An optimized method is presented to determine dissolved free (DFCHO) and
dissolved combined carbohydrates (DCCHO) in saline matrices, such as oceanic
seawater, Arctic ice core samples or brine using a combination of a
desalination with electro-dialysis (ED) and high-performance anion exchange
chromatography coupled to pulsed amperometric detection (HPAEC-PAD). Free
neutral sugars, such as glucose and galactose, were found with 95 %–98 %
recovery rates. Free amino sugars and free uronic acids were strongly
depleted during ED at pH=8, but an adjustment of the pH could result in
higher recoveries (58 %–59 % for amino sugars at pH=11; 45 %–49 % for
uronic acids at pH=1.5). The applicability of this method for the analysis
of DCCHO was evaluated with standard solutions and seawater samples compared
with another established desalination method using membrane dialysis. DFCHO
in field samples from different regions on Earth ranged between 11 and 118 nM
and DCCHO between 260 and 1410 nM. This novel method has the potential to
contribute to a better understanding of biogeochemical processes in the
oceans and sea–air transfer processes of organic matter into the atmosphere
in future studies.
Introduction
The majority of organic matter (OM) in oceanic seawater can be assigned to the chemical classes of proteinogenic amino acids, carbohydrates and lipids (Benner and Kaiser, 2003; Kaiser and Benner, 2009; Kuznetsova and Lee, 2002; Marty et al., 1979; Skoog et al., 1999; Wakeham et al., 1997). Previous studies uncovered that combined amino acids are the most abundant organic substances in fresh particles sinking within the water column (Wakeham et al., 1997), although more
recent studies indicate that carbohydrates may be equally abundant (Cisternas-Novoa et al., 2019), while
hydrolyzable carbohydrates dominate the chemical composition of dissolved
organic matter (DOM) (Kaiser and Benner,
2009; McCarthy et al., 1996). Marine carbohydrates also appear in high
concentrations in other related saline matrices, such as ice cores, brine
and melt ponds in the Arctic (Ewert and Deming, 2013; Underwood et al., 2013; Zeppenfeld et al., 2019). Hence, a reliable analysis of carbohydrates is essential for understanding biogeochemical processes in the ocean and their impact on Earth's atmosphere.
Most marine carbohydrates exist as polysaccharides or combined carbohydrates
(CCHO), which are linear or branched chains of monosaccharides, including
hexoses, pentoses, deoxy sugars, amino sugars and uronic acids. In aquatic
environments, CCHO either appear in a particulate (PCCHO) or dissolved form
(DCCHO). In living marine microorganisms including prokaryotes,
polysaccharides assume their functions as structural compounds or as energy
storage (Skoog and Benner, 1997).
Storage carbohydrates mainly consist of glucose, such as laminarin and
other glucans, while structural heteropolysaccharides (e.g., galactans) such
as occurring in algal cell walls can contain a lot of galactose, mannose and
rhamnose (McCarthy et al., 1996). Furthermore, an
elevated release of polysaccharides by phytoplankton, mostly of gelatinous
nature, has been associated with stress situations, such as a deficiency of
nutrients, freezing or fluctuating water potential (Berman-Frank
et al., 2007; Bianchi and Canuel, 2011; Borchard and Engel, 2012, 2015;
Ittekkot et al., 1981; Krembs et al., 2002; Krembs and Deming, 2008). These
exuded polysaccharides are relatively depleted in glucose and galactose and
mainly contain acidic sugars, fucose, rhamnose and arabinose in their
chemical structure (Borchard and Engel, 2012; Passow, 2002). Even though polysaccharides are ubiquitous in nature, a recent study revealed that the individual sugar pattern is different between algae and terrestrial plants (Hepp et al., 2016) and may allow a source apportionment of carbohydrates in seawater.
Dissolved free carbohydrates (DFCHO) have been found to form another
fraction of marine carbohydrates (Engel and Händel, 2011; Ittekkot et al., 1981; Kirchman et al., 2001). DFCHO are considered to be either directly released by phytoplankton cells or be the product of enzymatic degradation of CCHO (Pakulski and Benner, 1994). DFCHO are mostly found in lower concentrations than CCHO, since marine microbes utilize them with high turnover rates (Engbrodt, 2001; Engel and Händel, 2011; Ittekkot et al., 1981; Thornton et al., 2016) as it has been reported for amino acids analogously as well (Kuznetsova and Lee, 2002). From the concentrations of DFCHO, or rather the ratio between CCHO and DFCHO, information about in situ
activities of local phytoplankton and bacteria in the seawater can be
obtained (Pakulski and Benner, 1994; Sakugawa and Handa, 1985).
Recently, correlations between the concentrations of free glucose in Arctic
surface water samples and their ice nucleating activity (INA) suggested a
potential link between the formation of INA and marine carbohydrates
(Zeppenfeld et al., 2019).
At the ocean surface, wind and wave interactions lead to bubble bursting.
The emitted sea spray aerosol contains marine carbohydrates, including
hydrogels, which contribute to the chemical and physical properties of these
particles (Bigg and Leck, 2008; Frossard et al., 2014; Hawkins and Russell, 2010; Rosenørn et al., 2006). They have been detected in particles in different marine environments on Earth, including the North Atlantic, the Arctic and Antarctica (Barbaro et al., 2015; Frossard et al., 2014; Gao et al., 2011, 2012; Leck et al., 2013; Russell et al., 2010). However, understanding the quantitative fluxes
of marine carbohydrates from the ocean to the atmosphere is still
challenging, since chemical analysis of sugars in seawater strongly suffers
from matrix effects, especially caused by sea salt.
The concentrations of individual monosaccharides in seawater, related saline
matrices and aerosol particles can be determined with different kinds of
chromatographic methods, such as high-performance liquid chromatography and
gas chromatography. These methods require a prior derivatization in order to
enable the chromatographic separation and detectability of these
carbohydrates (Panagiotopoulos and Sempéré, 2005). In the last decades, high-performance anion
exchange chromatography coupled to pulsed amperometric detection (HPAEC-PAD)
has been established as a reliable alternative, since it facilitates a
sensitive quantification of sugar compounds both in seawater and in airborne
particles without a prior derivatization (Iinuma et al., 2009; Panagiotopoulos and Sempéré, 2005; van Pinxteren et al., 2012; Skoog and Benner, 1997). However, the high ionic content in seawater samples strongly affects the chromatographic performance of the
HPAEC-PAD and needs to be removed before analysis.
Several procedures are available for the desalination of seawater. The
desalination using anion exchange resins AG2-X8 and the cation exchange
resin AG50W-X8 exhibits strong drawbacks such as the complete loss of
charged sugars (amino sugars, uronic acids) and quite low recovery rate of
neutral sugars between 20 % and 80 % depending on the individual monosaccharide (Borch and Kirchman, 1997; Mopper et al., 1992; Rich et al., 1996). The use of silver cartridges (Dionex OnGuard II Ag/H Cartridges) is faster and easier, but requires very expensive consumables and the capacity of removable sea
salt per cartridge is strongly limited (Mopper et al., 1992; Panagiotopoulos and Sempéré, 2005). The desalination applying
dialysis membranes achieves reproducible and very high recovery rates of
hydrolyzable polysaccharides (>90 %). However, this method
does not allow the analysis of DFCHO, since these small molecules pass the
membrane during dialysis (Engel and Händel, 2011).
Electro-dialysis (ED) is a fast way to remove ions by applying an electrical
field. The use of two different chemo-selective ion exchange membranes
allows the exclusive removal of small anions, or cations, respectively.
Hence, uncharged small substances (neutral DFCHO) and macromolecules (CCHO)
can, in principle, be recovered in high quantities. Amongst others, ED is
being used for the desalination of salty water to generate potable water and
the denitrification of wastewater and soil remediation (Gain et al., 2002; Ottosen et
al., 2000; Sadrzadeh and Mohammadi, 2008; Tsiakis and Papageorgiou, 2005;
Wisniewski et al., 2001). For analytical sample preparation, ED has been
reported as a powerful desalination, e.g., for the analysis of DOM and marine
neutral DFCHO (Josefsson, 1970; Koprivnjak et al., 2009; Mopper et al., 1980; Vetter et al., 2007; Wirth et al., 2019). However, following biases, which have hitherto not been
discussed in this analytical context, can occur during the application of ED
and might falsify the determined concentration of the analytes in the
sample. In contact with ion exchange membranes, the passive transport of
water (osmosis) and solutes with a low molecular weight (diffusion), such as DFCHO, can
occur triggered by a concentration gradient between the sample and
concentration channels (Galama et al., 2014; Galier et al., 2012). Additionally, the active transport of charged
molecules (migration) and water bound to ions in their hydration sphere
(electro-osmosis) takes place by operating an electrical field (Galama
et al., 2014; Han et al., 2015, 2017). While osmosis and electro-osmosis
induce an unavoidable loss of water and hence of the total volume of the
sample, diffusion and migration of the analytes result in a loss of
analyzable molecules. Furthermore, water splitting and associated pH
fluctuations have been reported, when a limiting current is exceeded during
an ED desalination
(Cowan,
1962; Martí-Calatayud et al., 2018; Ottosen et al., 2000; Vetter et
al., 2007).
Within the present study, a novel protocol for the desalination of seawater
samples and other saline samples (e.g., ice cores and brine from Arctic sea
ice), applying ED and HPAEC-PAD is presented, accounting for the biases
described above. With a low need of consumables, this method allows the
analysis of monosaccharides with (DCCHO) and without hydrolysis (DFCHO),
including the possible determination of free amino sugars and free uronic
acids. This developed technique was applied to analyze a diverse set of
carbohydrates in different kinds of ambient seawater samples.
ExperimentalChemicals and materials
Prior to the analysis of carbohydrates in seawater, all used laboratory
glassware had been washed with ultra-pure water (resistivity >18.2MΩcm) thoroughly and pre-heated in a muffle furnace at
550 ∘C for 4 h. All plastic equipment was first rinsed with
10 % HCl solution three times and then washed with ultra-pure water
another three times. For calibrating the HPAEC-PAD and determining the
recovery of individual monosaccharides, a mixed stock solution was prepared
from fucose (Roth, 95 %), galactosamine (Sigma, 99 %), rhamnose (Sigma, 99 %), arabinose (Sigma, 99 %), glucosamine (Fluka), galactose (Fluka, 99 %), glucose (99 %), xylose (Fluka, 99 %), mannose (Fluka, 99 %), fructose (Aldrich, 99 %), ribose (Aldrich, 98 %), muramic acid (Sigma, 95 %), galacturonic acid (Sigma-Aldrich, 97 %), glucuronic acid (Sigma, 97 %), mannuronic acid (Sigma, 90 %). Synthetic seawater samples were made from commercially available sea salt (Sigma) achieving four solutions with salinities S of 10, 20, 30 and 40 on the practical salinity scale. The salinity and the pH of water aliquots were measured by using a conductivity meter (pH/Cond 3320, WTW).
Field samples
Seven different seawater samples, one ice core from Arctic sea ice and two
brines collected within Arctic ice cores (Table 1) were measured and used for evaluating recovery rates and comparability of
the method presented here. These saline samples were collected during
different sampling campaigns and stored at -20∘C. All sampling
bottles had been rinsed with dilute hydrochloric acid (10 % v/v) prior to
the campaign. Field blanks (ultra-pure water filled up in sampling bottles
during the campaign) were collected during each campaign and treated in the
same way as the samples.
Sampling details of discussed saline samples including seawater
(SWS), an ice core (IC) and brine (B). SML stands for surface
microlayer (Engel et al., 2017).
Saline sampleLocationSampling dateCampaignLatitudeLongitudeDepth(SS)(m)SWS 1Tropical Atlantic13 November 2011Cabo Verde16.935∘ N024.915∘ W0 (SML)SWS 2Tropical Atlantic13 November 2011Cabo Verde16.935∘ N024.915∘ W2SWS 3Raunefjorden16 May 2011Raunefjorden60.274∘ N005.181∘ E2SWS 4North Atlantic07 May 2012ANT-XXVIII-533.3∘ N013.5∘ W0 (SML)SWS 5Arctic Ocean13 July 2017PS 106*81.229∘ N018.744∘ E1SWS 6Arctic Ocean14 July 2017PS 106*81.015∘ N026.883∘ E1SWS 7North Sea25 May 2017PS 106*57.288∘ N005.213∘ E1IC 1Arctic Ocean12 June 2017PS 106*81.824∘ N011.571∘ E0–0.8B 1Arctic Ocean12 June 2017PS 106*81.824∘ N011.571∘ E0–0.8B 2Arctic Ocean12 June 2017PS 106*81.824∘ N011.571∘ E0–1.5
* Wendisch et al. (2019).
The ED system
The centerpiece of the PCCell Micro Bench ED system for small sample volumes
consisted of three separated compartments (Fig. 1): the sample compartment was an open chamber that was filled up with 9 mL of the standard solution or seawater sample. The functionalized anion exchange membrane (quaternary ammonium aliphatic polyether) and cation exchange membrane (sulfonated aromatic polyether) bordered this compartment on both sides. Depending on their chemical properties, the membranes allowed
exclusively the migration of either positively or negatively charged ions.
For that matter, the anion exchange membrane bordering the sample chamber
was oriented to the anode and the cation exchange membrane to the cathode.
The contact surface with the sample was 7.8 cm2 for each membrane. For
maintaining the conductivity within the system and receiving the sea salt
from the sample, the next compartment contained the concentration circuit, a
16 g L-1 NaCl solution (Merck). This concentration was chosen in
order to minimize the osmotic water transfer as discussed below. This
solution was circulated at a rate of 60 mL min-1. Two end
membranes on each side divided the concentration circuit from the third
compartment containing the electrodes. The end membranes were cation
exchange membranes with an increased chemical durability and an additional
reinforcement in order to withstand the strong differential pressure within
the ED system. The mixed metal oxide (MMO) anode was made of a titanium base
body coated with RuO2, IrO2 and TiO2. The MMO cathode was
made of stainless steel. The electrodes were permanently surrounded by a
circulating 0.25 M Na2SO4 (Fluka) electrolyte circuit for avoiding
unwanted redox reactions (e.g., the generation of corrosive elemental
chlorine from chloride). Spacers were inserted between each membrane for
keeping the electrolyte and concentration circuits well mixed. The sample
solution was homogenized during each desalination by drawing some liquid
into a Pasteur pipette and draining it immediately back to the sample
compartment. The electrolyte and the concentration solutions were renewed
after every tenth desalination. The maximal electrical current Imax within the ED cell was adjusted by an automatic online adaption of the voltage, which never exceeded 25 V. The maximal current was set on 0.6 A in order to perform a fast desalination but also to avoid a scaling of the membranes due to water splitting and is discussed more in detail below. The desalination was stopped when the electric current dropped to a value of 0.20 A.
Schematic setup of the used ED cell. Red circles represent cations, green circles anions, and blue hexagons are carbohydrates. CEM and AEM stand for cation exchange membrane and anion exchange membrane, respectively.
The used ion exchange membranes have a quite long lifetime as long as they
are not damaged mechanically. However, very high attention needs to be given
to remove residues of previous desalinated samples in order to avoid
carry-over phenomena and obtain good reproducibility. Hence, every time
before a new sample was desalinated, the sample chamber was always first
filled with ultra-pure water for 10 min and then flushed once with an
aliquot of the new sample, which was disposed after.
HPAEC-PAD system
HPAEC-PAD was applied for the analysis of marine carbohydrates in seawater
samples. Here, we used an Dionex ICS-3000 ion chromatography system coupled
to an autosampler (AS-1) as it has been already described for the analysis of
saccharidic biomass burning markers in atmospheric particles (Iinuma et al., 2009). Several neutral
monosaccharides, amino sugars and uronic acids were separated on a Dionex
CarboPac PA20 analytical column (3×150 mm) combined with a Dionex CarboPac PA20 guard column (3×30 mm). The column oven temperature was maintained at 30 ∘C. The separation of these saccharides was conducted by applying the gradient profile shown in Table 2,
which was an adaption of Meyer et al. (2008). Neutral and amino sugars were eluted in 4 mM NaOH within the first 19 min. By adding sodium acetate, sugar acids eluted. At the same time, organic and inorganic contaminants were flushed from the column. After the removal of the remaining acetate by 250 mM NaOH, the system was equilibrated with 4 mM NaOH
for the next sample injection. The flow rate of the eluent was
0.5 mL min-1. The retention times, peak widths and
resolution factors of the measured monosaccharides are shown in
Table 3. For the injection of a sample aliquot, a 25 µL loop was used. Each sample was measured in duplicate and each
standard in triplicate. Limits of detection (LODs) of individual
monosaccharides ranged from 2 to 12 nM, which is in good agreement with
reported data (Engel and Händel, 2011; Panagiotopoulos and Sempéré, 2005).
Gradient profile applied on the CarboPac PA20 column during HPAEC-PAD analysis.
Time%A%B%C%D(min)(250 mM NaOH)(20 mM NaOH)(1 M Na acetate/(H2O)250 mM NaOH)002008019020080205015803550158038200404039100000441000004502008078020080
Averaged peak characteristics of monosaccharide standards separated
by the presented elution averaged over 24 runs. Resolution factors are
calculated between a peak and the following peak in the chromatogram.
For the preparation of eluents A–D, filtered ultra-pure water (resistivity >18.2MΩcm) was degassed with helium for 20 min. Eluents A and B were made by adding a defined volume of low-carbonate NaOH
solution (Fisher Chemical, 50 % w/w) to the degassed water. Eluent C was
prepared by dissolving sodium acetate (Thermo Scientific, anhydrous) in
ultra-pure water, filtering it through a nylon membrane (0.2 µm,
Thermo Scientific), degassing the solution with helium for 20 min and adding
the corresponding volume of NaOH solution.
Protocol for the analysis of DFCHO and DCCHO in seawater and
other saline samples
Stored frozen samples were defrosted in a fridge at 4 ∘C. A total of 9 mL of
the filtered sample (0.2 µm, Millex, PTFE) was desalinated with ED as described above. At the end of each desalination, electro-(osmotic) water loss was replenished with ultra-pure water and mixed thoroughly. In order to analyze free amino sugars or uronic acids, pH could be adapted with
concentrated HCl or 1 M NaOH.
A concentration step using a vacuum concentrator (MiVac) at 55 ∘C
allowed the detection of expected DFCHO concentrations in seawater. For this
purpose, a round-bottom glass vial was filled with an aliquot of 6 mL
desalted sample, which was weighed empty and filled. After reaching a volume
of approximately 600 µL, the glass vial was weighed again (in order
to calculate the concentration factor) and the concentrated aliquot was
pipetted in the autosampler vial for HPAEC-PAD analysis. This step allowed a
decrease of LOD by a factor of 10. Each sample was prepared and measured in
duplicate.
In order to measure DCCHO, marine polysaccharides need to be cleaved into
their monomeric compounds by acid hydrolysis. We applied the optimized
conditions described by Engel and Händel (2011) with slight
modifications. An aliquot of 1 mL desalted sample was hydrolyzed with
hydrochloric acid (HCl concentration in sample of 0.8 M) in pre-heated (550 ∘C, 4 h) glass ampules for 20 h at 100 ∘C. Neutralization was performed by evaporating all liquid under vacuum at
55 ∘C until dryness. The dry residue was dissolved in 700 µL ultra-pure water, treated with a vortex homogenizer (IKA MS 3 basic) and
filled in the autosampler vial for HPAEC-PAD analysis. Each sample was
prepared and measured in duplicate.
Parameter optimization and assessment of methodImpact of osmosis and electro-osmosis during ED desalination
For quantifying the loss of water in the sample due to osmosis and
electro-osmosis, a synthetic sea salt solution was pipetted into the
desalination chamber, which was desalinated for 0, 5, 10, 15, 20 and 25 min
with a maximal voltage of 25 V and a maximal current of 0.6 A. After the
lapse of time, the total remaining volume was pipetted quantitatively into a
glass vial and weighed (Mettler Toledo, XS105 DualRange). These measurements
were repeated in triplicate for four different sea salt solutions (with S of 10, 20, 30 and 40). The recovery of the sample mass was calculated as the
ratio between the mass after the corresponding desalination time and the
averaged mass at 0 min.
Recovery of DFCHO within the ED membrane system
Standard addition experiments with seawater samples were performed for
quantifying the recovery of monosaccharides due to diffusion and migration
under consideration of all matrix effects. For that reason, sample 7 was
filtered (0.2 µm, Millex, PTFE) and spiked with a sugar standard mix (neutral sugars, amino sugars, uronic acids) resulting in a concentration
increase of 10 and 100 µgL-1. These samples
were desalinated using ED (Imax=0.6 A, stop at 0.2 A). At the end of each run, (electro-)osmotic water loss was either replenished or not, and
the sample directly measured with the HPAEC-PAD. These measurements were
repeated in triplicate for each concentration. In order to account for
possible wasting phenomena, repetitions were performed with new membranes
and membranes which already had been used for some time before. Given
recovery rates for neutral monosaccharides are the average of the results
for 10 and 100 µgL-1. For sugar acids and
amino sugars, only the averaged recovery rates for 100 µgL-1 are given for avoiding determinations close to the LOD.
In order to investigate the influence of pH on the migration of charged
monosaccharides, this experiment was repeated for three different pH values.
At pH=8 (natural pH of seawater), pH of 1.5 (acidified with concentrated
HCl) and pH of 11 (addition of 1 M NaOH). Since high pH in seawater leads to
precipitation of hydroxides of alkaline earth metals, additional
filtering (0.2 µm) was performed for these runs.
Recovery of CCHO within the ED membrane system
Recovery experiments were performed with solutions and a suspension of the
polysaccharide standards sodium alginate (Aldrich), laminarin from Laminaria
digitate (Sigma) and cellulose powder from spruce (Fluka) at natural pH.
Stock solutions were added to filtered sample SWS 7 resulting in
concentrations of 10 mg L-1. Aliquots of 1 mL with and without
desalinations were hydrolyzed (HCl 0.8 M, 100 ∘C, 20 h) and
neutralized by evaporation of the volatile liquid with the vacuum
concentrator (55 ∘C) until dryness. The residue was reconstituted
in 700 µL, treated with a vortex homogenizer (IKA MS 3 basic) and
filled in the autosampler vial for HPAEC-PAD analysis. Recovery rates were
calculated as a ratio between the determined monosaccharide concentrations
after hydrolysis of the standard solutions with and without desalination.
In order to compare our method on the recovery of DCCHO with another
established method, aliquots of four filtered (0.2 µm, Millex, PTFE)
seawater samples were treated following the ED protocol presented here and
the protocol by Engel and Händel (2011) using membrane desalination, an
acid hydrolysis with HCl (0.8 M, 100 ∘C, 20 h), neutralization by
evaporation (nitrogen, 50 ∘C) and an elution on a Dionex CarboPac
PA10 column.
Results and discussion
A reproducible quantification of carbohydrates in seawater samples using
HPAEC-PAD requires prior removal of sea salt. Here, we present ED as a
reliable desalination method, its parameter optimization and the discussion
of arising phenomena resulting in a protocol for the analysis of marine
carbohydrates.
Kinetics and efficiency of desalination
During the desalination of seawater by ED, anions and cations migrate
through an electrical field and pass chemo-selective membranes. Depending on
their electrical charge, they move either to the positively charged anode or
to the negatively charged cathode. In this process, the salt flux through
the membranes jS (mol m-2 s-1), which
determines the desalination time, is proportional to the applied electrical
current I (Han et al., 2017; Vanoppen et al., 2015). Figure 2 shows the current
within the used ED system and the salinity of the seawater sample during a
typical desalination of an artificial seawater sample (S=40) for two
different applied maximal currents Imax within the system. For almost the entire desalination run, the current I was maintained at Imax due to automatic adjustment of the voltage. During this time, the salt flux was approximately constant. Towards the end of the desalination, when almost all salt ions were removed, the current dropped down and the salt flux became
lower. Since a direct salinity measurement was not possible in the sample
chamber without contaminating the sample, the end of each desalination was
defined, when the current I reached a value of 0.2 A. At this point, the
salinity of the sample typically ranged between 0.2 and 0.4, which was found
to be sufficiently low for the carbohydrate analysis at the HPAEC-PAD. This
reduction in salinity represents an overall desalination of more than 99 %
of the initial salt concentration. A desalination reaching a salinity below
0.1 was possible but was not necessary for this application and would have
resulted in longer desalination times. Consequently, for minimizing the
required desalination time, a high Imax is favorable.
Measured current within the ED system and salinity of a synthetic sea water sample (S=40) versus desalination time with two
different maximal applied currents Imax (0.6 A solid line, 0.3 A dashed line). The red line represents the current and the corresponding salinity when desalination was stopped.
However, it was observed that the application of an Imax of more than
0.8 A during the desalination, resulted in a large pH increase and a white
precipitation in the (synthetic) seawater solution, apparently due to the
formation of hydroxides of alkaline earth metals. This uncontrolled
precipitation strongly disturbed the efficiency of the desalination and the
reproducibility of the carbohydrate measurements and caused a scaling of the
membranes. Previous studies explained these unfavorable changes of pH by a
strong concentration polarization at the membrane's surface leading to water
splitting to H+ and OH- ions, when a certain limiting current is exceeded. This phenomenon has been preferably observed at anion exchange
membranes with quaternary amino groups in the presence of divalent cations,
such as Mg2+ and Ca2+ (Cowan, 1962;
Martí-Calatayud et al., 2018; Ottosen et al., 2000). The precipitation
exclusively occurred when (synthetic) seawater was desalinated and not
during the desalination of NaCl standard solutions. This finding shows the
importance of performing parameter optimization tests with synthetic
seawater standards that include all important seawater constituents such as
divalent cations. In summary, the optimum maximal current Imax of 0.6 A
was found for the used ED system for avoiding scaling effects and performing
desalination as fast as possible.
Possible biases during the application of EDOsmotic and electro-osmotic transport of water
Osmosis describes the passive transport of free water molecules through a
partially permeable membrane caused by large differences of the osmotic
pressures between the concentrate circuit and the sample solution
(Sata, 2004). The direction and the quantity of the water
transport depend on the residence time tR of the sample solution within
the membrane system, the difference between the concentrations of solutes in
the sample solution and the concentration circuit(cs-cc) and membrane specific parameters, such as the osmotic water transfer coefficient the membrane area and the membrane thickness (Galama et al., 2014). The quantitative effect of osmosis can be reduced by minimizing tR and (cs-cc). Hence, cc was set at 16 g NaCl L-1, which is approximately in the
middle between the concentrations of a typical seawater sample before
(salinity of 30–39) and after the desalination (salinity of 0.2–0.4) for balancing the positive and negative contribution of osmosis on the total
sample volume during a typical desalination.
In aqueous solutions, water molecules form a hydration shell around ions
(Ohtaki and Radnai, 1993). Whenever ions pass through membranes during ED, a cotransport of these hydrating water molecules occurs, known as electro-osmosis (Galama et al., 2014). The
electro-osmotic water transfer jW (m3 m-2 s-1) is proportional to the salt flux jS in the system and can be
expressed by formula (1) with the molar volume of water VM (1.8×10-5 m3 mol-1) and the salt hydration number
nH (mol water mol-1 salt) (Galier and Balmann, 2015; Han et al., 2015).
jW=nH⋅VM⋅jS
The salt hydration number of NaCl, as the major compound of sea salt, has been reported with values between 11 and 14 (Han et al., 2015; Rutgers and Hendrikx, 1962; Singlande et al., 2006; Walker et
al., 2014). Assuming a NaCl concentration of 30 g L-1 and
nH to be 14, a maximal reduction of the sample volume by 13 %
due to electro-osmosis was expected, in addition to osmosis.
The recovery of the sample volume due to electro-osmosis and osmosis during
the desalination was characterized for four different salinities for the
used ED system (Fig. 3). During the active removal of sea salt, electro-osmosis is the dominating force causing the water loss in the sample. The electro-osmotic water loss is continual as long as the salt flux stays constant. However, in the final stages of each desalination, the salt flux decreases and consequently the electro-osmotic water transfer decreases, too. For a synthetic seawater sample with a salinity of 30, 84 % of sample mass was recovered. This is in good agreement with the
estimation mentioned above considering a small additional contemporaneous
contribution of osmosis. Once the sea salt is removed, osmotic water
transfer remained at a constant rate of approximately 0.1 % min-1.
Combined effect of electro-osmosis and osmosis (solid lines) and osmosis (dashed lines) on the recovery of sample mass as a function of the desalination time within the described membrane system (Imax=0.6 A, cc=16 g NaCl L-1) for artificial sea salt
solutions with four different initial salinities.
The overall water loss resulting from osmosis and electro-osmosis needs to
be taken into account since it falsifies the determined concentrations of
marine carbohydrates. For its compensation, the chamber was replenished with
ultra-pure water at the end of each desalination until the initial sample
volume was reached. This procedure was performed with a maximal overall
error of 0.5 %.
Analysis and recovery of DFCHO in seawater samples
The recovery of neutral monosaccharides during ED is impacted by diffusion
and convection processes (Galier and Balmann, 2015). Additionally, free amino sugars and uronic acids migrate through an electrical field due to their charge and pass the ion exchange membranes. Recovery tests were performed with standard solutions spiked to a
seawater samples with concentrations, which have been typically reported for
seawater samples before (Kirchman et al., 2001; Mopper et al., 1980; Skoog et al., 1999; Zeppenfeld et al., 2019). Recovery rates of neutral sugars (Glc, Man, Xyl, Gal, Ara, Fuc, Rha, Fru) ranged between 95 % and 98 % at the natural pH of seawater (approximately pH=8) (Table 4). Hence, the overall impact of diffusion and convection on the recovery of monosaccharides seems to be quite low for the short contact time with these membranes. However, a higher loss of neutral monosaccharides due to diffusion was observed, when the sample solution remained within the membrane system for a longer period of time, which calls for a fast desalination. This is in agreement with Vanoppen et
al. (2015), who concluded that diffusion and affinity for the membrane are
the main drivers for losses of uncharged, low-molecular organics during a ED
desalination. An overestimation of the determined concentrations was avoided
by performing a correction of the water loss in the end of each
desalination. Charged monosaccharides were found with much lower recoveries
of 25 %–31 % for uronic acids and 16 %–19 % for amino sugars at pH=8. This is due to their weak acidic/basic properties (pKa (amino sugars) of 7.6–8.5 (Bichsel and von Gunten, 2000; Sinnott, 2007), pKa (uronic acids) of 3.3–3.5 (Kohn and Kovác, 1978)) and hence their partially ionic state, which makes them
migrate through the electrical field. However, a low pH can protonate the
carboxylic group of uronic acids and a high pH deprotonates the amino group
of amino sugars for reducing this effect. Here, we found that an initial pH
of 1.5 before desalination could increase the recovery of free uronic acids
up to 45 %–49 %, while a high pH of 11 resulted into a higher recovery of free amino sugars up to 58 %–59 %. The recovery of neutral sugars seemed to
be quite unaffected within the range of the tested pH, with the exception of
fructose, which was 89 % recovered at pH of 1.5, certainly due to its
instability within acid conditions.
Recovery of individual free monosaccharides (neutral, amino sugars,
uronic acids) after desalination with ED including correction of (electro-)osmotic water loss.
Analysis and recovery of CCHO in seawater samples with standard
polysaccharides
Recovery experiments with standard solutions of common polysaccharides were
performed with and without desalination by ED. The neutral, water-soluble
polysaccharide laminarin was recovered with 91.0±5.4 %. The acidic
polysaccharide alginic acid was recovered with 93.2±5.3 %. Even
though alginic acid might move within the electrical field due to its acidic
molecular structure, its molecular weight does not allow passing the
membrane and it does not leave the sample solution. Standard desalination
experiments with a suspension of the water insoluble cellulose as a
representative of PCCHO resulted in much lower recoveries of 48±19 %. The reason for this high, less reproducible loss of polysaccharides
was likely sedimentation within the sample chamber. Engel and
Händel (2011) described adsorption processes during the desalination
with dialysis membranes and tackled this problem with sonification of the
membranes. However, sonification could not be applied in our apparatus. In
this study, flushing the chamber several times with a defined volume of
ultra-pure water after desalination and reuniting the washing water with the
desalinated sample could increase the yield of cellulose up to 85.2±6.9 % under consideration of dilution factors. This procedure was not
found to be feasible, since a dilution of a natural sample reduces the
sensitivity of low concentrated sugars in seawater in the analysis by
HPAEC-PAD. Rather, we recommend ED only for the application to filtered
samples (DCCHO), while PCCHO might be better analyzed from filters after
filtration.
Comparison of ED and dialysis method for the determination of
DCCHO in seawater samples
In order to evaluate the presented procedure for the analysis of DCCHO,
comparison studies were performed measuring four ambient seawater samples
(SWSs 1–4) with the established membrane dialysis protocol after Engel and
Händel (2011) and with the method presented here.
Figure 4 shows a comparison of the results of the individual monosaccharides after hydrolysis with HCl. The slope of the regression line using all sugar data together with the determination
coefficient (R2=0.89) indicates a good overall agreement between both
methods. Major concentrated sugars, such as glucose, galactose and
xylose/mannose, were determined at similar concentrations. Furthermore,
good agreement was observed for minor concentrated sugars, such as fucose
and galactosamine. Discrepancies were found for rhamnose and arabinose,
which was overestimated by the ED method, and glucosamine, which was
determined at lower concentrations. These variations might be explained by
statistical uncertainties or co-elution of unknown substances. In summary,
the method presented here using ED has shown to be in good agreement with
the established membrane dialysis method regarding the analysis of DCCHO. In
addition, the ED offers the major advantage of analyzing the full spectrum
of DFCHO as well – which comprise a group of hardly investigated but
potentially important marine compounds.
Determined monosaccharide concentrations in four seawater samples (SWSs 1–4) after hydrolysis (DCCHO) comparing the desalination by dialysis (Engel and Händel, 2011) and ED (presented in this study). The solid line represents the line of equality. The dotted line represents the regression line between the data of both methods.
(a) Full chromatogram of standard solution 100 µgL-1; (b–e) chromatograms of neutral sugars and amino sugars of (b) standard solution 100 µgL-1; (c) DFCHO in brine (B2) desalinated at natural pH; (d) DCCHO in a seawater sample (SWS 3); (e) DCCHO in Arctic brine (B2). 1: fucose, 2: galactosamine, 3: rhamnose, 4: arabinose, 5: glucosamine, 6: galactose, 7: glucose, 8: xylose, 9: mannose, 10: fructose, 11: ribose, 12: muramic acid, 13: galacturonic acid, 14: glucuronic acid, 15: mannuronic acid.
Chromatographic performance with HPAEC-PAD after desalination
Several kinds of saline samples were desalinated with ED and analyzed on the
CarboPac PA20 column. Figure 5 shows some examples for DFCHO and DCCHO chromatograms in a brine and a seawater sample after desalination with ED. The insufficient chromatographic separation of mannose and xylose using previous kinds of analytical columns has been frequently described in literature (Borch and Kirchman, 1997; Engbrodt, 2001; Engel and Händel, 2011; Kirchman et al., 2001). Therefore, xylose and mannose have been reported as sum concentrations frequently. The elution of the sugars on a CarboPac PA20 column, applied in the present study, strongly improved the separation between the both sugars mannose and xylose (resolution factor of 0.8), and allowed the individual determination of these two sugars. However, most of the analyzed samples showed high concentrations of xylose, which strongly overlapped the smaller peak of mannose. For these cases, we kept reporting a sum value for Xyl/Man.
DFCHO and DCCHO in saline field samples from different regions
Several samples were analyzed on DFCHO and DCCHO (Tables 5 and 6). In both
sugar fractions, glucose was the most abundant monosaccharide, as it has
been reported before (Panagiotopoulos and Sempéré, 2005). In some of the samples, free fructose could be determined reaching concentrations comparable to glucose. However, fructose
cannot be determined in DCCHO, since hydrolysis leads to complete
destruction of this sugar. High DFCHO was found in the samples from the
Arctic including brine and ice core samples reaching up to 118 nM in
comparison to seawater samples from the Atlantic (11–15 nM).
However, a clear regional trend could not be identified for DCCHO with
concentrations, ranging between 260 and 1410 nM. Traces of free amino sugars and uronic acids were found after neutral desalinations. However, a stronger
enrichment is required in order to determine them quantitatively and will be
the focus of further studies.
Molar percentages of individual neutral monosaccharides within DFCHO
in seawater, Arctic brine and ice core samples. <LOD stands for
below detection limit.
In this study, a novel protocol was presented for the analysis of both DFCHO
and DCCHO in saline aqueous samples by applying HPAEC-PAD with prior
desalination by ED. Recovery rates for neutral monosaccharides ranged
between 95 % and 98 %. By adjusting pH, charged monosaccharides such as free amino sugars and uronic acids could be recovered with 58 %–59 % at pH=11
and 45 %–49 % at pH = 1.5, respectively. Dissolved polysaccharide
standards, such as laminarin and alginic acid, showed good recovery rates of
91 %–93 %, while a suspension of insoluble cellulose was quite difficult to
recover reproducibly. Hence, ED for carbohydrate analysis is recommended to
be used for filtered samples or for samples with a low amount of particulate
matter. In this study, the osmotic and electro-osmotic loss of water was
considered in order to avoid an overestimation of the determined
concentrations. In seawater from different locations, Arctic brine and sea
ice core samples, DCCHO was found in concentrations between 260 and 1410 nM.
DFCHO ranged in much lower concentrations of 11–118 nM. Within both DFCHO
and DCCHO, the most dominant monosaccharide was glucose, followed by other
neutral sugars.
In this study, the successful application of ED in combination with
HPAEC-PAD for the analysis of marine carbohydrates (both free and combined)
in marine matrices, such as seawater, ice cores and brine, could be
demonstrated. The application of ED for other more salt-sensitive analyses
should be the focus of further research, e.g., the reported interference of
suspended sea spray aerosol in Arctic snow samples during the quantification
of insoluble light-absorbing impurities such as black carbon and dust
performed via nebulization. Hence, this developed method has the potential
to contribute strongly in further research studies understanding
biogeochemical processes in the oceans and related saline matrices and
sea–air exchange processes, especially for studying hotspot regions of
climate change, such as the Arctic.
Data availability
All data are available on the public PANGAEA repository;
https://doi.pangaea.de/10.1594/PANGAEA.910575 (Zeppenfeld et al., 2020).
Author contributions
SZ wrote the manuscript with contributions from MvP, HH and AE. SZ and MvP
collected seawater samples during different field campaigns. SZ optimized
the presented method and performed the chemical measurements. AE performed
DCCHO analysis with supplied samples following her published protocol for
evaluation purposes. All co-authors proofread and commented on the
manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “Marine organic matter: from biological production in the ocean to organic aerosol particles and marine clouds (ACP/OS inter-journal SI)”. It is not associated with a conference.
Acknowledgements
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft
(DFG, German Research Foundation). Additional support through the
Leibniz Association SAW funding of the project “Marine biological
production, organic aerosol particles and marine clouds: a Process Chain
(MarParCloud)” is also gratefully acknowledged. We thank for the opportunities to use aqueous samples from various sampling campaigns in order to develop the method presented here. We thank Swantje Pöge for supporting work in the laboratory. We thank Jon Roa for DCCHO analysis following the Engel and Händel (2011) protocol. We thank Susanne Fuchs and Kristin Recklies, and Christian Weller of Thermo Fisher in his in-house collaborations for fruitful discussions. We thank Patrick Altmeier and Philip Kalkhoff from PCCell GmbH (Heusweiler, Germany) for guidance and technical support for helping to put ED in operation in our laboratory.
Financial support
This research has been supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project ID 268020496 – TRR 172, within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” in subproject B04. Additional support through the Leibniz Association SAW funding of the project “Marine biological production, organic aerosol particles and marine clouds: a Process Chain (MarParCloud)” (SAW-2016-TROPOS-2).The publication of this article was funded by the Open Access Fund of the Leibniz Association.
Review statement
This paper was edited by Mario Hoppema and reviewed by two anonymous referees.
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