[Directory] [Data...]

Data server object:  ES_2017_porewater




  
    Chemical analysis from sediment core pore water samples collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017
    
  
  
    
    

Chemical analysis from sediment core pore water samples collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017

Website: https://www.bco-dmo.org/dataset/745905
Data Type: Other Field Results
Version: 1
Version Date: 2018-10-15

Project
» Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2 (Seagrass Blue Carbon)
ContributorsAffiliationRole
Burdige, David J.Old Dominion University (ODU)Principal Investigator
Long, MatthewWoods Hole Oceanographic Institution (WHOI)Co-Principal Investigator
Zimmerman, Richard C.Old Dominion University (ODU)Co-Principal Investigator
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
This dataset includes results of analysis on sediment cores collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017 - initial pH, alkalinity, sulfate, DIC, Fe, NH4, sulfide, and DOC.


Coverage

Spatial Extent: N:37.344 E:-75.798 S:37.266 W:-75.835
Temporal Extent: 2017-07-12 - 2017-07-21

Dataset Description

This dataset includes results of analysis on sediment cores collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017 - initial pH, alkalinity, sulfate, DIC, Fe, NH4, sulfide, and DOC.


Acquisition Description

Sediment cores were collected by divers, sealed in the field with rubber stoppers and returned to the lab for processing. Pore waters were collected by inserting rhizon samplers (Seeberg-Elverfeldt et al., 2005) through pre-drilled holes in the core tubes. Samples were collected in gas-tight glass syringes and filtered through 0.45 µm nylon filters into storage vials. Alkalinity samples were titrated within 12hr of collection; other samples were returned to the lab for analysis, using techniques routinely used in my lab: alkalinity and initial pH - Hu and Burdige (2008); sulfate, DIC, ammonium and DOC - Burdige and Komada (2011), Komada et al. (2016); sulfide - Cline (1969), Abdulla et al. (in prep.).

Alkalinity and initial pH were determined by Gran Titration using a Metrohm automatic titrator (model 785 DMP Titrino) combined with a Cole-Parmer pH electrode, calibrated using pH 4.00, 7.00 and 10.00 NIST-traceable buffers (Hu and Burdige, 2008).  Sulfate was determined by ion chromatography and conductivity detection with a Thermo-Fisher Dionex ICS-5000 ion chromatograph, while DOC was determined by high-temperature combustion using a Shimadzu TOC-V total carbon analyzer (Burdige and Komada, 2011; Komada et al. 2016).  Ammonium and DIC were determined by FIA analysis using a home-built system consisting of a Rainin Rabbit peristaltic pump and a Dionex CDM-II conductivity detector (Hall and Aller, 1992; Lustwerk and Burdige, 1995).  Total dissolved sulfide was determined spectrophotometrically with an Ocean Optics USB400 UV-Vis spectrophotometer (Cline, 1969; Abdulla et al., in prep.); Total dissolved iron was also determined spectrophotometrically by the ferrozine method using the same spectrophotometer  (Viollier et al., 2000).

Note: "ns" stands for "samples not collected for this analysis".


Processing Description

BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- added columns for site, lat, and lon


[ table of contents | back to top ]

Related Publications

Abdulla, H. A., D. J. Burdige, and T. Komada. Formation of abiotic dissolved organic sulfur in anoxic sediment of Santa Barbara Basin. in prep. for Org Geochem. [details]
Burdige, D. J., & Komada, T. (2011). Anaerobic oxidation of methane and the stoichiometry of remineralization processes in continental margin sediments. Limnology and Oceanography, 56(5), 1781–1796. doi:10.4319/lo.2011.56.5.1781 [details]
CLINE, J. D. (1969). SPECTROPHOTOMETRIC DETERMINATION OF HYDROGEN SULFIDE IN NATURAL WATERS1. Limnology and Oceanography, 14(3), 454–458. doi:10.4319/lo.1969.14.3.0454 [details]
Hall, P. . J., & Aller, R. C. (1992). Rapid, small-volume, flow injection analysis for total CO2, and NH4+ in marine and freshwaters. Limnology and Oceanography, 37(5), 1113–1119. doi:10.4319/lo.1992.37.5.1113 [details]
Hu, X., & Burdige, D. J. (2008). Shallow marine carbonate dissolution and early diagenesis—Implications from an incubation study. Journal of Marine Research, 66(4), 489–527. doi:10.1357/002224008787157449 [details]
Komada, T., Burdige, D. J., Li, H.-L., Magen, C., Chanton, J. P., & Cada, A. K. (2016). Organic matter cycling across the sulfate-methane transition zone of the Santa Barbara Basin, California Borderland. Geochimica et Cosmochimica Acta, 176, 259–278. doi:10.1016/j.gca.2015.12.022 [details]
Lustwerk, R. L., & Burdige, D. J. (1995). Elimination of dissolved sulfide interference in the flow injection determination of SCO2, by addition of molybdate. Limnology and Oceanography, 40(5), 1011–1012. doi:10.4319/lo.1995.40.5.1011 [details]
Seeberg-Elverfeldt, J., Schlüter, M., Feseker, T., & Kölling, M. (2005). Rhizon sampling of porewaters near the sediment-water interface of aquatic systems. Limnology and Oceanography: Methods, 3(8), 361–371. doi:10.4319/lom.2005.3.361 [details]

[ table of contents | back to top ]

Parameters

ParameterDescriptionUnits
sitesample collection site identifier unitless
Corecore number unitless
Depth_cmdepth in the core (relative to the sediment surface) centimeters
Initial_pHinitial pH determined during alkalinity titrations NBS scale
Alkalinity_mMpore water alkalinity milliMoles
Sulfate_mMpore water sulfate milliMoles
DIC_mMpore water dissolved inorganic carbon milliMoles
Fe_uMpore water dissolved iron microMoles
NH4_uMpore water dissolved ammonium microMoles
Sulfide_uMpore water total dissolved sulfide microMoles
DOC_uMpore water dissolved organic carbon microMoles
latlatitude; north is positive decimal degrees
lonlongitude; east is positive decimal degrees


[ table of contents | back to top ]

Instruments

Dataset-specific Instrument Name
Shimadzu TOC-V total carbon analyzer
Generic Instrument Name
Total Organic Carbon Analyzer
Dataset-specific Description
Used to measure dissolved organic carbon
Generic Instrument 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

Dataset-specific Instrument Name
Thermo-Fisher Dionex ICS-5000 ion chromatograph
Generic Instrument Name
Ion Chromatograph
Dataset-specific Description
Used to measure sulfate
Generic Instrument Description
Ion chromatography is a form of liquid chromatography that measures concentrations of ionic species by separating them based on their interaction with a resin. Ionic species separate differently depending on species type and size. Ion chromatographs are able to measure concentrations of major anions, such as fluoride, chloride, nitrate, nitrite, and sulfate, as well as major cations such as lithium, sodium, ammonium, potassium, calcium, and magnesium in the parts-per-billion (ppb) range. (from http://serc.carleton.edu/microbelife/research_methods/biogeochemical/ic....)

Dataset-specific Instrument Name
Cole-Parmer pH electrode
Generic Instrument Name
Benchtop pH Meter
Dataset-specific Description
Used to measure pH
Generic Instrument Description
An instrument consisting of an electronic voltmeter and pH-responsive electrode that gives a direct conversion of voltage differences to differences of pH at the measurement temperature. (McGraw-Hill Dictionary of Scientific and Technical Terms) This instrument does not map to the NERC instrument vocabulary term for 'pH Sensor' which measures values in the water column. Benchtop models are typically employed for stationary lab applications.

Dataset-specific Instrument Name
Metrohm automatic titrator (model 785 DMP Titrino)
Generic Instrument Name
Automatic titrator
Dataset-specific Description
Used to measure alkalinity and pH.
Generic Instrument Description
Instruments that incrementally add quantified aliquots of a reagent to a sample until the end-point of a chemical reaction is reached.

Dataset-specific Instrument Name
Ocean Optics USB400 UV-Vis spectrophotometer
Generic Instrument Name
Spectrophotometer
Dataset-specific Description
Used to measure total dissolved sulfide and t​otal dissolved iron
Generic Instrument Description
An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.

Dataset-specific Instrument Name
Dionex CDM-II conductivity detector
Generic Instrument Name
Conductivity Meter
Dataset-specific Description
Used to measure ammonium and dissolved inorganic carbon
Generic Instrument Description
Conductivity Meter - An electrical conductivity meter (EC meter) measures the electrical conductivity in a solution. Commonly used in hydroponics, aquaculture and freshwater systems to monitor the amount of nutrients, salts or impurities in the water.


[ table of contents | back to top ]

Project Information

Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2 (Seagrass Blue Carbon)

Coverage: Chesapeake Bay, Northern Gulf of Mexico, and Bahamas Banks


NSF abstract: This research will develop a quantitative understanding of the factors controlling carbon cycling in seagrass meadows that will improve our ability to quantify their potential as blue carbon sinks and predict their future response to climate change, including sea level rise, ocean warming and ocean acidification. This project will advance a new generation of bio-optical-geochemical models and tools (ECHOES) that have the potential to be transform our ability to measure and predict carbon dynamics in shallow water systems. This study will utilize cutting-edge methods for evaluating oxygen and carbon exchange (Eulerian and eddy covariance techniques) combined with biomass, sedimentary, and water column measurements to develop and test numerical models that can be scaled up to quantify the dynamics of carbon cycling and sequestration in seagrass meadows in temperate and tropical environments of the West Atlantic continental margin that encompass both siliciclastic and carbonate sediments. The comparative analysis across latitudinal and geochemical gradients will address the relative contributions of different species and geochemical processes to better constrain the role of seagrass carbon sequestration to global biogeochemical cycles. Specifically the research will quantify: (i) the relationship between C stocks and standing biomass for different species with different life histories and structural complexity, (ii) the influence of above- and below-ground metabolism on carbon exchange, and (iii) the influence of sediment type (siliciclastic vs. carbonate) on Blue Carbon storage. Seagrass biomass, growth rates, carbon content and isotope composition (above- and below-ground), organic carbon deposition and export will be measured. Sedimentation rates and isotopic composition of PIC, POC, and iron sulfide precipitates, as well as porewater concentrations of dissolved sulfide, CO2, alkalinity and salinity will be determined in order to develop a bio-optical-geochemical model that will predict the impact of seagrass metabolism on sediment geochemical processes that control carbon cycling in shallow waters. Model predictions will be validated against direct measurements of DIC and O2 exchange in seagrass meadows, enabling us to scale-up the density-dependent processes to predict the impacts of seagrass distribution and density on carbon cycling and sequestration across the submarine landscape. Status, as of 09 June 2016: This project has been recommended for funding by NSF's Division of Ocean Sciences.


[ table of contents | back to top ]

Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)
NSF Division of Ocean Sciences (NSF OCE)

[ table of contents | back to top ]

This document is created by info v 4.1f 5 Oct 2018 from the content of the BCO-DMO metadata database.    2020-02-17  16:11:29