Removal of Cu (II) and Ni (II) from Industrial Effluents by Brown

Dec 5, 2008 - Engineering, S. V. National Institute of Technology Surat, Surat 395007, Gujarat, India. The biomass of Cystoseira indica (RB) was chemi...
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Ind. Eng. Chem. Res. 2009, 48, 961–975

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Removal of Cu(II) and Ni(II) from Industrial Effluents by Brown Seaweed, Cystoseira indica Shaik Basha,†,‡ Z. V. P. Murthy,*,‡ and B. Jha† Discipline of Marine Biotechnology & Ecology, Central Salt and Marine Chemicals Research Institute, Council of Scientific and Industrial Research, BhaVnagar 364 002, Gujarat, India, and Department of Chemical Engineering, S. V. National Institute of Technology Surat, Surat 395007, Gujarat, India

The biomass of Cystoseira indica (RB) was chemically modified by cross-linking it with epichlorohydrin (CB1, CB2), and the same was oxidized by potassium permanganate (CB3) which was later employed for the treatment of Cu(II) and Ni(II) from effluents. The results indicated that biosorption equilibriums were rapidly established in about 30 and 75 min for Cu(II) and Ni(II), respectively. The metal biosorption was strictly pH dependent, and maximum removal of metals was observed at pH 6.0. The biosorption data dovetail the Langmuir isotherm, and the process obeyed pseudo-second-order kinetics. An intraparticle diffusion based Weber-Morris model was applied to evaluate rate-limiting steps, and the results suggested that film diffusion controlled the overall biosorption process. Fourier transform infrared analysis revealed that amino, hydroxyl, carboxyl, ether, and hydroxyl functional groups were involved in the metal binding and the sorption process was dominated by complexation as well as ion exchange. The loaded biosorbent was regenerated using HCl and used repeatedly over five cycles with little loss of uptake capacity beyond the second cycle. 1. Introduction The disposal of effluents containing heavy metals is related to a panoply of industrial operations, such as electroplating, chemical manufacturing, leather tanning, and especially mining and mineral processing. The removal of such contaminants up to levels approved by national or international agencies could not be entirely solved by conventional methods like precipitation, adsorption, coagulation, etc.1,2 Recently, recurrent interest in the application of biomass of diverse origin in heavy metal removal from various industrial effluents or water resources has been observed. Sorption with biomaterials has become an alternative to traditional methods of industrial wastewater treatment, which has been relatively inexpensive and nonhazardous, and might permit recovery of the metals from the sorbing biomass.3,4 The potential of nonviable brown seaweeds in the recovery of heavy metal ions from aqueous effluents has been well demonstrated.5,6 Recent investigations by various groups have shown that selected species of brown seaweeds possess impressive sorption capacities for the removal of Cu(II) and Ni(II) due to their high uptake capacities and availability in enormous amounts from oceans.7-9 Cystoseira indica, an abundantly available seaweed along the Suarashtra-Kutchch coast of India, could be economically used as a potential biosorbent for heavy metal removal from aqueous solutions. It was pretreated in order to enhance the sorption performance and also to strengthen it for sorption process applications. To enhance the removal efficiency of metal ions by the biomass, various pretreatments are available. Pretreatment may be in terms of hardening the cell wall structure through a cross-linking reaction using epichlorohydrin,10 or increasing the negative charge on the cell surface by NaOH treatment,11 or opening of the available sites for the adsorption by acid treatment,12 and enhancing ion exchange by Ca2+ solution treatment.13 However, * To whom correspondence should be addressed. Tel.: +91 261 2201641, +91 261 2223371to +91 261 2223374. Fax: +91 261 2227334. E-mail: [email protected] or [email protected]. † Council of Scientific and Industrial Research. ‡ S. V. National Institute of Technology Surat.

studies on the use of chemically modified seaweed for Cu(II) and Ni(II) removal from industrial effluents are very restricted.8,11 In the present work, the brown seaweed, Cystoseira indica, an bountifully available biomaterial, was studied as a low-cost biosorbent to remove Cu(II) and Ni(II) from industrial wastewater. The influence of exposure time, initial metal concentration, and pH on the sorption capacity of the metal onto the studied biomasses was investigated. In addition, kinetic as well as equilibrium modeling was carried out using well-known models to understand the mechanism that could possibly occur in the present liquid phase biosorption system. 2. Materials and Methods 2.1. Biomass and Chemical Modification. The brown alga Cystoseira indica was collected from the Suarashtra coast of Gujarat (Veraval), India, and its dried biomass (designated as the raw biomass, RB) of a size fraction of 0.35-0.50 mm was subjected to various chemical treatments. The chemical modification of C. indica was carried out by the procedure reported elsewhere.14 The biomasses CB1 and CB2 were obtained by cross-linking the raw biomass with epichlorohydrin followed by washing with 70 and 20% aqueous 2-propanol, respectively. The biomass CB2 was washed with 20% aqueous 2-propanol to reduce the cost of the treated sorbent. CB3 biomass was obtained by oxidizing raw biomass by potassium permanganate.14,15 The surface areas, pore volumes, and pore sizes of various forms of C. indica have been reported earlier.14 2.2. Wastewater Samples. The wastewater samples were collected from a metallurgical industry located in an industrial zone of Bharuch, Gujarat state, India. Triplicate samples were collected in polyethylene bottles and placed in a cooler for transportation to the research laboratory. Metal species in the samples were identified, and their initial concentrations were determined using inductively coupled plasma atomic emission spectrometry before the biosorption cycles were initiated. They contained Cu, Ni, Cd, and Cr at 1305 ( 13.75, 1075 ( 6.58, 0.615 ( 0.02, and 0.917 ( 0.014 mg/L, respectively, with pH 0.9 ( 0.1. Since the wastewater had very high concentrations

10.1021/ie801071w CCC: $40.75  2009 American Chemical Society Published on Web 12/05/2008

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of copper and nickel, appropriate dilutions were made before use to the working range of these metals and also to ensure that the other metals were below the detectable range. 2.3. Biosorption Experiments. In order to determine the contact time required to reach equilibrium, biosorption dynamic experiments were performed at a constant temperature of 25 ( 1 °C to be representative of environmentally relevant conditions. The effect of pH on biosorption was investigated in the pH range 0.9-7 with initial concentrations of 195.7 and 146.9 mg/L for Cu(II) and Ni(II), respectively. The pH was monitored and controlled with a pH meter using 2 M NaOH and/or HCl. The effect of biomass concentration on the removal of Cu(II) and Ni(II) at 122.63 and 91.45 mg/L concentrations was studied employing 0.5, 1.0, 1.5, 2.0 and 2.5 g/L biomass. After attaining equilibrium (8 h), the aqueous phases were separated from the biosorbents by filtration using 0.45 mm Whatman filter paper and the filtrates were stored for Cu(II) and Ni(II) analysis. Kinetic experiments were carried out in 250 mL Erlenmeyer flasks containing wastewater solutions (100 mL) of known concentrations to which known weights of biosorbent were added. The mixtures were agitated on a rotary shaker (200 rpm) at pH 6.0. The pH was monitored and controlled with a pH meter using 2 M NaOH and/or HCl. Samples (5 mL) were taken out at predetermined time intervals and filtered (membrane filtration, Millipore 0.45 mm pore size), and the filtrates were stored for analysis. Batch equilibrium sorption experiments were performed using 100 mL Erlenmeyer flasks at pH 6.0 and 25 ( 1 °C. The initial Cu(II) and Ni(II) concentrations varied from 42.6 to 211.7 and 29.46 to 154.9 mg/L, respectively. A given amount of biomass was suspended in 100 mL of metal solution and stirred at 200 rpm. Solution pH was adjusted by using 2 M NaOH and/or HCl solutions. After the sorption equilibrium was reached (8 h), the solution was separated from the biomass by membrane filtration (Millipore 0.45 mm pore size) and the filtrates were analyzed for the remaining Cu(II) and Ni(II). Stock solutions of copper and nickel at 1000 mg/L were prepared in double-distilled water using analytical grade reagents, copper sulfate, and nickel sulfate. In the competitive metal sorption experiments, two heavy metal ions were studied. In each experiment, the initial concentration of one heavy metal ion was fixed while that of the other one was varied by premade solutions of copper(II) and nickel(II). Other procedures were the same as those used in the biosorption isotherm experiments. 2.4. Desorption Experiments. In the desorption experiments, the metal-sorbed biomass (after copper or nickel biosorption at initial pH 6 with a 0.1 g amount of the biomass in 100 mL of metal solution for 8 h) was regenerated in 100 mL of 0.2 M HCl solution on a rotary shaker at 200 rpm for 1 h and then washed with 0.2 M NaOH solution and finally with Millipore water until a neutral pH was obtained. The regenerated biomass was reused in the next cycle of sorption experiments. All the biosorption/desorption experiments were repeated twice to confirm the results. The data were the mean values of two replicate determinations. Control experiments, processed without the addition of biosorbents, confirmed that the sorption of metals on the walls of glass flasks or in the filtration systems was negligible. 2.5. Analytical Procedure. Metal concentration was determined by inductively coupled plasma atomic emission spectrometry (ICP, Perkin-Elmer, Optima 2000). The amount of metal biosorbed at equilibrium, qe (mg/g), which represents the metal uptake, was calculated from the difference in metal

concentration in the aqueous phase before and after biosorption using the following equation: qe )

V(Ci - Ce) W

(1)

where V is the volume of metal solution (L), Ci and Ce are the initial and equilibrium concentrations of metal in solution (mg/ L), respectively, and W is the mass of dry seaweed (g). 2.6. FT-IR, SEM, and EDX Studies. Infrared spectra of unloaded and metal loaded biomasses of C. indica were obtained using a Fourier transform infrared spectrometer (FT-IR GX 2000, Perkin-Elmer). Before the analysis, the wet samples were freeze-dried, and 30 mg of finely ground biomass was pelleted with 300 mg of KBr (Sigma) in order to prepare translucent sample disks. The FT-IR spectra were recorded over the wavenumber range 400-4000 cm-1 with 10 scans at a resolution of 4 cm-1. The surface structure of biosorbents before and after sorption were analyzed by scanning electron microscopy (SEM) coupled with energy dispersive X-ray analysis (EDX) using a JEOL 5600 LV SEM. Unloaded and metal-loaded C. indica biomass samples were mounted on a stainless steel stab with a double-stick tape followed by sputter coating gold to improve conductivity to increase the electron conduction and to improve the quality of the micrographs. 2.7. Nonlinear Regression Analysis. All the model parameters were evaluated by nonlinear regression using the DATAFIT software (Oakdale Engineering, USA). The optimization procedure requires an error function to be defined in order to be able to evaluate the fitness of the equation to the experimental data.16 Apart from the regression coefficient (R2), the residual or sum-of-squares error (SSE) and the standard error (SE) of the estimate were also used to gauge the goodness of fit. SSE can be defined as m

SSE )

∑ (Q - q )

2

i

i

(2)

i)1

SE can be defined as SE )



m

∑

1 (Q - qi)2 m - p i)1 i

(3)

where qi is the observation from the batch experiment i, Qi is the estimate from the isotherm for the corresponding qi, m is the number of observations in the experimental isotherm, and p is number of parameters in the regression model. The smaller SE and SSE values indicate better curve fitting. The F-ratio is the ratio of the mean square of the model to the mean square of the true error. A good model will have a high mean square for the model; therefore, the larger this ratio, the better the model suits the experimental data. In the present study, the correlation coefficient, R2, SE, SSE, F-ratio, and predicted qe/qm (wherever applicable) values were used to determine the best-fit biosorption kinetic as well as isotherm model. 3. Results and Discussion 3.1. Effect of pH on Metal Sorption. The biosorption characteristics of Cu(II) and Ni(II) with various pH values in the range 0.9-7.0 were studied at initial concentrations of 195.7 and 146.9 mg/L, respectively, using four biomasses as shown in Figure 1. The biosorption of both metals by surface functional groups was strongly pH dependent and increased with pH for all biomasses. Cu(II) and Ni(II) biosorptions were very low at

Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 963

Figure 1. (a) Effect of pH on Cu(II) sorption by chemically modified and raw C. indica with initial Cu(II) concentration of 195.7 mg/L and solid to liquid ratio (s/l) of 1.0 g/L, for 300 min. (b) Effect of pH on Ni(II) sorption by chemically modified and raw C. indica with initial Ni(II) concentration of 146.9 mg/L and solid to liquid ratio (s/l) of 1.0 g/L, for 300 min.

pH e3, which later on increased to 90-95% within the next 3 pH units. The highest uptake capacities of Cu(II) and Ni(II) are 125.42 mg/g (1.97 mmol/g) and 97.96 mg/g (1.67 mmol/g) for CB1, respectively, at pH 6.0. This increase in metal uptake could be due to the ionization of carboxyl groups present in the seaweed at this pH, which could result in higher interaction with metals. With further increase in pH to about 7.0, the metal uptake of all the biomasses decreased. The reduction in uptake rate at pH values higher than 6.0 may be ascribed to metal hydroxylation yielding metal hydroxides or hydrated oxides which leads to metal passivation.17 Earlier studies on heavy metal biosorption have shown that pH is an important parameter affecting the biosorption process.7,17 The reaction of metal ions in the solution with the biomass can be described by the following equilibrium: HnB + Mn+ S MB + nH+

(4)

where M represents the metal, n its charge, and B the biosorptive active centers. According to equation 4, the pH should influence the metal ion biosorption because of the competition between the metal and H+ ions for the active biosorption sites.11 Furthermore, the pH dependency on the metal ion uptake by the biomasses could also be justified by the associationdissociation of certain functional groups, such as the carboxylic groups.11,18 In fact, it is known that, at low pH, most of the carboxylic groups are not dissociated and cannot bind the metal ions in solution, although they may take part in complexation reactions. With increasing pH, more ligands, such as amino and carboxyl groups, would be exposed leading to attraction between these negative charges and the metals and hence increases in biosorption onto the cell surface. 17 3.2. Biosorption Kinetics and Modeling. Various chemical modifications were applied to enhance metal removal by the C. indica biomass, and a series of batch experiments were carried out with the raw and chemically treated biomasses.

Figure 2. (a) Experimental and predicted kinetics of Cu(II) sorption by chemically modified and raw C. indica with initial Cu(II) concentration of 122.63 mg/L, pH 6.0, and solid to liquid ratio (s/l) of 1.0 g/L. (b) Experimental and predicted kinetics of Ni(II) sorption by chemically modified and raw C. indica with initial Ni(II) concentration of 91.45 mg/ L, pH 6.0, and solid to liquid ratio (s/l) of 1.0 g/L

Information on the kinetics of metal uptake is required for selecting the optimum operating conditions for further experiments. The uptake of heavy metal ions by seaweeds has often been observed to occur in two stages: an initial rapid uptake due to surface adsorption on the cell walls and a subsequent slow uptake due to membrane transport of the metal ions on the cytoplasm of the cells.5,19 Both Cu(II) and Ni(II) biosorption by various forms of Cystoseira indica algae exhibited the same behavior as shown in Figure 2a and 2b, respectively. It can be noticed that the contact time significantly affects the metal uptake: the metal sorption increases sharply in the first 30 and 75 min for Cu(II) and Ni(II), respectively, and tapers off thereafter, as equilibrium is approached. This relatively rapid metal uptake indicates that the sorption process occurs mainly on the surface of the sorbent. The uptake of heavy metal ions by biosorbents has often been observed to occur in two stages, the first rapid and quantitatively predominant and the second slower and quantitatively insignificant, which has been extensively reported in the literature.20 The rapid stage was probably due to the abundant availability of active sites on the biomass, and with the gradual occupancy of these sites, the sorption

964 Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 Table 1. Kinetic Model Parameters for Cu(II) and Ni(II) Biosorption on Various Forms of C. indicaa biomass CB1 parameter

CB2

Cu(II)

Ni(II)

Cu(II)

k (mg/g) V (1/min) kV (mg/g/min) R2 SE SSE F-ratio

31.386 ( 1.36 0.169 ( 0.05 5.314 ( 0.06 0.867 0.877 0.539 45.663

11.076 ( 1.04 0.336 ( 0.04 3.727 ( 0.05 0.954 0.418 0.122 145.14

29.845 ( 3.16 0.175 ( 0.01 5.217 ( 0.03 0.879 0.829 0.481 51.151

k1 (1/min) R2 SE SSE F-ratio

0.051 ( 0.011 0.034 ( 0.015 0.813 0.8545 1.350 1.1655 2.736 2.164 62.856 74.71

RE (mg/g/min) βE (g/mg) R2 SE SSE F-ratio

60.495 ( 2.68 0.091 ( 0.02 0.614 8.665 450.50 9.544

5.995 ( 0.46 0.071 ( 0.01 0.959 2.907 50.692 139.48

51.562 ( 5.43 0.091 ( 0.02 0.6384 8.237 407.14 10.576

qe (mg/g) 129.32 ( 2.16 0.002 k2 (g/mg/min) rads(i) ) h (mg/g/min) 11.735 ( 2.04 2.934 SR50 (mg/g/min) SR90 (mg/g/min) 0.117 2 0.994 R SE 0.054 SSE 0.017 F-ratio 1043.1

105.02 ( 1.05 0.0006 2.723 ( 0.96 0.681 0.027 0.994 0.062 0.023 960.22

119.99 ( 1.67 0.002 10.618 ( 1.56 2.654 0.106 0.994 0.054 0.017 1080.3

0.539 ( 0.11 0.613 0.576 1.327 6.338

2.450 ( 0.09 0.863 0.345 0.238 42.712

0.324 ( 0.05 0.850 0.402 0.646 22.631

βIS × 102 (1/min) R2 SE SSE F-ratio

0.744 ( 0.02 0.915 0.325 0.755 84.624

0.366 ( 0.05 0.973 0.247 0.424 185.67

0.602 ( 0.06 0.921 0.303 0.659 94.627

βIS × 102 (1/min) R2 SE SSE F-ratio

0.750 ( 0.08 0.932 0.248 0.370 104.36

0.364 ( 0.02 0.950 0.222 0.346 130.63

0.588 ( 0.07 0.934 0.248 0.369 11.024

CB3 Ni(II)

RB

Cu(II)

Ni(II)

Cu(II)

Ni(II)

23.365 ( 1.29 0.225 ( 0.02 5.264 ( 0.02 0.819 0.992 0.689 37.193

6.977 ( 2.67 0.418 ( 0.04 2.916 ( 0.05 0.973 0.311 0.068 257.95

31.083 ( 3.29 0.169 ( 0.01 5.249 ( 0.03 0.868 0.865 0.524 45.945

9.174 ( 1.22 0.372 ( 0.02 3.413 ( 0.02 0.959 0.377 0.099 186.60

Fractional-Power Model 9.564 ( 2.16 0.362 ( 0.03 3.461 ( 0.06 0.962 0.380 0.101 178.22

Pseudo-First-Order Model 0.046 ( 0.011 0.037 ( 0.017 0.855 0.853 1.222 1.180 2.295 2.195 77.28 69.102

0.051 ( 0.021 0.035 ( 0.016 0.049 ( 0.012 0.034 ( 0.014 0.876 0.795 0.848 0.813 1.174 1.266 1.260 1.233 2.182 2.425 2.405 2.327 80.87 31.102 65.155 63.261

Elovich Model 5.030 ( 0.62 0.069 ( 0.03 0.974 2.353 33.219 224.52

17.959 ( 2.42 0.073 ( 0.01 0.669 9.644 558.43 12.113

3.799 ( 0.79 0.067 ( 0.01 0.989 1.513 13.746 582.13

60.876 ( 5.16 0.093 ( 0.02 0.612 8.564 440.02 9.4620

4.829 ( 0.92 0.068 ( 0.03 0.975 2.340 32.957 236.69

95.62 ( 0.62 0.0004 1.794 ( 0.59 0.448 0.018 0.992 0.067 0.027 770.74

125.52 ( 2.16 0.002 11.521 ( 2.05 2.880 0.115 0.994 0.054 0.017 1068.7

101.09 ( 0.11 0.0005 2.149 ( 0.16 0.537 0.021 0.993 0.025 0.017 858.87

1.081 ( 0.06 0.779 2.027 8.215 7.650

0.417 ( 0.02 0.789 0.384 0.591 17.990

1.490 ( 0.15 0.894 0.745 1.112 16.912

0.279 ( 0.01 0.964 0.271 0.443 164.28

0.611 ( 0.08 0.946 0.276 0.513 142.37

0.331 ( 0.10 0.967 0.254 0.473 170.68

0.281 ( 0.02 0.974 0.165 0.190 264.95

0.606 ( 0.06 0.962 0.247 0.367 201.62

0.330 ( 0.02 0.957 0.193 0.262 180.17

Pseudo-Second-Order Model 99.85 ( 0.64 0.0006 2.388 ( 0.59 0.597 0.024 0.993 0.063 0.023 922.89

122.46 ( 1.58 0.001 6.115 ( 1.49 1.528 0.061 0.990 0.099 0.060 296.09

Intraparticle Diffusion Model kp (mg/g/min0.5) R2 SE SSE F-ratio

1.165 ( 0.27 0.836 0.431 0.372 29.117

0.316 ( 0.04 0.716 0.778 2.421 10.107

Mathews and Weber (M&W) Model 0.320 ( 0.02 0.936 0.295 0.622 110.29

0.545 ( 0.07 0.913 0.321 0.717 80.674

Frusawa and Smith (F&S) Model

a

0.315 ( 0.11 0.956 0.216 0.325 150.85

0.555 ( 0.09 0.893 0.356 0.759 85.627

SE, standard error of the estimate; SSE, residual or sum-of-squares error.

became less efficient in the slower stage.21 The quick equilibrium time may be attributed to the particle size. The effective surface area is high for small particles. This result was typical for biosorption of metals involving no energy-mediated reactions, where metal removed from solution is due to purely physicochemical interactions between the biomass and metal in solution. The rapid kinetics has significant practical importance as it will facilitate smaller reactor volumes, ensuring efficiency and economy. In order to examine the controlling mechanism of the adsorption process, experimental kinetic data were analyzed using four kinetic models: the fractional power,22 pseudo-firstorder,23 Elovich,24 and pseudo-second-order models.25 The estimated parameters of the fractional power model22 indicate that it satisfactorily described the time-dependent Ni(II)

compared to Cu(II) on various biomasses of C. indica as the values of the constant V for both the metals were less than 1 and the regression coefficients were greater than 0.954 for Ni(II) and 0.819 for Cu(II) (Table 1). Also, SE and SSE values were below 1 for both metals. The values of the product of power function model constants “kV”, which is “specific biosorption rate at unit time” followed the order CB1 > RB > CB3 > CB2 and CB1 > RB> CB2 > CB3 for Cu(II) and Ni(II), respectively. The kinetic constant, k1, of the pseudo-first-order model23 for the biosorption of Cu(II) and Ni(II) on to biomasses is given in Table 1. The results demonstrated that Lagergren model23 is not applicable in the present case as low regression coefficients (1.350) and SSE (>1.736) were observed for both metals. Therefore, the reaction involved in the present biosorption system is not of pseudo first order.

Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 965 24

The kinetic constants obtained from the Elovich equation are presented in Table 1. The results demonstrate a significant relationship between Ni(II) sorbed, qt, and t in these studies with regression coefficients greater than 0.959, while a very poor fit was observed in the case of Cu(II). However, SE and SSE values were greater than 1 for both metals. Therefore, the kinetic data of both Cu(II) and Ni(II) did not show satisfactory compliance with the Elovich equation. The results in Table 1 show the biosorption rate constant, k2, initial biosorption rate, h, and equilibrium biosorption capacity, qe, of the pseudo-second-order model.25 These results show very good compliance with the pseudo-second-order equation for both metals with high regression coefficients (>0.990) and low SE ( 10.62 (CB2) > 6.11 mg/g/min (RB). This indicates that CB1 can sorb Cu(II) more rapidly than RB, CB2, and CB3 from wastewater. Ni(II) also provided a similar trend; however, CB2 showed greater tendency than RB. Statistically, the pseudo-second-order model provided a good fit to the experimental data with low SE and SSE and high F-ratio values compared to other kinetic models. According to the pseudo-second-order kinetic model,25 the rate of a biosorption reaction nonlinearly decreased with time. For example, the instantaneous rates at 50 and 90% of metal biosorption (SR50 and SR90, respectively) can be calculated from pseudo-secondorder rate equations: k2qe2 h ) 4 4

(5)

k2qe2 h ) 100 100

(6)

SR50 ) k2[qe - (0.5qe)]2 ) SR90 ) k2[qe - (0.9qe)]2 )

Therefore, SR50 and SR90 values are 1/4 and 1/100 of the initial biosorption rate, h, respectively (Table 1), and comparisons reported here based on h values can be extended to the entire experiment duration. 3.3. Mass Transfer Effects during Biosorption. From a mechanistic point of view to interpret the kinetic experimental data, prediction of the rate-limiting step is an important factor to be considered in the sorption process.27 Although kinetic studies help to identify the sorption process, predicting the mechanisms is required for design purposes. By ignoring the diffusion resistance of Cu(II) and Ni(II) from bulk fluid to the liquid film surrounding the biosorbent, the diffusion of ions into C. indica can be divided into a three-step process: boundary layer diffusion, intraparticle diffusion, and biosorption on binding sites. In many cases of biosorption, there is the possibility that intraparticle diffusion will be the ratelimiting step and this is normally assessed by examining the relationship between the adsorption and the square root of time. An intraparticle rate constant can be defined using the equation described by Weber and Morris:28 qt ) t1/2

(7)

Figure 3. (a) Intraparticle diffusion plots for the biosorption of Cu(II) on various forms of C. indica. (b) Intraparticle diffusion plots for the biosorption of Ni(II) on various forms of C. indica.

comprised by two phases denoting that, although intraparticle diffusion is significant, more than one process is affecting the biosorption. This type of behavior has been reported previously,29 and the double nature of these relationships has been interpreted in terms of two processes: boundary diffusion, which gives the initial, curved portion, and intraparticle diffusion, which gives the final linear portion. Under these circumstances, the slope of the final linear portion of the plot has been identified as the intraparticle diffusion rate constant kp (mg/g/min1/2). Common to all experimental cases, the kp values of CB1 were higher than those of RB, CB2, and CB3 for both metals (Table 1). This indicates that both Cu(II) and Ni(II) diffuse into the pores of CB1 more easily than those of others. The chemical modification of C. indica enhanced the diffusion of metals in CB1; however, it was not significant in both CB2 and CB3. External mass transfer has rarely been investigated for metal ion sorption to biosorbent. To determine the extent of external mass transfer resistance around C. indica, a simple approach has been proposed for estimating the mass transfer coefficient in the boundary layer during the biosorption process using the Mathews and Weber (M&W) model and the Frusawa and Smith (F&S) model.30,31 The M&W model, as an application of Fickian laws, expresses the evolution of the concentration of the solute in the solution.31 Its equation is expressed as follows: Ct ) e-βISt Ci

(8)

where βI is the mass transfer coefficient (cm/min); S is the outer surface of biosorbent per unit volume of solution (cm-1). The F&S model equation is given by

1/2

The relationships between qt and t for Cu(II) and Ni(II) are shown in Figure 3a and 3b, respectively. Based on this figure, the biosorption processes of both Cu(II) and Ni(II) are

mKL - 1+mKL βISt Ct 1 ) + e mKL Ci 1 + mKL 1 + mKL

(9)

966 Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009

where Ci is the initial metal concentration (mg/L), Ct is the metal concentration (mg/L) at time t, m is the mass of sorbent per unit volume of solution (g/L), and KL is the Langmuir constant (L/mg). The βIS values were calculated along with R2, SE, SSE, and F-ratio values according to the above models (Table 1). The βIS values obtained from the F&S and M&W models for both metals were found to be close to each other, though the statistical parameters were slightly varied for the two models. The βIS values decreased in the order CB1 > RB > CB2 > CB3, indicating that the external mass transfer rate is slower for CB1.30 However, the βIS values of all the studied biosorbents indicate that the velocity of sorbent transport from the liquid phase to the solid phase is rapid enough to suggest the use of these biosorbents for the treatment of effluents enriched in these metals. The same conclusion was drawn by Panday et al.32 for Cu(II) removal and Ozer et al.30 for acid dye removal from effluents. In order to determine the actual rate-controlling step involved in the metal biosorption process, the experimental kinetic data were further analyzed using the kinetic expression given by Boyd et al.:33 F)1-

6 -Bbt e Π2

(10)

Df ) 0.23

Rpε qe t1/2 Ci

(14)

for the film diffusion coefficient, where Rp is the radius of the biosorbent, ε is the film thickness (10-3 cm),39 qe (mg/g) is the amount of metal sorbed, and Ci is the initial concentration (mg/ L). By considering the appropriate data and the respective overall rate constants, pore and film diffusion coefficients for various biomasses were determined (Table 2). It clearly appears that both Cu(II) removal and Ni(II) removal on C. indica are controlled by film diffusion, since coefficient values are on the order of 10-8 cm2/s. 3.4. Effect of Biomass Concentration. The biomass concentration is an important variable during metal uptake. In general, increase in biomass concentration reduces metal sorption per gram of biomass.40 It has been suggested that electrostatic interactions between cells could be a significant factor in the relationship between biomass concentration and metal sorption. In this connection, at a given metal concentration, the lower the biomass concentration in suspension, the higher will be the metal/biosorbent ratio and the metal retained by the sorbent unit, unless the biomass reaches saturation. High biomass concentrations can exert a shell effect, protecting the active sites from being occupied by metal. The result of this is

where Bb is a constant and F is the fractional attainment of equilibrium at time t given by F)

qt qe

(11)

where qe and qt represent the amount of metal sorbed (mg/g) at equilibrium and any time t, respectively. To compute Bbt, eq 10 is substituted into eq 11 and the kinetic expression becomes

( )

Bbt ) -0.4977 - ln 1 -

qt qe

(12)

Thus, the value of Bbt can be computed for each value of F, and then plotted against time (Figure 4a and 4b, respectively, for Cu(II) and Ni(II)) to configure the so-called Boyd plots.33 The linearity of these plots is employed to distinguish between external-transport-controlled (film diffusion) and intraparticletransport-controlled rates of biosorption. A straight line passing through the origin is indicative of biosorption processes governed by particle diffusion mechanisms; otherwise they are governed by film diffusion.34 In our case, the plots were neither linear nor passed through the origin (Figure 4). This indicates that, in all the sorbents, film diffusion is the rate-limiting biosorption process for both Cu(II) and Ni(II). Similar results were obtained by El-Kamash et al.35 and Wang et al.36 In order to confirm that the biosorption process is film diffusion controlled, attempts were made to calculate the coefficients of the process. If film diffusion was the rate-determining step, the value of the film diffusion coefficient (Df) should be in the range 10-6-10-8 cm2/s. If pore diffusion was rate limiting, the pore diffusion coefficient (Dp) should be in the range 10-11-10-13 cm2/s.36,37 Assuming spherical geometry for the sorbent, the overall rate constant of the process can be correlated with the pore diffusion coefficient and the film diffusion coefficient independently according to the following equations:38 Dp ) 0.03

Rp2 t1/2

for the pore diffusion coefficient, and

(13)

Figure 4. (a) Boyd plot for the biosorption of Cu(II) on various forms of C. indica. (b) Boyd plot for the biosorption of Ni(II) on various forms of C. indica. Table 2. Diffusion Coefficients for the Removal of Cu(II) and Ni(II) by C. indica pore diffusion coeff from eq 13 ( ×10-4 cm2/s)

film diffusion coeff from eq 14 ( ×10-8 cm2/s)

biosorbent

Cu(II)

Ni(II)

Cu(II)

Ni(II)

CB1 CB2 CB3 RB

14.114 ( 0.74 15.061 ( 0.81 13.115 ( 1.02 7.169 ( 0.69

4.715 ( 0.62 5.021 ( 0.27 4.372 ( 0.11 2.390 ( 0.24

5.956 ( 0.36 6.220 ( 0.48 5.350 ( 0.31 2.991 ( 0.17

2.161 ( 0.12 2.224 ( 0.09 1.890 ( 0.06 1.080 ( 0.02

Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 967

Figure 5. (a) Effect of solid to liquid ratio on Cu(II) sorption by chemically modified and raw C. indica with initial Cu(II) concentration of 122.63 mg/ L, pH 6.0, for 300 min. (b) Effect of solid to liquid ratio on Ni(II) sorption by chemically modified and raw C. indica with initial Ni(II) concentration of 91.45 mg/L, pH 6.0, for 300 min.

a lower specific metal uptake, that is, a smaller amount of metal uptake per biomass unit. Similar results were obtained with all the biomasses tested (Figure 5). In the tests, various biomass concentrations of 0.5, 1.0, 1.5, 2.0, and 2.5 g/L were used, while volume, initial concentration of the metal solution, and the pH value were kept constant. The results indicated that the maximum sorption capacity of both metals corresponded to the lowest biomass concentration of the five used (1.0 g/L), irrespective of the type of biomass, which confirms the loss of biosorbent effectiveness at high concentrations. Several researchers obtained similar results.41,42 3.5. Effect of Chemical Modification. Three different chemical modifications were applied to C. indica to enhance the uptake of metals, and these methods also can improve the mechanical stability and pressure resistance of the seaweed.43 Epichlorohydrin modification facilitated chemical cross-linking between various polysaccharides via the hydroxylic groups in alkaline conditions, and DMSO will expose the hidden metal binding groups before cross-linking.43 Jeon et al.15 reported that oxidation with potassium permanganate, which in turn results in carboxylated alginic acid, has a high uptake capacity to heavy metals. In the present study, the biomass oxidized with potassium permanganate (CB3) did not show any improvement in metal binding capacity compared to other biosorbents (CB1 and RB). The maximum uptake of both Cu(II) and Ni(II) followed the decreasing order CB1> RB > CB3 > CB2. The Cu(II) and Ni(II) uptake capacities of CB1 increase by 4.2 and 5.5%, respectively, compared with RB. Epichlorohydrin-modified biomass (CB1) showed a high uptake capacity for both metals compared with raw seaweed. Based on the maximum uptake capacity, CB2 is the best sorbent followed by RB for Cu(II) and Ni(II) removal applications.

Figure 6. (a) Experimental and Langmuir isotherms for sorption of Cu(II) at pH 6.0 and solid to liquid ratio (s/l) of 1.0 g/L. (b) Experimental and Langmuir isotherms for sorption of Ni(II) at pH 6.0 and solid to liquid ratio (s/l) of 1.0 g/L.

3.6. Biosorption Isotherms. The influence of initial Cu(II) and Ni(II) concentrations on biosorption were examined at pH 6.0, and isotherms along with predicted Langmuir isotherms are shown in Figure 6a and 6b, respectively. The equilibrium sorption capacities of all sorbents increased with increasing initial metal concentration of both Cu(II) and Ni(II) due to the increase in the number of ions competing for the available binding sites in the biomass. The uptake of Cu(II) and Ni(II) by all four sorbents gave a plateau beyond 180 and 132 mg/L, respectively, showing the saturation of binding sites at higher concentration levels. According to experimental data, the maximum amounts of Cu(II) biosorbed were 125.05, 110.65, 121.2, and 122.15 mg/g (1.96, 1.74, 1.90, and 1.93 mmol/g, respectively) and the maximum amounts of Ni(II) biosorbed were 100.38, 95.52, 96.68, and 98.05 mg/g (1.71, 1.63, 1.64, and 1.67 mmol/g, respectively) for CB1, CB2, CB3, and RB, respectively. The order of both metal uptakes for various biomasses was CB1 > RB > CB3 > CB2. The biosorption phenomena at the solid-liquid interface are commonly described by the sorption isotherm model, and sorption isotherms are an essential data source for the practical design of biosorption systems and understanding the relation of biosorbent and sorbate. In order to determine the mechanism of metal biosorption onto C. indica, the experimental data were applied to the Langmuir,44 Dubinin-Radushkevich,45 Frumkin,46 Harkins-Jura,47 and Sips48 isotherm equations. The model parameters along with statistical parameters are summarized in Table 3. The Langmuir model served to estimate the maximum metal uptake values where they could not be reached in the experi-

968 Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 Table 3. Equilibrium Model Parameters for Cu(II) and Ni(II) Biosorption on Various Forms of C. indica biomass CB1 parameter

Cu(II)

CB2 Ni(II)

CB3

Cu(II)

Ni(II)

RB

Cu(II)

Ni(II)

Cu(II)

Ni(II)

132.71 ( 2.61 0.007 0.022 0.990 0.156 0.073 95.962

111.26 ( 3.48 0.007 0.022 0.991 0.225 0.035 105.07

141.54 ( 4.39 0.006 0.043 0.995 0.117 0.022 114.37

121.35 ( 5.16 0.007 0.036 0.990 0.272 0.042 98.015

520.13 ( 14.29 133.81 ( 5.14 0.968 15.119 914.44 31.762

418.05 ( 19.64 112.02 ( 6.49 0.982 12.105 586.19 33.052

530.58 ( 21.35 135.49 ( 4.62 0.970 14.280 815.75 36.274

411.30 ( 17.62 113.63 ( 5.94 0.976 12.980 673.95 28.343

0.040 ( 0.016 3.974 ( 0.17 0.836 0.118 0.573 20.335

0.032 ( 0.01 1.939 ( 0.26 0.883 0.758 2.298 30.124

0.040 ( 0.02 3.966 ( 0.19 0.831 0.1238 0.608 17.367

0.032 ( 0.016 1.982 ( 0.12 0.881 0.7608 2.314 29.769

426.80 ( 5.96 2.086 ( 0.16 0.821 3.522 49.407 18.341

227.89 ( 11.24 1.985 ( 0.12 0.829 6.412 164.44 19.398

394.85 ( 14.37 2.080 ( 0.26 0.809 3.961 62.762 16.928

269.61 ( 9.63 1.992 ( 0.36 0.840 5.203 108.23 21.050

10 934 ( 226.7 8.219 ( 2.16 0.773 0.971 1.421 2.605 51.115

10 867 ( 208.3 7.156 ( 3.15 0.722 0.967 1.619 2.786 43.412

10 050 ( 128.6 9.468 ( 1.64 0.837 0.971 1.473 2.650 50.251

13 267 ( 154.3 6.145 ( 2.17 0.770 0.963 1.639 2.807 39.147

Langmuir Model qm (mg/g) KL (L/mg) RL R2 SE SSE F-ratio

143.31 ( 3.25 0.005 0.032 0.997 0.109 0.032 133.4

131.56 ( 4.69 0.006 0.030 0.997 0.143 0.053 125.9

137.17 ( 5.18 0.006 0.029 0.992 0.128 0.057 103.82

116.82 ( 4.25 0.007 0.025 0.995 0.156 0.048 118.22

B (mol2/kJ2) qm (mg/g) R2 SE SSE F-ratio

402.63 ( 12.15 132.54 ( 7.32 0.940 12.280 726.36 33.246

363.03 ( 10.05 113.42 ( 8.32 0.905 11.495 528.54 38.301

424.71 ( 12.69 122.22 ( 5.93 0.925 11.096 492.55 48.741

f -∆G° (kJ/mol) R2 SE SSE F-ratio

0.050 ( 0.01 3.312 ( 0.49 0.877 0.020 0.312 30.265

0.040 ( 0.01 3.418 ( 0.62 0.840 0.117 0.546 20.939

0.038 ( 0.015 3.446 ( 0.34 0.863 0.101 0.412 25.203

AHJ BHJ R2 SE SSE F-ratio

408.88 ( 15.62 2.077 ( 0.24 0.812 3.795 50.760 17.198

253.16 ( 20.36 1.979 ( 0.61 0.808 6.201 153.80 16.807

368.86 ( 18.62 2.075 ( 0.57 0.791 4.484 80.414 15.143

230.46 ( 10.64 1.979 ( 0.29 0.805 6.877 189.13 16.495

KS (L/g) aS (L/mg) Γ R2 SE SSE F-ratio

11 520 ( 239.6 9.267 ( 1.03 0.819 0.988 0.938 0.264 126.14

6 599.7 ( 395.7 9.035 ( 2.01 0.855 0.989 0.905 0.246 136.94

4 737.5 ( 428.4 16.299 ( 1.69 0.785 0.992 0.737 0.163 191.88

18 955 ( 159.6 6.051 ( 0.69 0.750 0.989 0.889 0.237 141.65

Dubinin-Radushkevich Model 357.46 ( 16.69 107.59 ( 6.35 0.906 10.858 471.65 38.677 Frumkin Model 0.039 ( 0.012 3.118 ( 0.22 0.848 0.109 0.473 22.395 Harkins-Jura Model

Sips Model

ments. The value of KL is a coefficient attributed to the affinity between the sorbent and sorbate.44 Model fits for Langmuir isotherm along and experimental data for Cu(II) and Ni(II) are presented in Figure 6a and 6b, respectively. The values of model constants along with the statistical parameters like R2, SE, SSE, and F-ratio for all biosorbent-metal systems are presented in Table 3. The isotherms of both Cu(II) and Ni(II) were found to be nonlinear over the whole concentration ranges studied, and the correlation coefficients varied from 0.9897 to 0.9985. Statistically, the Langmuir model provided a good fit to the experimental data with low SE and SSE and high F-ratio values compared other models. Moderate values of KL are reflected in the steep initial slope of a sorption isotherm, indicating desirable high affinity. The maximum biosorption capacities of Cu(II) and Ni(II) were determined as 143.3 mg/g (2.25 mmol/g) and 131.6 mg/g (2.24 mmol/g) for CB1, 137.2 mg/g (2.16 mmol/g) and 116.8 mg/g (1.99 mmol/g) for CB2, 132.7 mg/g (2.08 mmol/ g) and 111.3 mg/g (1.93 mmol/g) for CB3, and 141.54 mg/g (2.22 mmol/g) and 121.3 mg/g (2.06 mmol/g) for RB. The essential characteristics of a Langmuir isotherm can be explained in terms of the dimensionless separation factor, RL.49 The RL values are found in the ranges 0.022-0.043 and 0.022-0.036 for Cu(II) and Ni(II), respectively, showing favorable biosorption. The liquid phase biosorptions of Cu(II) and Ni(II) onto C. indica have been analyzed by the Dubinin-Radushkevich equation.45 The isotherm constants along with the statistical parameters are presented in Table 3. In all cases, the values of the correlation coefficients (0.9054-0.9820) were lower than

those of the Langmuir model but higher than those of other two-parameter models. Poor performance in terms of high SE and SSE values of the Dubinin-Radushkevich (D-R) equation indicated the involvement of a metal sorption mechanism other than van der Waals force. The statistical parameters of the Frumkin46 and Harkins-Jura47 models indicate that both models fail to predict the equilibrium isotherm. The abilities of a three-parameter equation, the Sips isotherm,48 to model the equilibrium biosorption data were examined. Table 3 shows the isotherm parameters obtained using nonlinear fitting analysis. At high sorbate concentrations, the Sips isotherm predicts a monolayer sorption capacity characteristic of the Langmuir isotherm. The Sips equation fits adequately the experimental results. The exponent γ value is in the range 0.72-0.85, meaning that the sorption data obtained in this study for both metals is more of a Langmuir form, which was also confirmed by the results shown in Table 3. The biosorption capacities of Cu(II) and Ni(II) onto C. indica were compared with other sorbents reported in the literature and are shown in Table 4. It can be observed that pH 6.0 was found to be optimum in most of the cases for both metals. This shows that C. indica has good biosorption capacity when compared with other sorbents. The values of Cu(II) and Ni(II) uptake capacities found in this work were significantly higher, with two exceptions for Ni(II),50,51 than reported elsewhere. The biosorption capacity differences of metal uptake are due to the properties of each sorbent such as structure, functional groups, and surface area.

Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 969 Table 4. Sorption Capacities for Cu(II) and Ni(II) Using Various Biosorbents copper

a

nickel

biosorbent

sorption capacity, mg/g (mmol/g)

pH

Cystoseira indica Ascophyllum nodosum50 Ascophyllum nodosum51 Sargassum fluitans51 Chlorella miniata52 Chlorella Vulgaris52 Scenedesmus obliquus41 DurVillaea potatorum53 DurVillaea potatorum43 Ecklonia radiate43 Sargassum hemiphyllum9 Sargassum sp.8 Padina sp.8 UlVa sp.8 Gracillaria sp.8 C. Vulgaris40 E. maxima54 Laminaria japonica55 Pilayella littoralis56 UlVa reticulate57 Padina paVonia58 tobacco dust59 biomatrix from rice husk60 Myriophyllum spicatum L.61 Lemna minor L.62 cork biomass63 Gelidium64 Gelidium65

125.05 (1.96) 53.97 (0.85) 100.06 (1.57) 23.26 (0.36) 18.75 (0.29) 33.31 (0.52) 83.27 (1.31) 69.92 (1.09) 69.92 (1.09) 62.93 (0.99) 72.46 (1.14) 47.67 (0.75) 37.50 (0.59) 89.02 (1.40) 94.0 (1.48) 101.03 (1.59) 54.01 (0.85) 56.3 (0.88) 36.0 (0.56) 10.8 (0.17) 29.0 (0.45) 69.0 (1.08) 20.9 (0.33) 33.0 (0.52) 13 (0.20)a

6.0 5.0 5.0 6.0 6.0 4.5 5.0 5.0 5.0 5.0 5.0 5.0 5.0 3.5 6.0 4.5 5.5 5.5 6.34 5.5 8.0 4.0 4.87 5.3 5.3

sorption capacity, mg/g (mmol/g) 100.37(1.71) 135.94(2.32) 114.99(1.96) 43.02(0.73) 20.36(0.35) 12.03(0.20) 30.17(0.51) 66.33(1.13) 35.39(0.60) 35.80(0.61) 36.98(0.63) 17.02(0.29) 16.43(0.28) 23.48(0.40) 22.81(0.39) 46.51(0.79) 58.71 (1.00) 24.5 (0.42) 5.4 (0.09) 3.0 (0.05) 59.0 (1.01) 10.5 (0.18) -

pH 6.0 6.0 5.0 5.0 6.0 6.0 4.0 6.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 4.5 5.0 6.34 6.0 8.0 5.0 5.2 -

Packed-bed column.

3.7. Competitive Effect on Metal Biosorption. The metal uptake can be affected by the presence of other competitive metal ions. Figure 7 demonstrates simultaneous copper and nickel biosorption onto raw biomass of C. indica (RB). Due to the presence of the competitive metal ions, the uptake of the metal ions is negatively affected. The influence on the metal binding, however, was dependent upon the binding strength of the metal ions onto the sorbent. As shown in Figure 7a, the presence of nickel ions slightly affected the biosorption of copper ions; however, copper ions greatly hindered the nickel uptake as demonstrated in Figure 7b. The maximum metal biosorption capacity for copper was 119.15 mg/g (1.88 mmol/ g) RB, while that for nickel was 94.05 mg/g (1.60 mmol/g) RB. Copper ions could form stronger metal complexes than nickel ions. As a result, the competitive effect from the copper ions is more obvious than that from the nickel ions. 3.8. FT-IR, SEM, and EDX Analysis. Numerous chemical groups have been responsible for biosorption metal binding by algae (carboxyl, hydroxyl, amide, ether, etc.); their importance for metal uptake depends on factors such as the quantity of sites, its accessibility, its chemical state, or the affinity between the site and metal.66 Infrared spectra of the biosorbents before metal sorption, termed “pristine biosorbents” (CB1, CB2, CB3, and RB) and metal-loaded sorbents (MCB1, MCB2, MCB3, and MRB) are shown in Figure 8a and 8b, respectively. The functional groups before and after biosorption on various forms of C. indica and the corresponding infrared absorption bands are shown in Table 5. The biomasses CB1 and CB2 showed almost similar spectra, while CB3 and RB showed different absorption peaks. The broad absorption peak at 3397 cm-1 in CB1 and CB2 may be assigned to N-H stretching of the amide group while the absorption peak at 3429 and 3428 cm-1 for CB3 and RB, respectively, may be attributed to the secondary amide group. This implies that the N-H stretching is available in excess quantity for the sorption. After metal biosorption, the peaks on the spectra of metal-contaminated biosorbents show a series of changes compared to those of pristine biosorbents.

Figure 7. (a) Simultaneous biosorption of copper and nickel ions onto raw biomass (RB) of C. indica vs initial Cu(II) concentration. (b) Simultaneous biosorption of copper and nickel ions onto raw biomass (RB) of C. indica vs initial Ni(II) concentration.

The broad and strong bands ranging from 3300 to 3500 cm-1 split into two sharper bands at 3441, 3448, 3362, and 3442 cm-1, which could be assigned to N-H stretching of amine and OH

970 Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009

Figure 8. (a) FT-IR spectra of various forms of C. indica (CB1, CB2, CB3, RB). (b) FT-IR spectra of metal-loaded biosorbents (MCB1, MCB2, MCB3, MRB).

stretching of polymeric compounds.67 One possible explanation is that part of the amine group may be involved in the metal binding. In the presence of formaldehyde, amine could react with the aldehyde group. Another possibility is that formaldehyde could react with an alcoholic group to form a dative linked structure according to the literature:68 2R-OH + HCHO f (R-O)2CH2 + H2O -1

(15)

The shift in the peak at 2929 cm , which was observed in all pristine biosorbents (indicative of the existence of O-H stretching of the carboxylic group), was not observed in metalloaded biosorbents except MCB3. However, the absorbance at 1729 cm-1 for CB1 and CB2 and 1620 cm-1 for CB3 correspond to stretching vibrations of the carbonyl double bond (CdO) and CdO chelate stretching of the carboxylic group, respectively.

After the metal ions are biosorbed onto CB, CB2, and CB3, the carbonyl double bond stretching band exhibits a clear shift to a lower frequency at 1604 and 1649 cm-1, while the CdO chelate stretching band increases to 1635 cm-1 corresponding to the complexation of the metal to CdO bond.69 The infrared frequencies at 2358, 2359, 2364, and 2362 cm-1 for CB1, CB2, CB3, and RB, respectively, were assigned to the P-H group.70 The involvement of the P-H group in the binding of metal ions is not clear during the shift in the absorbency ranging from -3 to +3 cm-1 compared to metalloaded biosorbents. The shift of the absorbance peak of -C-O stretching of alcoholic groups at 1032 and 1031 cm-1 for CB3 and RB, respectively, after metal biosorption provided the evidence that alcoholic groups would be one of the biosorption sites for

Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 971 Table 5. FT-IR Spectral Characteristics of Various Forms of C. indica before and after Biosorption sorption bands (cm-1) biosorbent

before biosorption

after biosorption

difference

CB1

3397 2358 1729 1112

3441 2361 1604 1027

-44 -3 +125 +85

N-H stretching of amide group P-H group CdO stretching C-O stretching of ether groups

CB2

3397 2359 1729

3448 2362 1649

-51 -3 +80

N-H stretching of amide group P-H group CdO stretching

CB3

3429 2929 2364 1620 1438 1032

3362 2923 2361 1635 1420 1058

+67 +6 +3 -15 +18 -26

secondary amide group O-H stretching of carboxylic group P-H group CdO chelate stretching of carboxylic groups asymmetric and symmetric stretching of -NdN- group -C-O stretching of alcoholic groups

RB

3428 2362 1460 1031

3442 2360 1457 1027

-14 +2 +3 +4

secondary amide group P-H group asymmetric and symmetric stretching of -NdN- group -C-O stretching of alcoholic groups

removing these metal ions. Similarly, the shift of bands at 1438 and 1460 cm-1 for CB3 and RB, respectively, represent asymmetric and symmetric stretching of the -NdN- group, after biosorption indicated involvement of the azo or diamide group. The absorption peaks at 1112 cm-1 for CB1 and CB2 were due to the -C-O stretching of ether groups, while the -C-O stretching of alcoholic groups was assigned at 1032 and 1031 cm-1 for CB3 and RB, respectively. Although other absorption peaks were observed, it was difficult to interpret all. FT-IR spectra indicate that the secondary amine group, CdO stretching, carboxyl groups, C-O stretching of ether groups, and the -C-C- group especially played a major role and both ion exchange and complexation occurred in metal biosorption. Samples of biosorbents before and after metal sorption were observed using the SEM/EDX technique with the aim to identify the surface microstructures and determine the chemical composition. The SEM images of the biosorbents in Figure 9a-d show less pore development occurring in the biosorbents. They also display a rough structure on the surface with moderate surface area. The SEM images of copper- and nickel-sorbed biosorbents are depicted in Figure 9e-h. The sorption of metals on the biosorbents leads to distinct changes in the structure of the biomass morphology. The amorphous and granular surfaces of biomass are found to be much more compact and denser due to accumulation of metal ions. As shown in Table 6, the surface compositional measurement (atomic %) of all the biosorbents by EDX is inconsistent. For pristine biosorbents, the average atomic ratio of C/O equals 0.876; however, this ratio decreases to 0.705 after metal binding, implying that the matrix of biosorbents becomes harder after ion exchange. The oxygen-containing polar groups were unable to retreat from the surface to lower the surface energy during the drying process, since polysaccharide chains were flexible in the wet state. As illustrated in Table 6, the sodium atomic % on the C. indica surface decreases while metal atomic % increases, indicating metal uptake mechanisms of the ion exchange. However, the decrease in the sodium atomic % was higher than the increase in the copper atomic % (Table 6). This inconsistent observation is due to the limitation of EDX since it can only determine the elemental compositions on the surfaces.71 3.9. Desorption. After sorption of the metals on the biomass, the sorbents were regenerated using hydrochloric acid (0.2 M). After 1 h of treatment, the extent of desorption for all the

assignment

biosorbents ranged from 96.5 to 97.5% for copper and 95.5 to 96.9% for nickel. The desorption process was rapid, with equilibrium achieved within 90-120 min for both metals. During desorption, the hydrogen ions in the solution compete (or exchange) with the metal ions on the sorption sites. The regenerated biomass was treated with NaOH solution before being reused in subsequent cycles. Parts a and b of Figure 10 show the sorption capacity of the biomasses for copper and nickel in five successive cycles, respectively. In the first sorption cycle, the sorption capacities ranged from 63.04 to 65.85 mg/g (0.99 to 1.03 mmol/g) and 49.36 to 53.15 mg/g (0.84 to 0.90 mmol/g) for copper and nickel, respectively, but decreased to from 62.52 to 65.33 mg/g (0.98 to 1.02 mmol/g) and 48.84 to 52.64 mg/g (0.83 to 0.89 mmol/g) in the second cycle, which may be due to incomplete regeneration or the loss of the broken biomass during regeneration or the interactions between the complexing agent and the functional groups or active sites of the biomass. It is expected that these sites would be blocked in an irreversible way by metal already biosorbed in the previous cycle.72 However, the sorption capacity remained relatively constant in subsequent cycles; the sorption capacities attained were in the ranges 61.75-64.56 mg/g (0.97-1.01 mmol/g) and 48.07-51.87 mg/g (0.82-0.88 mmol/g) for copper and nickel in the fifth cycle, indicating that the metal-sorbed biomass may be regenerated completely using hydrochloric acid solution. Evidently, the biomass could be used repeatedly for metal ion sorption from wastewaters. 4. Conclusions Biosorption performances of the various forms of pretreated brown seaweed, Cystoseira indica, are studied for the removal of Cu(II) and Ni(II) from industrial wastewater. The kinetic experiments show that biosorption on all sorbents is rapid and maximum sorption capacities are achieved in 30-75 min. The removal of metals increases with an increasing pH, and an optimum pH of about 6.0 was observed and the optimum solid to liquid ratio is 1.0 g/L. The chemical modification of C. indica biomass, especially CB2 and CB3, did not show significant improvement in the sorption capacity compared to raw biomass for the studied metals. The biosorption data fit the Langmuir isotherm, and the process obeyed pseudo-second-order kinetics. The order of maximum Cu(II) and Ni(II) uptakes for various biomasses was CB1 > RB > CB2 > CB3. An intraparticle

972 Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009

Figure 9. SEM micrographs of pristine and metal-loaded biosorbents: (a) CB1, (b) CB2, (c) CB3, (d) RB, (e) MCB1, (f) MCB2, (g) MCB3, and (h) MRB. Table 6. Composition (atomic % in Average ( Standard Deviation) Obtained by the EDX Microanalysis of the Biosorbents sorbent

O

C

N

Na

Cu

Ni

pristine biosorbents metal-loaded biosorbents

45.37 ( 6.44 49.52 ( 6.59

38.22 ( 9.03 33.64 ( 8.42

11.41 ( 2.71 11.90 ( 1.68

4.98 ( 1.11 2.43 ( 1.61

1.45 ( 0.63

1.03 ( 0.53

diffusion based Weber-Morris model was applied to evaluate the rate-limiting steps of the biosorption processes. The results

suggested that the film diffusion controlled the overall biosorption process. External mass transfer coefficients obtained by both

Ind. Eng. Chem. Res., Vol. 48, No. 2, 2009 973

Figure 10. (a) Sorption capacity of various forms of C. indica for copper after regeneration. (b) Sorption capacity of various forms of C. indica for nickel after regeneration.

the Mathews and Weber model and the Frusawa and Smith model were consistent. FT-IR analysis revealed that the sorption mechanisms were complex, and the amine, carboxyl, and hydroxyl groups were also involved in the sorption apart from the -C-C group. The SEM images showed less pore development occurring in the pristine biosorbents and the presence of divalent metals affected their surface morphology. The metalsorbed biosorbent may be regenerated completely using HCl solution, and the uptake capacity was relatively constant beyond the third cycle. The study revealed that C. indica has much potential as a biosorbent for the removal of metals from wastewaters. Acknowledgment S.B. and B.J. thank Dr. P. K. Ghosh, Director, Central Salt and Marine Chemicals Research Institute (CSMCRI), and Dr. (Mrs.) K. H. Mody, Group Leader of Marine Environment, CSMCRI, for their constant encouragement and support throughout the work. Supporting Information Available: Description of various kinetic and equilibrium models used in the present study. This material is available free of charge via the Internet at http:// pubs.acs.org. Nomenclature AHJ ) Harkins-Jura model constant aS ) Sips model constant

B ) constant in Dubinin-Radushkevich sorption model, mol2/kJ2 Bb ) constant in eq 10 AHJ ) Harkins-Jura model constant Ce ) equilibrium concentration of sorbate in solution, mg/L Dp ) pore diffusion coefficient, cm2/s Df ) film diffusion coefficient, cm2/s e ) Polanyi potential, kJ/mol E ) mean free energy, kJ/mol f ) Frumkin model constant F ) fractional attainment of equilibrium at time t h ) initial biosorption rate in pseudo-second-order model, mg/g/ min k ) fractional power model constant kp ) intraparticle diffusion rate constant, mg/g/min0.5 k1 ) Lagergren’s biosorption isotherm rate constant, 1/min k2 ) pseudo-second-order biosorption rate constant, g/mg/min KF ) Freundlich isotherm constant, L/g KL ) Langmuir isotherm equilibrium binding constant, L/mg KS ) Sips isotherm constant, L/g k ) fractional power kinetic constant, mg/g k1 ) pseudo-first-order model constant, 1/min k2 ) pseudo-second-order model constant, g/mg/min m ) number of experimental data points n ) exponent in Freundlich isotherm p ) number of parameters in the sorption isotherm qe ) amount of sorbate sorbed at equilibrium, mg/g qi ) observed sorption capacity of batch experiment i qm ) maximum sorption capacity, mg/g qt ) amount of sorbate sorbed at time t, mg/g Qi ) estimated sorption capacity of batch experiment i R ) universal gas constant, 8.314 J/mol/K R2 ) regression coefficient RL ) Langmuir separation factor Rp ) radius of the biosorbent rads(i) ) rate of adsorption, mg/g/min S ) outer surface of biosorbent per unit volume of solution, 1/cm SE ) standard error SSE ) sum-of-squares error SR50 ) instantaneous rate at 50% of biosorption SR90 ) instantaneous rate at 90% of biosorption t ) biosorption time, min t1/2 ) half-life period, min V ) fractional power model constant, 1/min V ) volume of metal solution, L W ) mass of sorbent, g ∆G° ) Gibbs free energy change, kJ/mol RE ) initial biosorption rate in Elovich model, mg/g/min βE ) desorption constant in Elovich model, g/mg γ ) Sips model exponent βI ) mass transfer coefficient, cm/min ε ) film thickness, cm

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ReceiVed for reView July 13, 2008 ReVised manuscript receiVed September 9, 2008 Accepted October 27, 2008 IE801071W