Adsorption Equilibria of Cu2+, Zn2+, and Cd2+ on ... - ACS Publications

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Adsorption Equilibria of Cu2+, Zn2+, and Cd2+ on EDTA-Functionalized Silica Spheres Diego Q. Melo,† Vicente O. S. Neto,‡ Juliene T. Oliveira,† Allen L. Barros,† Elis C. C. Gomes,§ Giselle S. C. Raulino,‡ Elisane Longuinotti,† and Ronaldo F. Nascimento*,† †

Department of Analytical Chemistry and Physico-Chemistry, Federal University of Ceará, Rua do Contorno, S/N, Campus do Pici, Bl. 940 CEP: 60451-970, Fortaleza, CE, Brazil ‡ Department of Hydraulic and Environmental Engineering, Federal University of Ceará, Rua do Contorno, S/N Campus do Pici, Bl. 713 CEP: 60451-970, Fortaleza, CE, Brazil § Department of Organic and Inorganic Chemistry, Federal University of Ceará, Rua do Contorno, S/N Campus do Pici, Bl. 940 − CEP: 60451-970, Fortaleza, CE, Brazil ABSTRACT: Ethylenediaminetetraacetic acid (EDTA) functionalized silica spheres were used to remove metal ions from aqueous solutions. The adsorption kinetics of Cu2+, Zn2+, and Cd2+ (60 mg·L−1, pH 5.5) were fitted to the pseudosecond order model. Adsorption equilibria were reached within 20 min, indicating that chemisorption may be the limiting step in the adsorption process. Adsorption isotherms were analyzed with nonlinear models by considering the ERRSQ error function and the determination coefficient R2. The data with monoion solutions (10 mg·L−1 to 300 mg·L−1) were tested with Langmuir, Freundlich, and Redlich−Peterson isotherm models. The best fit was found with the Langmuir model, and maximum adsorption capacities followed the order: Cu2+ > Zn2+ > Cd2+. Breakthrough curves were obtained using filled columns. The adsorbed ions were quantitatively recovered on elution with hydrogen chloride (0.10 M). After three adsorption−recovery cycles, the metal ions could still be recovered almost quantitatively, which demonstrates the good performance of the EDTA-functionalized silica spheres.

1. INTRODUCTION

metal ions, which makes them an important material for adsorption studies. In this work, silica spheres functionalized with APTS (3aminopropyltriethoxysilane) and EDTA (ethylenediaminetetraacetic acid) (synthesis described elsewhere)13 was used as an adsorbent for the removal of Cu2+, Zn2+, and Cd2+ ions from aqueous solution in both batch and fixed-bed column systems. In this study equilibrium isotherms and kinetics were evaluated by testing Langmuir, Freundlich, and Redlich−Peterson isotherm models, and pseudofirst order, pseudosecond order, and Weber−Morris models.

The contamination of natural waters by biological and chemical agents has become a matter of vivid public interest. Among the various toxic pollutants that can be found in water, toxic metal ions deserve special attention since they are also bioaccumulative. Therefore, their occurrence in the environment may result in risks to fauna, flora, and human health. Consequently, the implementation of removal technologies for the treatment of effluents from various industries (mining, textile, painting, electroplating, pesticide-producing) has become a matter of urgency, since in many cases the effluents are discarded into water bodies with no suitable treatment.1−3 The processes used for metal ion removal from an aquatic environment include chemical precipitation, membrane filtration, ion-exchange, and adsorption,4 the latter being the most popular due to the simplicity and the low cost.5 A wide range of materials have been used in adsorption processes: mineral adsorbents, such as zeolites,6 silica,7 and alumina,8 as well as organic adsorbents, such as activated carbon,9 sugar cane bagasse,10 coconut fiber,11 chitin, and chitosan.12 The use of activated carbon and silica has been widely investigated for the removal of metal ions from aqueous matrices. Silica is an adsorbent of particular interest due to its high surface area and its physical and chemical stability. Derivatives are also expected to be efficient for the removal of © 2013 American Chemical Society

2. MATERIALS AND METHODS 2.1. Preparation of Solutions. Analytical-grade chemicals and ultrapure water (Millipore Direct Q3 Water Purification System) were used to prepare the solutions. Monoelement and multielements stock solutions of Cu2+, Zn2+, and Cd2+ (500 mg·L−1) were prepared with CuSO4·5H2O, ZnSO4·8H2O, and CdSO4·8/3H2O (Merck, São Paulo, Brazil), respectively. The acetate buffer was prepared with sodium acetate and glacial acetic acid. NaOH (0.10 mol·L−1) and HCl (0.10 mol·L−1) solutions were used for pH adjustments. Erlenmeyers (50.0 Received: December 17, 2012 Accepted: February 20, 2013 Published: March 1, 2013 798

dx.doi.org/10.1021/je3013364 | J. Chem. Eng. Data 2013, 58, 798−806

Journal of Chemical & Engineering Data

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calculated by considering metal concentrations in samples collected at the outlet of the column. 2.8. Nonlinear Regression Analysis. Linear regression is the most widely used method for the determination of isotherms parameters, so that the quality of a model is given by the values of the resulting determination coefficients, with a higher quality of the model being associated to determination coefficients closer to the unit. However, some studies have warned about errors resulting from linearization methods, while considering a nonlinear approach to be robust and to provide higher determination coefficients. Therefore, in this work nonlinear methods were used to determine the parameters of Langmuir, Freundlich, and Redlich−Peterson isotherm models. The optimization procedure was carried out for each experimental data set by using the solver add-in for Microsoft Excel, considering the values obtained for the sum of the squares of the errors (ERRSQ), the most widely used error function,15 represented by the following eq 2.

mL) and an orbital shaker device (Marconi, Brazil) operating at 250 rpm and 28 ± 2 °C were used in the experiments. The adsorbent (25.0 mg) and the respective solutions (25.0 mL) containing the analytes were added to each flask. The tests were performed in duplicate. The equilibrium adsorption capacity of the adsorbent was calculated with eq 1:14 qe =

(Co − Ce) V W

(1)

where qe is the equilibrium adsorption capacity (mg of metal/g adsorbent), Co is the initial concentration of the metal ion in mg·L−1, Ce is the equilibrium concentration of metal ion in mg·L−1, V is the volume of the solution in liters, and W is the mass of adsorbent in grams. Control experiments were carried out in the absence of adsorbent to check for any adsorption on the walls of the flasks. 2.2. Metal Quantitation. The concentrations of Cu2+, Zn2+, and Cd2+ were measured with an atomic absorption spectrophotometer (933 plus, GBC, Australia) by using hollow cathode lamps and detection at the wavelengths 324.7 nm, 213.9 nm, and 228.8 nm, respectively. Prior to analysis, samples were filtrated and properly diluted with ultrapure water. The concentration of the analytes could fit the linear range of the calibration curves, which ranged from (1.0 to 5.0) mg·L−1, (0.4 to 1.5) mg·L−1, and (0.2 to 1.8) mg·L−1 for Cu2+, Zn2+, and Cd2+, respectively. 2.3. Adsorption Kinetics. Adsorption kinetics studies allow the evaluation of the extent of removal as well as the identification of the prevailing mechanisms involved in the adsorption process. A multielements solution (60.0 mg·L−1) was continuously shaken (250 rpm) at pH 5.5. Aliquots of the supernatant were collected in regular periods of time, up to 240 min. Adsorption capacities were calculated by the differences between initial and final concentrations at any given time. 2.4. Adsorption Isotherms. EDTA-functionalized silica spheres (25.0 mg) were added to monoelement and multielements solutions (25.0 mL) in 50 mL Erlenmeyer flasks, with metal ion concentrations in the range of (10 to 300) mg·L−1. The mixtures were mechanically stirred (250 rpm) for 24 h at room temperature (28 ± 2 °C). The data obtained for the adsorption isotherm in the monoelement systems were described according to the Langmuir, Freundlich, and Redlich−Peterson models. The Langmuir extended equation was used for the multielement system. 2.5. Column Adsorption. The solutions (100 mL) containing Cu2+, Zn2+, and Cd2+ (1 mg·L−1 each) were percolated through a column (5 cm × 0.5 cm I.D.) containing 0.10 g of Si-APTS-EDTA spheres at a constant flow of 0.70 mL·min−1, adjusted with the aid of peristaltic pump. Samples of 5 mL of each effluent were collected at the outlet of the column and subjected to analysis. 2.6. Desorption Study. After column saturation was reached, 10.0 mL of a HCl solution (0.10 mL) was percolated through the column at a constant flow of 0.70 mL·min−1. Aliquots of 1.0 mL of the eluate were collected at the outlet of the column for the determination of metal ion concentrations. 2.7. Regeneration Dtudy. To study the column regeneration, acetate buffer (10.0 mL) was percolated through the column, followed by the multielements solution (50.0 mL). Then, the column was rinsed with water (10.0 mL) and with HCl (0.10 M, 10.0 mL). This procedure was repeated for three adsorption cycles. The removal efficiency in each cycle was

p

ERRSQ =

∑ (qexp − qcal)2i i=1

(2)

where qexp is the experimental value for each sample from the batch experiment and qcal is the corresponding value, estimated with the isotherm model. All of the data presented are the mean values of two results obtained in identical essays. Variation coefficients were found to be lower than 5 %, and the statistical analysis was carried out with Microsoft Excel software.

3. RESULTS AND DISCUSSION 3.1. Effect of pH. The value of the pH is one of the most important factors on adsorption of metal ions, since it can affect the speciation of the ions in aqueous solutions as well as the electric charge of adsorption sites on the adsorbent surface, Figure 1.16 The effect of pH on the adsorption of Cu2+, Zn2+,

Figure 1. Distribution of copper species as a function of pH.

and Cd2+ onto Si-APTS-EDTA was studied at pH values of 3.0, 3.5, 4.5, and 5.5. The results are presented in Figure 2. The degree of ionization, surface charges, and the metal ion speciation are influenced by the pH, thus influencing both adsorption mechanisms and adsorption capacities. The removal efficiency increased as the pH increased from 3 to 5.5. At a pH of 3.0, −NH groups become protonated, so that protons and metal ions compete for adsorption sites; in addition, −COOH groups are also not ionized, thus limiting the extent to which 799



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Figure 2. Effect of initial pH on the adsorption of Cd2+, Zn2+, and Cu2+ onto Si-APTS-EDTA. C0 = 60 mg·L−1, temperature: 28 ± 2 °C.

metal ions approach and adsorb onto the adsorbent. At high pH values, −OH, −NH, and − COOH groups are on their ionized forms, and interactions between metal ions and the adsorbent material are favored. The surface charge density was also found to play an important role. The point of zero charge (PZC) of Si-APTS-EDTA is around pH 5.0.13 At higher pH values, copper occurs in aqueous solutions as Cu2+, Cu(OH)+, and Cu(OH)22+ species, which are likely to be adsorbed on the negatively charged adsorbent. At pH > 6, precipitation of metal hydroxides is expected to occur. As seen in Figure 2, the optimum pH value for removal of the metals was 5.5. At this pH, neither precipitation of the metal hydroxides nor protonation of the adsorbent material is expected to take place. 3.2. Adsorption Isotherms. An adsorption isotherm describes the distribution of a solute between the solid and liquid phases at a certain temperature and different equilibrium concentrations, thus providing a better assessment of the system under study. 3.3. Batch Models for Sorption. Evaluating the fitting of experimental data to different isotherm models is an important step for the determination of the most suitable model for the adsorption process under study.17 To determine the mechanisms related to the adsorption of copper, cadmium, and zinc onto Si-APTS-EDTA, Langmuir, Freundlich, and Redlich− Peterson isotherm models were tested with the experimental data with the parameters being obtained using nonlinear regression. The adsorption isotherms obtained are shown in Figure 3, and the parameters calculated for the models used are presented in Table 1. According to Figure 3, adsorption was observed to be similar for the different metal ions at lower concentrations, probably due to the great availability of adsorption sites. As the equilibrium concentrations increase, adsorption sites become no longer available. 3.3.1. Langmuir Isotherm Model. A Langmuir model takes into account the decrease in the number of available adsorption sites as the metal ion concentration increases.18,19 The model considers the occurrence of a monolayer adsorption and is expressed by eq 3:20,21 qe =

Figure 3. Isotherms for the adsorption of (a) Cu2+, (b) Zn2+, and (c) Cd2+, by Si-APTS-EDTA at pH 5.5, constant ionic strength, and room temperature.

where Ce is the solute concentration at equilibrium (mg·L−1), qe is the amount of ions metals adsorbed at equilibrium (mg·g−1), qmax is the monolayer capacity of the adsorbent (mg·g−1), and KL is the Langmuir adsorption constant (L·mg−1), which expresses the affinity between the adsorbate and the adsorbent. Efficient adsorbents are expected to have high qmax and KL values. The values of qmax followed the order: Cu2+ > Zn2+ > Cd2+ and were found to be higher than those obtained experimentally ((24.70, 27.16, and 19.94) mg·g−1 for copper, zinc, and cadmium, respectively). 3.3.2. Freundlich Adsorption Isotherm. A Freundlich isotherm model considers adsorption as a multilayer, heterogeneous process.22 The model is expressed by eq 4:

qmax KLCe (1 + KLCe)

qe = K f Ce1/ n

(3) 800

(4) dx.doi.org/10.1021/je3013364 | J. Chem. Eng. Data 2013, 58, 798−806


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Table 1. Parameters of Isotherm Models for Monoelement Systemsa model

parameter

Cu2+

Zn2+

Cd2+

Qmax KL R2 ERRSQ KF 1/n R2 ERRSQ KRP aRP β R2 ERRSQ

37.59 7.2·10−3 0.99 1.57 1.10 0.56 0.99 2.64 0.27 7.7·10−3 0.99 0.99 1.53

36.38 1.2·10−2 0.99 2.17 1.51 0.54 0.99 12.03 0.41 1.2·10−2 0.97 0.99 0.85

23.67 2.9·10−2 0.99 5.03 5.46 0.24 0.98 11.10 0.92 6.1·10−2 0.92 0.98 6.73

Langmuir

Freundlich

Redlich−Peterson

Figure 4. Experimental adsorption isotherms of Cu2+, Zn2+, and Cd2+ from multielement systems by Si-APTS-EDTA at pH 5.5, constant ionic strength, and room temperature.

a

The coefficients of variation were lower than 5 % for the data presented.

where Kf (L·mg−1) and n are Freundlich adsorption isotherm constants, indicative of the saturation capacity and intensity of adsorption, respectively. It is well-known that favorable adsorption processes are associated to “1/n” values between 0.1 and 1.23 “1/n” was found to be in this range for all metal ions studied in this work. 3.3.3. Redlich−Peterson Isotherm. A Redlich−Peterson model is represented by a three-parameter, empirical equation, which is capable of representing an adsorption equilibrium over a wide concentration range.24 This equation has the form (eq 5): qe =

q=

−1

n

1 + ∑ j = 1 KL, jCj

(6)

where j = 1, 2, ..., n, with i and j representing the components of the solution; q is the adsorption capacity; qmax is the maximum adsorption capacity in a monoelement system, and KL is the Langmuir constant. In a multielement system, the effect of the ionic interaction in the adsorption process can be expressed by the ratio between the adsorption capacity of a metal in the presence of other ions, qMi, and its adsorption capacity in a monoelement solution, q, so that: when qMi/q > 1 the sorption is promoted by the presence of the other metal ions; if qMi/q = 1, no interaction is detected; when qMi/q < 1 the sorption is suppressed by the presence of the competing metal ions.26 The results of the ionic interactions by the qMi/q ratio revealed that the adsorption of the ions copper (0.77) and zinc (0.87) was suppressed, while that of cadmium (1.14) was promoted to a great extent. It can be seen in Table 2 that the Si-APTS-EDTA spheres showed good adsorption capacity when compared to other adsorbents. This may be related to the experimental conditions and also to the structure of the composites, as well as to the affinity of the metal ions by the functional groups present on the adsorbent surface. 3.5. Adsorption Kinetics. The adsorption of metal ions by Si-APTS-EDTA involves the coordination of these metal ions by oxygen and nitrogen atoms, whose free electrons favor the formation of metal−adsorbent complexes onto the adsorbent surface. The rate at which metal ions are transferred from the solution to the adsorbent surface determines the rate of the adsorption kinetics.32 Its study enables the identification of controlling mechanisms in the adsorptive process as well as the assessment of how kinetics is dependent on both the initial concentration and the adsorbent characteristics. Figure 5 depicts the adsorption kinetics of Cu2+, Zn2+, and Cd2+ by SiAPTS-EDTA as a function of time. Initial concentrations were (69.24, 55.44, and 60.78) mg·L−1, respectively, and the adsorption equilibrium was reached in approximately 20 min, which indicates that the adsorption takes place soon after the contact between the adsorbates and the adsorbent. Adsorption capacities were calculated with eq 1, and the results obtained were (22.21, 12.50, and 4.45) mg·g−1 for copper, cadmium, and zinc, respectively. The lowest value observed for zinc is

KRPCe 1 + aRPCe β

qmax ·KL, i·Ci

(5) −1

where KRP (L·mg ), aRP (L·mg ), and β are Redlich− Peterson parameters. The Redlich−Peterson model takes into consideration the characteristics of Langmuir and Freundlich isotherms, with limiting behaviors corresponding to the Langmuir form (when β is equal to 1) and to Henry’s law form (when β is equal to 0).24 β-values were found to be close to 1 (0.99, 0.97, and 0.92), thus indicating that, for copper, zinc, and cadmium, the model adopts the Langmuir form. According to Table 1, both Langmuir and Redlich−Peterson isotherms showed good correlation with experimental data, as expressed by the high determination coefficients and the low values of the error function. The lower the error function, and the higher the determination coefficient, the better the experimental data fit the assumptions of a model. Even though the experimental data of copper and zinc better fit the Redlich− Peterson model, the latter becomes the Langmuir model itself since β is close to unit in both cases. This is observed by the proximity or equality of KL and aRP values of the two models. 3.4. Adsorption in a Multielement System. For a better comparison of the binding affinities, adsorption essays were also performed in the multielement solutions containing the same amounts of each one of the metals studied (Figure 4). Since any solid adsorbent has its own surface area, the presence of solutes results in the competition for available adsorption sites. However, some sites are specific, so that not all ions compete for the same adsorption sites.25 A study on the competition was carried out with multielement solutions, using the Langmuir extended equation (eq 6).23 801



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Table 2. Comparison of the Adsorption of Cu2+, Zn2+, and Cd2+ onto Modified Silicas qmax (mg·g−1) adsorbent

a

Si-APTS-EDTA Si-AMPS Si-DHAQ NH2-MCM-41 Si-DHB SNHS Si-NH2 NH2−SNHS

2+

Cu

Zn2+

Cd2+

pH

m/mg

reference

37.59 19.9

36.38

23.67

11.9

8.1 18.25 3.6 20.82 31.89 40.73

5.5 4.5 7.0 5.0 6.0 to 7.5 4.5 4.5 4.5

25 50 100 500 50 15 15 15

this work 27 28 29 30 31

22.11

10.98

a

Si: silica; APTS: 3-aminopropyltriethoxysilane; EDTA: ethylenediaminetetraacetic acid; AMPS: 2-acrylamido-2-methylpropanesulfonic acid; DHAQ: 1,8-dihydroxyanthraquinone; DHB: 3,4-dihydroxybenzene; SNHS: silica nano hollow sphere; NH2-SNHS: silica nano hollow sphere modified/3-aminopropyltriethoxysilane.

Table 3. Parameters of Pseudofirst-Order and Pseudosecond-Order Adsorption Kinetics Models experimental pseudofirst order

pseudosecond order

qe qcal K1 R2 qcal K2 R2

Cu2+

Zn2+

Cd2+

22.21 39.93 0.01 0.82 22.36 0.02 0.99

4.45

12.50 4.2 0.01 0.74 12.50 0.03 0.99

4.43 0.09 0.99

the pseudosecond-order model, which is also based on the sorption capacity of the solid phase, expressed by eq 8:35,36 dq = k 2(qe − qt )2 dt

Figure 5. Multielements kinetic for the adsorption of Cu2+, Zn2+, and Cd2+ by Si-APTS-EDTA at pH 5.5, constant ionic strength, and room temperature.

where k2 is the rate constant of second-order adsorption (g·mg−1·min−1). The linear plot of t/qt versus t was used to calculate the second-order rate constant k2 and the equilibrium adsorption capacity qe, by considering the values of the slope and the intercept, respectively. It follows from Table 3 that the experimental data best fitted to the pseudosecond-order kinetic model. The values of the determination coefficient R2 are higher than those obtained with the pseudofirst-order model and the calculated qe values also showed good agreement with experimental values, thus indicating chemisorption as the limiting step of the process.37 The pseudosecond order rate constant k2 was 0.02, 0.03, and 0.09 for copper, cadmium, and zinc, respectively. The value of k2 obtained for zinc is at least three times higher than the values obtained for copper and cadmium. Since k2 has similar values for copper and cadmium, the greater extent of copper adsorption is probably related to some properties, such as electronegativity (1.90 and 1.70) and ionic radius (0.72 and 1.03 Å), for copper and cadmium, respectively.38 The electronegativity measures the attraction of electrons in a chemical bond and is related to the atomic radius. The smaller the atom, the greater the attractive forces are, since the distance between the nucleus and the electrosphere is reduced; hence, the lower affinity for cadmium can be explained by its lower electronegativity.39−41 It has been reported in various works that the adsorption of metals onto modified silica can be described according to a pseudosecond-order model, as in the cases of thiol-functionalized silica and NH2-MCM-41 used for cadmium removal, resulting in rate constants 0.021 and 0.005, respectively.42,29

probably a consequence of its lower initial concentration. Pseudofirst- and pseudosecond-order kinetic models were applied to the data obtained. 3.5.1. Kinetic Models. The pseudofirst-order kinetic model,33 based on the capacity of the solid, assumes that the rate of change in the solute sorption as a function of time is directly proportional to difference in the saturation concentration (qe) and the amount removed by the solid as a function of time. The nonlinear pseudofirst-order equation can be expressed by eq 7:34

dqt dt

= k1(qe − qt )

(8)

(7)

where qe and qt are the amounts of metal ions adsorbed per gram of adsorbent (mg·g−1) at equilibrium and at time t, respectively; k1 is the rate constant of the first order adsorption (min−1). The rate constant k1 (min−1) was calculated from the slope of a ln(qe − qt) versus t plot for copper, zinc, and cadmium. The experimental qe values were not in agreement with those calculated with the kinetic model, and the R2 values obtained were found to be lower than those of the pseudosecond-order model. In addition, the experimental data for zinc did not fit the model (Table 3). These results suggest that the adsorption of copper, cadmium, and zinc onto SiAPTS-EDTA spheres does not follow pseudofirst-order kinetics. The experimental kinetic data were then tested with 802



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According to the intraparticle diffusion model, the adsorption kinetics is controlled by several factors, including: transfer of the adsorbate from the solution onto the film that surrounds the particle; diffusion of the adsorbate through the film onto the surface of the adsorbent particle (intrafilm diffusion); and surface diffusion onto intraparticle sites (intraparticle diffusion).43 The intraparticle diffusion model is expressed by the following kinetic eq 9: qt = Kd ·t 0.5

(9) −1

where qt (mg·g ) is the amount of metal adsorbed at time t (min) and kd (mg·g−1·min−0.5) is the intraparticle diffusion rate constant. A plot of Qt versus t0.5 is expected to be linear when the data fit to the intraparticle diffusion model (Figure 6), according to

Figure 7. Experimental breakthrough curve at a flow rate of 0.7 mL·min−1, 1 mg·L−1 ternary initial concentrations for Cu2+, Zn2+, and Cd2+ by Si-APTS-EDTA at pH 5.5, constant ionic strength, and room temperature.

The upper area in the breakthrough curve represents the total mass of metal adsorbed (qtotal, mg) that can be determined by eq 10: qtotal =

F 1000

t = t total

∫t =0

⎛ C ⎞ ⎜1 − e ⎟d t Co ⎠ ⎝

(10)

where (1 − (Ce)/Co) is the concentration of adsorbed metal (mg·L−1), and F is the flow rate (mL·min−1), which can be calculated by dividing the volume of effluent (mL) by the total time (min). The amount of metal ions sent to the column (mg) is calculated with the following expression (eq 11):

Figure 6. Weber and Morris models for Cu2+, Zn2+, and Cd2+ at pH 5.5, constant ionic strength, and room temperature.

mtotal =

which diffusion is the predominant mechanism, if the graph obtained is linear and passes through the origin.42 However, although the model is not satisfactory through the entire time interval studied, valuable information concerning the diffusion mechanism was obtained. Figure 6 shows that the diffusion process occurs in two steps. The first step is related to the adsorption onto the external adsorbent surface, also considered as an instantaneous adsorption.44 The second step is the final stage of equilibrium in which intraparticle diffusion decreases either due to extremely low concentrations in the solution or to the adsorbent saturation. These steps suggest that both surface adsorption and intraparticle diffusion occur simultaneously and contribute to the adsorption mechanism. However, the experimental data best fitted to the pseudosecond-order model, indicating that two or more steps are involved in the process, with chemisorption expected to be the limiting step, due to the characteristics of the adsorbent. 3.6. Column Adsorption. In batch adsorption studies, solution concentrations continuously decrease in contact with an adsorbent. In fixed-bed adsorption, the adsorbent keeps in contact with an effluent of approximately constant composition. The concept of fixed-bed adsorption is usually expressed by socalled breakthrough curves (Figure 7). In a system of dynamic adsorption, the effluent enters the column at a concentration Co and a concentration gradient or profile is established within a finite zone (adsorption zone or breakthrough zone), in which the solute concentration ranges from Co to Ce. Co approaches or equals Ce when the column bed is saturated.45

CoFte 1000

(11)

The removal efficiency can be calculated by the ratio of the amount of adsorbed metal (qtotal) and the amount of metal sent to the column (total mass), as follows (eq 12): q R = total ·100 mtotal (12) The adsorption capacity at equilibrium, qe (mg·g−1), can be calculated with the following eq 13: q qe = total (13) m The adsorption capacity and the removal efficiency calculated with eqs 12 and 13 were (0.32, 0.39, and 0.37) mg·g−1 and 96.00 %, 94.80 %, and 97.40 % for copper, cadmium, and zinc, respectively. The on-column removal efficiency column followed the order: Zn > Cu > Cd. Although several models can be used to calculate kinetic constants and maximum adsorption capacities of a column, the Thomas model is most used. The Thomas equation for an adsorption column can be expressed by eq 14:46 Ce 1 = Co 1 + exp((KThqThm /F ) − KThCoV /F )

(14)

−1

where Ce is the efluent concentration (mg·L ), C0 is the initial concentration (mg·L−1), F is the flow rate (mL·min−1), m is the mass of adsorbent (g), V is the volume (mL), and KTh (L·mg−1·min−1) and qTh (mg·g−1) are the adsorption kinetic 803



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rate of 0.70 mL·min−1, and the column was reused up to three adsorption−desorption cycles without significant reduction of the adsorption capacities. Copper and zinc were completely recovered in the three cycles, while the cadmium recovery followed the order 100 %, 98 %, and 97 %. Such possibility of repeated use of the adsorbent material is an extremely advantageous feature in adsorption processes.

rate constant and the maximum adsorption capacity of the column, respectively. Table 4 displays the model parameters, where KTh represents the mass transfer of metal ions from the solution to the Table 4. Calculated Parameters for Thomas Model parameters cation

KTh

qTh

qexp.

R%

R2

ERRSQ

Cu2+ Zn2+ Cd2+

0.07 0.04 0.04

0.35 0.38 0.40

0.32 0.37 0.39

96.00 97.40 94.80

0.98 0.99 0.99

1.30·10−2 9.30·10−4 1.20·10−4

4. CONCLUSIONS The optimal pH for removal of Cu2+, Zn2+, and Cd2+ ions was found to be 5.5. The adsorption kinetics indicated that the multielements adsorption equilibrium was reached within 20 min for all metal ions studied and that the experimental data best fitted to the pseudosecond order kinetic model. The analysis of the isotherms by the nonlinear model showed that the experimental data for Cu2+, Cd2+, and Zn2+ were best described by the Langmuir model, since high R2 and low ERRSQ values were obtained. The maximum adsorption capacities followed the order: Cu2+ > Zn2+ > Cd2+. Breakthrough curves revealed that saturation was reached with 35.0 mL of solution for the three metal ions with an efficiency of column saturation in the order: Zn (97.4 %) > Cu (96.0 %) > Cd (94.8 %). HCl (0.10 M) was demonstrated to be effective for desorption/recovery of the metal ions from the column. The adsorbent showed excellent regeneration capability, with quantitative recovery reached for all metal ions, in three regeneration cycles. Finally, the results support the use of EDTA-functionalized silica spheres for removal of toxic Cu2+, Zn2+, and Cd2+ ions from aqueous solutions.

functionalized spheres, following the order: Cu > Cd ∼ Zn. If compared to other works47,48 the model can be used to explain the adsorption process. 3.7. Desorption and Regeneration. After the saturation of the column is reached, further experiments must be performed to study the metal ions desorption previously adsorbed, as well as the adsorbent regeneration. Desorption is an extremely important procedure, since it can make the metal ions recovery and of adsorbent materials feasible, thus contributing to the economical viability and sustainability of adsorption-based treatments. Many substances can be used as desorption agents and must be carefully chosen, since several chemicals may promote permanent changes in the adsorbent material, lowering its adsorption capacities. A compromise between the required concentration to be used and the desorption efficiency attained must be observed. In this work, hydrochloric acid (0.10 M) was used as the eluent for desorption of the metal ions (Table 5).

■

Corresponding Author

*Phone: +55-85-3366-9958/Fax: +55-85-3366-9038. E-mail address: [email protected].

Table 5. Removal of Cu2+, Zn2+, and Cd2+ with HCl (0.1 M) eluate volume/mL 1 2 3

%Cu

2+

100

%Zn

2+

88.6 11.4

AUTHOR INFORMATION

2+

%Cd

Funding

69.15 30.85

The authors are grateful to FUNCAP (Fundaçaõ Cearense de ́ Apoio ao Desenvolvimento Cientifico e Tecnológico), CAPES ́ (Coordenaçaõ de Aperfeiçoamento de Pessoal de Nivel Superior) and CNPq (Conselho Nacional de Desenvolvimento ́ Cientifico e Tecnológico) for grants and fellowships.

As seen in Table 5, the use of 1.0 mL of eluent resulted in nearly complete metals ions recovery, with an almost quantitative recovery found for all metal ions with only 2.0 mL of eluent (Figure 8). All metal ions were eluted at a flow

Notes

The authors declare no competing financial interest.

■

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Figure 8. Elution of Cu2+, Zn2+, and Cd2+ with HCl (0.1 M) using a flow rate of 0.7 mL·min−1. 804



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