The effect of contact time on the adsorption of Pb, Mn, and Cu in landfill leachate is shown in Figs. 1a and 1b. The adsorbent dosage was fixed at 1 g/100 mL (10 g L− 1) and the pH value of the fresh leachate was 5.1. The removal rate of the heavy metals experienced a drastic initial increase followed by a gradual rise to reach a plateau, which indicates equilibrium condition. Instant adsorption rate of heavy metals onto BC gradually declined to zero with the equilibrium point of adsorption lay between 150–200 min and 100–150 min for, respectively, PWB and CWB, suggesting that the contact time of 200 min and 150 min is sufficient to establish dynamic balance. The importance of contact time to provide sufficient contact between adsorbates and adsorbent surface has been emphasized by several authors [24, 26]. It can be inferred from Figs. 1a and 1b that the removal of Pb, Mn, and Cu was greater when PWB was used as adsorbent, compared to CWB. Moreover, longer period of contact time was required for the equilibrium state to be established when biochar with smaller particle size i.e. PWB was used, implying slower occupation of adsorption sites on the surface of PWB due to the greater specific surface provided by PWB relative to CWB. The highest removal rate of 87.96% by PWB was obtained for Pb.
As reaction time prolonged, repulsive forces between the metal ions adsorbed to biochar and those in the aqueous phase might be increased. In addition, unoccupied adsorption sites and therefore adsorption rate will be quickly declined until the establishment of dynamic balance in the system.The same observation was found for Ni uptake from aqueous solution by AC derived from sugar bagasse [26]. From the adsorption diffusion viewpoint, two distinct adsorption stages could be distinguished for the uptake of Pb, Mn, and Cu onto BC in landfill leachate; surface diffusion during which the mass transfer is rapid and physical processes control the adsorption, followed by intra-particle diffusion that is characterized by slow adsorption. Greater adsorption rate for heavy metals was observed for all the applied dosages of BC at initial stages of the experiment, that may be attributed to the higher availability of adsorption sites on BC surface which are rapidly occupied by the solutes in the leachate. When equilibrium is reached mass transfer from the leachate to the surface of BC was significantly restricted (Figs. 1a and 1b), which is consistent with those reported in the literature [21].
3.2. Effect of BC dosage on the adsorption of heavy metals in landfill leachate
BC dosage varied from 0.05 to 5 g/100 ml (0.5 to 50 g L− 1) at initial pH of 5.1, with the reaction times of 200 min and 150 min, respectively, for PWB and CWB. Results indicated that the removal rate of the heavy metals was significantly raised by 1.2, 1.4, and 1.6 times, respectively, for Pb, Mn, and Cu, when PWB content of the leachate increased from 0.5 to 5 g L− 1. Obtained results are consistent with the findings of Krishnan et al. (2011), where removal of Ni from aqueous phase increased by AC dosage [26]. The removal rate of Pb, Mn, and Cu did not change significantly as BC content exceeded 2 g/100 mL in leachate, suggesting the optimal dosage of 20 g L− 1 for both PWB and CWB to achieve the highest economical adsorption capacity for the heavy metals. Unsaturated adsorption sites may increase as BC dosage exceeds the optimum amount. The highest removal rate was obtained for Pb followed by Mn and Cu due to addition of PWB (Fig. 1c) and CWB (Fig. 1d).
Removal rate of Mn and Cu was comparable, with slightly higher elimination for Mn. Amount of Pb, Mn, and Cu adsorbed to each gram of BC reduced with rising adsorbent dosage, likely due to the availability of more adsorption sites on the surface of both PWB and CWB. Optimum AC dosage of 7 g/100 mL was found to effectively adsorb COD and NH3-N from landfill leachate [21], which is markedly higher than the optimum dosage of biochar obtained in this study. It might be attributed to the higher levels of COD and NH3-N in leachate compared to those of heavy metals in this study. Biochar dosage may also induce pH variation, which in turn affects adsorption of adsorbates in aqueous systems by changing the adsorbent surface charge and degree of ionization of adsorbates. Addition of high levels of BC to fresh leachate may increase pH and promote the formation of metal hydroxides. However, adverse effect of low pH on adsorption of Ni onto AC has been reported due to competence with hydrogen ions [27]. The influence of pH on adsorption of heavy metals on various adsorbents has been well documented [28].
3.3. Adsorption Kinetics
Batch kinetic experiments were carried out for the adsorption of Pb, Mn, and Cu onto PWB and CWB in landfill leachate. The kinetics for adsorption of heavy metals onto BC was simulated using two kinetic models: pseudo second-order and Elovich kinetic models. The experimental effectiveness is controlled by the adsorption kinetics. Adsorption kinetic models are typically used to investigate the adsorption mechanism and the potential rate of the processes such as mass transfer and chemical reactions [21].
3.3.1. Pseudo second-order kinetic model
The non-linear form of pseudo second-order model is represented as follow:
Where k2p is the second-order adsorption constant (g mg− 1 min− 1), qe is the amount of heavy metals adsorbed onto biochar when dynamic balance researched (mg g− 1), and qt is the amount of adsorbate adsorbed onto biochar at any time, t. In order to gain the linear form of the pseudo second-order kinetic model the following equation should be solved through integration:
If the boundary conditions of qt = 0 to qt = qt and t = 0 to t = t is applied, the model can be written as follows:
Plots of t/qt versus t for adsorption of Pb onto PWB and CWB are illustrated in Fig. 2. Similar graphs could be constructed using the obtained data for Mn and Cu, with the same trend as Pb. Figures 2a and 2b clearly illustrates higher adsorption capacity of PWB compared to CWB for the heavy metals. The pseudo second-order kinetic constants and the theoretical qe values using the pseudo second-order expression are given in Tables 1 for all the studied metals. Very high values of R2 (≥ 0.999) were found for the pseudo second-order kinetic model in all applied levels of PWB and CWB indicating an excellent linearity. Results showed an excellent agreement between the experimental data and the calculated adsorption capacity by the pseudo second-order kinetic model which is consistent with the literature, where heavy metals in an aqueous solution were removed by carbon nanotubes [5]. Error analysis indicated that deviation occurred by application of the pseudo second-order kinetic model is very small for all levels of BC, regardless of the biochar particle size. This supports the chemisorptions theory behind the pseudo second-order kinetic model for the heavy metals/BC system; however, evaluation of variation of adsorption energy using appropriate isotherms such as Temkin model could provide deeper insight into the nature of metal adsorption onto BC. It can be inferred from Table 1 that the adsorption equilibrium rate for the studied heavy metals, regardless of the BC size, has the following order: Pb > Cu > Mn. The applicability of pseudo second-order model to fit the experimental kinetics data was also reported for adsorption of heavy metals onto sewage sludge [14]. Predicted adsorption capacity decreased by increasing dosage of PWB and CWB. The adsorption process is mainly a surface phenomenon and increase in adsorption sites on the surface of an adsorbent at a constant adsorbate level could result in alleviated adsorption intensity.
3.3.2. Elovich kinetic model
The Elovich adsorption kinetic equation which was initially developed to describe chemisorption kinetics of gas onto solids [29], has recently gained increasing attention to describe kinetics of adsorption of adsorbates in aqueous phase onto adsorbents. The elovich kinetic model is expressed as follows:
Where α is the initial adsorption rate (mg g− 1 min− 1) and β is defined as desorption constant (g mg− 1) during any experiment [25]. Elovich differential equation can be solved assuming α βt > > 1 and by applying the boundary conditions of qt=0 at t = 0 and qt= qt at t = t [29]. Therefore, the linear form of the elovich equation can be presented as follows:
In order to study the adsorption kinetics using Elovich model a straight line of qt versus ln t should be plotted to be able to calculate the model constants of α and β from the slope and the intercept of the plot. For instance, Pb adsorption capacity of BC predicted by the Elovich kinetic model is shown in Fig. 3. Parameters of the Elovich kinetic model for adsorption of Pb, Mn and Cu onto PWB and CWB are presented in Table 2. Pretty high R2 and low SSE values obtained for the Elovich kinetic model suggesting that adsorption kinetics of the heavy metals onto BC in landfill leachate can be adequately represented by the Elovich kinetic model. However, higher values of R2 and lower values of SSE found for the pseudo second-order kinetic model compared to the Elovich kinetic expression in this study. Comparison of the kinetic data obtained in this study suggests pseudo second-order kinetic expression is the optimum kinetic expression to represent adsorption of Pb, Mn, and Cu onto BC in landfill leachate.
3.4. Modeling of adsorption isotherms
The equilibrium data were modeled using the Langmuir, non-linearized Freundlich, linearized Freundlich and Temkin isotherms in this study to predict adsorption capacity of PWB and CWB for heavy metals in landfill leachate. Experimental data versus the predicted adsorption of Pb, Mn and Cu onto BC in the leachate using different adsorption isotherms are shown in Fig. 4. Experimental results indicated that Pb could be adsorbed on BC to a higher degree than Mn and Cu. Adsorption of Mn on BC was comparable with that of Cu with slightly higher adsorption for Mn.
3.4.1. Langmuir isotherm
The Langmuir model which is an empirical isotherm assumes uniform energies of adsorption onto the adsorbent surface with no interaction between adsorbate molecules on adjacent sites. All adsorption is also assumed to occur through the same mechanism to form a layer with a thickness of one molecule on solid surface [15]. Once a site is occupied, no further adsorption can proceed at that site based on the Langmuir isotherm representing the surface saturation condition. Langmuir isotherm has been extensively used to evaluate adsorption capacity of a wide range of contaminants such as heavy metals, organic pollutants and dyes [30]. Langmuir model describes a homogeneous adsorption assuming that all the adsorption sites on the surface of a given adsorbent have equal solute affinity. It is also assumed that adsorption of solute at one site does not affect the adsorption at an adjacent site [31]. Therefore, the maximum adsorption capacity obtained by using the Langmuir isotherm is based on complete monolayer coverage of the surface of adsorbent. All adsorption is assumed to occur through the same mechanism. The non-linear expression of Langmuir isotherm model can be illustrated as follows:
where, b is adsorption equilibrium constant (L mg− 1) which is related to the apparent energy of adsorption, qm is the quantity of adsorbate required to form a single monolayer on unit mass of a given adsorbent (mg g− 1) and qe is the quantity of adsorbate adsorbed on unit mass of the adsorbent (mg g− 1) when the equilibrium concentration is Ce (mg L− 1). Langmuir model equation can be linearized to five different linear types. Details of the various linearized Langmuir expressions and the corresponding plots to determine Langmuir constants i.e. qm and b were presented in Table 3.
Values of the constants for different types of linearized Langmuir isotherm are presented in Table 4 for the adsorption of Pb, Mn and Cu onto BC. Results showed the best fitting parameters for the linearized Langmuir types 1 and 5 for PWB with the highest R2 among the applied linearized forms. Among the five different linearized forms of Langmuir isotherm equations, types 1 and 2 have been used more frequently in the literature [32]. Langmuir isotherm can be further analyzed and the favorable nature of adsorption of adsorbate onto adsorbent can be expressed through determination of the separation factor, RL, which is a dimensionless equilibrium parameter defined by the following equation:
Where C0 is the initial concentration of adsorbate in the bulk solution (mg L− 1) and b is the Langmuir model constant related to the free energy of adsorption (L mg− 1). The separation factor, RL, indicates the shape of the isotherm. Values of 0 < RL < 1 indicates favorable adsorption, whereas RL > 1 represents an unfavorable adsorption. In addition, RL = 0 represents irreversible adsorption, while the adsorption is linear if RL = 1 [33, 34]. The dimensionless separation factors calculated for adsorption of the heavy metals onto PWB were between zero to one that shows favorable adsorption, while the corresponding values for CWB were greater than 1 indicating an unfavorable adsorption (Table 4).
The values of R2 and RL obtained from Langmuir-1 expression indicate positive evidence that the adsorption of Pb, Mn, and Cu onto PWB follows the Langmuir isotherm. The fit of the measured data to the Langmuir model reveals the possibility of sorption of the heavy metals onto PWB through chemisorptions [35]. Negative values obtained for maximum adsorption capacity of CWB reveals that adsorption of Pb, Mn and Cu onto CWB in the leachate does not follow Langmuir isotherm, suggesting that heavy metals do not follow the monolayer adsorption on the surface of CWB. In another study, negative values for adsorption capacity of dyes onto AC was obtained [24], which is practically and experimentally impossible. The highest value of the Langmuir constant b, 3.22 L mg− 1, was obtained for Pb adsorption onto PWB (Table 4) exhibiting greater affinity of Pb to the surface of PWB compared to Mn and Cu in landfill leachate.
Maximum adsorption capacities determined using different forms of Langmuir expressions are slightly higher than the experimental adsorbed amounts of Pb onto PWB. The same trend was found for Mn and Cu, to a higher degree compared with Pb. It seems that the monolayer adsorption capacity of Pb onto PWB provided a better fit to the experimental data compared to Mn and Cu. Table 4 indicates that the Langmuir constants obtained from different linear expressions are divergent, implying that transformation of non-linear model to linear forms may alter the error structure of a given isotherm. Smaller values of determination coefficients were gained in types 3 and 4.
Lower values of the SSE were obtained for Langmuir-4 and Langmuir-1 expressions, while Langmuir-5 expression give the highest SSE in most cases. Overally, the lowest value of the SSE will be generated for the Langmuir-1 expression compared to other linear forms, if the BC dosage of 0.05 mg g− 1 is overlooked. For instance, that 83% of the calculated SSE was attributed to the deviation occurred at dose of 0.05 mg g− 1, when the experimental adsorption of Cu onto CWB were modeled using the Langmuir-1 expression. Experimental results showed that adsorbed amounts of the heavy metals on BC was clearly increased with rising adsorbent dosage. Figure 4 compares the simulated isotherm curves and measured data for adsorption of Pb, Mn and Cu onto BC based on Langmuir-Type 1 expression. Results indicated that Langmuir isotherm is unable to describe the equilibrium data perfectly in most cases; however, Langmuir-1 expression could better simulate equilibrium data for adsorption of heavy metals on PWB in the leachate, compared to the other linearized forms of Langmuir model. The error structure varied upon linearization of non-linear Langmuir isotherm equation. Results indicated that the values of R2, RL and SSE are required to reliably determine the most appropriate form of the linearized type of the Langmuir model to fit the experimental adsorption data.
3.4.2. Linearized and non-linearized Freundlich isotherms
The Freundlich isotherm has been widely applied to characterize the adsorption of organic and inorganic pollutants using various adsorbents [36]. Freundlich isotherm constants found through plotting ln qe vs ln Ce are given in Table 5. The ratio of the amount of adsorbate adsorbed onto a given mass of adsorbent to the adsorbate concentration in the solution using the Freundlich model is represented by the following equation:
where, Ce is the equilibrium concentration (mg L− 1), qe is the amount adsorbed to solid phase (mg g− 1), Kf is the Freundlich constant representing the relative adsorption intensity of the adsorbent related to the bonding energy, and n is the heterogeneity factor indicating the deviation from linearity of adsorption which is commonly known as Freundlich coefficient. Linearized form of the Freundlich isotherm can be used to evaluate the adsorption data and determine the Freundlich model constants as follows:
The corresponding coefficients of correlation for Freundlich model were found to be high for adsorption of Pb, Mn, and Cu onto PWB and CWB (≥ 0.99) indicating a good linearity; however, the values of Freundlich coefficient, n, did not fall within the favorable range for CWB. Favorability of the Freundlich isotherm is generally indicated by the magnitude of the exponent n. The values of n ranging from 2 to 10 is stated to represent a good fit, values ranging from 1 to 2 indicates relatively difficult adsorption, and less than 1 shows poor adsorption characteristics [37]. Acceptable adsorption characterized by values of n between 1 and 10 has also been reported in the literature [33, 38]. The highest value of the Freundlich coefficient was obtained for adsorption of Pb onto PWB (n = 1.992) (Table 5). Higher values of Kf were found for adsorption of the heavy metals onto PWB indicating the greater relative adsorption capacity of PWB compared to CWB to eliminate Pb, Mn, and Cu from the landfill leachate. Results show that linearized Freundlich and Langmuir models could not adequately describe adsorption of Pb, Mn, and Cu onto CWB in landfill leachate. In order to find the Freundlich maximum adsorption capacity, qm, it is necessary to keep the initial concentration of adsorbate constant and use the variable dosage of adsorbent; that means ln qm is the extrapolated value of ln q for C = C0. Thus, the Freundlich maximum adsorption capacity can be described as follows:
Where, qm is the Freundlich maximum adsorption capacity (mg g− 1), KF is the Freundlich constant, and C0 is the initial concentration of adsorbate in the bulk solution (mg L− 1). The calculated maximum adsorption capacity of PWB for Pb, Mn, and Cu using the Freundlich isotherm were greater than the corresponding values for CWB, respectively, by a factor of 2.3, 5.3, and 1.4. Comparing the maximum adsorption capacity produced by application of the Freundlich and Langmuir-1 models reveals that predicted qmax using the Freundlich isotherm is markedly lower than the corresponding values obtained by the Langmuir-1 expression for PWB.
It can be inferred from the Figs. 5a, 5b and 5c that the predicted adsorption capacity of PWB and CWB using the linearized Freundlich isotherm is drastically underestimated for Pb, Mn and Cu. Error analysis also indicates high values of SSE for linearized Freundlich isotherm. The SSE values found for the Freundlich model are significantly higher than the obtained values for the Langmuir model. Overally, results indicated no adequate agreement between the predicted and measured adsorption data, implying the lack of validity of the linearized Freundlich isotherm to model the adsorption of the heavy metals onto BC in the leachate. Both linear and non-linear fitting of the experimental data to the Freundlich model yields high coefficients of determination in most cases but the error analysis presented a great difference between linear and non-linear fitting. The value of SSE calculated for non-linear fitting was much lower than that obtained for linear fitting, as it could also be realized by comparing experimental and modeled data presented in Figs. 5d, 5e and 5 f. Results indicate that non-linear fitting of the measured data to the Freundlich isotherm could provide significantly more robust prediction compared to the linear fitting. However, the obtained values for the constant n was less than 1 when CWB was used as an adsorbent both for linear and non-linear fitting of data indicating unfavorable adsorption of Pb, Mn, and Cu onto CWB. Results indicated much higher values of qm when non-linearized regression was applied. In other words, linearization of the Freundlich isotherm caused underestimation of qm, while fitting the measured data to non-linearized form of the Freundlich model depicted greater affinity between the experimental and predicted data. Application of non-linear Freundlich isotherm produced more valid data with significantly higher values of determination coefficient as well as much smaller SSE. Overally, results indicated that linearization of the Freundlich isotherm to fit the experimental data may generate higher errors and significantly deviate the predicted adsorption capacity of a given adsorbent from the experimental data.
3.4.3. Temkin Isotherm
The Temkin isotherm is based on the assumption that the heat of adsorption of all the molecules in the layer declines as adsorbent surface coverage increases due to adsorbate-adsorbate repulsions. Fall in the heat of adsorption is considered to be linear for Temkin isotherm rather than logarithmic as implied in the Freundlich isotherm. Adsorption of adsorbate onto adsorbent is also characterized by a unisonous distribution of binding energies up to ca. maximum binding energy [28]. Temkin isotherm equation contains a factor that reflects the adsorbent-adsorbate interactions. The nonlinear form of Tempkin isotherm is represented by the following equation:
Where, T is the absolute temperature in Kelvin (K), R is the universal gas constant, 8.314 J mol− 1 K− 1, bT is the constant related to the heat of adsorption indicating the variation of adsorption energy (J mol− 1), and KT is the Temkin equilibrium binding constant (L g− 1) corresponding to the maximum binding energy. The dimensionless term (RT)/bT can be substituted by BT, thus Temkin isotherm equation can be linearized as given by the following equation:
The obtained parameters of Temkin model are given in Table 6. Values of R2 found using the linear transformation of the Temkin equation, were comparable were the non-linearized Freundlich model. The variation of adsorption energy, bT, was positive for all the studied heavy metals implying that the adsorption of Pb, Mn and Cu onto BC is an exothermic reaction (21.73 KJmol− 1). Salam et al. (2013) reported that the physical adsorption is characterized by adsorption energy in the range of 5–40 KJmol− 1 [39]. Physiosorption may occur as a result of weak forces of Van der Waals between the adsorbates and adsorbents [30]. Higher amounts of variation of energy obtained using the Temkin isotherm for adsorption of Pb, Mn, and Cu onto PWB relative to those obtained for CWB indicates greater capacity of PWB to adsorb heavy metals in landfill leachate. It should be noticed that the Temkin isotherm does not provide any estimation of the maximum adsorption capacity of a given adsorbent, qm. In spite of the non-linear Langmuir equation, if the equilibrium concentration is increased, the adsorption capacity of the original Temkin equation, qe, does not converge to any limiting value. Figure 6 indicates that the predicted equilibrium curves using Temkin model are very close to those obtained experimentally; however, deviation of the predicted adsorption using the Temkin model slightly increased when lower dosage of BC was applied. Error analysis indicates smaller values of the SSE relative to the Langmuir-1 and linear Freundlich isotherms; however, the non-linear Freundlich model exhibited the lowest values of SSE for adsorption of Pb, Mn and Cu onto biochar in this study. Based on the obtained results it seems that Temkin model can adequately describe the adsorption of the heavy metals onto PWB and CWB in the leachate. Adsorption of Pb, Mn and Cu onto BC in landfill leachate was adequately represented by the applied isotherm models, except the linear Freundlich model implying that adsorption of heavy metals onto BC may be controlled by surface diffusion and pore diffusion simultaneously as well as adsorption at an active preoccupied site. Overally, results indicated promising removal of the heavy metals from landfill leachate using biochar, which could be well described by non-linearized Freundlich and Temkin models.