Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

Sampling was conducted aboard the CCGS John P. Tully during five cruises (2018-2020) in the northeast Pacific from Vancouver Island to Station P (50°N, 145°W). 
Fisheries and Oceans Canada (DFO) Cruise numbers: 2018-40, 2019-001, 2019-006, 2019-008, 2020-001

Particulate Nitrogen and Carbon

Cruise 2018-040:  Prior to use, Whatman 25 mm GF/C filters (~1.2 μm pore size) were placed in aluminum foil packets and baked at 450°C for 4.5 hours and allowed to cool overnight, sealed, and stored in a zip-lock bags in plastic Tupperware containers previously cleaned with a dilute solution of RBS-35 (Thermo Scientific) in deionized water. Filters were not pre-weighed for this cruise. Particulate concentration was determined using the amount of water filtered.

Cruises 2019-001, 2019-006, 2019-008, and 2020-001:  Whatman 25 mm GF/F filters (~0.7 μm pore size) were used for all other cruises. Prior to use, GF/F filters were baked at 450°C for 4 hours and allowed to cool in the muffle furnace overnight. Further cooling took place in a desiccator. Once cooled to air temperature, filters were weighed on a Sartorius LE225B balance and then stored in individual PALL plastic 47mm filter holders until use.

All Cruises:
For all cruises, all water bottles and silicone tubing used for sampling were initially cleaned in a dilute Extran solution and thoroughly rinsed with Type 1 deionized water. Water samples were collected from Niskin bottles directly into 330 mL to 1L HDPE bottles, through silicon tubing or, at times, directly from the Niskin. Sample bottles were rinsed three times with aliquots from the Niskin and then filled. Volumes varied depending on availability of bottles. Samples were filtered immediately. People doing the sampling wore either vinyl or nitrile gloves. Sample bottles/tubing were reused through the cruise and well-rinsed with sample water between Niskins/casts.

Pre-combusted filters were placed onto a filtration manifold and samples were filtered under vacuum at 5 mm Hg or less. For total particulate carbon, 0.2 μm filtered seawater was used as a final rinse down the sides of the filtration cups. For particulate organic carbon, acidified seawater (10% HCl) was used as a final rinse to purge off the carbonate.

Cleaned forceps were used to remove filters from the manifold and returned to their original containers. After sampling, the filters were oven dried at 30°C. Filters were then stored at -80°C until returned to the lab where they were dried at 30°C for 24 hours. Samples were cooled in a dessicator. They were then sent to Stanford University for further chemical analysis. Samples that arrived at Stanford were placed into plastic petri dishes.

At Stanford University, filters from all cruises were loaded into a Costech Analytical Technologies Zero Blank carousel attached to a Carlo Erba NA1500 Series 2 elemental analyzer (EA) at the Stanford University Stable Isotope Laboratory Facility. The EA was configured with a 10 ml oxygen loop, a combustion oxidation reactor set at 1080°C, reduction reactor at 650°C, magnesium perchlorate column to remove water, the chromatography column set to 60°C, and the thermal conductivity detector set at 190°C. The UHP grade helium flow rate was 65 ml per minute and the UHP oxygen used to enhance combustion was 20 ml per minute. 

All standards were loaded into 5×9 mm tin capsules (Costech Analytical Technologies). An empty 5×9 mm tin was analyzed with each run sequence for blank correction. All GF/C and GF/F filters were loaded into 9×10 mm tin capsules and one pre-combusted GF/C or GF/F filter was loaded into a 9×10 mm tin capsule for blank correction. Each 31-drop run sequence was composed of 2 conditioners, 1 5×9 mm tin blank, 1 9×10 mm filter blank, 2 acetanilide standards, 7 unknown filters, 1 acetanilide standard, 7 unknown filters, 1 acetanilide standard, 7 unknown filters, 2 acetanilide standards.

Though instrument precision is relatively high (± 1 µg N, and ± 2 µg C), overall uncertainty is strongly tied to the sampling procedure, with errors anticipated to range from 10% to 25%.

Dissolved Inorganic Carbon, Total Alkalinity, and pH
Samples were collected following standard protocols (Dickson et al., 2007) into 500 mL borosilicate glass bottles and preserved with 200 μL saturated mercuric chloride for later analysis. Samples were shipped to and analyzed at the Monterey Bay Aquarium Research Institute (MBARI). Three parameters (DIC, TA, and pH) were measured from each 500 mL sample bottle. All samples were run in triplicate, and the results were averaged. DIC and TA instrument performance was monitored by measuring Certified Reference Material (CRM; provided by Andrew Dickson at SIO) approximately hourly.

Particulate Nitrogen and Carbon
Analyses were conducted using a Costech Analytical Technologies Zero Blank carousel attached to a Carlo Erba NA1500 Series 2 elemental analyzer (EA). The instrument precision was estimated from Acetanilide standards (189 measurements over 24 unique sampling dates) as the standard deviation of weight percent measurements for both carbon and nitrogen multiplied by the mean total weight.

The data obtained from the Carlo Erba NA1500 Series 2 elemental analyzer were calibrated using Acetanilide standard composed of 10.36 Wt. % N and 71.09 Wt. % C.

K-factor (KF) method was used to correct all unknown data using 6 acetanilide standards using the following equations.
Where:   KF = (mass mg * 10.36)/(Area N – Area N blank)
               KF = (mass mg * 70.09)/(Area C – Area C blank)

Sample C and N concentrations were calculated as follows: 
Where:   μg/L N = {(Average KF * (Area N – Area N blank))/Volume Filtered (L)} x (1000 μg / 1 mg)
               μg/L C = {(Average KF * (Area C – Area C blank))/Volume Filtered (L)}
 

Dissolved Inorganic Carbon (DIC)
DIC was analyzed using a custom automated system in which a Kloehn V6 syringe pump (5 mL syringe) handles fluid control, delivering 1.75 mL of sample to a custom designed CO₂ stripping chamber. 200 µL of 5% phosphoric acid (H₃PO₄) is subsequently added to the CO₂ stripping chamber for acidification of the sample. CO₂-free gas is then bubbled through the acidified sample and the evolved CO₂(g) is delivered to a LiCOR 7000 Nondispersive Infrared gas analyzer for measurement. Carrier gas flow rate is controlled using a mass flow controller. The DIC concentration of the sample is proportional to the integral of the LiCOR CO₂(g) sample peak. The LiCOR 7000 is calibrated annually using WMO traceable standard gases containing known CO₂ mole fractions. The average accuracy of the instrument relative to CRMs is better than than 1μmol kg^-1.

Sampling precision (σ_s) was estimated by analyzing sets of replicate samples drawn from the same Niskin bottle during rosette casts. The average standard deviation between replicate sets was found to be ±1.5 μmol kg^-1 (n = 8).  Analytical precision (σ_i) was estimated as the standard deviation of CRM samples, post calibration factor implementation, analyzed intermittently with the cruise samples over the course of a few days. The analytical precision was found to be ±0.7 μmol kg^-1 (n = 23). The overall measurement precision of 1.6 μmol kg^-1 was estimated by combining the sampling precision and analytical precision [(σ_s² + σ_i²)^0.5], which is the square root of the sum of the squares. 

Total Alkalinity (TA)
Total Alkalinity was analyzed using a Metrohm 855 automated titrator following standard open cell alkalinity titration procedures. The titrant was comprised of 0.1 M hydrochloric acid (HCl) in a 0.7 M sodium chloride (NaCl) background solution. The titration temperature was held constant at 20.0 ± 0.2°C throughout the titration. The temperature of the sample was measured immediately upon delivery to the jacketed cell for later sample mass determination using density and volume. The average accuracy of the instrument relative to Certified Reference Material (CRM) is better than 1 μmol kg^-1. 

Sampling precision (σ_s) was estimated by analyzing sets of replicate samples drawn from the same Niskin bottle during rosette casts. The average standard deviation between replicate sets was found to be ±1.5 μmol kg^-1 (n = 8).  Analytical precision (σ_i) was estimated as the standard deviation of CRM samples, post calibration factor implementation, analyzed intermittently with the cruise samples over the course of a few days. The analytical precision was found to be ±1.4 μmol kg^-1 (n = 13). The overall measurement precision of 2.1 μmol kg^-1 was estimated by combining the sampling precision and analytical precision [(σ_s² + σ_i²)^0.5], which is the square root of the sum of the squares. 

pH
pH was analyzed using an Agilent 8453 spectrometer in an automated system designed after the one described in Carter et al., (2013). The temperature of the sample was held constant at 20°C using a 10-cm jacketed cell, and every sample was immersed in a 20°C water bath for at least 25 minutes before analysis. An indicator dye (purified m-cresol purple from Sunburst Sensors - lab batch 6) solution (2 mM) was used to assess sample pH. The sample pH perturbation caused by dye addition was quantified by adding both the normal amount and twice the amount of dye to seawater solutions of ~pH 7.4, 7.8, and 8.1. The pH perturbation caused by dye addition to the sample was quantified by adding both the normal amount and twice the amount of dye to a subset of seawater samples. The average precision of the instrument is ±0.004. 

Sampling precision (σ_s) was estimated by analyzing sets of replicate samples drawn from the same Niskin bottle during rosette casts. The average standard deviation between replicate sets was found to be ± 0.0031 (n = 9). Instrument precision (σ_i) is estimated to be ±0.004. The overall measurement precision of 0.005 was estimated by combining the sampling precision and instrument precision  [(σ_s² + σ_i²)^0.5], which is the square root of the sum of the squares. 

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BCO-DMO Processing:

• Imported data from source file "LineP_QCd_bottle_data.xlsx" into the BCO-DMO data system.
• Data file imported using missing data identifiers "NaN”. The missing data identifier "NaN" in the original source file will be displayed as appropriate based on the type of file you download from the BCO-DMO data system. For example, missing data will be shown as blank (null) values in the csv files. In MATLAB .mat files it will be displayed as NaN. When viewing data at BCO-DMO the missing value will be shown as "nd" meaning "no data."
• Adjusted dates to be four digit years, and padded time column with leading zeros.  Then converted separate date and time to single datetime column with ISO8601 format.  
• Added column for vessel/ship
• Added conventional header with dataset name, PI name, version date.
• Modified parameter (column) names to conform with BCO-DMO naming conventions. (The only allowed characters are A-Z,a-z,0-9, and underscores. No spaces, hyphens, commas, parentheses, or Greek letters).

OCE-1756932 Start Date: 2018-03-01
OCE-2032754 Start Date: 2020-05-28

NSF abstract:
A goal in chemical oceanography is to advance our understanding of the global carbon cycle, specifically to quantify the transfer of carbon from the surface ocean to depth through the sinking of particles produced by marine organisms. Yet, modern global estimates of this process (commonly called carbon export) differ by over 100%. These estimates are often derived from regional relationships between ocean measurements and satellite observations that are then applied globally. Persistent differences between the satellite and field-based estimates of carbon export have been found throughout the ocean, suggesting that improvements are needed. This project will determine whether profiling floats equipped with chemical sensors can be used to estimate the export of carbon in the ocean. Floats will be deployed at Ocean Station Papa, but the approach is scalable in nature and could be used to validate and improve the satellite algorithms used for global carbon export determinations. The project will support a female, early career scientist and a postdoc, as well as facilitate international collaboration with Canadian scientists. Additionally, the results may assist the National Aeronautics and Space Administration (NASA) EXPORTS campaign as well as other satellite carbon export development efforts.

Modern global estimates of the biological pump differ by over 100% (~5 to >12 Pg C yr-1) making it challenging to determine the role of marine biogeochemical (BGC) cycling in modern climate and climate variability. Global carbon export estimates are often derived from regional empirical relationships between field and satellite observations that are then applied globally. Persistent discrepancies between unique satellite algorithms and unique geochemical approaches suggest that accurately quantifying the biological pump remains a fundamental research goal. This project will assess the capability of using BGC profiling floats to estimate the export of distinct biogenic carbon pools (dissolved and particulate organic carbon, and particulate inorganic carbon). By using BGC floats to close multiple upper ocean tracer budgets this project will address two known issues common to other geochemical approaches: assumptions about (1) dissolved organic carbon cycling and (2) the integration depth used for annual carbon export assessments. The method will be tested at Ocean Station Papa, but is scalable in nature and could be used to develop a carbon export database suitable for the validation and training of satellite algorithms required for global carbon export determinations. Results from the floats will be compared to satellite carbon export algorithm estimates over the 5-year float lifetimes. Ten years of existing BGC data from profiling floats and a mooring in the region will also be used to provide further context about interannual variability.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.