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Journal of Chemistry
Volume 2015, Article ID 495257, 9 pages
http://dx.doi.org/10.1155/2015/495257
Research Article

Calcium Pretreated Hevea brasiliensis Sawdust for Copper Removal: Batch and Column Study

1Department of Environmental Engineering, NIT Agartala, Tripura 799046, India
2Department of Civil Engineering NIT Agartala, Tripura 799046, India

Received 10 September 2015; Accepted 25 October 2015

Academic Editor: Wenshan Guo

Copyright © 2015 Swarup Biswas and Umesh Mishra. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Calcium pretreated Hevea brasiliensis sawdust has been used as an effective and efficient adsorbent for the removal of copper ion from the contaminated water. Batch experiment was conducted to check the effect of pH, initial concentration, contact time, and adsorbent dose. The results conclude that adsorption capacity of adsorbent was influenced by operating parameters. Maximum adsorption capacity found from the batch adsorption process was 37.74 mg/g at pH of 5.6. Various isotherm models like Langmuir, Freundlich, and Temkin were used to compare the theoretical and experimental data, whereas the pseudo-first-order, pseudo-second-order, and intraparticle diffusion models were applied to study the kinetics of the batch adsorption process. Dynamic studies were also conducted in packed-bed column using different bed depths and the maximum adsorption capacity of 34.29 was achieved. Characterizations of the adsorbent were done by Fourier transform infrared spectroscopy, scanning electron microscope, and energy dispersive X-ray spectroscopy.

1. Introduction

Pollution due to copper is a considerable environmental concern in the recent years. Though copper is essential for the body, excessive amount of copper in living beings may cause serious health problem [13]. Copper is widely used in various industrial processes like pesticides, electroplating, tannery, herbicides, and paper manufacturing contaminating both surface water and ground water [4]. According to Environmental Protection Agency (EPA) maximum level permitted for copper in discharge water is 1.0 mg/L [5]. Most common methods of copper ion removal from wastewaters are chemical precipitation [6], ion exchange [7], membrane processes [8], chemical oxidation/reduction [9], and adsorption [10] among which adsorption is the most favorable due to its economic viability, availability, profitability, easy operation, high efficiency, and environmental friendly behavior. In recent years, wheat shell [11], herbaceous peat [12], cork biomass [13], food waste [14], tea industry waste [15], peanut hulls [16], tobacco dust [17], modified rice husk [18], raw pomegranate peel [19], newspaper pulp [20], and jute [21] were used as a naturally available low-cost adsorbent for the removal of copper. However, many of these naturally available adsorbents have low copper adsorption capacity and slow process kinetics. Thus, there is a need to develop innovative low-cost adsorbents useful both for the industry and for the environment.

The objective of the study was to develop an efficient and economical adsorbent for the removal of copper ion from aqueous solution. Calcium pretreated Hevea brasiliensis sawdust (CaBHSD) was prepared by treating the Hevea brasiliensis with the calcium and it was utilized as an efficient adsorbent for the removal of copper ion. The influence of the operating parameter like pH, initial concentration, contact time, and adsorbent dose was examined. Isotherm models and kinetic models were utilized for better understanding of the adsorption process. Column study was also done to check the breakthrough behavior of the adsorption experiment.

2. Materials and Methods

2.1. Preparation of Ca Pretreated Biomass

Hevea brasiliensis sawdust collected from rubber wood processing industry, Nagechera, Tripura, India, was washed with distilled water. Sawdust was dried in forced air circulation oven at 60°C for one day. Dried sawdust was sieved to get the desire particle size ranging from 0.5 mm to 1 mm. For pretreatment of sawdust 5 g of sawdust was added in 500 mL of CaCl2 (0.2 M) solution. Sawdust slurry was maintained for 24 h and after the treatment the sawdust was washed thoroughly with the distilled water to remove the unbounded calcium. Then the sawdust was kept in force air circulation oven drier at 60°C for 24 hours [22] and stored in a plastic container.

2.2. Preparation of the Solution

All the chemicals used in the experiment were of analytical grade and purchased from Merck, India. A stock solution (1000 mg/L) of copper was prepared by adding appropriate amount of CuCl2·5H2O in 1 L of distilled water. For preparation of required concentration the stock solution was utilized. For pH adjustment 0.1 M NaOH and HCl were used in the experiment.

2.3. Characterization of the Adsorbent

Concentrations of the metal ion were determined by using atomic absorption spectrophotometer (PerkinElmer Model AAS 700). Functional groups of the adsorbent were determined by Fourier transform infrared spectroscopy (FTIR) (Bruker 3000 Hyperion, Germany). Scanning electron microscope (SEM) (JELO JSM7600F) was used to analyze the morphological structure of the adsorbent. Simultaneously EDS (energy dispersive X-ray spectroscopy) (Oxford AZtec energy system) was also utilized to observe the adsorption characteristics.

2.4. Batch Experiment

Batch adsorption was carried out using Pyrex glass flasks in magnetic stirrer at the speed of 120 rpm. Experiments for the determination of the equilibrium time were carried out at different concentration (5 mg/L to 30 mg/L), different pH (2.1 to 6.8), and different adsorbent dosage (0.25 g/L to 5 g/L). After copper adsorption experiment the mixture was filtered and the concentration of the residual copper ion was determined. The removal percentage of copper ion was calculated using the following equation:

The adsorption capacity was obtained by the following equation:where (mg/g) is adsorption capacity at equilibrium. Initial and equilibrium concentration are denoted as (mg/L) and (mg/L). (g) is the mass of adsorbent and (L) is the volume of solution.

2.5. Dynamic Adsorption

Batch adsorption study was conducted to check the efficiency of the adsorbent and the operating parameters before going for more costly experiment. Hence to check the applicability of the adsorbent for large scale application the column operation was also studied. Column study was conducted in a glass column having diameter of 2.54 cm and length of 10 cm. At the bottom of the column glass wool was used to prevent any loss of the adsorbent. Copper solution with the influent concentration of 20 mg/L was fed from the top of the column at the pH of 5.2 and flow rate of 15 mL/min. Different bed depths of 2 cm, 5 cm, and 7 cm were utilized to evaluate the breakthrough data. The effluent samples were collected from the bottom of the column at different time intervals.

3. Results and Discussion

3.1. Characterization of the Adsorbent

Results of the FTIR analysis were shown in Figures 1(a) and 1(b) where the functional groups were identified. Before adsorption of copper ion the peaks at 3428 cm−1 and 2923 cm−1 were due to O–H starch and C–H starch, whereas the peak at 1634 cm−1, 1741 cm−1, and 609 cm−1 reflected the presence of C=C, C=O, and C–H group. After adsorption of copper ion peaks were shifted. This may have happened because in adsorption process the calcium ions present in the raw CaHBSD were released into the solution and the vacant pores were occupied by the copper ion. Before and after adsorption the surface morphology of the adsorbent was analyzed by SEM (Figures 2 and 3). After adsorption process the presence of copper ion was observed in EDS shown in Figures 4 and 5 which also justified adsorption of copper ion by the CaHBSD.

Figure 1: FTIR spectra of (a) CaHBSD and (b) copper loaded CaHBSD.
Figure 2: SEM of CaHBSD before copper adsorption.
Figure 3: SEM of CaHBSD after copper adsorption.
Figure 4: EDS of CaHBSD before copper adsorption.
Figure 5: EDS of CaHBSD after copper adsorption.
3.2. Batch Result Analysis
3.2.1. Effect of pH

Effect of pH was observed in batch experiment and it was found that adsorption capacity became higher at the pH of 5.6 (Figure 6). The adsorption capacity was lower at higher and lower pH. As the binding sites of the adsorbent were occupied by the H+ ion the adsorption capacity became decreased at lower pH and at higher pH the precipitation of the copper ion was observed.

Figure 6: Effect of the pH on the adsorption of copper by CaHBSW.
3.2.2. Effect of Contact Time

Percentage removal and adsorption capacity by the CaHBSD with respect to the contact time were evaluated. Figure 7 showed that the greatest adsorption capacity took place within 30 min. As calcium ions were released in water the active site of the adsorbent was increased which leads to the higher adsorption capacity. After half an hour the surface sites of the CaHBSD were occupied by the copper ion and gradually the adsorption process became slower.

Figure 7: Effect of the contact time on the adsorption of copper by CaHBSW.
3.2.3. Effect of Initial Concentration

Effect of initial metal ion concentration was also evaluated where it was found that the adsorption capacity was increased with the increasing concentrations (Figure 8). As the concentrations were increased from 5 mg/L to 30 mg/L the adsorption capacities were also increased from 9.2 mg/g to 32.8 mg/g. At higher initial concentration maximum binding sites were occupied by the metal ion which gave the higher adsorption capacity.

Figure 8: Effect of the concentration on the adsorption of copper by CaHBSW.

3.2.4. Effect of Adsorbent Dosage

The adsorbent dose greatly influenced the adsorption process and it was found that as the adsorbent doses were increased from 0.25 g/L to 5 g/L the adsorption capacities were decreased from 3.88 mg/g to 31.51 mg/g. The binding sites were increased with the increasing adsorbent dose; the removal percentage was increased but the adsorption capacity was decreased (Figure 9).

Figure 9: Effect of the adsorbent dose on the adsorption of copper by CaHBSW.
3.2.5. Adsorption Isotherms

Different isotherm models such as Langmuir, Freundlich, and Temkin were applied to evaluate the best fitted model (Table 1).

Table 1: Quantitative description of the Langmuir, Freundlich, and Temkin models in adsorption of copper onto CaHBSW.
Figure 10: Langmuir isotherm plots for adsorption of copper ions onto CaHBSD.
Figure 11: Freundlich isotherm plots for adsorption of copper ions onto CaHBSW.
Figure 12: Temkin isotherm plots for adsorption of copper ions onto CaHBSW.

Langmuir adsorption isotherm was evaluated by [36]

As the values of (0.86–0.96) were greater than 0 and smaller than 1 the Langmuir isotherm model was favorable for the present copper adsorption process. The parameters of Freundlich isotherm are illustrated in Table 1. In case of Freundlich isotherm the value of is 2.09 () and as a result it can be said that Freundlich isotherm is also favorable for copper adsorption. Another important isotherm is Temkin isotherm which is also applied to the batch adsorption process and the values of its parameters are explained in Table 1. Three different isotherms (Langmuir, Freundlich, and Temkin models) were applied to check the experimental data. Best fitted model was selected on the basis of correlation coefficients (). As the correlation coefficients () of Langmuir model were higher than the other models it was considered as the best fitted model for the present adsorption system.

3.2.6. Adsorption Kinetics

Batch kinetic study was used to determine the rate of adsorption process. Different kinetic models such as pseudo-first-order, pseudo-second-order, and intraparticle diffusion models were used to explain the uptake of copper ion with time. The kinetic parameters of these three models were shown in Table 2.

Table 2: Kinetic characterization of the copper adsorption onto CaHBSW.
Figure 13: Pseudo-first-order plot for adsorption of copper ions onto CaHBSW.
Figure 14: Pseudo-second-order plot for adsorption of copper ions onto CaHBSW.
Figure 15: Intraparticle diffusion plot for adsorption of copper ions onto CaHBSW.
Figure 16: Breakthrough curves at different bed depths for adsorption of copper ions onto CaHBSW.

In case of pseudo-first-order model and pseudo-second-order model the calculated adsorption capacities were in good agreement with the experimental adsorption capacity. The values for the pseudo-first-order model and pseudo-second-order model were 0.975 and 0.995 which indicate that the adsorption process was more appropriately described by the pseudo-first-order and pseudo-second-order model compared to the intraparticle diffusion model as the value of was lower in case of intraparticle diffusion model.

3.3. Mechanism of Ion Exchange

Adsorption of copper ion by CaHBSD can be explained as ion exchange process. As proton has the good influence in solution chemistry the mechanism is involved with the copper ion and calcium ion. According to Crist et al. [37] two protons are adsorbed for each calcium and magnesium ion. In calcium pretreatment process the calcium ion binds to the active site of the Hevea brasiliensis sawdust by replacing the existing cations in the sawdust. When the calcium pretreated adsorbent is used for the copper adsorption the calcium is released into the aqueous solution and binding site is filled by the copper ion.

3.4. Dynamic Adsorption

Breakthrough capacity and the exhaustion capacity have been evaluated from the break through curve and the adsorption capacity at 10% breakthrough was measured by the breakthrough data [38]. It was observed that in column process the maximum adsorption capacity was found as 34.29 mg/g.

Column experiment was conducted in three different bed depths (2 cm, 5 cm, and 7 cm) and it was found that adsorption capacity of metal ion in fixed bed column was increased with the increasing bed depth. Breakthrough time decreased from 480 min to 90 min with decreasing the bed depth from 7 cm to 3 cm and a steeper breakthrough curves were observed with decrease in bed depth (Figure 16). At the low bed depth axial dispersion phenomenon effects in mass transfer reduce the adsorption capacity. As residence time of solution in the column was low in lower bed depth the copper ion did not get enough time to diffuse into the hole of the adsorbent.

3.5. Comparison with Other Adsorbents

Comparison of copper adsorption capacities in batch mode and in column mode is in Table 3. Furthermore direct comparison between the other adsorbent found in the literature was difficult because of different experimental conditions. However, the copper adsorption capacities of the CaHBSD in batch and column system were compared with the other low-cost adsorbents (Table 3). From the comparison the CaHBSD can be considered as a valuable and cost effective adsorbent for the treatment of copper contaminated wastewater.

Table 3: Comparison of adsorption capacities of CaHBSD with some low-cost adsorbents.

4. Conclusions

CaHBSD provided a low-cost and potential adsorbent for the removal of copper ion from aqueous solution. Maximum adsorption capacity of the adsorbent was found as 37.74mg/g in batch mode whereas it was 34.29mg/g in column process. In batch adsorption process all the models were well fitted model but Langmuir model was found as the most perfect model to describe the equilibrium process. Similarly in the kinetic study pseudo-first-order and pseudo-second-order model were able to explain the adsorption process properly. The main mechanism of this adsorption process was ion exchange process where calcium ions attached to Hevea brasiliensis sawdust were replaced by the copper ion. The investigations conclude that calcium pretreated Hevea brasiliensis sawdust may be an efficient adsorbent for the removal of copper ion.

Conflict of Interests

The authors hereby declare no conflict of interests.

Acknowledgment

The authors are thankful to the Director of National Institute of Technology Agartala for providing necessary research facilities.

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