03-28T09:54:29Z (local files)
2024-03-28T09:54:29Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_750917.das";
    String infoUrl "https://www.bco-dmo.org/dataset/750917";
    String institution "BCO-DMO";
    String instruments_0_acronym "TOC analyzer";
    String instruments_0_dataset_instrument_description "Used to measure total organic carbon concentration";
    String instruments_0_dataset_instrument_nid "750939";
    String instruments_0_description "A unit that accurately determines the carbon concentrations of organic compounds typically by detecting and measuring its combustion product (CO2). See description document at: http://bcodata.whoi.edu/LaurentianGreatLakes_Chemistry/bs116.pdf";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB04/";
    String instruments_0_instrument_name "Total Organic Carbon Analyzer";
    String instruments_0_instrument_nid "652";
    String instruments_0_supplied_name "Shimadzu Model TOC-V CSH carbon analyzer";
    String keywords "aerodynamic, bco, bco-dmo, biological, campaign, Campaign_Sequence_Number, chemical, CI_50_Aerodynamic_Cut_Diam, comments, cut, data, dataset, date, depth, diam, dmo, end, erddap, iso, ISO_DateTime_local_end, latitude, local, longitude, management, number, oceanography, ocwe, OCwe_STD, office, preliminary, profiler, S_Sample_Location, salinity, salinity-temperature-depth, sample, Sample_ID, Sample_Type, sequence, so4, start, std, temperature, time, type";
    String license "https://www.bco-dmo.org/dataset/750917/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/750917";
    Float64 Northernmost_Northing 41.4;
    String param_mapping "{'750917': {'lat': 'master - latitude', 'lon': 'master - longitude', 'ISO_DateTime_local_start': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/750917/parameters";
    String people_0_affiliation "University of Virginia";
    String people_0_affiliation_acronym "UVA";
    String people_0_person_name "William C. Keene";
    String people_0_person_nid "708330";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Refractory DOC Recycling";
    String projects_0_acronym "Refractory DOC Recycling";
    String projects_0_description 
"The oceans hold a massive quantity of organic carbon that is greater than all terrestrial organic carbon biomass combined. Nearly all marine organic carbon is dissolved and more than 95% is refractory, and cycled through the oceans several times before complete removal. Refractory dissolved organic carbon (RDOC) concentrations are uniform with depth in the water column and represent the \"background\" carbon present throughout the oceans. However, very little is known regarding RDOC production and removal processes. One potential removal pathway is through adsorption of RDOC onto surfaces of rising bubbles produced by breaking waves and ejection via bubble bursting into the atmosphere. Building on prior research, the investigators will evaluate the importance of ocean- atmosphere processing in recycling marine RDOC during a research cruise in the northwestern Atlantic Ocean. Results of the research will provide important insights regarding the coupled ocean-atmosphere loss of RDOC, thereby improving understanding of and ability to predict the role of RDOC in oceanic and atmospheric biogeochemistry, the global carbon cycle, and Earth's climate. The research will involve three early career faculty, and will provide training for undergraduate and graduate researchers.
Recent results based on a limited set of observations indicate that the organic matter (OM) associated with primary marine aerosol (PMA) produced by bursting bubbles from breaking waves at the sea surface is comprised partly to wholly of RDOC rather than OM of recent biological origin as has been widely assumed. The injection of RDOC into the atmosphere in association with PMA and its subsequent photochemical oxidation is a potentially important and hitherto unrecognized sink for RDOC in the oceans of sufficient magnitude to close the marine carbon budget and help resolve a long-standing conundrum regarding removal mechanisms for marine RDOC. This project will involve a shipboard investigation and modeling study to (1) quantify the relative contributions of marine refractory dissolved organic carbon (RDOC) to primary marine aerosol organic matter (PMA OM) produced from near-surface seawater in biologically productive and oligotrophic regions and from North Atlantic Deep Water, and to (2) determine the importance of atmospheric photochemical processing as a recycling pathway for RDOC. To test these hypotheses, a high-capacity aerosol generator will be deployed at four hydrographic stations in the NW Atlantic Ocean to characterize (1) the natural abundance of 14C in PMA and in surface and deep seawater; (2) the surface tension and physical properties of bubble plumes; (3) size-resolved production fluxes, chemical composition, organic carbon enrichments, spectral absorbance, and photochemical evolution of PMA; and (4) the carbon content, optical properties, and physical properties of seawater. The importance of RDOC recycling via PMA production and photochemical evolution will be interpreted with model calculations.
EN589 Cruise Track";
    String projects_0_end_date "2018-12";
    String projects_0_geolocation "Northwest Atlantic Ocean";
    String projects_0_name "Collaborative Research: Coupled Ocean-Atmosphere Recycling of Refractory Dissolved Organic Carbon in Seawater";
    String projects_0_project_nid "708310";
    String projects_0_start_date "2015-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 35.04;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset describes the ionic composition of western North Atlantic seawater and the corresponding chemical composition of mPMA produced from that seawater in a high-capacity generator over ranges of operating conditions. Measurements were taken during cruise EN589 on RV/Endeavor during September and October 2016.";
    String time_coverage_end "2016-10-14T14:37:00Z";
    String time_coverage_start "2016-09-18T09:55:00Z";
    String title "Chemical composition of 'model' Primary Marine Aerosol (mPMA) and seawater measured on R/V Endeavor EN589 during Sept. - Oct. 2016";
    String version "1";
    Float64 Westernmost_Easting -71.16;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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