The issues surrounding water are expected to grow worse in the coming decades with water scarcity occurring globally. Due to rapid industrialization there is a tremendous increase in the use of heavy metals over the past few decades. Despite of the usefulness of metals, they can be very harmful to humans and the environment if they are present in excess due to their toxic nature. ‘Heavy metal’ is a general collective term applying to the group of metals and metalloids with an atomic density greater than 6 g/cm³ [1]. Heavy metals such as Cd, Cr, Cu, Hg, Ni, Pb, and Zn are commonly associated with pollution and toxicity problems. Heavy metals are toxic, carcinogenic, mutagenic and often teratogenic [2].

In view of the aforesaid problems, much attention has been focused on the development of adsorbents from various types of biomaterials for the removal of metals from water and wastewater [3-5]. Considerable success has been achieved in the development of biosorbents for the removal of a wide variety of metal ions from aqueous solutions. Recently, Volesky [6] has shared his views concerning the biosorption of metal ions from aqueous solution in his review. In his view, ‘biosorption of metals’ is only the ‘tip of the ice-berg’ and in the future, it will be useful for purification and recovery of other valuable materials like proteins, steroids and drugs that cost thousands of dollars per gram. Biosorption is a physico-chemical process and includes mechanisms such as absorption, adsorption, ion exchange, surface complexation and precipitation [7]. Survey of the literature by ISI Web of Science [Topic = (biosorption) AND Topic = (Iron(III)), Refined by: Document type = (ARTICLE OR REVIEW), Timespan = 2001？2010. Databases = SCI-EXPANDED] further revealed that the most widely studied metal ions through biosorption are divalent cadmium, copper, lead, zinc, and nickel followed by hexavalent and trivalent chromium (Fig. 1). In view of this we have carried a study related to biosorption cadmium and copper ions from aqueous solution using a low-cost agricultural waste Moringa oleifera bark powder.

Moringa oleifera belongs to the family Moringaceae. Moringa oleifera bark is abundantly available with no commercial use in several countries. Due to wide cultivation of this tree, a massive amount of bark is produced, which is being disposed of as waste. The bark tissue of M. oleifera contains 4-(α-Lrhamnopyranosyloxy)- benzylglucosinolate [8]. Every glucosinolate contains a central carbon atom, which is bonded to the thio-

glucose group (making a sulfated ketoxime) via a sulfur atom and to a sulfate group via a nitrogen atom. These functional groups containing sulfur and nitrogen are good metal sequesters from the aqueous solution. Due to the composition of Moringa oleifera bark and its availability, it was chosen as a biosorbent for the removal of Cd(II) and Cu(II) from aqueous solutions.

In the present study, a simple and economic preparation of the biosorbent was performed and biosorption experiments have been conducted in order to determine the metal biosorption mechanism. The influence of pH, time, biosorbent dosage, and initial concentration were discussed in detail. The data from the experiments were fitted with different kinetic models to identify the adsorption mechanism. The results would contribute to a better understanding of biosorption and aid in the development of potential biosorption, which possess almost complete removal efficiency for Cd(II) and Cu(II) from an aqueous environment using Moringa oleifera bark.

Moringa oleifera bark samples were collected from Punganur (Andhra Pradesh, India). All the chemicals used were of analytical grade and obtained from M/S Qualigens Fine Chemicals, Mumbai, India. The synthetic solutions were prepared by dilut-ing Cd(II) and Cu(II) standard stock solutions (concentration 1,000 ± 2 mg/L). Fresh dilutions were used in each experiment.

Moringa oleifera bark samples were collected from Punganur (Andhra Pradesh, India). Bark samples were cut into small pieces then air dried and ground in a mill to obtain fine powder, the bark pieces and bark powder was shown in Fig. 2. The bark powder was washed twice with deionized water and dried at 60℃ for 24 hr, then boiled in double distilled water by changing the water repeatedly until the water became colorless, which indicated the removal of water soluble color compounds. The washed and boiled bark was oven dried at 80℃ for 24 hr and stored in a desiccator to prevent moisture adsorption before its use. This treated Moringa oleifera bark powder is called MOB [9].

The functional groups present in MOB were analyzed by Thermo Nicolet IR-200 (Waltham, NC, USA) Fourier transform infrared spectroscopy (FTIR), using potassium bromide discs. Vario EL (Elementar, Hanau, Germany) was used for elemental analysis of the MOB. An atomic absorption spectrophotometer (AAS) (Model AA 6300; Shimadzu, Tokyo, Japan) was used for determination of Cd(II) and Cu(II) before and after biosorption.

The biosorption tests were performed by the batch technique in a single system using stoppered conical flasks on a temperature- controlled water bath shaker set at 200 rpm and maintained at the desired temperature. After the prescribed contact time, the solutions were filtered through Whatman filter paper No. 41 and the concentration of metal in the filtrate was measured using AAS. The extent of biosorption was calculated as follows.

The percentage of removal and the amount of metal ion sorbed onto the MOB were calculated according to the following equations:

Where C_i and C_f are concentrations of the metal ions in the solution initially and after biosorption. Also, v and m are solution volume and mass of biosorbent, and Q_e is the amount of metal ions adsorbed on the biomass (mg/g), respectively.

From elemental analysis results it was identified that MOB is composed of 44.8 ± 1.50% carbon, 5.9 ± 0.18% hydrogen, 0.8 ± 0.01% nitrogen, 0.9 ± 0.01% sulphur and 47.6 ± 1.82% oxygen. Sulphur groups, which are soft bases, have chemical affinity towards metal ions and the presence of sulphur in MOB qualifies it as a potential biosorbent.

The FTIR spectrum of MOB revealed the presence of many functional groups, indicating the complex nature of MOB bio-

sorbent (Fig. 3). A strong band at 3,418 cm^-1 indicated the presence of hydroxyl groups. A peak at 2,920 cm^-1 observed is due to the C-H stretching frequency and the peak at 1,644 cm^-1 is due to the C = O stretching mode of the primary and secondary amides (NH₂CO). The peaks at 1,510 cm^-1 and 1,375 cm^-1 are indicative of the N-H stretching regarding the primary and secondary amides, and the presence of amide (III) or sulfamide band, respectively. Bands at 1,320 and 1246 cm^-1 indicate the presence of carboxylic acids [9].Weak bands at 1,462 and 1,510 cm^-1 are attributed to aromatic C = C and two sharp peaks at 1,733 and 1,644 cm^-1 are characteristic of carbonyl group stretching. The strong C-O band at 1,054 cm^-1 confirms the lignin structure of the MOB [10].

In addition to the FTIR characterization of the functional groups in the pure biomass MOB, the technique was used to determine the functional groups that are involved in the binding of the metals onto the biomass in biosorption process of metals. The infrared spectra of the biomass loaded with Cd(II) and Cu(II) shown in Fig. 3. The asymmetrical stretching vibration at 3,418 cm^-1 for the pure biomass was shifted to the lower region 3,361？3,380 cm^-1 in the FTIR spectra of MOB loaded with Cd(II) and Cu(II). The absorption peak at 1,732 cm^-1 of MOB is slightly shifted to a higher wave number of 1,733？1,732 cm^-1 on Cd(II), and Cu(II) adsorption as reported in earlier studies. The FTIR spectrum of metal loaded MOB shows a shift in the C-O absorption peak of MOB from 1,054 cm^-1 to 1,025？1,035 cm^-1 indicating the involvement of the C-O functional group in the binding of Cd(II) and Cu(II). The variation in intensity and shift in asymmetrical stretching frequencies at 3,418, 1,732, 1,644, and 1,054 cm？1 of MOB on biosorption was presumably due to the coordination of the Cd(II) and Cu(II) ions with hydroxyl, carboxyl, and carbonyl groups present on the surface of MOB.

The effect of pH on metal biosorption has been studied by many researchers, and the results indicated that the pH values of the solution could significantly influence biosorption [11, 12]. The pH level affects the network of negative charge on the surface of the biosorbent cell walls, as well as the physic-chemistry and hydrolysis of the metal. Therefore, preliminary experiments have been performed in order to find out the optimum pH for

maximizing the metal removal by varying pH 2？8 (Fig. 4). It has been observed that under highly acidic conditions (pH ？ 2.0) the amount of metal removal was very small. The lower removal efficiency at low pH is apparently due to the presence of a higher concentration of H⁺ in the solution, which competes with metal ions for the adsorption sites of the MOB. A trend of increasing metal ion binding with increasing pH from 3.0 to 6.0 could be observed for all metal ions. The results revealed that the optimum biosorption pH values for Cd(II) and Cu(II) onto MOB were 5.0 and 6.0. After pH 6.0, a decrease biosorption of Cd(II) ions was observed. It suggests that the binding strength of Cd(II) on biomass seems to be weaker than that of Cu(II) at higher pH since the biosorption of Cd(II) was less than Cu(II). Besides, with the rise in pH, fewer H⁺ ions exist, and consequently, Cd(II) ions have a better chance to bind to free binding sites. Later, when the pH enters basic conditions (Eqs. 3-5), the formation of Cd(OH)₃― takes place due to the dissolution of Cd(OH)₂ and as a result, the adsorption rate decreases.

Another explanation for metal ion removal has been provided when considering the point of zero charge (PZC) regarding MOB. The PZC of biosorbent was determined according to the procedure described in another study [13]. At a pH below 4.2 ± 0.67 (PZC), the surface of MOB was positively charged due to protonation. This protonation effect was more pronounced at lower pH values due to the presence of a higher concentration of H+ ions in the solution, which is unfavorable for biosorption. At the optimum pH values (pH 5.0 and 6.0) the surface of the MOB is negatively charged and favorable to the biosorption of Cd(II) and Cu(II) ions. Decreased biosorption at higher pH (pH > 6) was due to the formation of soluble hydroxylated complexes of the metal ions and their competition with the active sites, and as a consequence, the retention decreased further.

Biosorption of Cd(II) and Cu(II) onto MOB was studied by changing the quantity of sorbent from 0.1 to 0.8 g in the test solution while maintaining the initial concentration 50 mg/L, pH 6 and contact time of 2 hr constant. Obviously, the biosorption efficiency increased as the sorbent dose increased, but it remained almost constant when the sorbent dose reached 0.4 g, the maximum removal observed is >90% respectively for Cd(II) and Cu(II) ions. This may be explained by the following analysis. When sorbent dose is minimal, the active sites for binding metal ions on the adsorbent surface is decreased, so the adsorption efficiency is low; when the biosorbent dose increased, more metal ions were adsorbed. Thus, it resulted in the increment of adsorption efficiency until saturation.

For practical applications, the process design, operation control, and sorption kinetics are very important. The effect of contact time on the biosorption of Cd(II) and Cu(II) onto MOB at various initial concentrations was carried out at different time intervals (5？70 min) by keeping pH and dose constant. For all metals, it is shown that sorption occurred very fast because equilibrium was reached within 30 min. The majority of cations were removed within the first 20 min of contact time with the biosorbent. After a very rapid biosorption, the biosorption rates for all metals slowly declined. Initially, the biosorption sites are open and the metal ions interact easily with the sites and hence a higher rate of biosorption is observed. Further, the driving force for biosorption the concentration difference between the bulk solution and the solid-liquid interface is initially higher and this resulted in a faster biosorption rate. However, after the initial period, a decrease in biosorption may be due to the slower diffusion of solute into the interior of the biosorbent [14]. Despite the same experimental conditions used, it is interesting to note that the fixation capacities were different according to the metal sorbed. Also, the equilibrium times were slightly different among the metals. Quantitatively, more Cd(II) ions were adsorbed than Cu(II).

In order to further investigate the biosorption mechanism of

Cd(II) and Cu(II) ions onto MOB and the rate-controlling steps, a kinetic investigation was conducted, pseudo-first, pseudo-second- order and intra-particle diffusion kinetic models have been used for testing the experimental data. The pseudo-first-order kinetic model was proposed by Lagergren [15]. The integral form of the model was generally expressed as follows:

where, q_e (mg/g) and q_t (mg/g) are the adsorption amounts at equilibrium and time t (min), respectively. Also, k₁ (min^-1) is the rate constant in the pseudo-first-order adsorption process. The constants were determined experimentally by plotting log(q_e-q_t) versus t.

The pseudo-second-order kinetic model, proposed by Ho and McKay [16] is based on the assumption that the adsorption follows second-order chemisorption. The linear form can be written as:

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

An empirically found functional relationship, common to most adsorption processes, is that the uptake varies almost proportionally with t^1/2, as per the Weber-Morris plot, rather than with the contact time, t [17]:

where q (mg/g) is the adsorbed metal amount and K_i is the intra- particle diffusion rate constant (mg/g/min^1/2). According to this model, the plot of uptake (q) versus the square root of time should be linear if intra-particle diffusion is involved in the adsorption process and if these lines pass through the origin then intra-particle diffusion is the rate-controlling step.

For the Lagergren’s first-order kinetic model [15], a plot of log (q_e-q) against t according to Eq. (6) should give a straight line to confirm the applicability of the kinetic model. In a true first order process log q_e should be equal to the intercept of a plot of log (q_e- q) against ‘t’. From the results in Table 1, it is observed that the

theoretical values (q_e,cal) were far lower than those of the experimental data, q_e,exp and low correlation coefficient values obtained for the pseudo-first-order model indicated that sorption does not occur exclusively on one site per ion.

The pseudo-second-order model was developed based on the assumption that the rate limiting step may be chemisorption promoted by either valence forces, through sharing of electrons between the biosorbent and sorbate, or covalent forces, through the exchange of electrons between the parties involved [16]. A plot of “t/q_t” versus “t” should give a linear relationship for the applicability of the second-order kinetic. The rate constant (K₂) and adsorption at equilibrium (q_eq) can be obtained from the intercept and slope, respectively. The dependence of t/q_t versus t gave a linear relation for all experimental concentrations (Fig. 5).

The comparison of experimental adsorption capacities and the theoretical values estimated from the first- and second-order equation are presented in Table 1. The Lagergren’s model did not provide sufficient information to explain the experimental kinetic data. Whereas, the theoretical q_eq values for the adsorption of heavy metal ions on the biosorbent are very close to the experimental q_eq values in the case of the second-order kinetic (Table 1). This suggests that the rate-limiting step may be the chemical adsorption not the mass transport limitation. The initial adsorption rate, h₀ (mg/g/min) is given in Eq. (8). The values of q_e, k₂, h₀, and R² are listed in Table 1. All the R² values are closer to “one”, confirming the applicability of the pseudo-second-order equation. The values of the rate constants varied with the initial concentration for all metals. Although consistency is expected for these values when a single controlling mechanism is assumed by the model, variations do occur for natural biosorbents and are usually attributed to the heterogeneous nature of the biosorbent surface [18]. From Table 1, it can be observed that, with an increase in the initial metal concentration, the initial sorption rate (h₀) also increased. In accordance with the pseudo-second reaction mechanism, the overall rate of Cd(II) and Cu(II) sorption processes appears to be controlled by the chemical processes, through the sharing of electrons between the biosorbent and sorbate, or covalent forces, through the exchange of electrons between the particles involved.

An empirically found functional relationship, common to most adsorption processes, is that the uptake varies almost proportionally with t^1/2, as per the Weber-Morris plot, rather than with the contact time, ‘t’. According to this model, the plot of uptake (q) versus the square root of time should be linear if intra-particle diffusion is involved in the adsorption process and if these lines pass through the origin then intra-particle diffusion is the rate-controlling step. The low correlation coefficient values obtained (Table 1) for the intra-particle diffusion model indicated that adsorption does not occur in the pores of biosorbent in accordance with surface adsorption. Increasing metal ion concentration in the aqueous solutions seems to reduce the external diffusion of the adsorbate and enhances the intra-particular diffusion. If the intra-particle diffusion was involved in the adsorption process, then a plot regarding the amount of heavy metal adsorbed per unit mass of adsorbent (q_t) against square root of time (t^1/2) gave a straight line and the particle diffusion would be the controlling step, if this line passed through the origin. The deviation of straight lines from the origin indicates that intraparticle transport is not the rate-limiting step. As seen from the figure, the intra-particle diffusion rate equation fits well to the initial stages of the adsorption process for all the tested metal ions with the MOB biomass system.

The successful representation of the dynamic adsorptive separation of the solute from solution onto an adsorbent depends upon an appropriate description of the equilibrium separation between two phases [19]. In order to determine the mechanism of Cd(II) and Cu(II) ions biosorption onto MOB and to evaluate the relationship between biosorption temperatures, the experimental data was applied to the two-parameter non-linear isotherm models, i.e., Langmuir, Freundlich, Dubinin-Radushkevich (D-R), and Temkin models by the nonlinear estimation method in the Origin 7.0^® software (MicroCal, Northampton, MA, USA).

The Langmuir isotherm [20] equation can be written in the following form:

where parameters q_m and b are Langmuir constants related to maximum adsorption capacity (monolayer capacity) and bonding energy of adsorption, respectively, which are functions for the characteristics of the system as well as time. The Langmuir equation is used for homogeneous surfaces.

The essential features of the Langmuir biosorption isotherm can be expressed in terms of a dimensionless constant separation factor (R_L), which is defined in Eq. (11).

where K_L is the Langmuir constant (L/mg) and C₀ is the initial adsorbate concentration (mg/L). The R_L values between 0 and 1 indicate favorable adsorption [21].

Freundlich isotherm is an empirical equation. This equation is among one of the most widely used isotherms for the description of adsorption equilibrium. Freundlich isotherm is capable of describing the adsorption of organic and inorganic compounds on a wide variety of adsorbents including biosorbent [22]. This equation has the following form

As a robust equation, Freundlich isotherm has the ability to fit nearly all experimental biosorption-desorption data, and is especially excellent for fitting data from highly heterogeneous sorbent systems. Accordingly, this isotherm can adequately represent the biosorption isotherm for most of the systems studied. The 1/n values were between 0 and 1 indicating favorable biosorption of Cd(II) and Cu(II) onto M. oleifera bark biosorbent.

Dubinin and his co-workers conceived this equation for subcritical vapors in micropore solids where the adsorption process follows a pore-filling mechanism onto an energetically nonuniform surface [23]. The Dubinin-Radushkevich (D-R) model, which does not assume a homogeneous surface or a constant biosorption potential as the Langmuir model, was also used to test the experimental data.

Where Q_m is the maximum amount of the metal ion that could be sorbed onto a unit weight of sorbent (mg/g), ε is the Polanyi potential, which is equal to RT ln (1+1/C_e), where R and T are the universal gas constant (kJ/mol/K) and the absolute temperature (K), respectively. K is related to the mean free energy of sorption per mole of the sorbate when it is transferred to the surface of the solid from infinity in the solution and this energy can be computed using the following relationship.

At first, the Temkin equation was proposed to describe the adsorption of hydrogen on platinum electrodes within acidic solutions. The Temkin isotherm [24] assumes that the heat of adsorption for all the molecules in the layer decreases linearly with coverage due to adsorbent-adsorbate interactions, and that the adsorption is characterized by a uniform distribution of the binding energies, up to some maximum binding energy [25].

Where constant B₁ = RT/b, which is related to the heat of adsorption, R is the universal gas constant (J/mol/K), T is the temperature (K), b is the variation of adsorption energy (J/mol) and K_T is the equilibrium binding constant (L/mg) corresponding to the maximum binding energy.

A model isotherm graph for the biosorption of Cd(II) at 313 and 323 K is shown in Fig. 6. The Langmuir adsorption constants calculated from the corresponding isotherms with the correlation coefficients are presented in Table 2. The maximum theoretical adsorption capacities of Cd(II) and Cu(II) calculated from Langmuir equation are 39.41 and 36.59 mg/g biosorbent, respectively at 323 K. Comparisons between the correlation coefficients and the chi-square square values of four isotherm models it was observed that equilibrium data was well represented by the Langmuir isotherm model. The conformity of the biosorption data to the Langmuir isotherm could be interpreted as an indication of a homogeny adsorption process, leading to monolayer binding. Based on the effect of the separation factor, R_L values are in the range of 0 < R_L < 1, which indicates that the biosorbent is a favorable adsorbent for the removal of Cd(II) and Cu(II) ions from aqueous solution. The constant q_m and K_L increased with increase in temperature.

The constants for the Freundlich models, K_F and 1/n, are constants related to biosorption capacity and intensity of biosorption, respectively. The 1/n values are between 0 and 1, indicating that the biosorption of Cd(II) and Cu(II) onto the MOB is favorable at the studied conditions. Furthermore, the correlation coefficient values for the Freundlich model are lower than the Langmuir isotherm model.

The equilibrium biosorption data was also fitted with the D-R isotherm expression, however the correlation coefficients were found to be lower than that of the Langmuir model. The mean free energy of biosorption (E) gives an idea about the biosorption mechanism, whether physical or chemical. If the value of E lies between 8 to 16 kJ/mol, the biosorption process takes place chemically and if the value of E is less than 8 kJ/mol, then the

biosorption process takes place physically. In the present study, the value of E at three different temperatures for Cd(II) and Cu(II) ions is between 8？16, which shows that the biosorption is found to be chemical in nature.

Temkin isotherm constants are given in Table 2. K_T is the equilibrium binding constant corresponding to the maximum binding energy and constant B is related to the heat of biosorption. The Temkin isotherm model exhibited low correlation coefficient values compared to the Langmuir isotherm model.

The chi-square (χ²) test was also carried out to find the best fit among the biosorption isotherm models. The equation for

evaluating the best fit model is to be evolved as:

where q_e,m is the equilibrium capacity obtained by calculating from a model (mg/g) and q_e is the experimental data of equilibrium capacity (mg/g).

The high values of correlation coefficient and low chi-square values demonstrate equilibrium data was well fitted to Langmuir isotherm model comparing with other isotherm models (Table 3). This suggests the applicability of the monolayer coverage for Cd(II) and Cu(II) ions on the MOB surface. Furthermore, from Table 2 it was observed that the maximum adsorption capacity increases as the process temperature rises, which means that an increase in energy favors the biosorption onto the MOB surface. This behavior indicates an enthalpy variation during positive biosorption or the endothermic process. However, this behavior is inverted in Henry’s infinite dilution region, that is, at very low concentrations (up to 10 ppm).

Based on the fundamental thermodynamic concept, it is assumed that in an isolated system, energy cannot be gained or lost and the entropy change is the only driving force. In environmental engineering practice, both energy and entropy factors must be considered in order to determine which process will occur spontaneously.

In this research, the thermodynamic parameters, such as standard Gibbs free energy G° (kJ/mol), the standard enthalpy (ΔH°), and the standard entropy (ΔS°) for the biosorption of Cd(II) and Cu(II) onto MOB were calculated using the following equation,

where K (L/g) an equilibrium constant obtained by multiplying the Langmuir constants q_m and K_L [26]. R is the universal gas constant (8.314 × 10^-3 kJ/mol/K) and T is the absolute temperature (K). The enthalpy (ΔH°) and entropy (ΔS°) parameters were estimated from the following equation:

Eq. (20) can be written as:

The Gibbs free energy, which changes for the biosorption process are presented in Table 4 and the results demonstrate that

the change in Gibbs free energy values is negative. The negative ΔG° values of Cd(II) and Cu(II) at various temperatures indicated that the biosorption process is spontaneous, and the values of ΔG° (Table 4) decreased with an increase in temperature, indicating the spontaneous nature of biosorption for Cd(II) and Cu(II). The value of ΔH° is positive, indicating the endothermic nature of the biosorption for Cd(II) and Cu(II) onto MOB. In addition, the positive values of ΔS° shows an affinity of biosorbent and the increasing randomness at the solid-solution interface during the biosorption of Cd(II) and Cu(II) on the bark.

The present study demonstrated that MOB is an effective biosorbent for the removal of Cd(II) and Cu(II) ions from aqueous solutions by adsorption. The uptake of metal ions by MOB seemed to be quite rapid and the experimental data obeyed the pseudo-second-order model well. Also, the equilibrium data fit well to the Langmuir isotherm model. Based on the obtained results, it is believed that the application of the biosorption process using MOB for the purification of industrial waste water containing Cd(II) and Cu(II) ions can be achieved in a bioreactor design or large-scale batch biosorption systems.