Equilibrium Modeling of Lead Adsorption onto a “Red Soil” as a

“Red soils” are silty-clay materials typical of Central Italy, with a high content of iron and aluminum (hydro)oxides, resulting from dissolution ...
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1946

Ind. Eng. Chem. Res. 2002, 41, 1946-1954

Equilibrium Modeling of Lead Adsorption onto a “Red Soil” as a Function of the Liquid-Phase Composition Marco Petrangeli Papini,* Annalisa Bianchi,† Mauro Majone,‡ and Mario Beccari§ Department of Chemistry, University “La Sapienza”, P.le Aldo Moro 5, 00185 Rome, Italy

“Red soils” are silty-clay materials typical of Central Italy, with a high content of iron and aluminum (hydro)oxides, resulting from dissolution of carbonates and mixed with particles of volcanic origin. These soils are becoming interesting because of their large availability in Central and Southern Italy and large attenuation capacity with respect to heavy metals due to their geochemical characteristics (high surface area, cation-exchange capacity, and pH). Thus, their possible use as a daily landfill coverage or as a low-cost sorbent material is under evaluation. Lead adsorption, as representative of heavy metals in polluted streams, has been studied as a function of the composition of the liquid phase. Different background electrolytes (NaClO4, NaNO3, NaCl, and CH3COONa) and different pHs (4-7) were used in order to obtain different lead speciation in the liquid phase. Lead adsorption occurred not only to the account of free lead, and positively charged complexes (PbNO3+, PbCl+, and CH3COOPb+) strongly contributed to the total metal removal. An adsorption model was developed based on the surface complexation concept, which can be proposed as a general approach for characterizing metal adsorption on heterogeneous natural sorbents as a function of the composition and pH of the liquid phase. The model was characterized by the presence of two surface complexation and one ion-exchange sites onto which the different lead species can be sorbed. A maximum sorption capacity of 21.7 mg g-1 was calculated for lead and gives to the red soil a particular interest as a possible alternative low-cost sorbent. Introduction Heavy-metal contamination is recognized as a priority problem at hazardous waste sites. The contamination by metals can occur in both soils and groundwater as a result of industrial activities such as mining, metal plating, tanneries, and petroleum refining.1-3 Another source of groundwater metal contamination is related to the migration of leachates from uncontrolled landfill sites. Because of their strong complexing capacity (because of the high concentration of organic and inorganic ligands), metals can be strongly extracted by the dumped wastes and move easily to the groundwater.4 With respect to the other categories of contaminants, heavy metals are particularly dangerous because they are not biodegradable and accumulate in living organisms. Available technologies for heavy-metal-contaminated waste stream and soil treatments are usually carbon adsorption, ion exchange, precipitation, membrane filtration, reverse osmosis, and solidification/stabilization. Sorbent-based processes are probably the most used, although the cost of substrate materials and regeneration is a limiting factor. Thus, great attention is given to the characterization of the sorption properties of alternative low-cost materials that range from natural sorbent phases to dead biomass.5 In this regard, “red soils”, a widely distributed type of soils classified as Ultisols under the U.S. system of soil taxonomy, represent an interesting natural sorbing * Corresponding author. E-mail: marco.petrangelipapini@ uniroma1.it. Tel.: +390649913646. Fax: +3906490631. † E-mail: [email protected].: +390649913716. ‡ E-mail: [email protected]. Tel.: +390649913646. § E-mail: [email protected]. Tel.: +390649913651.

material. They are silty-clay soils derived from a variety of parent materials usually characterized by a high content of iron and aluminum (hydro)oxides, resulting from dissolution of carbonates and mixed with particles of volcanic origin. Because of their large availability in Central and Southern Italy (where uncontrolled landfills are still largely present), these types of soils are becoming interesting from the environmental point of view in our country. On the other hand, their geochemical characteristics [high surface area, cation-exchange capacity (CEC), and pH] cause a large attenuation capacity with respect to heavy metals, which might result in interest in their use as a daily landfill coverage or as a low-cost sorbent material. Usually, sorption properties of solid phases for technological applications are studied in simplified conditions (pure aqueous phase with a single dissolved metal) and represented by empirical or semiempirical adsorption isotherms (such as Langmuir- and/or Freundlichtype equations), with their main advantages being simplicity of use, ease of parameter optimization, and possibility of comparison by a few parameters (two or three at the maximum).6,7 The main drawback of this approach is that the adsorption behavior is uneasily extrapolated to conditions different from those used in the experiments. This aspect becomes relevant especially when sorbent has to be used with contaminated liquid phases of complex composition where simultaneous processes (such as metal complexation in the liquid phase and competition of different species for adsorption sites) can strongly alter the extent of metal removal.8-10 Moreover, the heterogeneity of the sorbent material, as is always the case for naturally occurring solid phases, cannot be easily taken into account by these kinds of models.

10.1021/ie010594u CCC: $22.00 © 2002 American Chemical Society Published on Web 03/14/2002

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In the past decades, a lot of scientific work has been done about the development of mechanistic adsorption models, most of which are based on the surface complexation approach.11-15 Mechanistic models have been developed and tested mostly on pure phases (such as clays or oxides), where specific and quantitative information is available on the structure of the liquid/solid interface. However, the general approach is nowadays applied in the description of the adsorption properties of heterogeneous sorbent material.16-18 The aim of this paper was thus to study and to model the adsorption properties of a selected red soil by choosing lead as representative of heavy metals. Adsorption tests were carried out with different background electrolytes (NaClO4, NaNO3, NaCl, and CH3COONa) and different pHs (4-7) in order to obtain different lead speciation in the liquid phase. The development of the adsorption model was based on the so-called “generalized composite (GC) approach” of surface complexation.

Table 1. Formation Reactions and Equilibrium Constants Used for Lead Speciation in the Liquid Phase from the Mineql+ Database (Ionic Strength ) 0 mol L-1, T ) 25 °C)

Materials and Methods

and natural pH without any adjustment) was flushed by an “open-loop” configuration at constant flow rate and for an optimized time (preliminary experiments). At the end of this phase, the solution was quantitatively removed from the column by gravity (residual humidity < 2%). This ”washing” phase was adopted in order to make initial conditions reproducible with respect to the solid phase; all of the natural presorbed ions were removed, and the soil was thus equilibrated with the background electrolyte. (b) pH equilibration: The chosen solutions (the same composition of the adsorption test) were recycled through the columns (“closed-loop” configuration), and the pH was corrected to the chosen value until the system reached the equilibrium. The total solution volume for each column was 60 mL. (c) Lead adsorption: A total of 50 mL of the solution in each of eight reactors was substituted with the same quantity of a solution of the same composition but with a prechosen concentration of total dissolved lead. Then the solutions were recycled through the columns (closedloop configuration) for 24 h; the pH was periodically measured and corrected if necessary. After the system had reached the equilibrium, the total lead concentration was determined by ICP-AES directly on the liquid phase. Sorbed lead was calculated by the difference between the initial and equilibrium total dissolved concentrations. Theoretical Speciation. Lead speciation for the different solution compositions was calculated by the Mineql+ speciation code.21 Table 1 reports all of the formation reactions used for the calculations with their corresponding equilibrium constants (25 °C, ionic strength ) 0 mol L-1). Equilibrium constants are corrected by the speciation code for the actual ionic strength at the used experimental conditions (0.1 mol L-1). Input values were total component concentrations and equilibrium pH. Table 2 reports the theoretical speciation at the different solution composition as calculated by the Mineql+ code. Only species more abundant than 1% are reported. No solid precipitation was predicted under the adopted experimental conditions. Because of the high concentration of the background electrolytes, lead speciation was independent of the total lead concentration in the adopted experimental range. Data Regression. Lead adsorption at the different conditions was represented by an adsorption model

Solid Phase. The solid phase (Italian red soil) was collected in the basin of the Amaseno River (Italy), airdried, and sieved down to a size fraction of less than 590 µm before the adsorption tests. Preliminary experiments19 have shown that this size fraction behaved similarly to the raw material with respect to the adsorption. Qualitative X-ray diffraction (XRD) analysis revealed the presence of different clays (mainly illite and kaolinite), (hydr)oxides (goethite), and calcite. The specific surface area was 56.8 m2 g-1 as measured by the Brunauer-Emmett-Teller method. The CEC was 9 ( 2 mequiv/100 g as measured by the BaCl2 method (three replicates). The soil pH was measured according to standard methods, and results were 8.53, 7.41, and 7.99 for H2O, 0.1 M KCl, and 0.01 M CaCl2‚2H2O solutions, respectively. Total carbon was measured by an automatic analyzer (Strho¨hlein Instrument), and the result was 1.3 ( 0.2% (made up of 0.3 ( 0.1% and 1.0 ( 0.1% of total inorganic and organic carbon, respectively). The total metal content was determined by an inductively coupled plasma atomic emission spectrometer (ICP-AES Varian Liberty 150) with ultrasonic nebulization (Cetac U-5000 AT+), after microwave mineralization (Milestone MLS 1200 mega), and results were as follows: Al, 13%; Fe, 5%; Ca, 1.5%; Mg, 0.5%; K, 0.2%; Mn, Na, Zn, Cu, Ni, and Pb at trace level (between 10-3 and 10-4%). Adsorption Tests. The adsorption tests were performed by the flow-through reactor setup20 at several total lead concentrations and solution compositions. Four different background electrolytes (NaClO4, NaNO3, NaCl, and CH3COONa at 0.1 mol L-1 at pH 6.0) and different pHs (4-7 in CH3COONa solutions) were chosen in order to obtain different dissolved lead speciation. The experimental system was composed of eight reactors (Bio-Rad Econo Column, 10 cm length, 1.5 cm internal diameter) fed by a multihead peristaltic pump (Masterflex L/S) with the chosen solution stored in eight polyethylene bottles maintained under magnetic stirring and constant temperature. The experimental procedure has been previously optimized19 and was as follows: (a) Soil preequilibration: A known amount of soil (0.500 ( 0.005 g) was placed in each reactor, and the liquid phase (with the background electrolyte chosen for the subsequent adsorption test, at the prechosen concentration

log K Pb2+ + H2O S Pb(OH)+ + H+ Pb2+ + 2H2O S Pb(OH)2(aq) + 2H+ 2Pb2+ + H2O S Pb2(OH)3+ + H+ Pb2+ + 3H2O S Pb(OH)3- + 3H+ Pb2+ + 4H2O S Pb(OH)42- + 4H+ 3Pb2+ + 4H2O S Pb3(OH)42+ + 4H+ Pb2+ + NO3- S PbNO3+ Pb2+ + Cl- S PbCl+ Pb2+ + 2Cl- S PbCl2(aq) Pb2+ + 3Cl- S PbCl3Pb2+ + 4Cl- S PbCl42CH3COO- + H+ S CH3COOH CH3COO- + Na+ S CH3COONa Pb2+ + CH3COO- S CH3COOPb+ Pb2+ + 2CH3COO- S (CH3COO)2Pb Pb2+ + 3CH3COO- S (CH3COO)3PbPb2+ + 4CH3COO- S (CH3COO)4Pb2-

-7.710 -17.120 -6.360 -28.060 -39.699 -23.880 1.170 1.600 1.800 1.699 1.380 4.760 -0.180 2.870 4.080 3.590 3.400

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Table 2. Lead Speciation in the Liquid Phase for Different Solution Compositions As Calculated by the Mineql+ Code (Equilibria Are from Table 1)

Pb2+ Pb(OH)+ Pb(NO3)+ PbCl+ PbCl2 Pb(CH3COO)+ Pb(CH3COO)2 Pb(CH3COO)3a

NaClO4 (pH ) 6.0)

NaNO3 (pH ) 6.0)

NaCl (pH ) 6.0)

CH3COONa (pH ) 4.0)

CH3COONa (pH ) 5.0)

CH3COONa (pH ) 6.0)

CH3COONa (pH ) 7.0)

98.8 1.2

64.7

38.5

11.1

2.8

2

1.9

72.8 16.0

56.0 40.2

50.4 46.1 1.4

49.6 46.7 1.4

34.5 55.3 5.3

Only species greater than 1% are reported.

Figure 1. Experimental lead adsorption at pH ) 6.0 for different background electrolytes (0.1 mol L-1) as a function of the total equilibrium lead (a) and free equilibrium lead activity (b) in the liquid phase. Solid lines are the corresponding Langmuir-Freundlich isotherms calculated by the nonlinear regression of the single sets of data (univariate regression).

presented in the Results and Discussion section. Model adjustable parameters were optimized by simultaneous multivariate nonlinear least-squares fitting of all of the experimental results by means of a commercial software.22 The minimization procedure was based on the Levenberg-Marquardt algorithm, and the goodness of fit was evaluated by the coefficient of determination which measures the fraction of the total variance accounted for by the model. Comparison of models with different numbers of parameters was based on the calculation of the model selection criterion, which relates the coefficient of determination to the number of parameters (or the number of degrees of freedom).22 Results and Discussion Adsorption as a Function of Solution Composition. To investigate the effect of lead speciation on the adsorption capacity of the natural sorbent material, different background electrolytes and pHs were chosen to obtain a large range of species distribution. As reported in Table 2, from the results of theoretical speciation, the free dissolved lead concentration ranged from 99% in the case of the NaClO4 solution to less than 2% in the CH3COONa solution. Depending on the solution composition, different aqueous complexes are formed with positive [Pb(NO3)+, PbCl+, and Pb(CH3COO)+], negative [Pb(CH3COO)3-], and neutral [PbCl2(aq) and Pb(CH3COO)2] charge. Moreover, speciation in the CH3COONa solution is strongly dependent

on pH, and the lead distribution significantly changes especially in the range of pH ) 4-6. Figure 1a reports the results of the adsorption experiments carried out with the different background electrolytes at pH ) 6.0 and constant ionic strength (0.1 mol L-1) in terms of sorbed lead as a function of total dissolved equilibrium lead in solution. For a better understanding and comparison of the experimental behavior, single sets of data are reported along with the corresponding calculated isotherms according to the Langmuir-Freundlich equation:23

Q)

MKCn 1 + KCn

(1)

where Q is the lead concentration in the solid phase (mmol/g) and C is the equilibrium lead concentration in the liquid phase (mmol L-1), whereas M, K, and n are the maximum adsorption capacity, the affinity constant, and the heterogeneity index, respectively. It has to be stressed that, at this stage, no physical significance was attributed to the adjusted parameters. The composition of the solution has a strong effect on the adsorption capacity of the red soil. For the entire experimental range of lead concentration, the extent of the adsorption is greater in the NaNO3 solution and then it decreases moving to NaClO4, NaCl, and CH3COONa, respectively. Moreover, the experimental lead adsorption in CH3COONa seems to follow a pattern

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different from those in other electrolytes. Indeed, at the highest lead concentration adsorption in CH3COONa is significantly lower even if the isotherm seems to be already in a “saturation” range (calculated M according to Langmuir-Freundlich ) 0.020 mmol g-1). On the contrary, adsorption isotherms in NaClO4, NaNO3, and NaCl solutions, even though affected by the background electrolyte at lower lead concentration, seem to tend toward a common Langmuir-type maximum (calculated M according to Langmuir-Freundlich ) 0.065, 0.063, and 0.050 mmol g-1 respectively for NaClO4, NaNO3, and NaCl) which significantly differs from that observed in the case of the CH3COONa solution. This behavior suggests that lead adsorption in a sodium acetate solution involves a different kind of surface site. As was already discussed in a previous work (where NaNO3 experiments were not available),19 the lead adsorption onto the red soil is not directly linked to the concentration of free lead, as calculated by the theoretical speciation (Figure 1b). In this case, for the same equilibrium free lead activity, lead removal in a perchlorate solution (all lead in free form) is lower with respect to nitrate, chloride, and acetate (where lead is also present in complexed forms). The observed behavior strongly supports that species other than free lead can contribute to lead adsorption at the surface, with different affinities with respect to free lead. In this regard, several authors have already observed an increase/decrease in metal removal due to possible adsorption of charged complexes or ternary surface complexes formation,24-27 mostly dealing with metal adsorption in the presence of organic ligands. Few works deal with inorganic ligands, generally limited to chloride.28,29 Barrow et al. (1981)28 observed an increase of lead adsorption onto goethite in NaCl with respect to a NaNO3 solution. Modeling of lead removal was possible only considering both free lead and PbCl+ as sorbing species. Bargar et al. (1998)29 by the use of an advanced spectroscopic technique (XAFS) revealed the presence of ternary Pb(II)-chloro surface complexes in the goethite system specifically adsorbed as innersphere species. Thus, depending on the relative affinity of the charged metal complexes for the surface, the presence of complexing agents in the liquid phase can affect significantly the total extent of the removal. Adsorption Modeling. The development of the adsorption model able to represent the experimental behavior at the different experimental conditions followed the so-called “GC” approach based on the surface complexation model.16 The GC approach is generally used when dealing with a heterogeneous surface, as it is in the case of the red soil. When the composition of the solid phase is too complex to be represented quantitatively as the sum of individual contributions of wellrecognized phases, the surface reactivity can be described in terms of generic surface functional groups, the number and stoichiometry of which is determined only by fitting experimental data. On the basis of the available information, a set of reasonable reactions is proposed and new reactions are added until the model is able to represent the experimental behavior without losing significativity (i.e., too large degree of freedom). This approach has been successfully applied to simulate Zn2+ adsorption by sediment16 and to describe the adsorption of lead as a function of the total lead concentration and pH onto a natural porous media.30 The development of the adsorption model was based

on the characterization of the solid phase (Materials and Methods section) and the experimental adsorption behavior observed in the different electrolytes (adsorption as a function of a solution composition section). XRD analysis, the high CEC, the influence of electrolytes in determining the soil pH along with the low total organic carbon, and significant percentages of total Al and Fe suggested that at least two types of sites characterize the surface, either with surface complexation (justified by the occurrence of different oxides of iron and aluminum) or cation-exchange nature (due to the fraction of clays such as illite and kaolinite). Moreover, the experimental isotherms have clearly indicated that adsorption was due to both free lead and charged complexes. The particular adsorption pattern observed in a sodium acetate solution suggested the presence of one more adsorption site. After several adjustments (data not reported), the description of the experimental behavior with the four background electrolytes at the same pH (pH ) 6.0) and with sodium acetate at four different pHs (pH ) 4.0, 5.0, 6.0, and 7.0) required at least the presence of three sites, two of which act as surface complexation and the third which acts as cation exchange. The adsorption onto all sites was initially considered possible for all charged species occurring in the liquid phase, as determined by theoretical speciation, and competition among them on each site was taken into account. The minimum number of reactions needed to represent the system was chosen on the basis of statistical analyses by comparing the goodness of fit with the number of parameters (model selection criterion). The final formulation of the model is as follows: (i) A surface complexation site tS where Pb2+, Pb(NO3)+, PbCl+, and H+ can be sorbed with a competitive mechanism, according to the following equilibria:

tS + Pb2+ S tSPb

KtSPb )

{tSPb} {tS}[Pb2+]y2

tS + PbNO3+ S tSPbNO3 KtSPbNO3 )

tS + PbCl+ T tSPbCl

tS + H+ T tSH

{tSPbNO3} {tS}[PbNO3+]y1

KtSPbCl )

KtSH )

(2)

(3)

{tSPbCl} {tS}[PbCl+]y1 (4) {tSH}

{tS}[H+]y1

(5)

(ii) A second surface complexation site tS1 where Pb(CH3COO)+ and H+ can be competitively sorbed, according to the following:

tS1 + CH3COOPb+ T tSCH3COOPb {tSCH3COOPb} KtS1CH3COOPb ) (6) {tS}[CH3COOPb+]y1 tS1 + H+ T tS1H

KtS1H )

{tS1H} {tS1}[H+]y1

(7)

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(iii) A cation-exchange site X where Pb and Na undergo cation exchange, according to the following:

Table 3. Adjustable Parameters of the Adsorption Model As Calculated by Means of Nonlinear Multivariate Regression of All Lead Adsorption Data

2XNa + Pb2+ T X2Pb + 2Na+ + 2

KNaPb )

{X2Pb}[Na ] y1

2

{XNa}2[Pb2+]y2

(8)

In all expressions y1 and y2 are the activity coefficients for a monovalent and divalent dissolved cation, respectively, as calculated by the extended Davies equation:

log yi ) -AZi2

[

]

I2 - 0.3I 1 + xI

(9)

a

adjustable param

units

estimates

Stot S1tot CECa KtSPb KtSPbNO3 KtSPbCl KtSH KtS1CH3COOPb KtS1H KNaPb

mmol g-1 mmol g-1 mmol g-1 L mmol-1 L mmol-1 L mmol-1 L mmol-1 L mmol-1 L mmol-1 g L-1

0.0445 0.0153 0.0450 1.38 × 104 3.32 × 104 5.62 × 103 2.41 × 104 4.30 × 103 2.24 × 103 2.09 × 107

Fixed value.

where A ) 1.82 × 106(DT)-3/2, D ) dielectric constant for water, T ) temperature (K), Zi ) ionic charge, and I ) solution ionic strength. Considering the constant high ionic strength, activities of charged species were not corrected for electrostatic interactions.17 For each site, the mass balance was

{tS}tot ) {tSfree} + {tSPb} + {tSPbNO3} + {tSPbCl} + {tSH} (10) {tS1}tot ) {tS1free} + {tS1CH3COOPb} + {tS1H} (11) CEC ) {XNa} + 2{X2Pb}

(12)

Combining the mass action expressions with the correspondent mass balances allowed one to represent the contribution of each possible sorbing species to the overall lead adsorption in the form of competitive Langmuir equations:

tSPb ) StotKtSPb[Pb2+]y2/{1 + KtSPb[Pb2+]y2 +

KtSPbNO3[Pb(NO3)+]y1 + KtSPbCl[PbCl+]y1 + KtSH[H+]y1} (13)

tSPbNO3 ) StotKtSPbNO3[Pb(NO3)+]y1/{1 + KtSPb[Pb2+]y2 + KtSPbNO3[Pb(NO3)+]y1 + KtSPbCl[PbCl+]y1 + KtSH[H+]y1} (14) tSPbCl ) StotKtSPbCl[PbCl+]y1/{1 + KtSPb[Pb2+]y2 + KtSPbNO3[Pb(NO3)+]y1 + KtSPbCl[PbCl+]y1 +

KtSH[H+]y1} (15) tS1CH3COOPb ) S1totKtS1CH3COOPb[CH3COOPb+]y1 1 + KtS1CH3COOPb[CH3COOPb+]y1 + KtS1H[H+]y1 (16) Considering also the presence of the cation-exchange site, the total adsorption was expressed by

QPb total ) tSPb + tSPbNO3 + tSPbCl + tS1CH3COOPb + X2Pb (17) which was used to fit all of the experimental sorption data.

Figure 2. Correlation between experimental and calculated lead adsorption according to the adsorption model (after multivariate nonlinear regression of all of the experimental data; parameters are from Table 3).

Optimization of model parameters was obtained by simultaneous nonlinear least-squares regression of all experimental adsorption data (multivariate regression), and their values are reported in Table 3. Independent variables were the concentration of all of the possible sorbing species as calculated by theoretical speciation at the different experimental conditions [Pb2+, Pb(NO3)+, PbCl+, CH3COOPb+, and H+]. Considering the high number of adjustable parameters (nine), the model could be too flexible and multiminimal points could be reached by the multivariate regression (i.e., different sets of parameters, with the same goodness of fit, could be obtained depending on the starting guess values). To avoid this problem, the model was initially used to fit the NaClO4 adsorption data, where only free lead and proton were the sorbing species. The adjusted parameters where then used as guess values to fit simultaneously the NaClO4 and NaNO3 adsorption data. The same procedure was then applied to NaCl and CH3COONa adsorption data. In this way it was possible to obtain good estimates of specific parameters to be used as guess values in the final multicomponent regression. Moreover, we have chosen to use all of the experimental data for the multivariate regression because of the higher number of adsorption data relative to free lead, which was present in all of the used background

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Figure 3. Comparison between experimental lead adsorption and calculated behavior according to the optimized model (parameters are from Table 3) at pH ) 6.0 for different background electrolytes: (a) NaClO4, (b) NaNO3, (c) NaCl, (d) CH3COONa. Lines are total adsorption and individual contributions due to the different adsorption sites. Stacked bars show lead speciation in the liquid phase for each condition.

electrolytes. This allowed one to obtain a more precise estimate particularly for KtSPb and KNaPb other than Stot. The overall coefficient of determination was 0.992, indicating a good correlation as confirmed by Figure 2, where a correlation between calculated and experimental Pb sorption is reported. The model is able to represent lead adsorption in all of the experimental conditions without any systematic deviation. The model performance can be evaluated for any single isotherm, as obtained in the different experimental conditions. Figures 3 and 4 report the comparison between experimental data and calculated behavior at fixed pH for any background electrolyte (Figure 3; pH ) 6.0, NaClO4, NaNO3, NaCl, and CH3COONa, respectively) and at different pHs (Figure 4; pH ) 4.0, 5.0, 6.0, and 7 in CH3COONa, respectively). For each condition the figures include the theoretical speciation of lead in the equilibrium solution as calculated on the basis of the total composition (stacked bars). Despite some small deviations observed in CH3COONa solutions, each set of data is well described by the model. The contribution of the single species and different mechanisms to the total extent of lead removal can be

better evaluated by the speciation at the solid/liquid interface which can be calculated by the adjusted model. It is important to remember that we refer to species which were not directly measured but calculated by the model. However, the calculated surface speciation is a useful tool to verify the reasonability of the model prediction and to clarify the relevance of the single mechanisms. For this purpose, Figures 3 and 4 report, along with the experimental and calculated total lead adsorption, the calculated adsorption onto the three proposed sites of the different species. The relative contribution to overall adsorption depends on both the actual concentration of each possible lead species in the liquid phase (Table 2 and stacked bars in Figures 3 and 4) and their affinities for the adsorption sites (K values as optimized by data regression; Table 3). Considering Figure 3 (all sets at pH ) 6.0), it is noteworthy to observe that the relative contribution of free lead adsorption on surface complexation sites decreases from NaClO4 to a NaCl, NaNO3, and CH3COONa solution in favor of positively charged lead complexes. As an example, if we consider the fixed value of the total equilibrium lead in a solution of 8 ×

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Figure 4. Comparison between experimental lead adsorption and calculated behavior according to the optimized model (parameters are from Table 3) in CH3COONa at different pHs: (a) 4.0, (b) 5.0, (c) 6.0, (d) 7.0. Lines are total adsorption and individual contributions due to the different adsorption sites. Stacked bars show lead speciation in the liquid phase for each condition.

10-3 mmol L-1, adsorption onto site tS is quantitatively due to free lead (tSPb) in a perchlorate solution, whereas in chloride and nitrate solutions, free lead accounts for 44.6 and 26.6% of adsorption onto site tS, respectively (with the remaining part being due to adsorption of corresponding charged complexes). Lead adsorption in an acetate solution is mostly due to site tS1 where only charged CH3COOPb+ can be sorbed. Even though ion exchange is necessary to well represent the experimental behavior, its extent is always small with respect to the surface complexation mechanism. Despite the high exchange constant (see Table 3), sorbed lead onto ion-exchange site X is much less than the measured CEC value (0.045 mmol g-1) because of the sodium concentration in the liquid phase (0.1 mol L-1), quite higher than the dissolved lead in all of the experimental range. The pH affects lead adsorption in the presence of CH3COONa in two different ways: on the one hand, it strongly affects lead speciation in the liquid phase (see Table 2 and stacked bars in the single graphs) changing the concentration of species that can sorb with different affinities onto different sites; on the other one, proton

competes with the other sorbing species for all of the adsorption sites. Indeed, if we consider the K values relative to reactions (5) and (7) which account for the weak acid characteristics of the surface complexation sorption sites, we obtained 7.3 and 6.3 as pK acidity values for sites tS and tS1, respectively. In this regard, it is noteworthy to observe that the calculated pK’s fall into the range of values available in the literature for surface hydroxyl groups in pure oxides31 representative of phases (aluminum, iron, and silicon oxides) occurring in natural solid phases and which are assumed to control the extent of heavy-metal adsorption. This means that, in the experimental range of pH, proton competition is a relevant process governing the extent of lead adsorption. Conclusions Lead adsorption properties of an Italian red soil have been studied as a function of liquid composition, investigating lead removal for a large spectrum of speciation in the liquid phase. Positively charged complexes

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(PbNO3+, PbCl+, and CH3COOPb+) strongly contributed to the total adsorption other than free lead ion. This is particularly relevant when adsorption has to be predicted in the presence of several complexing agents, either organic or inorganic, as it is for landfill leachates32 or contaminated waste streams. An adsorption model was developed based on the surface complexation concept, which can be proposed as a general approach for characterizing metal adsorption on heterogeneous natural sorbents in a large range of experimental conditions. Considering the high heterogeneity of the red soil, the surface complexation approach was not applied as a mechanistic description of all of the possible solid/liquid interactions but as a determination of the minimum number of reactions which allowed one to obtain a good representation of experimental behavior without introducing excessive complexity for practical use. The model well represented the experimental behavior in all of the different conditions and was characterized by the presence of two surface complexation and one ion-exchange sites onto the different lead species which can be sorbed. From the applicative point of view the red soil shows an interesting overall adsorption capacity as revealed by the values of site concentration and CEC. Converting the total site concentrations from Table 3 in terms of more used units, a maximum sorption capacity of 21.7 mg g-1 can be calculated. This value is well comparable with the range of adsorption capacity of potentially lowcost sorbents for heavy metals, and it is similar to those obtained with commercial clays.5 Acknowledgment This work was supported by the Italian National Research Council (Progetto Strategico “Ambiente e Territorio”, Area Tematica: Criticita` delle disponibilita` di acqua da utilizzare a scopi potabile, 1998-2000) and by ANPA (Italian National Protection Agency, Project “Contaminant transport through natural saturated and unsaturated porous media: modeling of reactive migration in soils”). The authors thank Dr. G. Giuliano for essential comments and enjoyable discussion in the organization of the research and Teresa Saurini for skillful laboratory assistance. Literature Cited (1) Byrnes Brower, J.; Ryan, R. L.; Pazirandeh, M. Comparison of Ion-Exchange Resins and Biosorbents for the Removal of Heavy Metals from Plating Factory Wastewater. Environ. Sci. Technol. 1997, 31, 2910. (2) Recent Developments for in situ treatment of metal contaminated soils. Office of Solid Waste and Emergency Response Technology Innovation Office; U.S. EPA: Washington, DC, Mar 5, 1997. (3) Prasad, M.; Saxena, S.; Amritphale, S. S.; Chandra, N. Kinetics and isotherms for aqueous lead adsorption by natural minerals. Ind. Eng. Chem. Res. 2000, 39, 3034. (4) Petrangeli Papini, M.; Majone, M.; Rolle, E. Kaolinite Sorption of Cd, Ni and Cu from Landfill Leachates: Influence of Leachate Composition. Proceedings of Paris 2000, the 1st World Congress of the International Water Association (IWA), Paris, July 3-7, 2000. (5) Bailey, S. E.; Olin, T. J.; Bricka, R. M.; Adrian, D. D. A review of potentially low-cost sorbents for heavy metals. Water Res. 1999, 33, 2469.

(6) Altin, O.; Ozbelge, H. O.; Dogu, T. Use of general purpose adsorption isotherms for heavy metal-clay mineral interactions. J. Colloid Interface Sci. 1998, 198, 130. (7) Celis, R.; Hermosin, M. C.; Cornejo, J. Heavy metal adsorption by functionalized clays. Environ. Sci. Technol. 2000, 34, 4593. (8) Egozy, Y. Adsorption of cadmium and cobalt on montmorillonite as a function of solution composition. Clays Clay Miner. 1980, 28, 311. (9) Lee, S.-Z.; Chang, L.; Yang, H.-H.; Chen, C.-M.; Liu, M.-C. Adsorption characteristics of lead onto soils. J. Hazard. Mater. 1998, 63, 37. (10) Hayes, K. F.; Leckie, J. O. Modeling ionic strength effect on cation adsorption at hydrous oxide/solution interfaces. J. Colloid Interface Sci. 1987, 115, 564. (11) Barbier, F.; Duc, G.; Petit-Ramel, M. Adsorption of lead and cadmium ions from aqueous solution to the montmorillonite/ water interface. Colloids Surf. 2000, 166, 153. (12) Schindler, P. W.; Liechti, P.; Westall, J. C. Adsorption of copper, cadmium and lead from aqueous solution to the kaolinite/ water interface. Netherlands J. Agric. Sci. 1987, 35, 219. (13) Du, Q.; Sun, Z.; Forsling, W.; Tang, H. Adsorption of copper at aqueous illite surfaces. J. Colloid Interface Sci. 1997, 187, 232. (14) Dzombak, D. A.; Morel, F. M. M. Surface Complexation Modeling. Hydrous Ferric Oxide; John Wiley and Sons: New York, 1990. (15) Koretsky, C. The significance of surface complexation reactions in hydrologic systems: a geochemist’s perspective. J. Hydrology 2000, 230, 127. (16) Davis, J. A.; Coston, J. A.; Kent, D. B.; Fuller, C. C. Application of the surface complexation concept to complex mineral assemblages. Environ. Sci. Technol. 1998, 32, 2820. (17) Wen, X.; Du, Q.; Tang, H. Surface complexation model for the heavy metal adsorption on natural sediment. Environ. Sci. Technol. 1998, 32, 870. (18) Wang, F.; Chen, J.; Forsling, W. Modeling sorption of trace metals on natural sediments by surface complexation model. Environ. Sci. Technol. 1997, 31, 448. (19) Petrangeli Papini, M.; Marucci, D.; Majone, M.; Beccari, M. Lead adsorption onto “red soils” as function of environmental conditions. Ann. Chim., J. Anal. Environ. Chem. 2001, 91, 479. (20) Grolimund, D.; Borkovec, M.; Federer, P.; Sticher, H. Measurement of sorption isotherms with flow-through reactors. Environ. Sci. Technol. 1995, 29, 2317. (21) Schecher, W. Mineql+, version 4.0; Environmental reasearch software, 1998. (22) Scientist: Experimental Data Fitting; Microsoft Windows Version 1.05; Micromath Inc., 1986-1994. (23) Kinniburgh, D. G.; Barker, J. A.; Whitfield, M. A comparison of some simple adsorption isotherms for describing divalent cation adsorption by ferrihydrite. J. Colloid Interface Sci. 1983, 95 (2), 370. (24) Schroth, B. K.; Sposito, G. Effect of landfill leachate organic acids on trace metal adsorption by kaolinite. Environ. Sci. Technol. 1998, 32, 1404. (25) Holm, T. R.; Zhu, X.-F. Sorption of kaolinite of Cd2+, Pb2+ and Cu2+ from landfill leachate-contaminated groundwater. J. Contam. Hydrol. 1994, 16, 271. (26) Garcia-Miragaya, J.; Page, A. L. Influence of ionic strength and inorganic complex formation on the sorption of trace amounts of Cd by montmorillonite. Soil Sci. Soc. Am. J. 1976, 40, 658. (27) Gunneriusson, L.; Lovgren, L.; Sjoberg, S. Complexation of Pb(II) at the goethite (R-FeOOH)/water interface: the influence of chloride. Geochim. Cosmochim. Acta 1994, 58, 4973. (28) Barrow, N. J.; Bowden, J. W.; Posner, A. M.; Quirk, J. P. Describing the adsorption of copper, zinc and lead on variable charge mineral surface. Aust. J. Soil Res. 1981, 19, 309. (29) Bargar, J. R.; Brown, G. E., Jr.; Parks, G. A. Surface complexation of Pb(II) at oxide-water interfaces: III. XAFS determination of Pb(II) and Pb(II)-chloro adsorption complexes on goethite and alumina. Geochim. Cosmochim. Acta 1998, 62, 193. (30) Petrangeli Papini, M.; Duale-Kahie, Y.; Troia, B.; Majone, M. Adsorption of lead at variable pH onto a natural porous medium: modeling of batch and column experiments. Environ. Sci. Technol. 1999, 33, 4457.

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Received for review July 12, 2001 Revised manuscript received January 22, 2002 Accepted February 3, 2002 IE010594U