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Automated spectrophotometric determination of carbonate ion concentration in seawater using a portable syringe pump based analyzer
Accepted Manuscript Automated spectrophotometric determination of carbonate ion concentration in seawater using a portable syringe pump based analyzer
Qipei Shangguan, Huilin Shu, Peicong Li, Kunning Lin, Robert H. Byrne, Quanlong Li, Dongxing Yuan, Jian Ma PII: DOI: Reference:
S0304-4203(18)30276-7 https://doi.org/10.1016/j.marchem.2019.01.007 MARCHE 3630
To appear in:
Marine Chemistry
Received date: Revised date: Accepted date:
1 November 2018 15 January 2019 27 January 2019
Please cite this article as: Q. Shangguan, H. Shu, P. Li, et al., Automated spectrophotometric determination of carbonate ion concentration in seawater using a portable syringe pump based analyzer, Marine Chemistry, https://doi.org/10.1016/ j.marchem.2019.01.007
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Automated spectrophotometric determination of carbonate ion concentration in seawater using a portable syringe pump based analyzer Qipei Shangguan1 , Huilin Shu1 , Peicong Li1 , Kunning Lin1 , Robert H. Byrne2 , Quanlong Li1 ,
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Dongxing Yuan1 , Jian Ma1
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1. State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, College of the Environment and Ecology, Xiamen
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University, Xiamen, 361102, People’s Republic of China 2. College of Marine Science, University of South Florida, 140 7 th Avenue South, St. Petersburg,
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Florida, 33701, United States
Corresponding author: [email protected] (Dr. J. Ma) 1
ACCEPTED MANUSCRIPT ABSTRACT Observations of seawater carbonate ion concentrations are critical to assess the ecological effects of ocean acidification. Nevertheless, currently available methods are labor intensive or
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too complex for field applications. Here, we report the design and performance of the first fully
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automated portable carbonate ion analyzer. Measurements are based on reaction of carbonate and
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chloride ions with Pb(II) followed by quantitative UV spectrophotometric detection of the
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PbCO3 0 complex. The core hardware is a syringe pump equipped with a multi-position valve that
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is controlled by software written in LabVIEW. Measurement precision is 1.1% (n=13) with a
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measurement frequency of 12 h-1 . The analyzer was used to continuously monitor carbonate ion
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concentration variations in a 2500 L coral reef tank for five days (test 1), and used for shipboard
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underway and vertical profile analysis during a 13-day cruise (test 2). The analyzer attained a combined standard uncertainty of 3.0%, which meets the Global Ocean Acidification Observing
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Network’s “weather level” goal. Through use of a syringe pump mechanism for mixing seawater
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and reagent solution, the analyzer is robust, functionally flexible, and quite suitable for continuous environmental monitoring under harsh conditions. KEYWORDS Seawater; carbonate ion; automated flow analysis; spectrophotometric detection; coral reef; underway analysis
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ACCEPTED MANUSCRIPT 1. INTRODUCTION Approximately 30% of global anthropogenic carbon emissions have been absorbed by the oceans (Sabine et al., 2004). Chemical reactions that occur when anthropogenic CO 2 invades
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seawater reduce seawater pH, carbonate ion (CO 32-) concentration, and the saturation state of
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seawater with respect to biologically important CaCO 3 minerals (e.g. calcite and aragonite) (Doney et al., 2009). Extensive studies of this process, commonly referred to as ocean
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acidification, have demonstrated a wide variety of physiological effects on marine biota (Feely et
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al., 2004; Mostofa et al., 2016). To better understand how ocean acidification will affect future
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ecosystems, there is a clear need for carbonate mineral saturation state data with improved
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temporal and spatial resolution. Toward this end, improved autonomous techniques and
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instruments are needed to assess relationships between the rapidly changing ocean carbon cycle
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and consequent impacts on ocean ecology (Byrne et al., 2010; Byrne, 2014; Martz et al., 2015; Schuster et al., 2009).
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Because calcium concentrations ([Ca2+]) are nearly proportional to salinity, carbonate mineral saturation states are largely determined by variations in [CO 3 2-], which are typically calculated from any two of the four conventionally measured CO2 system parameters: pH, fugacity of CO 2 (fCO 2 ), dissolved inorganic carbon (DIC), and total alkalinity (TA) (Orr et al., 2018; Millero, 2007). Using a methodology analogous to spectrophotometric pH measurements
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(Rérolle et al., 2012), Byrne and Yao (2008) demonstrated the use of UV spectrophotometric determinations of Pb(II) equilibrium speciation in seawater (competitive complexation of Pb(II) by chloride and carbonate ions) to directly determine carbonate ion concentrations at a fixed
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temperature of 25 ℃. This research group subsequently applied the technique to directly
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determine [CO 3 2−] in the Arctic and the Eastern Pacific Oceans (Easley et al., 2013), and
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developed improved algorithms based on large datasets obtained in the Gulf of Mexico and east coast waters of the USA (Patsavas et al., 2015). Subsequent to these developments, Fajar et al.
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(2015) assessed the reliability of this methodology during cruises in the Atlantic Ocean and the
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Mediterranean Sea over a wider range of salinities and pH. Furthermore, Sharp et al. (2017)
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eliminated incongruous [CO 3 2−] values made with different spectrophotometers after correcting
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instrument-dependent offsets, and also introduced an empirical model to calculate in-situ
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carbonate mineral saturation states from shipboard observations. More recently, this
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methodology was extended to a wider temperature range, allowing measurements to be performed at in-situ temperatures (Sharp and Byrne, 2018). In addition to the spectrophotometric methods, acidimetric titrations with UV detection (Martz et al., 2009) and micro carbonate ion electrodes have been applied for carbonate ion concentration measurements (Cai et al., 2016; de Beer et al., 2008; Han et al., 2014).
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The precision as well as the spatial and temporal resolution of carbonate measurements can be improved by automation (Ma et al., 2016). Here, we report the development of a novel, low- maintenance, automated analyzer for robust [CO 3 2−] measurements that is based on
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recordings of UV Pb(II) spectra in seawater. The core hardware is a syringe pump equipped with
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a multi-position valve that is controlled by software written in LabVIEW (Ma et al., 2018). The
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objective in this work was to design an instrument capable of providing high frequency, as well as high precision and accurate measurements of [CO 3 2-].
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2. PRINCIPLES
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Procedures to directly determine [CO 3 2−] in seawater (Byrne and Yao, 2008) are based on
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observations that the speciation and absorbance characteristics of dissolved Pb(II) upon its
Measurement procedures
for determining
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ion concentrations,
like
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2008).
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addition to seawater and complexation as carbonate and chloride species (Byrne, 1981; Soli et al.,
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spectrophotometric pH determinations, involve observations of absorbance ratios to enhance measurement precision. While Pb(II) spectra in seawater with different carbonate ion concentrations exhibit substantial variations at 250 nm, absorbances at 234 nm show much smaller variations (Byrne and Yao, 2008). Carbonate ion concentrations can therefore be quantified by monitoring absorbance ratios (A250 /A234 ) along with characterizations of Pb(II)
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thermodynamic and optical properties in seawater. Carbonate ion concentrations are calculated with the following equation: -log[CO 3 2-] = log{(CO3 β1 )/(e2 )}+ log{(R-e1 )/(1-Re3 /e2 )} is the formation constant of the lead carbonate complex PbCO 3 0 ,
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CO3 β1
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parameters are molar absorptivity ratios: e1
PbCO 250nm ， e2 Pb 250nm ， e3 Pb 234nm PbCO 234nm PbCO 234nm PbCO 234nm 3
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3
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3
and the ei
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where
(1)
(2)
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Absorbance at 350 nm is also measured to correct for any small baseline changes (350 nm is
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outside the region of absorbance by Pb(II) carbonate and chloride species). R is calculated in the
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form (A250 -A350 )/(A234 -A350).
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The salinity (S) dependencies of the parameters in Eq. (1) were determined at 25 ℃ in previous works (Easley et al., 2013; Patsavas et al., 2015; Sharp et al., 2017). The most recent
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parameterizations at 25 ℃ were produced and verified by Sharp et al. (2017) after correction of
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small but significant instrumental differences among previously used electrical and optical systems, and the parameters are given by: log{(CO3 β1 )/(e2 )}=6.87057-0.142142 S+0.00190892 S2
(3)
e1 =0.787458-0.0339648 S+0.000583574 S2
(4)
e3 /e2 =2.52288-0.0383205 S
(5)
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3. MATERIALS AND METHODS 3.1 Reagents Pure water (18.2 M cm) obtained from a Millipore Purification System was used for
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preparation of all solutions. Analytical grade sodium bicarbonate (NaHCO 3 ), sodium chloride
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(NaCl), sodium hydroxide (NaOH), and hydrochloric acid (HCl) were purchased from
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Sinopharm Chemical Reagent Co., China and used without further purification. Lead perchlorate (Pb(ClO 4 )2 ) purchased from Fisher Scientific (99% purity) was used to prepare a 2.2 mmol/L
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titrant solution. In order to calibrate the analyzer, synthetic saline solutions of 0.7 mol/L NaCl
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and 2 mmol/L NaHCO 3 were used in this study in addition to natural seawater.
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3.2 Apparatus
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The fully automated carbonate ion concentration measurement manifold is shown in Figure
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1. A programmable syringe pump (XLP6000, Tecan) was used to deliver variable volumes of
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seawater and lead titrant to the various components of the analyzer. The syringe pump incorporated a precise stepper motor and a gas-tight 2.5 mL syringe, and was connected to a 6-port distribution valve. The volumetric precision of the pumps for a full piston stroke delivery was better than ± 0.05%. PTFE tubing, 0.8 mm i.d. with standard PEEK fittings (1/4-28, IDEX), was used for liquid connections throughout the system. Although the syringe itself can act as a
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mixing chamber, an additional mixing coil was used to facilitate complete mixing (discussed below). The fused quartz flow-cell body was custom- made with a 100 mm pathlength. The 3x3x100
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mm cell had an internal volume of ~1 mL including connecting tubing, and was inserted into a
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custom-engineered cuvette holder equipped with two collimating lenses (74-UV, Ocean Optics).
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These lenses were connected to the light source (continuous wave deuterium lamp, D-2000, Ocean Optics) and the detector (CCD spectrophotometer, Maya2000 Pro, Ocean Optics) via
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optical fibers and SMA-905 optical connectors. Solarization-resistant fibers with an internal
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diameter of 600 μm (XSR, Ocean Optics) were used to prevent transmission degradation in the
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UV region.
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Temperature control is critical for precise measurements. Before entering the flow system,
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the sample was thermostated to 25±0.1 ℃ by passing through a quartz coil (310 cm length, 21
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mL volume) immersed in a sealed water bath. This allowed seawater samples with temperatures ranging from 5~45 ℃ to be precisely adjusted to 25 ℃ with a precision better than 0.1 ℃. All components of the flow system (except for the deuterium light source) were housed in a constant temperature air bath, made from a laboratory- modified car refrigerator. This analyzer combined Peltier cooling with a heating mat and a Proportional–Integral–Derivative (PID) controller to maintain the optical cell at 25±0.1 ℃. All temperature probes in the air and water baths were 8
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calibrated with a platinum resistance thermometer (8821 IP67 HACCP RTD Thermometer, AZ Instrument Corp). 3.3 Analytical procedure
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Prior to the implementation of continuous measurement procedures, the light source is
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switched off. A dark spectrum is obtained (integration time ~20 ms), and subsequently
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subtracted from counts acquired during measurement procedures with the light source on. A baseline spectrum is recorded before each measurement cycle to compensate for lamp aging as
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well as for variations in the properties of seawater samples.
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Seawater samples pass slowly (~8 minutes) through the quartz temperature-controlled cell
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and then enter the automated carbonate analyzer. The 17-step analytical procedure programmed
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in LabVIEW is shown in Table 1. Associated spectrophotometric signals are shown in Figure 2.
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Measurements begin by rinsing the syringe, coil and flow cell three times (steps 1-6). Step 4
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removes air bubbles by directing 0.1 mL of the solution in the optical cell to the waste receptacle via port 4. This highly-essential bubble removal step is used before introducing all solutions into the flow cell. The cleaning steps (1-6) reduce contamination from previous samples and return absorbance signals to baseline levels. In steps 7-9, the flow cell is filled with seawater to obtain and record a reference spectrum (i.e. a background spectrum without Pb(II)). The syringe is then (a) partially filled with a seawater sample (1 mL), followed by (b) a 12.5 μL addition of Pb(II) 9
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perchlorate solution, and then (c) addition of more seawater, creating a total volume of 2.5 mL (steps 10-12). In order to rapidly and completely mix the seawater and lead perchlorate solution, the mixture in the syringe is then injected into the mixing coil (1.4 m length, 1.6 mm i.d., 2.8 mL
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total volume) and withdrawn back into the syringe 3 times (steps 13-15). The mixed solution is
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then dispensed into the flow cell (steps 16-17), and a spectrum of the seawater/titrant mixture is
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recorded. The syringe and mixing coil then undergo a rinse in preparation for subsequent measurements. All spectral acquisitions are performed when transmitted optical signals are stable,
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which occurs less than 30 seconds after sample injection into the flow cell (Figure 2). A total of
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50 spectra scans are averaged to improve the signal/noise ratio. A flow rate of 3.75 mL/min was
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chosen for aspiration to avoid formation of bubbles that can occur during rapid decreases in
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3.4 System calibration
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pressure. For quick cleaning, a higher flow rate (16.7 mL/min) was used in all dispensing steps.
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Spectrophotometric determinations of carbonate ion concentrations implicitly assume that the analytical wavelengths and band-pass are identical to those used to determine the absorptivity calibration parameters. The Agilent 8453 spectrophotometers used in previous studies have a spectral resolution of 1.5 nm. The wavelength accuracy claimed by the manufacturer is within ±0.5 nm, and is necessarily validated with wavelength standards before [CO 3 2−] measurements (Sharp et al., 2017). In comparison, the Maya2000 Pro spectrophotometer in our analyzer has a 10
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similar 1- nm bandpass, but the wavelength accuracy is uncertain over the spectral region of interest. To address this issue, we established a functional relationship between RA (R value from the analyzer spectrophotometer) and RS (R value from a manually operated standard
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spectrophotometer), similar to the approach of Yang et al. (2014). RA was converted to RS, which
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procedure can be found in the Supplementary Material.
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was used in equation (1) to produce final values of [CO 3 2−]. A detailed description of this
RA and RS exhibited good linearity: RS = k·RA + Int., where k and Int. are slope and
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intercept, respectively. However, it was observed that the calibration curve can shift during
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long-term operation of the analyzer due to drift in signal intensity and non- linearity of the CCD
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detector. Accordingly, the intercept (Int.) in the RS vs RA relationship was considered as
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time-dependent, with the slope (k) remaining constant but Int. being variable. A time-dependent
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calibration routine was then devised as follows: (1) A sample with known [CO 3 2-] is measured on
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the analyzer every two days; (2) The Int. value for the analyzer at any time (t) is adjusted to produce an accurate [CO 32-] value for this sample. This process results in a new “perfect” calibration relationship at time (t) of the calibration; (3) The time-dependent Int. values produced by this process (e.g., Int.1 at time t1 and Int.2 at time t2 ) are linearly interpolated to provide Int. values at any time between calibrations. RS was thereafter determined with RA from the analyzer and an Int. value appropriate at the time of measurement. The [CO 3 2-] values used in the 11
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calibrations were obtained (calculated) from carbonate system parameters (TA and DIC) and thermodynamic relationships. Certified reference materials (CRMs) contain mercuric species, which may alter Pb(II) equilibria and contribute to UV spectra, were not directly used for
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been collected and carefully analyzed for TA and DIC (see 3.5).
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calibrations. Alternatively, field calibrations were conducted using seawater samples that had
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3.5 Sampling and field application
The precision and accuracy of the analyzer system were evaluated in both shore-based and
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shipboard laboratories.
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From May 2-7, 2017, the analyzer was deployed in an artificial reef aquarium tank for five
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days to observe diurnal changes in carbonate ion concentrations. The tank volume was 2500 L
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and the saline water was prepared using sea salt (Instant Ocean) and deionized water. The tank
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contained marine fish (surgeonfish, angelfish, damselfish), and scleractinian corals (Acropora,
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Pocilopora damicornis, montipora, stylophora pistilata) from Hainan province in southern China. System controls included twenty 80-watt T5HO lamps with HEP ballast (ATI), two protein skimmers (one from Aqua Excel and the other from Reef Octopus), four circulation pumps (Hagen), and two wavemakers (EcoTech Marine). During the five-day field trial, salinity was measured with a portable conductivity meter, ProfiLine Cond 3110 (WTW), and temperature was recorded every half minute using a HOBO Water Temp Pro v2 (Onset). 12
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The carbonate ion analyzer was deployed during cruise KK1703 on the XMU R/V Tan Kah Kee during August 2-14, 2017. The cruise included testing of marine acoustic equipment in the South China Sea (SCS) until August 6, and then proceeded to the western Pacific across the
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Luzon Strait on August 7, 2017. Throughout the cruise, seawater from the ship’s underway
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seawater line flowed into a ~150 mL sampling chamber, with a nominal throughput of 2 L/min.
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The sampling chamber was continuously flushed, thereby minimizing the presence of bubbles and particles. Samples were aspirated from the chamber to the analyzer, and processed as
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described in section 3.3. Temperature and salinity were measured with a thermosalinograph
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mounted near the ship’s seawater intake (SBE21, Sea-Bird Electronics), and shipboard GPS
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recorded time and position. In addition to real-time underway monitoring, discrete samples from
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two vertical profiles were measured on board. Hydrographic data (temperature, salinity, and
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depth) at the two sites were obtained with a rosette- mounted CTD (SBE9, Sea-Bird Electronics).
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Profiling Station 1 (S1), with 22 depth levels to 5000 m, was located at 19.31°N, 125.22°E, and Station 2 (S2), with 22 depth levels between the surface and 4000 m, was located at 19.66°N, 125.55°E. Seawater samples for discrete [CO 3 2-] measurements were collected in Niskin bottles, transferred to 250 mL borosilicate glass bottles, and sealed using greased ground glass stoppers. The samples were kept in the dark at room temperature without poisoning and analyzed within 9
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hours. Figure S1 shows the cruise route and the position of sampled stations plotted with Ocean Data View (Schlitzer, 2009). During the shore-based trial, 40 discrete sample pairs were collected in the reef tank for TA
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and DIC analysis (Dickson et al., 2007). Of these, 3 sample pairs were used for system
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calibration, and the others were used for evaluation of accuracy. During the shipboard trial, 39
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discrete sample pairs were collected from the ship’s underway system and 5 of these were used for system calibration. A total of 44 vertical profile sample pairs were collected. Vertical profile
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sample pairs were taken immediately after collection of discrete carbonate ion samples from
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each Niskin bottle. Each sample was poisoned with a few μL of saturated HgCl2 solution at the
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time of collection. TA was measured by potentiometric titration and Gran function end-point
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determination with a commercial open-cell Kloehm digital syringe pump-based titrator
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(AS-ALK2, Apollo SciTech) and a ROSSTM combination electrode 8102 (Thermo Fisher
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Scientific). DIC was measured by acidification of seawater samples (0.5 mL) with 0.5 mL H3 PO4 (10%, v/v) and subsequent quantification of released CO 2 with a commercial infrared gas analyzer (AS-C3, Apollo SciTech). Both TA and DIC measurements were calibrated against certified reference materials (CRMs) provided by Dr. Dickson of Scripps Institute of Oceanography. The accuracy and precision of both methods were ±2-3 μmol/kg (Huang et al., 2012; Millero, 2007). Carbonate concentrations ([CO 3 2−]) were calculated from TA-DIC with 14
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CO2SYS version 2.1 (Pierrot and Wallace, 2006) using the carbonic acid dissociation constants of Lueker et al. (2000), the total-boron-to-salinity ratio from Lee et al. (2010), and K HSO4 from Dickson et al. (1990).
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3.6 Data analysis
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Differences between [CO 3 2-] values that were directly measured with the analyzer
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([CO 3 2-]mea) and values that were calculated from TA and DIC ([CO 3 2-]cal) are reported as Δ[CO 3 2-]=[CO3 2-]mea-[CO 32-]cal. Sharp and Byrne (2018) pointed out that Δ[CO 3 2-] values are
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proportional to [CO 3 2-] itself. Relative differences and relative precision were used throughout
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this paper. The former refers to the difference between measured and calculated (from TA and
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DIC) carbonate ion concentrations for samples, whereas the latter refers to the difference
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between the repetitive measurement of the same sample.
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The importance of estimating uncertainty of carbonate system variables has been addressed
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in the context of the Global Ocean Acidification Observing Network (GO A-ON) (Newton et al., 2015). Combined standard uncertainties should include both random and systematic sources of uncertainty (Orr et al., 2018). Mirroring the procedures of Sharp and Byrne (2018), relative precision from the analyzer was assigned as the random component. Relative standard deviation (RSD), obtained from mean value of [CO 3 2-]cal (µ) and the standard deviation of Δ[CO 32-] (δ), was used to assess the systematic component, which consisted of the uncertainties in the 15
ACCEPTED MANUSCRIPT parameters of the Pb(II) model (eq. (1)-(3)) and the analyzer output (RSD = δ/µ × 100%). 3.7 Caution: The lead-enriched seawater is toxic to aquatic life and should be collected via special treatment (e.g. passing through ion-exchange resin or treated with other techniques to
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remove Pb ions) before being discarded (Sharp et al., 2017).
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4. RESULTS AND DISCUSSION
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4.1 Calibration and instrument performance
The relationship between RS and RA can be expressed by the following equation: R2 =0.9972, n=15
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RS = 1.0491RA + Int.,
(6)
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Once the analyzer was constructed, we observed that its performance was affected by issues
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with optical detection. For this analyzer, a value of 1.0491 was assigned to the slope (k) based on
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multiple experimental measurements as described in 3.4. This treatment was an empirical
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approach as laboratory tests showed that slope displayed good reproducibility while optical shift
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was directly reflected in the intercept (Int.). Output signals for each of the three wavelengths used in carbonate ion analyses are shown in Figure 2, where signals at 234 nm were considerably lower than signals at the other two wavelengths. In order to assure the linear response range to Beer's Law at 234 nm after mixing of the sample and Pb(II) titrant, the final Pb(II) concentration in the mixture was adjusted to ~11.2 μmol/kg, somewhat lower than the 15.2 μmol/kg concentration used by Sharp et al. (2017). A 16
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discussion of the influence of final Pb(II) concentrations (i.e. perturbation effects) can be found in the Supplementary Material. The short term precision of [CO 3 2−] measurements, evaluated by consecutively analyzing
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seawater stored in an 18 L polycarbonate container, revealed that [CO 3 2-] = 101±1.1 μmol/kg
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(1.1%, n=13). The sampling frequency throughout this analysis was 12 h-1 .
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4.2 Field measurements of carbonate ion concentrations
During two field tests, the automated carbonate ion analyzer worked continuously without
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any maintenance or intervention. After obtaining the raw data, outliers (≥3 sigma residuals) were
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discarded to ensure data quality. The remaining carbonate ion concentration data were smoothed
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by taking running 5-point averages.
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4.2.1 Field measurements of carbonate ions in aquarium tank
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During the five-day field trial in the reef aquarium tank, a total of 1,659 measurements were
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obtained and ~3.1% of the data were discarded as outliers. Figure 3a shows [CO 3 2-] values obtained using the calibration procedures described in sections 3.4, as well as [CO 3 2-] values obtained by treating the Int. value as a constant. Without correcting for time-dependent effects on Int., the [CO 3 2-] values showed a significant upward trend. Considering the blank intensity ratio (Figure 3b), an optical drift was apparent. Rs for each measurement was necessarily compensated by a corresponding Int. value determined using three TA/DIC pairs and linear 17
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interpolation. Structural breaks in the blank intensity ratio data occurred after Day 4, likely due to unintentional movement of flow cell position, but did not affect carbonate ion concentration results.
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As shown in Figure 3c, relative differences in carbonate concentrations are evenly scattered
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around zero; the mean and standard deviation are 1.0% ± 7.3% (n=37). Parameters in the Pb(II)
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model (eq. (1)-(3)) were optimized for [CO 3 2-] values below 260 μmol/kg (Sharp et al. 2017). For samples with carbonate ion concentrations in the same range as those observed in our work,
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the mean relative difference and standard deviation decreased to -0.1% ± 3.7% (n=14).
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There are several difficulties in this validation and assessment of field measurement
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uncertainties. The coral reef water was prepared using commercial sea salt and may be somewhat
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different from natural seawater in composition and physicochemical properties. It is likely that
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Pb(II) speciation and thermodynamics were affected by the sample matrix, increasing the
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uncertainties in Pb(II) model parameters (eq. (1)-(3)). Although the Int. calibration routine somewhat reduced this effect, rapid changes in seawater properties might degrade calibration effectiveness and CO 2 system internal consistency. Because of the heterogeneity of the water in the aquarium, representative sampling might be a problem contributing to measurement uncertainty. The portable salinity meter used in this work has a resolution of 0.1, corresponding to ~1% uncertainty in [CO 3 2-]. Overall, the RSD obtained in this trial was 3.7% for [CO 32-] 18
ACCEPTED MANUSCRIPT below 260 μmol/kg and 9.2% for the whole dataset. Though RSD (systematic component of the uncertainty) might seem to be high, especially for high [CO 3 2-] samples, there was good agreement in the temporal variability between calculated and measured [CO 3 2-]. An approximate
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100 μmol/kg daily variation in carbonate ion concentrations was observed (Figure 4). Organic
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carbon metabolism (photosynthesis and respiration) and inorganic carbon transformations
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(calcification and dissolution) all caused changes in [CO 32-]. Diel patterns in temperature and [CO 32-] mirrored those for DIC and TA. Photosynthetic uptake of CO 2 resulted in reduced DIC
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and elevated [CO 3 2-] (due to increased pH) when temperature and light were high (8 am to 6 pm),
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while high DIC and low [CO 3 2-] occurred at night. Changes in TA were caused by CaCO 3
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calcification and dissolution, which reduced [CO 3 2-] in the light due to calcification, and gave
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rise to increasing [CO 3 2-] in the dark due to dissolution. Interestingly, salinity showed a slight
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systematic decrease during periods of measurement, possibly caused by sustained input of
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low-salinity nutrient solutions. Data from the analyzer provided real- time variability of [CO 32-] (Figure 4a), while discrete TA and DIC only reflected running averages with lower temporal resolution (Figure 4b). Hence, this analyzer will be especially useful in environments where coral productivity and calcium carbonate processes are highly dynamic. 4.2.2 Field measurements of carbonate ions during research cruise
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During the 13-day research cruise, the carbonate ion analyzer measured both underway (3101 measurements) and discrete samples. About 1.3% of the data were discarded as outliers. A total of 39 TA-DIC sample pairs were collected and 5 of these pairs were used for calibration. As
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shown in Figure 5, the blank intensity ratio experienced the same downward trend observed in
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the coral tank trial. With the Int. calibration routine, the analyzer exhibited good accuracy and
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was immune to optical drift (Figure 5c). The relative differences between calculated and measured [CO 3 2-] were between -3.6% to 9.0%, with a mean value and standard deviation of 0.6%
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± 2.7% (n=34).
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The distributions of carbonate ion concentrations are presented in Figure 6. The observed
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[CO 32-] during this cruise ranged from 198 μmol/kg to 248 μmol/kg, with the lowest values and
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largest variability in coastal seas, where upwelling events and river plumes had significant
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impacts (Cao et al., 2011; Gan et al., 2009; Guo and Wong, 2015). Nevertheless, [CO 32-]
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remained fairly constant in the Northern open SCS. From August 4 to 6, the analyzer yielded 846 measurements with an average of 223 μmol/kg. RSD was 1.0% (n=846). After transitioning to the Western Pacific, [CO 32-] increased by ~10 μmol/kg. Excluding profile sample analysis, 1229 measurements were obtained from August 8 to 12 with a RSD of 1.8% (average=231 μmol/kg). Although these results demonstrated the stability of this analyzer under harsh conditions at sea,
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use of the analyzer in coastal areas that have higher short-term variability may be especially valuable and informative. The purposes of our vertical profile analyses were: (1) evaluation of analyzer accuracy over
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a wide range of conditions in seawater and (2) assessment of analyzer precision by performing
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triplicate measurements for each sample. As shown in Figure 7, good agreement was observed
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between carbonate analyzer measurements and carbonate calculations from TA-DIC. The analyzer achieved a short term relative precision of 1.4 % ±1.2% (n=22) for S1 and 1.5% ± 0.8%
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(n=22) for S2, which were slightly higher than the typical precision observed using artificial
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seawater in a land-based laboratory (1.1%). This difference can be attributed to gas exchange
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because triplicate bottle measurements took ~15 min, and during this time the bottle contents
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were exposed to the air. Relative accuracy for the two profiles, ranged from -2.2% to 0.9% for
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S1 with an average of -0.3% ± 1.3% (n=22), and from -4.1% to 9.8% for S2 with an average of
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3.1% ± 3.7% (n=22). Based on these results, this analyzer can provide good accuracy over the wide range of [CO 32-] that may be encountered in ocean environments. The detailed data are shown in Figure S4 and S5. Overall, comparisons of data obtained at sea, including surface underway samples (n=34) and two vertical profiles (n=44), indicated a relative accuracy of 1.0% ± 3.0 % (n=78). Based on calculation of RSD for the whole dataset, a value of 2.8% (n=78) was assigned to the systematic 21
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component of uncertainties. Based on the relative precision obtained in the laboratory and at sea, a value of 1.1% was assigned for the random component. Estimates for the systematic component (2.8%) and random component (1.1%) were combined in quadrature to obtain an
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estimate of 3.0% for combined standard uncertainty. Sharp and Byrne (2018) reported a
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combined standard uncertainty of 1.9% for manual handling of spectrophotometric [CO 32-]
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values. Uncertainty in the analyzer output was therefore estimated to be 2.3%. In the context of GOA-ON’s measurement quality goals, this analyzer meets the requirements of GOA-ON’s
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weather objective (10%) and falls slightly short of the climate objective (1%) (Newton et al.,
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2015). The primary source of uncertainty in the analyzer output came from optical drift and the
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calibration routine required to address the drift. Ongoing research will include deployments of
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this instrument with aged seawater stored in a gas- impermeable bag with known TA and DIC
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values. The valve for selection of this bag’s contents at port 6 will allow automated calibration
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rather than use of collected discrete samples. Due to small sample consumption requirements (~12.5 mL per sample), a 3-L bag will enable 10 days of operation with hourly calibration and should significantly improve data quality. Sharp and Byrne (2018) recently extended the Pb(II) model to a temperature range of 3 to 40 ℃, allowing all measurements to be performed at in-situ temperatures. Further development and testing of this analyzer will include elimination of temperature control components, thus 22
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reducing cost and complexity. 4.3 CONCLUSIONS AND IMPLICATIONS Carbonate ion concentrations can be considered as the fifth independently measurable inorganic carbon system.
Spectrophotometric [CO 3 2−]
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for describing the
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parameter
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measurements are precise, fast, and easily adapted for automated systems. This work presents
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results of the first automated analyses of carbonate ion concentrations in aqueous samples, demonstrating high sample throughput, and precision comparable to other methods (e.g., manual
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operation, calculation from other parameters, etc.). Based on shore-based and shipboard testing
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and performance assessment (precision, accuracy, uncertainty) in this work, this analyzer is
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especially suitable for highly dynamic and complex systems where monitoring of [CO 3 2-] and
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saturation states with high-resolution is required. These systems might include coral reef
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ecosystems, coastal areas subject to upwelling and river inputs, and laboratory mesocosm
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experiments. Sharp and Byrne (2018) noted that, for low-salinity samples, trace amounts of PbCO3 (s) might form, thereby reducing measurement quality. Absorbance measurements should be performed promptly after mixing of the lead perchlorate solution with seawater. Samples measured in this work all had salinities above 32.5. If this analyzer is deployed in low-salinity regions in the future, it could benefit from fast acquisition of spectra from a CCD detector, and
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flexibly-adjusted amounts of added lead perchlorate using the syringe pump might also alleviate this potential issue. This analyzer adds flexibility to future development of an integrated analyzer capable of
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on- line measurements of two or more carbonate parameters for comprehensive descriptions of
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the inorganic carbonate system (Wang et al., 2007, 2015). Because of the highly precise
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sample/reagent ratio obtained with the syringe pump used in this work, it is very easy to use a pH indicator instead of Pb(II) titrant, and thereby obtain pH measurements (Liu et al., 2006), or
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implement single point titrations for TA analysis (Li et al., 2013). With further optimization, this
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analyzer can provide simple, portable and user-friendly spectrophotometric determinations of
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Acknowledgements
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nutrients, metals, and other environmental and marine parameters.
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This work was financially supported by the National Natural Science Foundation of China (41576097), Natural Science Foundation of Fujian Province (2014J05050) and Program for New Century Excellent Talents in Fujian Province University (2016). We sincerely acknowledge Dr. Di Qi, Dr. Xinqing Zheng, Mr. Yan Li and Ms. Chenying Wang (TIO) for instrument testing, Dr. Yongming Huang (XMU) for instrument design, Ms. Liguo Guo and Ms. Yan Li (XMU) for measuring TA and DIC samples, the captain and crews of R/V Tan Kah Kee for their help during 24
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the cruise, Dr. Xianghui Guo for data discussions and MEL visiting scholar Tom Trull (ACE CRC) for proofreading. The critical comments from the associate editor and three journal
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reviewers greatly improved the manuscript.
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Cao, Z., Dai, M., Zheng, N., Wang, D., Li, Q., Zhai, W., Meng, F. and Gan, J., 2011. Dynamics of the carbonate system in a large continental shelf system under the influence of both a river plume and coastal upwelling. J. Geophys. Res. 116, G02010.
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Dickson, A.G., Sabine, C.L., Christian, J.R., 2007. Guide to best practices for ocean CO2 measurements, PICES Spec. Publ. 3. Doney, S.C., Fabry, V.J., Feely, R.A., Kleypas, J.A., 2009. Ocean acidification: The other CO 2 problem, Annu. Rev. Mar. Sci. 1, 169-192. Easley, R., Patsavas, M.C., Byrne, R.H., Liu, X., Feely, R.A., Mathis, J.T., 2013. Spectrophotometric measurement of calcium carbonate saturation states in seawater, Environ. Sci. Technol. 47, 1468-1477. Fajar, N.M., García-Ibáňez, M.I., Sanleón-Bartolomé, H., Álvarez, M., Pérez, F.F., 2015. Spectrophotometric measurements of the carbonate ion concentration: Aragonite saturation states in the Mediterranean Sea and Atlantic Ocean, Environ. Sci. Technol. 49, 11678-11687. 26
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Li, Q., Wang, F., Wang, Z.A., Yuan, D., Dai, M., Chen, J., Dai, J., Hoering, K.A., 2013. Automated spectrophotometric analyzer for rapid single-point titration of seawater total alkalinity, Environment. Sci. Technol. 47, 11139-11146.
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Ma, J., Li, P., Chen, Z., Lin, K., Chen, N., Jiang, Y., Chen, J., Huang, B., Yuan, D., 2018. Development of an integrated syringe-pump-based environmental-water analyzer (iSEA) and application of it for fully automated real-time determination of ammonium in fresh water. Anal. Chem. 90, 6431-6434. Ma, J., Yuan, D., Lin, K., Feng, S., Zhou, T., Li, Q., 2016. Applications of flow techniques in seawater analysis: A review, Trends in Environ. Anal. Chem. 10, 1-10. Martz, T.R., Daly, K.L., Byrne, R.H., Stillman, J.H., Turk, D., 2015. Technology for ocean acidification research: Needs and availability, Oceanography 28, 40-47. Martz, T.R., Jannasch, H.W., Johnson, K.S., 2009. Determination of carbonate ion concentration and inner sphere carbonate ion pair in seawater by ultraviolet spectrophotometric titration, Mar. Chem. 115, 145-154. Millero, F.J., 2007. The marine inorganic carbon cycle, Chem. Rev. 107, 308-341.
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ACCEPTED MANUSCRIPT Mostofa, K.M.G., Liu, C.-Q., Zhai, W., Minella, M., Vione, D., Gao, K., Minakata, D., Arakaki, T., Yoshioka, T., Hayakawa, K., Konohira, E., Tanoue, E., Akhand, A., Chanda, A., Wang, B., Sakugawa, H., 2016. Ocean acidification and its potential impacts on marine ecosystems, Biogeosciencs 13, 1767-1786.
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Newton, J.A., Feely, R.A., Jewett, E.B., Williamson, P., Mathis, J., 2015. Global ocean acidification observing network: requirements and governance plan, 2nd Edition, GOA-ON, http://www.goa-on.org/documents/resources/GOA-ON_2nd_edition_final.pdf. Accessed on October 31, 2018.
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Sakugawa, H., 2016. Reviews and syntheses: Ocean acidification and its potential impacts on marine ecosystems, Biogeosciences 13, 1767-1786. Orr, J.C., Epitalon, J.-M., Dickson, A.G., Gattuso, J.-P., 2018. Routine uncertainty propagation for the marine carbon dioxide system. Mar. Chem. 207, 84-107.
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Patsavas, M.C., Byrne, R.H., Yang, B., Easley, R.A., Wanninkhof, R., Liu, X., 2015. Procedures for direct spectrophotometric determination of carbonate ion concentrations: Measurements in US Gulf of Mexico and East Coast waters, Mar. Chem. 168, 80-85.
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Pierrot, D.P., Wallace, D.W.R., 2006. MS Excel program developed for CO 2 system calculations, Carbon dioxide information analysis center, Oak Ridge National Laboratory. U.S. Department of Energy.
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Sabine, C.L., Feely, R.A., Gruber, N., Key, R.M., Lee, K., Bullister, J.L., Wanninkhof, R., Wong, C.S., Wallace, D.W.R., Tilbrook, B., Millero, F.J., Peng, T.-H., Kozyr, A., Ono, T., Rios, A.F., 2004. The ocean sink for anthropogenic CO 2 , Science 305, 367-371. Schlitzer, R., 2009. Ocean Data View, http://www.odv.awi.de.
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Schuster, U., Hannides, A., Mintrop, L., Körtzinger, A., 2009. Sensors and instruments for oceanic dissolved carbon measurements, Ocean Sci. 5, 547-558. Sharp, J.D., Byrne, R.H., Liu, X., Feely, R.A., Cuyler, E.E., Wanninkhof, R., Alin, S.R., 2017. Spectrophotometric determination of carbonate ion concentration: Elimination of instrument-dependent offsets and calculation of in situ saturation states, Environ. Sci. Technol. 51, 9127-9136. Sharp, J.D., Byrne, R.H., 2018. Carbonate ion concentrations in seawater: Spectrophotometric determination at ambient temperatures and evaluation of propagated calculation uncertainties, Mar. Chem. in press, doi:10.1016/j.marchem.2018.12.001
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ACCEPTED MANUSCRIPT Soli, A.L., Stewart, Z.I., Byrne, R.H., 2008. The influence of temperature on PbCO 3 0 formation in seawater, Mar. Chem. 110, 1-6. Wang, Z.A., Liu, X., Byrne, R.H., Wanninkhof, R., Bernstein, R.E., Kaltenbacher, E.A., Patten, J., 2007. Simultaneous spectrophotometric flow-through measurements of pH, carbon dioxide fugacity, and total inorganic carbon in seawater, Anal. Chim. Acta 596, 23-36.
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Wang, Z.A., Sonnichsen, F.N., Bradley, A.M., Hoering, K.A., Lanagan, T.M., Chu, S.N., Hammar, T.R., Camilli, R., 2015. In situ sensor technology for simultaneous spectrophotometric measurements of seawater total dissolved inorganic carbon and pH, Environ. Sci. Technol. 49, 4441-4449.
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Yang, B., Patasavas, M.C., Byrne, R.H., Ma, J., 2014. Seawater pH measurements in the field: A DIY photometer with 0.01 unit pH accuracy, Mar. Chem. 160, 75-81.
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Table 1 Operational sequence of the analyzer for determination of carbonate ion concentrations in aqueous samples. Step
Port
Syringe position (mL)
1
1
0→2.5
2
3
2.5→0
3
0→2.5
4
4
2.5→2.4
5
5
2.4→0
3
6
Time (m:ss)
0:00-0:52
0→2.5
4
2.5→2.4
9
5
2.4→0
10
1
0→1
2
1→1.0125
1
1.0125→2.5
2:35-3:05
3:05-3:25
12 13 14
3 3:48-4:35
16
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0→2.5
U N
A
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Syringe alternatively draws seawater and Pb(II) perchlorate solution for preliminary mixing.
Syringe pump dispenses and draws back 2.5 mL of mixture into the mixing coil for further mixing. Repeat steps 11-12 twice to complete mixing and record reference baseline signals of unmodified seawater (injected at step 9)
4
2.5→2.4
5
2.5→0
4:35-4:48 17
E C
2.5→0
C S
Fill syringe with seawater sampler Remove bubbles to waste. Transfer seawater to the flow cell for reference baseline spectra (obtained at step 15).
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3 3:25-3:48
15
I R
Repeat steps 1-5 two times. 1
11
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Syringe pump aspirates 2.5 mL seawater to fill the mixing coil and then pulls it back. 0.1 mL solution is dispensed via port 4 to remove bubbles and the remainder is sent through the flow cell for the 1st rinse. During this first rinse (steps 1-2),the spectra are recorded for the previous sample+Pb(II) mixture
0:52-2:35
7 8
Description
Remove bubbles to waste. Transfer analyte mixture to the flow cell, for spectra acquisition during steps 1-2 of the next sample
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Figure 1 Schematic diagram of the portable analyzer
Figure 2 Typical signal outputs of the analyzer. The operational steps are listed in Table 1.
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Figure 3 Data from deployments in a reef aquarium tank. (a) Continuous carbonate ion
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concentration data from the analyzer with calibration are compared to data without calibration and calculated carbonate ion concentrations from TA-DIC pairs. (b) Blank intensity ratio and
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continuous Int. values. (c) Relative differences between the measured carbonate ion concentrations and values calculated from the discrete TA and DIC sample pairs.
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Figure 4 Zoomed view of a complete diel cycle. (a) Continuously measured [CO 3 2-] from the
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analyzer and calculated [CO 3 2-]. (b) TA and DIC. (c) Temperature and salinity.
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Figure 5 Data from deployments at sea. (a) Continuous carbonate ion concentration data from
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the analyzer with calibration are compared to data without calibration and calculations of carbonate ion concentrations from TA-DIC pairs. (b) Blank intensity ratio and continuous Int.
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values. (c) Relative differences between the measured carbonate ion concentrations and values
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calculated from the discrete TA and DIC sample pairs.
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Figure 6 Field observations of carbonate ion concentrations at sea (August 2-14, 2017)
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Figure 7 Carbonate ion concentration profiles at S1 (left) and S2 (right).
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ACCEPTED MANUSCRIPT Highlights
First fully automated determination of carbonate ion concentration in seawater; A flow batch analyzer with laboratory-made hardware and software;
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High resolution field seawater analysis with rare maintenance.
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13-day real-time underway determination of carbonate ion in the South China Sea;
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Qipei Shangguan, Huilin Shu, Peicong Li, Kunning Lin, Robert H. Byrne, Quanlong Li, Dongxing Yuan, Jian Ma PII: DOI: Reference:
S0304-4203(18)30276-7 https://doi.org/10.1016/j.marchem.2019.01.007 MARCHE 3630
To appear in:
Marine Chemistry
Received date: Revised date: Accepted date:
1 November 2018 15 January 2019 27 January 2019
Please cite this article as: Q. Shangguan, H. Shu, P. Li, et al., Automated spectrophotometric determination of carbonate ion concentration in seawater using a portable syringe pump based analyzer, Marine Chemistry, https://doi.org/10.1016/ j.marchem.2019.01.007
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Automated spectrophotometric determination of carbonate ion concentration in seawater using a portable syringe pump based analyzer Qipei Shangguan1 , Huilin Shu1 , Peicong Li1 , Kunning Lin1 , Robert H. Byrne2 , Quanlong Li1 ,
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Dongxing Yuan1 , Jian Ma1
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1. State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, College of the Environment and Ecology, Xiamen
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University, Xiamen, 361102, People’s Republic of China 2. College of Marine Science, University of South Florida, 140 7 th Avenue South, St. Petersburg,
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Florida, 33701, United States
Corresponding author: [email protected] (Dr. J. Ma) 1
ACCEPTED MANUSCRIPT ABSTRACT Observations of seawater carbonate ion concentrations are critical to assess the ecological effects of ocean acidification. Nevertheless, currently available methods are labor intensive or
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too complex for field applications. Here, we report the design and performance of the first fully
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automated portable carbonate ion analyzer. Measurements are based on reaction of carbonate and
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chloride ions with Pb(II) followed by quantitative UV spectrophotometric detection of the
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PbCO3 0 complex. The core hardware is a syringe pump equipped with a multi-position valve that
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is controlled by software written in LabVIEW. Measurement precision is 1.1% (n=13) with a
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measurement frequency of 12 h-1 . The analyzer was used to continuously monitor carbonate ion
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concentration variations in a 2500 L coral reef tank for five days (test 1), and used for shipboard
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underway and vertical profile analysis during a 13-day cruise (test 2). The analyzer attained a combined standard uncertainty of 3.0%, which meets the Global Ocean Acidification Observing
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Network’s “weather level” goal. Through use of a syringe pump mechanism for mixing seawater
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and reagent solution, the analyzer is robust, functionally flexible, and quite suitable for continuous environmental monitoring under harsh conditions. KEYWORDS Seawater; carbonate ion; automated flow analysis; spectrophotometric detection; coral reef; underway analysis
2
ACCEPTED MANUSCRIPT 1. INTRODUCTION Approximately 30% of global anthropogenic carbon emissions have been absorbed by the oceans (Sabine et al., 2004). Chemical reactions that occur when anthropogenic CO 2 invades
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seawater reduce seawater pH, carbonate ion (CO 32-) concentration, and the saturation state of
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seawater with respect to biologically important CaCO 3 minerals (e.g. calcite and aragonite) (Doney et al., 2009). Extensive studies of this process, commonly referred to as ocean
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acidification, have demonstrated a wide variety of physiological effects on marine biota (Feely et
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al., 2004; Mostofa et al., 2016). To better understand how ocean acidification will affect future
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ecosystems, there is a clear need for carbonate mineral saturation state data with improved
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temporal and spatial resolution. Toward this end, improved autonomous techniques and
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instruments are needed to assess relationships between the rapidly changing ocean carbon cycle
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and consequent impacts on ocean ecology (Byrne et al., 2010; Byrne, 2014; Martz et al., 2015; Schuster et al., 2009).
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Because calcium concentrations ([Ca2+]) are nearly proportional to salinity, carbonate mineral saturation states are largely determined by variations in [CO 3 2-], which are typically calculated from any two of the four conventionally measured CO2 system parameters: pH, fugacity of CO 2 (fCO 2 ), dissolved inorganic carbon (DIC), and total alkalinity (TA) (Orr et al., 2018; Millero, 2007). Using a methodology analogous to spectrophotometric pH measurements
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(Rérolle et al., 2012), Byrne and Yao (2008) demonstrated the use of UV spectrophotometric determinations of Pb(II) equilibrium speciation in seawater (competitive complexation of Pb(II) by chloride and carbonate ions) to directly determine carbonate ion concentrations at a fixed
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temperature of 25 ℃. This research group subsequently applied the technique to directly
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determine [CO 3 2−] in the Arctic and the Eastern Pacific Oceans (Easley et al., 2013), and
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developed improved algorithms based on large datasets obtained in the Gulf of Mexico and east coast waters of the USA (Patsavas et al., 2015). Subsequent to these developments, Fajar et al.
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(2015) assessed the reliability of this methodology during cruises in the Atlantic Ocean and the
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Mediterranean Sea over a wider range of salinities and pH. Furthermore, Sharp et al. (2017)
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eliminated incongruous [CO 3 2−] values made with different spectrophotometers after correcting
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instrument-dependent offsets, and also introduced an empirical model to calculate in-situ
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carbonate mineral saturation states from shipboard observations. More recently, this
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methodology was extended to a wider temperature range, allowing measurements to be performed at in-situ temperatures (Sharp and Byrne, 2018). In addition to the spectrophotometric methods, acidimetric titrations with UV detection (Martz et al., 2009) and micro carbonate ion electrodes have been applied for carbonate ion concentration measurements (Cai et al., 2016; de Beer et al., 2008; Han et al., 2014).
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The precision as well as the spatial and temporal resolution of carbonate measurements can be improved by automation (Ma et al., 2016). Here, we report the development of a novel, low- maintenance, automated analyzer for robust [CO 3 2−] measurements that is based on
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recordings of UV Pb(II) spectra in seawater. The core hardware is a syringe pump equipped with
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a multi-position valve that is controlled by software written in LabVIEW (Ma et al., 2018). The
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objective in this work was to design an instrument capable of providing high frequency, as well as high precision and accurate measurements of [CO 3 2-].
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2. PRINCIPLES
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Procedures to directly determine [CO 3 2−] in seawater (Byrne and Yao, 2008) are based on
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observations that the speciation and absorbance characteristics of dissolved Pb(II) upon its
Measurement procedures
for determining
carbonate
ion concentrations,
like
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2008).
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addition to seawater and complexation as carbonate and chloride species (Byrne, 1981; Soli et al.,
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spectrophotometric pH determinations, involve observations of absorbance ratios to enhance measurement precision. While Pb(II) spectra in seawater with different carbonate ion concentrations exhibit substantial variations at 250 nm, absorbances at 234 nm show much smaller variations (Byrne and Yao, 2008). Carbonate ion concentrations can therefore be quantified by monitoring absorbance ratios (A250 /A234 ) along with characterizations of Pb(II)
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thermodynamic and optical properties in seawater. Carbonate ion concentrations are calculated with the following equation: -log[CO 3 2-] = log{(CO3 β1 )/(e2 )}+ log{(R-e1 )/(1-Re3 /e2 )} is the formation constant of the lead carbonate complex PbCO 3 0 ,
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CO3 β1
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parameters are molar absorptivity ratios: e1
PbCO 250nm ， e2 Pb 250nm ， e3 Pb 234nm PbCO 234nm PbCO 234nm PbCO 234nm 3
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3
and the ei
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where
(1)
(2)
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Absorbance at 350 nm is also measured to correct for any small baseline changes (350 nm is
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outside the region of absorbance by Pb(II) carbonate and chloride species). R is calculated in the
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form (A250 -A350 )/(A234 -A350).
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The salinity (S) dependencies of the parameters in Eq. (1) were determined at 25 ℃ in previous works (Easley et al., 2013; Patsavas et al., 2015; Sharp et al., 2017). The most recent
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parameterizations at 25 ℃ were produced and verified by Sharp et al. (2017) after correction of
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small but significant instrumental differences among previously used electrical and optical systems, and the parameters are given by: log{(CO3 β1 )/(e2 )}=6.87057-0.142142 S+0.00190892 S2
(3)
e1 =0.787458-0.0339648 S+0.000583574 S2
(4)
e3 /e2 =2.52288-0.0383205 S
(5)
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3. MATERIALS AND METHODS 3.1 Reagents Pure water (18.2 M cm) obtained from a Millipore Purification System was used for
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preparation of all solutions. Analytical grade sodium bicarbonate (NaHCO 3 ), sodium chloride
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(NaCl), sodium hydroxide (NaOH), and hydrochloric acid (HCl) were purchased from
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Sinopharm Chemical Reagent Co., China and used without further purification. Lead perchlorate (Pb(ClO 4 )2 ) purchased from Fisher Scientific (99% purity) was used to prepare a 2.2 mmol/L
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titrant solution. In order to calibrate the analyzer, synthetic saline solutions of 0.7 mol/L NaCl
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and 2 mmol/L NaHCO 3 were used in this study in addition to natural seawater.
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3.2 Apparatus
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The fully automated carbonate ion concentration measurement manifold is shown in Figure
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1. A programmable syringe pump (XLP6000, Tecan) was used to deliver variable volumes of
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seawater and lead titrant to the various components of the analyzer. The syringe pump incorporated a precise stepper motor and a gas-tight 2.5 mL syringe, and was connected to a 6-port distribution valve. The volumetric precision of the pumps for a full piston stroke delivery was better than ± 0.05%. PTFE tubing, 0.8 mm i.d. with standard PEEK fittings (1/4-28, IDEX), was used for liquid connections throughout the system. Although the syringe itself can act as a
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mixing chamber, an additional mixing coil was used to facilitate complete mixing (discussed below). The fused quartz flow-cell body was custom- made with a 100 mm pathlength. The 3x3x100
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mm cell had an internal volume of ~1 mL including connecting tubing, and was inserted into a
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custom-engineered cuvette holder equipped with two collimating lenses (74-UV, Ocean Optics).
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These lenses were connected to the light source (continuous wave deuterium lamp, D-2000, Ocean Optics) and the detector (CCD spectrophotometer, Maya2000 Pro, Ocean Optics) via
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optical fibers and SMA-905 optical connectors. Solarization-resistant fibers with an internal
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diameter of 600 μm (XSR, Ocean Optics) were used to prevent transmission degradation in the
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UV region.
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Temperature control is critical for precise measurements. Before entering the flow system,
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the sample was thermostated to 25±0.1 ℃ by passing through a quartz coil (310 cm length, 21
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mL volume) immersed in a sealed water bath. This allowed seawater samples with temperatures ranging from 5~45 ℃ to be precisely adjusted to 25 ℃ with a precision better than 0.1 ℃. All components of the flow system (except for the deuterium light source) were housed in a constant temperature air bath, made from a laboratory- modified car refrigerator. This analyzer combined Peltier cooling with a heating mat and a Proportional–Integral–Derivative (PID) controller to maintain the optical cell at 25±0.1 ℃. All temperature probes in the air and water baths were 8
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calibrated with a platinum resistance thermometer (8821 IP67 HACCP RTD Thermometer, AZ Instrument Corp). 3.3 Analytical procedure
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Prior to the implementation of continuous measurement procedures, the light source is
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switched off. A dark spectrum is obtained (integration time ~20 ms), and subsequently
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subtracted from counts acquired during measurement procedures with the light source on. A baseline spectrum is recorded before each measurement cycle to compensate for lamp aging as
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well as for variations in the properties of seawater samples.
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Seawater samples pass slowly (~8 minutes) through the quartz temperature-controlled cell
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and then enter the automated carbonate analyzer. The 17-step analytical procedure programmed
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in LabVIEW is shown in Table 1. Associated spectrophotometric signals are shown in Figure 2.
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Measurements begin by rinsing the syringe, coil and flow cell three times (steps 1-6). Step 4
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removes air bubbles by directing 0.1 mL of the solution in the optical cell to the waste receptacle via port 4. This highly-essential bubble removal step is used before introducing all solutions into the flow cell. The cleaning steps (1-6) reduce contamination from previous samples and return absorbance signals to baseline levels. In steps 7-9, the flow cell is filled with seawater to obtain and record a reference spectrum (i.e. a background spectrum without Pb(II)). The syringe is then (a) partially filled with a seawater sample (1 mL), followed by (b) a 12.5 μL addition of Pb(II) 9
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perchlorate solution, and then (c) addition of more seawater, creating a total volume of 2.5 mL (steps 10-12). In order to rapidly and completely mix the seawater and lead perchlorate solution, the mixture in the syringe is then injected into the mixing coil (1.4 m length, 1.6 mm i.d., 2.8 mL
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total volume) and withdrawn back into the syringe 3 times (steps 13-15). The mixed solution is
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then dispensed into the flow cell (steps 16-17), and a spectrum of the seawater/titrant mixture is
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recorded. The syringe and mixing coil then undergo a rinse in preparation for subsequent measurements. All spectral acquisitions are performed when transmitted optical signals are stable,
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which occurs less than 30 seconds after sample injection into the flow cell (Figure 2). A total of
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50 spectra scans are averaged to improve the signal/noise ratio. A flow rate of 3.75 mL/min was
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chosen for aspiration to avoid formation of bubbles that can occur during rapid decreases in
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3.4 System calibration
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pressure. For quick cleaning, a higher flow rate (16.7 mL/min) was used in all dispensing steps.
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Spectrophotometric determinations of carbonate ion concentrations implicitly assume that the analytical wavelengths and band-pass are identical to those used to determine the absorptivity calibration parameters. The Agilent 8453 spectrophotometers used in previous studies have a spectral resolution of 1.5 nm. The wavelength accuracy claimed by the manufacturer is within ±0.5 nm, and is necessarily validated with wavelength standards before [CO 3 2−] measurements (Sharp et al., 2017). In comparison, the Maya2000 Pro spectrophotometer in our analyzer has a 10
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similar 1- nm bandpass, but the wavelength accuracy is uncertain over the spectral region of interest. To address this issue, we established a functional relationship between RA (R value from the analyzer spectrophotometer) and RS (R value from a manually operated standard
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spectrophotometer), similar to the approach of Yang et al. (2014). RA was converted to RS, which
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procedure can be found in the Supplementary Material.
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was used in equation (1) to produce final values of [CO 3 2−]. A detailed description of this
RA and RS exhibited good linearity: RS = k·RA + Int., where k and Int. are slope and
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intercept, respectively. However, it was observed that the calibration curve can shift during
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long-term operation of the analyzer due to drift in signal intensity and non- linearity of the CCD
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detector. Accordingly, the intercept (Int.) in the RS vs RA relationship was considered as
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time-dependent, with the slope (k) remaining constant but Int. being variable. A time-dependent
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calibration routine was then devised as follows: (1) A sample with known [CO 3 2-] is measured on
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the analyzer every two days; (2) The Int. value for the analyzer at any time (t) is adjusted to produce an accurate [CO 32-] value for this sample. This process results in a new “perfect” calibration relationship at time (t) of the calibration; (3) The time-dependent Int. values produced by this process (e.g., Int.1 at time t1 and Int.2 at time t2 ) are linearly interpolated to provide Int. values at any time between calibrations. RS was thereafter determined with RA from the analyzer and an Int. value appropriate at the time of measurement. The [CO 3 2-] values used in the 11
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calibrations were obtained (calculated) from carbonate system parameters (TA and DIC) and thermodynamic relationships. Certified reference materials (CRMs) contain mercuric species, which may alter Pb(II) equilibria and contribute to UV spectra, were not directly used for
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been collected and carefully analyzed for TA and DIC (see 3.5).
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calibrations. Alternatively, field calibrations were conducted using seawater samples that had
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3.5 Sampling and field application
The precision and accuracy of the analyzer system were evaluated in both shore-based and
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shipboard laboratories.
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From May 2-7, 2017, the analyzer was deployed in an artificial reef aquarium tank for five
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days to observe diurnal changes in carbonate ion concentrations. The tank volume was 2500 L
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and the saline water was prepared using sea salt (Instant Ocean) and deionized water. The tank
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contained marine fish (surgeonfish, angelfish, damselfish), and scleractinian corals (Acropora,
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Pocilopora damicornis, montipora, stylophora pistilata) from Hainan province in southern China. System controls included twenty 80-watt T5HO lamps with HEP ballast (ATI), two protein skimmers (one from Aqua Excel and the other from Reef Octopus), four circulation pumps (Hagen), and two wavemakers (EcoTech Marine). During the five-day field trial, salinity was measured with a portable conductivity meter, ProfiLine Cond 3110 (WTW), and temperature was recorded every half minute using a HOBO Water Temp Pro v2 (Onset). 12
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The carbonate ion analyzer was deployed during cruise KK1703 on the XMU R/V Tan Kah Kee during August 2-14, 2017. The cruise included testing of marine acoustic equipment in the South China Sea (SCS) until August 6, and then proceeded to the western Pacific across the
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Luzon Strait on August 7, 2017. Throughout the cruise, seawater from the ship’s underway
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seawater line flowed into a ~150 mL sampling chamber, with a nominal throughput of 2 L/min.
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The sampling chamber was continuously flushed, thereby minimizing the presence of bubbles and particles. Samples were aspirated from the chamber to the analyzer, and processed as
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described in section 3.3. Temperature and salinity were measured with a thermosalinograph
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mounted near the ship’s seawater intake (SBE21, Sea-Bird Electronics), and shipboard GPS
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recorded time and position. In addition to real-time underway monitoring, discrete samples from
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two vertical profiles were measured on board. Hydrographic data (temperature, salinity, and
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depth) at the two sites were obtained with a rosette- mounted CTD (SBE9, Sea-Bird Electronics).
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Profiling Station 1 (S1), with 22 depth levels to 5000 m, was located at 19.31°N, 125.22°E, and Station 2 (S2), with 22 depth levels between the surface and 4000 m, was located at 19.66°N, 125.55°E. Seawater samples for discrete [CO 3 2-] measurements were collected in Niskin bottles, transferred to 250 mL borosilicate glass bottles, and sealed using greased ground glass stoppers. The samples were kept in the dark at room temperature without poisoning and analyzed within 9
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hours. Figure S1 shows the cruise route and the position of sampled stations plotted with Ocean Data View (Schlitzer, 2009). During the shore-based trial, 40 discrete sample pairs were collected in the reef tank for TA
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and DIC analysis (Dickson et al., 2007). Of these, 3 sample pairs were used for system
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calibration, and the others were used for evaluation of accuracy. During the shipboard trial, 39
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discrete sample pairs were collected from the ship’s underway system and 5 of these were used for system calibration. A total of 44 vertical profile sample pairs were collected. Vertical profile
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sample pairs were taken immediately after collection of discrete carbonate ion samples from
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each Niskin bottle. Each sample was poisoned with a few μL of saturated HgCl2 solution at the
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time of collection. TA was measured by potentiometric titration and Gran function end-point
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determination with a commercial open-cell Kloehm digital syringe pump-based titrator
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(AS-ALK2, Apollo SciTech) and a ROSSTM combination electrode 8102 (Thermo Fisher
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Scientific). DIC was measured by acidification of seawater samples (0.5 mL) with 0.5 mL H3 PO4 (10%, v/v) and subsequent quantification of released CO 2 with a commercial infrared gas analyzer (AS-C3, Apollo SciTech). Both TA and DIC measurements were calibrated against certified reference materials (CRMs) provided by Dr. Dickson of Scripps Institute of Oceanography. The accuracy and precision of both methods were ±2-3 μmol/kg (Huang et al., 2012; Millero, 2007). Carbonate concentrations ([CO 3 2−]) were calculated from TA-DIC with 14
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CO2SYS version 2.1 (Pierrot and Wallace, 2006) using the carbonic acid dissociation constants of Lueker et al. (2000), the total-boron-to-salinity ratio from Lee et al. (2010), and K HSO4 from Dickson et al. (1990).
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3.6 Data analysis
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Differences between [CO 3 2-] values that were directly measured with the analyzer
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([CO 3 2-]mea) and values that were calculated from TA and DIC ([CO 3 2-]cal) are reported as Δ[CO 3 2-]=[CO3 2-]mea-[CO 32-]cal. Sharp and Byrne (2018) pointed out that Δ[CO 3 2-] values are
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proportional to [CO 3 2-] itself. Relative differences and relative precision were used throughout
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this paper. The former refers to the difference between measured and calculated (from TA and
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DIC) carbonate ion concentrations for samples, whereas the latter refers to the difference
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between the repetitive measurement of the same sample.
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The importance of estimating uncertainty of carbonate system variables has been addressed
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in the context of the Global Ocean Acidification Observing Network (GO A-ON) (Newton et al., 2015). Combined standard uncertainties should include both random and systematic sources of uncertainty (Orr et al., 2018). Mirroring the procedures of Sharp and Byrne (2018), relative precision from the analyzer was assigned as the random component. Relative standard deviation (RSD), obtained from mean value of [CO 3 2-]cal (µ) and the standard deviation of Δ[CO 32-] (δ), was used to assess the systematic component, which consisted of the uncertainties in the 15
ACCEPTED MANUSCRIPT parameters of the Pb(II) model (eq. (1)-(3)) and the analyzer output (RSD = δ/µ × 100%). 3.7 Caution: The lead-enriched seawater is toxic to aquatic life and should be collected via special treatment (e.g. passing through ion-exchange resin or treated with other techniques to
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remove Pb ions) before being discarded (Sharp et al., 2017).
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4. RESULTS AND DISCUSSION
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4.1 Calibration and instrument performance
The relationship between RS and RA can be expressed by the following equation: R2 =0.9972, n=15
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RS = 1.0491RA + Int.,
(6)
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Once the analyzer was constructed, we observed that its performance was affected by issues
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with optical detection. For this analyzer, a value of 1.0491 was assigned to the slope (k) based on
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multiple experimental measurements as described in 3.4. This treatment was an empirical
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approach as laboratory tests showed that slope displayed good reproducibility while optical shift
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was directly reflected in the intercept (Int.). Output signals for each of the three wavelengths used in carbonate ion analyses are shown in Figure 2, where signals at 234 nm were considerably lower than signals at the other two wavelengths. In order to assure the linear response range to Beer's Law at 234 nm after mixing of the sample and Pb(II) titrant, the final Pb(II) concentration in the mixture was adjusted to ~11.2 μmol/kg, somewhat lower than the 15.2 μmol/kg concentration used by Sharp et al. (2017). A 16
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discussion of the influence of final Pb(II) concentrations (i.e. perturbation effects) can be found in the Supplementary Material. The short term precision of [CO 3 2−] measurements, evaluated by consecutively analyzing
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seawater stored in an 18 L polycarbonate container, revealed that [CO 3 2-] = 101±1.1 μmol/kg
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(1.1%, n=13). The sampling frequency throughout this analysis was 12 h-1 .
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4.2 Field measurements of carbonate ion concentrations
During two field tests, the automated carbonate ion analyzer worked continuously without
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any maintenance or intervention. After obtaining the raw data, outliers (≥3 sigma residuals) were
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discarded to ensure data quality. The remaining carbonate ion concentration data were smoothed
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by taking running 5-point averages.
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4.2.1 Field measurements of carbonate ions in aquarium tank
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During the five-day field trial in the reef aquarium tank, a total of 1,659 measurements were
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obtained and ~3.1% of the data were discarded as outliers. Figure 3a shows [CO 3 2-] values obtained using the calibration procedures described in sections 3.4, as well as [CO 3 2-] values obtained by treating the Int. value as a constant. Without correcting for time-dependent effects on Int., the [CO 3 2-] values showed a significant upward trend. Considering the blank intensity ratio (Figure 3b), an optical drift was apparent. Rs for each measurement was necessarily compensated by a corresponding Int. value determined using three TA/DIC pairs and linear 17
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interpolation. Structural breaks in the blank intensity ratio data occurred after Day 4, likely due to unintentional movement of flow cell position, but did not affect carbonate ion concentration results.
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As shown in Figure 3c, relative differences in carbonate concentrations are evenly scattered
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around zero; the mean and standard deviation are 1.0% ± 7.3% (n=37). Parameters in the Pb(II)
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model (eq. (1)-(3)) were optimized for [CO 3 2-] values below 260 μmol/kg (Sharp et al. 2017). For samples with carbonate ion concentrations in the same range as those observed in our work,
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the mean relative difference and standard deviation decreased to -0.1% ± 3.7% (n=14).
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There are several difficulties in this validation and assessment of field measurement
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uncertainties. The coral reef water was prepared using commercial sea salt and may be somewhat
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different from natural seawater in composition and physicochemical properties. It is likely that
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Pb(II) speciation and thermodynamics were affected by the sample matrix, increasing the
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uncertainties in Pb(II) model parameters (eq. (1)-(3)). Although the Int. calibration routine somewhat reduced this effect, rapid changes in seawater properties might degrade calibration effectiveness and CO 2 system internal consistency. Because of the heterogeneity of the water in the aquarium, representative sampling might be a problem contributing to measurement uncertainty. The portable salinity meter used in this work has a resolution of 0.1, corresponding to ~1% uncertainty in [CO 3 2-]. Overall, the RSD obtained in this trial was 3.7% for [CO 32-] 18
ACCEPTED MANUSCRIPT below 260 μmol/kg and 9.2% for the whole dataset. Though RSD (systematic component of the uncertainty) might seem to be high, especially for high [CO 3 2-] samples, there was good agreement in the temporal variability between calculated and measured [CO 3 2-]. An approximate
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100 μmol/kg daily variation in carbonate ion concentrations was observed (Figure 4). Organic
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carbon metabolism (photosynthesis and respiration) and inorganic carbon transformations
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(calcification and dissolution) all caused changes in [CO 32-]. Diel patterns in temperature and [CO 32-] mirrored those for DIC and TA. Photosynthetic uptake of CO 2 resulted in reduced DIC
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and elevated [CO 3 2-] (due to increased pH) when temperature and light were high (8 am to 6 pm),
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while high DIC and low [CO 3 2-] occurred at night. Changes in TA were caused by CaCO 3
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calcification and dissolution, which reduced [CO 3 2-] in the light due to calcification, and gave
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rise to increasing [CO 3 2-] in the dark due to dissolution. Interestingly, salinity showed a slight
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systematic decrease during periods of measurement, possibly caused by sustained input of
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low-salinity nutrient solutions. Data from the analyzer provided real- time variability of [CO 32-] (Figure 4a), while discrete TA and DIC only reflected running averages with lower temporal resolution (Figure 4b). Hence, this analyzer will be especially useful in environments where coral productivity and calcium carbonate processes are highly dynamic. 4.2.2 Field measurements of carbonate ions during research cruise
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During the 13-day research cruise, the carbonate ion analyzer measured both underway (3101 measurements) and discrete samples. About 1.3% of the data were discarded as outliers. A total of 39 TA-DIC sample pairs were collected and 5 of these pairs were used for calibration. As
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shown in Figure 5, the blank intensity ratio experienced the same downward trend observed in
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the coral tank trial. With the Int. calibration routine, the analyzer exhibited good accuracy and
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was immune to optical drift (Figure 5c). The relative differences between calculated and measured [CO 3 2-] were between -3.6% to 9.0%, with a mean value and standard deviation of 0.6%
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± 2.7% (n=34).
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The distributions of carbonate ion concentrations are presented in Figure 6. The observed
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[CO 32-] during this cruise ranged from 198 μmol/kg to 248 μmol/kg, with the lowest values and
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largest variability in coastal seas, where upwelling events and river plumes had significant
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impacts (Cao et al., 2011; Gan et al., 2009; Guo and Wong, 2015). Nevertheless, [CO 32-]
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remained fairly constant in the Northern open SCS. From August 4 to 6, the analyzer yielded 846 measurements with an average of 223 μmol/kg. RSD was 1.0% (n=846). After transitioning to the Western Pacific, [CO 32-] increased by ~10 μmol/kg. Excluding profile sample analysis, 1229 measurements were obtained from August 8 to 12 with a RSD of 1.8% (average=231 μmol/kg). Although these results demonstrated the stability of this analyzer under harsh conditions at sea,
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use of the analyzer in coastal areas that have higher short-term variability may be especially valuable and informative. The purposes of our vertical profile analyses were: (1) evaluation of analyzer accuracy over
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a wide range of conditions in seawater and (2) assessment of analyzer precision by performing
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triplicate measurements for each sample. As shown in Figure 7, good agreement was observed
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between carbonate analyzer measurements and carbonate calculations from TA-DIC. The analyzer achieved a short term relative precision of 1.4 % ±1.2% (n=22) for S1 and 1.5% ± 0.8%
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(n=22) for S2, which were slightly higher than the typical precision observed using artificial
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seawater in a land-based laboratory (1.1%). This difference can be attributed to gas exchange
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because triplicate bottle measurements took ~15 min, and during this time the bottle contents
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were exposed to the air. Relative accuracy for the two profiles, ranged from -2.2% to 0.9% for
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S1 with an average of -0.3% ± 1.3% (n=22), and from -4.1% to 9.8% for S2 with an average of
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3.1% ± 3.7% (n=22). Based on these results, this analyzer can provide good accuracy over the wide range of [CO 32-] that may be encountered in ocean environments. The detailed data are shown in Figure S4 and S5. Overall, comparisons of data obtained at sea, including surface underway samples (n=34) and two vertical profiles (n=44), indicated a relative accuracy of 1.0% ± 3.0 % (n=78). Based on calculation of RSD for the whole dataset, a value of 2.8% (n=78) was assigned to the systematic 21
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component of uncertainties. Based on the relative precision obtained in the laboratory and at sea, a value of 1.1% was assigned for the random component. Estimates for the systematic component (2.8%) and random component (1.1%) were combined in quadrature to obtain an
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estimate of 3.0% for combined standard uncertainty. Sharp and Byrne (2018) reported a
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combined standard uncertainty of 1.9% for manual handling of spectrophotometric [CO 32-]
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values. Uncertainty in the analyzer output was therefore estimated to be 2.3%. In the context of GOA-ON’s measurement quality goals, this analyzer meets the requirements of GOA-ON’s
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weather objective (10%) and falls slightly short of the climate objective (1%) (Newton et al.,
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2015). The primary source of uncertainty in the analyzer output came from optical drift and the
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calibration routine required to address the drift. Ongoing research will include deployments of
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this instrument with aged seawater stored in a gas- impermeable bag with known TA and DIC
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values. The valve for selection of this bag’s contents at port 6 will allow automated calibration
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rather than use of collected discrete samples. Due to small sample consumption requirements (~12.5 mL per sample), a 3-L bag will enable 10 days of operation with hourly calibration and should significantly improve data quality. Sharp and Byrne (2018) recently extended the Pb(II) model to a temperature range of 3 to 40 ℃, allowing all measurements to be performed at in-situ temperatures. Further development and testing of this analyzer will include elimination of temperature control components, thus 22
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reducing cost and complexity. 4.3 CONCLUSIONS AND IMPLICATIONS Carbonate ion concentrations can be considered as the fifth independently measurable inorganic carbon system.
Spectrophotometric [CO 3 2−]
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for describing the
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parameter
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measurements are precise, fast, and easily adapted for automated systems. This work presents
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results of the first automated analyses of carbonate ion concentrations in aqueous samples, demonstrating high sample throughput, and precision comparable to other methods (e.g., manual
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operation, calculation from other parameters, etc.). Based on shore-based and shipboard testing
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and performance assessment (precision, accuracy, uncertainty) in this work, this analyzer is
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especially suitable for highly dynamic and complex systems where monitoring of [CO 3 2-] and
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saturation states with high-resolution is required. These systems might include coral reef
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ecosystems, coastal areas subject to upwelling and river inputs, and laboratory mesocosm
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experiments. Sharp and Byrne (2018) noted that, for low-salinity samples, trace amounts of PbCO3 (s) might form, thereby reducing measurement quality. Absorbance measurements should be performed promptly after mixing of the lead perchlorate solution with seawater. Samples measured in this work all had salinities above 32.5. If this analyzer is deployed in low-salinity regions in the future, it could benefit from fast acquisition of spectra from a CCD detector, and
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flexibly-adjusted amounts of added lead perchlorate using the syringe pump might also alleviate this potential issue. This analyzer adds flexibility to future development of an integrated analyzer capable of
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on- line measurements of two or more carbonate parameters for comprehensive descriptions of
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the inorganic carbonate system (Wang et al., 2007, 2015). Because of the highly precise
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sample/reagent ratio obtained with the syringe pump used in this work, it is very easy to use a pH indicator instead of Pb(II) titrant, and thereby obtain pH measurements (Liu et al., 2006), or
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implement single point titrations for TA analysis (Li et al., 2013). With further optimization, this
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analyzer can provide simple, portable and user-friendly spectrophotometric determinations of
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Acknowledgements
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nutrients, metals, and other environmental and marine parameters.
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This work was financially supported by the National Natural Science Foundation of China (41576097), Natural Science Foundation of Fujian Province (2014J05050) and Program for New Century Excellent Talents in Fujian Province University (2016). We sincerely acknowledge Dr. Di Qi, Dr. Xinqing Zheng, Mr. Yan Li and Ms. Chenying Wang (TIO) for instrument testing, Dr. Yongming Huang (XMU) for instrument design, Ms. Liguo Guo and Ms. Yan Li (XMU) for measuring TA and DIC samples, the captain and crews of R/V Tan Kah Kee for their help during 24
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the cruise, Dr. Xianghui Guo for data discussions and MEL visiting scholar Tom Trull (ACE CRC) for proofreading. The critical comments from the associate editor and three journal
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reviewers greatly improved the manuscript.
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Dickson, A.G., 1990. Thermodynamics of the dissociation of boric-acid in synthetics seawater from 273.15 to 318.15 K, Deep-Sea Res. 37, 755-66.
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Dickson, A.G., Sabine, C.L., Christian, J.R., 2007. Guide to best practices for ocean CO2 measurements, PICES Spec. Publ. 3. Doney, S.C., Fabry, V.J., Feely, R.A., Kleypas, J.A., 2009. Ocean acidification: The other CO 2 problem, Annu. Rev. Mar. Sci. 1, 169-192. Easley, R., Patsavas, M.C., Byrne, R.H., Liu, X., Feely, R.A., Mathis, J.T., 2013. Spectrophotometric measurement of calcium carbonate saturation states in seawater, Environ. Sci. Technol. 47, 1468-1477. Fajar, N.M., García-Ibáňez, M.I., Sanleón-Bartolomé, H., Álvarez, M., Pérez, F.F., 2015. Spectrophotometric measurements of the carbonate ion concentration: Aragonite saturation states in the Mediterranean Sea and Atlantic Ocean, Environ. Sci. Technol. 49, 11678-11687. 26
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Lee, K., Kim, T.W., Byrne, R.H., Millero, F.J., Feely, R.A., Liu, Y.M., 2010. The universal ratio of boron to chlorinity for the North Pacific and North Atlantic oceans, Geochim. Cosmochim. Acta, 74, 1801-11.
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Li, Q., Wang, F., Wang, Z.A., Yuan, D., Dai, M., Chen, J., Dai, J., Hoering, K.A., 2013. Automated spectrophotometric analyzer for rapid single-point titration of seawater total alkalinity, Environment. Sci. Technol. 47, 11139-11146.
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ACCEPTED MANUSCRIPT Soli, A.L., Stewart, Z.I., Byrne, R.H., 2008. The influence of temperature on PbCO 3 0 formation in seawater, Mar. Chem. 110, 1-6. Wang, Z.A., Liu, X., Byrne, R.H., Wanninkhof, R., Bernstein, R.E., Kaltenbacher, E.A., Patten, J., 2007. Simultaneous spectrophotometric flow-through measurements of pH, carbon dioxide fugacity, and total inorganic carbon in seawater, Anal. Chim. Acta 596, 23-36.
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Table 1 Operational sequence of the analyzer for determination of carbonate ion concentrations in aqueous samples. Step
Port
Syringe position (mL)
1
1
0→2.5
2
3
2.5→0
3
0→2.5
4
4
2.5→2.4
5
5
2.4→0
3
6
Time (m:ss)
0:00-0:52
0→2.5
4
2.5→2.4
9
5
2.4→0
10
1
0→1
2
1→1.0125
1
1.0125→2.5
2:35-3:05
3:05-3:25
12 13 14
3 3:48-4:35
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0→2.5
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Syringe alternatively draws seawater and Pb(II) perchlorate solution for preliminary mixing.
Syringe pump dispenses and draws back 2.5 mL of mixture into the mixing coil for further mixing. Repeat steps 11-12 twice to complete mixing and record reference baseline signals of unmodified seawater (injected at step 9)
4
2.5→2.4
5
2.5→0
4:35-4:48 17
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2.5→0
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Fill syringe with seawater sampler Remove bubbles to waste. Transfer seawater to the flow cell for reference baseline spectra (obtained at step 15).
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3 3:25-3:48
15
I R
Repeat steps 1-5 two times. 1
11
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Syringe pump aspirates 2.5 mL seawater to fill the mixing coil and then pulls it back. 0.1 mL solution is dispensed via port 4 to remove bubbles and the remainder is sent through the flow cell for the 1st rinse. During this first rinse (steps 1-2),the spectra are recorded for the previous sample+Pb(II) mixture
0:52-2:35
7 8
Description
Remove bubbles to waste. Transfer analyte mixture to the flow cell, for spectra acquisition during steps 1-2 of the next sample
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Figure 1 Schematic diagram of the portable analyzer
Figure 2 Typical signal outputs of the analyzer. The operational steps are listed in Table 1.
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Figure 3 Data from deployments in a reef aquarium tank. (a) Continuous carbonate ion
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Figure 4 Zoomed view of a complete diel cycle. (a) Continuously measured [CO 3 2-] from the
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analyzer and calculated [CO 3 2-]. (b) TA and DIC. (c) Temperature and salinity.
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Figure 5 Data from deployments at sea. (a) Continuous carbonate ion concentration data from
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values. (c) Relative differences between the measured carbonate ion concentrations and values
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Figure 6 Field observations of carbonate ion concentrations at sea (August 2-14, 2017)
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Figure 7 Carbonate ion concentration profiles at S1 (left) and S2 (right).
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ACCEPTED MANUSCRIPT Highlights
First fully automated determination of carbonate ion concentration in seawater; A flow batch analyzer with laboratory-made hardware and software;
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High resolution field seawater analysis with rare maintenance.
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13-day real-time underway determination of carbonate ion in the South China Sea;
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