Model VI

Applied Geochemistry Applied Geochemistry 22 (2007) 1624–1635 www.elsevier.com/locate/apgeochem

Modelling the interactions of Hg(II) and methylmercury with humic substances using WHAM/Model VI E. Tipping

*

Centre for Ecology and Hydrology Lancaster, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster LA1 4AP, United Kingdom Available online 20 March 2007

Abstract WHAM, incorporating Humic Ion Binding Model VI, was used to analyse published data describing the binding of Hg(II) and methylmercury (CH3Hg) by isolated humic substances. For Hg(II), the data covered wide ranges of pH and levels of metal binding, whereas for CH3Hg the range of metal binding was relatively narrow. Data were fitted by adjustment of a single model parameter, log KMA, the intrinsic equilibrium constant characterising, in the standard version of the model, the binding of metal ions and their first hydrolysis products to humic carboxylic acid groups. Other model parameters, including those characterising the tendency of metal ions to interact with ‘‘softer’’ ligand atoms (N and S), were held at their default values. The importance of the first hydrolysis products in binding was considered, and also the possible influence of competition by residual Fe(III), bound to the humic matter. Of the 11 data sets for Hg(II), eight gave results reasonably consistent with one another, and with the previously-estimated default values of log KMA. There was no consistent indication that assuming the presence or absence of competing Fe(III) gave superior fits; neither did the inclusion or exclusion of HgOH+ binding provide consistently better results. The experimental data and the model show that apparent binding strength towards Hg(II) is highly dependent upon the metal loading, reflecting the high degree of heterogeneity in binding sites for the metal. Of the 24 metals to which WHAM/Model VI has now been applied, Hg(II) shows the strongest binding to humic substances, and the greatest range in binding affinities. The relatively few data characterising the interactions of CH3Hg with humic substances can be approximately fitted with the model. The results show that CH3Hg binding is appreciably weaker than that of Hg(II). New default values of log KMA are 3.6 for Hg(II)–HA binding, 3.1 for Hg(II)–FA and 0.3 for CH3Hg–HA and CH3–FA.  2007 Elsevier Ltd. All rights reserved.

1. Introduction Mercury is a significant global pollutant, with deleterious effects on both natural ecosystems and humans. In soils and waters, the major form of the metal is Hg(II), but bioaccumulation depends

*

Tel.: +44 1524595866. E-mail address: [email protected]

upon the formation and uptake of methylmercury, CH3Hg. The strong interactions of both forms of the metal with natural organic matter are considered to exert important controls on Hg biogeochemistry (Schuster, 1991; Loux, 1998; Morel et al., 1998; Ravichandran, 2004), and quantitative description of the interactions is needed in order to predict Hg behaviour. This might be achieved by parameterising comprehensive speciation models such as WHAM (Tipping, 1994) and NIC(C)A (Kinniburgh

0883-2927/$ - see front matter  2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.apgeochem.2007.03.021

E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

et al., 1999) with data obtained from laboratory studies on natural organic matter isolates. A number of authors have reported data describing Hg binding by fulvic and humic acids. In early studies, the Hg concentrations used tended to be far higher than those in the natural environment (Cheam and Gamble, 1974; Kerndorff and Schnitzer, 1980), and consequently the modelling of binding by humic matter was restricted to conditions under which Ocontaining ligands dominate. More recently, techniques have been developed that allow more realistic metal loadings to be used with both Hg(II) (Benoit et al., 2001; Haitzer et al., 2002, 2003; Khwaja et al., 2006) and CH3Hg (Hintelmann et al., 1995, 1997; Amirbahman et al., 2002); binding under these conditions is thought to involve reduced S ligands of the organic matter (Loux, 1998; Ravichandran, 2004). The newer data mean that we are now in a position to quantify the interactions more comprehensively, and the present paper reports the application of WHAM incorporating Humic Ion Binding Model VI (Tipping, 1998) to the available binding data for isolated fulvic and humic acids, and similar fractions. In the following text, ‘‘Hg(II)’’ is used in a general way, to indicate all forms, or any unspecified form(s), of divalent Hg, and ‘‘CH3Hg’’ generally for methylmercury. Terms for sub-divisions (e.g. [Hg]filt for filterable Hg concentration) or individual species (e.g. CH3Hg+) are used when more precision is required. The variable m (mol metal bound per g humic matter) – sometimes referred to as the metal loading – is used to characterise binding. The abbreviations FA and HA are used for fulvic acid and humic acid, respectively. 2. The model The calculations were performed using WHAM/ Model VI, which combines Humic Ion Binding Model VI (Tipping, 1998) with an inorganic speciation code (Tipping, 1994). 2.1. Humic Ion-Binding Model VI (Tipping, 1998, 2002) Proton dissociation is represented by postulating eight groups with different acid strengths, the reactions being characterised by intrinsic equilibrium constants, the negative logarithms of which are denoted by pK1 – pK8. The four most strongly-acid groups (groups 1–4) are referred to as type A groups, and consist mainly of carboxylic acid

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groups, while the remaining four groups (type B) represent weaker acids, such as phenolic acids. The eight pKi values are expressed in terms of four constants; pKA and pKB are the average pK values of the two types of group, and DpKA and DpKB are measures of the spread of the individual pKi values around the means. Each type A group is assigned an abundance of nA/4 mol g1 humic matter, and each type B group an abundance of nA/ 8 mol g1. Thus, within a type, each group is present in equal amounts, and there are half as many type B groups as type A groups. The imposed regularity of the groups facilitates the formulation of bidentate and tridentate sites for metals. Metal binding at the type A and B sites is described with average intrinsic equilibrium constants (KMA, KMB) and associated ‘‘spread factors’’ DLKA1 and DLKB1. The occurrence of bidentate and tridentate sites is calculated probabilistically. Additional binding site heterogeneity is generated by a parameter, DLK2, that characterises the tendency of the metal to interact with ‘‘softer’’ ligand atoms. Thus, 9% of the bidentate sites have the logarithms of their binding constants increased by DLK2, while 0.9% have increases of 2 DLK2. For the tridentate sites, the respective increases are 1.5 DLK2 and 3 DLK2. This feature (DLK2) is extremely important in modelling the binding of Hg. In the standard model, all metal cations (e.g. Al3+, Cu2+, Hg2+) and their first hydrolysis products (AlOH2+, CuOH+, HgOH+) compete with each other, and with protons, for binding. The combination of multi-denticity and the increased binding strength of some sites, due to DLK2, generates many binding sites with a wide range of affinities. The most abundant (monodentate) sites are the weakest binders, while the least abundant (tridentate sites enhanced by 3 DLK2) are the strongest. The intrinsic equilibrium constants are modified by empirical electrostatic terms, that take into account the attractive or repulsive interactions between ions and the charged macromolecule. A Donnan sub-model is used to compute counterion accumulation in the diffuse zone around the molecule; each counterion can be assigned a selectivity coefficient (Ksel), so that accumulation can be made to depend on more than just the counterion charge; for example, Ca2+ can be favoured over Mg2+. 2.2. Data fitting With proton binding described using intrinsic equilibrium constants, site densities, and electro-

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E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

Table 1 Model VI parameters used in the present study; see Section 2.2 Parameter

HA

FA

Comments

M r (nm) nA (mol g1)

15000 1.72 3.3 · 103

1500 0.80 4.8 · 103

nB (mol g1) pKA

1.65 · 103 4.1

2.4 · 103 3.2

pKB

8.8

9.4

DpKA DpKB P fprB

2.1 3.6 330 0.50

3.3 4.9 115 0.42

fprT

0.065

0.03

DLK1

2.8

2.8

Molecular weight Radius Number of type A groups = 0.5 · nA Median proton dissociation constant for type A groups Median proton dissociation constant for type B groups Range factor for pKA Range factor for pKB Electrostatic parameter Proximity factor for bidentate sites Proximity factor for tridentate sites Range factor for metal binding

log KMA Mg Al Ca Fe(III) Cu Zn Hg CH3Hg

0.7 2.6 0.7 2.4 2.0 1.5 3.0 (3.0)

1.1 2.5 1.3 2.6 2.1 1.6 3.5 (3.0)

Intrinsic equilibrium constants for monodentate binding at type A sites. Values for type B sites are obtained from the relation: log KMB = 3.39 log KMA – 1.15 (r2 = 0.80)

DLK2 Mg Al Ca Fe(III) Cu Zn Hg MeHg

0.12 0.46 0.0 2.20 2.34 1.28 5.1 3.6

0.12 0.46 0.0 2.20 2.34 1.28 5.1 3.6

Strong binding site term, obtained from the relation: DLK2 = 0.55 log K NH3 (r2 = 0.66), where K NH3 is the equilibrium constant for complexation with NH3

static parameters (Table 1), the maximum number of parameters that can be optimised to describe metal binding is six (KMA, KMB, DLKA1, DLKB1, DLK2, Ksel). In practice however, this number can be substantially reduced. Thus, Tipping (1998) described the setting of a single value DLK1, instead of specifying both DLKA1 and DLKB1 for each metal, and the estimation of DLK2 by correlation with the logarithm of the equilibrium constant for complex formation with NH3 ðK NH3 Þ. (Note that the use of this correlation does not mean that the stronger binding associated with softer ligand atoms

is attributed simply to monodentate interactions with an N-containing ligand.) For dilute systems, Ksel can be set to unity. Finally, KMA and KMB are strongly correlated. Therefore, the fitting of a new data set for metal binding can usually be achieved by adjusting only KMA. Table 1 shows parameters for metals relevant to the present work (Tipping, 1998; Tipping et al., 2002). They include starting default values for Hg, estimated for HA by fitting the multiple metal data set of Kerndorff and Schnitzer (1980), as described by Tipping (1998), and for FA from linear free-energy relationships (Tipping, 2002). In the case of CH3Hg, the default values of 3.0 are approximations based on equilibrium constants for binding to simple carboxylic acids (Martell and Smith, 1977). In attempting to fit individual data sets for Hg and MeHg, the main approach was to apply the model in its standard form. The value of DLK2 for Hg(II) was set to 5.1, by correlation with the published value for log K NH3 (Martell and Hancock, 1996). For CH3Hg, the value of log K NH3 was estimated to be 6.2, using the equation of Martell and Hancock (1996) in which electrostatic, covalent and steric contributions to formation constants are combined. Then DLK2 was estimated by correlation to be 3.6. Both values of DLK2 are high, indicating that the metals are favoured by the low-abundance ‘‘strong’’ sites, associated, according to the model, with N groups, or more generally with softer ligand atoms. In a few cases, adjustment of DLK2 was also made. Both Hg2+ and CH3Hg+ are subject to hydrolysis even in acid solutions (see below), and therefore the model’s assumption of equally strong binding by the first hydrolysis product (see above) is significant. Therefore, fittings were carried out with and without the assumption of binding by HgOH+ and CH3HgOH. The model permits all metals to bind at all sites, and so competition effects may be seen, and in the case of experiments with very low concentrations of Hg, even small amounts of ‘‘contaminating’’ metals, notably Al and Fe(III), may be significant. It was assumed that most samples would be free of Al, since this would be released under acid conditions during isolation. However Fe(III) is likely to be present in all samples. An average Fe(III) content of 105 mol g1 was found for 15 dissolved organic matter samples isolated by Aiken and co-workers (pers. comm.). Varshal et al. (1998) used a sample of HS containing 0.2% ash, which could represent

E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

2 · 105 mol Fe(III) g1 if all the ash were present as Fe oxide. Tipping et al. (2002) treated a sample of HA extensively with acid and achieved an Fe content of 3.6 · 106 mol g1. Taking all these results together, a typical Fe(III) content of 105 mol g1 was adopted to explore the possible effects of competition on Hg binding. 2.3. Inorganic speciation The humic ion-binding model is combined with an inorganic speciation model, the species list and constants for which were given by Tipping (1994). The inorganic reactions in this database are Table 2 Constants for reactions with inorganic ligands and acetate used in the modelling calculations Reaction

Log K (25 C)

DH kcal mol1

Hg2+ + OH = HgOH+ Hg2+ + 2OH = Hg(OH)2 Hg2þ þ 3OH ¼ HgðOHÞ 3 Hg2+ + Cl = HgCl+ 2+  Hg + 2Cl = HgCl2 Hg2þ þ 3Cl ¼ HgCl 3 Hg2þ þ 4Cl ¼ HgCl2 4 Hg2þ þ SO2 4 ¼ HgSO4 +  MeHg + OH = MeHgOH MeHg+ + Cl = MeHgCl  MeHgþ þ HPO2 4 ¼ MeHgHPO4 +  MeHg + Ac = MeHgAc

10.6 21.83 20.9 7.21 13.98 15.06 15.42 2.0 9.37 5.25 5.48 2.98

5.8 16.2 20.0 4.8 12.8 15.0 14.9 (0.0) (0.0) (0.0) (0.0) (0.0)

Log K values refer to zero ionic strength. Values for Hg are from the compilation of Tipping (1994), for MeHg from Amirbahman et al. (2002). Values in brackets indicate that no data are available.

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restricted to monomeric complexes of metals. Ionic strength effects on the inorganic reactions are taken into account using the extended Debye–Hu¨ckel equation. Temperature effects on reactions between inorganic species are taken into account using published or estimated enthalpy data, but in the absence of experimental information, reactions involving humic substances are assumed to be independent of temperature. The thermodynamic constants for Hg(II) used in the present work (Table 2), compiled by Tipping (1994) are all very close to the recommended or provisional values given by Powell et al. (2004). Complexation by carbonate species, which is very weak, was not considered. Constants for CH3Hg were taken from Amirbahman et al. (2002); they include values for buffer ligands used in binding studies with HA. The main species in halide-free media are the free ions and the hydrolysis products (HgOH+, CH3HgOH, etc.). When Cl is present, its complexes with the metals can predominate. For some data sets, inorganic speciation calculations had been performed by the authors to estimate concentrations of metal species; in such cases, the values provided by the authors were used. 3. Results Papers are considered that report sufficient experimental data to deduce amounts of Hg(II) or CH3Hg bound to isolated HA, FA, or similar fractions, together with corresponding concentrations of Hg2+ or CH3Hg+, or of total metal not bound to humic matter. The data sets are summarised in

Table 3 Summary of data sets used for model fitting Form of Hg

Authors

Humic material

Medium

pH

Log [Mz+]a

Log m

Hg(II)

Cheam and Gamble (1974) Kerndorff and Schnitzer (1980) Yin et al. (1997) Varshal et al. (1998) Melamed et al. (2000) Benoit et al. (2001) Haitzer et al. (2002) Haitzer et al. (2003) Cruz-Guzma´n et al. (2003) Lamborg et al. (2003) Khwaja et al. (2006)

Soil FA Soil HA Soil HA Soil HA Aldrich HA Aquatic DOMb fractions Hydrophobic DOMb Hydrophobic DOMb Histosol HA Fluka HA Peat and wetland HA

0.1 M NaNO3 0.015 M NaNO3 0.1 M NaNO3 0.001 M NaNO3 0.01 M KCl 0.01 M NaCl 0.1 M NaClO4 0.1 M NaClO4 0.001 M HNO3 0.025 M Phosphate 0.167 M Ca(NO3)2

3.0–4.0 2.4–5.8 4.0–6.0 1.4–4.8 2.7–3.6 4.0–6.0 4.9–7.0 4.0–7.3 3.0 7.5 3.0–5.0

4.9–6.3 3.7–19.6 7.1–12.8 2.8–11.9 14.8–15.6 18.3–19.2 10.2–27.0 24.3–29.6 2.7–10.4 22.0 28.2–34.0

2.5–2.7 2.6–5.0 4.8–6.5 2.7–4.3 4.9–5.6 3.7–5.5 2.9–7.0 6.3 2.7–3.7 5.9 6.4–8.3

CH3Hg

Hintelmann et al. (1995, 1997) Amirbahman et al. (2002)

Aquatic FA and HA Aquatic and peat HA

0.0001 M NaClO4 Various buffers

7.0 3.5–9.2

12.0–15.0 9.9–15.9

9.2–12.2 6.1–7.4

a b

Free ion concentrations in mol l1; either reported values, or calculated from total unbound concentrations. Dissolved organic matter.

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E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

Table 3. Some other studies (Strohal and Huljev, 1971; Mantoura et al., 1978; Thanabalasingam and Pickering, 1985; Rocha et al., 1998) provide information on binding, including stability constants, but insufficient information for modelling. 3.1. Hg(II) binding Cheam and Gamble (1974) studied the interactions of Hg(II) with FA at pH 3 and 4 in 0.1 M NaNO3 solution. The amounts of bound Hg were high, greater than 103 mol gFA1. Full data were not reported, but from this paper and an earlier publication by one of the authors (Cheam, 1973), approximate experimental details can be deduced. In the simple binding model used by the authors for data interpretation, the following conditional stability constant was defined; K¼

½Cx ½M½FA

ð1Þ

where [Cx] is the molar concentration of bound metal, [M] is the concentration of unbound metal, and [FA] is the concentration of bidentate chelating sites not occupied by bound metal; the bidentate site content of FA was estimated to be 3 · 103 mol g1. WHAM/Model VI was used to calculate values of K, for different assumptions about the presence of Fe(III) in the sample, and whether or not HgOH+ is able to bind. The presence or absence of Fe(III) had no effect. With HgOH+ allowed to bind, and with log KMA = 3.3, K was found to be 4.9 at pH 3 and 5.1 at pH 4, in exact agreement with the values reported by Cheam and Gamble (1974). Without binding of HgOH+, a value of log KMA of 3.4 gave the best result. Kerndorff and Schnitzer (1980) determined the simultaneous adsorption of 11 metals, including Hg(II), by HA, in the pH range 2–6 with 0.015 M NaNO3 as the background electrolyte. The data were analysed with Humic Ion Binding Model VI by Tipping (1998), by setting the binding parameters for all the metals other than Hg(II) to their default values, and adjusting the KMA for Hg(II) to obtain the overall best fit for all the metals (i.e., not Hg(II) alone). The best value of log KMA was 3.5. Observed and fitted amounts of sorbed metal were plotted by Tipping (1998). Yin et al. (1997) worked with HA isolated from soil by a simple extraction with NaOH. Mercury binding was determined using an iodide selective electrode, with 0.1 M NaNO3 as the background

electrolyte. The results (55 data points) were presented as binding isotherms at pH 4, 5 and 6. Application of WHAM/Model VI was performed first by assuming the HA to be free of both Al and Fe(III), then assuming the presence of 105 mol g1 of each metal, then 104 mol g1 of each metal; the high contents of Al and Fe(III) might be expected since extensive ‘‘clean up’’ of the HA sample was not performed. With DLK2 set to the default value of 5.1, poor fits were obtained in all cases, with rootmean-square deviations (RMSD) in log [Hg]free of about 1.0 (log KMA  1.5). Better fits (RMSD  0.2) could be obtained by making DLK2 smaller; the best fit was for Al and Fe(III) contents of 104 mol g1, DLK2 = 1.3 and log KMA = 2.6. Thus, the experimental data suggest much weaker binding than expected from the default Model VI parameters. Varshal et al. (1998) measured Hg(II) binding to low-ash soil HA by filtrations of acid suspensions, in 1 mM NaNO3. High concentrations of Hg (>104 M) were used, giving relatively high loadings of the organic matter. The Hg(II) passing the filter was assumed to be solely in inorganic forms. In one set of experiments, binding was studied as a function of pH (range 1–5), while in a second set, binding at different Hg concentrations, at a constant pH of 3, was determined. For modelling, it was assumed that Al was absent from the HA, and WHAM/Model VI was fitted for the following 4 cases; (a) no Fe(III), HgOH+ binds; (b) no Fe(III), HgOH+ does not bind; (c) 105 mol g1 Fe(III), HgOH+ binds; (d) 105 mol g1 Fe(III), HgOH+ does not bind. The goodness of fit was about the same in each case. The optimal value of log KMA was 3.0 in cases (a) and (c) and 3.2 in cases (b) and (d). Results for case (c) are shown in Fig. 1. The model predicts essentially complete binding in the pH dependence experiment, whereas the data show low binding at pH 1.4. Melamed et al. (2000) studied Hg(II) binding by HA at 3 pH values in the range 2.7–6.8, with a background solution of 0.01 M KCl, a total of 13 data points. They estimated the concentration of unbound Hg by reduction with SnCl2. The model could approximately simulate the results at low pH values (2.7 and 3.6), with a log KMA of 2.8. However, the reported unbound Hg concentrations at pH 6.8 were many orders of magnitude greater than expected by the model. Benoit et al. (2001) determined the binding of Hg(II) by two isolated aquatic samples, using a

E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

Table 4 Observed and simulated results of Benoit et al. (2001) for Hg(II) binding by two fractions of aquatic dissolved organic matter (DOM); see Section 3.1 for modelling assumptions

Hg ads mmol g

-1

2.0 1.5 1.0

DOM type

0.5

1.0

1.5

2.0

2.5

3.0

2

3 pH

4

5

Fig. 1. Hg(II) adsorption by particulate HA, determined by Varshal et al. (1998). The upper panel shows binding as a function of filterable metal concentration, [Hg]filt, which was assumed to correspond to inorganic forms of Hg(II) not bound to the HA; the results refer to pH 3, and only the five points with [Hg]filt measurably greater than zero were used for fitting. The lower panel shows binding as a function of pH at constant concentrations of HA (2.5 g l1) and Hg (5 · 104 M).

method that involved partitioning of HgCl2 into octanol. The background electrolyte was 0.01 M NaCl. The four data points obtained with a hydrophobic fraction (HPoA) covered the pH range 4–6, and were approximately explained by the model. The best fit (RMSD in log [Hg]free = 0.35) was obtained by assuming Fe(III) to be present at 105 moles per g DOM, and letting HgOH+ bind, with an optimised log KMA of 3.4. With the same assumptions, the two data points obtained with a hydrophilic fraction (HPiA), at pH 6, required log KMA to be 2.5. For HpoA, the optimal value of log KMA varied only slightly with different assumptions about Fe(III) and HgOH+, but for HpiA somewhat higher values of log KMA, 2.8 without Fe(III), 2.9 with Fe(III), were needed if HgOH+ binding was not allowed. Observed and simulated speciation data are shown in Table 4. Calculated concentrations of Hg2+ in the experiments were in the range 1020–1018 M. Haitzer et al. (2002) measured the binding of Hg(II) by an isolated hydrophobic fraction of DOM (the same HPoA studied by Benoit et al., 2001), using the equilibrium dialysis ligand

Calc

Obs

Calc

9.75 9.02 9.37 8.61

5.51 4.70 4.38 3.68

5.40 4.65 4.34 4.16

HpiA

6.0 6.0

9.34 8.96

9.32 8.69

5.35 4.72

5.30 5.04

mol Hg bound per g DOM.

exchange (EDLE) method, with a background electrolyte of 0.1 M NaClO4. Data at pH 7 covered a wide range of Hg–DOM ratios, and some additional data were reported for lower pH values, giving a total of 33 data points. Assuming the HPoA to contain 105 mol g1 Fe(III), and that HgOH+ binds, the best value of log KMA was 3.0, which gave an RMSD of 1.1 (Fig. 2). Equally good fits, but somewhat different log KMA values, were obtained with different assumptions (no Fe(III) present, no binding of HgOH+). Haitzer et al. (2003), again using the EDLE method, reported more data on the HPoA sample, examining the pH dependence of binding at low levels of Hg. Fig. 3 shows the observed pH variation of the apparent equilibrium constant, K 0DOM defined as [HgDOM]/[Hg2+] [DOM], together with the modelled values, obtained by assuming the HPoA to contain 105 mol g1 Fe(III), and with either HgOH+ binding (log KMA = 3.5) or not binding (log KMA = 3.7). In this case, the pH dependence -2 -3

pH 4.9

-4 log νHg

-1

0.0 1

Obs 9.19 9.02 9.50 9.03

a

0.1

LogmHg a

4.0 5.0 6.0 6.0

3.5

0.2

Log [Hg]inorg

HpoA

[Hg]filt mM

Hg ads mmol g

pH

0.5 0.0 0.0

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pH 5.6

-5 -6

pH 7.0

-7 -8 -35

-30

-25

-20

-15

-10

-5

2+

log [Hg ] Fig. 2. Observed (points) and simulated (lines) results of Haitzer et al. (2002), for Hg(II) binding by HpoA.

1630

E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

26 with HgOH+

log KDOM'

24

without HgOH+

22 20 18 16

3

4

5

6

7

8

pH Fig. 3. The dependence of the logarithm of the apparent stability constant for Hg binding by HPoA on pH, measured by Haitzer et al. (2003), shown by the points, and simulated with WHAM/ Model VI, shown by the lines.

is better reproduced if HgOH+ is not allowed to bind. Cruz-Guzma´n et al. (2003) measured Hg(II) binding to HA by centrifugation-depletion in 103 M HNO3 (pH 3). Hg(II) not sedimented was assumed to correspond to inorganic forms of the metal. In applying WHAM to the 3 data points that permit optimisation, the same log KMA value (4.0) and goodness-of-fit were obtained with or without the binding of HgOH+ and whether or not the sample was assumed to contain 105 mol g1 Fe(III). The comparatively high log KMA could simply

reflect a higher binding capacity than the default value. Observed and fitted adsorption isotherms are shown in Fig. 4. Lamborg et al. (2003) carried out studies of Hg(II) binding to HA (and DOM in natural waters) using ‘‘reducible Hg’’ titrations to determine labile forms of the metal, which were assumed to comprise only inorganic species. Their summarised data for HA refer to pH 7.5 with a background electrolyte of 0.025 M phosphate buffer, and they fitted their titration data with a single class of Hg binding sites having an abundance of 2.7 · 106 mol gHA1 and a conditional stability constant of 1021.5. To reproduce this binding strength with WHAM/Model VI, a log KMA of only 1.9 was required, substantially smaller than required to fit other data sets. As with the Melamed et al. (2000) data considered above, this may indicate that the reducible Hg includes organic forms, thereby overestimating the concentrations of inorganic species. Khwaja et al. (2006) measured Hg(II) binding at low levels by HA, using a competitive ligand (dl-penicillamine) technique at low pH (3 to 3.5), in a background electrolyte of 0.167 M Ca(NO3)2, separating the solution phase from the solids by centrifugation. They reported 11 data points that were fitted with WHAM/Model VI. The goodness-of-fit (RMSD in log [Hg2+]  1.0) did not depend greatly on the assumptions made, but log KMA varied from 3.4 (no Fe(III) present, with or without HgOH+ binding) to 3.9 (Fe(III) present, no HgOH+ binding). Fig. 5 shows results for two cases. Measurements

3

2

-1

log10 νHg (mol g )

Hgads mmol g

-1

-6

1

0

0

1

2

-7

-8

3

[Hg]SN mM Fig. 4. Adsorption isotherm for Hg(II) binding by particulate HA at pH 3; [Hg]SN is the concentration of metal in the supernatant after centrifugation, assumed to comprise unbound, inorganic forms of Hg(II). The points are the data of CruzGuzma´n et al. (2003). The line shows the model simulation, based on fitting to the three points for which [Hg]free is measurably greater than zero.

-9 -33

-32

-31

-30

-29

-28

-27

-26

log10 [Hg2+] Fig. 5. Results of Khwaja et al. (2006) for Hg(II) binding by IHSS HA at pH  3 (open circles) and 3.5 (closed circles). The full lines indicate the model fit assuming Fe(III) to be present and HgOH+ to bind; the dashed lines were obtained assuming Fe(III) to be absent and HgOH+ not to bind.

E. Tipping / Applied Geochemistry 22 (2007) 1624–1635 -5.5 -6.0 -1

log10 ν (mol g )

were also made at higher pH (4.3–5.0) on six other wetland HA samples. These were treated as a single data set. The best fit (RMSD in log [Hg2+] = 1.1, log KMA = 4.0) was obtained assuming Fe(III) to be present and for HgOH+ to bind. Almost as good a fit (RMSD = 1.2, log KMA = 4.2) was obtained with Fe(III) present, but without HgOH+ binding. However without Fe(III) competition, the fits were appreciably worse, with HgOH+ binding (RMSD = 2.0) or without it (RMSD = 2.2).

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pH 3.5 pH 5.2 pH 9.2

-6.5 -7.0 -7.5 -8.0 -8.5 -12.0

3.2. CH3Hg binding

-11.5

-11.0

-10.5

-10.0

-9.5

-9.0

-9.5

-9.0

-1

Table 5 Optimised values of log KMAfor the binding of CH3Hg by HA and FA (see text) Fe(III) CH3HgOH FLHAa LVFAa LHAa SRHAb PHAb No No Yes Yes

No Yes No Yes

0.4 0.4 0.3 0.2

0.1 0.1 0.9 0.6

0.1 0.1 0.8 0.7

0.5 0.2 0.9 0.4

0.1 0.2 0.6 0.2

The first two columns indicate whether Fe(III) was assumed to be present in the system, and whether CH3HgOH was considered to bind. a Hintelmann et al. (1997). b Amirbahman et al. (2002).

log10[CH3Hg]dial (mol L ) -5.5 -6.0 -1

log10 ν (mol g )

Hintelmann et al. (1995, 1997) reported the results of equilibrium-dialysis studies in which CH3Hg binding to three isolated aquatic samples (Fawn Lake HA, Lake Vernon FA, Lake Vernon HA) was measured. The data are not fully presented in the publications, and so trends in data were backcalculated from the reported fitted model parameters. The m values (mol CH3Hg bound per g humic matter) are of the order of 1010–106.5, the CH3Hg+ concs are in the range 1016–1012 M. The results refer only to pH 7, and to a background electrolyte of 104 M NaClO4. The values of log KMA for the three humic samples, and for different assumptions about the presence of Fe(III) and the binding of CH3HgOH, are summarised in Table 5. The RMSDs in the logarithm of the free CH3Hg concentration were in the range 0.07–0.28. Amirbahman et al. (2002) measured MeHg binding to two isolated HA samples by equilibrium dialysis, reporting 55 points for Suwannee River Humic Acid (SRHA) and 52 for peat humic acid (PHA), both from the IHSS. The results refer to a range of pH from 3.5 to 9.2, and an ionic strength of 103 M, controlled by different buffers. At pH 7.1, the range of values of m was 108–106, correspond-

-6.5 -7.0 -7.5

pH 4.6 pH 7.1

-8.0 -8.5 -12.0

-11.5

-11.0

-10.5

-10.0 -1

log10[CH3Hg]dial (mol L )

Fig. 6. Binding of CH3Hg by Suwannee River HA, as a function of dialyzable metal, [CH3Hg]dial, not bound to the HA. The points are the data of Amirbahman et al. (2002) and the lines are model fits, assuming Fe(III) to be present, but with no binding of CH3HgOH.

ing to the upper range of the values of Hintelmann et al. (1995, 1997); see above. The data could be fitted approximately with the model (Fig. 6), although at low pH, the simulated binding is appreciably lower than the observed levels. The optimised values of log KMA depended upon the assumptions made about the presence of Fe(III) and the participation of CH3HgOH in binding (Table 5). For each data set, the best fit was obtained with Fe(III) present but without CH3HgOH binding, and the worst with Fe(III) present and CH3HgOH binding. The RMSD values (residuals in log free CH3Hg) were in the range 0.2–0.5. 4. Discussion Mercury is a difficult metal to work with experimentally, especially at the very low concentration

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E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

levels most relevant to natural systems (Ravichandran, 2004). Consequently, there are fewer binding data, of poorer quality, than can be obtained for other metals. The methods used to obtain the data analysed here were mostly separation techniques (equilibrium dialysis, centrifugation, filtration, aqueous–organic partitioning), sometimes combined with a competing ligand. These methods have possible drawbacks, notably incomplete retention by the dialysis membranes (Haitzer et al., 2002), influence of the organic solvent on the humic matter, and the formation of mixed ligand complexes. There is danger of contamination when working at low Hg levels. Furthermore, the samples of humic substances used to obtain the published results were isolated by different methods, and are likely to have differed in their contents of both reduced S groups (important for binding at low Hg levels) and potentially competing metals. It is therefore not surprising that the experimental results show appreciable scatter, and this significantly hampers high precision fitting with complexation models. The present study has applied WHAM/Model VI with adjustment only of a single parameter (log KMA); ideally, this should both fit the data and have a similar value for each class of humic substances (HA and FA). It must be remembered, however, that the model parameter DLK2, which is not fitted, has a major influence on Hg binding, by generating binding sites with a wide range of affinities, including small numbers of very strong sites. In addition, an examination has been made of the effects of assumptions about the presence of Fe(III) and the participation of hydrolysis products in binding. This

approach, the main aim of which is to obtain generally applicable default model parameters, has the advantage that it can be applied to both small and large data sets, and indeed most of the data sets considered here are in the former category. The fits, expressed as RMSDs in logarithmic variables, are generally worse than has been found for other metals. For example, the RMSD for the relatively large data set of Haitzer et al. (2002) is 1.1, whereas that for the data set of Cu (Benedetti et al., 1995) which also covered several pH values and a large free metal concentration range, was only 0.07. As noted above, some of the greater error arises from ‘‘noise’’ in the data, while some must be due to inaccuracies and approximations in the model. Table 6 summarises the log KMA values from the eight ‘‘accepted’’ data sets, i.e., those cases where the results are in reasonable accord with the assumptions of the model. Results from the data sets of Yin et al. (1997), Melamed et al. (2000) and Lamborg et al. (2003) have been omitted from Table 6, for reasons given in Section 3.1. The log KMA (3.5) estimated from the data set of Kerndorff and Schnitzer (1980), previously taken to be the default value (Section 2.2), has also been omitted because it refers to a complex multiple metal system, with consequent uncertainties about competition effects among metals. The values of log KMA from the different data sets are in fair agreement. The average values for FA and HA are quite close to the original default values of Table 1. The differences in log KMA depending upon the assumptions about Fe(III) and HgOH are not great. In one case (Haitzer et al., 2003), better agreement between

Table 6 Summary of accepted values of log KMA for Hg binding by isolated humic substances, with different assumptions about the presence of Fe(III) and the participation of HgOH+ in binding No Fe(III) No HgOH

No Fe(III) HgOH

Fe(III) No HgOH

Fe(III) HgOH

Fulvic acids, etc. Cheam (1973) Benoit et al. (2001) HpoA Benoit et al. (2001) HpiA Haitzer et al. (2002) Haitzer et al. (2003)

3.4 3.3 2.8 3.2 3.3

3.3 3.2 2.4 2.7 3.0

3.4 3.4 2.9 3.4 3.7

3.3 3.4 2.5 3.0 3.5

Mean (SD)

3.2 (0.2)

2.9 (0.4)

3.4 (0.3)

3.1 (0.4)

Humic acids Varshal et al. (1998) Cruz-Guzma´n et al. (2003) Khjawa et al. (2006)

3.2 4.0 3.6

3.0 4.0 3.5

3.2 4.0 4.0

3.0 4.0 3.9

Mean (SD)

3.6 (0.4)

3.5 (0.5)

3.7 (0.5)

3.6 (0.6)

E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

40

30 Hg(II) z+

log10 ν / [M ]

observation and simulation was achieved by preventing HgOH+ from binding, thereby lowering the pH-dependence of the interactions, whereas in another (Benoit et al., 2001) the reverse was true. Fits were not significantly different whether or not Fe(III) was assumed to be present, and to compete with Hg(II) for binding, although of course competition by Fe(III) led to somewhat higher log KMA values. The new default log KMA values are most logically, in terms of previous modelling efforts, taken to be those applying to the case where HgOH+ binding is assumed to occur, and where competing residual Fe(III) is assumed to be present in the samples, i.e., 3.1 for FA and 3.6 for HA. These intrinsic equilibrium constants refer to the binding of the metal with COO to form a monodentate complex, and they are within the range (2.9– 3.7) of published log K values for the binding of Hg(II) by monodentate carboxylic acids (Martell and Smith, 1977). However, even at the highest reported values of m, Hg(II) is not bound at simple monodentate sites, as evidenced by the log conditional constants of ca. 5 reported by Cheam and Gamble (1974). The data considered here for Hg(II) cover the following ranges; pH 1.4 – 7.5, [Hg2+] 1034–103 M, m 108–103 mol g1, ionic strength 0.001–0.1 M (Table 3). The ability of WHAM/Model VI to account approximately for binding over such a wide range of experimental conditions, without adjustment of default parameters other than log KMA, appears consistent with its formulation of multidentate binding sites, and the participation of softer ligand atoms in metal binding (Section 2.1). It also explains why reported conditional stability constants, referring to narrow ranges of experimental conditions, are highly variable (Ravichandran, 2004). The parameter values log KMA and DLK2 for Hg(II) are the highest found so far for any metal interacting with humic matter. This means that the metal binds strongly to carboxylate groups, and also that it has binding sites with a wide range of affinities, including small numbers of very strong sites. The combined effect of log KMA and DLK2 on the prediction of metal binding is illustrated in Fig. 7 where default model parameters for the binding by HA of Ca, Zn, Cu, Hg(II) and CH3Hg are used to generate the function log (m/[Mz+]), a measure of ‘‘local’’ binding affinity, as a function of metal loading (m). Not only is Hg(II) the most strongly bound metal, it also exhibits the greatest variation in bind-

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20 Cu

10 CH Hg 3 Zn 0 Ca -7

-6

-5 log10 ν

-4

-3

-2

Fig. 7. Variation in binding affinity, expressed as log (m/[Mz+]), with metal loading (m) of HA. The results are simulations with WHAM/Model VI for pH 7.0 and 0.01 M NaNO3.

ing affinity, i.e., the greatest heterogeneity in binding sites. Thus, the model is able to account for the very high binding affinities found in studies with low concentrations of Hg(II) or CH3Hg (most relevant to field situations), as well as the more moderate affinities encountered at higher loadings. Considering the plots in Fig. 7, binding at log m  3 is due mainly to bidentate sites formed by the abundant carboxyl and phenolic groups, and as m decreases, sites with higher affinities come increasingly into play. Model VI does not explicitly identify these sites, but it is reasonable to suppose that they involve N-ligands at intermediate log m(5) and S-ligands at low m. An important point to note is that Model VI predicts significant competition by other metals for Hg(II) binding, since even though their binding affinities may be lower than that of Hg(II), this can be compensated for by higher concentrations. We have seen in the model applications described here that Fe(III) influences the predicted binding of Hg(II) at lower values of m. Experimental studies by Lu and Jaffe (2001) and Wu et al. (2004), both involving non-isolated dissolved organic matter and comparatively high levels of Hg(II) binding, showed competition by Mg and Ca. However, competition may be less significant at the very low levels of Hg(II) found in natural systems, where high affinity sites involving reduced S atoms are thought to dominate Hg binding (Loux, 1998; Ravichandran, 2004). Such sites would not be expected to interact strongly with major cationic metals such as Mg, Al, Ca and Fe(III), and so competition effects might be small. Some evidence for lack of competition

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E. Tipping / Applied Geochemistry 22 (2007) 1624–1635

comes from the experiments of Skyllberg et al. (2000), who showed that high concentrations of Al had no measurable effect on the binding of low levels of Hg(II) by acid organic soil. Competition for Hg(II) and CH3Hg in the field, or in insufficiently extracted isolated humic matter, might be exerted by soft metals such as Cd (A. Amirbahman, pers. comm.). There is a clear need for competition studies with Hg(II) and these other metals. The data fits for CH3Hg are only approximate, and the pH dependence is not captured at acid pH (Fig. 6). Moreover, the log KMA values are considerably lower than expected from linear free energy relationships (cf. Table 1). Thus, while CH3Hg binds to simple carboxylic acids with logarithmic stability constants of ca. 3 (Martell and Smith, 1977), the log KMA values are less than 1 (Table 5). A possible explanation is that, by requiring a relatively low overall binding strength, the model is compensating for the restricted ability of CH3Hg to form multidentate bonds. It seems quite clear, from both the experimental data and the modelling results, that the affinity of humic matter for CH3Hg is appreciably weaker than for Hg(II); the binding strengths of the two forms of Hg are compared in Fig. 7. Consequently, competition effects by other metals are expected to be greater, although if binding in the field is due mainly to ligands containing reduced S atoms, the comments made above with respect to Hg(II) may apply. The default Model VI value of log KMA is taken to be 0.3, which, in view of the relatively few data for FA, is assumed to apply to both HA and FA. 5. Conclusions Adjustment of a single key parameter (log KMA, the intrinsic equilibrium constant for metal binding to carboxylate groups) in Humic Ion Binding Model VI provides approximate descriptions of most of the available data describing Hg(II) binding by isolated humic matter (HA and FA). The experimental data and the model show that apparent binding strength towards Hg(II) is highly dependent upon the metal loading. Of the 24 metals to which WHAM/Model VI has been applied, Hg(II) shows the strongest binding to humic substances, and the greatest range in binding affinities. The relatively few data characterising the interactions of CH3Hg with humic substances can be approximately fitted with the model, and the results show that CH3Hg binding is appreciably weaker than that of Hg(II). New

default values of log KMA are 3.6 for Hg(II)–HA binding, 3.1 for Hg(II)-FA and 0.3 for CH3Hg– HA and CH3–FA. Acknowledgements The author is grateful to the following for helpful discussion and/or the provision of raw data; G.R. Aiken, H.E. Allen, A. Amirbahman, P.R. Bloom, J.R. Kramer, C. Lamborg, L. Lo¨vgren, J. Ryan and U. Skyllberg. The paper also benefited from the comments of two anonymous reviewers. This work was financially supported under Contract EPG 1/3/188, by the UK Department for Environment, Food and Rural Affairs, the Scottish Executive, the National Assembly of Wales and the Department of the Environment (in Northern Ireland). References Amirbahman, A., Reid, A.L., Haines, T.A., Kahl, J.S., Arnold, C., 2002. Association of methylmercury with dissolved humic acids. Environ. Sci. Technol. 36, 690–695. Benedetti, M.F., Milne, C.J., Kinniburgh, D.G., van Riemsdijk, W.H., Koopal, L.K., 1995. Metal ion-binding to humic substances – application of the nonideal competitive adsorption model. Environ. Sci. Technol. 29, 446–457. Benoit, J.M., Mason, R.P., Gilmour, C.C., Aiken, G.R., 2001. Constants for mercury binding by dissolved organic matter isolates from the Florida Everglades. Geochim. Cosmochim. Acta 65, 4445–4451. Cheam, V., 1973. Chelation study of copper(II): fulvic acid system. Can. J. Soil Sci. 53, 377–382. Cheam, V., Gamble, D.S., 1974. Metal-fulvic acid chelation equilibrium in aqueous NaNO3 solution. Hg(II), Cd(II), and Cu(II) fulvate complexes. Can. J. Soil Sci. 54, 413–417. Cruz-Guzma´n, M., Celis, R., Hermosı´n, M.C., Leone, P., Ne`gre, M., Cornejo, J., 2003. Sorption–desorption of lead(II) and mercury(II) by model associations of soil colloids. Soil Sci. Soc. Am. J. 67, 1378–1387. Haitzer, M., Aiken, G.R., Ryan, J.N., 2002. Binding of mercury(II) to dissolved organic matter: the role of the mercury-to-DOM concentration ratio. Environ. Sci. Technol. 36, 3564–3570. Haitzer, M., Aiken, G.R., Ryan, J.N., 2003. Binding of mercury(II) to aquatic humic substances: influence of pH and source of humic substances. Environ. Sci. Technol. 37, 2436–2441. Hintelmann, H., Welbourn, P.M., Evans, R.D., 1995. Binding of methylmercury compounds by humic and fulvic acids. Water Air Soil Pollut. 80, 1031–1034. Hintelmann, H., Welbourn, P.M., Evans, R.D., 1997. Measurement of complexation of methylmercury(II) compounds by freshwater humic substances using equilibrium dialysis. Environ. Sci. Technol. 31, 489–495. Kerndorff, H., Schnitzer, M., 1980. Sorption of metals on humic acid. Geochim. Cosmochim. Acta 44, 1701–1708.

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