Removal of nickel(II) from aqueous solution using Citrus Limettioides peel and seed carbon

Ecotoxicology and Environmental Safety 117 (2015) 115–123

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Removal of nickel(II) from aqueous solution using Citrus Limettioides peel and seed carbon R. Sudha, K. Srinivasan n, P. Premkumar Department of Chemistry, Gnanamani College of Technology, Namakkal 637018, Tamil Nadu, India

art ic l e i nf o

a b s t r a c t

Article history: Received 26 November 2014 Received in revised form 19 March 2015 Accepted 23 March 2015

The agricultural wastes like Citrus Limettioides peel and seed to be suitable precursor for the preparation of carbon [Citrus Limettioides peel carbon (CLPC) and seed carbon (CLSC)] has been explored in the present work, utilizing sulfuric acid as the activating agent. Adsorption studies were performed by varying contact time, solution pH, adsorbent dose and temperature. The equilibrium time for Ni(II) ions was determined as 4 h and optimal pH was 4–7. Surface morphology and functionality of the CLPC and CLSC were characterized by SEM, EDX and FT-IR. The experimental data were analysed using the Freundlich, Langmuir, Temkin, Redlich–Peterson, Sips and Dubinin–Radushkevich adsorption isotherm equations using nonlinear regression analysis. Equilibrium data were found to fit well in the Langmuir isotherm, which confirmed the monolayer coverage of Ni(II) ions. The Langmuir monolayer adsorption capacity of CLPC and CLSC was found to be 38.46 and 35.54 mg/g. The thermodynamic parameters indicated that the adsorption process was spontaneous and exothermic in nature. The kinetic data followed pseudo-second order model with film diffusion process. The adsorbents were tested with Ni(II) plating wastewater in connection with the reuse and selectivity of the adsorbents. & 2015 Elsevier Inc. All rights reserved.

Keywords: Adsorption Citrus limettioides Nickel Isotherms Kinetics

1. Introduction Heavy metals are one of the most widespread origins of pollution both in water and soil, and increasing levels of heavy metals in the environment are causing public concern. The heavy metals, such as lead, copper, cadmium, zinc and nickel are among the most common pollutants found in industrial effluents. The removal of these heavy metals from aqueous environment has received considerable attention in recent years due to their toxicity and carcinogenicity which may cause damage to various systems of the human body. Nickel is one of the most common toxic pollutant, and its acute poisoning causes headache, dizziness, nausea, vomiting, chest pain and tightness, dry cough, skin dermatitis, rapid respiration, cyanosis and extreme weakness (Nuhoglu and Malkoc, 2009; Arain et al., 2014; Kazi et al., 2013; Baig et al., 2012). The major sources of nickel contamination to water comes from industrial process such as electroplating, battery and accumulator manufacturing, stainless steel, ceramic, mining and metallurgy, porcelain enameling and forging (Asberry et al., 2014; Reddy et al., 2011). The US Environmental Protection Agency (EPA) and Bureau of Indian Standards (BIS) require nickel not to exceed 0.015 mg/L in drinking n

Corresponding author. E-mail address: [email protected] (K. Srinivasan).

http://dx.doi.org/10.1016/j.ecoenv.2015.03.025 0147-6513/& 2015 Elsevier Inc. All rights reserved.

water (Hannachi et al., 2010; Murugesan et al., 2014).Various technologies such as chemical precipitation, ion-exchange, chemical coagulation, adsorption, extraction, and membrane separation have been recently developed for heavy metals removal from aqueous solution (Lin et al., 2000). Among these technologies, adsorption process offers optimum removal of heavy metals from aqueous solution in terms of initial cost, simple design, and easy operation. Although a variety of materials can be employed in adsorption process, activated carbon is among the most widely used adsorbent (S. Shrestha et al., 2013b; Reddy and Lee, 2013). Activated carbon derived from various agricultural waste products, such as almond husks (Hasar, 2003), peanut shells (Wilson et al., 2006), palm shell (Onundi et al., 2010), guava seeds (Zewail and El-Garf, 2010), tamarind nuts (Suganthi and Srinivasan, 2011), apricot stones (Kobya et al., 2005), olive stones (Ugurlu et al., 2009; Alslaibi et al., 2014), tobacco stem (Narasimha Rao et al., 2014), pine park (Reddy and Lee, 2014), cottonseed cakes (Ozbay, 2009), and coconut oil cakes (Hema and Srinivasan, 2010) have been successfully applied toward Ni(II) removal. Citrus Limettioides is one of the low cost nutritious fruit variety consumed in rural areas of India and belongs to Rutaceae family. Extracted acid from these fruits are used as flavoring and preservative in food and beverages, especially in soft drinks and the peel and seeds are disposed off as waste materials. The citrus limettioides fruit is mainly composed of D-limonene, myrcene, citronellal and β-citronellol (Jayaprakash et al., 2013). The present

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study aims to investigate the adsorption of Ni(II) ions from aqueous solutions onto activated carbon prepared from waste material such as Citrus Limettioides peel and seed. The adsorption capacity of adsorbents was investigated using batch experiments. The influences of contact time, pH, adsorbent dosage, temperature were investigated and the experimental data obtained were evaluated and fitting using adsorbent equilibrium isotherms, and kinetic models. Various thermodynamic parameters, such as ΔG0, ΔH0, and ΔS0, have also been evaluated.

was varied from 0.5 to 7 h by adding 0.1 g of adsorbent, for various Ni(II) concentrations over the range 5–10 mg/L at an optimum pH. The quantity of Ni(II) ions adsorbed at time t, qt (mg/g), was calculated by:

qt =

(C0 − Ct ) V m

(2)

where Ct is the concentration of Ni(II) ion at any time t (mg/L).

2.4. Adsorption isotherms 2. Materials and methods 2.1. Preparation of carbon adsorbent The Citrus limettioides peel and seed, was collected from a local juice manufacturing unit in Rasipuram (Tk), India and subsequently, the material was washed with boiling, deionized water five to six times for removing water soluble, extractable organics and acids. The washed material was dried for 2 days and cut into small pieces using a cutter machine. The dried raw material was subsequently digested with sufficient quantities of perchloric acid to break down the fibers and then subsequently treated with concentrated sulfuric acid in a 1:2 ratio by weight and kept at 16075 °C in an air-oven for 24 h. The carbonized material was washed with distilled water and soaked in 1% sodium bicarbonate for 24 h to remove any free acid. The carbon material was washed, dried and sieved to 20-50 ASTM mesh for use in the experiments. Here after in the present research paper the citrus limettioides peel carbon and seed carbon will be designated as CLPC and CLSC respectively. A Schematic diagram for preparation of activated carbon and photographic images of Citrus Limettioides, CLPC and CLSC are shown in Fig. S1a–d. 2.2. Preparation of the NI(II) solutions A stock solution of Ni(II) (100 mg/L) was prepared by dissolving 0.4479 g of AR NiSO4
6H2O in 1000 mL of deionized water. Nickel (II) solutions with the desired concentrations were prepared by diluting the stock solution. The pH of the solution was adjusted using 0.1 N HCl or 0.1 N NaOH solutions. The nickel-plating industry wastewater was collected from M/S Metal platers in Chennai, India. Because the wastewater has a very high concentration of nickel (2200 mg/L), it was diluted to 10 times for the studies with CLPC and CLSC. 2.3. Batch adsorption experiments Batch adsorption experiments were carried out by varying contact time (0.5–7 h), solution pH (2–12), adsorbent dose (0.05– 3.5 g) and temperature (27–47 °C). In each experimental study accurately weighed quantity of adsorbent dose was added to 100 mL of 10 mg/L of Ni(II) solution taken in a 300 mL polythene bottle and the reaction mixture was agitated at 120 rpm in a temperature-controlled shaker. At the end of agitation, the solutions were centrifuged and the concentrations of Ni(II) ions were determined by an atomic absorption spectrophotometer (Elico Model-SL 163). Each determination was repeated for three times and the average results are presented in this work. The data obtained in this study were used to calculate the removal of Ni(II) ions by using the following mass balance relationship:

C0 − Ce %Nickel(II) Removal = ×100 C0

(1)

where C0 and Ce are the initial and equilibrium concentrations of Ni(II) solution (mg/L) respectively. In kinetic studies, contact time

Adsorption isotherms were conducted with 10–60 mg/L of Ni (II) solutions by adding 0.1 g of adsorbent and equilibrated for 24 h at room temperature. The residual concentration of Ni(II) ions in the solution was measured by AAS. The amount of Ni(II) ions adsorbed at equilibrium, qe (mg/g), was calculated by the following relationship:

qe =

(C0 − Ce ) V m

(3)

where, V is the volume of the Ni(II) solution (L) and m is the mass (g) of the adsorbent. The adsorption isotherm indicates how the adsorbate molecules distribute between the liquid phase and the solid phase at equilibrium. The analysis of the isotherm data by fitting them into different isotherm models is an important step to find the suitable model that can be used for design process. The experimental data were applied to the two and three parameter non-linear isotherm models: namely Freundlich, Langmuir, Temkin, Redlich–Peterson, Sips, and Dubinin–Radushkevich. 2.4.1. Freundlich isotherm The Freundlich isotherm is suitable for a highly heterogeneous surface and expressed by the following (Freundlich, 1906):

qe = KF Ce1/ n

(4) (1/n)

where KF is the Freundlich constant ((mg/g)(L/mg) ) related to the bonding energy and n (g/L) is a measure of the deviation from linearity of adsorption. This value indicates the degree of nonlinearity between solution concentration and adsorption as follows: if n ¼1, adsorption is linear; if n o1, adsorption is a chemical process; if n4 1, adsorption is a physical process. 2.4.2. Langmuir isotherm The Langmuir model is obtained under the ideal assumption of totally homogenous adsorption surface and represented as follows (Langmuir, 1918):

qe =

qm KL Ce 1 + KL Ce

(5)

where qm (mg/g) is the maximum monolayer adsorption capacity, and KL (L/mg) Langmuir constant relating to adsorption energy. The essential characteristics of the Langmuir isotherm parameters can be used to predict the affinity between the sorbate and sorbent using separation factor or dimensionless equilibrium parameter, “RL”, expressed as in the following equation (Weber and Chakraborty, 1974):

RL =

1 1 + KL C0

(6)

where KL is the Langmuir constant and C0 is the initial concentration of Ni(II) ions. The value of RL indicated the type of Langmuir isotherm to be irreversible (RL ¼0), favorable (0 oRL o1), linear (RL ¼1), or unfavorable ((RL 41).

R. Sudha et al. / Ecotoxicology and Environmental Safety 117 (2015) 115–123

2.4.3. Temkin isotherm The Temkin isotherm model (Temkin and Pyzhev, 1940) contains a factor that explicitly takes into account adsorbing species– adsorbate interactions. This model assumes that the heat of adsorption of all the molecules in the layer decreases linearly with coverage due to adsorbent–adsorbate interactions, and the adsorption is characterized by a uniform distribution of binding energies, up to a maximum binding energy. The Temkin isotherm has been applied in the following form:

qe = B ln(ACe )

(12)

The magnitude of E is used to determine the type of adsorption mechanism, When one mole of ions is transferred to the adsorbent surface, its value is less than 8 kJ/mol which indicates physical adsorption (Kundu and Gupta, 2006), the value of E is between 8 and 16 kJ/mol, indicates the adsorption process follows ion-exchange (Helfferich, 1962) while its value in the range of 20–40 kJ/ mol indicates chemisorptions (Chen et al., 2010).

(7)

where A (L/mg) is the equilibrium binding constant that corresponds to the maximum binding energy, and B is a Temkin constant related to the heat of adsorption (kJ/mol). 2.4.4. Redlich–Peterson isotherm The Redlich–Peterson (Redlich and Peterson, 1959) isotherm is an empirical isotherm incorporating three parameters. It combines both Langmuir and Freundlich equations and the mechanism of adsorption is a hybrid and does not follow ideal monolayer adsorption. The equation is given as:

qe =

⎡ 1 ⎤ ⎥ E=⎢ ⎢⎣ 2β ⎥⎦

117

KR Ce 1 + aR Ceg

(8) g

g

where KR (L/g) and aR (L /mg ) are Redlich–Peterson isotherm constants and g is an exponent that lies between 0 and 1. For g ¼1, the equation converts to the Langmuir isotherm; for g ¼0, it simplifies to Henry’s law equation; and for 1 5 aR Ceg , it is identical with the Freundlich isotherm.

3. Results and discussion 3.1. FT-IR analysis The FT-IR spectral data for CLPC and CLSC before and after Ni(II) adsorption are shown in Fig.1(a-d). The spectra for CLPC and CLSC contained broad, intense peaks at 3444 and 3433 cm  1, respectively that correspond to OH stretching. The peaks at 1706 and 1710 cm  1 are attributed to the C¼ O stretching vibration of the carboxylic acid group. The peak at 1377 and 1359 cm  1 are assigned to the S¼O asymmetric stretching of the sulfonic acid group. The presence of the hydroxyl, carboxylic and sulfonic acid groups are confirmed in the FT-IR spectra. After Ni(II) adsorption, some of the peaks, such as the –OH, –C¼ O from carboxyl groups, – S¼O in sulfonic acid groups, and –C ¼C–, are shifted, implicating the participation of these functional groups in the metal binding process. 3.2. SEM-EDX ANAlysis

2.4.5. Sips isotherm Sips isotherm (Sips, 1948) is a combined form of Langmuir and Freundlich expressions used for predicting the heterogeneous adsorption systems and circumventing the limitation of the rising adsorbate concentration associated with Freundlich isotherm model. It can be written in the following form:

qe = qmax

Ks Ceγ 1 + Ks Ceγ

(9)

where qmax (mg/g) is the Sips maximum adsorption capacity, Ks (L/ mg) the Sips equilibrium constant, and γ is the Sips model exponent. 2.4.6. Dubinin–Radushkevich isotherm The Dubinin–Radushkevich isotherm is applied to find out the adsorption mechanism based on the potential theory assuming a heterogeneous surface. Dubinin–Radushkevich isotherm is expressed as follows (Dubinin and Radushkevich, 1947):

qe = qmD e−βε ²

(10)

where qmD (mg/g) is the Dubinin–Radushkevich monolayer capacity, β is a constant related to sorption energy, and ε is the Polanyi potential which is related to the equilibrium concentration as follows

⎡ 1⎤ ε = RT ln ⎢1 + ⎥ Ce ⎦ ⎣

(11)

where R is the gas constant (8.314 J/mol K) and T is the absolute temperature. The constant β gives the mean free energy, E, of sorption per molecule of the sorbate when it is transferred to the surface of the solid from infinity in the solution and can be computed using the relationship:

The SEM image of Fig. 1e and f reveals the porous structure of the CLPC and CLSC surface. Comparing the SEM images of the CLPC and CLSC before and after adsorption demonstrates that the metal ions are adsorbed, as confirmed with an EDX analysis. After adsorbing the metal ions, the pores on CLPC and CLSC are covered. The EDX spectra of the Ni(II) ions adsorbed on CLPC and CLSC shows that the peaks for the metal ions in addition to the other cations, confirming the adsorption of Ni(II) ions on the surface of the adsorbent (Fig. 1g and h). 3.3. Effects of the contact time The effect of contact time on the removal of Ni(II) ions from aqueous solutions in the concentration of 10 mg/L at pH 5.0 and 27 °C is shown in Fig. S2a. The results obtained from the adsorption of Ni(II) ions onto the CLPC and CLSC showed that the adsorption increases with increase in contact time. The rate of removal is higher in the beginning due to the large number of available adsorption sites on the adsorbent for the removal of Ni (II) ions. From Fig. S2a it was observed that the time necessary to reach the equilibrium with 4 h. Hence the optimum equilibrium was taken as 4 h for subsequent experiments. 3.4. Effect of solution pH The solution pH is an important controlling parameter in the adsorption process. The pH value affects the surface charge of the adsorbent, the degree of ionization and speciation of adsorbate during the adsorption process. Fig. S2b shows that the adsorption increases when the pH is increased, attaining the maximum removal of 92% and 90% over the pH range at 4.0–7.0 for CLPC and CLSC, respectively. The pH dependency of adsorption efficiency could be explained by the functional groups involved in metal

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Fig. 1. ((a), (b), (c) and (d)) FT-IR spectrum of CLPC and CLSC before and after Ni(II) adsorption. Fig. 1 (e), (f) and (g), (h) SEM image of CLPC and CLSC and EDX patterns onto CLPC, CLSC for after Ni(II) adsorption.

uptake and metal chemistry. The FT-IR spectroscopic analysis shows that the CLPC and CLSC has a variety of functional groups such as hydroxyl, carboxylic and sulfonic acid groups which are involved in almost all the potential binding mechanisms. Moreover, depending on the solution pH the functional groups

participate in metal ion bindings. At low pH values, H þ ions occupy most of the adsorption sites on the adsorbent surface and less nickel could be sorbed because of electric repulsion with H þ ions on adsorbent surface. When the pH value increases, adsorbent surface is more negatively charged and the adsorption of

R. Sudha et al. / Ecotoxicology and Environmental Safety 117 (2015) 115–123

119

Fig. 2. (a) and (b) Nonlinear adsorption isotherms for Ni(II) with CLPC and CLSC.

Table 1 Nonlinear fitting isotherm parameters for the adsorption of Ni(II) onto CLPC and CLSC Isotherm model

Parameter

CLPC

CLSC

Freundlich

KF((mg/g) n R2 SSE RMSE

9.633 2.631 0.943 24.11 2.455

9.463 2.748 0.922 28.78 2.682

Langmuir

Temkin

Redlich-Peterson

Sips

Dubinin–Radushkevich

qm (mg/g) KL (L/mg) R2 SSE RMSE RL

38.46 0.188 0.970 13.08 1.857 0.347–0.081

35.54 0.184 0.965 13.13 1.812 0.352–0.083

A B R2 SSE RMSE

2.116 3.482 0.965 14.57 1.909

2.091 3.299 0.956 16.38 2.017

KR (L/g) aR (L/mg) g R2 SSE RMSE

8.793 0.319 0.907 0.969 13.79 2.088

6.398 0.156 0.947 0.964 13.07 2.087

qmax (mg/g) Ks (L/mg) γ R2 SSE RMSE

42.52 0.146 0.849 0.968 13.97 2.098

37.15 0.178 0.925 0.964 13.06 2.086

qmD (mg/g) β (mg2/ J) E (kJ/ mol) R2 SSE RMSE

28.32 1.854x10-7 1.642 0.773 95.52 4.887

26.95 1.936x10-7 1.607 0.759 89.28 5.237

Ni(II) ions increased and reached equilibrium at 4.0–7.0. The decrease in adsorption efficiency at higher pH (4 7.0) was due to the formation of soluble hydroxylated complexes of the nickel ions and their competition with the active sites as a result, the

Table 2 Monolayer adsorption capacities in the literature for Ni(II) adsorption. Adsorbent

qm (mg g  1) References

Palm shell Orange peel Garlic peel Ceiba pentandra hulls Almond husk activated with H2SO4 Walnut shell waste Cajanus cajan L millsp seed shell activated carbon Watermelon rind

0.13 49.14 32.00 34.34 37.18

Onundi et al. (2010) Guo et al. (2011) Liang et al. (2013) Ramana et al. (2012) Hasar (2003)

15.34 25.75

Wang et al. (2010) Thamilarasu et al. (2011)

35.30

Cottonseed cake Ricinus communis pericarp

25.00 31.15

Parthenium hysterophorus L Carica papaya seed Lapsi (Choerospondias axillaris) seed stone Coconut dregs residue CLPC CLSC

17.24 5.58 28.25

Lakshmipathy and Sarada (2013) Ozbay (2009) Madhavakrishnan et al. (2008) Lata et al. (2008) Chithra et al. (2014) R.M. Shrestha et al. (2013a)

5.86 38.46 35.54

Kamari et al. (2014) Present study Present study

retention would decrease again. The influence of solution pH on Ni (II) removal can be explained in terms of zero point charge of the adsorbent. The point of zero charge (pHpzc) was determined by the solid addition method (Rao and Ikram, 2011). The pHpzc of CLPC and CLSC in distilled water is found to be 6 (Figure not given) showing that surface is positively charged below pH 6. Therefore, at high pH value (above 6) Ni(II) species mainly present as Ni (OH) þ and Ni(OH)2 were sorbed (due to microprecipitation). 3.5. Effect of adsorbent dose The effect of adsorbent dose on the percentage removal of Ni(II) has been shown in Fig. S2c. It can be seen from the figure that initially the percentage removal increases very sharply with the increase in adsorbent dose but beyond 1.5 g/L, the percentage removal reaches almost a constant value and this may be due to reduction in concentration gradient. The maximum removal efficiency of Ni(II) ions onto CLPC and CLSC was found to be 99% at an adsorbent dose of 1.5 g/L. The increase in removal efficiency of Ni (II) ions can be attributed to the increase in surface area resulting from the increase in adsorbent mass or greater availability of the exchangeable sites for adsorption.

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3.6. Adsorption isotherms The isotherm constants, correlation coefficients (R2), sum of squares error (SSE) and root mean squared error (RMSE) values were estimated from the plot of qe versus Ce (Fig. 2a and b) and are listed in Table 1. The R2 values closer to 1 and small SSE, RMSE values indicate better curve fitting. Based on the R2, SSE and RMSE values from Table 1, the Langmuir, Redlich–Peterson and Sips isotherm model exhibited a better fit for CLPC and CLSC to the adsorption Ni(II) ions respectively. Note that the Redlich–Peterson and Sips model fit was superimposed on the Langmuir fit (Fig. 2a and b). The Redlich–Peterson and Sips exponent g and γ values in Table 1 are closer to 1 for CLPC and CLSC, which means that the Langmuir isotherm is preferably. Hence, the good fit of equilibrium data in Langmuir isotherm expression for CLPC and CLSC confirms the monolayer adsorption of Ni(II) ions. Furthermore, the RL values for the Langmuir isotherm fall between 0 and 1 (Table 1), indicating a favorable adsorption of Ni(II) on CLPC and CLSC. The calculated E values of the present study is below 8 kJ/mol, which indicates that the adsorption of Ni(II) ions onto the CLPC and CLSC follows physical adsorption type. Therefore, the adsorption of Ni (II) ions onto CLPC and CLSC surface is a complex, involving more than one mechanism. The comparison of maximum monolayer adsorption capacity of Ni(II) ions onto various adsorbents is presented in Table 2. The value of Ni(II) ions sorption observed in the present study is in good agreement with values found by other researchers. Differences of metal uptake are due to the properties of each adsorbent such as structure, functional groups and surface area. Therefore, it could be concluded that the CLPC and CLSC has a promising adsorbent for the removal of Ni(II) from aqueous solutions.

ln Kc =

ΔS 0 ΔH 0 − R RT

(16)

where, Kc is the equilibrium constant (L/g), Ce is the equilibrium concentration (mg/L), Ca is the amount of Ni(II) adsorbed on the adsorbent per liter of solution at equilibrium (mg/L), R is the gas constant (8.314 kJ/mol K) and T is the absolute temperature (Kelvin). The values of enthalpy change (ΔH0) and the entropy change (ΔS0) were determined from the slope and the intercept from the plot of ln Kc versus 1/T (Fig. S3b) and are listed in Table S1. The negative value of ΔG0 implies that the adsorption of Ni(II) ions onto CLPC and CLSC was spontaneous and feasible. The ΔG0 value is more negative when decreasing the temperature, suggesting that lower temperatures favor the adsorption.The negative ΔH0 value indicates the exothermic nature of adsorption and the ΔS0 can be used to describe the randomness at the adsorbent–solution interface during the sorption.

3.8. Sorption kinetics In order to investigate the adsorption mechanism and rate controlling steps, the adsorption kinetic data were modeled using pseudo-first-order and pseudo-second-order kinetic equations. A pseudo-first order equation of Lagergren (Lagergren, 1898) is generally expressed as:

log(qe − qt ) = log qe −

k1 t 2.303

(17)

where qe (mg g  1) and qt (mg g  1) are the adsorption amount at equilibrium and at time t (min), respectively. k1 (min  1) is the rate constant of the pseudo-first order adsorption process. The constants were determined experimentally by plotting of log (qe  qt) versus t. Pseudo-second order model was also generally applied to fit the experimental data. The linear form of pseudo-second order model (Ho, 2006) can be expressed as:

3.7. Effect of temperature and thermodynamic parameters The adsorption of Ni(II) ions on CLPC and CLSC was investigated as a function of temperature and the maximum removal of Ni(II) ions was obtained at 27 °C. The batch adsorption studies were performed at different temperatures of 27, 37 and 47 °C for the initial Ni(II) ions concentration of 10 mg/L at constant adsorbent dose of 1 g/L and an optimum pH value of 5. The percentage removal of Ni(II) ions decreases with the increase in temperature (Fig. S3a). This is mainly due to the decrease in surface activity suggesting that the adsorption between Ni(II) and CLPC, CLSC is an exothermic process. Thermodynamic parameters such as free energy (ΔG0), enthalpy (ΔH0) and entropy (ΔS0) change of adsorption can be evaluated from the following equations

Kc =

(15)

ΔG 0 = ΔH 0 − T ΔS 0

t 1 t = + qt qe k2 qe2

(18) 1

1

where k2 (g mg min ) is the rate constant of adsorption. By plotting a curve of t/qt against t, qe and k2 can be evaluated. The initial adsorption rate, h0 (mg g  1 min  1) is defined as (Ho, 2003):

h0 = k2 qe2

Ca Ce

(13)

ΔG 0 = − RT ln Kc

(19)

In order to compare quantitatively the applicability of kinetic models in fitting to data, the percentage relative deviation (P %) was calculated by the following equation:

(14)

Table 3 Pseudo-first order and Pseudo-second order constants for Ni(II) adsorption onto CLPC and CLSC at different initial concentrations. Adsorbent

C0 (mg/L )

qe (exp) (mg/g)

Pseudo-first order

Pseudo-second order

k1 (min  1)

qe (cal) (mg/g)

R2

P (%)

k2 (g/ mg/ min)

qe (cal) (mg/g)

h0

R2

P (%)

CLPC

5 7 10

4.70 6.90 9.60

0.007 0.023 0.028

0.74 2.98 2.80

0.868 0.957 0.974

84.26 56.81 70.83

0.041 0.029 0.015

4.65 7.00 9.90

0.887 1.421 1.470

1.000 0.990 0.999

1.06 1.45 3.13

CLSC

5 7 10

4.80 6.70 9.90

0.028 0.014 0.023

3.60 1.45 2.07

0.975 0.779 0.844

25.00 78.36 79.09

0.018 0.015 0.012

5.65 6.94 10.20

0.575 0.722 1.248

0.993 0.998 0.999

1.77 3.58 3.03

R. Sudha et al. / Ecotoxicology and Environmental Safety 117 (2015) 115–123

10 mg/L 7 mg/L 5 mg/L CLPC

10

8 q t (m g/g)

q t (mg/g)

10 mg/L 7 mg/L 5 mg/L CLSC

10

8 6 4

6 4 2

2

0

0 0

3

6

9 t

12

15

0

18

3

6

9

12

15

150

200

18

(1/2)

(1/2)

t

10 mg/L 7 mg/L 5 mg/L CLPC

3.0

10 mg/L 7 mg/L 5 mg/L CLSC

3.5 3.0

2.5

-ln (1 -(q t /q e ))-0 .4 9 7 7

-ln (1 -(q t /q e ))-0 .4 9 7 7

121

2.0 1.5 1.0 0.5

2.5 2.0 1.5 1.0 0.5 0.0

0.0 0

50

100

150

200

250

0

50

100

250

Time (min)

Time (min)

Fig. 3. (a) and (b) Intraparticle diffusion model for adsorption of Ni(II) by CLPC and CLSC. (c) and (d) Boyd kinetic plot for adsorption of Ni(II) by CLPC and CLSC.

⎡ qe (exp) − qe (theo) P (%) = 100/N ∑ ⎢ ⎢⎣ qe (exp)

⎤ ⎥ ⎥⎦

3.9. Adsorption mechanism

(20)

where qe(exp) and qe(cal) are experimental and calculated value of Ni (II) adsorbed on the adsorbents, N is the number of measurements made. It is found that the lower value of percentage deviation (P%), better is the fit. It is generally accepted that when P% value is less than 5, the fit is considered to be excellent (Ayranci and Duman, 2005). All kinetic parameters, correlation coefficients, and P (%) are listed in Table 3. The correlation coefficient (R2) for the pseudosecond order model is much closer to unity. The calculated qe value is found to be much closer to the experimental qe value. Furthermore, the percent relative deviation (P%) is also found to be less than 5% in the case of pseudo-second order. These results confirm that the adsorption kinetics of Ni(II) ions onto the CLPC and CLSC is mainly governed by pseudo-second order equation and hence the rate-limiting step of Ni(II) ions onto CLPC and CLSC may be chemisorptions.

It is most important to predict the rate-limiting step in an adsorption process to understand the adsorption mechanism associated with the phenomena. For a solid–liquid sorption process, the solute transfer is usually characterized by either external diffusion (boundary layer diffusion) or intraparticle diffusion or both. The following three steps can describe the adsorption dynamics (Acharya et al., 2009). 1. The movement of adsorbate molecules from the bulk solution to the external surface of the adsorbent (film diffusion). 2. Adsorbate molecules move to the interior part of the adsorbent particles (particle diffusion). 3. Sorption of the solute on the interior of the pores and capillary spaces of adsorbent (sorption).

3.9.1. Weber and Morris intraparticle diffusion model Taking into account that the kinetic results were fitted very well to a chemisorptions model, the intraparticle diffusion model

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was plotted in order to verify the influence of mass transfer resistance on the binding of Ni(II) to the adsorbents. The kinetic results were analysed by the (Weber and Morris (1963) intraparticle diffusion model to elucidate the diffusion mechanism, the model is expressed as:

qt = kd t 1/2 + C

(21)

where C is the intercept and kd is the intraparticle diffusion rate constant (mg/g min1/2), which can be evaluated from the slope of the linear plot of qt versus t(1/2) as shown in Fig. 3a and b. The dual nature of the curve was obtained due to the varying extent of sorption in the initial and final stages of adsorption experiment. This can be attributed to the fact that in the initial stages the sorption was due to boundary layer diffusion effect whereas in the later stages (linear portion of the curve) it was due to the intraparticle diffusion effects. The intercept of the plot reflects the boundary layer effect. The larger is the intercept and greater will be the contribution of the surface sorption in the rate controlling step. If the regression in the plot of qt versus t(1/2) is linear and passes through the origin, then intraparticle diffusion is the sole rate-limiting step. However, the linear plots at each concentration did not pass through the origin. This deviation from the origin may perhaps be due to the difference in the rate of mass transfer in the initial and final stages of adsorption. This indicated that there is some degree of boundary layer control and this further showed that the intraparticle diffusion was not only the rate-limiting step, but also be the rate controlling of sorption or all may be operating simultaneously. 3.9.2. Boyd kinetic model The Boyd kinetic plot predicts the actual rate-determining step involved in the adsorption process. The Boyd kinetic (Boyd et al., 1947) equation is expressed as:

F=1−

6 exp (Bt ) π2

(22)

where F¼qe/qt, F represents the amount of Ni(II) adsorbed at any time t, and Bt is a mathematical function of F. Eq. (22) can be rearranged by taking the natural logarithm to obtain the equation:

Bt = − 0.4977 − ln (1 − F)

4. Conclusions The present study shows that the activated carbon prepared from Citrus Limettioides peel (CLPC) and seed (CLSC) has considerable potential for the removal of Ni(II) ions from aqueous solutions. The optimum contact time and pH was found to be 4 h and 4.0–7.0. The presence of hydroxyl, carboxylic and sulfonic acid groups are confirmed by FT-IR spectroscopy. Equilibrium data agreed well with Langmuir isotherm and the sorption process was spontaneous and exothermic in nature. The adsorption is followed by pseudo-second order kinetics, which indicates the chemisorptions with film diffusion process being essential rate controlling step. The adsorbents can be regenerated and reused upto five cycles. Finally, it could be concluded that the use of CLPC and CLSC may be an alternative adsorbent to more costly materials such as ion-exchange resins, carbon nanotubes, etc. for the treatment of wastewater containing toxic Ni(II) ions.

(23)

The plot of Bt versus t can be employed to test the linearity of the experimental values. If the plots are linear and pass through the origin, then the slowest step in the adsorption process is the internal diffusion. From Fig. 3c and d, it was observed that the plots are linear but does not pass through the origin suggesting that the adsorption process is controlled by film diffusion. The B values were used to calculate the effective diffusion coefficient, Di (cm2/s) using the following relationship:

π ² Di B= r²

concentration of nickel (2200 mg L  1), it was diluted to 10 times to conduct experiments with CLPC and CLSC. To get a quantitative removal of 1 L wastewater containing 220 mg/L of Ni(II) ions, a minimum adsorbent dose of 3 g/L is required for the maximum removal of 98 (70.5) %. Therefore, CLPC and CLSC is an effective adsorbent for the removal of Ni(II) from nickel-plating wastewater. In order to explore the practical efficiency of the adsorbent over repeated uses, 0.7 N HCl was used to regenerate the carbon over five cycles of operation. A slight increase in the sorption of Ni(II) could be observed after each and every cycle with CLPC and CLSC, improving the recovery of Ni(II) ions. This increase in the sorption (98.0–99.9%) may occur because additional surface active sites present on the sorbent surface open after repeated regeneration cycles. However, the recovery of Ni(II) is decreased from 96.20V to 80.70% for CLPC and 94.50–78.90% for CLSC during fifth cycle because the Ni(II) ions were strongly bound to the new opening sites. Therefore, CLPC and CLSC have a greater potential for repeated uses and the recovery of Ni(II) ions. The attrition losses were also calculated at the end of the fifth cycle. The CLPC showed 3.0% losses on average, while CLSC showed 5–6% losses at the end of the cycle during batch mode operations.

(24)

where Di is the effective diffusion coefficient of Ni(II) ions in the adsorbent surface and r is the radius of the adsorbent particle. The Di values were found to be 1.559  10  8, 1.503  10  8, 1.298  10  8 cm2/s for CLPC and 1.824  10  8, 1.571  10  8, 1.183  10  8 cm2/s for CLSC at an initial Ni(II) ions concentration of 5, 7 and 10 mg/L respectively. 3.10. NI(II) removal from electroplating wastewater and regeneration studies Batch experiments with nickel electroplating wastewater have been carried out to elucidate the applicability of both sorbents under batch mode operations. As the wastewater has a very high

Conflict of interest The authors have no conflict of interest to declare.

Acknowledgements Authors thank the Chairman, Department of Chemistry, Gnanamani College of Technology, Anna University (Tamil Nadu), India, for providing research facilities.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.ecoenv.2015.03. 025.

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