INTRODUCTION:
Heavy metal releases to the environment have been increasing continuously as a result of industrial activities and technological developments, posing a significant threat to the environment and public health because of their toxicity, accumulation in the food chain and persistence in nature. Living organisms require varying amounts of heavy metals viz Iron, cobalt, copper, manganese, etc in small quantities. But excessive levels can be damaging to the organism and their accumulation over time in the bodies of animals can cause serious illness [1].
Zinc is a trace element that is essential for human health. It is important for the physiological functions of living tissue and regulates many biochemical processes. The proposed limit of Zinc in drinking water is 5 ppm as proposed by FDA. However, too much zinc can cause eminent health problems, such as stomach cramps, skin irritations, vomiting, nausea and anemia [2].
It is essential to remove Zn (II) from industrial wastewater before being discharged. For this reason, it is generally used the advanced treatment processes such as chemical reduction, ion exchange, reverse osmosis, electro dialysis and adsorption. Since the costs of these processes are rather expensive, the use of agricultural residues having biological activities has been received with considerable attention [4].
Adsorption is considered quite attractive in terms of its efficiency of removal from dilute solutions. Many adsorbents have been used for removal of heavy metals [3, 4]. These adsorbents were used in raw state [6, 7] or with modified surface [8-10]. Agricultural materials contain proteins, polysaccharides and lignin which are associated with functional groups responsible for metal ion adsorption [11]. The abundant natural occurrence and presence of large amount of surface functional groups make various agricultural wastes good alternatives to expensive synthetic adsorbents [12]. In recent years, agricultural by-products have been widely studied for metal removal from water. These include peat, wood, pine bark, banana pith, soybean and cottonseed hulls, peanut, shells, hazelnut shell, rice husk, sawdust, wool, orange peel, compost, leaves and almond husk [13]. Thus, there is a growing demand to find relatively efficient, low cost and easily available adsorbents for the adsorption of heavy metals, particularly if the adsorbents are the wastes [14]. The present study was carried out to show the potential of zinc adsorption on Acacia nilotica bark. The aim of this research, were to evaluate the adsorption behavior of zinc (II) onto microwave assisted carbonized Acacia nilotica bark (MACANB).
EXPERIMENTAL:
Preparation of the adsorbent
The experiments were carried out using the adsorbent Acacia nilotica bark. Acacia nilotica bark were collected from the local area and washed several times with distilled water to remove dust and other impurities. Then drying, it was ground using domestic mixer and sieved to 300 mesh size. The sample is washed with distilled water to remove colour and dried in an oven at 800C for 24 hours. The dried Acacia nilotica bark powder was carbonized on muffle furnace for 5 Hours at 500oC. This carbonized bark powder again activated in domestic microwave (900MW) by one minute intervals for 30 minutes. The microwave assisted carbonized Acacia nilotica bark (MACANB) then washed with deionised water to remove colour and other impurities. This MACANB was dried at 110°C in vacuum oven for 24 hours, grind well and kept in air tight plastic bottles for further use.
Preparation of stock solution of Zn (II):
All reagents used are of analytical reagent grade. A Stock solution of 1000 ppm of Zn (II) ion was prepared by dissolving zinc nitrate hexahydrate [Zn(NO3)2.6H2O] in deionised water. Adsorption experiments were conducted to study the influence of adsorption parameters such as pH, initial Zn (II) ion concentration, adsorbent dose, contact time and temperature by using MACANB.
Adsorption Experiment:
Batch adsorption experiments of zinc were carry out to determined the adsorption capacity of MACANB at different Zn (II) ion concentrations ranging from 25 to 150 ppm. The 100 ml of Zn (II) solutions of specified concentration of samples were shaken at 120 rpm for predetermined pH, adsorbent dose, contact time and temperature. The initial and final concentrations of the solutions were measured and determined by Atomic absorption spectrophotometer (AAS) at the maximum adsorption wavelength and the adsorption capacities of the adsorbent were calculated. After equilibrium was attained, the metal uptake capacity for each sample was calculated according to a mass balance on the metal ion using equation (1):
Where m is the mass of adsorbent (g), V is the volume of the solution (L), C0 is the initial concentration of metal (mg L-1), Ce is the equilibrium metal concentration (mg L-1) and qe is the metal quantity adsorbed at equilibrium (mg/g). Experiments were carried out at different initial pH values. The initial pH of the solution was adjusted with either HCl or NaOH. The percent removal of metals from the solution was calculated by the following equation (2):
Where C0 (mg/L) is the initial metal ion concentration and Ce (mg/L) is the equilibrium metal ion concentration in the solution.
RESULTS AND DISCUSSION:
Effect of pH on Zn (II) adsorption:
Figure 1, illustrated that pH obviously influenced the removal efficiency of the zinc ions in the aqueous solution. The results indicated that Zn (II) removal was increased to maximum and then decreased with pH variation from 2 to 10 keeping all other parameters constant (adsorbent dose = 0.2 g, initial Zn (II) concentration = 50 ppm, contact time= 60 min, agitation speed = 120 rpm and T = 30°C). The maximum % removal of Zn (II) was about 92.40% at pH 4. At pH < 3.0, H+ ions compete with Zn(II) ions for the surface of the adsorbent which would hinder Zn(II) ions from reaching the binding sites of the sorbent caused by the repulsive forces. However, the metal removal is minimum presumably due to the enhanced competition of proton with zinc ions for ligand binding sites and complex formation. At pH > 7.0, the Zn(II) ions get precipitated due to hydroxide anions forming a zinc hydroxide precipitate. For this reason, the optimal pH value was selected to be 5.0.
Effect of Contact time on Zn (II) adsorption:
The effect of contact time on the adsorption of Zn (II) ions by MACANB can be seen in figure 2. All parameters such as pH, adsorbent dose, etc. were kept constant (pH = 4, adsorbent dose = 0.2 g, initial Zn (II) concentration = 50 ppm, agitation speed = 180 rpm and T = 30°C). The removal of Zn (II) ions increased rapidly with time up to 60 min and there after increased slowly. According to the results, the equilibrium reached at 60 min and wastaken as the optimal contact time for the subsequent experiments.
Fig 1. : Effect of pH on removal of Zn(II)
Fig 2. : Effect of contact time on removal of Zn(II)
Effect of adsorbent dose on Zn (II) adsorption:
Adsorption efficiency of Zn (II) adsorption was studied by varying the amount of adsorbents from 0.1-0.5 gm keeping other parameters constant (pH = 4, initial Zn (II) concentration = 50 ppm, contact time = 60 minutes, agitation speed = 120 rpm and T = 30°C). Figure 3 shows the effect of adsorbent dose on removal of Zn (II) uptake for MACANB. The removal efficiency of the zinc usually improved on increasing adsorbent doses. This may occur due to the fact that the higher dose of adsorbents in the solution provides the greater availability of exchangeable sites for the ions. From the figure 3, it is clear that the no further increase in adsorption after a certain amount of adsorbent was added (0.2 gm). Hence, optimal adsorbent dose was selected to be 0.2 g. This result also suggest that after a certain dose of adsorbent, the equilibrium conditions reached and hence the amount of ions bound to the adsorbent and the amount of free ions in the solution remain constant even with further addition of the dose of adsorbent.
Fig. 3 : Effect of adsorbent dose on removal of Zn(II)
Effect of temperature on Zn (II) adsorption:
The temperature dependence of the adsorption process is related with several thermodynamic parameters. The temperature showed the negative effect on adsorption of zinc onto MACANB as adsorbent. The temperature effect on removal of zinc ion using MACANB was studied within the range of 300C to 600C keeping other parameters constant (pH = 4, adsorbent dose = 0.2 g, initial Zn (II) concentration = 50 ppm, contact time = 60 minutes and agitation speed = 120 rpm). With increase in temperature from 300C to 600C the percent removal of zinc ions was decreased. From the figure 4, it is clear that the low temperatures are in favours of zinc ion removal. This may be due to a tendency for the metal ions to escape from the solid phase to the bulk phase with an increase in temperature of the solution. The result shows that adsorption mechanism related with removal of zinc is physical in nature. The adsorption process takes place from the electrostatic interaction, which is in general related with low adsorption heat. This implies that the adsorption process was exothermic in nature [15].
Fig. 4 : Effect of temperature on removal of Zn(II)
Effect of initial Zn (II) ion concentration on adsorption:
The effect of initial zinc ion concentration on the adsorption rate was studied in the rage 25 – 150 ppm at pH 4, adsorbent dose 0.2 g, contact time 60 minutes, agitation speed 120 rpm and temperature 30ºC. Figure 5 indicates the effect of initial Zn (II) ion concentration on the adsorption by MACANB. When the initial Zn(II) concentration of sample was increased from 25 to 150 ppm, the removal decreased from 93.60 % to 43.27 % for MACANB. Therefore it was evident from the results that zinc adsorption was dependent on the initial metal concentration.
Fig. 5 : Effect of initial Zn (II) ion concentration.
Adsorption Isotherms of Zn (II) onto MACANB:
The equilibrium adsorption study of zinc removal was carried out by contacting 0.2 g of the MACANB as adsorbent with 100 ml of diverse concentrations from 25 mg/L to 150 mg/L in 250 ml conical flasks for 60 minutes contact time. The data obtained was fitted into four well known adsorption isotherms i.e. Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models.
Freundlich isotherm:
The Freundlich model [16] is a well known equation based on sorption on a heterogeneous surface. In Freundlich equation (3), qe is the amount of zinc adsorbed by sorbent at equilibrium (mg/g), Ce is the equilibrium concentration of zinc (mg /L), KF and n are Freundlich constants shows measure of the adsorption efficiency (mg/g) and adsorption intensity respectively.
Freundlich adsorption parameters were calculated by converting the Freundlich equation (3) into its linear form.
A value of 1/n less than 1 indicates a normal Freundlich isotherm while 1/n more than 1 is suggestive of supportive adsorption [17, 18]. The Freundlich isotherm constants KF and n were estimated from the slope and intercept from Fig. 6. The value of 1/n = 0.204 while n = 4.901 confirms that the adsorption of zinc onto MACANB is favourable along with the R2 value 0.657.
Langmuir isotherm:
Langmuir isotherm model [19] was used to estimate zinc adsorption onto MACANB. The Langmuir isotherm is given by Eq. (5).
Converting the Langmuir equation (5) into its linear form is used to calculate parameters of Langmuir adsorption isotherm.
Where, qm is the adsorption capacity at complete monolayer coverage (mg /g) and KL (L/mg) is the Langmuir isotherm constant which relates to the energy of sorption. Slope and intercept of the straight line plot of Ce/qe vs. Ce were used to calculate the values of qm and KL. The feasibility of the Langmuir isotherm can be expressed in terms of a dimensionless constant or separation factor, RL of Eq. (7) where KL is the Langmuir isotherm constant and C0 is the initial concentration of zinc (mg/L).
In the present study, the maximum monolayer coverage adsorption capacity (qm) from Langmuir Isotherm model was found to be 32.258 mg/g, KL (Langmuir isotherm constant) is 0.794 L/mg, RL (the separation factor) is 0.047 which confirms that the equilibrium sorption was favourable and the R2 value is 0.993 (Fig.7). This shows that adsorption isotherm data fitted well to Langmuir isotherm model.
Temkin Isotherm:
Temkin Isotherm contains a factor that clearly takes account of interactions among the adsorbent–adsorbate. By avoiding the particularly low and large value of concentrations, the model considers that heat of adsorption (function of temperature) of all molecules in the layer would decrease linearly rather than logarithmic coverage [20, 21]. As shown in the equation, its derivation is considered by a regular distribution of binding energies was carried out by plotting the quantity adsorbed qe against lnCe. The model is known by the following equation (8):
Where, Ce (mg/L) is equilibrium concentration of zinc, qe (mg/g) is amount of zinc adsorbed at equilibrium, KT (L/g) represent the Temkin isotherm equilibrium binding constant, bT is the Temkin isotherm constant and B (J/mol) is Constant related to heat of adsorption. In this study, the linear plot of qe versus LogCe gave a straight line with the R2 value of 0.686 (Fig. 8). Temkin constants KT, bT and B are calculated from the values of slope and intercept of the plot.
Dubinin–Radushkevich isotherm:
Dubinin–Radushkevich (D-R) isotherm is usually used to state the adsorption mechanism with a Gaussian energy allocation onto a heterogeneous surface [22, 23]. The D-R model effectively fitted high solute activities and the transitional range of concentrations data.
In the above D-R isotherm equation, qe is amount of adsorbate in the adsorbent at equilibrium(mg/g); qD is theoretical isotherm saturation capacity (mg/g); KD is Dubinin–Radushkevich isotherm constant (mol2/kJ2 ) and ɛ is Dubinin–Radushkevich isotherm constant. The method was usually applied to differentiate the physical and chemical adsorption of zinc ions with its mean free energy, E per molecule of adsorbate can be determined by the relationship [24, 25]:
Where, KD is D-R isotherm constant. In the meantime, the parameter e can be designed as:
Where, R is gas constant (8.314 J/mol K), T is absolute temperature (K) and Ce represent adsorbate equilibrium concentration (mg/L). Dubinin-Radushkevich (D-R) isotherm model lies on the reality that it is temperature-dependent, which when adsorption data are fitted at different temperatures as a function of logarithm of amount adsorbed (lnqe) vs e2 (the square of potential energy), all appropriate data will be positioned on the same curve, named as the characteristic curve [26]. From the linear plot of D-R model (Fig. 9), qD was found to 31.55 mg/g, the mean free energy (E) = 0.104 KJ/mol and R2 = 0.977 higher than that of Tempkin model.
Langmuir, Freundlich, Temkin and Dubinin-Radushkevich adsorption isotherms for removal of zinc from aqueous solution onto MACANB are described in Fig. 6, 7, 8, and 9. It established that the experimental information fitted well to all these isotherm models. Correlation coefficients values indicated that Langmuir isotherm gives a good model for the adsorption system, which is based on monolayer sorption on to the surface limiting finite number of identical sorption sites. The values of various constants of isotherm models were determined and were represented in the Table-1.
Fig. 6 : Freundlich model for zinc sorption onto MACANB.
Fig. 7 : Langmuir model for zinc sorption onto MACANB.
Fig. 8 : Temkin model for zinc sorption onto MACANB.
Fig. 9 : Dubinin-Radushkevich model for zinc sorption onto MACANB
Adsorption Kinetic Study of Zn (II) onto MACANB:
The kinetic study of adsorption of metal ions from aqueous solutions plays an important role because it demonstrates important insight into the reaction pathways and mechanism of the adsorption process. The rate and kinetics of adsorption of zinc on to the MACANB was studied with pseudo first-order model, pseudo second-order model, Intra-particle diffusion model and Elovich kinetic model.
Pseudo first-order kinetic model:
The pseudo first-order kinetic model [27] has been extensively used to understand the metal adsorption kinetics. The pseudo first-order kinetic model is given by equation (12),
Where k1 (min−1) is the rate constant of the pseudo first-order adsorption, qt (mg/g) represent the amount of adsorption at time t (min) and qe (mg/g) is the amount of adsorption at equilibrium. By applying boundary conditions qt =0 at t = 0 and qt = qt at t = t, the integrated form of equation (12) becomes,
The sorption rate can be estimated by plotting log (qe−qt) versus t. Linear kinetics plot were obtained that can be clearly seen in Fig 10 with excellent correlation coefficient (R2 = 0.934), which shows that pseudo first-order kinetic model is suitable to the zinc adsorption onto MACANB. The zinc adsorption was found with the rate constants k1 = 5.98 x 10-2 min−1. The amount of zinc adsorbed (qe) was estimated and it was found to be 40.179 mg/g.
Table-1. : Langmuir, Freundlich, Temkin and Dubinin-Radushkevich Isotherm parameters of zinc sorption on MACANB
|
Isotherm |
Parameters |
|
|
Langmuir Isotherm |
qm (mg/g) |
32.258 |
|
|
KL (L/mg) |
0.794 |
|
|
RL |
0.048 |
|
|
R2 |
0.993 |
|
Freundlich Isotherm |
KF (mg/g) |
14.621 |
|
|
1/n |
0.204 |
|
|
N |
4.901 |
|
|
R2 |
0.657 |
|
Temkin Isotherm |
KT (L/mg) |
34.348 |
|
|
B (J) |
4.311 |
|
|
bT |
584.307 |
|
|
R2 |
0.686 |
|
Dubinin-Radushkevich Isotherm |
qD (mg/g) |
31.55 |
|
|
KD (mol2/kJ2) |
4.606 x 10-5 |
|
|
E (KJ/mol) |
0.104 |
|
|
R2 |
0.977 |
Pseudo second-order kinetics model:
Ho’s pseudo second-order kinetics [27] was used to analyze the adsorption kinetic data. This is represented by,
By applying boundary conditions qt=0 at t = 0 and qt = qt at t = t , integrated form of equation (14) becomes,
Where k2 (g/mg.min) symbolise the rate constant of the pseudo-second-order adsorption, qt (mg/g) represents the amount of adsorption at time t (min) , qe (mg/g) stand for the amount of adsorption at equilibrium and initial sorption rate , h stand for k2qe2 (mg/g min). Plot of t/qt versus t, gives the parameters of pseudo second-order kinetics model. From Fig. 11, the values of qe, k2, h and correlation coefficient (R2) was found to be 32.258 mg/g, 9.02 x 10-4 g mg-1min-1, 0.938 mg g-1min-1 and 0.961 respectively.
Intra-particle diffusion model:
Intra-particle diffusion kinetic model was proposed by Weber and Moris [28–30] for the diffusion controlled sorption process. The intra-particle diffusion equation is given by Eq. (16),
Where, kd is the intra-particle rate constant (mg g−1 min−0.5). Plot of qt versus t0.5 was determined the values of the intra-particle rate constant and constant C (mg g−1) that gives an idea about the thickness of the boundary layer, i.e., the higher the value of C, greater is the boundary layer effect. Fig. 12 suggested that two different types of mechanisms are mixed up in the adsorption process. The preliminary curve represents the boundary layer effect while the linear part relates to intra-particle diffusion. The high correlation coefficient (R2) value (Table 2) indicates the probability of the sorption process being inhibited by both the particle and the pore diffusion models [31–32].
Elovich kinetic model:
Elovich kinetic model [33] is the useful kinetic models for describing sorption process. The Elovich equation is known by Eq. (17) where A is the initial sorption rate (mg g−1min−1) and B is the constant of desorption (g mg−1) for adsorption experiment. Eq. (18) is the simplified appearance of Elovich kinetic equation [34].
The plot of qt against ln t (Fig. 13) gives a slope 1/B, which shows the number of available sites to put up zinc ions. From the information of available sites, the adsorption behaviour of the adsorbent is designed which eventually validates that chemisorption step is rate determined [35]. The correlation coefficient (R2) values from Table 2 validated the appropriateness of this model.
The validity of the above kinetic models for the removal of zinc onto MACANB was observed in the subsequent order as pseudo second-order > pseudo-first-order > Elovich > Intra-particle diffusion. The reported correlation coefficients (R2) value indicates that the adsorption experimental results shows better fit to pseudo second order kinetic model. The values of different constants of kinetic models were calculated and were presented in the Table-2.
Fig. 10 : Pseudo first order model for zinc adsorption
Fig. 11 : Pseudo second order model for zinc adsorption
Fig. 12 : Intra-particle diffusion model for zinc adsorption
Fig. 13 : Elovich kinetic model for zinc adsorption
Thermodynamic Study:
Thermodynamic study is much more useful as it provides effective information on carrying out adsorption. To find out thermodynamic parameters of zinc adsorption onto MACANB study was carried at four different temperatures i.e. 303, 313, 323,333 K. This helpful study was done to see the consequence of temperature on zinc adsorption onto MACANB, thermodynamic parameters related with adsorption method, such as standard free energy change (ΔG°), standard enthalpy change (ΔH°) and standard entropy change (ΔS°)) were determined by using the following equations (19, 20 and 21) [36].
Where Kc is adsorption equilibrium constant; R is Universal gas constant (8.314 Jmol-1K-1) and T is Temperature in Kelvin.
The values of ΔS° and ΔH° can be determined from intercept and slope of linear plot of logK against 1/T (Fig 14). The calculated values of ΔG°, ΔH°, and ΔS° are shown in Table 3. The negative value of ∆G° indicates the feasibility and spontaneous nature of the adsorption process and more negative which indicates that the adsorption process becomes more spontaneous with rise in temperature, which favours the adsorption process. The negative value of ∆H0 represents an exothermic adsorption process and negative value of ∆S0 indicates the decrease in randomness at the solid-solution interface during sorption process [37].
Table-2. : Kinetics parameters of the different kinetic models for adsorption of Zn (II).
|
Kinetic Model |
Parameters |
|
|
Pseudo first-order model |
qe (mg/g)) |
40.179 |
|
|
k1 (min-1) |
5.98 x 10-2 |
|
|
R2 |
0.934 |
|
Pseudo second-order model |
qe (mg/g) |
32.258 |
|
|
k2 (g mg-1min-1) |
9.02 x 10-4 |
|
|
h ( mg g-1min-1) |
0.938 |
|
|
R2 |
0.961 |
|
Intra-particle diffusion model |
kd (g mg-1min-0.5) |
2.142 |
|
|
C |
2.83 |
|
|
R2 |
0.827 |
|
Elovich kinetic model |
A (mg g-1 min-1) |
1.735 |
|
|
B (g mg-1) |
0.128 |
|
|
R2 |
0.916 |
Fig. 14 : The plot of logK vs. 1/T
Table-3 : Thermodynamic parameters of adsorption of zinc onto MACANB
T(K) |
∆G (kJ/mole) |
∆H (kJ/mole) |
∆S (kJ mol-1 K1) |
|
303 |
-4.547 |
- 47.925 |
- 0.144 |
|
313 |
-2.286 |
||
|
323 |
-1.003 |
||
|
333 |
-0.0142 |
CONCLUSION:
Present paper reported the efficiency and applications of microwave assisted carbonized Acacia nilotica bark (MACANB), one of the modified inexpensive easily available adsorbent for the removal of zinc from aqueous solution. The investigation of effect of initial pH, initial zinc ion concentration, contact time, temperature and adsorbent dose on the removal capacity of zinc by MACANB indicates the dependency on these parameters. Quantitative adsorption equilibrium study of removal of zinc onto MACANB from aqueous solution confirms the validity of obtained results and the adsorption data are well fitted for the Langmuir adsorption isotherm model. The kinetic data obtained for adsorption of zinc on MACANB followed the pseudo second-order kinetic model with good correlation coefficient value. Thermodynamic study of sorption of zinc using MACANB indicates the feasibility and spontaneous nature of the adsorption process.
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Received on 27.01.2017 Modified on 05.02.2017
Accepted on 21.02.2017 © AJRC All right reserved
Asian J. Research Chem. 2017; 10(1):45-53.
DOI: 10.5958/0974-4150.2017.00009.8