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19 Effects of Humic Substances on Metal Speciation

E. Michael Perdue

School of Geophysical Sciences, Georgia Institute of Technology, Atlanta, GA 30332

This chapter addresses some of the problems that must be understood and solved before the effects of metal-humic substance complexation on water-treatment processes can be quantitatively addressed. The heterogeneity of ligands in a humic substance not only complicates the mathematical description of equilibrium data, but also makes the complexation capacity of a humic substance almost impossible to determine accurately. Complexation capacities (meq/g) of humic substances are widely reported to vary with pH, ionic strength, concentration of the humic substance used in the measurement, and nature of the metal being studied. By analogy with the behavior of a simple ligand (citrate), this chapter demonstrates that the reported effect of humic-substance concentration on complexation capacity is probably an artifact and that other experimental parameters affect conditional concentration quotients for metal complexation reactions. These effects create the illusion that complexation capacity is a function of pH, ionic strength, and nature of the added metal ion.

HUMIC SUBSTANCES ARE UBIQUITOUS in the aquatic environment, and their ability to form complexes with metal ions is well documented by many experimental and modeling studies. The interaction of humic substances with metal ions has been the subject of several recent review papers (1-6). In the context of water-treatment chemistry, the interaction of humic substances with metal ions can potentially affect removal of humic substances by coagulation-flocculation processes, removal of toxic heavy metals from polluted waters, and rates and products of reaction of humic substances with disinfectants.

0065-2393/89/0219-0281$06.00/0 © 1989 American Chemical Society

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In Aquatic Humic Substances; Suffet, I., et al.; Advances in Chemistry; American Chemical Society: Washington, DC, 1988.

282 AQUATIC HUMIC SUBSTANCES

Rather than process-oriented aspects of metal-humic substance complexation, the focus here is on describing some of the experimental and conceptual pitfalls that undermine our efforts to quantitatively describe metal-humic substance complexation in a predictive manner. Until such problems are clearly understood, the effects of metal-humic substance complexation on water-treatment processes wil l remain obscure, and trial-and-error wil l continue to be the most common approach toward the development of water-treatment methodologies.

Experimental studies can be conducted to examine metal complexation by humic substances at any p H , ionic strength, or combination of competing metal ions. Quantitative modeling of metal-humic substance complexation has not advanced, however, beyond single-metal complexation at constant p H and ionic strength. Even in such relatively simple systems, proper recognition of the effects of p H , ionic strength, nature of the metal, and the concentration of humic substances used in an experiment on metal-humic substance complexation equilibria is needed for interpretation of complex-ation-capacity measurements and interpretation of thermodynamic data on metal-humic substance complexation.

Overview of Metal Complexation Equilibria This section presents an overview of the pertinent equations that describe metal-ligand complexation equilibria, both for a simple ligand and for a complex mixture of ligands. The distinction between concentrations and activities must be clearly developed and maintained. Equilibrium constants depend only on temperature and pressure; concentration quotients depend on temperature, pressure, and ionic strength; and conditional concentration quotients depend on temperature, pressure, ionic strength, p H , concentrations of competing metals, and ligands.

Complexation by a Single Ligand. The reactions between a metal ion (M) and a single binding site (Lt) can be described by either overall or stepwise formation constants. For example, for the 1:1 metal-to-ligand complexation reaction, M + Lj = M L 4 , the overall and stepwise formation constants are the same (the stepwise Κ wi l l be used):

{ M L } [ML,] 7ML, = R M

* { M R U [M][LJ * 7M7L{

1 ' U

where M is a metal aqueous ion; L* is a fully deprotonated binding site; ML{

is the complex formed from 1 mol each of M and L f ; braces { } and square brackets [ ] denote activities and concentrations, respectively; and 7-values are activity coefficients. K{ is a true thermodynamic constant, but the concentration quotient and the activity coefficient ratio Γ( are complementary

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19. PERDUE Humic Substances and Metal Speciation 283

functions of ionic strength. For most simple metal-ligand complexes, basic electrostatic considerations (Debye-Hiickel theory) indicate that the activity coefficient ratio (Γ,) equals 1 at zero ionic strength and increases with increasing ionic strength. values therefore equal K{ values at zero ionic strength and tend to decrease with increasing ionic strength. In a given solution of metal and ligand, the concentration of the complex M L 4 is thus expected to decrease upon addition of a background electrolyte. Experimental studies generally yield concentrations, rather than activities, of reac-tants and products. Consequently, Kt values cannot be directly measured, but must be obtained either by estimation of Γ< values or by extrapolation of Ki° values (obtained at several ionic strengths) to zero ionic strength.

Another factor that affects the extent of complexation of M by Lj is competition from side reactions, especially the hydrolysis of the metal ion to produce hydroxy complexes and the protonation of the ligand to produce its conjugate acid(s). These reactions do not actually change K(

c as we have defined it, but they do affect the degree of complexation of M by L f . As a general rule, ligands tend to form protonated ligands at low p H and metal ions tend to form hydroxy complexes at high p H . Consequently, the reaction between the metal ion and the ligand is often most favorable at intermediate p H values.

For mathematical convenience, a conditional concentration quotient K{* is often defined, in which the precise terms in equation 1 are replaced by more convenient terms:

= [M^bound)]

^ [ M ( M W M ]

In this equation, M (free) represents all forms of the metal ion that are not bound to the ligand of interest, L,(free) represents all forms of the ligand that are not bound to the metal ion, and ML ((bound) represents all complexes of 1:1 metal-to-ligand stoichiometry. Unlike K ^ , which is a function only of ionic strength, K ( * is a function of ionic strength, p H , concentrations of competing metal ions and ligands, and so on. If all side reactions are well understood, K f * is a useful parameter that can be directly related to Kf.

Complexat ion by a Mul t i l i gand M i x t u r e . In the previous section, the use of K,* instead of Kf was a matter of mathematical and experimental convenience. In the study of metal binding by a multiligand mixture such as humic substances, however, there is no choice. It is simply not possible to fully describe the side reactions of a ligand mixture whose individual components are unknown. Conditional concentration quotients or related hybrid expressions are used exclusively, even though the users of such expressions may not always recognize their limitations. In extending the concept of a conditional concentration quotient for metal complexation by a

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single ligand to multiligand mixtures, an expression that formally resembles equation 2 is usually written

X [Ml^bound)] K* = (3)

[M(free)] £ Wfree)] 1 '

where 2[ML t(bound)] is the sum of the concentrations of all complexes formed between M and the multiligand mixture, X[Lf(free)] is the sum of the concentrations of all binding sites that are not associated with M , and [M(free)] is the sum of metal species that are not associated with the multiligand mixture.

The experimental methods that are used to study metal complexation by humic substances directly provide either none or, at best, one of the three terms in equation 3. The missing terms are always calculated from the experimental data and some stoichiometric assumptions about the system being studied. The most common assumptions involve the neglect or invocation of the existence of simple inorganic complexes (hydroxy and_car-bonato complexes) in the system under investigation. For example, K * is often calculated directly from experimental data as

K * = C " - M (4) [ M ] ( C L - C M + [M]) W

where C M and C L are the total stoichiometric concentrations of metal and ligand in the system under study and [M] is the concentration of free metal ion. In calculating £[ML,(bound)] as ( C M - [M]), the presence of inorganic complexes of the metal ion has been neglected. In calculating Σ [L/free)] as ( C L - C M + [M]), an average 1:1 metal-to-ligand stoichiometry has been assumed for the mixture of binding sites. It is also assumed that C L is known. Most of the remainder of this chapter wil l address the experimental determination of C L from metal-binding data.

Although an expression can be written for K * in equations 3 and 4 that formally resembles the conditional concentration quotient in equation 2 (Κ·*), Κ * is not a constant at a given p H and ionic strength. Rather, K * wil l decrease steadily as_the total metal-to-ligand ratio ( C M / C L ) increases. The functional nature of K * arises from preferential reactions of stronger ligands at low metal-to-ligand ratios and has been discussed by several investigators (1-11). Nevertheless, the variation of K* with the total metal-to-ligand ratio has often erroneously been cited as evidence for the existence of two binding sites in a humic substance, one reacting more favorably than the other with the metal ion. Average K* values are ultimately functions of ionic strength, p H , and the degree of saturation of the multiligand mixture with metal ion. This latter term is loosely reflected in the C M / C L ratio. Reported stability

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"constants" for metal-humic-substance complexation are not actually constant and should be viewed with skepticism.

In simple systems containing one metal ion and one ligand, K f * , Kf, and K | values can be interconverted, as described in the preceding section. In metal-multiligand mixtures, however, similar interconversions of K * , Kc, and Κ values are not practical at all. For example, to remove the p H dependence of K * values, it would be necessary to treat all pH-dependent side reactions of the metal ion and all components of the multiligand mixture quantitatively. Although such corrections are practical for metal-ion hydrolysis, there is not yet a rigorous treatment of the acid-base chemistry of humic substances (12). Even if the corrections could be made, the resulting Kc values would still be functions of ionic strength and the degree_of satu-ratiorurf the multiligand mixture with metal ion. The conversion of Kc values into Κ values could theoretically be accomplished by extrapolation to zero ionic strength of Kc values obtained at constant degree of saturation of the multiligand mixture with metal ion and variable ionic strength. The resulting Κ values would still be functions of the degree of saturation of the multiligand mixture with metal ion. The remaining functional dependence is a fundamental characteristic of mixtures, and it cannot be eliminated by any experimental method short of total fractionation of the mixture into pure compounds that could be studied separately.

Complexation Capacity: Definitions and Measurements Definition of Complexation Capacity. For a pure ligand reacting

with divalent or trivalent metal ions, even though complexes of higher stoi-chiometry (1:2, 1:3, etc.) may form at low levels of bound metal, 1:1 complexes predominate at higher levels of added metal. Thus, the complexation capacity of the ligand is usually about 1 mol of metal per mole of ligand. The important point is that complexation capacity is a compositional, rather than thermodynamic, parameter. The complexation capacity of citrate ion (Cit 3 - ) , for example, is about 1 mol of metal per mole of citrate, regardless of p H , ionic strength, nature of the metal, or the concentration of citrate ion used in the measurements.

Theoretically, the complexation capacity (CC) of a humic substance or other complex mixture is, to a good approximation, a weighted average of the complexation capacities of the individual ligands in the mixture:

2 (CCMweightL

2, [weight],

where (CC) f is the complexation capacity of the ith ligand in the mixture and [weight], is a weighting factor that reflects the relative abundance of

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that ligand in the multiligand mixture. The nature of the weighting factor depends on the dimensional units of C C , commonly given in milliequivalents per gram. If (CC) t values are also in milliequivalents per gram, then [weight]4

is the mass of the ith ligand in the mixture. If the mixture is not fractionated, C C wil l be an average constant from which total ligand concentrations (C L) can be computed for use in equilibrium expressions (equation 4). The metal-humic substance literature suggests that the complexation capacity of a humic substance varies considerably with almost every conceivable experimental variable: increasing at higher p H (13-18), decreasing at higher ionic strength (13, 16), increasing at higher humic-substance concentrations (13-15, 19, 20), and generally varying with the nature of the added metal ion (13, 14, 17, 21). The differences between these reported results and theoretical expectations must be resolved.

Major Misconceptions Concerning Complexation Capacities. Two fundamental misconceptions are responsible for much of the confusion over complexation capacities and their reported dependence on experimental conditions (13-21). First, the effects of experimental conditions on conditional concentration quotients (K*) are erroneously interpreted as modifications of the complexation capacity (CC) of the humic substance. Complexation capacity data are usually interpreted with no regard for the fact that K * values are affected by p H , ionic strength, and the nature of the reacting metal. It is simply easier to saturate ligands with metal at near-neutral p H , low ionic strength, and with a strongly binding metal such as C u 2 + than otherwise. This greater ease of formation of metal-humic substance complexes leads directly to apparently higher C C values under these optimum conditions. Second, the effect of simple dilution on the position of the equilibrium in reactions of the type M + L , M L , is erroneously interpreted as a variation of C C with humic-substance concentration. Because metal complexation equilibria shift toward free metal and ligand with dilution, it is more difficult (at a constant C M / C L ratio) to saturate a dilute ligand mixture than a concentrated ligand mixture, which gives rise to the illusion that the C C of a humic substance decreases with dilution. These apparent effects on C C values wil l be demonstrated in a later section of the chapter.

A potential source of confusion in reported C C values for metal-humic substance complexation is dimensional units. A typical humic substance has a carboxylic acid content of about 5 meq/g and contains about 50% carbon. Suppose that the C C of that humic substance is also 5 meq/g for divalent and trivalent metal ions. Then, depending on the choice of dimensional units and the charge of the metal ion, C C might be reported as 10 meq/g of C, 5.0 mmol/g of C, 3.3 mmol/g of C, 5 meq/g, 2.5 mmol/g, or 1.67 mmol/g. A l l of these dimensional units can be found in the literature on metal-humic substance complexation, as well as much poorer choices

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such as milligrams per gram or milligrams per gram of C. This potentially confusing problem is not particularly serious and, if recognized, it is easily corrected.

If C L values in K * expressions such as equation 4 are obtained from C C values, C L is actually a binding-site concentration, where a binding site is defined as a group of one or more donor atoms in the humic substance that can bind a single metal ion. It is implicit in this definition that all metal-ligand complexes are of 1:1 stoichiometry (one metal ion per binding site). If a total ligand concentration is defined in this manner, metal complexation data should not be interpreted in terms of a mathematical model that assumes the occurrence of complexes of greater than 1:1 stoichiometry.

Simulation of Complexation Capacity Titrations. The integrated effects of ionic strength, p H , nature of the added metal ion, and ligand concentration on apparent C C values can be demonstrated by computer simulations of C C titrations for a system of one metal and one ligand. The additional inherent complications that are due to the multiligand nature of humic substances could be demonstrated only by analogous computer simulations of multiligand mixtures. In this chapter, complexation capacity titrations have been simulated for citrate ion, with C u 2 + and C a 2 + as titrants at several p H values (4, 5 , 6, 7), ionic strengths (0, 0 .1) , and total ligand concentrations [log(CL) = - 4 , - 5 , - 6 ] . Thermodynamic data were obtained from a recent tabulation (22) and are given in Table I. Experimental parameters for 1 0 simulated titrations are given in Table II. In all cases, titrations were simulated over a C M / C L range of 0 . 0 - 3 . 0 . The choice of an upper C M / ^ L r a t i ° of 3 . 0 was based on this value as typical of most complexation

Table I. Typical Thermodynamic Data for Metal-Citrate Complexation Reactions at Zero Ionic Strength and 298 Κ Reaction log Keq

H + + Cit3" <± HCit2" 6.40 2H + + Cit3" ?± H2Cit" 11.16 3H + + Cit3" <̂ H3Cit° 14.29 Cu 2 + + H 2 0 « ± C u O H + + H + -7.50 Cu 2 + + 2H20 «± Cu(OH)2° + 2H + -16.20 Cu 2 + + 4H20 +± Cu(OH)4

2" + 4H + -39.60 2Cu 2 + + 2H20 τ± Cu2(OH)2

2 + + 2H + -17.60 Cu 2 + + Cit3" CuCif 7.20 Cu 2 + + H + + Cit3" +± CuHCit0 10.70 Cu 2 + + 2H + + C i t ^ C u H z C i t * 13.90 Cu 2 + + H 2 0 + Cit3" ?± CuOHCit2- + H + 2.40 2Cu 2 + + 2Cit3" i± Cu2(Cit)2

2" 16.30 Ca 2 + + H 2 0 ? ± C a O H + + H + -12.85 Ca 2 + + Cit3" +± CaCit" 4.70 Ca 2 + + 1H + + Cit3- ?± CaHCit0 9.50 Ca 2 + + 2H + + Cit 3 +±CaH 2 Cit + 12.30

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Table U . Experimental Parameters for Simulated Complexation Capacity Titrations of Citrate Ion

Curve0 Symbol* Metal pH I logCt 1 H Cu 7 0 2 Δ Cu 5 0 3 · Ca 7 0 4 + Cu 5 0 5 x Cu 5 0.1 6 V Ca 7 0 7 • Ca 7 0.1 8 Ο Ca 7 0 9 Φ Ca 4 0 10 ο Cu 4 0

-4 -5 -4 -6 -6 -5 -5 -6 -4 -6

"Curve numbers are used in Figures 1-3. bThese symbols are used in Figure 3.

capacity experiments. In most such studies, the bound-metal concentration is calculated as C M - [M], which becomes experimentally indistinguishable from C M at higher excess CM values.

The simulated titration data sets were analyzed by three common graphical methods that are used to obtain C C values. In the first method, [M] is plotted versus C M , with the expectation that the resulting curve wil l have a slope of 1:1 when the ligand is saturated. The C C of the ligand can be obtained by extrapolation of the h igh-C M data to an X-axis intercept. In the second method, the bound-metal concentration [ML] (assuming that [ML] = C M - [M]) is plotted versus C M , with the expectation that [ML] will approach a constant limiting value (the CC) at high C M values. The C C is estimated from such plots by fitting data to an empirical equation of the form: Y = CC(1 - exp (fcX)). The second approach generally yields higher estimates of C C than the first approach. In the third method, [ML] is plotted as a function of p M , where p M = -log[M]. This type of plot is characteristically S-shaped, with an inflection point at p M = log K * and

For graphical convenience in presenting the results of simulated titrations over a wide range of ligand concentrations, the [M], [ML] , and C M

data were normalized to C L . In these simulations, where the C L value can be expressed in molar units, the X and Y variables have dimensional units of moles of metal per mole of ligand. Similar normalizations can be done for humic substances if C L is used in mass units (e.g., grams per liter). In this case, the X and Y variables would have dimensional units of moles of metal per gram of humic substance. The results of 10 typical simulations are shown in Figures 1-3.

Figure 1 illustrates what is probably the most common graphical approach toward estimation of complexation capacities. Curve 1 ( C u 2 + , p H 7, ionic strength (I) = 0, log(C L ) = -4) typifies extremely favorable metal-ligand complexation (high K,*). Below a C M / C L ratio of 1.0, very little

[ M L ] / C L = C C / 2 .

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Figure 1. Simuhted complexation capacity titration of citrate ion: free metal versus total metal. See Table II for explanation of curves 1-10.

[M] is present at equilibrium; however, at higher C M / C L ratios, [ M ] / C L

increases linearly (1:1 slope) with increasing C M / C L . Extrapolation of the high C M / C L data to an X-axis intercept wil l accurately estimate C C from this titration curve. At the opposite extreme is curve 10 ( C u 2 + , p H 4, I = 0, log(C J = -6). In this case, there is no obvious indication from the graph that C u 2 + is being incorporated into complexes at all. The other curves (2-9) are intermediate in behavior. Thus, the common extrapolation to an X-axis intercept wil l significantly underestimate C C in almost every case.

A simple transform of Figure 1 is presented in Figure 2. Instead of plotting [ M ] / C L as the dependent variable, its stoichiometric complement [ M L ] / C L is used. The resulting figure more clearly illustrates the effects of p H , ionic strength, nature of the added metal, and ligand concentration on

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Figure 2. Simulated complexation capacity titration of citrate ion: bound metal versus total metal. See Table II for exphnation of curves 1 -10.

C C estimates. In Figure 2, curve 1 initially rises steeply (1:1 slope) until the ligand becomes saturated with added metal (at C M / C L = 1.0); then it levels off at [ M L ] / C L = 1.0. The C C of the sample can thus be easily determined from curve 1. Curve 10 indicates the weakest metal binding, but at least Figure 2 more readily demonstrates that metal binding is taking place in that titration (compare with curve 10 in Figure 1). Curves 2-9 are again intermediate in behavior. It is doubtful that the correct C C value could be obtained by fitting data to the empirical equation: [ M L ] / C L = CC(1 -exp (bCM/CL)) for curves 4-10. Such an approach would work for curve 1 and possibly for curves 2-3.

Figures 1 and 2 present basically the same information, but Figure 2 more effectively illustrates the effects that are being evaluated in this sim-

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1.0 n

0.8

0.6

0.4 H

0.2

0.0 12.0 10.0

Figure 3. Simuhted complexation capacity titration of citrate ion: bound metal versus hg (free metal). See Table II for explanation of curves 1-10.

ulation. Typical effects of individual experimental parameters at otherwise-constant conditions on experimental estimates of C C can be observed in these figures by comparing the following curves. The effect of ρ H is exemplified by comparison of curves 4 and 10 and of curves 3 and 9. The effect of C L is particularly evident in curves 3, 6, and 8 and in curves 2 and 4. Ionic-strength effects, which are smaller but significant, are seen in curves 4 and 5 and in curves 6 and 7. The effect of the nature of the metal ion is seen in curves 1 and 3.

One of these effects, ligand concentration (C L ), is an artifact that results from the use of C M rather than [M] as the independent variable in Figures 1 and 2. The extent to which a ligand is saturated with a metal ion at equilibrium is a direct function of [M], not of C M . For example, in the

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generalized reaction M 4- L M L , [ M L ] / C L i s given by the expression [ M L ] / C L = K[M]/(1 + K[M]), where Κ is a conditional concentration quotient. If the simulated titration data are plotted as [ M L ] / C L versus p M , the curves in Figure 3 are obtained. Some of the 10 curves exactly overlap one another in this figure, so symbols were used rather than smooth lines to distinguish between curves. Curves 3, 6, and 8 and curves 2 and 4 are perfectly overlapped, although the maximum achieved level of metal binding differs from one curve to another. For these overlapping curves, all parameters other than C L were constant. The observed overlap is not evident in Figures 1 and 2, in which CM was used as the independent variable. Recalling that the inflection point in each curve in Figure 3 corresponds to p M = log Kf and [ M L ] / C L = C C / 2 , it is evident that the simulated titration curves, which appeared to indicate different C C values in Figures 1 and 2, actually indicate different log values.

These simulated titrations demonstrate the ambiguities that can arise in interpreting complexation capacity titration experiments, even in a one-ligand system. Clearly, the effect of C L on C C estimation is an artifact that is easily eliminated by using plots such as Figure 3 for analysis of experimental data. The remaining effects alter the energetics of the complexation (Κι*) and thus make it difficult to experimentally realize the complexation capacity of a ligand under less-than-optimal experimental conditions. As a general conclusion, these simulated titrations suggest that higher levels of saturation of ligand at a given C M / C L ratio can be attained in experimental studies that are conducted at near-neutral p H , low ionic strength, with a strongly binding metal ion such as C u 2 + , and at high ligand concentrations.

Experimental Limitations in Complexation-Capacity Measurements. From an experimental perspective, it is extremely difficult to actually saturate a humic substance with an added metal ion, even under optimal conditions. The complex mixture of compounds in humic substances includes molecules with strong, average, and weak Kf values. Accordingly, not all binding sites are equally saturated with M at a given p M . A binding site with a log K, of 5.0 wil l be about 90% saturated with M when log[M] = -4.0 and about 99% saturated when log[M] = -3.0, but a weaker binding site with a log K{ of 4.0 will only be half-saturated with M when log[M] = -4.0 and about 90% saturated when log[M] = -3.0.

Given the relative abundance of carboxylic acid functional groups and the very low concentrations of N - and S-containing ligands in humic substances, most metal-binding sites probably are relatively weak (as are proton-binding sites). Such binding sites are not easily saturated with metal ions in dilute aqueous solutions such as natural waters. Attempts to measure complexation capacities of unconcentrated humic substances directly in a water sample will always underestimate the true C C of the sample. For example, suppose that a dissolved humic substance in a lake water contains 10 5 M

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of a ligand with a log of 4.0. A C M / C L of at least 10:1 is required just to half-saturate the binding site, and at least a 100-fold excess of metal ion is required to realize 90% of the complexation capacity of that ligand. In the presence of such large excesses of added metal ion, [M] ~ C M , and changes in [ML] with increasing C M are almost impossible to determine accurately.

If the first two graphical methods of data analysis are used, the illusion that C C values change with experimental conditions is strengthened by the heterogeneity of binding sites in humic substances. Kf does not change as C M / C L is increased in the single-ligand system used in the computer simulations. If a humic substance is titrated with a metal ion, however, the titration of very strong ligands at low C M / C L values gradually shifts to a titration of much weaker ligands at high C M / C L values. This change in the nature of reacting ligands with C M / C L ratio causes metal-binding curves such as those in Figure 2 to resemble curve 1 at low C M / C L and curve 10 at high C M / C L . The resulting initial steepness and later flatness of the binding curves visually enhance the illusion that the C C of a relatively strong ligand has been reached. To avoid this pitfall, metal-humic substance C C titration data should always be examined graphically, according to the approach taken in Figure 3. The resulting plots probably wil l not indicate more than half-saturation of the humic substance.

The optimum conditions for saturating a humic substance with metal ion (a relatively large excess of metal ion in a rather concentrated solution of the humic substance) tend to cause metal-humic substance flocculation to occur. Flocculation results in considerable ambiguity in C C estimates. Some consideration should be given to using total acidity as a surrogate parameter for the complexation capacity of a humic substance. Even though total acidity and C C are probably not equal, total acidity provides an upper limit for C C that can be measured by well-established methods (12).

Summary and Conclusions The use of thermodynamic models to calculate the effect of humic substances on metal speciation requires that the complexation capacity (CC) of the humic substance be determined. If the C C of a humic substance, like that of a single ligand, is viewed as a compositional rather than thermodynamic property, then the conventional approaches toward experimental measurements and calculations of complexation capacities need to be reexamined. I propose that the C C of a humic substance is approximately equivalent to its total exchangeable acidity, and that the extent to which this C C can be realized in experimental measurements is strongly a function of p H , ionic strength, nature of the metal, and the concentration of humic substances used in the measurement. The first three parameters affect conditional concentration quotients for metal complexation, and the last parameter is simply an example of Le Chateliers principle in metal-ligand complexation reactions.

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The results of modeling studies of the effects of p H , ionic strength, and the nature of the metal ion in the complex could be more properly interpreted if the concept of C C as a compositional, rather than thermodynamic, parameter is accepted.

The current state of the art in mathematical modeling of metal-humic substance complexation is still somewhat unsophisticated. No models can quantitatively describe even the effects of p H and ionic strength on the extent of complexation of a single metal ion. Multimetal binding cannot be modeled at all. These modeling deficiencies, together with the limitations on experimental determinations of complexation capacities, present a substantial challenge to those working in this area of environmental chemistry.

Acknowledgments Although the research described in this chapter has been funded wholly or in part by the United States Environmental Protection Agency through Cooperative Agreement No. CR813471-01 to Georgia Institute of Technology, it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.

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stances: Volume 3—Interactions with Metals, Minerals, and Organic Chemicals; Swift, R.; Hayes, M.; MacCarthy, P.; Malcolm, R., Eds.; Wiley: Chichester, England, 1988; in press.

2. Fish, W.; Dzombak, D. Α.; Morel, F. M. M. Environ. Sci. Technol. 1986, 20, 676-683.

3. Sposito, G. CRC Crit. Rev. Environ. Control 1986, 16, 193-229. 4. Turner, D. R.; Varney, M. S.; Whitfield, M.; Mantoura, R. F. C.; Riley, J. P.

Geochim. Cosmochim. Acta 1986, 50, 289-297. 5. Fish, W.; Morel, F. M. M. Can. J. Chem. 1985, 63, 1185-1193. 6. Cabaniss, S. E.; Shuman, M. S.; Collins, B. J. In Complexation of Trace Metals

in Natural Waters; Kramer, C. J. M.; Duinker, J. C., Eds.; Junk: The Hague, 1984; pp 165-179.

7. Dempsey, B. A.; O'Melia, C. R. In Aquatic and Terrestrial Humic Materials; Christman, R. F.; Gjessing, Ε. T., Eds.; Ann Arbor Science: Ann Arbor, 1983; pp 239-273.

8. Perdue, E. M.; Lytle, C. R. In Aquatic and Terrestrial Humic Materials; Christman, R. F.; Gjessing, Ε. T., Eds.; Ann Arbor Science: Ann Arbor, 1983; pp 295-313.

9. Perdue, Ε. M.; Lytle, C. R. Environ. Sci. Technol. 1983, 17, 654-660. 10. Gamble, D. S.; Underdown, A. W.; Langford, C. H. Anal. Chem. 1980, 52,

1901-1908. 11. MacCarthy, P.; Smith, G. C. In Chemical Modeling in Aqueous Systems; Jenne,

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12. Perdue, E. M. In Humic Substances in Soil, Sediment, and Water—Geochemistry, Isolation, and Characterization; Aiken, G. R.; McKnight, D. M.; Wershaw, R. L.; MacCarthy, P.; Eds.; Wiley-Interscience: New York, 1985; pp 493-526.

13. Langford, C. H.; Gamble, D. S.; Underdown, A. W.; Lee, S. In Aquatic and Terrestrial Humic Materials; Christman, R. F.; Gjessing, E. T., Eds.; Ann Arbor Science: Ann Arbor, 1983; pp 219-237.

14. Weber, J. H. In Aquatic and Terrestrial Humic Materials; Christman, R. F.; Gjessing, E. T., Eds.; Ann Arbor Science: Ann Arbor, 1983; pp 315-331.

15. Lytle, C. R. Ph.D. Thesis, Portland State University, 1982. 16. Gamble, D. S.; Langford, C. H.; Underdown, A. W. Org. Geochem. 1985, 8,

35-39. 17. Campbell, P. G. C.; Bisson, M . ; Gagné, R.; Tessler, A. Anal. Chem. 1977, 49,

2358-2362. 18. Chau, Y. K.; Gachter, R.; Lum-Shue-Chan, K. J. Fish. Res. Board Can. 1974,

31, 1515-1519. 19. Giesy, J. P.; Alberts, J. J.; Evans, D. W. Environ. Toxicol. Chem. 1986, 5,

139-154. 20. Perdue, Ε. M.; Lytle, C. R. In Mineral Exploration: Biological Systems and

Organic Matter, Rubey Volume V; Carlisle, D.; Berry, W. L.; Kaplan, I. Α.; Watterson, J., Eds.; Prentice-Hall: Englewood Cliffs, 1986; pp 428-444.

21. Tuschall, J. R.; Brezonik, P. L. In Aquatic and Terrestrial Humic Materials; Christman, R. F.; Gjessing, Ε. T., Eds.; Ann Arbor Science: Ann Arbor, 1983; pp 275-294.

22. Morel, F. M. M. Principles of Aquatic Chemistry; Wiley-Interscience: New York, 1983; pp 242-249.

RECEIVED for review July 24, 1987. ACCEPTED for publication February 29, 1988.

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