Skip to main content

Metal–organic complexation in the marine environment


We discuss the voltammetric methods that are used to assess metal–organic complexation in seawater. These consist of titration methods using anodic stripping voltammetry (ASV) and cathodic stripping voltammetry competitive ligand experiments (CSV-CLE). These approaches and a kinetic approach using CSV-CLE give similar information on the amount of excess ligand to metal in a sample and the conditional metal ligand stability constant for the excess ligand bound to the metal. CSV-CLE data using different ligands to measure Fe(III) organic complexes are similar. All these methods give conditional stability constants for which the side reaction coefficient for the metal can be corrected but not that for the ligand. Another approach, pseudovoltammetry, provides information on the actual metal–ligand complex(es) in a sample by doing ASV experiments where the deposition potential is varied more negatively in order to destroy the metal–ligand complex. This latter approach gives concentration information on each actual ligand bound to the metal as well as the thermodynamic stability constant of each complex in solution when compared to known metal–ligand complexes. In this case the side reaction coefficients for the metal and ligand are corrected. Thus, this method may not give identical information to the titration methods because the excess ligand in the sample may not be identical to some of the actual ligands binding the metal in the sample.


In the last two decades, our knowledge of trace metal speciation has grown tremendously. With the advent of trace metal clean sampling techniques[1] and sensitive voltammetric techniques, [24] the marine community now recognizes that metal speciation in seawater and estuarine waters is dominated by complexation with organic compounds of unknown composition and origin. [512] Recent culture work [1318] has shown that microorganisms produce a variety of low molecular weight organic compounds that complex metals with high stability constants. These compounds have a variety of functional groups that include phosphate, carboxylic acids, amines, thiol and hydroxy groups. Specific functional groups such as hydroxamate, catecholate and β-hydroxyaspartate are bidentate groups and organisms make molecules with three bidentate groups in a molecule.[14, 1921] In addition, plant degradation products [2230] such as porphyrins are significant organic ligands that bind metals through four N atoms in a square planar arrangement. These latter multidentate molecules have very high stability constants with metals and are also kinetically inert to metal–ligand dissociation processes. [3134] For this reason, organisms generally uptake the free metal ion rather than a metal–ligand form.[35, 36] Thus, an understanding of metal–organism interactions requires an understanding of the amount of dissolved free ion present relative to the total dissolved metal concentration as well as the metal acquisition methods that an organism can use. [3537]

In this paper we review and compare the principal voltammetric methods, which provide evidence for metal–organic complexes. Most voltammetric work is performed with the hanging mercury drop electrode (HMDE) or the rotating disk electrode (RDE) with a thin mercury film (TMF) because these permit the measurement of metal–organic complexation at (sub)nanomolar levels directly in the solution of interest. The actual experimental methods can be broken into two broad categories and are based on the electrochemical behavior of the metal bound to an organic ligand.

The first method consists of titration experiments that measure the amount of ligand in excess to the metal in the solution [3844] and the conditional stability constant, Kcond M'L , for the excess ligand with the metal. The Kcond M'Lis generally assumed to be a 1:1 metal–ligand complex and is given by

Kcond M'L= [ML]/([M'] [L'])

where M' and L' are the concentrations of the metal and ligand that are not bound to each other. These are related to the total metal [M]T and [L]T via

[M'] = [M]T - [ML] and [L'] = [L]T - [ML].

The free metal [Mn+] plus the metal bound to other inorganic ligands equals [M'],

[M'] = [Mn+] + Σ MX i

and the fraction of free metal in the solution without the organic ligand is given by

[Mn+] = [M'] αM


αM = 1/(1 + Σ , [X] i )

This has also been expressed as the side reaction coefficient for M', αM', which is the reciprocal of αM or

αM' = [M']/[Mn+]

The conditional constant for M'L is related to Mn+L by

Kcond ML= [ML]/([Mn+] [L']) = Kcond M'LM')

Similar equations can be written for the organic ligand to give a thermodynamic constant,

Ktherm = [ML]/([Mn+] [Ln-]) = Kcond M'LM') (αL')

but in environmental samples the interactions of H+, Ca2+ and Mg2+ with the ligand are unknown.

The titration experiments include (1) anodic stripping voltammetry[2] (ASV), which is useful for metals that react at the electrode directly (Cu2+, Zn2+, Cd2+, Pb2+), and (2) cathodic stripping voltammetry/competitive ligand exchange[3, 8, 9] (CSV-CLE) which is useful for metals that do not react at the electrode directly but have a metal–ligand complex that does (Fe3+, Co2+). The CSV-CLE method depends on the measurement of a known metal–ligand complex (the competing ligand), that adsorbs to the mercury electrode. In addition, a kinetic CSV-CLE approach [1012] for excess ligand binding a metal has been used to measure the metal organic formation rate constant (kf), dissociation rate constant (kd), the half-life or residence time (t1/2) of the complex and Kcond M'L(from kf/kd). The second type of voltammetry method involves the breakdown of the actual complex in situ and is termed pseudovoltammetry, [4548] which is useful for metals that react at the electrode directly. This method gives information on the amount of ligand binding to a specific complex with a thermodynamic constant, Ktherm, that differs from Kcond ML. Kcond ML is corrected for the side reaction coefficient of the metal but not the ligand whereas Ktherm is corrected for the side reaction coefficients of the metal and ligand via comparison to metal–ligand complexes of known Ktherm (chelate scale).

We describe the use of these methods for unknown ligands in seawater as well as with model ligands in UV irradiated seawater for the metals Cu(II), Zn(II) and Fe(III). In the case of CSV-CLE, we show for known Fe(III)-organic complexes that the use of different ligands [1-nitroso-2-napthol, or 1N2N, and salicylaldoxime, or SAL) gives comparable K and ligand concentration data.


The details of the experimental procedures for ASV and pseudovoltammetry work have been previously described by our group.[45, 46] Total Zn and Cu concentrations were performed using the method of Bruland et al.[1] CSV-CLE and kinetic Fe(III) measurements with 1N2N were performed as we have outlined previously. [1012] CSV-CLE experiments with SAL were performed as described by Rue and Bruland.[6, 7] Examples of model ligands commonly used in experiments are given in Appendices 1 and 2. Appendix 2 shows types of strong ligands (functional groups are circled) that bind to Fe(III) and which may bind to other metals.

Results and discussion

Metal–ligand complexes

Voltammetry can provide information on a ligand actually binding a metal because many metal–ligand complexes give a discrete peak or half-wave potential. In a sample, these peaks can be compared to known ligand–metal complexes in the form of a metal-chelate scale (see pseudovoltammetry below). Fig. 1A shows the voltammetric reduction of inorganic Zn(II) in UV irradiated seawater (Ep = -1.05 V) and Fig. 1B shows the reduction when Zn(II) is bound to two nitrilotriacetic acid molecules (NTA; Ep = -1.52 V). The reduction is more negative for the Zn complex with NTA than for inorganic Zn(II) because the ligand donates electrons more strongly than simple monodentate ligands such as chloride and hydroxide. In addition, two to four atoms in one NTA molecule can bind to Zn(II) and the displacement of monodentate inorganic ligands by multidentate ligands gives rise to higher stability constants via the "chelate" effect which is an entropy driven reaction; i.e., there are more product molecules than reactant molecules for the reaction[49] (generalized eqn. (1) and (2); charges omitted for simplicity).

Figure 1
figure 1

Cyclic voltammograms of (A) 100 μM inorganic Zn in seawater and (B) 100 μM Zn with 50 μM NTA. Peak 2 is due to the reduction of Zn in ZnNTA2. Peak 1 in each CV is due to inorganic Zn reduction and peak 3 is due to the oxidation of Zn in the amalgam.

M(H2O)6 + L-L → M(H2O)4(L-L) + 2H2O     (1)

where L-L indicates a bidentate ligand

ΔG = ΔH - TΔS = -RT ln K     (2)

Every ligand that reacts with a metal can have a unique reduction potential that can be used for analysis and this is the basis for both the CSV-CLE and pseudovoltammetry approaches.

ASV titrations

We first discuss the titration approach for the measurement of metal–organic ligand complexes for metals that react directly at the Hg electrode (ASV experiment). In titration experiments, metal is added to an unknown sample and the inorganic form of the metal (e.g., Fig 1A for inorganic Zn indicates that the deposition potential should be more negative than -1.1 V) is analyzed via deposition experiments for possible reaction at the Hg electrode. More than 95–99% of the metal is normally bound to an unknown organic compound(s), which is in excess to the metal in the sample. Fig. 2A shows that the inorganic Zn reduction peak from a Delaware Bay sample is suppressed until the excess ligand has been titrated by the addition of inorganic Zn. Linearization of the titration data is typically performed by use of the Langmuir or Ruzic transformation [3841] [eqn. (3)] or the Scatchard transformation[39] [eqn. (4)]. For the Langmuir linearization (Fig. 2B),

Figure 2
figure 2

ASV titration of a Delaware Bay sample (A); Langmuir transformation of the titration data (B) and Scatchard-Langmuir transformation of the titration data. 1/slope = [L] = 36.1 nM and K = 1/(intercept [L]) (log K = 9.03).

a plot of [M]/[ML]) vs. [M] yields a straight line with slope CL from which Kcond ML (the conditional stability constant uncorrected for the side reaction coefficient of the ligand) can be evaluated from the intercept. Note that MT - [M] = [ML], [M] is the labile or inorganic M, and αM' is the side reaction coefficient of the metal ion (αM' for the divalent cations of the first transition series in seawater is usually < 0.2 log K units).[50, 51] In Fig. 2B, the linearization plot for data in Fig. 2A shows that there is a single straight line showing only one complex with a CL = 36.1 nM and a log Kcond ML = 9.03.

The Scatchard transformation is given by eqn. (4) and shown in Fig. 2C for the

data in Fig. 2A. A plot of [ML]/[M] vs. [ML] gives a slope which is Kcond ML and [CL] is the x-intercept for the regression line. In this linearization, two separate slopes are noted with a total ligand content of 37.1 nM. These data suggest that two ligands or ligand classes may be present in the sample. By convention, L1 is the stronger ligand with a higher log Kcond ML of 9.13 (concentration = 33.7 nM) and L2 is the weaker ligand with a smaller log Kcond ML of 8.89 (concentration is 37.1 - 33.7 = 3.4 nM). The Scatchard transformation is usually the better of the linearization methods for determining separate ligand classes especially when the log Kcond ML data are similar. More recently, non-linear methods[42] have been gaining popularity.

It is important to reiterate that the Kcond ML data cannot be corrected for the side reaction coefficient of the unknown ligand in samples. Bruland[2] showed that the Zn-EDTA complex has a log Kcond ML = 7.9 in UV seawater but log Kcond ML > 11 in 0.1 M KC1 of the same pH. The difference in these constants is due to the interaction of Ca and Mg in seawater with the carboxylic acid functional groups of EDTA. However, the actual thermodynamic constant for Zn-EDTA is log Ktherm = 16.3. The fact that a log Kcond ML > 11 is calculated indicates that there is a titration window for these types of ASV titration experiments. The titration window depends on the concentration of the unknown ligand and the metal. In general, there is a window of about six log K units for these types of titrations.

CSV-CLE titrations

Any known metal–organic complex, which gives a voltammetry signal, can be used to study the interactions of that metal with an unknown ligand(s) in a sample. In this example, the known ligand is a competitive ligand, one competing for the metal in a sample. This approach must be used for metals such as Fe(III)[3, 6, 12] and Co(II)[8, 9] that do not react directly at the mercury electrode. Several studies have also used this approach for metals[40, 41, 44, 46] such as Zn and Cu, which can be measured at the electrode. Comparison of the ASV and CSV-CLE methods[44] for these metals shows similar [CL] and Kcond ML data.

In the CSV-CLE case, metal in increasing concentration (from zero added metal) is added to a series of electrochemical cells containing the sample with the same amount of a competitive ligand. After analyzing each electrochemical cell, a plot similar to Fig. 2A results. Linearization of the data is given in eqn. (5), which is identical to eqn. (4)

except for αML, which is the side reaction coefficient for the metal with the competitive ligand. Much work has been performed to understand Fe(III) speciation in seawater. For Fe(III), the Kcond Fe(III)L of a Fe-natural ligand complex and total natural ligand concentration [CL] can be calculated from the intercept and slope of a [Felabile]/[FeL] vs. [Felabile] plot. [Felabile] is that metal that can bind with the competitive ligand and is obtained from the CSV Fe peak current, iP, and the sensitivity, S (slope of a standard curve in UV seawater); i.e. [Felabile] = ip/S = [Fe3+] (αFe' + αFe 1N2N) and [FeL] = C Fe - [Fe labile ]. The αFe' is the a coefficient for all inorganic species of Fe3+ (108.4 at pH = 7; 1010.0 at pH = 8)[34] and αML is the side reaction coefficient for Fe(III)L competitive ligand complexes. For Fe(III) with 1N2N, [3, 12, 52] the αFelN2N is about 1013.04 at pH = 7 and 8. For salicylaldoxime,[6] the αFeSal is about 102 at pH = 8. The window for determination of Kcond Fe(III)Lis smaller that the ASV method (about two log units) but can be varied by changing the ligand concentration. The low αFeSal for salicylaldoxime indicates that the Kcond Fe(III)L calculated is dependent on the accuracy of αFe' used. Byrne et al.[53] have estimated a value of αFe' of 1011.5 so Kcond Fe(III)L can vary 1.5 log units based on the αFe' used.

Fig. 3 shows the log Kcond Fe(III)L data for several model ligands in UV seawater determined by CSV-CLE titrations with the two competitive ligands (1N2N and SAL). In these calculations[54] an αFe' of 1010.0 at pH = 8 was used. The data show that the log Kcond Fe(III)L data are similar – usually within one log K unit – when using either competitive ligand. The use of 1N2N at pH = 7, where the FelN2N voltammetric peak is most sensitive, does not compromise the data. The main reason for this is the high αFe1N2N when compared to the αFe' of Fe(III) at these pH values. The vertical lines in Fig. 3A and 3B show the range of reported Fe(III)L log K values from the world's oceans. Fig. 3 also shows that the model ligands binding Fe(III) give similar log Kcond Fe(III)L data regardless of their structure. This will be discussed below.

Figure 3
figure 3

Data for log Fecond Fe(III)L complexes (A) CLE-CSV at pH = 7 using 1N2N as the competitive ligand and (B) kinetic method at pH = 8 using SAL as the competitive ligand.

Kinetic approach

This approach has been used to assess the rate constants for formation and dissociation of Fe(III)L complexes. The approach is briefly described but is detailed elsewhere.[1012, 55] Excess Fe' is added to a sample without any competitive ligand so that the excess Fe' can bind to the organic ligand(s) in seawater (eqn. (6)). Aliquots of this solution are measured over time at the pH of the sample after addition of a competitive ligand to the aliquot. The kf (rate of formation of FeL is determined from this experiment) for the excess ligand binding to Fe' is determined by kinetic analysis of the time course.

Fe' + L → FeL     (6)

The kd and t1/2 are determined by recovering Fe' in FeL by adding a competitive ligand such as 1N2N to an equilibrated sample (eqn. (7)). This is monitored over time.

FeL + 3(1N2N) → Fe(lN2N)3 + L     (7)

Eqn. (7) can be broken into two eqn. (8) and (9)

FeL → Fe' + L     (8)

Fe' + 3(1N2N) → Fe(lN2N)3     (9)

The kd is evaluated using the steady state approximation for Fe' which simplifies the kinetic expression to ln[FeL] = kd t. The Kcond Fe'L = kf/kd and Kcond Fe(III)L = Kcond Fe'LFe') where αFe' = 1010. Fig. 4 shows the log Kcond Fe(III)L data obtained from the kinetic approach at pH = 8 and the CSV-CLE approach for model ligands bound to Fe(III) in UV seawater. The agreement is excellent indicating that both methods give comparable results. To date the window for Kcond Fe(III)L using this method is log K 18–23. In addition to the stability constant data, the kinetic data for Fe'L (Table 1) reflect the fast reaction rates via kf and slow dissociation rates via kd. The t1/2 and residence times for Fe(III)L complexes come directly from the k d data (t1/2 x kd = 0.693) and correlate with other estimates of iron residence times in the ocean.[56, 57]

Figure 4
figure 4

Data for log Fecond Fe(III)L complexes (A) CLE-CSV at pH = 7 and (B) kinetic method at pH = 8 using 1N2N as the competitive ligand.

Table 1 Comparison of model FeL complex formation and dissociation rate constants, conditional stability constants, and Fe' and Fe3+residence times in treated with Chelex, photo-irradiated seawater as determined using the kinetic method. Errors represent average mean ± s (standard deviation) from two separate replicates.[1] Data taken from ref. 12

These CSV-CLE and kinetic data as well as solubility data[58, 59] indicate that Fe(III) is primarily complexed by natural organic compounds in seawater.

Pseudovoltammograms and chelate scales

Metal reduced to an amalgam; e.g. ZnL + 2e-→ Zn(Hg) + L

When a metal–ligand complex is reduced to a metal amalgam, the half-wave potential of a metal complex, E1/2', or the peak potential, Ep, can be directly related to the thermodynamic stability constant, Ktherm, [4548] by eqn. (10):

E1/2' = E1/2 - [2.303 RT log Ktherm]/nF     (10)

where E1/2 is the reduction potential of the free metal ion and n is the number of electrons involved in the process and Ktherm = Kox = [ML]/{[M] [L]} for a 1:1 complex (for simplicity). Ktherm is corrected for ionic strength effects, the side reaction coefficients of the metal and the ligand in the solution of interest and is a pH independent constant. This particular form of the Lingane equation assumes: (a) no dependence on the reduced metal since it is an amalgam; thus, the complex is destroyed which is a measure of the bond strength and Ktherm; (b) E1/2' is independent of ligand concentration, which can be checked by titrating the metal with ligand until no further change in E1/2' is observed.

At trace concentrations for metal–ligand complexes, pseudopolarograms or pseudovoltammograms are recorded by performing a stripping experiment. Deposition experiments are performed over a range of potentials and the current recorded at each potential. The range of potentials should provide current values where the analyte is and is not electroactive. Plots of i vs. deposition potential (E dep ) give an "s"-shape Nernstian curve from which E1/2 can be evaluated. For complexes which give a discrete E1/2 based on the pseudopolarogram, E1/2 for the complex is directly related to the decomposition of the metal–ligand complex via Ktherm (eqn.(ll))

E1/2= E1/2+ [RT In Ktherm]/nF     (11)

where E1/2 is the potential of the analyte in the absence of complexation by any organic ligand in the matrix of interest. A plot of E'1/2vs. In Ktherm for a series of metal–ligand complexes can be constructed from the literature or from experiment to derive information on Ktherm from unknown ligands in natural samples.

Fig. 5A shows SWV peaks for 100 micromolar Zn(II) with NTA and Fig. 5B shows a pseudovoltammogram for 10 nanomolar Zn(II) with NTA. The data are similar for the Zn(NTA)2 complex. Inorganic Zn(II) varies because of the much higher concentration in Fig. 5A than Fig. 5B. These data show that inorganic ions in seawater do not bind high concentrations of Zn(II) effectively. Based on these types of data, a chelate scale (E1/2 vs. log Ktherm) can be constructed for Zn with a variety of ligands. Fig. 6 shows a scale for seven known ligands[45] covering the range of log Ktherm 4 to 18. These data indicate that the window for estimation of log Ktherm data is much larger for the chelate scale approach than the ASV titration approach. The upper limit for log Ktherm for Zn as well as other metals is controlled by sodium ion reduction which begins near -1.75.

Figure 5
figure 5

(A) Square wave voltammogram of 100 μM Zn with 50 μM NTA and (B) pseudovoltammogram of 10 nM Zn with 500 nM NTA using anodic stripping square wave voltammetry.

Figure 6
figure 6

A plot of E'1/2 from pseudovoltammograms vs. log Ktherm for Zn-organic complexes dissolved in seawater. 1 = oxalic acid; 2 = CTP; 3 = ethylenediamine; 4 = glycine; 5 = 8-hydroxyquinoline; 6 = iminobis(metnylenephosphonic acid); 7 = EDDA; 8 = NTA as Zn(NTA)2. The numbers 9–11 refer to unknown complexes in Delaware Bay waters (see Fig. 7).

Fig. 7A and Fig. 7B show pseudovoltammograms obtained from rainwater (September 5, 1992) and seawater (June 26, 1992) from the mouth of Delaware Bay with the Atlantic Ocean. The rainwater sample shows no organic complexation for Zn(II) whereas the seawater sample shows that there are two moderate-strength ZnL complexes at -1.24 V (log Ktherm = 7.77) and -1.40 V (log Ktherm = 11.45, respectively. A possible weak third-ligand complex at -1.082 V (log Ktherm = 4.14 M-1) is due to inorganic ligands and/or weak acids such as oxalate. The Zn concentration bound to each of these complexes in increasing negative potential is 1.7, 0.90 and 3.5 nM (5.7 nM combined based on the Zn peak sensitivity) whereas the total Zn concentration in the sample is 24.7 nM. Thus, 19 nM of complexed Zn compounds are still unaccounted for. This could be due to strong organic complexes (log Ktherm > 18) or multinuclear sulfide complexes[60] which have been found in natural waters that have log Ktherm > 40. These Zn-ligand complexes cannot be determined by the pseudovoltammetry approach because of sodium ion reduction, which permits an upper limit of log Ktherm = 18 for Zn.

Figure 7
figure 7

(A) Pseudovoltammogram of a rainwater sample from Lewes, Delaware on 5 September 1992; (B) pseudovoltammogram of Delaware Bay water on 26 June 1992.

These data are now compared with the ASV titration approach shown in Fig. 2. The latter method indicates that one complex (perhaps a second) with ligand in excess to the metal is present with a value for the conditional log Kcond ML = 9.03.

The conditional Kcond ML and Ktherm data are not readily comparable for Zn(II) because Ktherm data are due to the actual ligand complexes in the sample and Kcond ML data are for the ligands in excess to the metal in seawater. The actual ligands binding Zn may or may not be the same as the excess ligands to total Zn in the sample. The log Ktherm data that are less than 9.03 are weak complexes that are not detected by both Langmuir and Scatchard linear transformations. The complex with log Ktherm = 11.45 (close to the ZnEDDA complex)[45] may not be related to the log Kcond ML data of 9.03 either because the actual ligand concentration binding Zn in this case via the pseudovoltammograms is smaller than the ASV titration calculation of 36.1 nM. Thus, the two methods appear to be giving information on different Zn complexes.

A similar approach has been used for Cu(II)[46] as shown in Fig. 8. In that study, 17 known organic ligands were used to develop a chelate scale with a log Ktherm range of 12–26.5. The upper limit for this scale based on the sodium reduction wave is log Ktherm ~49. Interestingly, the largest log Ktherm value for a CuL ligand is smaller than the estimated CuL data from field and culture samples (E'1/2 is more negative for the field samples) demonstrating that very strong CuL complexes can be formed. The strong CuL complex found in Martha's Vineyard waters was matched by a ligand produced by a strain of Synechoccous. The moderately strong CuL complex in Eel's Pond and in Martha's Vineyard waters did not match the ligands from other cultures. The three cultures tested showed a great variability of ligands that can be produced by different organisms. The log Kcond Cu(II)L for these complexes as determined by ASV titration ranged from 10.8 to 14.3. These conditional constants indicate that the side reaction coefficients for the ligand(s) are high and similar to what has been observed for ligands that form Fe(III) complexes, which are discussed below.

Figure 8
figure 8

A plot of E'1/2 from pseudovoltammograms vs. log Ktherm for Cu(II)-organic complexes dissolved in seawater. Blue symbols are from cultures and green symbols are from natural waters as indicated.

Reduction of a metal complex to a lower valency (no amalgam formation) Fe3+L + e- ↔ Fe2+L

Similar chelate scale data can be obtained for metal complexes which do not decompose at the electrode to form metal amalgams.[47, 48] In this case, E'1/2 is proportional to the ratio of the thermodynamic stability constants of the reduced and oxidized complexes according to eqn. (12):

E'1/2 = E1/2 - [2.303 RT/nF] log Kox/Kred     (12)

where Kox and Kred are the stability constants of Fe3+L and Fe2+L, respectively. If the Kred values for all complexes are similar as shown for Fe(III) then the Kred term can be incorporated into the intercept and the equation simplifies to eqn. (13):

E'1/2 = [E 1/2 + (2.303 RT/nF) log Kred] -2.303 RT/nF log Kox     (13)

For this case the electrode processes are reversible (checked by CV or SWV) because the complex does not dissociate or become destroyed, and E'1/2 is independent of the ligand concentration (check by titrating the metal with ligand until no further change in E'1/2 is observed).

A chelate scale for Fe(III)[47] has been developed using seven natural ligands (Table 2 and Fig. 9) which react with Fe(III) to form complexes spanning 20 log Ktherm units. For this example we discuss the binding properties with regard to eqn. (2). The first 3 complexes contain CDTA or NTA with or without a catechol. The low Ep and log K reflect that carboxylic acids do not bind (lower ΔH) with Fe(III) like the other complexes which contain only catechol functional groups. Fe(cat)2 - is stronger than these but weaker that the tris-catechol complexes. The nitro-catechol binds more weakly in the tris complex to Fe(III) than catechol because the nitro group is an electron withdrawing group. The enterobactin complex with Fe(III) shows the stronger binding effect of one molecule with three catechol groups than three separate catechol ligands. This is related to entropic effects via the "chelate" effect.[49] For example, Fe(cat)3 3- and Fe(ent)3- have the following reactivity [eqn. (14a) and (14b)] based on Fe(III).

Figure 9
figure 9

A plot of E'p from square wave voltammograms vs. log Ktherm for Fe(III)-organic complexes dissolved in 0.1 M KC1. Numbers refer to compounds in Table 2.

Table 2 Electrochemical and stability constant data for Fe(III) complexes with selected "model" ligands47and natural siderophores.[48] Measurements were made in 5 mM Bistris buffer adjusted to 0.1 M ionic strength with NaCl

+ 3 cat2- + 6H2O     (14a)

+ ent6- → Fe(ent)3- + 6H2O     (14b)

The larger log Ktherm reflects that ΔG is controlled by ΔS in eqn.(14b) because the ΔH term for catechol functional groups is similar for eqn.(14a) and (14b). These data suggest that k d for the Fe(ent)3- containing a tris-catechol structure is smaller than for three separate catechol groups in Fe(cat)3 3-. Because K = kf/kd, K and ΔG increase with smaller kd.[49]

Fig. 9 also shows data for catechol ligands produced by different organisms.[47, 48]Mytilus edulis produces a 100 kDa foot protein (mefpl) which contains several catechol groups. It is not known how many catechol groups bind to Fe(III) in the protein but Ep and log Ktherm are larger than the bis-catechol Fe(III) complexes. Tryptic digests of the foot protein produce decapeptides that react to form FeL2, bis-catechol complexes, as in Fig. 10. These bind more strongly with Fe(III) than two catechols in Fe(cat)2 - and this stronger binding appears related to interaction of the pep tide chains with each other which helps to lower kd. Similar results[47] have been noted for the bis(catechol) complex of alterobactin-B from Alteromonas luteoviolacea.

Figure 10
figure 10

Hyperchem MM + 2 calculation for the FeL2 complex from a decapeptide prepared from Mytilus edulis foot protein 1. The two decapeptide ligands appear to interact to stabilize the complex and prevent dissociation. The log Ktherm estimated is 40.2 vs. 34.7 for the bis(catechol) complex. The Fe atom bound to six oxygen atoms is in the upper left part of the figure.

These data show that the known ligands have a significant difference in log Ktherm. However, these ligands and other known Fe(III) binding ligands have remarkably similar log Kcond Fe(III)L values (Fig. 3 and 4) despite having different structures. This suggests that proton loss from the ligand and not Mg, Ca binding are important for the binding of Fe by the ligand. The side reaction coefficients for these ligands differ in such a way that when correcting for proton effects, the Ktherm data is different. The model ligands range from catecholate groups, which have 2 protons per functional group (6 total for enterobactin), to one proton per functional group for hydroxamates (3 total for desferrioxamine because there is no proton attached to the C = O group). The three proton difference for enterobactin (also alterobactin-A) vs. that for desferrioxamine leads to a different Ktherm. In addition, porphyrins have 2 protons per functional group and all four N atoms can bind Fe. The effect of losing 6 protons from Alterobactin-A, 3 protons from desferrioxamine and 2 protons from a porphyrin lead to similar log Kcond Fe(III)L.


The ASV and CSV-CLE methods for the determination of organic-metal complexation give similar results for Kcond MLand ligand concentration. These data relate to the ligand in excess to the metal in solution. ASV titrations have a larger Kcond ML window than CSV-CLE, which can be varied by changing the competing ligand concentration. The excess ligand may or may not be the same as the actual ligand in the metal–ligand complex in the sample. The pseudovoltammogram method gives Ktherm and ligand concentration data on the actual complex(es) in solution within the window limited by the reduction of sodium ion. The data from the titration methods and the pseudovoltammogram data are not necessarily similar as shown for Zn. For Fe(III), the choice of competitive ligand for the CSV-CLE methods does not appear to affect the log Kcond Fe(III)L data. The kinetic approach also agrees with the CSV-CLE methods. These similarities are due to measuring the same ligand types; i.e. excess ligand to the metal in the sample.


Appendix 1

Appendix 2


  1. Bruland KW, Franks RP, Knauer GA, Martin JH: Anal Chim Acta. 1979, 105: 233-10.1016/S0003-2670(01)83754-5.

    Article  Google Scholar 

  2. Bruland KW: Limnol Oceanogr. 1989, 34: 176-

    Article  Google Scholar 

  3. Gledhill M, van den Berg CMG: Mar Chem. 1994, 47: 41-10.1016/0304-4203(94)90012-4.

    Article  Google Scholar 

  4. Van den Berg CMG, Nimmo M, Abollino O, Mentasti E: Electroanalysis. 1991, 3: 477-10.1002/elan.1140030606.

    Article  Google Scholar 

  5. Kozelka PB, Bruland KW: Mar Chem. 1998, 60: 267-10.1016/S0304-4203(97)00107-2.

    Article  Google Scholar 

  6. Rue EL, Bruland KW: Mar Chem. 1995, 50: 117-10.1016/0304-4203(95)00031-L.

    Article  Google Scholar 

  7. Rue EL, Bruland KW: Limnol Oceanogr. 1997, 42: 901-

    Article  Google Scholar 

  8. Saito MA, Moffett JW: Mar Chem. 2001, 75: 49-10.1016/S0304-4203(01)00025-1.

    Article  Google Scholar 

  9. Ellwood MJ, van den Berg CMG: Mar Chem. 2001, 75: 33-10.1016/S0304-4203(01)00024-X.

    Article  Google Scholar 

  10. Witter AE, Luther GW: Mar Chem. 1998, 62: 241-10.1016/S0304-4203(98)00044-9.

    Article  Google Scholar 

  11. Witter AE, Lewis BL, Luther GW: Deep Sea Res. 2000, 47: 1517-10.1016/S0967-0645(99)00152-6.

    Article  Google Scholar 

  12. Wu J, Luther GW: Mar Chem. 1995, 50: 159-10.1016/0304-4203(95)00033-N.

    Article  Google Scholar 

  13. Haygood MG, Holt PD, Butler A: Limnol Oceanogr. 1993, 38: 1091-

    Article  Google Scholar 

  14. Martinez JS, Zhang GP, Holt PD, Jung H-T, Carrano CJ, Haygood MG, Butler A: Science. 287: 1245-10.1126/science.287.5456.1245.

  15. Wilhelm SW, Maxwell DP, Trick CG: Limnol Oceanogr. 1996, 41: 89-

    Article  Google Scholar 

  16. Wilhelm SW, MacAuley K, Trick CG: Limnol Oceanogr. 1997, 43: 992-

    Article  Google Scholar 

  17. Reid RT, Butler A: Limnol Oceanogr. 1991, 36: 1783-

    Article  Google Scholar 

  18. Reid RT, Live DH, Faulkner DJ, Butler A: Nature. 1993, 366: 455-10.1038/366455a0.

    Article  Google Scholar 

  19. Hofte M: Classes of microbial siderophores. Iron chelation in plants and soil microorganisms. Edited by: Barton LL, Hemming BC. 1993, Academic Press, Inc., San Diego, CA, 4-

    Google Scholar 

  20. Loomis LD, Raymond KN: Inorg Chem. 1991, 30: 906-10.1021/ic00005a008.

    Article  Google Scholar 

  21. Wong GB, Kappel MJ, Raymond KN, Matzanke B, Winkelmann GJ: J Am Chem Soc. 1983, 105: 810-10.1021/ja00342a027.

    Article  Google Scholar 

  22. Hutchins DA, Wang WX, Fisher NS: Limnol Oceanogr. 1995, 40: 989-

    Article  Google Scholar 

  23. Hutchins DA: Prog Physiol Res. 1995, 11: 1-

    Google Scholar 

  24. Hutchins DA, Witter AE, Butler A, Luther GW: Nature. 1999, 400: 858-10.1038/23680.

    Article  Google Scholar 

  25. Hutchins DA, Bruland KW: Mar Ecol Prog Ser. 1994, 110: 259-

    Article  Google Scholar 

  26. Gobler CJ, Hutchins DA, Fisher NS, Cosper EM, Sanudo-Wilhelmy SA: Limnol Oceanogr. 1997, 42: 1492-

    Article  Google Scholar 

  27. Palmer SE, Baker EW: Science. 1978, 201: 49-

    Article  Google Scholar 

  28. Suzumura M, Kamatani A: Geochim Cosmochim Acta. 1995, 59: 1021-10.1016/0016-7037(95)00006-2.

    Article  Google Scholar 

  29. Suzumura M, Kamatani A: Limnol Oceanogr. 1995, 40: 1254-

    Article  Google Scholar 

  30. Theil EC: Ann Rev Biochem. 1987, 56: 289-10.1146/

    Article  Google Scholar 

  31. Crumbliss AL: Aqueous solution equilibrium and kinetic studies of iron siderophore and model siderophore complexes. CRC Handbook of Microbial Iron Chelates. Edited by: Winkelmann G. 1991, CRC Press, Boca Raton, FL, 177-232.

    Google Scholar 

  32. Hering J, Morel FMM: Geochim Cosmochim Acta. 1989, 45: 855-

    Google Scholar 

  33. Hudson RJM, Morel FMM: Deep-Sea Res. 1993, 40: 129-10.1016/0967-0637(93)90057-A.

    Article  Google Scholar 

  34. Hudson RJM, Covault DT, Morel FMM: Mar Chem. 1992, 38: 209-10.1016/0304-4203(92)90035-9.

    Article  Google Scholar 

  35. Sunda WG, Gillespie PA: J Mar Res. 1979, 37: 761-

    Google Scholar 

  36. Butler A: Science. 1998, 281: 207-10.1126/science.281.5374.207.

    Article  Google Scholar 

  37. Bruland KW, Donat JR, Hutchins DA: Limnol Oceanogr. 1991, 36: 1555-

    Article  Google Scholar 

  38. Ruzic I: Anal Chim Acta. 1982, 140: 99-10.1016/S0003-2670(01)95456-X.

    Article  Google Scholar 

  39. Ruzic I: Kinetics of complexation and determination of complexation parameters in natural waters. Complexation of trace metals in natural waters. Edited by: Kramer CJM, Duinker JC. 1983, Dr W Junk Publishers, The Hague, 131-147.

    Google Scholar 

  40. Van den Berg CMG: Mar Chem. 1984, 15: 1-10.1016/0304-4203(84)90035-5.

    Article  Google Scholar 

  41. Van den Berg CMG, Donat JR: Anal Chim Acta. 1992, 257: 281-10.1016/0003-2670(92)85181-5.

    Article  Google Scholar 

  42. Gerringa LJA, Herman PMJ, Poortvliet TCW: Mar Chem. 1995, 48: 131-10.1016/0304-4203(94)00041-B.

    Article  Google Scholar 

  43. Miller LA, Bruland KW: Anal Chim Acta. 1997, 343: 161-10.1016/S0003-2670(96)00565-X.

    Article  Google Scholar 

  44. Donat JR, Bruland KW: Mar Chem. 1990, 28: 301-10.1016/0304-4203(90)90050-M.

    Article  Google Scholar 

  45. Lewis BL, Luther GW, Lane H, Church TM: Electroanalysis. 1995, 7: 166-10.1002/elan.1140070213.

    Article  Google Scholar 

  46. Croot PL, Moffett JW, Luther GW: Mar Chem. 1999, 67: 219-10.1016/S0304-4203(99)00054-7.

    Article  Google Scholar 

  47. Taylor SW, Luther GW, Waite JH: Inorg Chem. 1994, 33: 5819-10.1021/ic00103a032.

    Article  Google Scholar 

  48. Lewis BL, Holt PD, Taylor SW, Wilhelm SW, Trick CG, Butler A, Luther GW: Mar Chem. 1995, 50: 179-10.1016/0304-4203(95)00034-O.

    Article  Google Scholar 

  49. Shriver DF, Atkins P, Langford CH: Inorganic Chemistry. 1994, Freeman WH and Co., NY, 819-2

    Google Scholar 

  50. Baes CFJ, Messmer RE: The hydrolysis of cations. A 59 critical review of hydrolytic species and their stability constants in aqueous solution. 1976, Wiley, New York, 229-237.

    Google Scholar 

  51. Turner DR, Whitfield M, Dickson AG: Geochim Cosmochim Acta. 1981, 45: 855-10.1016/0016-7037(81)90115-0.

    Article  Google Scholar 

  52. Van den Berg CMG: Mar Chem. 1995, 50: 139-10.1016/0304-4203(95)00032-M.

    Article  Google Scholar 

  53. Byrne RH, Kump LR, Cantrell KJ: Mar Chem. 1988, 25: 163-10.1016/0304-4203(88)90062-X.

    Article  Google Scholar 

  54. Witter AE, Hutchins DA, Butler A, Luther GW: Mar Chem. 2000, 69: 1-10.1016/S0304-4203(99)00087-0.

    Article  Google Scholar 

  55. Luther GW, Wu J: Mar Chem. 1997, 57: 173-10.1016/S0304-4203(97)00046-7.

    Article  Google Scholar 

  56. Johnson KS, Gordon RM, Coale KH: Mar Chem. 1997, 57: 137-10.1016/S0304-4203(97)00043-1.

    Article  Google Scholar 

  57. Johnson KS, Gordon RM, Coale KH: Mar Chem. 1997, 57: 181-10.1016/S0304-4203(97)00047-9.

    Article  Google Scholar 

  58. Millero FJ: Earth Planet Sci Lett. 1998, 154: 323-10.1016/S0012-821X(97)00179-9.

    Article  Google Scholar 

  59. Kuma K, Nishioka J, Matsunaga K: Limnol Oceanogr. 1996, 41: 396-

    Article  Google Scholar 

  60. Rozan TF, Lassman ME, Ridge DP, Luther GW: Nature. 2000, 406: 879-10.1038/35022561.

    Article  Google Scholar 

Download references


This work was supported by two grants from the National Science Foundation (OCE-9730334 and OCE-9714302). We wish to congratulate Frank Millero on receiving the first ACS Division of Geochemistry award and for his encouragement over the years.

Author information

Authors and Affiliations


Corresponding author

Correspondence to George W Luther III.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Luther, G.W., Rozan, T.F., Witter, A. et al. Metal–organic complexation in the marine environment. Geochem Trans 2, 65 (2001).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


  • Ligand Complex
  • Ligand Concentration
  • Enterobactin
  • Anodic Strip Voltammetry
  • Model Ligand