Kinetics, Isotherms and Thermodynamics of Heavy Metal Ions Sorption onto Raw and Agro-Based Magnetic Biosorbent

In this study, the kinetics, isotherms, and thermodynamics of heavy metal ions sorption onto novel magnetic biosorbents synthesized from the Oil Palm Empty Fruit Bunch (EFB) fibers, Ceiba pentandra (kapok) and cellulose extracted from EFB were evaluated. Different effective factors such as contact time, initial metal ion concentration and also temperature were investigated for the removal of Pb(II), Cu(II), Zn(II), Mn(II) and Ni(II) ions from the aqueous solutions. The adsorption efficiency of metal ions onto magnetic biosorbents was increased as compared to when using the micro-sized raw fibres. The experimental data fitted well to the pseudo-second-order kinetics while the equilibrium sorption data for both the raw and magnetic sorbents obeyed the Freundlich isotherm model. The n value for Freundlich and the RL separation factor for Langmuir suggested that the metal ions are favorably adsorbed by all the three magnetic biosorbents. Furthermore, the E value from Dubinin-Redushkevich (D-R) equation indicated the low contribution of physisorption mechanism. The thermodynamics analyses indicate that the metal ions sorption on all the examined biosorbents is feasible, spontaneous and generally endothermic in nature.


Introduction
Ground water contamination is one of the pressing environmental issues, a result of excessive and uncontrolled humans, animals and other biological activities. Heavy metal ions affecting the water resources are especially of great concerns due to the toxicities, even at low concentrations, and their propensity to bioaccumulation and non-biodegradability [1]. The term "heavy metal" is applied to the naturally occurring metals and metalloids, having an atomic density equal to or greater than 6 g cm -3 , such as Cr(III,VI), As(III,V), Cd(II), Pb(II), Cu(II), Zn(II) and Hg(II). Mining, metal plating, energy and fuel combustion for heat or power generation, steel or cement manufacturing, agricultural applications, and plumbing are among many industries with high heavy metal contamination in the production process wastewater [2][3][4][5][6][7][8][9][10].
Water contamination from the release of heavy metals in water and wastewater is hazardous. The toxicological and physicochemical properties are actually influenced by the elemental speciation [4]. Having metallic ions above permitted limits in drinking water is deleterious on human health, a fact that has been known for a long time. The removal of heavy metal ions pollution from water, at least to below the regulatory level, is therefore necessary. Various removal techniques have been developed, and adsorption specifically is attracting much attention due its simplicity, flexibility and effectiveness. A variety of adsorbents including organic, inorganic, natural, synthetic, activated or modified materials have been applied for aqueous [11][12][13][14] or soil remediation [6,14]. A great majority of the technique involves chemical modification which may produce by-products and indirectly causing harmful effects on the environment. The activated carbon, though mentioned by the US Environmental Protection Agency as an excellent treatment technology [15], the synthesis and application is expensive and non-green if obtained from the non-renewable initial materials like lignite, coal and petroleum coke, requiring significant amount of energy for the synthesis.
The cost-effective methods for heavy metal ions removal will be via adsorption using waste or non-waste biomass with minimal energy consumption such as with physical modification, instead of chemical modification. The greener remediation technique based on biosorption has become increasingly the main focus by making use of the property of biomolecules to bind and concentrate selected ions or other molecules from aqueous solutions [16]. Natural biosorbents especially agricultural wastes such as EFB [17], Ceiba pentandra, activated carbon from sugarcane bagasse, bamboo husk, sawdust [18], and other raw and modified lignocellulosic materials, have been reported. While these adsorbents are extremely porous which provide high surface area for adsorption, the intraparticle diffusion may cause reduction in vacant space and the adsorption capacity. The development of versatile biocompatible adsorption with possible continued use, low intraparticle diffusion rate, large surface area and active surface sites is therefore becoming necessary. The magnetic nano-particle technology has received increasing attention to resolve the environmental issues [19]. It provides large surface area and small diffusion resistance with the feature of easy separation process [20]. The application of magnetic lignocellulose-based materials for the removal of dyes and heavy metal cations from water and wastewater [21] has been reported, but the issue related to its costly synthesis must be addressed for its potential wide application in environmental remediation. Surface functionalized Magnetic Nanoparticles (MNPs) and Magnetic Biosorbent (MBSs) can be applied to adsorb pollutants from aqueous or effluents and can be separated from the medium by using a magnetic field for continuous use. Natural organic materials, mainly biopolymers such as cellulose, chitosan, cyclodextrin, gum arabic, gum kondagogu, orange peel, and alginate are applied as effective additive materials to capture the advantages of different functional groups presentation in their structure for high capacity and selectivity towards dyes and heavy metals [22].
The raw EFB has been developed as biosorbent without any chemical modification, achieving more than 92% adsorption efficiency with the highest Pb(II) sorption at 47.98 mg/g after 90 min at pH 7.5 [17]. At 0.005-0.02 mm powder size, it reaches 94% efficiency with 47.49 mg/g Pb(II) ion removal at pH 7.5, in 60 min [23]. The cellulosic fibers of EFB have also been modified with Ethylene Diamine Tetra Acetic Acid (EDTA) to obtain the highest Pb(II) sorption at 236.7 mg/g sorbents [24]. The cellulose from EFB is also further developed into composite with hydroxyapatite to form chemically-modified carbon electrode and has successfully detected trace Pb(II) ions in the complex medium such as blood serum, in the physiologically relevant range of 10-60 ppb [25]. We have reported the study on preparation, characterization and development of Agro-Based Magnetic Biosorbents (AMBs) from Ceiba pentandra (RKF), EFB and Celluloses (CEL) extracted from EFB, using a novel, simple and cost-effective preparation technique for the removal of Pb(II), Cu(II), Zn(II), Mn(II) and Ni(II) ions from aqueous solutions. Under optimal conditions, the magnetic biosorbent based on kapok showed the best Pb(II) removal efficiency of 99.4% and 49 mg/g adsorption capacity as compared to 98.2% for cellulose and 97.7% for EFB, and successfully performed for 5 adsorption/desorption cycles. The magnetic biosorbents also exhibited 10.3% higher removal efficiency than the raw sorbents [26]. To the best of our knowledge, there has yet to be any comprehensive studies on the use of magnetic biosorbent based on oil palm and Ceiba pentandra fibres for general environmental remediation application. This study could pave the way for the use of magnetic biosorbent for waste water treatment and environmental remediation of heavy metal and oil contamination.
The objective of current study was to evaluate the kinetics, isotherms and thermodynamics of heavy metal ions sorption onto raw and agro-based magnetic biosorbent of EFB (Fe 2 O 3 @EFB), Cellulose (Fe 2 O 3 @CEL) and Kapok (Fe 2 O 3 @RKF).

Materials and chemicals
The EFB were obtained from the FELCRA Nasaruddin Palm Oil Mill, Bota, Perak, Malaysia; while the RKF was collected from Telok Belanja Village in Dungun, Terengganu, Malaysia [23]. The micro-sized raw EFB from the shredded fibres and the kapok fibres were produced by two cycle of grinding using a grinder and a hammer mill and a Planetary Mono Mill (FRITSCH GmbH) to achieve the sizes ranging from 0.005-0.02 mm [23]. The purely extracted CEL was obtained from EFB fibres as reported before [27,28]. The Fe 2 O 3 nano-particles (5-50 nm) were purchased from Merck. Pb(NO 3 ) 2 , CuCl 2 , ZnSO 4 , NiCl 2 and MnCl 2 (Merck) were used to prepare the stock solutions of Pb(II), Cu(II), Zn(II), Ni(II) and Mn(II), respectively, by dissolving the required amount in distilled water at room temperature. The magnetic biosorbent from the raw agro-based materials were prepared via a novel dispersion method as reported earlier [26].

Batch adsorption by raw and magnetic biosorbent
Batch adsorption studies were performed at different temperatures (298 to 338K). Fifty mL of each metal ion solution at different concentration levels (100-1000 ppm) was separately added to 0.5 g of the sorbents. The mixture was continuously shaken at 150 rpm for different duration (5-150 min). Then, the solution was filtered using filter paper and a magnet to separate out the raw and magnetic biosorbents, respectively.
Free metal ions before and after adsorption was determined by an Atomic Adsorption Spectroscopy (AAS, Hitachi Z-5000). Each experiment was performed in triplicate and the average values were reported. The adsorption capacity (q e ) and the removal efficiency (µ) of adsorbents were calculated as follows: (2) where C i and C e are the initial and equilibrium metal ion concentration (mg/L), respectively; V is the volume of metal ion solution (L); and W is the weight of biosorbent (g).

Adsorption kinetic models
The adsorption kinetics provides the rate of adsorbed sorbate onto the raw and magnetic biosorbents within the equilibrium contact time. The pseudo-first-order and pseudo-second-order kinetic models as two commonly used models, were applied to estimate the rate constant of the adsorption process.

Pseudo-first-order:
The pseudo-first-order kinetic model is originally based on the adsorption of ocalic acid and malonic acid onto charcoal, and generally expressed as follows: log(q e − q t ) = log q e − ( )t where q e is the equilibrium concentration of metal ions adsorbed per unit mass of sorbent (mg g -1 ), q t is the metal ions concentration (mg g -1 ) adsorbed at time t (s), and k 1 (s -1 ) is the adsorption rate constant.
Linear plot of log (q e -q t ) versus t provides the slope of k 1 as the rate of reaction and the intercept of log q e . Theoretical adsorption capacity in equilibrium, q e.cal was calculated and compared with the experimental q e,exp.
Pseudo-second-order: Pseudo-second-order kinetic model in linear form can be expressed as [29]: The plot of t/q versus t gives a straight line with q e determined from the slope, m, as q e = 1/m. Adsorption rate constant, k 2 (g/mg/min) is obtained from the intercept, C, as k 2 = 1/(Cq e 2 ). The initial sorption rate, h (mg min -1 ) of metal ions describes the feasibility of adsorption.
Intra-particle diffusion model: Intra particle diffusion model proposed [29] as: q t = k i t 1/2 +C where k i is the rate constant of the intra-particle diffusion (mg g −1 min −1/2 ) and C is the intercept. In this model, because of the porous nature of the adsorbent, the pore diffusion is assumed to be via the surface sorption.

Adsorption isotherms
The adsorption isotherm describes an overview of the distribution of adsorbate species in the solid and aqueous phase onto the adsorbent surface at an equilibrium condition. For a batch sorption study, the experimental data fitness to some types of adsorption isotherm models determines the most appropriate interaction between the adsorbate and the adsorbents that can be used in the optimization of solvent to solute ratio at particular operating condition. In this study, the adsorption isotherm was carried out based on three models -Langmuir, Freundlich and Dubinin-Radushkevich (DR) Isotherm. The linearized forms of the mathematical equations were utilized to fit the equilibrium data for ease of comparison of the parameters and constant values.
Langmuir model: The Langmuir adsorption isotherm has been used for many sorption processes [30]. It can predict the maximum monolayer adsorption capacity of the adsorbent and also characterize if the adsorption is desirable or not. The linearized Langmuir isotherm is as follows: where C e is the metal concentration at equilibrium (mg L −1 ), q e is the adsorption capacity at equilibrium (mg g −1 ), K is the Langmuir adsorption constant (L mg −1 ), and q o is the maximum concentration taken by the adsorbent (mg g −1 ). The feasibility of adsorption process could be calculated by using separation factor, R L . The separation factor R L is the dimensionless function of Langmuir model, which helps to classify the Langmuir type adsorption isotherm process, whether favorable or unfavorable, expressed as follows [31]: Freundlich model: The Freundlich adsorption isotherm model is based on multilayer adsorption. In this model, the mechanism of adsorption and the rate of adsorption are the functions of the constants, n and k f . The Freundlich adsorption isotherm is described as follows: where C e is the metal concentration at equilibrium (mg L −1 ), q e is the adsorption capacity at equilibrium (mg g −1 ) , and k f and n are the isotherm constants signifying the capacity and the intensity of the adsorption, respectively.

Dubinin-Radushkevich model:
Dubinin-Radushkevich isotherm is generally applied to express the adsorption mechanism with a Gaussian energy distribution onto a heterogeneous surface and to distinguish the physical and chemical adsorption of metal ions. The maximum adsorption capacity and the energy of adsorption per unit of adsorbate also can be predicted by this model. The D-R isotherm model is expressed where B D is relevant to the free energy of sorption per mole of the sorbate as coverage to the sorbent surface and q D is the D-R isotherm constant indicating the theoretical monolayer saturation capacity (mol g −1 ). The linear form of the equation can expressed as follows [32]: The mean free energy or apparent energy, E per molecule of adsorbate (for removing a molecule from its location in the sorption space to the infinity) is calculated as follows [33]:

Thermodynamics studies
The thermodynamic parameters including Gibbs free energy (∆G), the enthalpy change (∆H) and entropy change (∆S) are used to determine the sorption type of Pb(II) onto EFB and Fe 2 O 3 @EFB. ∆G is calculated by the following equation: where K is the adsorption equilibrium constant obtained from Langmuir model. Van't Hoff correlation describes the relation between K and the thermodynamic parameters of ∆H and ∆S in eq 15: ∆H and ∆S can be calculated from the slope and intercept of the ln K versus 1/T plot, respectively.

Adsorption kinetics
Pseudo-first-order model: Figure 1 shows the linearized plots of the pseudo-first order kinetic model of Pb(II), Cu(II), Zn(II), Ni(II) and Mn(II) cations onto raw EFB and magnetic biosorbent at room temperature for 500 ppm initial concentrations. The plots of pseudo-first order kinetic model for Pb(II) uptake with raw and magnetic nanosorbent of Cellulose and kapok are not shown. All showed similar trends of negative slopes and positive intercepts. The model constants, k 1 , the initial rate of sorption, h, and the normalized standard deviation Δq value which describe the sorption process and the  Kinetic model q e.exp (mg g −1 ) Metal ion Sorbent Intra-particle diffusion Pseudo-second-order Pseudo-first-order  During the initial contact time, the pseudo-first order model is approximately followed, but it deviates in the subsequent time indicating that the pseudo first order model could not predict the adsorption process accurately. The physisorption mechanism may therefore only partially control the sorption process.
Pseudo-Second-order model: Figure 2 shows the linearized plots of the pseudo-second-order kinetic model for Pb(II), Cu(II), Zn(II), Ni(II) and Mn(II) ions onto raw EFB and magnetic biosorbent (Fe 2 O 3 @EFB) at room temperature for 500 ppm initial concentrations. Figure 3 shows the plots of Pb(II) uptake onto raw and magnetic biosorbents of Cellulose and kapok. The R 2 > 0.999 values obtained for all plots for all initial concentrations (Table 1) suggest very good agreement between the experimental and the calculated adsorption amount, with the deviations in the lower range of 0.2% to 4.2%. The adsorption of metal ions onto all sorbents therefore follows pseudo-second-order kinetics very well which is similarly reported before for other metal ions sorption onto different sorbent systems [34][35][36]. The pseudo-second-order kinetic model is based on the theory that the rate controlling step of adsorption system is chemisorption which can predict the controlling behavior over the total range of contact time [37]. However, the major issue with chemisorption is the irreversible sorption. The overall rate is controlled by the ion exchange or sharing of valence electrons between the adsorbate and adsorbent. The physisorption may have some contributions but may not be rate-controlling. Intra-particle Diffusion: The adsorption process may be controlled by one or several steps including adsorption on the pore surface, pore diffusion, film or external diffusion and surface diffusion. There is a possibility of a slow intraparticle diffusion of the metal ion from the bulk of the external surface into the pores of the adsorbents which is described as the intra-particle diffusion model [38]. The adsorption rate is controlled by the adsorbate concentration, the size of the adsorbate molecule, the affinity of adsorbate and adsorbent, the pore-size distribution of the adsorbent, the diffusion coefficient of the adsorbate, and the degree of mixing [39]. Based on intra-particle diffusion model (Equation 7), if the plot of q t versus t 1/2 has a straight line passing through the origin, it can be expected that the mechanism contains the diffusion of the species. From figures 4 and 5, none of the plots show any lines passing through the origin and this may suggest the difference in the mass transfer rate between the initial and final stages of the adsorption. However, within the trend of a single ion sorption, multi-linearity representing three sorption stages can be discerned. The first stage shows steeper slope attributable to the fast rate of external surface adsorption. The second stage indicates the gradual adsorption stage, where intra-particle diffusion is a rate-limiting step. The third stage is where the intra-particle diffusion rate begins to decline because of the low concentrations of adsorbate in the solution.
The complete sorption process involves the fast-initial sorption rate which becomes slower nearing the equilibrium time. The fast-external surface sorption in the first stage proceeded for 10 to 25 mins signifying the low mass transfer resistance for the sorbate ions to occupy the large surface area of the sorbent. The sorption rate slowed down as observed in the second stage and plateaued in the last stage.   . 08 .

Isotherms study
Langmuir Isotherm: Based on Langmuir model, the sorption energy is invariable and self-governing and does not depend on surface loading [30]. The adsorption process happens on restricted sites without any interaction between sorbate species. The maximum adsorption takes place when the surface is covered with adsorbate monolayer. Although the Langmuir plots of Pb(II) are linear (data not shown) and the correlation coefficients are high (R 2 =0.80-0.99), the maximum expected adsorption capacity was determined as 149, 181, 303, 400, 416 and 312 mg/g for EFB, Fe 2 O 3 @EFB, Cellulose, Fe 2 O 3 @ CEL, RKF and Fe 2 O 3 @RKF at 25°C, respectively (Table 2) far higher than the maximum experimental value of 98.2 mg/g at the same condition. At higher temperatures, there could be simultaneous adsorption-desorption process taking place as high temperature energizes the solutes to adsorb and also to leave the active sites. The R L values (dimensionless constant separation factor) calculated are in the range of 0.29 to 0.87 for Pb(II) onto different sorbent at 25-65°C, indicating favorable adsorption and that high metal ion sorption is achievable at even low initial concentrations [40].   Freundlich Isotherm: Freundlich model incorporates the heterogeneity of the surface-active sites of extensive affinities. The exponential distribution and the energies of active sites are the main foundation of the model. The stronger binding sites are engaged for sorption first and the binding force decreases with the increase in degree of site occupation. The plot of ln q e against ln C e (Equation 11) provides a straight line with a slope of 1/n and an intercept of ln k f (Figure 6). Freundlich constants, k f and n are calculated where n establishes an indication of how favorable the adsorption process at different temperature is, and k f represents the adsorption or distribution coefficient of Pb(II) onto the adsorbent at equilibrium concentration ( Table  2). The value of n greater than 1 suggests that Pb(II) ions are favorably adsorbed on all studied sorbent [40] and the higher the value of n, the better the adsorption with a relatively strong bond formation between the adsorbent and the adsorbate [40].  [26]. Similarly, for raw sorbents, the k f values are in the range of 0.68-0.71 and 1.67-2.21 for EFB and RKF, respectively. The big difference between values for EFB sorbent and the values for RKF confirm the more than 40% higher adsorption efficiency of raw RKF than the EFB [26].
In other study, the availability of grafted carboxylic groups and pores may contribute towards heterogeneous active sites for Pb(II) ions attachment. The modified lignocellulosic sorbents such as Trametes versicolor, orange peel, cellulose-pulp-acrylate, sunflower stalks-amidoxime [2] have all been reported to be best described by Freundlich isotherms. Dubinin-Radushkevich Isotherm: Table 2 shows the constant parameters obtained from the linear D-R plots (plots not shown). The linearized D-R isotherm model is shown by eq. 13, and the apparent energy, E, of adsorption is shown in eq 14. The difference between q o from the Langmuir and q D from the derived D-R models is large and can be attributed to the different description of the maximum adsorption capacity for each model. In Langmuir model, q o signifies the maximum adsorption of metal ions at monolayer coverage, whereas q D in D-R model signifies the maximum metal ions adsorption within the total volume of adsorbent. In this study, the E value is in the range of 11.1-82.6 kJ mol −1 . In some sorbents, especially in magnetic biosorbents, the values are more than the range of adsorption reaction 8-16 kJ mol −1 . The mean adsorption energy, E, gives information about the physical and chemical adsorption [41]. The high E value suggests that physical sorption cannot have a big contribution in the sorption mechanism.
Based on the R 2 values of 0.82-0.999, the parameters of the Pb(II) ion sorption onto the three magnetic sorbents are best fitted to Freundlich than to Langmuir and D-R isotherms. The sorption process could therefore be based on the heterogeneous multilayer phenomenon as proposed by Freundlich. Table 3, summarizes all the constants and R 2 values obtained from the three isotherm models for the adsorption of copper, zink, nickel and manganese on EFB and Fe 2 O 3 @ EFB, at different temperatures (figures not shown). All metal ions sorption are also better described by Freundlich model as compared to Langmuir and D-R (especially for Cu(II)). The Langmuir exponent, R L , values for all metals are between 0 and 1, indicating that the adsorption of metal ions onto the investigated adsorbents are favourable under the conditions being studied. The Freundlich exponent 1/n is less than one also suggests a favorable sorption process. The heterogeneity of the surfaces or pores of the adsorbents play an essential role in the adsorption of the ions. The trends obtained from these plots are similar to that found for the adsorption of Pb(II) ions earlier except for EFB. Several studies have shown that the Freundlich model is the best to describe the adsorption of Cu(II), Zn(II) and Mn(II) ions onto pecan shell carbon [42], and raw and acid treated corncob biomass [36] and also from the tea-industry waste [43]. However, sorption of Mn(II) and Pb(II) ions on raw and oxalic acid modified maize husk follows Langmuir isotherm [44]. Also, the Langmuir-type isotherm model is more suitable to describe the sorption of Cd(II) from aqueous solutions onto the cetyltrimethylammonium bromide (CTAB)-treated adsorbent where the treated surface is suggested to be more homogenous and adsorption is accomplished via monolayer formation. Based on the maximum adsorption capacity, it can be concluded that Fe 2 O 3 @EFB shows higher sorption capacity for all ions than EFB. In the case of CEL and RKF, the magnetic sorbents also exhibited higher sorption capacity for Pb(II) ions. This can be attributed to the presence of a higher number of active sites.

Thermodynamics study
The thermodynamics characteristics of metal adsorption on both raw and magnetic biosorbents are shown in tables 4 and 5. The parameters of ΔH° and ΔS° are estimated from the slope and intercept, respectively, of the ln K d against 1/T plot. The thermodynamics equilibrium constants (K d ) are calculated from the ln(q e /C e ) against q e plot and extrapolating q e to zero [45]. Gibbs free energy, ΔG°, is calculated from equation 15. The values of the thermodynamic parameters for the adsorption of Pb(II) ions in our study are in good agreement with previous reports [46,47].  [48,49] while others have reported positive ΔH° for Mn(II) and Ni(II) [50,51]. The negative ΔH° value indicates the exothermic nature of the adsorption interactions where the adsorption capacity decreases with increasing temperature. It is due to the successive desorption of adsorbate species in the equilibrium mixture as a result of the deterioration of weak Van der Waals forces between the active sites on the sorbent and the adsorbate species. The increasing temperature therefore may decrease the capacity as the physical bonding between the adsorbate and the active sites of the adsorbent is destabilized [52].
The positive values of ΔH indicate the endothermic nature of metal ions sorption where heat is used to transfer the ions from aqueous onto the solid phase. Under transition metals group, Mn(II) (161 pm) and Ni(II) (149 pm) have larger atomic radii than Zn(II) (142 pm) and Cu(II) (145 pm). Pb(II) (154 pm) is from the Post-transition metal group having almost equivalent atomic radii but with larger atomic number. The smaller radii ion may require heat to enhance sorption efficiency. Increase in temperature should increase the diffusion rate of the adsorbate species across the external boundary layer into the pores of the adsorbent particle, reduce the viscosity [53], enhance the pore size distribution and increase the active surface sites proportionally [18]. As the pore sizes of the sorbents are varied, the conflicting ΔH° values as observed for Mn(II) and Ni(II) suggest that the larger atomic radii ions may have varied chances of penetration into the sorbent pores by either heat-driven or heat-releasing processes.    The thermodynamics characteristic of an adsorption system is very much governed by the particle size or physical shape of the adsorbent, the physical properties and the surface functional groups of the sorbent, and the nature of the sorbate. The transition metal ions should give up a large share of their hydration water before they could enter to the smaller pores [54]. Such water release from the divalent cations yields positive values of ΔS which indicates increase in the disorderliness of the system. The positive ΔS values also suggest the redistribution of energy between the adsorbate and the adsorbent [55]. The negative values of ΔS° in contrast is related to the decrease in the degree of freedom of the adsorbed species [18]. Before adsorption, the heavy metal ions near the adsorbent surface are more orderly than in the subsequent adsorbed state, and the ratio of free heavy metal ions to ions interacting with the adsorbent is higher than in the adsorbed state. Therefore, the distribution of rotational and translational energy between a small number of molecules will increase with an increase in adsorption. The randomness will subsequently increase at the solid-solution interface. However, the major limitation is that it does not address the irreversible sorption associated with the chemisorption process and the different constituents of the fibres in each biosobent system which are responsible for the different efficiency and degree of metal ions removal. These are beyond the scope of current study and is a subject for future research. The applicability of the developed magnetic sorbent system is currently being explored and tested with a mixture of heavy metals and a real wastewater, to evaluate the sorbents efficiency for heavy metal ion and oil remediation and for diesel desulphurization.

Conclusion
This study showed that the best adsorption of Pb(II) ions was achieved by the magnetic biosorbent based on cellulose and raw kapok fibres, followed by the EFB. The adsorption of metal ions onto the magnetic sorbents is well represented by the pseudo-second-order kinetic model. The chemi-sorption mechanism is the main controlling mechanism. A multi-linear trend of intra-particle diffusion model further suggests that the adsorption of all metal ions onto the raw and magnetic biosorbents is not entirely controlled only by the intra-particle diffusion. The heterogeneity of the adsorption active sites of extensive affinities is illustrated by the best fitness of Freundlich isotherm to the data. The calculated adsorption free energy (ΔG) suggests the feasibility of the adsorption process. The thermodynamics analyses prove that the adsorption onto the surface of raw and magnetic EFB biosorbent is spontaneous and endothermic in nature, except for Ni(II) and Mn(II) ions, and the differences are attributable to atomic radii, resistances at the solid-liquid interface, the pore sizes and the distribution of active sites.