Biosorption of binary mixtures of Cr(III) and Cu(II) ions by Sargassum sp

Abstract

The adsorption of two metal ions, Cr(III) and Cu(II), in single-component and binary systems by Sargassum sp., a brown alga, was studied. Equilibrium batch sorption studies were carried out at 30ºC and pH 3.5. Kinetic tests were done for a binary mixture (chromium + copper) for a contact time of 72 hours to guarantee that equilibrium was reached. The monocomponent equilibrium data obtained were analyzed using the Langmuir and Freundlich isotherms. The binary equilibrium data obtained were described using four Langmuir-type and Freundlich isotherms. The F-test showed a statistically significant fit for all binary isotherm models. The parameters for isotherms of the Langmuir-type were used to determine the affinity of one metal for the biosorbent in the presence of another metal. The chromium ion showed a greater affinity for Sargassum sp. than the copper ion.

biosorption; chromium; copper; isotherm; multicomponent; Sargassum

Biosorption of binary mixtures of Cr(III) and Cu(II) ions by Sargassum sp

E.A.Silva^I; E.S.Cossich^II; C.G.Tavares^II; L.Cardozo FilhoII^*; R.GuirardelloIII^*

^ISchool of Chemical Engineering, UNIOESTE, Rua da Faculdade 645, 85903-000, Phone: (+55) (45) 252-3535, Toledo - PR, Brazil

^IIDepartment of Chemical Engineering, UEM, Av. Colombo 5790, 87020-900, Phone: (+55) (44) 226-2727, Maringá - PR, Brazil, E:mail: [e-mail]

^IIISchool of Chemical Engineering, UNICAMP, Av. Albert Einstein 500, 13083-970, Phone: (+55) (19) 3788-3955, Campinas - SP, Brazil, E-mail:[e-mail]

ABSTRACT

The adsorption of two metal ions, Cr(III) and Cu(II), in single-component and binary systems by Sargassum sp., a brown alga, was studied. Equilibrium batch sorption studies were carried out at 30^oC and pH 3.5. Kinetic tests were done for a binary mixture (chromium + copper) for a contact time of 72 hours to guarantee that equilibrium was reached. The monocomponent equilibrium data obtained were analyzed using the Langmuir and Freundlich isotherms. The binary equilibrium data obtained were described using four Langmuir-type and Freundlich isotherms. The F-test showed a statistically significant fit for all binary isotherm models. The parameters for isotherms of the Langmuir-type were used to determine the affinity of one metal for the biosorbent in the presence of another metal. The chromium ion showed a greater affinity for Sargassum sp. than the copper ion.

Keywords: biosorption, chromium, copper, isotherm, multicomponent, Sargassum.

INTRODUCTION

The increase in metal consumption on an industrial scale is an important environmental issue. Conventional methods for removing metals, such as chemical precipitation and sedimentation, oxidation, reduction and separation by membranes and ionic resins, may be expensive and sometimes ineffective depending on concentration. Biosorption processes have been proposed as an alternative method for recovering and removing metals from industrial effluents with metal concentrations in the range of 1 to 100 mg/L (Volesky, 1990).

The objective of this work was to determine the isotherms for copper and chromium ions by the marine alga Sargassum sp., using equilibrium data for solutions of these metal ions. These isotherms may provide useful information for the design of processes to remove these metal ions from industrial effluents at low concentrations.

Biosorbents made from marine algae biomass have been studied due to their wide availability and low cost. Although thousands of species of algae have been identified in the last two centuries, very little has been investigated in order to determine their relative capacity to retain toxic metallic ions (Çetinkaya et al., 1999). The brown marine alga Sargassum can be found in large amounts in the south and southwest Brazilian coast (Silva, 2001).

Equilibrium Isotherms

Biosorptive metal uptake can be quantitatively evaluated using experimental biosorption equilibrium isotherms. The two widely accepted isotherm models for single-solute systems are the Langmuir and Freundlich isotherms, described by equations (1) and (2), respectively:

where q_max and k are the Langmuir constants, and

where a and n are the Freundlich constants.

Multimetal systems are often encountered in industrial operations. Evaluation, interpretation and representation of biosorption results for two-metal systems is more difficult. Generally the results obtained for a single metal in solution cannot be used to predict the behavior of two-metal systems.

The effects of metal mixtures on a biosorption system can be complex, and three kinds of possibilities can arise (Ting et al., 1991): (i) the effect of the mixture is bigger than the sum of the effects of the components of the mixture (synergism); (ii) the effect of the mixture is smaller than the sum of the effects of the components of the mixture (antagonism); (iii) the effect of the mixture is the same as the sum of the effects of the components of the mixture (noncompetitive).

Reliable knowledge, correlation, and analysis of multicomponent equilibrium data are essential for achieving an understanding of biosorption dynamics and for further development of biosorption separation processes which represent a whole new area in environmental biotechnology (Chong and Volesky, 1995). Therefore, isotherm models for equilibrium of multicomponent mixtures should be used.

The Langmuir isotherm for a binary mixture is represented by the following equation:

where q_max, k₁ and k₂ are binary Langmuir constants.

The Langmuir model has also been used to analyze multicomponent biosorption equilibrium data (Chong and Volesky, 1995; Sag and Kutsal, 1996; Chong and Volesky, 1996; Sánchez et al., 1999; Figueira et al., 1997).

Analysis of binary biosorption data for metallic ions has also been carried out by using modified Langmuir models (Chong and Volesky, 1995; Sánchez et al., 1999). These models are represented by equations (4) through (6).

Equation (4) was originally developed to describe the noncompetitive inhibition in kinetic enzymatic studies (Bailey and Ollis, 1986). This equation is similar to the Langmuir model, with additional terms in the numerator and the denominator and an additional parameter, K:

By incorporating new constants (b₁, b₂) as exponents for each equilibrium concentration in the denominator of the Langmuir isotherm, the following mathematical expression may be obtained:

Using constants b₁ and b₂ as exponents in both the numerator and denominator of the Langmuir isotherm, the Langmuir-Freundlich isotherm is obtained, and it is represented by the following mathematical expression (Ruthven, 1984):

Sag et al. (1998) used the Freundlich empirical model to describe the biosorption equilibrium data in binary systems, whose mathematical representation is given by equations (7) and (8):

where a₁, n₂, a₂ and n₂ are Freundlich isotherm constants, obtained from the individual component equilibrium data. The other constants, a₁₁, a_12, a₂₁, a₂₁, a₁₂ and a₂₁, are determined from equilibrium binary data.

Metal Biosorption by Biomass

The first step in the design of a process for metal removal by biosorption, through ion exchange or adsorption, is the choice of the biosorbent material. The main criteria for the selection of the biosorbent material are cost, removal capacity and selectivity. The metal ion removal capacity is determined through experimental equilibrium data, which are also useful in the design and simulation of fixed bed columns for removal of metallic ions from the solution. A number of researchers in the literature have studied metal biosorption by biomass.

Kratochvil et al. (1998) studied chromium(III) removal by protonated Sargassum biomass (H₂SO₄ 0.2 M) and the same biomass linked with calcium (Ca(OH)₂). The equilibrium concentration of the chromium ion in the solution ranged from 0 to 9 mmol/L. These experiments were carried out at pH 4.0, and the biomass was able to retain around 0.769 mmol/g. Kratochvil et al. (1997) studied copper(II) ion removal by protonated (HCl 0.1 M) Sargassum fluitans seaweed biomass linked with calcium (CaCl₂). The interval of the chromium ion equilibrium concentration in the solution was similar to the one used in the present work. With pH 4.5 the biomass was able to retain around 1.18 mmol/g.

Chong and Volesky (1995) correlated sorption equilibrium data for binary metallic systems (Cu + Zn), (Cu + Cd) and (Zn + Cd) by FCAN2 biomass (manufactured from Ascophyllum nodosum marine alga) using equations (3), (4) and (5). Chong and Volesky (1995) fitted their data to the same models in a manner very similar to that used in the current work. The model with the lowest number of parameters was chosen.

Sánchez et al. (1999) correlated equilibrium data on sorption for a binary metallic system (Cu+Zn) by Cymodocea nodosa seaweed, pH 4.5, using equations (3), (4) and (5) as adsorption isotherms. The three models tested also represented the binary equilibrium data in a very similar manner.

Sag et al. (1998) tested equations (3), (5) and (6) to describe binary equilibrium data for sorption of Cu(II) and Zn by Rhizopus arrhizus fungus at pH 4.0 and 5.0 and a temperature of 25^oC and observed that of the isotherm models tested, only the Freundlich model could effectively represent the data.

The affinity of the metallic ions for the sites on the biosorbent material depends on several factors, such as ionic radii, pH and interaction of the ion with the biomass. There are few studies in the literature about the effect of temperature on the biosorption, such as the one by Cossich (2000) who studied the biosorption of cromium ion by Sargassum sp.

The dependency of pH on the biosorption capacity indicates that weakly acid carboxyl groups are the probable sites of ion exchange (Kratochvil and Volesky, 1998). Carboxylate has been identified as the chemical group responsible for capturing the metallic ions in the seaweed and in the gram-positive bacteria (Churchill et al., 1995; Kratochvil and Volesky, 1998). The biosorbent used in this work also has carboxylate in its cell wall.

Churchill et al. (1995) studied the removal of Cr⁺³, Co⁺², Ni⁺² and Cu⁺² ions by biosorbents prepared from biomass of gram-positive and gram-negative bacteria. The results obtained by the study of sorption at equilibrium showed the following affinity series: Cr⁺³ > Cu⁺² > Co⁺² > Ni⁺².

In this work, experiments were conducted to determine the length of time required for equilibrium of the metal ion to be reached in the solution and the Sargassum sp. biomass, and the equilibrium data for different concentrations of solutions of chromium, copper and a mixture of both. The results were used to fit the model parameters, using isotherm models represented by equations (3) through (8).

MATERIAL AND METHODS

The methodology used in this work is similar to the one used by a number of researchers in the literature (Chong and Volesky, 1995; Chong and Volesky, 1996; Cossich, 2000; Kratochvil et al., 1998; Sag and Kutsal, 1996; Sag et al., 1998; Sánchez et al., 1999; Volesky, 1990). The procedure is described as follows:

Biomass

The biomass used in the experiments was the brown Sargassum sp. It was washed in water, rinsed with distilled water and dried in an oven at 60^oC during 24 hours. The dry weight of the biomass was determined after drying at 105^oC during 24 hours. The dry biomass was then chopped and sieved to different fraction sizes. Dry particles with an average diameter of 0.625 mm were used for the sorption experiments.

Preparation of Chromium and Copper Solutions

Solutions of Cr(III) in distilled water were prepared using chromium and potassium sulfate salt (CrK(SO₄)₂.12H₂O – Sigma).

Solutions of Cu(II) in distilled water were prepared using copper sulfate salt (Cu(SO₄).5H₂O – Merck).

Kinetic Experiments

The kinetics of biosorption of chromium and copper and a mixture of both by the Sargassum sp. biomass was evaluated in 2000 mL Erlenmeyer flasks with 1000 mL of solution and 1.5 g of biomass (dry weight). Two kinetic tests were carried out for each ion in the following concentrations: 3.10 and 6.32 mmol Cr/L, 2.92 and 5.49 mmol Cu/L. For the binary mixture (chromium + copper), two kinetic tests were also carried out in the following concentrations: 1.10 mmol Cr/L and 0.93 mmol Cu/L, 3.17 mmol Cr/L and 2.8 mmol Cu/L.

The flasks were maintained at 30^oC under constant agitation (140 rpm) on a rotary shaker (Marconi MA830). A series of 1 mL samples of solution was removed from the flasks at predetermined time intervals and analyzed by atomic absorption spectroscopy (AA) to ascertain metal concentrations.

Sorption Equilibrium Experiments

Batch equilibrium sorption experiments were carried out in 125 mL Erlenmeyer flasks containing 50 ml of the metal solution to which 0.15 g of dry biomass particles had been added. The suspensions were agitated on a rotary shaker at 160 rpm at 30^oC and pH 3.5. When sorption equilibrium was reached (according to the time determined by the kinetic experiments) the solution was filtered and then analyzed by atomic absorption spectroscopy.

The initial pH of the chromium (III) solution ranged from 3.3 to 3.7, whereas the chromium concentration ranged from 0.5 to 3 mmol/L. However, Cossich (2000) observed the formation of precipitate in solutions containing 1 mmol/L of chromium when the pH was adjusted to 4.0 by adding NaOH. Microprecipitation can produce a distortion of sorption results and hinder determination of the amount of metal uptake. Thus, it was decided to work at pH 3.5. The pH was adjusted to 3.5 before and during the sorption experiments by adding 0.1 N NaOH or 0.1 N H₂SO₄, as required.

The biomass was removed by vacuum filtration. Initial and final concentrations for the metallic ions in the solution in each flask were measured by atomic absorption spectroscopy (Varian SpectrAA-10 plus).

The equilibrium concentration of metallic j ion in the solid biomass phase () was calculated from the initial concentration () and the equilibrium concentration () in each flask, using the following equation:

where V is the volume of the solution and m_s, the biosorbent mass (dry weight).

The same methodology was used to obtain the equilibrium data for the biosorption of the chromium-copper binary system by Sargassum sp. The concentration of binary solutions ranged from 1 to 10 mmol/L.

All equilibrium sorption experiments were carried out in duplicate.

Statistical Methods

The following definitions and statistical methods were used to evaluate the binary isotherm models given by equations (3) through (8) in the representation of experimental equilibrium data:

The average of the absolute value of the relative deviation (AD) is defined by equation (10):

where and are the experimental equilibrium uptake values and the values predicted using the isotherm model for each point i, respectively, and ne is the number of experimental points. For replications and repeated experiments, is given by equation (11):

which is the average of the experimental equilibrium uptake values ( k=1,...,nr_i ) for the replications of each experiment i ( i=1,...,ne ). In this work, all sorption experiments were carried out in duplicate (nr_i = 2 ).

The quadratic sum of the residue (SQ_r) is defined by equation (12):

The quadratic average of the residue (MQ_r) is defined by equation (13):

where p is the number of parameters in the model and .

The quadratic sum of the regression (SQ_R) is defined by equation (14):

where is the average of all experimental values , given by equation (15):

The quadratic average of the regression (MQ_R) is defined by equation (16):

The multiple coefficient of determination (R²) is defined by equation (17):

The model parameters were determined by the criterion of least squares using the objective function given by equation (18), which is the sum of the squares of the relative errors:

The procedure used to obtain the minimum value for F_obj was the simplex method (Nelder and Mead, 1965). For replications and repeated experiments, is given by equation (11).

The models were analyzed using the F-test with a confidence level of 95%. As a criterion, Box and Wetz (1973) suggest that the ratio MQ_R / MQ_r must be at least 4 or 5 times greater than the value expected for the F-distribution, where MQ_R and MQ_r are the quadratic averages of the regression and the residue, respectively, so that regression can be statistically significant and useful for making predictions.

The models were also analyzed using the average of the absolute value of the relative deviation (AD) and the multiple coefficient of determination (R²). When multiplied by 100, R² represents the percentage of variability in the observed variable that is explained by the regression (Anderson et al., 1991).

RESULTS AND DISCUSSION

Kinetic Experiments

Figures 1 and 2 show the results obtained in the kinetic tests of sorption for chromium and for copper at different concentrations. The metallic j ion fraction removed from solution was calculated by the following expression:

where the equilibrium concentration is the ion concentration in the solution at the end of the experiment.

It can be observed from Figure 1 that the system with chromium attained final equilibrium after a contact time of 48 hours. Also, from Figure 2 it can be observed that the system with copper attained final equilibrium after a contact time of 8 hours. Therefore, in order to guarantee that equilibrium was reached, contact times of 72 and 48 hours were used in the chromium and copper equilibrium sorption experiments, respectively.

Contact time for equilibrium is a function of several factors: biomass type (number and types of metal-binding sites), size and forms of biomass, state of biomass (active or inactive, free or immobilized), etc. The results of kinetic biosorption tests showed that copper removal is faster than chromium removal. The greater mobility of the copper ion is probably due to its smaller ionic radius, since the chromium ion is in a hydrated form in the conditions tested and therefore has a greater ionic radius than the copper ion.

After 6 hours, approximately 70% of the chromium had been removed when C⁰ = 6.32 mmol/L, and 80% when C⁰ = 3.10 mmol/L. However, irrespective of the value for initial concentration, the time required for the system to reach equilibrium was about the same.

After 30 minutes, approximately 87% of the copper had been removed when C⁰= 10.97 meq/L, and 82% when C⁰ = 5.84 meq/L. However, irrespective of the value for initial concentration, the time required for the system to reach equilibrium was about the same.

The results of the kinetic tests for the binary mixture (chromium + copper) are shown in Figures 3 and 4. It can be verified that a minimum contact time of 48 hours was necessary for the system to reach equilibrium. Thus, in the equilibrium experiments a contact time of 72 hours was allowed to guarantee that equilibrium would be reached.

The two kinetic curves for the binary mixture show that the initial concentration of metallic ions affects the shape of the curve, and at the beginning, the copper ion is captured faster than the chromium ion. In addition, it can be verified that after a short interval of time the copper concentration in the solution had increased. This indicates that copper is being released by the biosorbent.

At the beginning there are many sites available, and since the availabilities of the ions are similar and the mobility of copper is greater, it occupies more sites than chromium. Later on, the chromium ions migrate to the biosorbent surface to occupy more available sites, including some that were previously occupied by copper, because chromium has a higher affinity for Sargassum sp. than copper has. When this happens, an increase in copper concentration in the solution is observed, as illustrated in Figures 3 and 4.

Individual Sorption of Chromium and Copper Ions by Sargassum sp.

The data on sorption of chromium and copper ions by Sargassum sp. were used to fit the model parameters in the Langmuir and Freundlinch isotherms. The results, which are shown in Table 1, were calculated by fitting the curves to the experimental data using the simplex method with the criterion of least squares (Nelder and Mead, 1965).

Values for the correlation coefficient (R²) and for the average of the absolute value of the relative deviation (AD) for the Langmuir and Freundlich models used to represent single-component equilibrium data are shown in Table 2.

The Freundlich model was the one that better represented the equilibrium data on chromium ion sorption because it had the largest correlation coefficient and the smallest average deviation. The equilibrium data on copper ion sorption were better represented by the Langmuir model.

The results obtained in this work indicate that the Sargassum sp. biomass has a chromium removal capacity of around 1.30 mmol/g and a copper removal capacity of around 1.08 mmol/g, both at 30 °C and pH 3.5.

Binary Sorption of Chromium and Copper Ions by Sargassum sp

The experimental equilibrium data for the sorption of a binary mixture of chromium and copper ions by Sargassum sp. were compared using five different isotherm models, represented by equations (3) through (8). These models and their parameters are shown in Table 3.

The results for Langmuir-type and Freundlich isotherm parameters are shown in Table 4. The k_j constants from the Langmuir-type isotherm are the ratio between desorption and sorption rates. Therefore, low values of these constants indicate a strong metal affinity for the sites on the adsorbent material. From the results shown in Table 4 for models 1, 2, 3 and 4, it can be observed that the Cr⁺³ ion had a stronger affinity for Sargassum sp. than the Cu⁺². The same affinity was obtained by Churchill et al. (1995), who used a biomass that also had carboxylate in its cell wall.

The Langmuir-type isotherm described by model 2 is based on a kinetic model of sorption that allows the formation of the following complexes: B – M₁, which represents the sites occupied by metal M₁; B – M₂, which represents the sites occupied by metal M₂, and B – M₁ – M₂, which represents the sites occupied simultaneously by metals M₁ and M₂. The formulation and development of the equilibrium relationships for this model are presented in Chong and Volesky (1995) and Sánchez et al. (1999). The K constant for model 2 is related to the ratio between desorption and adsorption rates for the B – M₁ – M₂ complex. By the results in Table 4, it can be observed that the value for K is higher than the value for k₁ and lower than the value for k₂, showing that the formation of the B – M₁ – M₂ complex is less likely than the formation of the B – M₁ complex but more likely than the formation of the B – M₂ complex, where M₁ is Cr⁺³ and M₂ is Cu⁺².

Parameter values for the Freundlich isotherm are shown in Table 4, and since the formulation of the isotherm is empirical, its constants have no physical signification. However, this model showed the best numerical fit (Tables 5, 6 and 7).

Table 5 shows the percentages of points whose experimental equilibrium concentration in the biosorbent deviated less than 10% from the calculated concentration values using the five models.

Values for the quadratic sum of the residue (SQ_r), the average deviation (AD) and the sum of the squared relative residue (objective function F_obj) for each of the models used to represent binary equilibrium data are shown in Table 6.

The models were analyzed using the F-test with a confidence level of 95%, and the results are shown in Table 7. The criterion suggested by Box and Wetz (1973) was satisfied in all models in this work (the ratio MQ_R / MQ_r was at least 4 or 5 times greater than the value expected for the F-distribution).

The experimental equilibrium uptake values and the values predicted using the five isotherm models described in Table 3 are shown in Figures 5 through 9. It can be observed that the least dispersion of data was seen for models 4 and 5, in agreement with the statistical analyses presented in Tables 6 and 7.

Selection of the best model was based on the results of an analysis of variance of the models tested. The Freundlich and Langmuir-Freundlich isotherms were the ones which best represented the binary equilibrium data on biosorption, as can be seen in Tables 6 and 7. These models showed the least average deviation and the highest percentage of explained variation.

The graphic representation of sorption isotherms for binary systems is a three-dimensional surface, where the equilibrium concentration of the target metal in the biosorbent is described as a function of the equilibrium concentration of metallic ions in solution. It was observed that, for high levels of total concentration of metallic ions in solution, the biosorbent reaches the level of saturation easily, resulting in an extensive plateau on these surfaces. Table 8 shows the experimental data on sorption of chromium and copper ions by Sargassum sp. and theoretical equilibrium values calculated using the Freundlich binary isotherm model.

The effect that different levels of secondary metal have on primary metal uptake in a binary system at equilibrium can be better evaluated by fixing the primary metal concentration on the adsorption isotherms. Figure 10 illustrates the effect of the reduction in copper uptake on the biosorbent with the increase in the concentration of chromium ion in solution. For example, for the low equilibrium concentration of copper in solution of 0.5 mmol/L, the amount of copper adsorbed by alga is 0.80 mmol/g, in the absence chromium. When 0.5 mmol/L Cr or 4.0 mmol/L Cr are present in solution, the amount of copper adsorbed decreases to 0.20 mmol/g (reduction of 75.0%) or 0.11 mmol/g (reduction of 86.3%), respectively.

For the high equilibrium concentration of copper in the fluid phase of 3.0 mmol/L, the amount of copper adsorbed by alga is 0.98 mmol/g, in the absence chromium. When 0.5 mmol/L Cr or 4.0 mmol/L Cr are present in solution, the amount of copper adsorbed decreases to 0.50 mmol/g (reduction of 49.0%) or 0.34 mmol/g (reduction of 65.3%), respectively.

The reduction in adsorption is also observed by fixing the concentration of chromium in solution (0.5 and 3.0 mmol/L) and using different concentrations of copper. However, the effect is much less pronounced than in the previous case. It can be observed that for the levels of concentration studied (0.5 mmol/L and 3.0 mmol/L), the amount of copper uptake was more sensitive to the presence of chromium than the reverse. This significant reduction in ion removal capacity is due to the effect of competition, indicating that chromium has a greater affinity for the biosorbent than copper.

CONCLUSIONS

Batch equilibrium experiments showed that the maximum capacities of Sargassum sp. biomass for chromium and copper were 1.30 mmol/g and 1.08 mmol/g, respectively, at 30°C and pH 3.5.

A number of Langmuir-type and Freundlich models was used to correlate equilibrium data on sorption of chromium-copper metallic ions by Sargassum sp. at 30^oC and pH 3.5. The F-test showed a statistically significant fit for all binary isotherm models. However, the Freundlich and Langmuir-Freundlich isotherms represented the binary equilibrium data better than other models, according to the results of the analysis of variance. The Freundlich isotherm represented the equilibrium data slightly better than the Langmuir-Freundlich model.

Langmuir isotherm parameters were used to determine the affinity of one metal for the biosorbent in the presence of the other metal, showing that the chromium ion had a greater affinity for Sargassum sp. than the copper ion.

NOMENCLATURE

Received: April 14, 2000

Accepted: April 2, 2003

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To whom correspondence should be addressed

Publication Dates

• Publication in this collection
  05 Sept 2003
• Date of issue
  Sept 2003

History

• Accepted
  02 Apr 2003
• Received
  14 Apr 2000