Modeling Adsorption of Copper(II), Cadmium(II) and Lead(II) on

Tipping, E.; Berggren, D.; Mulder, J.; Woof, C. Eur. J. Soil Sci. 1995, 46, 77. [Crossref], [CAS]. (16) . Modeling the solid-solution distributions of...
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Modeling Adsorption of Copper(II), Cadmium(II) and Lead(II) on Purified Humic Acid Aiguo Liu† and Richard D. Gonzalez*,‡ Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, and Chemical Engineering Department, Tulane University, New Orleans, LA 70118 Received May 18, 1999. In Final Form: December 16, 1999 In this study, a system consisting of Pb, Cu and Cd as typical heavy metal pollutants, and purified Aldrich humic acid as a representative of natural organic materials were selected as prototypes to model the environmental system. The effect of environmental factors such as pH, salinity, and concentration on the interaction between metals and humic acid were investigated in detail. The experimental results show that pH and ionic strength are the most important variables in controlling metal adsorption on humic acid. The results also show a high complexation capacity of humic acid for the metals, especially Cu and Pb. The strength of binding of the three metals is in the sequence of Pb > Cu > Cd. A theoretical model featured by surface complexation reactions and double layer theory combined with the Poisson-Boltzmann equation was applied to simulate the experimental data. Titration data of humic acid with NaOH and Ba(OH)2 were used as concentrations of strong and weak acid groups on HA and the input data for the model calculations. Intrinsic adsorption constants and capacitance are estimated based on literature values and optimized to obtain the best agreement between the experimental and the model results. The model was also used to predict surface properties such as the speciation of the metals adsorbed on humic acid. Good agreement between theoretical modeling results and experimental data suggests the applicability of the theoretical model to this system. Given these parameters, theoretical calculations obtained using the model proposed in this study can give a detailed picture of the actual environmental conditions. Also, the model calculations will help in the evaluation of the actual toxicity of heavy metal pollutants in the aquasystem.

Introduction The distribution and fate of heavy metal pollutants in aqueous solution is strongly influenced by the presence of natural organic material. They are present in aqueous systems and can exist either in solution or as a precipitate mixed with sediments. Important characteristics of humic substances are their ability to form water-soluble and water-insoluble complexes with metal ions and sediments or suspended particulates. Humic and fulvic acids represent a fraction of humic substances that are functionally defined according to their solubility.1,2 In natural water, about 50% of the dissolved organic materials (DOM) consists of humic acid (HA) and fulvic acids.3 The environmental significance of metal sorption by humic substances derives from the fact that humic substances provide an important source of dissolved adsorbent organic ligands and, therefore, are expected to influence the bioavailibility and mobility of metals in soil, sediments and aquatic systems. With respect to the potential toxicity of heavy metals, metal adsorption by humic substances is believed to reduce metal uptake by organisms. The ecotoxicology of heavy metals is determined by the pathway of decontamination in natural aqueous systems. The phenolic and carboxylic groups (-OH and -COOH) are believed to be the most active adsorption sites on humic and fulvic acid and that the order of heavy metal sorption * To whom correspondence should be addressed. Fax: 5048656744. Telephone: 504-8655741. E-mail [email protected]. † Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University. ‡ Chemical Engineering Department, Tulane University. (1) Suffet, I. H.; MacCarthy P. Aquatic Humic Substances; American Chemical Society: Washington, DC, 1989. (2) Sposito, G. Crit. Rev. Environ. Control 1986, 16, 193. (3) Thurman, E. M.; Malcolm, R. L. Environ. Sci. Technol. 1981, 15, 463. (4) Lo¨vgren, L.; Sjo¨berg, S. Water Res. 1989, 23, 327.

efficiency is a function of pH. Hg(II) was the metal most easily adsorbed by HA and Mn was the most difficult.4,5 The hardness metals, Ca and Mg, inhibit the adsorption of trace metals on HA.6 Electrochemical methods, such as ion-selective electrodes (ISE) and anodic stripping voltammetry (ASV), have been widely used to study metal adsorption on HA and fulvic acid.6-11 The advantage of electrochemical methods of analysis is that one can make in-situ measurements without the need to separate the complexed ions from the free metal ions. A major drawback of electrochemical methods, from our own experience, is that the presence of HA interferes with the measurement and a steady reading is not easy to obtain. This may be due to the adsorption of HA or fulvic acid molecules on the surface of the electrodes. Malcolm and MacCarthy12 concluded that commercial HAs are not representative of aquatic or soil HAs. Following a comparison using calcium titration data for Aldrich and Suwannee HAs, Hering and Francois13 suggested that the use of reprecipitated commercial HA in preliminary studies of metal complexation, is adequate to within a first approximation. Sposito2 reviewed the models concerning the sorption of trace metals by humic materials. In this review, the (5) Kerndorff, H.; Schnizer, M., Geochim. Cosmochim. Acta 1980, 44, 1701. (6) O’Shea, T. A.; Mancy, K. H. Water Res. 1978, 12, 703. (7) Saar, R. A.; Weber, J. H. Can. J. Chem. 1979, 57, 1263. (8) Saar, R. A.; Weber, J. H. Environ. Sci. Technol. 1980, 14, 877. (9) Buffle, J.; Greter F.; Haerdi, W. Anal. Chem. 1977, 49, 216. (10) Aualiitia, T. U.; Pickering, W. F. Water Res. 1986, 20, 1397. (11) Mota, A. M.; Rato, A.; Brazia, C.; Goncalves, M. L. S. Environ. Sci. Technol. 1996, 30, 1970. (12) Malcolm, R. L.; MacCarthy, P. Environ. Sci. Technol. 1986, 20, 904. (13) Hering, J. G.; Francois, M. M. Environ. Sci. Technol. 1988, 22, 1234.

10.1021/la990607x CCC: $19.00 © 2000 American Chemical Society Published on Web 03/08/2000

Modeling Adsorption on Purified Humic Acid

Scatchart, Buffle, Henderson-Hasselbalch, PerdueLytle, polyelectrolyte, and Gamble models were characterized as quasiparticle models because all the models made a hypothetical assumption that the humic material was a mixture of nonreacting macromolecules bearing unspecified charge. Sposito14 revised this model by introducing two side-reaction coefficients fM and fL which are pH dependent. The generalized Freundlich, Langmuir-Freundlich, and To¨th adsorption isotherms are commonly used to fit the overall adsorption data.15 The advantage of these models over the Scatchard quasiparticle model is that they reduce the number of adjustable parameters in an isotherm to approximately half. Tipping and co-workers16 developed humic ion-binding model V. They assume that humic compounds have a hypothetical sizeshomogeneous molecules that carry proton-dissociation groups. The formation constant of a proton is described by the combination of an intrinsic equilibrium constant and the electrostatic term. A further development based on the above adsorption isotherm was intended to take into account the multicomponent adsorption and to describe the metal ion binding to humic substances. By assuming the HA molecule to be a small rigid and impermeable cylindrical or spherical particle of a certain size and a variable surface charge density depending on pH and salt concentration, de Wit et al.17,18 successfully described proton binding by HA. They assessed the particle radii to be from 0.6 to 4.4 nm with a median value of 0.85 nm for a spherical configuration and from 0.19 to 2.5 nm with a median value of 0.32 nm for a cylindrical configuration. The same group further examined the isotherms for multicomponent adsorption to heterogeneous surfaces and proposed such models as nonideal competitive adsorption (NICA) and NICA-Donnan.19-22 The goal of this research is to experimentally measure the adsorption of different metals and to formulate and test a model based on surface complexation and the double layer theory. Similar models have been used by Bartschat et al.23 and Bose and Bechhow.24 In this study, the adsorption of Cu, Cd, and Pb on HA as a function of pH, ionic strength and metal concentration has been measured. A set of surface dissociation and complexation reactions was coordinated using the Poisson-Boltzmann equation. The model features simultaneous accommodation of variables such as adsorbate concentration, ionic strength, and solution pH.

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for each species and were corrected using the DebyeHu¨ckel equation.25,26 The effect of metal concentration (usually in the range 10-4-10-5 M) was neglected because its concentration was much lower than that of the background ion, which was above 10-3 M. The results of the speciation calculation show that a significant amount of metal ions exist as MeOH+. This factor is considered in the model calculations by allowing the first product of the hydrolysis to adsorb on the surface. The difficulty with this consideration is that the intrinsic adsorption constants Kint for MeOH+ are usually unavailable in the literature and almost impossible to measure experimentally. As an approximation, the intrinsic equilibrium constant Kint for the MeOH+ is initially assumed to be equal to the Kint of its mother ion whenever MeOH+ is included in the adsorption equilibrium calculation16 but allowed to be adjustable by iteration to obtain the best fit of model results. Basic Assumptions of the Mathematical Model. A rigid and cylindrical configuration was assumed for HA molecules. A double layer structure based on the SternGouy-Chapman (S-G-C) model27 was assumed at the interface of HA and the aqueous solution. The S-G-C model assumes a charge free region from 0 < r < d. Theoretically, only ions that are easily dehydrated can enter into the layer. Na+ and K+ have relatively small ionic radii and water molecules are strongly bound to them so that they cannot approach the surface closer than that of the plane x ) d. In other words, they are not specifically adsorbed at the interface.27 Their adsorption is determined purely by their response to the electric field in the diffuse part of the double layer. When one assumes that the potential of the bulk solution is zero, the Poisson equation takes the form

∇2ψ ) -

1 0r

( )

∑i ni0zie exp -

(14) Sposito, G.; Blaser P. Soil Sci. Soc. Am. J. 1992, 56, 1095. (15) Kinniburgh, D. G.; Barker J. A.; Whitefield, M. J. Colloid Interface Sci. 1983, 95, 370. (16) Tipping, E.; Berggren, D.; Mulder, J.; Woof, C. Eur. J. Soil Sci. 1995, 46, 77. (17) de Wit, J. C. M.; van Riemsdijk, W. H.; Koopal, L. K. Environ. Sci. Technol. 1993, 27, 2005. (18) de Wit, J. C. M.; van Riemsdijk, W. H.; Koopal, L. K. Environ. Sci. Technol. 1993, 27, 2015. (19) Koopal, L. K.; van Riemsdijk, W. H.; de Wit, J. C. M.; Benedetti, M. F. J. Colloid Interface Sci. 1994, 166, 51. (20) Benedetti, M. F.; van Riemsdijk, W. H.; Koopal, L. K. Environ. Sci. Technol. 1996, 30, 1805. (21) Kinniburgh, D. G.; Milne, C. J.; Benedetti, M. F.; Pinheiro, J. P.; Filius, J.; Koopal, L. K.; van Riemsdijk, W. H. Environ. Sci. Technol. 1996, 30, 1687. (22) van Riemsdijk, W. H.; de Wit, J. C. M.; Mous, S. L. J.; Koopal, L. K.; Kinniburgh, D. G. J. Colloid Interface Sci. 1996, 183, 35. (23) Bartschat, B. M.; Cabaniss S. E.; Morel F. M. M, Envrion. Sci. Technol., 1992, 26, 284 (24) Bose P.; Reckhow, D. A. Envrion. Sci. Technol. 1997, 31, 765.

kT

(1)

The Laplace operator ∇2 will take different forms in accordance with the coordination. The 0 and r are vacuum and relative permittivities, respectively. The PoissonBoltzmann equation is the basis for calculating the potential distribution in an electrolyte solution which surrounds a charged surface. If it is assumed that the charge density at the x ) d plane is σd, the boundary conditions for eq 1 in a cylindrical coordination are

Modeling Speciation and Activity Coefficient Correction. Hydrolysis products of metal ions were calculated using the stepwise hydrolysis constants and activity coefficients

zieψ

(∂ψ∂r ) (∂ψ∂r )

r ) r0+d

)-

rf∞

σd 0r

)0

(2) (3)

The relationship between ψ and σ in the region has been proposed as follows27

ψ0 - ψd )

σ0 σd )C C

(4)

where ψ0 and ψd are the potentials at the surface and plane d, respectively. σ0 is the surface charge density and is determined by the dissociation of functional groups and (25) Baes, C. F.; Mesmer, R. E. The Hydrolysis of Cations; John Wiley & Sons: New York, 1986. (26) Lange, N. Lange’s Handbook of Chemistry, 12th ed.; McGrawHill: New York, 1979. (27) Hunter, R. Foundations of Colloid Science; Oxford University Press: New York, 1986; pp 316-391.

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ion adsorption on the HA surface. These surface reactions will be discussed later in detail. C is capacitance. The purpose of assuming a linear distribution of potentials in the region 0 < r < d is to avoid the complexity that can arise when the relative permittivity r is no longer a constant in the near vicinity of a charged surface. In our system, H+, OH-, Na+, NO3-, and Me2+ together with their hydrolysis products, primarily MeOH+, are present. Here we assume that H+, OH-, and Me2+ as well as the hydrolysis products can penetrate into the region of r < d. Na+ and NO3- are indifferent ions.27 The specific adsorption differences between ions are reflected in the differences in their intrinsic adsorption constants without considering the detailed mechanisms of each adsorbed ion. Two kinds of primary adsorption sites on HA are assumed, i.e., strong acid site S1 and weak acid site S2. Each of the sites shown here are assumed to have a negative charge, which is omitted to express the equations more clearly. No further division is made in each of the groups. To simplify the calculation, only monodentate binding is considered. The possible bidentate binding is neglected. Because the surface of HA is negatively charged above pH 3.0, the anion adsorption is neglected. The ion concentration in the vicinity of HA surface is determined by the Boltzmann distribution law

(

[Zni ]s ) [Zni ]b exp -

)

neψ0 kT

(5)

where [Zni ]s and [Zni ]b are the surface and bulk concentrations of ion i with a valence n, respectively. The surface reactions considered in the modeling are listed in Table 1. The total number of adsorption sites on HA was assumed to be equal to the total acidity. The total acidity was determined by barium hydroxide titration.28 The strong acid groups on HA were determined by direct titration with NaOH. Therefore

σ0 )

B (-[S1] - [S2] + [S2H2+] + [S1Me+] + AHA [S1Me+] (6)

Ta ) ([S1] + [S2] + [S2H2+] + [S2Me+] + [S1MeOH] + [S2MeOH] + [S1H] + [S2H]) (7) TC ) ([S1] + [S1Me+] + [S1MeOH] + [S1H])

(8)

where, AHA is the surface area of the HA molecule. Ta and TC are the total acidity and the total concentration of strong acid groups, respectively. B is a conversion factor and is equal to 96.485 coulomb/(mol/L). The specific surface area of HA measured on dried samples may be a small part of the total surface area exposed in solution. The BET surface area cannot be used for HA. If a cylindrical configuration is assumed for HA molecules, the following equation can be obtained

AHA )

a Fr

(9)

where a ) 2 for the cylinder, r is the radius of the cylinder, (28) Vilks, P.; Isolation and Characterization of Humics. In Binding Models Concerning Natural Organic Substances In Performance Assessment; OECD: Paris, 1995; pp 57-74. (29) Aster, B.; Burba, P.; Broekaert, J. Fresenius J. Anal. Chem. 1996, 354, 722.

Table 1. List of Surface Reactions and Corresponding Expression of Intrinsic Equilibrium Constants surface reaction

intrinsic equilibrium constant

H+ + S1 ) S1H

int KH-S ) 1

H+ + S2 ) S2H

int KH-HS 2

Me2+ + S1 ) S1Me+

int KMe-S 1

MeOH+ + S1 ) S1MeOH Me2+ + S2 ) S2Me+ MeOH+ + S2 ) S2MeOH

exp

( ) ( ) ( ) ( ) ( ) ( ) ( ) eψ0 kT

eψ0 exp kT [H+]b[S2] [S2H+ ] eψ0 2 exp ) + kT [H ]b[S2H] + [S1Me ] 2eψ0 exp ) kT [Me2+] [S ]

int KH-S ) 2

H+ + S2H ) S2H2+

[S1H] [H+]b[S1] [S2H]

b

1

[S1MeOH]

eψ0 exp kT [MeOH+]b[S1] + [S Me ] 2eψ 2 0 int exp KMe-S ) 2 kT [Me2+]b[S2] [S2MeOH] eψ0 int KMeOH-S exp ) + 2 kT [MeOH ] [S ] int KMeOH-S ) 1

b

2

and F is the density of the HA particle. F is defined as the mass of the dry HA divided by its hydrated volume. The range of values for F is between 700 and 1700 kg m-3. The median value of r is 0.32 nm for a cylindrical configuration.17 By combination of the above equations and the surface complex reactions listed in Table 1, the equilibrium adsorption of metal ions and the surface speciation on the surface of HA can be calculated under various conditions. Experiment Materials and Supplies. HA was prepared from sodium humate (Aldrich Chemical Co.). The commercial sodium humate was first dissolved in deionized water (Nanopure) at an approximate concentration of 0.5% (w/v) and stirred for 2 h using a magnetic stirrer. Following stirring, the solution was decanted for a period of 1/2 h. The precipitate that was formed was discarded and the supernatant solution was acidified using HNO3 to a pH of 1.5. Stirring was continued at low speed for a period of 2 h. This solution was then centrifuged for 15 min at 10 000 rpm and the supernatant was discarded. The precipitate was redissolved in deionized water. This solution was further purified by ultrafiltration.29 Ultrafree-15 filtration units, provided by the Millipore Company, were made of polysulfone membranes with a molecular weight cut offÅ (MWCO) of 5000 and 10 000. The wall of the units was made of polycarbonate. They could fit into 50 mL centrifuge tubes and achieve separation by centrifugal force. The concentrate from the 10 000 MWCO membrane filtration and the filtrate permeated through 5000 MWCO membrane filtration were discarded. Following each filtration, the concentrate was washed three times with deionized water. The pH of the HA solution was preadjusted to 6 prior to each filtration. Figure 1 details the procedure for the purification of HA. The purified solution was used as HA stock solution. The concentration in these solutions is expressed in term of total carbon content. This was determined by combustion analysis. The strong acid groups and the total acidity of HA were determined by NaOH titration and the barium hydroxide method, respectively.28 The weak acidic groups were calculated as the difference between the total acidity and that of the strong acid groups. The results of the titration and the elemental analysis of the purified Aldrich HA are listed in Tables 2 and 3. The 1000 ppm samples of Cu(NO3)2, Cd(NO3)2, and Pb(NO3)2 standard were purchased from Fisher Scientific. The concentrations of these standard solutions was guaranteed by the supplier, and they were each used both as a standard and as the metal solution for the adsorption experiments. All other chemicals used were reagent grade or better. Adsorption Procedures. Batch adsorption was carried out using 50 mL scaled centrifuge tubes made out of polypropylene. Following mixing of the desired volume of stock solution, the pH was adjusted by the addition of dilute HNO3 or NaOH. The final

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Figure 1. Schematic for the pretreatment of humic acid. Table 2. Titration Results of Purified Humic Acid total acidity (equiv/kg) concentration of strong acid groups(equiv/kg) concentration of weak acid groups(equiv/kg)

3.18 ( 0.15 2.55 ( 0.12 0.63

Table 3. Elemental Analysis of Purified Humic Acida humic acid purified soil soil water (Aldrich)b humic acidb humic acidc fulvic acidc humic acidd %C %H %O %N

59.59 3.90 (35.55) 0.80

54.87 4.45 (39.14) 1.23

38.99 3.95 36.35 0.60

45.52 5.63 45.97 2.78

52.07 5.07 39.93 2.37

a Unit is in percentage by weight. b Data of this study. c From Narkis and Rebhun.31 d From Mota et al.11

volume was adjusted to 40 mL using deionized water. The concentration of HA was controlled to 48 mg/L for all samples provided that no other specific explanations were given. The initial concentrations for the pH and the ionic strength experiments were set at 3.86 × 10-5 , 7.14 × 10-5, and 12.6 × 10-5 mol/L for Pb, Cd, and Cu, respectively. For the samples used in the adsorption isotherm measurements, the initial concentration of metals was set as a series from 3 × 10-6 to 8 × 10-5 M. The samples were placed in an orbital shaker and shaken for 48 h at 25 °C. Ten-milliliter aliquots of the samples were then transferred into the ultrafiltration unit equipped with a 5000 MWCO polysulfone ultrafiltration membrane to separate complexed metal ions from uncomplexed ions. The separation was carried out by centrifugation at about 5000 rpm (∼2000g). Metal concentrations in the filtrate were analyzed by atomic absorption. HA concentrations were determined following 0.45 µm syringe filter filtration. Analyses. The concentration of metals in the aqueous phase was determined by atomic absorption. A Perkin-Elmer model 500 atomic absorption spectrophotometer was used in these measurements. A calibration curve was determined using standard samples prior to each measurement. HA concentration was measured using a UV160 spectrophotometer at a wavelength of 400 nm. Pettersson et al.30 used absorption at 250 nm to analyze for the concentration of HA. However, at this wavelength the absorption is very sensitive to the NO3- present in our samples. To eliminate the effect of pH on the absorption, samples (usually 5 mL) for HA concentration analysis were mixed with a 2 mL NaAc-HAc buffer solution to (30) Pettersson, S.; Ha¨kansson, K.; Allard, B. Water Res. 1993, 27, 863.

Figure 2. Adsorption of Pb on humic acid as a function of pH at two ionic strengths, 0.02 and 0.8 M. Total humic acid concentration was 0.0468 g/L. Initial metal concentration was 3.86 × 10-5 M. The lines represent the results of model calculations. stabilize the solution pH to approximately 4.5. The concentration of HA was expressed as ppm carbon. The concentration in the stock solution of HA was determined by an EAGER 200 combustion elemental analyzer. The standard solution of HA was obtained by diluting the stock solution of HA. A linear correlation between the absorbance at 400 nm and the HA concentration was obtained for use in a typical calibration curve. The amount of metal adsorbed on HA was determined by mass balance.

Results Metal adsorption on HA as a function of solution pH and ionic strength. Figures 2-4 show the results of metal adsorption as a function of pH at two values of the ionic strength (0.02 and 0.8 M NaNO3). The solid points represent the experimentally measured results, and the lines represent the results obtained by model calculations which will be discussed later. For all three metals, an increase in the pH results in an increase in the amount of adsorbed metals on HA, especially when the pH is in the range 2.5-5.0. At low ionic strength, a larger adsorption of metals on HA was observed over the entire pH

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Figure 3. Adsorption of Cd on humic acid as a function of pH at two ionic strengths, 0.02 and 0.8 M. Total humic acid concentration was 0.0468 g/L. Initial metal concentration was 7.14 × 10-5 M. The lines represent the results of model calculations.

Figure 4. Adsorption of Cu on humic acid as a function of pH at two ionic strengths 0.02 and 0.8 M. Total humic acid concentration was 0.0468 g/L. The initial metal concentration was 1.26 × 10-4 M. The lines represent the results of model calculations.

range tested. For Cu, the effect of ionic strength was less noticeable than for the other two metals when the pH was less than 5.0. Metal Adsorption on HA as a Function of Metal Ion Concentration. The experimental results obtained for the adsorption isotherms for the three metals are shown in Figure 5. The solid points represent the isothermal adsorption of Pb, Cd, and Cu on HA at a constant equilibrium pH of 6.0 and an ionic strength of 0.1 M NaNO3. For the three metals, the amount of metal adsorbed increased when the metal concentration was increased. The strength of binding of the three metals is in the sequence of Pb > Cu > Cd. Of the three metals studied, Cd is the most difficult metal ion complexed by HA. Estimation of Intrinsic Adsorption Constants and Parameters. The values of these constants were estimated in reference to literature values.17,18,20,22 Literature works from which the initial value of each intrinsic constant was cited are listed as a footnote in Table 4. The value of capacitance C for the mineral surface is used. These literature values were the results of model fitting to experimental data. Although these parameters have the same definition, different authors may obtain a

Liu and Gonzalez

different value due to the assumptions made when establishing a model. The final values were optimized to obtain the best agreement between the experimental and the model results of metal adsorption as a function of pH. The estimated values were used later without further adjustment to simulate the experimental results of metal adsorption as a function of ionic strength and the results of the adsorption isotherms. Table 4 lists all of the parameters used in the calculation. A small change in these surface complexation parameters will result in a change in the overall shape of the calculated results. Therefore, reasonable values of these parameters were in a relatively narrow range over which they could be adjusted. Comparing the available values of the parameters taken from the literature to the estimated values, suggests that the agreement is quite good. The actual experimental conditions, i.e., the pH, ionic strength, and equilibrium metal concentration, were input as the initial parameters in the calculation, and the calculated results of metal adsorbed on humic acid were plotted together with the experimental results. Modeling Results. The calculations were carried out under the same conditions as those used in the experiments. The calculated results of the metal adsorption as a function of pH at two different ionic strengths are shown in Figures 2-4 as lines. The model results have successfully predicted the adsorption equilibrium and, more importantly, the tendency of changes in the metal adsorption in the range of pH tested in this study. This certainly can be partially attributed to the optimization process of the surface complexation constants as previously stated. It may be worth while to point out that better agreements between the calculated and experimental results are achieved at higher ionic strength (I ) 0.8 M), which may be explained by the compression of the double layer at higher ionic strength. Because of the compression, the HA surface may become more rigid and electric charges delocalized more evenly. Therefore, the fundamental assumption of double layer structure in the model becomes more reasonable. The calculated results of the adsorption isotherms are shown as lines in Figure 5. The agreement between the experimental (points) and calculated (lines) results are acceptable. In the case of Pb, a relatively large error between the calculated results and the experimental results is observed at high concentrations of the metal. A possible explanation is that in order to simplify the calculation used in the theoretical model, all of the metal ions and the hydrolyzed ions in the form of MeOH+ were assumed to adsorb directly on the HA surface. This assumption might not hold for metal ions with large hydration radii because it would be difficult for these hydrated ions to penetrate into a compact layer. Comparing the results of the adsorption isotherm of Cu in Figure 5 and the adsorption of Cu as a function of pH in Figure 4, it is observed that Cu shows a different adsorption pattern to that of the other two metals. A possible reason may be due to bidentate adsorption based on the fact that the Cu2+ ion can be more readily complexed to electron donors. Effect of Ionic Strength. The effect of ionic strength on the adsorption of Cu on humic acid predicted by the model is shown in Figure 6. A pH of 6.0 and a metal concentration of 1.0 × 10-5 mol/L were assumed. This is very close to the actual experimental conditions. Because the effect of ionic strength was examined at only two different ionic strengths (0.02 and 0.8 M) by measuring the adsorption of metals on humic acid as a function of pH, there were only two points available to compare to

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Langmuir, Vol. 16, No. 8, 2000 3907

Figure 5. Adsorption isotherm of metal ions on humic acid. The points represent the experimental results. The initial concentrations of metals were set as a series from 3 × 10-6 to 8 × 10-5 M and the humic acid concentration was 0.0468 g/L. The lines represent the results of model calculations which were carried out at a fixed pH of 6.0 and an ionic strength of 0.1 M. Table 4. Constants and Parameters Used in Model Calculation of Metal Adsorption on Humic Acid range of literature values (log K)

constants int KH-S 1 int KH-S 2 int KH-HS 2 int KMe-S 1 int KMe-S 2 int KMeOH-S 1 int KMeOH-S 2

3.4-5.7a 8.1-9.0a 2.85-2.98a Pb Cdb 3.04-5.1 N/Ac 4.5-4.7 N/A N/A N/A N/A N/A

other params r F C

Cub 3.2-5.9 8.4-9.9 N/A N/A

literature values nma

0.32 700-1700 kg/m3 a 140 µF/cm2

estimated value for model calculation (log K)

Cd 3.12 4.60 3.95 5.50

2.75 7.5 1.8 Pb 3.40 8.75 4.20 9.50

Cu 3.60 7.60 4.55 8.50

value used 0.32 nm 1200 kg/m3 140 µF/cm2

a Data from de Wit, et al.17,18 b Data from Benedetti, et al.20 and van Riemsdijk, et al.22 c Data not available.

Figure 6. Effect of ionic strength on the adsorption of Cu on humic acid. The line represents predicted results by the model assuming a pH of 6.0 and a metal concentration of 1.0 × 10-5 mol/L.

the theoretical results. Comparing the model results and the experimental results at an ionic strength of 0.02 and 0.8 M, it can be seen that the agreement is quite good. It is observed from Figure 5 that when the ionic strength is

lower than 0.01 M, the metal adsorption is very sensitive to changes in the ionic strength. When the ionic strength is higher than 0.1 M, the change in ionic strength will cause a relatively small change in the metal adsorption. The Calculated Distribution of Surface Species as a Function of Solution pH. Figure 7 shows the distribution of surface species as a function of solution pH. A constant ionic strength and metal concentration is assumed in the calculations for each metal. Because of the similarity and highly dependent nature of the model assumptions, the modeling results of the distribution of the surface species are shown for Pb only at two ionic strengths of 0.02 and 0.8 M. Comparing the results shown in Figure 7, it can be seen that at low pH, the S1H are the dominant species. As the pH is increased, the concentration of negatively charged S1 increases due to the dissociation of S1H. Because of the relatively high adsorption of metal at a lower ionic strength on HA, there are more S1 group attached to the metals. For this reason the concentration of S1 is relatively lower at an ionic strength of 0.02 M than at an ionic strength of 0.8 M. The same explanation applies to the weak acid group. However, because of its low concentration it is not obvious from the figure. At a higher pH when more S2H groups dissociate into S2, its role in complexing the metal ions becomes more significant due to its high complexation ability. There are relatively more PbOH+ species adsorbed at a high pH (Figure 7A). This can be explained by the hydrolysis of Pb2+. The calculated results of the hydrolysis of Pb2+ at a pH of about 6 shows that more than 50% of the Pb2+ is hydrolyzed to PbOH+. Similar patterns for the distribution of surface species are observed for Cu and Cd, and the detailed discussion is omitted. Discussion It was observed experimentally that the strength of binding of the three metals should be in the sequence of Pb > Cu > Cd. Of the three metals studied, Cd is the metal which is the most difficult to be complexed by HA. This result is consistent with the sorption efficiency order Hg ) Fe ) Pb ) Al ) Cr ) Cu > Cd > Zn > Ni > Co > Mn as measured at a pH of 5.8 by Kerndorff and Schnitzer.5 However, a comparison of the intrinsic equilibrium

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Liu and Gonzalez

Figure 7. Surface speciation of Pb adsorption on humic acid at ionic strengths of (A) I ) 0.02 M and (B) I ) 0.8 M as a function of solution pH.

constants used in the model calculation, show that the int for the three metals is not as differences between KMe-S 1 int large as that for KMe-S2. This effect may not be significant at low pH due to the protonation of the functional groups. But at a higher pH, this means that the weak acid adsorption sites become a dominant factor in determining the metal binding sequence. The difference between Pb and Cu may not be very significant considering the uncertainty in the estimation. However, all the parameters obtained for Cd are considerably lower than those observed for Pb and Cu. Kinniburgh et al.21 obtained similar results by using the nonideal competitive adsorption (NICA) -Donnan model to fit the adsorption data of metal ions on purified peat HA. In the modeling, two general terms, i.e., strong acid and weak acid, were used to describe the primary functional groups on HA to avoid a detailed structural discussion. The possibilities exist that other functional groups might be involved in the metal adsorption or proton dissociation/binding. However, carboxylic -COOH and phenolic -COH groups are believed to be the most important adsorption sites on HA.4,5,6,21 From the titration data, de Wit et al.18 assigned the larger of the two peaks in the log K range 3-4 to carboxylic groups and the peak

positioned at log K ) 8-9 to phenolic type groups. Correspondingly, the primary functional group is the carboxylic group in S1 and the phenolic group in S2. Because of the iterative nature of the intrinsic constants assigned to these sites, these parameters are to some extent lumped together and do not exclude the possible participation of other functional groups in the metal adsorption or proton binding/dissociation. In the present stage, it is desirable to keep the model as simple as possible and in line with the experimental observations. If more adsorption sites or functional groups are revealed in future structural studies of HA molecules, there would be no difficulty in incorporating them into the model. Recent developments in theoretical modeling reactions of surface adsorption have a tendency to take the heterogeneous properties of the particle surface into consideration.17-22,32-33 These models successfully simulate the proton binding of HA. Although this consideration has a strong conceptual and mathematical base considering the (31) Narkis, N.; Rebhun, M. Am. Water Works Assoc. J. 1975, 67, 101. (32) Nederlof, M. M.; Van Riemsdijk, W. H.; Koopal, L. K. J. Colloid Interface Sci. 1990, 135, 410. (33) Nederlof, M. M.; de Wit, J. C. M.; Van Riemsdijk, W. H.; Koopal, L. K. Envrion. Sci. Technol. 1993, 27, 846.

Modeling Adsorption on Purified Humic Acid

complexity of the HA molecule, a satisfactory method to establish the distribution functions for metal ions is not fully developed. An available discussion is limited to a very simple case based on the assumption that the nonideality function takes on an explicit simple form.19 This may become more difficult for the heavy metal ions because of their more complicated properties such as hydrolysis and complexation. Applying the Donnan model to smaller HA molecules should be avoided when dealing with smaller HA molecules which are more significant in the spectrum of NOM.24 The subdivision into each of two primary functional groups in Tipping’s model V is somewhat arbitrary, and an empirical factor P had to be introduced to correlate the proton charge to ionic strength. Mathematically, for a small molecule such as HA, assuming an evenly distributed charge density inside the HA molecule is essentially the same as assuming that all charges are located at the HA surface. When it is assumed that the metal ions (as well as their hydrolysis products) adsorb directly on the HA surface, the total surface charge density of HA is determined by both the proton binding/ dissociation and the metal adsorption. Essentially, the Donnan model assumes HA as a polyelectrolyte gel with charges distributed both on the HA surface and inside a gel phase.20 Whether the adsorbed ions stay on the surface or diffuse into the inner layer bears little effect on the equilibrium calculation provided that a fixed radius is assumed for HA. While no single model of metal-HA interaction has yet proven to be superior, the fact that the

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intrinsic complexation constants obtained by the surface complexation and double layer model can be used to predict the competitive nature of the interactions among the metal ions presents a powerful argument for the use of the model. The assumption of two discrete adsorption sites on the HA molecule, although somewhat simplified, is consistent with the well-established characterization methods of humic materials. If more HA structural data become available, more adsorption sites can be added into the model used in this research without any difficulty. During the calculation exercises, it was found that when the ionic strength was too low, for example lower than 10-3 M, the iteration might not converge to a point. One of the possible reasons may be that in the ionic strength calculation, the concentration of protons in solution was neglected based on the fact that the pH of interest was usually higher than 3. However, the error caused by this omission becomes greater when the pH is high and the ionic strength is low. Under these conditions, the computer program will have difficulties in finding the point of overall charge neutrality. Acknowledgment. The authors wish to acknowledge financial support from US Department of Energy as a part of Tulane/Xavier joint program of Hazardous Wastes in Aquatic Environment of the Mississippi River Basin. LA990607X