copper complexation in the northeast pacific

Limnol. Oceanogr., 33(5), 1988, 1084-l 101 @ 1988, by the American Society of Limnology and Oceanography, Inc.

Copper complexation in the Northeast Pacific

Kenneth H. Coale’ and Kenneth W. B&and Institute of Marine Sciences, University of California, Santa Cruz 95064

Abstract

Copper titrations were conducted at sea with differential pulse anodic stripping voltammetry to examine the degree to which copper was associated with organic ligands. Greater than 99.7% of the total dissolved copper in surface waters of the central Northeast Pacific shallower than 200 m was estimated to be associated with strong organic complexes. Below 200 m, increasing proportions of inorganic or labile copper spccics were observed. At middepths (1,000 m), about 50-70% of the total dissolved copper was in the organically complexed form. Whereas total copper varies by a factor of only three from the surface to middepths (0.6-I .8 nM), copper complexation gives rise to extremely low cupric ion activities in surface waters ({Cu!‘} = 1.4 x lo-l4 M) and higher values at middepth ({Cuz-I} = lo- I1 M)-a variation of three orders of magnitude. Two classes of copper- binding ligands were found to be responsible for this complexation: an extremely strong ligand class [log K’cond (cu,j = 11.5 J at low concentrations (- 1.8 nM) -which dominated copper complexation in the surface waters and decreased with depth, and a weaker class of ligands [log K’cond(Cu3 = 8.51 at higher concentrations (8-10 nM) which was observed throughout the water column and showed no apparent structure in its vertical distribution. These findings have significant implications concerning the toxicity and bioavailability of copper in open ocean systems.

Complexation of trace metals has long been implicated as the dominant control on bioavailability and toxicity of trace metals to phytoplankton (Anderson and Morel 1978; Jackson and Morgan 1978). Copper complexation has attracted considerable at- tention in this respect due to copper’s requirement as a micronutrient and its toxicity. For example, natural levels of copper in recently upwelled seawater have been reported to cause toxicity in phytoplankton (Brand et al. 1986). In these studies, suppression of algal growth occurred in seawater replete with plant nutrients. Optimal growth in these systems could be restored upon addition of metal chelators or other metal micronutrients (Mn and Fe), suggest-

-- I To whom all correspondence should be sent. Now

at: Moss Landing Marine Laboratories, Moss Landing, California 95039.

Acknowledgments We express our sincere appreciation to the crew and

officers of the RV Pt. Sur, M. Gordon, and S. Fitzwater for collection of the seawater samples used in this study, R. Flegal for his performance as Chief Scientist, W. Broenkow, and M. Yuen for the CTD data reported here. We thank J. Donat, G. Gill, W. Sunda, R. Collier, and an anonymous reviewer for reviews of this manu- script. Thanks are also extended to J. Hering for sup- plying the copy of FITEQL used in this study.

This work was supported by ONR Contract NO00 14- 83-K-0683.

ing that copper toxicity was due to competitive inhibition by copper of other metal-requiring enzyme systems. Competitive inhibit ion experiments with phytoplankton and theoretical calculations have linked this toxic rlesponse to cupric ion activity (Sunda and Guillard 1976; Jackson and Morgan 1978).

Copper is a required constituent in many enzyme systems, the most notable of which are perhaps the enzyme, cytochrome oxi- dase, and the electron carrier, plastocyanin. That low levels of copper can limit plant growth has been observed in higher plants (Shkolnik 1984) and suggested for phytoplankton (Manahan and Smith 1973; Schenck 1984). However, there have been no conclusive studies indicating that copper limitation actually occurs in natural assemblages of marine phytoplankton.

Recently, complexation has been pro- posed to play an important role in deter- mining trace metal-particle reactivity and geochemical behavior (Davis and Leckie 1978; Morel 1982). The partitioning of copper between dissolved and particulate forms results from a competition between dissolved ligands and binding sites on parti- cles. IJsing a synthetic particulate substrate (MnO,), van den Berg (1982) has exploited this competition in the determination of copper complexation with natural organic

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https://www.researchgate.net/publication/223239420_Limitation_of_marine_phytoplankton_reproduction_rates_by_copper_and_cadmium_J_Exp_Mar_Biol_Ecol_96_225-250?el=1_x_8&enrichId=rgreq-93af7861-5256-4c2c-968b-e0d3cac01599&enrichSource=Y292ZXJQYWdlOzIzODIwOTA0ODtBUzoxMDI2ODA0MDM5MDY1NjJAMTQwMTQ5MjMyNDQ1MA==

NE PaciJic copper complexation 1085

ligands. Although the magnitude of this competition in seawater (containing natural dissolved ligands and particulate substrates) is not known, copper complexation will control, to some extent, this interaction.

These studies illustrate that interest in copper complexation is considerable, but the ability to determine copper complexation by natural ligands has been limited. Several investigators have reported studies of copper complexation in open-ocean seawater. The majority of these studies have been carried out in the Atlantic (van den Berg et al. 1984; Sunda and Ferguson 1983; Huizenga and Kester 1983; van den Berg 1984; Kra- mer 1986). The results, in general, indicate a significant degree of copper complexation with organic ligands in surface waters, although large variability exists between data sets. The source of this variability may be natural variability in complexation, but it may also reflect variability in techniques and models used to study complexation. In the present study, natural samples were titrated with copper, and labile copper was detected by differential pulse anodic stripping voltammetry (DPASV) with a rotating glassy carbon electrode. This technique was used to obtain a profile for copper speciation in the eastern North Pacific Ocean. Detailed copper titration results are presented to en- able others to critically evaluate these data.

Methods Most of the samples collected for this

study were obtained (in the central North- east Pacific, 33”N, 139”W) in September 1986, as part of the VERTEX (VI) research program (VERTEX Sta. Sea. 1). Seawater was collected with Teflon-coated, 30-liter Go-Flo bottles (General Oceanics) deployed on Kevlar (Philadelphia Resins) hydrowire and tripped with a Teflon messenger. Upon recovery, the Go-Flo bottles were pressur- ized to 0.5 atm with filtered nitrogen gas, and the seawater was forced through acid- cleaned, 142-mm-diameter, 0.3-pm pore- size polycarbonate membrane filters (Nuclepore) using Teflon filter holders (Mil- lipore). Dissolved (and total) samples were collected in 2-liter FEP Teflon bottles. All sample manipulations took place within a

positive-pressure van or under a class 100, laminar flow, clean air bench.

Dissolved organic and trace-metal-free seawater was prepared from Monterey Bay surface seawater cleanly collected about 8 km from shore and returned to the laboratory. It was pumped at 2 ml min-’ through a continuous flow system consisting of a 0.4~pm polycarbonate filter (Nuclepore), Duolite S-587 resin (Diamond Shamrock Corp.) to remove dissolved organics, Su- michelate Q- 1OR resin (Sumitomo Chem- icals) and Chelex- 100 resin (Bio-Rad) to remove trace metals, an ultraviolet irradiation system (1.2 kW Hanovia Hg arc lamp, irradiation time = 5 h) to destroy residual dissolved organics, two Chelex- 100 resin columns in series to remove any dissolved trace metals previously bound to residual organics, and finally through a C, 8 resin (Sep- Pak, Waters Assoc.) in an attempt to remove any remaining refractory dissolved organics. To ensure that this treated seawater had the proper balance of major cations, we allowed the initial 2 liters (over 50 column volumes) of seawater to run through the system before collection. Resulting seawater had a pH of 2 7.5 and is referred to as UVSW.

Total dissolved copper determinations- Total dissolved copper was concentrated with an ammonium 1 -pyrrolidinedithiocar- bamate (APDC) and diethylammonium diethyldithiocarbamate (DDDC) chelation and solvent extraction technique described elsewhere (Bruland et al. 1979, 1985). Sea- water concentrates (N 200 : 1) were analyzed by graphite furnace atomic absorption spec- trometry (GFAAS) on a Perkin-Elmer 5000 atomic absorption spectrometer. The spectrometer was equipped with an HGA-500 heated graphite atomizer with tungsten background correction and L’Vov graphite platform furnace inserts. Standard addition techniques were used to compensate for ma- trix effects.

DPASV determinations -The DPASV apparatus and instrumental modifications used in this study have been described elsewhere (Bruland et al. 1985; Mart et al. 1980, 1983, 1984). The system uses a rotating glassy carbon working electrode consisting of a highly polished carbon disk (28 mm2)

1086 Coale and Bruland

Feedback Generator r Control Cable

Stainless Steel Ax

Bearings--------

Counter Electrod

TFE Cell Cap-

Acrylic Motor Housing

Si Tubing Junction

Coimmersion of Axle Segment Pt Electrode Lead

S-Working Electrode Lead

Reference Electrode Lead

Acrylic Cell Stand

Electrode Body FEP Sheathed Electrode with Vycor Tip

Hg Junction Carbon Electrode

Fig. 1. Schematic of DPASV electrode configuration, driver assembly, and cell construction. Typically, t .wo such assemblies and three purge cell positions are incorporated into one acrylic cell stand. (After Bruland et al. 1985.)

embedded in a polycarbonate or acrylic electrode body. Coiled platinum wire and coiled silver wire (onto which AgCl has been plated) serve as the counter and reference electrodes, respectively. Both counter and reference electrodes are filled with an ultrapure saturated KC1 solution and isolated from the sample via FEP tubing fitted with a porous vycor tip (Fig. 1).

For a given analysis, the working electrode was polished with 0.05~pm Al,O, at low rotation rate (100 rpm), then rinsed with dilute, quartz-distilled HCl. Blanks were prepared with 60 ml of ultrapure HZ0 (Mil- lipore, Milli-Q system), 200 ~1 of saturated KCl, and 200 ~1 of 5,000 ppm Hg2+. Blanks were degassed with oxygen-free N, for 10 min then plated at - 1.0 V and working electrode rotation rate of 5,000 rpm for 20 min. After the blank deposition and Hg film formation period, the electrode rotation was stopped, and following a 30-s quiescent pe-

riod the film was stripped by scanning the potential toward more positive values in the differential pulse mode (scan rate: 20 mV s-l; pu.lse modulation amplitude: 50 mV; pulse repetition period: 200 ms; decay period: 13 ms). If the blank voltammogram showed low or undetectable levels of metals and a satisfactory baseline slope, sample analysis would proceed.

Our cell stand accommodates two rotating disk electrodes in cell positions 1 and 2 and three other positions for sample purg- ing. One of two N,-purged 5 5-65-ml sample aliquots, in replicate TFE Teflon electrochemical cells, was transferred to the analysis position to rinse the electrodes and gas purge tubing of residual Hg. This sample rinse was then discarded and the replicate sample placed in the analysis position. This precaution was taken to ensure only a min- imal amount of residual mercury would be left in the sample to be titrated for copper.

NE Pacific copper complexation 1087

Samples for copper (and Pb) analysis under- went electrodeposition at - 0.75 V and 5,000 rpm (working electrode rotation) for 20 min. The sample was then scanned in the differential pulse mode as described earlier. The scan was stopped and held at -0.15 V with the electrode rotating for 3.5 min between depositions to strip the film completely of residual metals. This 20-min deposition was then repeated to obtain a second “zero addition” voltammogram. This step ensured that the electrode was conditioned under seawater conditions and that the scans were reproducible. Subsequently a Pb spike yielding an increase of -40 pM was added and the deposition-stripping cycle repeated. After two additions of Pb (a total of -0.08 nM Pb added), copper additions were performed. Lead results from these samples will be reported elsewhere.

Four initial copper additions each increased the copper concentration in the cell by about 0.6 nM. All copper additions were allowed to equilibrate for 5.5 min between depositions. After a copper oxidation peak appeared in the titration sequence, signaling the presence of ASV-labile copper, additions of copper were increased stepwise (1.2, 2.4, and 5 nM; see Table 2). Most titrations were carried out to about 30 nM added copper (yielding about 14 data points). Upon completion of a titration, the sample vol- ume was measured. Throughout the course of these titrations, pH stayed relatively constant (about 8.0), never varying more than 0.15 pH units.

At a deposition potential of -0.75 V, a broad, apparently tensametric wave (Bond 1980) often appeared in the region of the copper half-wave oxidation potential. To compensate for this feature, we performed O-min depositions during each metal addition-equilibration period to evaluate the electrode-stripping response in the absence of accumulated metal in the film. This O-min deposition was obtained after a scan with a quiescent period of 30 s with no rotation of the working electrode. The electrode was then switched to the deposition potential of -0.75 V for 30 s. The sample was then scanned to obtain an estimate of the tensametric contribution to the copper peak at the copper peak potential. This component

was subtracted from the preceding voltammogram.

Time-series equilibration experiments were performed at sea to assess the kinetic behavior of complexation between copper and natural organic ligands. In these experiments aliquots of about 60 ml of sample were transferred to a series of acid-cleaned and sample-rinsed 60-ml FEP Teflon bottles. Each aliquot was spiked with copper to an amount equivalent to the standard additions used in a normal copper titration. These sets of bottles, each set representing a single titration, were allowed to equilibrate up to 96 h before analysis. DPASV analyses of these samples were similar to a normal titration except that the electrode was turned off after completion of the deposition-stripping cycle for each spiked aliquot so that the next degassed aliquot could be transferred to the analysis position.

Concepts and terms The copper titrations and total dissolved

copper determinations in this report yield information regarding copper-binding ligand concentrations and their affinity for copper. These parameters are related by the complexation equilibrium between cupric ions and natural organic ligands. For 1 : 1 complexation

cu2+ + L”- T= CuL2-” , (1)

the thermodynamic equilibrium constant (or stability constant) at infinite dilution can be expressed as

K = [CuL2-n]/[Cu2+][Ln-] (2)

where square brackets denote molar concentrations of these species. In higher ionic strength solutions such as seawater, a conditional stability constant (K’) (Table 1) can be described (Eq. 3) from the relationship

{cu2+} = [cu2+]ycu (3)

K’ = mcuYLh”L) = [CuL2-n]/[Cl.l2+][Ln-] (4)

where curly brackets denote activities of the solution species and the ion activity coefficient (7) accounts for nonspecific ion-


screening effects. The solution-equilibrium between metal ions and organic ligands may be further affected by specific inorganic complexation of the metal ion with solution anions (such as CO 32-, OH-, and Cl-) and by organic ligand association with H+ and major cations (such as Ca2+ and Mg2+). The extent to which a solution species undergoes inorganic side reactions can be estimated with a side reaction coefficient ((Y, Ringbom and Still 1972):

CxM = 1 + 2 (Kj[Xi]‘) LJ

where Kj is the ith stepwise ionic-strength- corrected stability constant for the complex formed between species M and the jth species X. These side reactions can dra- matically reduce the free metal ion and free (organic ligand concentrations and must be considered when defining a stability constant (Kcond) for a specific set of solution ‘conditions. Where these side reactions occur, the free copper ion and free ligand anion ,concentrations are

[Cu2+] = y and IL”-] = 3 (6)

where [Cu’] is defined as the concentration of dissolved copper present in all inorganic forms and [L’] is defined as the total concentration of ligand not complexed with Cu2+. The free cupric ion and free ligand activities are

( cu2+) = Yc&u’1 ~Chl

and {L”-} = YL.ELI] . (7)

The use of a conditional stability constant of the form K’ cond rather than K’ is necessary because aL is usually unknown for natural organic ligands, so [L’] is the quantity obtained, not [L”-1. Depending on the species of copper actually measured (Cu2+ or Cu’):

K’ DJLI cond (CUT+) = [cu2+][L’]

(i.e. with respect to Cu2+), or

Table I. List of symbols, their meanings and units.

Meaning IJnits

Y.x Rx

K

R

R cond

[Cu,1 [Cu,1

Ku’1

lL’1

unitless unitless

liters mol-’

liters mol-’

liters mol- l

mol liter-l mol. liter-l

mol liter -I

mol liter -I

K’ [CuU cond (Cu’) = Ku’1 &‘I

(i.e. with respect to Cu’). In experiments where bioassays or ion selective electrodes are used, Cu2+ activity or free [Cu2+] is determined directly (Sunda and Ferguson 1983; Sunda et al. 1984; Hering et al. 1987). The same seems to be true for equilibration techniques with MnO, (van den Berg 1984), catechol (van den Berg 1984), or EDTA (Sunda and Hanson 1987). These techniques can be used to estimate Kcond (cU2+) (e.g. with respect to free Cu2+).

Electrochemical methods such as anodic stripping voltammetry and Cu(II)/Cu(I) charge transfer amperometry detect inorganic forms of copper and any weakly bound, labile organic complexes of copper such as Cu-Gly or Cu-acetate (Waite and Morel 1983). In seawater, the concentrations of such weak organic ligands are so low (nM, Lee and Bada 1975,1977) that these organic complexes are not formed to any apprecia- ble extent. Thus, ASV techniques measure predominantly [Cu’]. Conditional stability constants determined with respect to [Cu’], K’ cond (cUJ), can be corrected for the inorganic side reaction coefficients of copper in sea-

NE PaciJic copper complexation 1089

UV-Oxidized Seawater

2ooo I-

0 7

?O Copper (nM)

Fig. 2. Copper titration in UVSW described in text. y2 = 0.99. Linear transformation of this data with a subsequent linear regression of the results yields r2 = 0.378, indicating no significant concentration of ligands present.

water in order to be compared to conditional stability constants determined with respect to [Cu2+] or even free Cu2+ activity.

Lab results There has been substantial controversy

over the application of ASV techniques in the study of copper-organic ligand interactions in natural waters. Criticism of the technique has focused on the potential for reduction of organically complexed metal species at the electrode surface due to the deposition potential used or due to the kinetic lability of organically complexed metal within the diffusion layer or both (Tuschall and Brezonik 198 1). Both processes would lead to overestimates of the free or inor- ganically complexed metal fraction and underestimates of the conditional stability constant of the metal-organic ligand complex. In this study an effort was made to minimize these potential sources of error by using a relatively weak deposition potential for high chloride media (- 0.75 V relative to Ag/AgCl) to minimize reduction of organically complexed copper. Also, a high rotation rate of the working electrode (5,000 rpm) was used to minimize the residence time of metal-organic complexes in the electrode diffusion layer and thereby minimize any kinetic contribution due to metal-ligand dissociation. An attempt was also made to more rigorously define the operational nature of the species detected or estimated by this technique by testing it against model ligand systems.

EDTAiILUVSW

6ooo~

4ooo--

3ooo--

2ooo--

A

0 10 20 30 40 I

Copper

UnearTranaformation,EDTA

0

o.oI 0 6 10 16 20 26 30

Cu’ (nM)

Fig. 3. A. Copper titration of 10.02 nM EDTA in UVSW, estimated log K’cond((.u,j = 8.7, see text. B. Lin- car transformation of the EDTA titration data yielding ligand concentration of 10.7 nM and log Klcond (cu,j = 8.5.

We observed the ASV response to copper additions in the absence of complexing organic ligands by titrating UVSW according to the procedure outlined above. The results (presented in Fig. 2) show a linear response (r2 = 0.994) indicating no apparent loss of copper due to adsorption or complexation in the absence of a complexing ligand. The wet UV oxidation technique has recently come under question with respect to its ability to completely destroy all organics in seawater (Sugimura and Suzuki 1988). Slight concave upward curvature was occasionally observed in titrations of some batches of UVSW, which suggests that the UV treatment may not always quantitatively remove all weak ligands with affinity for copper. This UV oxidation treatment does appear, however, to remove all strong copper-complexing ligands.

When 10.0 nM EDTA was added to this


Temp (“C) Salinity (o/oo) Tram. (Z) NO-2+3(yM) 0 10 20 34 35 80 85 90 0 25 50

. C: D

I .

1500’ .

- --- Fig. 4. Hydrographic water column characteristics for the VERTEX seasonal station. A. Temperature vs.

depth. B. Salinity vs. depth. C. Transmissivity vs. depth. D. Nitrate plus nitrite vs. depth.

UVSW and allowed to equilibrate with copper additions for 24 h, subsequent analyses yielded the results shown in Fig. 3. These titrations were modeled with the linear transformation method of Ruzic (1982) and Ruzic and Nikolic ( 1982). In this experiment, copper spikes were added until at least four sequential additions gave a linear response. The slope of the response to these last four additions (i.e. the sensitivity) was used to calculate the inorganic metal observed for each addition. If copper and organic ligands form complexes whose binding stoichiometry is 1 : 1, a plot of inorganic copper, [Cu’], divided by organically complexed copper, [Cu,] (where Cub = total copper -- Cu’), vs. inorganic copper yields a straight line:

P’l _ 1

DJbl Ll x ICu’1 1

+ v-4 x Jcond (Cu’) - (lo)

The inverse of the slope of the line generated by this transformation represents the total ligand concentration [L]. The inverse of the intercept times the slope represents the conditional stability constant, Kcond (cu,j, for such a system (Ruzic 1982).

The experimentally derived ligand concentration agrees closely (Fig. 3) with the concentration of EDTA present (10.0 present vs. 10.7 measured). This experiment was repeated four times and the average ligand concentration determined was 10.4 t- 1.6 nM

( 1 g) and an average log Kcond (culj of 8.6 t- 0.1 ( 1 a) was obtained. The agreement between the measured and calculated conditional stability constants varies depending on which of the many stability constants and inorganic side reaction coefficients for copper are chosen. Using thermodynamic constants from Mattel and Smith (1974), corrected to an ionic strength of 0.7 (by the Davies equation), side reaction coefficients for ‘EDTA (a EDTA) of lo8 and copper (a,& of 24 (Byrne and Miller 198 5), we calculate log K’ ,..ond (cupj for the Cu-EDTA formation to be 8.7. Extrapolation to pH = 7.5 yields cy (cuI of -7 however, and a corresponding log K’ cond (culJ = 9.2 for EDTA. Agreement between measured and calculated Ktcond ccupj at pH = 7.5 is within about half of a log unit, Idepending on the actual pH of the UVSW. The implication is that we may be slightly underestimating the strength of the ligands measured in the field.

Field studies The VERTEX seasonal station (39”N,

133”W) was occupied during September 1986. Temperature, salinity, and nitrate profiles indicate a mixed-layer depth of about 45 m (Fig. 4). Samples for copper complexation analysis were collected at 14 depths at this station during our 4-d occu- pation. The titration results, including DPASV response (nA), copper added (nM), total copper [Cu,], ASV labile copper [Cu’], and organically complexed copper [Cu,] for every depth, are presented in Table 2. The results of the time-series equilibration ex-

NE Pa&k copper complexation 1091

Table 2. Copper titration results for the upper 1,400 m from the VERTEX seasonal station (39”N, 139”W), September 1986. Peak current normalized to lo-min depositions.

Peak current

(nA) Cu added

(nM)

0 0.000 0 0.624

32 1.247 56 1.871 86 2.494

160 3.756 232 5.017 288 7.512 624 10.00 808 12.50

1,120 15.00 1,690 20.04 2,400 25.09

0 0.000 0 0.614

16 1.227 52 1.841 98 2.454

190 3.696 294 4.937 550 7.392 768 9.846

1,088 12.30 1,390 14.76 2,180 19.72 3,160 24.69 4,000 29.65

0 0.000 0 0.538

24 1.076 48 1.614 68 2.151

142 3.240 208 4.329 392 6.480 560 8.63 1 727 10.78 793 12.93

1,433 17.29 1,960 21.64

0 0.000 0 0.645 0 1.289

16 1.934 48 2.578

120 3.882 220 5.187 444 7.765 690 10.34 927 12.92

20 m 0.582 1.206 1.829 2.453 3.076 4.338 5.599 8.094

10.06 13.08 15.58 20.06 25.67 30 m 0.589 1.203 1.816 2.430 3.043 4.285 5.526 7.98 1

10.44 12.89 15.53 20.3 1 25.28 30.24

40 m 0.566 1.104 1.642 2.180 2.717 3.806 4.895 7.046 9.197

11.35 13.50 17.85 22.21 60 m 0.662 1.307 1.951 2.596 3.240 4.544 5.849 8.427

11.00 13.58

0.000 0.582 0.000 1.206 0.557 1.573 0,448 2.005 0.687 2.389 1.279 3.059 1.854 3.745 2.301 5.792 4.986 5.602 6.457 6.625 8.950 6.627

13.51 7.119 19.18 6.492

0.000 0.589 0.000 1.203 0.092 1.726 0.293 2.137 0.555 2.488 1.071 3.214 1.657 3.869 3.100 4.880 4.329 6.106 6.133 6.756 7.836 7.508

12.29 8.021 17.81 7.463 22.55 7.695

0.000 0.566 0.000 1.104 0.200 1.442 0.401 1.779 0.568 2.149 1.186 2.620 1.737 3.158 3.273 3.773 4.675 4.522 6.070 5.279 6.621 6.879

11.96 5,890 16.36 5.843

0.000 0.662 0.000 1.307 0.000 1.951 0.109 2.487 0.327 2.913 0.817 3.727 1.498 4.35 1 3.023 5.404 4.697 6.308 6.311 7.272

Table 2. Continued

Peak current

(nA) Cu added

WV

1,200 15.50 16.16 8.169 7.992 2,007 20.72 21.38 13.66 7.715 2,590 25.93 26.60 17.63 8.963 3,560 31.15 31.81 24.24 7.576

0 0.000 0 0.590 8 1.180

24 1.770 32 2.360 94 3.554

158 4.748 296 7.108 460 9.468 656 11.83 807 14.19

1,307 18.96 1,770 23.74 2,320 28.51

80 m 0.598 1.188 1.778 2.368 2.958 4.152 5.346 7.706

10.07 12.43 14.79 19.56 24.34 29.11

0.000 0.598 0.000 1.188 0.076 1.702 0.229 2.139 0.306 2.653 0.897 3.255 1.508 3.838 2.826 4.880 4.392 5.674 6.263 6.162 7.704 7.082

12.48 7.083 16.90 7.438 22.15 6.964

0 0.000 12 0.629 32 1.257 56 1.886 78 2.515

128 3.787 180 5.059 300 7.574 454 10.10 645 12.60 833 15.12

1,373 20.2 1 1,880 25.30 2,560 30.38

125 m 0.622 1.251 1.879 2.508 3.137 4.409 5.68 1 8.196

10.71 13.23 15.74 20.83 25.92 31.00

0.000 0.622 0.107 1.144 0.286 1.593 0.501 2.007 0.698 2.439 1.145 3.264 1.610 4.07 1 2.684 5.512 4.06 1 6.650 5.770 7.455 7.452 8.288

12.28 8.547 16.82 9.099 22.90 8.104

0 0.000 66 0.624

120 1.247 182 1.871 312 3.133 332 4.394 741 6.889

1,053 9.393 1,340 11.88 1,690 14.37 2,560 19.42 3,480 24.47 4,520 29.5 1

150 m 0.736 1.360 1.983 2.607 3.869 5.130 7.625

10.13 12.61 15.11 20.16 25.20 30.25

0.000 0.736 0.354 1.006 0.644 1.339 0.976 1.631 1.673 2.196 1.781 3.349 3.974 3.65 1 5.648 4.48 1 7.187 5.426 9.064 6.044

13.73 6.425 18.66 6.537 24.24 6.006

36 0.000 66 0.683

100 1.366 188 2.669 284 3.974 395 5.278 621 7.856

200 m 0.926 1.609 2.292 3.595 4.900 6.204 8.782

0.268 0.659 0.490 1.119 0.743 1.549 1.397 2.198 2.110 2.790 2.935 3.269 4.615 4.167


Table 2. Continued Table 2. Continued

Peak current

WI

Cu added (nW

CU,

0-W (2)

~- -- Peak

current Cu added @A) (nW

891 10.43 11.36 6.621 4.739 1,220 13.01 13.94 9.066 4.873 1,500 15.59 16.52 11.15 5.370 2,200 20.8 1 21.73 16.35 5.386 2,9201 26.02 26.95 21.70 5.251 3,600 31.24 32.17 26.75 5.415

80 0.000 104 0.685 134 1.316 196 2.572 286 3.829 360 5.086 544 7.570 768 10.05

1,080 12.54 1,360 15.02 2,060 20.05 2,880 25.08 3,880 30.10

250 m 1.143 1.801 2.459 3.715 4.972 6.229 8.713

11.20 13.68 16.17 21.19 26.22 31.25

0.480 0.663 0.624 1.177 0.804 1.655 1.176 2.539 1.716 3.256 2.159 4.070 3.263 5.450 4.607 6.590 6.478 7.204 8.158 8.008

12.36 8.836 17.28 8.944 23.27 7.972

137 0.000 248 1.361 332 2.723 382 4.084 6 13 5.446 960 8.137

1,290 10.83 1,590 13.52 1,940 16.21 2,800 21.66 3,780 27.10 4,920 32.55

300 m 1.210 2.571 3.933 5.294 6.656 9.347

12.04 14.73 17.42 22.87 28.3 1 33.76

0.752 0.458 1.361 1.210 1.822 2.111 2.097 3.197 3.365 3.29 1 5.270 4.077 7.08 1 4.957 8.728 6.002

10.65 6.772 15.37 7.496 20.75 7.562 27.01 6.750

141 0.000 262 1.326 374 2.653 470 3.979 635 5.306 988 7.928

1,340 10.55 1,680 13.17 2,090 15.80 3,100 21.10 4,180 26.4 1 5,360 31.71

400 m 1.808 3.134 4.46 1 5.787 7.114 9.736

12.36 14.98 17.60 22.9 1 28.22 33.52

0.687 1.121 1.276 1.858 1.822 2.639 2.290 3.497 3.094 4.020 4.814 4.922 6.529 5.829 8.185 6.796

10.18 7.420 15.10 7.806 20.37 7.850 26.11 7.406

71 0.000 118 1.304 259 2.608 330 3.913 512 5.217 912 7.795

1,420 10.37 1,700 12.95 2,180 15.53

500 m 1.808 3.112 4.416 5.721 7.025 9.603

12.18 14.76 17.34

0.414 1.394 0.687 2.425 1.509 2.907 1.922 3.799 2.983 4.042 5.313 4.290 8.272 3.909 9.904 4.855

12.70 4.637

3,010 20.75 22.55 17.54 5.019 4,080 25.96 27.77 23.77 4.002 4,780 31.18 32.99 27.85 5.141

93 0.000 126 1.315 244 2.630 338 3.946 501 5.261 864 7.86 1

1,660 13.06 2,110 15.66 3,240 20.92 4,380 26.18 5,540 31.44

1,000 m 2.186 3.501 4.816 6.132 7.447

10.05 15.25 17.85 23.11 28.37 36.63

0.428 1.758 0.580 2.92 1 1.123 3.693 1.556 4.576 2.306 5.141 3.977 6.070 7.64 1 7.606 9.712 8.135

14.91 8.195 20.16 8.209 25.50 8.130

141 1.150 176 1.710 253 2.290 352 4.870 728 7.160

1,077 9.440 1,523 11.73 2,040 16.37 3,880 25.72

1,400 m 3.029 3.589 4.169 6.749 9.039

11.32 13.61 18.25 27.60

0.829 2.200 1.035 2.554 1.488 2.68 1 2.07 1 4.678 4.282 4.757 6.335 4.984 8.959 4.650

12.00 6.249 22.82 4.775

pcriment are listed in Table 3. There were no significant changes in ligand concentrations or conditional stability constants when copper additions to three sets of aliquots of the same sample were allowed to equilibrate for 5.5 min, 24 h, or 96 h (Table 3). In addition, no significant differences were observed in ligand concentrations or conditional stability constants between one aliquot of a sample which was titrated immediately after collection and temperature e,quilibration and a separate aliquot of the same sample titrated 24 h later.

For a typical titration from 60 m (Fig. 5), the fi:rst two copper additions yielded no DPASV response. The added copper appears to be completely complexed with or-

Table 3. Time-series experiments.

Equilibration time L, (nW L WV h ~CO”d u-2)

5 min 1.80 5.21 8.84 24 h 2.00 5.10 9.08 96 h 1.96 5.11 8.78

- - - - I -

NE Pa&c copper complexation 1093

8

l 0

O-,llr mg ,

0 10 20 30 40

coppmr (nld)

Linear Rnndormntion, 60 m

B

0.04 I 0 a 4 6 6 10

Cu’ (nM)

Fig. 5. A. Shipboard copper titration of a sample from 60 m. Note that copper in the first deposition- stripping cycle and after two subsequent additions is not detectable. As an indication of the model fits to the data, circles represent field data; squares and triangles represent FITEQL and linear-transformation- model-predicted instrumental responses. TITRATOR (Cabaniss 1987) was used to calculate the responses with FITEQL and linear transformation estimates of values of L and K. B. Linear transformation of the 60-m titration data. This linearization was performed on data transformed (Cu, - last total copper value to give zero response) to reflect the total binding of the copper in the strong ligand fraction, as described in the text. L, concentration from this plot is calculated to be 6.58 nM with log Klcond (cUPj = 8.73.

ganic ligands, forming electrochemically inert complexes. This phenomenon was observed for all samples shallower than 200 m and required the application of a modi- fied linear transformation model to estimate ligand concentrations and conditional stability constants. On the basis of the amount of copper added before the first detectable ASV signal and the dissolved copper originally present in the sample, it appears that there is at least 1.95 nM of a strong copper-complexing ligand or class of ligands (assuming 1 : 1 stoichiometry). This

1OOOm

BOO0 -- b 0 A

l

l m9 , 0 10 Bo 30 40

Linear Transformation, 1000 m

0 6 10 16 20 26 30

Cu' (nM)

Fig. 6. A. Shipboard copper titration of a sample from 1,000 m. Note that first run shows detectable inorganic copper. Circles represent field data; triangles represent linear transformation instrumental responses predicted with TITRATOR (as in Fig. 5). B. Linear transformation of the 1,000-m titration data indicate [L,] = 8.74 nM and log K’cO,,d~cU~~ = 8.86.

estimate is conservative for the concentration of the strong ligand class, [L,], because copper was added incrementally (as 0.6 nM additions) during the titration and only the last addition to yield a zero response was used to calculate [L,] ([L,] = total copper added to the sample before copper was detected in the titration + total dissolved copper initially present in situ). Therefore estimates of the L, concentration with this method could be low by as much as 0.6 nM. To estimate the concentration of the weaker ligand (L,), whose presence causes curvature in the titration response between 2 and 15 nM, we subtracted the concentration of L, (e.g. 1.95 nM copper for this 60-m sample) from the organically complexed copper [Cub] data before applying the linear transformation to obtain estimates of LZ.

The discrete-ligand, computer-based, nonlinear, numerical optimization routine,

1094 Coale and B&and

FITEQL (Westall 1982) was also used to model the titration results for the upper 150 m of the water column. With FITEQL in most cases the optimization procedure con- verged, yielding estimates for L1, LZ, and K2 similar to those obtained with the linear transformation method. An advantage of FITEQL over the method described above is that it yields estimates for L1, K,, LZ, and K2 without requiring an estimate of our detection limit or transformation of our titration data. Agreement between both methods seems quite good especially for L2 and K2.

For samples deeper than 200 m, the initial deposition-stripping cycle indicated the presence of labile copper, (Cu’), before any additions were made to the sample. A typical titration of such a deep-water sample is shown in Fig. 6 (0). For these deeper samples data were modeled as a one-ligand system and the linear transformation could be applied directly to the titration data (A- responses calculated from the linear transformation-derived parameters L, and Kz). [LJ from the surface to 1,400 m averages 7.6 + 1.7 nM (1 a) with a corresponding average log Ktcond (cuzj = 8.5 + 0.3 (1 a).

Discussion The ability to collect, process, and store

seawater samples without contamination is a fundamental prerequisite for accurate studies of speciation. The degree of complexation could be significantly underestimated due to even very small amounts (e.g. 0.5 nM) of inadvertent contamination. Pro- files of total dissolved copper are routinely collected, analyzed, and compared to previously reported values to ensure that our samples are not contaminated and that the proper oceanographic consistency is obtained (Boyle et al. 1977; Bruland 1980). Since the total dissolved copper profile agrees well with previous reports, we feel confident that the concentration of the complexing ligand has not been underestimated due to contamination.

Although sample analysis in this study usually occurred within about 18 h of collection and the potential for ligand lability was of concern to us, the results of the time- series experiments showed little difference

d 1

Log K’ cond’ L2 5 7 9 .Ll 13 15

Fig. 7. A. Vertical distributions sponding log K’cond (cu’).

of [L,]. B. Corre-

in ligand concentration and conditional stability constants (Table 3). These results suggest that the copper-complexing ability of the lig,ands is relatively stable over a period appro.aching a week and that the kinetics of association of copper with both ligand classes is relatively rapid (Ruzic 1984). An indication that the natural ligands show a specific preference for copper was obtained by adding amounts of zinc, lead, and iron, in molar excess of the copper-complexing ligands, to a few samples that had been par- tially titrated with copper. After a 5.5-min equilibration and a 20-min deposition, the copper signal during the subsequent stripping cycle showed no change.

Copper-complexing ligands and conditional stability constant distributions- Oc- cupation of the VERTEX seasonal station provided a unique opportunity to determine the extent of copper complexation with natural organic ligands in seawater, yielding the first of a series of seasonal profiles obtained at this station.

The apparent lack of vertical structure in profiles of the concentration of the weaker copper-complexing ligand, Ld2, and its conditional stability constant (Fig. 7) may indicate either conservative distribution of these quantities or insufficient precision in our results to resolve significant vertical trends. An attempt was made to conduct all titrations and treat all data identically so that our data set would be internally consistent and allow comparisons between depths. Nonetheless, the linear transformation method is somewhat sensitive to the precision of the titration data, especially in computing Ktcond CCUOj, and no significant

NE Pa& copper complexation 1095

Table 4. Total dissolved copper for each depth and model-derived estimates of L,, Lz, K,, and K, (first row each depth) and estimates of the goodness of fit (linear transformation) (second row each depth).

Model fit P Depth (m) Cu, (nM) L, (nW L (nM) 1% KI log Kz S0.YDF-t

20 0.582 > 1.21 6.53 > 10.71 8.58 0.908 8.09 8.65

30 0.589 > 1.20 7.23 > 10.71 8.67 0.994 1.58 8.60 11.75 8.35 5.83 1

40 0.566 >l.lO 5.90 > 10.67 8.53 0.980 1.19* 6.77 11.96 8.38 18.48

60 0.662 > 1.95 6.58 B 10.92 8.73 0.986 2.40 7.32 11.26 8.41 4.938

80 0.598 >1.19 6.41 > 10.71 8.83 0.995 2.15 6.71 10.55 8.39 11.86

125 0.622 >0.62 8.78 > 10.42 8.68 0.990 0.84§ 0.63 12.24 8.42 5.779

150 0.736 >0.74 7.28 > 10.50 8.24 0.984 - - -

200 0.926 - 5.89 8.69 0.998 - - - -

250 1.143 - 10.20 8.44 0.954 - - -

300 1.210 - 9.80 - 8.12 0.867 - - -

400 1.50911 - 9.09 8.33 0.983 - - -

500 1.808 - 4.83 9.10 0.972 - -

1,000 2.186 - 8.74 8.86 0.998 - -

1,400 1.879 - 5.17 9.24 0.976 - - - -

* From the linear transformation of the titration data, this value represents r* for the line with the equation: [Cu’]/[CuJ = l/{[L] x [Cu’]} + l/{[L]

t ~h~~%%al analysis in FITEQL is not rigorous; however, the estimates given here are consistent with current usage. In general, values of SOS/ DF between 0.1 and 20 arc common for a reasonably good lit (Westall 1982).

$ For FITEQL convergence, first two zero-response signals were estimated. 8 For FITEQL convergence, first zero-response signal was estimated. ]I Sample lost; value estimated via interpolation.

vertical structure either in LZ concentration or K’ cond(cu’) for LZ can be readily discerned. [LJ averages 7.6 k 1.7 nM ( 1 a) for the entire 1,400-m water column, while log Ktcond (cU,) for L2 averages 8.5 kO.3 (1 a) (Table 4). If we assume that these profiles represent a nearly conservative distribution of a relatively uniform class of refractory, copper- binding organic ligands, then their water- column residence times must be long with respect to the time scales of the mixing of the main thermocline (tens to hundreds of years).

As mentioned above, no Cu’ was initially detected in samples shallower than 200 m. The concentration of the strong ligand class responsible for this complexation was de-

rived with F’ITEQL and also estimated: [L,] = (total dissolved copper present + total copper added, before detection of Cu’). On the basis of our detection limit of 0.02 nM copper and the titration results in the surface waters, a minimum value for K’cond (CU? can be estimated as follows. At the point in the titration just before detection of Cu’, we assume that [Cu’] < 0.02 nM; [Cub] is equal to the average euphotic-zone concentration of L1 = 1.3 nM and that L1’ is present in concentration equal to half the copper titration increments of 0.60 nM. Therefore, K’ cond (Cu’) > 1.3 x 1O-g M/(x0.02 x 1O-g M)(0.3 x 10eg M) > 10’ 1.3. This represents a combined conditional stability constant due to the suppression of [Cu’] by both L,


nM 0 1 2 3

Fig. 8. Vertical distributions of [L,] (A), total dissolved copper (0) and inorganic copper (0). Extremely low values for Cu’ indicate the dominant effect of L, controlling copper complexation in the surface waters. As L, decreases to undetectable by 200 m, Cu’ begins to increase.

and L2. To estimate factor out the [Cu’]

K’ cond (Cu’) for

suppression L,, we can due to L2

alone. This value is equivalent to an a side reaction coefficient for CuL, that can be calculated from the previous section: acU = 3.9 for L2 in the surface waters. This yields a minimum Ktcond (cuc) for Ll > 1010’7.

FITEQL-calculated values for [L,] are about 0.4 nM higher than those estimated with the conservative approximation (1.3 nM vs. 1.8 nM). Similarly, except for the 80-m titration where Ktcond (cujj values are obtained, values calculated with FTTEQL for log K',,,, (cu,j are almost 1 log unit higher than those conservatively estimated (log K’ cond(cu’) for Ll = 1 1.5 vs. 10.7 for the conservative estimate).

In marked contrast to the relatively featureless distribution of L2, the vertical distribution of the stronger ligand, LI, shows some striking trends (Fig. 8). Above 200 m, L, is present in excess of the total copper concentration. The excess of this ligand over total copper represents the amount of inorganic copper that could be added to these waters, complexed, and rendered undetectable by DPASV. The average concentration of L, in the surface 100 m is 1.8kO.5 nM. At and below 200 m, copper is detectable before any copper is added to the sample, indicating that the copper concentration is

mgC/m3/day

Fig. 8. A. Vertical distributions of [L,] (O), total copper (O), and inorganic copper (A), as in Fig. 8. B. Primary productivity profile for the upper water column at the VERTEX seasonal station (G. Knauer and D. Ridalje pers. comm.). Primary productivity profiles were obtained about 30 d after the copper speciation profile yet hydrographic conditions during both legs were similar. Productivity data points: 12-h incubations--O; 24-h incubations-O. Note maximum in productivity and maximum in [L,] coincident at 50- 60 1-n.

in excess of the concentration of L,. Since the vertical gradient in total copper is not as gre#at as the vertical gradient in L,, the ligand concentration appears to be decreas- ing with depth faster than it is being titrated naturally by increasing copper. As will be seen, the gradient in this hgand profile con- trols the free copper distribution.

The: mixed layer of the temperate North Pacific varies seasonally in thickness from 20 m in late summer to 150 m during winter mixing (Bathen 1972; Robinson 1976). Due to the presence of L, in the mixed layer and only shallow penetration of L, into the thermocline, we believe it to be a relatively labile class of organic ligands with a residence time that is short with respect to the formation of the seasonal thermocline (< It yr), yet lolng with respect to our equilibration experiments (N 1 week). Thus, the input rate of L, must be greater than the rate at which a surface maximum would be diluted by seasonal mixing. Mechanisms for removal of L, are unknown, yet processes such as photo-oxidation or uptake by phytoplankton or bacteria are possible and have been shown to occur for other labile organics.

Experiments with filtered and unfiltered seawater indicate that both L, and L, are primarily associated with the dissolved fraction (<0.3 pm). We believe that L, is

NE Pac$c copper complexation 1097

Table 5. Recent literature values for copper-complexing ligands in seawater.

Location WI1 NM) Ll (nW logK,* - logK,* Tcchniquc Reference?

GM, Atlantic 5 15 >12 9.8 Bioassay 1 Atlantic 11 33 12.6 10.6 DPCSV 2 Atlantic 31 87 10.3 9.4 MnO, 3 Atlantic 4-36 23-99 10.2-l 2.4 8.3-9.2 ASV, CSV, MnO, 4 N. Atlantic - 20-86 - 9.1-10.0 DPASV 5 N. Pacific 1.8 7.6 12.9 9.5-10.6 DPASV 6 * These values have been normalized to a common inorganic side reaction coeflicicnt for copper of 24 (Byrne and Miller 1985). Therefore, values

for log Kcond represent stability constants with rcspcct to free copper, CtP+. t 1 -Sunda and Ferguson 1983; 2-van den Berg 1984; 3-van den Berg et al. 1984; 4-Buckley and van den Berg 1986; 5-Kramer 1986; 6-this

paper.

produced by phytoplankton or lower tro- phic microbial processes. Although conclusive evidence is lacking, the phytoplankton primary production maximum and a minimum in beam transmissometry were coincident with the depth where L, concentrations were greatest (Figs. 4C and 9). Although the correlation of L1 concentration and primary production does not in itself identify primary producers as the source of L,, the hy- pothesis that such ligands are produced by phytoplankton is not new. The production of ligands with affinity for copper has been demonstrated for laboratory cultures of algae (e.g. McKnight and Morel 1978), and natural assemblages of phytoplankton have been observed to produce ligands with affinity for zinc (Imber et al. 1985) and specific for iron (Trick et al. 1983).

We reviewed recent literature values for the concentrations and conditional stability constants, Ktcond (cU21 ), for copper-complexing ligands reported for open-ocean seawater (Table 5). Open-ocean values were chosen to narrow the wide range of values that would result if coastal and estuarine systems were considered since these systems may be influenced by terrigenous or sedimentary sources. Although sizable variability in the accepted inorganic side reaction coefficients for copper has been reported in the literature (e.g. Morel and Morel-Laurens 1983; Symes and Kester 1985; Zuehlke and Kester 1983; Turner et al. 198 l), a value of 24 (Byrne and Miller 1985) was chosen for surface waters to nor- malize (where necessary) the conditional stability constants in Table 5 with respect to free Cu2+. This value is in good agreement with that of Sunda and Hanson (1987).

Cabaniss et al. (19 84) have examined var-

ious numerical and graphical models used in deriving ligand concentrations and conditional stability constants from titration data such as ours. They pointed out possible weaknesses in these methods and cautioned users against blind acceptance of the results of the models, especially when comparing them to other literature values. We recog- nize that any model will reflect the product of one’s assumptions and data. In this respect, model-derived parameters such as L and K are highly sensitive to one’s assumptions and may not necessarily reflect the reality of the environment. In this study we have chosen to observe the rule of Occam’s razor and apply the simplest model war- ranted by our observations. These assumptions yield results not dissimilar from those already in the literature. We include Table 2 for those who wish to make more or less elaborate assumptions of their own.

In any case, we believe that Table 5 is useful for obtaining an order-of-magnitude perception of copper-organic ligand interactions in the open-ocean environment. Fo- cus on two ligands in the literature has be- come common, and there appears to be a converging trend, Literature values for L2 concentrations vary between 15 and 99 nM with a log Kfcond (,-“2 kj that varies between 8.3 and 10.6 (Table 5). Since the concentration of dissolved organic carbon (DOC) in open- ocean surface waters is about 300 ,uM (Su- gimura and Suzuki 1988) and since the DOC is composed of many compounds, we believe that higher precision titrations to higher concentrations of copper might reveal even more classes of ligands at even higher concentrations but lower stability constants. Our somewhat limited titration range (O-30 nM) possibly missed the presence of what others


would call L2, but enabled us to detect the presence of a smaller concentration of ligands having a stronger interaction with copper. Our titrations reflect the range of copper concentrations that would be ex- pected in nature and may, therefore, have greater relevance, than titrations to higher concentrations, to the natural system.

There are few profiles of the strong ligand class, L,, with which to compare. This lack is due in part to the lack of an analytical technique that can readily detect (Cu’) at concentrations below 10 pM and in part to copper contamination during sample collection and analysis. Buckley and van den Berg ( 1986) reported the vertical distribution of a “strong” ligand in the Atlantic, yet their profile and conditional stability constants indicate that this ligand may, in fact, correspond to those of our weaker ligand. It is probable that they were unable to resolve very low concentrations of a high affinity ligand class. Due to our limitations in sensitivity and titration precision, it is possible that we are missing an even stronger ligand class as well. Huizenga and Kester (1983) reported ASV-detectable copper (at pH = 4.7) for a profile from the western North Atlantic. Although the depth distribution of ASV-labile copper is similar to our own, the samples yielding the profile were not titrated so no indication of ligand concentration can be made. Except for the two weaker types of L, reported, Ktcond (cU2+) < 10’ I, there appears to be between 1.8 and 11 nM of this ligand class in oceanic surface waters. Corresponding conditional stability constants with respect to free Cu2+ are about 10’3.

Free Cu*+ -Estimates of K’cond tculj for L1 and measurements of L,, Lz, and Ktcond tcu~j for L2 allow us to calculate [Cu’], [Cu2+], and (Cu2+} in surface oceanic and middepth seawater. If we use Krcond ccutj for L1 > 10 l Is and [L,] = 1.8 nM, Ktcond scuds = lO8.4 for L2 and [L2’] = 7.4 nM, for the surface waters [Cu’] = 1.6 pM. If we use the inorganic side reactions of copper in surface waters, cycu = 24 (Byrne and Miller 1985), [Cu2+] = 65 fM. If we use an activity coefficient for Cu2+, y = 031 {cu2+) = 14 fM (or pCu2+ = 13.9, where iCu2+ = -log{Cu2+}). Since carbonate and hydroxide anions contribute to the

PCU 2+

14 13 12 11 10 0 I - I

72

1; 500-- 4 II)

Ii LA

d

‘i 4 lOOO--

1500 4:.

Fig. 10. Free copper activity as a function of depth. Copper activity expressed as pCu2+ where pCu*+ = -log{Cu*+}. These values were derived with FITEQL estimates for L,, L,, K,, and K, in the upper water column and linear transformation estimates for L, and K2 at depth. TITRATOR (Caban iss 1987) was used to calculate free copper activities.

complexation of copper, inorganic complexation varies as a function of pH and therefore of depth in the oceans. A GEO- SECS pH profile taken from Takahashi et al. (1970) was used in conjunction with pH- dependent log acu values (Sunda pers. comm .; Byrne and Miller 198 5) to calculate CYST, for each depth. These inorganic side reaction coefficients vary from 24 in the surface waters to lo+ 2 depending on the 1 g variation in pH at middepth. In the middepths where [L2] = 7.6 nM and [L,] = 0, [Cu,] == 1.5 nM, [Cu2+] = 49 pM, and {Cu2+} = 10 pM ( pCu2+ = 11). We can see from Fig. 10 that there is a strong buffering of {Cu2+} due to the presence of L1. In surface waters the total dissolved copper could be alm.ost tripled without appreciably affecting {Cw2+}. As [L,] decreases with depth, however, .CCu2+} increases by about three orders of magnitude, in marked contrast to the relatively featureless profile for total dissolved copper (Fig. 8).

Based on these data one can also estimate a minimum organic side reaction coefficient for copper for surface and deep waters. For surface waters where total dissolved copper does not exceed L, , aorg c.u = 3 8 5. In deep waters where total dissolved copper does not exceed L2, (xorgcU = 4.1. When inorganic

https://www.researchgate.net/publication/235921953_Copper_complexation_profiles_in_the_Atlantic_Ocean_A_comparative_study_using_electrochemical_and_ion_exchange_techniques?el=1_x_8&enrichId=rgreq-93af7861-5256-4c2c-968b-e0d3cac01599&enrichSource=Y292ZXJQYWdlOzIzODIwOTA0ODtBUzoxMDI2ODA0MDM5MDY1NjJAMTQwMTQ5MjMyNDQ1MA==

NE Pa&k copper complexation 1099

side reactions are considered we can calculate a “total” side reaction coefficient for copper in the surface waters, q cU = 9.2 x 1 03; in the deep waters, cy, cU = 4 1.

The profile for pCu 2+ should be of much greater biological significance than that for total copper because biological response to copper is thought to reflect changes in free copper activity rather than to total dissolved copper and total dissolved copper varies by roughly a factor of three from surface waters to middepths, whereas {Cu2+} varies by three orders of magnitude. Al- though there have been no definitive experiments indicating that low copper activities limit natural marine phytoplankton production, Brand et al. ( 1986), using single species cultures of natural isolates, showed that the reproductive rates of cyanobacteria and eucaryotic algae are differentially affected by copper activities within these ranges, with reduced reproductive rates in most cyanobacteria at {Cu2+} > lo-l2 M. Eucaryotic algae on the other hand generally showed normal growth up to { Cu2+} = 10-l l M. These experiments suggest that growth rates of cyanobacteria could be reduced in water upwelled from 200 m, where L, is not detectable, yet eucaryotic algae would only be on the brink of limitation and therefore at an advantage over cyanobacteria.

Schenck (1984) examined the growth rate of a dinoflagellate (Gonyaulux tamarensis) in metal-ion-buffered culture media over a wide range of copper activities. High rates of growth were observed at p{Cu2+} between 11 and 12.3 with optimal growth between 12 and 12.3. Copper limitation occurred at p { Cu2+} of 12.5 and greater. In light of our results (Fig. lo), water upwelled from 200 to 300 m would be toxic to this dinoflagellate, whereas surface waters would be biolimiting with respect to copper. It therefore seems that open-ocean and coastal systems might be sensitive to small inputs and complexation of metals such as copper-a topic which is currently under in- vestigation in our laboratory.

Conclusions Strong evidence for two copper-complex-

ing ligand classes having distinctly different vertical distributions and binding strengths

has been observed in a vertical profile from the Northeast Pacific. Concentrations of L2, the weaker ligand, show no apparent vertical structure and L2 is thought to be mixed conservatively with a residence time in the oceanic environment on the order of tens to hundreds of years or greater. Concentra- tions of L,, the stronger ligand, show a vertical distribution that mimics that of primary productivity in the same area and is consistent with a biogenic source (presum- ably phytoplankton) operating on relatively short time scales in the surface euphotic zone. The residence time of this strong ligand is thought to be on the order of months. These ligands significantly depress the free Cu2+ activity to values of 14 fM (pCu2+ = 13.9) in the surface waters and to values of about 10 pM (pCu 2+ = 11) at middepths. From culture experiments of L. Brand, R. Schenck, and others, our data suggest that these ligands may hold free copper in a dy- namic biological balance between copper limitation in surface waters and copper toxicity at depth.

Together, these observations of L, and L2 are consistent with the suggestions of Bada and Lee (1977) that dissolved organic mat- ter (DOM) can be grouped into two frac- tions: extremely stable and inert material, comprising the bulk of the DOM and having radiocarbon ages on the order of several thousand years; and trace organic compounds derived from living organisms which are rapidly degraded. It would appear that L2 and Lr would fit these two descriptions.

References ANDERSON, D. M., AND F. M. M. MOREL. 1978. Cop-

per sensitivity of GonyauIax tamarensis. Limnol. Oceanogr. 23: 283-295.

BADA, J. L., AND C. LEE. 1977. Decomposition and alteration of organic-compounds dissolved in seawater. Mar. Chem. 5: 523-534.

BATHEN, K. H. 1972. On the seasonal changes in the depth of the mixed layer in the North Pacific Ocean. J. Geophys. Res. 77: 7138-7150.

BOND, A. M. 1980. Modern polarographic methods in analytical chemistry. Dekker.

BOYLE, E. A., R. SCLATER, AND J. M. EDMOND. 1977. The distribution of dissolved copper in the Pacific. Earth Planet. Sci. Lett. 37: 38-54.

BRAND, L. E., W. G. SUNDA, AND R. R. L. GUILLARD. 1986. Reduction of marine phytoplankton reproduction rates by copper and cadmium. J. Exp. Mar. Biol. Ecol. 96: 225-250.

https://www.researchgate.net/publication/223239420_Limitation_of_marine_phytoplankton_reproduction_rates_by_copper_and_cadmium_J_Exp_Mar_Biol_Ecol_96_225-250?el=1_x_8&enrichId=rgreq-93af7861-5256-4c2c-968b-e0d3cac01599&enrichSource=Y292ZXJQYWdlOzIzODIwOTA0ODtBUzoxMDI2ODA0MDM5MDY1NjJAMTQwMTQ5MjMyNDQ1MA==


BRULAND, K. W. 1980. Oceanographic distributions of cadmium, zinc, nickel and copper in the North Pacific. Earth Planet. Sci. Lett. 47: 176-198.

__ K. H. COALE, AND L. MART. 1985. Analysis of’scawater for dissolved cadmium, copper and lead: An intercomparison of voltammetric and atomic absorption methods. Mar. Chem. 17: 285- 300.

-, R. P. FRANKS, G. A. KNAUER, AND J. H. MAR- TIN. 1979. Sampling and analytical methods for the determination of copper, cadmium, zinc and nickel at the nanogram per liter level in sea water. Anal. Chim. Acta 105: 223-245.

BUCKLEY, P. J. M., AND C. M. G. VAN DEN BERG. 1986. Copper complexation profiles in the Atlantic ocean. A comparative study using electrochemical and ion exchange techniques. Mar. Chem. 19: 281- 296.

BYRNE, R. H., AND W. L. MILLER. 1985. Copper (II) carbonate complexation in seawater. Geochim. Cosmochim. Acta 49: 1837-1844.

CABANISS, S. E. 1987. Titrator: An interactive program for aquatic equilibrium calculations. Envi- ron. Sci. Technol. 21: 209-210.

-, M. S. SHUMAN, AND B. J. COLLINS. 1984. Metal-organic binding: A comparison of models, p. 165-179. Zn C. J. M. Kramer and J. C. Duinker [eds.], Complexation of trace metals in natural waters. Junk.

DAVIS, J. A., AND J. 0. LECKIE. 1978. Effect of ad- sorbed complexing ligands on trace metal uptake by hydrous oxides. Environ. Sci. Technol. 12: 1309-1315.

HERING, J. G., W. G. SUNDA, R. L. FERGUSON, AND F. F. M. MOREL. 1987. A field comparison of two methods for the determination of copper complexation: Bacterial bioassay and fixed-potential amperometry. Mar. Chem. 20: 299-3 12.

HUIZENGA, D. L., AND D. R. KESTER. 1983. The distribution of total and electrochemically available copper in the northwestern Atlantic Ocean. Mar. Chem. 13: 28 l-29 1.

IMBER, B. E., M. G. ROBINSON, A. M. ORTEGA, AND J. D. BURTON. 1985. Complexation of zinc by ex- udates from Skeletonema costatum grown in culture. Mar. Chem. 16: 131-139.

JACKSON, G. A., AND J. J. MORGAN. 1978. Trace metal- chelator interactions and phytoplankton growth in seawater media: Theoretical analysis and comparison with reported observations. Limnol. Oceanogr. 23: 268-282.

KFWMER, C. J. M. 1986. Apparent copper complexation capacity and conditional stability constants in North Atlantic waters. Mar. Chem. 18: 335- 349.

LEE, C., AND J. BADA. 1975. Amino acids in equatorial Pacific Ocean water. Earth Planet. Sci. Lett. 26: 61-68.

--, AND -. 1977. Dissolved amino acids in the equatorial Pacific, the Sargasso Sea, and Bis- cayne Bay. Limnol. Oceanogr. 22: 502-5 10.

MCKNIGHT, D. M., AND F. M. M. MOREL. 1978. Re- lease of weak and strong copper complexing agents by algae. Limnol. Oceanogr. 24: 823-837.

MANAHAN, S. E., AND M. J. SMITH. 1973. Copper

micronutrient requirement for algae. Environ. Sci. Technol. 7: 829-833.

MART, I,., H.-W. N~~RNBERG, AND D. DYRSSEN. 1983. Low level determination of tract metals in Arctic Sea water and snow by differential pulse anodic stripping voltammetry, p. 113-l 30. Zn Trace metals in sea water. NATO Conf. Ser. 4, Mar. Sci. V. 9. F’lenum.

-- ~ AND H. RUTZEL. 1984. Comparative studies on ‘cadmium levels in the North Sea, Nor- wegian Sea, Barents Sea and the eastern Arctic Ocean. Fresenius Z. Anal. Chem. 317: 201-209.

-- - AND P. VALENTA. 1980. Prevention of;ontammation and other accuracy risks in voltammetric trace metal analysis with a multicell- system designed for clean bench working. Fre- senius Z. Anal. Chem. 300: 350-362.

MARTEL.L, A. E., AND R. M. SMI.TH. 1974. Critical stability constants. V. 1. Amino acids. Plenum.

MOREL, F. M. M. 1982. Principles of aquatic chemistry. Wiley.

-, AND N. M. L. MOREL-LAURENS. 1983. Trace metals and plankton in the oceans: Facts and spec- ulations, p. 84 l-868. Zn Trace metals in sea water. NATO Conf. Ser. 4, Mar. Sci. V. 9. Plenum.

RINGBOM, A., AND E. STILL. 1972. The calculation and use of (Y coefhcients. Anal. Chim. Acta 59: 143-146.

ROBINSON, M. K. (ASSISTED BY R. A. BAUER). 1976. Atl.as of North Pacific Ocean monthly mean tem- peratures and mean salinities of the surface layer. U.S. Naval Oceanogr. Office Ref. Publ. 2 (NO0 RP-2).

RUZIC, I. 1982. Theoretical aspects of the direct titration of natural waters and its information yield for trace metal speciation. Anal. Chim. Acta 140: 99-l 13.

--. 1984. Kinetics of complexation and determination of complexation parameters in natural waters, p. 131-148. Zn C. J. M. Kramer and J. C. Duinker [eds.], Complexation of trace metals in natural waters. Junk.

-- , AND S. NIKOLIC. 1982. The influence of kinetics on the direct titration curves of natural water systems-theoretical considerations. Anal. Chim. Acta 140: 13 1-147.

SCHENCK, R. C. 1984. Copper deficiency and toxicity in Gonyaulax tamarensis (Lebour). Mar. Biol. Lett. 5: 13-19.

SHKOLNIK, M. Y. 1984. Developments in crop science. V. 6. Trace elements in plants. Elsevier.

SUGIMURA, Y., AND Y. SUZUKI. 1988. A high temperature catalytic oxidation method of non-vola- tile dissolved organic carbon in seawater by direct injection of liquid sample. Mar. Chem. In press.

SUNDA, W. G., AND R. L. FURGUSON. 1983. Sensi- tivity of natural bacterial communities to additions of copper and to cupric ion activity: A bioassay of copper complexation in seawater, p. 871- 890. Zn Trace metals in sea water. NATO Conf. Ser. 4, Mar. Sci. V. 9. Plenum.

-, AND R. R. L. GUILLARD. 1976. The relationship between cupric ion activity and the toxicity of copper to phytoplankton. J. Mar. Res. 34: 5 1 l- 52,9.

NE Pac@c copper complexation 1101

-, AND A. K. HANSON. 1987. Measurement of free cupric ion concentration in seawater by a ligand competition technique involving copper sorption onto C,, SEP-PAK cartridges. Limnol. Oceanogr. 32: 537-551.

-, D. KLAVENESS, AND A. V. PALUMBO. 1984. Bioassays of cupric ion activity and copper complexation, p. 399-409. In C. J. M. Kramer and J. C. Duinker [cds.], Complexation of trace metals in natural waters. Junk.

SYMES, J. L., AND D. R. KESTER. 1985. Copper (II) interaction with carbonate species based on mal- achite solubility in perchlorate medium at the ionic strength of seawater. Mar. Chem. 16: 189-2 11.

TAKAHASHI, T., AND OTHERS. 1970. A carbonate chemistry profile at the 1969 GEOSECS intcrcal- ibration station in the eastern Pacific Ocean. J. Geophys. Res. 75: 7648-7666.

TRICK, C. G., R. J. ANDERSEN, A. GILLAM, AND P. J. HARRISON. 1983. Prorocentrin: An extracellular siderophore produced by the marine dinoflagellate Prorocentrum minimum. Science 219: 306-308.

TURNER, D. R., M. WHITFIELD, AND A. G. DICKSON. 198 1. The equilibrium speciation of dissolved components in freshwater and seawater at 25°C and 1 atm. pressure. Geochim. Cosmochim. Acta 45: 855-88 1.

TUSCHALL, J. R., AND P. L. BREZONIK. 1981. Eval- uation of the copper anodic stripping voltammetry complcxometric titration for complexing capaci- ties and conditional stability constants. Anal. Chem. 53: 1986-1989.

VAN DEN BERG, C. M. G. 1982. Determination of copper complexation with natural organic ligands

in seawater by equilibration with MnO,. Part 1: Theory; Part 2: Experimental procedures and application to surface seawater. Mar. Chem. 11: 307- 342.

-. 1984. Determination of the complexing capacity and conditional stability constants of com- plexcs of copper(B) with natural organic ligands in seawater by cathodic stripping voltammetry of copper-catechol complex ions. Mar. Chem. 15: l- 18.

-, P.M. BUCUEY,ANDS.DHARMAVANIJ. 1984. Determination of ligand concentrations and conditional stability constants in seawater. Compar- ison of the DPASV and MnO, adsorption techniques, p. 213-216. In C. J. M. Kramer and J. C. Duinker [eds.], Complexation of trace metals in natural waters. Junk.

WAITE, T. D., AND F. M. M. MOREL. 1983. Char- acterization ofcomplexing agents in natural waters by copper(II)/copper(I) amperomctry. Anal. Chem. 55: 1268-l 274.

WESTALL, J. C. 1982. FITEQL: A program for the determination of chemical equilibrium constants from cxperimcntal data. Oregon State Univ. Dep. Chem. Tech. Rep.

ZUEHLKE, R. W., AND D. R. KESTER. 1983. Copper speciation in marine waters, p. 773-788. In Trace metals in sea water. NATO Conf. Ser. 4, Mar. Sci. V. 9. Plenum.

Submitted: 19 July 1987 Accepted: 18 November I987

Revised: 23 June 1988

copper complexation in the northeast pacific

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