# Valorization of Toxic WeedLantana camara L. Biomass for Adsorptive Removal of Lead

Authors: Vipin Kumar Saini; Surindra Suthar; Chaudhari Karmveer; Kapil Kumar
Journal: Journal of Chemistry
 (2017)

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## Abstract

Valorization ofLantana camara L., which is a recognized invasive plant, as a potential source of activated carbon is proposed in this study. Its stem and leaf have been utilized for the preparation of activated carbon (ACL and ACS) by following acid-impregnation technique, followed by thermal treatment. The developed activated carbon samples were characterized for their structural and surface related properties by low-temperature nitrogen adsorption isotherm, SEM techniques, and pHPZC method. The samples show reasonable high surface area and pore volume; nonetheless, these properties are higher in case of ACL as compraed to ACS. Both of these samples developed negative charge on their surface due to acid treatment that resulted in an increase in adsorption at pH > 5. The batch adsorption studies on these samples shows the Pb(II) ion adsorption capacities of ACL and ACS were 36.01 and 32.24 mg·g−1, respectively, at 25°C. The kinetics of adsorption with both the sample systems follow the pseudo-second-order model, whereas the experimental equilibrium isotherm data of ACL and ACS were explained by Freundlich and Langmuir models, respectively. For these samples, the HCl shows maximum desorption with which the recycling test on these samples shows that ACS has better recycling potential over ACL samples.


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## Body

## 1. Introduction

Lantana camara is a flowering plant that belongs to Verbenaceae family and is often planted in gardens. It is native to Central and South America and spread to around more than 40 different countries [1], where now it has become an invasive species [2]. It was brought by Dutch explorers to Europe from America, where it was cultivated widely and soon it spread into Asia and other countries, where it became the world’s most notorious weed. It grows impassable thickets which suppress the growth of native species. Its growth often competes with, suppresses, and crowds out more desirable species, which leads to a loss of plant diversity, in affecting the area. Other problems with this species include its toxicity to livestock and if it invades agricultural land it may cause a decrease in productivity [3]. In India, Australia, and South Africa, it is widespread occupying millions of hectares of land [1]. There is a quest if we can fight the spread of invasive species or we need to develop strategies for their adaptive management.According to literature, its spread is being controlled by several methods on a large scale, including mechanical (stickraking, bulldozing, plowing, and grubbing), chemical (using fluroxypyr and glyphosate), and biological methods (using different bug, beets, and seed-feeding fly) [4]. Use of this plant for a pollution abatement technique would be a most cost-effective management tool, in its control. One of the possible uses of converting this biomass into applicable materials is shown in [2]. One way of its valorization could be its use in environmental applications like wastewater treatment.Among various technologies to treat industrial wastewater, the adsorption is an established technique for its efficiency and cost of operation. In adsorption technique, an extremely porous material (adsorbent) is used, which selectively adsorb the impurities from the aqueous phase by noncovalent bonding (H-bond, electrostatic bonding, and coordination bonding) [5]. The key challenge in the use of adsorption technique for water treatment applications is the cost of adsorbent. Activated carbon is a well-known adsorbent particularly due to its microporous structure and high surface area. It is prepared from a variety of carbonaceous sources like nutshells, coconut husk, peat, coir, lignite, coal, and wood. Physical or chemical activation processes are generally used for its development. The cost of activated carbon depends upon the choice of the process as well as the price of starting carbonaceous material (raw material) [5, 6]. So far, numerous plant materials and agricultural, industrial wastes have been explored for the development of activated carbon and their application in water treatment. But, surprisingly, there were no such studies on invasive weeds in general andLantana camara in particular. Only recently have few researchers started to investigate its use as a source of activated carbon and study its potential for removal of water pollutants. But these studies show limited adsorption capacity and are limited to dyes [7] and phenol [8]. In this context, it is apparent that if processed and activated suitably, thisLantana camara L. can become a potential source of activated carbon, and this can valorize its biomass for adsorptive removal of water pollutants.Like many other heavy metals, lead is also toxic and known for bioaccumulation that affects various body systems and is predominantly unsafe to young children [9]. It comes into water through the combustion of fossil fuels and the smelting of sulfide ore and into lakes and streams by acid mine drainage. Process industries, such as battery manufacturing and metal plating and finishing, are also a prime source of lead pollution [10]. Lead accumulates mainly in bones, brain, kidney, and muscles and may cause many serious disorders like anemia, kidney disease, nervous disorders, and sickness and even death. There is no known level of lead exposure that is considered safe. Current EPA drinking water standard for lead is 0.05 ppm, but a level of 0.02 ppm has been proposed and is under review [11].In this study, leaves and stem ofLantana camara L. were used to prepare activated carbon by chemical activation method. The developed carbon was characterized by its structural and surface properties. The adoptions potentials of both the prepared materials were studied compared with selective adsorption of lead from aqueous solutions. The isotherm and kinetic modeling were used to explore adsorption behavior of these materials. Sustainability of optimized material in adsorption application was investigated in the light of their reusability in different adsorption cycle. To the best of our knowledge, this is the first study where an invasive weed likeLantana camara L. has been used as a precursor for activated carbon and used for adsorptive removal of pollutants.


## 2. Experimental

### 2.1. Materials

All chemicals used in this work were of analytical grade and were purchased from Merck (India). The solutions were prepared by using deionized water. Analytical grade lead nitrate (Pb(NO3)2), 99% pure, was used to prepare a lead solution. All the experiments were conducted at a constant temperature of 25±0.1°C unless otherwise specified.


### 2.2. Adsorbent Preparation

The leaves and stems samples ofLantana camarawere collected locally, from the premises of Doon University, Dehradun. To remove dirt particles from leaves and stems, it was washed several times with tap water and then in the end with double distilled water. The washed samples were air dried, followed by drying in a hot air oven for 24 hours at 80°C. The dried samples were shredded and then crushed to powdered form. For chemical activation, the method was adopted from literature [12]. In this method, the dried powders of sample were mixed with concentrated H2SO4 (Lantana leaves or stem: H2SO4 ratio; 1 : 1.5 w/v) and were kept at 200°C for 24 h. The chemically burned (carbonized) samples were then washed several times with distilled water to remove any free acid and were then soaked overnight in 1% sodium bicarbonate solution to remove any residual acid from pores. The material then was again washed twice with distilled water and dried in hot air oven at 105°C. The dried samples were then finely ground and sieved to get a particle size of 150 μm. The as-prepared samples of activated carbon from leaves and stem were labeled as ACL and ACS, respectively, and stored in desiccators until required.


### 2.3. Adsorbent Characterization

The morphological structure of the prepared carbon samples was observed by means of scanning electron microscopy (SEM) using a ZEISS EVO Series Microscope EVO 50. BET surface areas of samples were measured by liquid nitrogen adsorption method at 77 K using Micromeritics ASAP 2020. To characterize the surface charge of adsorbent, the experiment of the point of zero-chargepHzpc was carried out. The methodology for determination of pHzpc was adopted from an earlier study [13]. For this purpose, 0.025 g of adsorbent sample was kept in contact with 25 mL of a solution under 11 different pH conditions (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12) adjusted with solutions of 0.1 M NaOH or HNO3. The samples were kept stirring on a water bath at 25°C. After this step, the pH of each solution was measured and a plot of the initial pH versus the final pH was obtained. From this plot, the pH at which the values of initial and final pH are found identical is testified as pHPZC, the point of zero charge.


### 2.4. Adsorption Studies

Several parameters individually influence the adsorption properties of a given adsorbent. It is, therefore, essential to study the variation in the amount of adsorption as a function of the different parameter, like time, pH, temperature, and adsorbate (lead ion in the present case) concentration. The effect of pH on Pb(II) ion concentrations in solutions without adsorbent was also examined so as to evaluate the attribution of precipitation to the sorption process. Thereafter the % precipitation was deducted from total removal present to calculate the correct % adsorption amount. The adsorption studies were performed in the form of batch experiments. The samples obtained from batch adsorption experiments were filtered through Millipore SLHN033NB Millex HN Syringe Filter with Nylon Membrane (0.45μm) and analyzed by iCE™ 3300 AAS Atomic Absorption Spectrometer. The adsorbed amount was calculated with the following mass balance equation, where qe is the amount of adsorption (mg·g−1), C0 and Ce are the initial and equilibrium concentrations (mg·L−1), m denotes the mass (g) of adsorbent, and V is volume (mL) of adsorbate solution.(1)qe=C0-CeVm×1000.The equilibrium time of adsorption was observed with both the adsorbents. For this, 2.5 g of sample was added to 500 mL lead solution 200 mg·L−1 in a conical flask. The solution was stirred with a magnetic stirrer in a water bath at 25°C. Periodically, the aliquots of 3 mL were sampled from this flask, up to 4 h. The effect of pH on the adsorption was studied by adjusting the pH of the lead solution from 2 to 12, using 0.1 M NaOH or HCl solutions. To study the effect of temperature on adsorption the batch adsorption experiments on two temperatures 25 and 45°C were carried out.


### 2.5. Adsorption Isotherms

The mechanism of adsorption in terms of adsorbate-adsorbent interaction and maximum adsorption capacity can be explored with the help of adsorption isotherms. These isotherms are characterized by certain constants and describe the mathematical relationship between the amount of adsorbate adsorbed per unit mass of adsorbent and the equilibrium concentration of adsorbate in the solution. For this study, Pb(II) solutions (each 100 mL) of different concentration ranging from 50 to 500 mg·L−1 were stirred with 0.5 g of adsorbents until equilibrium adsorption time, after which the samples were collected, filtered, and analyzed by AAS to determine Ce and qe. To observe an adsorption isotherm for a given adsorbent-adsorbate system, qe are plotted as a function of Ce. Then different mathematical models of adsorption were applied to these isotherms and compared for better fitting [14]. In this study, nonlinear models of Langmuir (see (2)) and Freundlich (see (3)) were applied.(2)qe=qmax·b·Ce1+b·Ce,(3)qe=Kf·Ce1/n.In these equations,qmax and “b” are the Langmuir constants that denote maximum adsorption potential and equilibrium constant. Similarly, Kf and “n” are the Freundlich constant pertaining to the adsorption capacity and adsorption intensity, respectively.


### 2.6. Adsorption Kinetics

The adsorption kinetics were investigated with the help of contact time data. This data shows the progress of adsorption (mg·g−1) with respect to contact time, t (min). This kinetic data was then fitted to linear models of the pseudo-first-order (see (4)), pseudo-second-order (see (5)), and intraparticle diffusion (see (6)) models [15, 16]. The linear forms of these equations are expressed as follows:(4)log⁡qe-q=log⁡qe-k12.303t,(5)tq=1k2qe2+1qet,(6)q=kidt0.5+C,where q is the amount of adsorption at any time (t, min), k1 (min−1) is the pseudo-first-order adsorption rate constant, k2 (g·mg−1·min−1) is the pseudo-second-order adsorption rate constant, kid (mg·g−1·min−1/2) is the intraparticle diffusion rate constant, and C (mg·g−1) is a constant in the intraparticle diffusion model that reflects the significance of the boundary layer on mass transfer effect.


### 2.7. Evaluation of Desorption Using Different Desorbing Solvents

Desorption of adsorbed metal from the surface of adsorbent is necessary for the sake of recovery of metal as well as reuse of adsorbent. For this purpose, different desorbent solutions were tested. In this experiment, the assay was prepared in two steps. In the first step, 0.5 g of activated carbon was stirred with 100 mL of 200 mg·L−1 Pb(II) solution at 25°C up to equilibrium time. In the end, the AC samples were collected by filtration on a glass filter, washed with distilled water, and placed in an oven for 6 h at 60°C. The filtrate was analyzed to observe Ce. In the next step, the dry AC samples were placed in contact with 100 mL of different solution independently, like 0.1 M HNO3, HCl, H3PO4, NaCl, and distilled water for 6 h on a magnetic stirrer in a water bath at 25°C. The liquid phase was filtered through membrane filters and analyzed for desorbed Pb(II) ion concentration. The desorbed percentage was determined according to (7). The solution which achieves the maximum percentage of Pb(II) desorption from the loaded adsorbent was identified and used in successive adsorbent reuse test.(7)% desorbed=amount desorbedamount adsorbed×100.


### 2.8. Adsorbent Reuse Test

The reusability is critical for the cost-effectiveness of a new adsorbent [27]. The reuse assay was performed in cycles, starting with the adsorption and ending with the desorption of the Pb(II) ions using identified desorbing solvent. After each cycle, the mass of AC samples was washed with distilled water and dried in an oven at 80°C for 2 h. Four cycles were conducted with the same mass of AC samples.


## 2.1. Materials

All chemicals used in this work were of analytical grade and were purchased from Merck (India). The solutions were prepared by using deionized water. Analytical grade lead nitrate (Pb(NO3)2), 99% pure, was used to prepare a lead solution. All the experiments were conducted at a constant temperature of 25±0.1°C unless otherwise specified.


## 2.2. Adsorbent Preparation

The leaves and stems samples ofLantana camarawere collected locally, from the premises of Doon University, Dehradun. To remove dirt particles from leaves and stems, it was washed several times with tap water and then in the end with double distilled water. The washed samples were air dried, followed by drying in a hot air oven for 24 hours at 80°C. The dried samples were shredded and then crushed to powdered form. For chemical activation, the method was adopted from literature [12]. In this method, the dried powders of sample were mixed with concentrated H2SO4 (Lantana leaves or stem: H2SO4 ratio; 1 : 1.5 w/v) and were kept at 200°C for 24 h. The chemically burned (carbonized) samples were then washed several times with distilled water to remove any free acid and were then soaked overnight in 1% sodium bicarbonate solution to remove any residual acid from pores. The material then was again washed twice with distilled water and dried in hot air oven at 105°C. The dried samples were then finely ground and sieved to get a particle size of 150 μm. The as-prepared samples of activated carbon from leaves and stem were labeled as ACL and ACS, respectively, and stored in desiccators until required.


## 2.3. Adsorbent Characterization

The morphological structure of the prepared carbon samples was observed by means of scanning electron microscopy (SEM) using a ZEISS EVO Series Microscope EVO 50. BET surface areas of samples were measured by liquid nitrogen adsorption method at 77 K using Micromeritics ASAP 2020. To characterize the surface charge of adsorbent, the experiment of the point of zero-chargepHzpc was carried out. The methodology for determination of pHzpc was adopted from an earlier study [13]. For this purpose, 0.025 g of adsorbent sample was kept in contact with 25 mL of a solution under 11 different pH conditions (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12) adjusted with solutions of 0.1 M NaOH or HNO3. The samples were kept stirring on a water bath at 25°C. After this step, the pH of each solution was measured and a plot of the initial pH versus the final pH was obtained. From this plot, the pH at which the values of initial and final pH are found identical is testified as pHPZC, the point of zero charge.


## 2.4. Adsorption Studies

Several parameters individually influence the adsorption properties of a given adsorbent. It is, therefore, essential to study the variation in the amount of adsorption as a function of the different parameter, like time, pH, temperature, and adsorbate (lead ion in the present case) concentration. The effect of pH on Pb(II) ion concentrations in solutions without adsorbent was also examined so as to evaluate the attribution of precipitation to the sorption process. Thereafter the % precipitation was deducted from total removal present to calculate the correct % adsorption amount. The adsorption studies were performed in the form of batch experiments. The samples obtained from batch adsorption experiments were filtered through Millipore SLHN033NB Millex HN Syringe Filter with Nylon Membrane (0.45μm) and analyzed by iCE™ 3300 AAS Atomic Absorption Spectrometer. The adsorbed amount was calculated with the following mass balance equation, where qe is the amount of adsorption (mg·g−1), C0 and Ce are the initial and equilibrium concentrations (mg·L−1), m denotes the mass (g) of adsorbent, and V is volume (mL) of adsorbate solution.(1)qe=C0-CeVm×1000.The equilibrium time of adsorption was observed with both the adsorbents. For this, 2.5 g of sample was added to 500 mL lead solution 200 mg·L−1 in a conical flask. The solution was stirred with a magnetic stirrer in a water bath at 25°C. Periodically, the aliquots of 3 mL were sampled from this flask, up to 4 h. The effect of pH on the adsorption was studied by adjusting the pH of the lead solution from 2 to 12, using 0.1 M NaOH or HCl solutions. To study the effect of temperature on adsorption the batch adsorption experiments on two temperatures 25 and 45°C were carried out.


## 2.5. Adsorption Isotherms

The mechanism of adsorption in terms of adsorbate-adsorbent interaction and maximum adsorption capacity can be explored with the help of adsorption isotherms. These isotherms are characterized by certain constants and describe the mathematical relationship between the amount of adsorbate adsorbed per unit mass of adsorbent and the equilibrium concentration of adsorbate in the solution. For this study, Pb(II) solutions (each 100 mL) of different concentration ranging from 50 to 500 mg·L−1 were stirred with 0.5 g of adsorbents until equilibrium adsorption time, after which the samples were collected, filtered, and analyzed by AAS to determine Ce and qe. To observe an adsorption isotherm for a given adsorbent-adsorbate system, qe are plotted as a function of Ce. Then different mathematical models of adsorption were applied to these isotherms and compared for better fitting [14]. In this study, nonlinear models of Langmuir (see (2)) and Freundlich (see (3)) were applied.(2)qe=qmax·b·Ce1+b·Ce,(3)qe=Kf·Ce1/n.In these equations,qmax and “b” are the Langmuir constants that denote maximum adsorption potential and equilibrium constant. Similarly, Kf and “n” are the Freundlich constant pertaining to the adsorption capacity and adsorption intensity, respectively.


## 2.6. Adsorption Kinetics

The adsorption kinetics were investigated with the help of contact time data. This data shows the progress of adsorption (mg·g−1) with respect to contact time, t (min). This kinetic data was then fitted to linear models of the pseudo-first-order (see (4)), pseudo-second-order (see (5)), and intraparticle diffusion (see (6)) models [15, 16]. The linear forms of these equations are expressed as follows:(4)log⁡qe-q=log⁡qe-k12.303t,(5)tq=1k2qe2+1qet,(6)q=kidt0.5+C,where q is the amount of adsorption at any time (t, min), k1 (min−1) is the pseudo-first-order adsorption rate constant, k2 (g·mg−1·min−1) is the pseudo-second-order adsorption rate constant, kid (mg·g−1·min−1/2) is the intraparticle diffusion rate constant, and C (mg·g−1) is a constant in the intraparticle diffusion model that reflects the significance of the boundary layer on mass transfer effect.


## 2.7. Evaluation of Desorption Using Different Desorbing Solvents

Desorption of adsorbed metal from the surface of adsorbent is necessary for the sake of recovery of metal as well as reuse of adsorbent. For this purpose, different desorbent solutions were tested. In this experiment, the assay was prepared in two steps. In the first step, 0.5 g of activated carbon was stirred with 100 mL of 200 mg·L−1 Pb(II) solution at 25°C up to equilibrium time. In the end, the AC samples were collected by filtration on a glass filter, washed with distilled water, and placed in an oven for 6 h at 60°C. The filtrate was analyzed to observe Ce. In the next step, the dry AC samples were placed in contact with 100 mL of different solution independently, like 0.1 M HNO3, HCl, H3PO4, NaCl, and distilled water for 6 h on a magnetic stirrer in a water bath at 25°C. The liquid phase was filtered through membrane filters and analyzed for desorbed Pb(II) ion concentration. The desorbed percentage was determined according to (7). The solution which achieves the maximum percentage of Pb(II) desorption from the loaded adsorbent was identified and used in successive adsorbent reuse test.(7)% desorbed=amount desorbedamount adsorbed×100.


## 2.8. Adsorbent Reuse Test

The reusability is critical for the cost-effectiveness of a new adsorbent [27]. The reuse assay was performed in cycles, starting with the adsorption and ending with the desorption of the Pb(II) ions using identified desorbing solvent. After each cycle, the mass of AC samples was washed with distilled water and dried in an oven at 80°C for 2 h. Four cycles were conducted with the same mass of AC samples.


## 3. Results and Discussions

### 3.1. Textural and Structural Characterization

Both the samples of prepared activated carbon were characterized for their surface and other adsorption related physicochemical properties. Porosity and surface area of prepared activated carbon samples were assessed by nitrogen adsorption at −196°C (Figure1). The isotherm of activated carbon prepared from leaf (ACL) as well as stem (ACS) shows similar shape, which is of type I and slightly type IV with H1 loop, which are the characteristics of micro- and mesoporous materials [28]. Both the isotherms have slow condensation step at a relative pressure (p/p0 = 0.8–0.99) which corresponds to the capillary condensation of N2 within uniform mesopores. These results show the essential micro- and mesoporous nature of the prepared activated carbon samples. However, a decrease in adsorption amount in ACS sample is noted, as compared to ACL sample. From N2 adsorption data the specific surface area, ABET, was determined through BET model (within p/p0 0.05–0.15) [29]; likewise the micropore volume Vmicro and total pore volume Vtotal of the materials are listed in Table 1. The anatomical differences in leaves and stem give rise to a change in their structural composition. The same difference has been translated into their surface area and pore volume properties after activation. The specific surface areas of ACL and ACS are 634 and 523 m2/g, respectively. It is evident that chemical activation has produced large numbers of new pores in the samples by continuous devolatilization of the char and carbon burn-off. The dried leaves contain spongy mesophyll as compared to cortex and pith in the stem [30]. The total pore volume of ACL is higher compared to ACS; both the activated carbon samples are microporous in nature which is confirmed by fraction of their micropore volume with respect to their total pore volume.Table 1
The surface properties of prepared activated carbon samples obtained from low-temperature nitrogen adsorption isotherm data.
Sample Specific Surface areaABET Total pore volumeVtotal Micropore volumeVμ m2/g cm3/g cm3/g ACL 634 0.31 0.22 ACS 523 0.26 0.19Figure 1
Low-temperature nitrogen adsorption isotherms, at −196°C, obtained from ACL and ACS samples.SEM technique has been used to observe the change in samples morphology, before and after the treatment. The changes can be observed in Figure2, where SEM images of raw materials (Lantana leaf and stem dust) are compared with, respectively, activated carbons (ACL and ACS). The surface of leaf sample seems uniform before activation and after activation it shows emergence of porous structure on the surface. Likewise, the stem sample surface also shows variation before and after activation; however, this variation is not as noticeable as in the case of leaves sample. It is likely due to the variation in the biochemical composition of leaves and stem [31]. In brief, it is evident from the SEM images that the surface of raw materials gets changed after acid treatment, though the extent of change is different for each sample.Figure 2
SEM images of different magnification ofL. camara (stem and leaves) samples before and after acidic treatment.
(a) (b) (c) (d)In the chemical as well as physical activation method, the variation in original chemical composition resulted in the difference in surface functionality, because different compounds present in the surface and matrix of the sample give rise to different charge group (cationic or anionic) on the surface after carbonization and activation [32]. To observe this phenomenon in the context of the present samples pHPZC analysis has been carried out and the results are presented in Figure 3. It shows that pHPZC is approximately 5.0 for both the samples, which means at pH > 5.0 the activated carbons would have predominantly a negative charge at the surface while below this value the surface is positively charged. Typically, the pH at the point of zero charges on activated carbon is approximately 7 [33, 34]. However, this was not observed from the AC samples prepared in the present study. The value of 5.0 can be explained by acid treatment to raw material which was used to prepare activated carbon. The H+ ions present on the surface after treatment will be released into the solution which resulted in lowering of pH. The adsorption of cations, such as metal ions, is favored at pH > pHPZC while the adsorption of anions is favored at pH < pHPZC [35, 36]. Thus, the lead adsorption process should be carried out at pH equal to or greater than 5.0, to identify the optimal pH range.Figure 3
Determination ofpHZPC of ACL and ACS samples (T=25°C).


### 3.2. Effect of Contact Time

The effect of contact time on the amount of adsorption by ACL and ACS is shown in Figure4. It was observed that after more than 3 h at 25°C ACL and ACS adsorb approximately 90% and 81%, respectively, from 200 mg·L−1 Pb(II) solution. It also shows the maximum adsorption capacity of ACL and ACS as 36.3 and 32.2 mg·g−1, respectively. Beyond 3 h up to 24 h, there was a small variation <2% in the remaining concentration of Pb(II), which indicate adsorption equilibrium point. Hence, a minimum contact time of 3 h was adopted in all the subsequent tests. The data shows that >50% of adsorption takes place in the initial 15 mins. During initial 10 mins of adsorption both ACS and ACL show the same rate of adsorption, but, subsequently, the rate of ACS system gets slightly slower compared to ASL system. This is possibly due to the higher surface area in the latter sample (ACL), as the rate of adsorption is influenced by the fraction of surface area available for adsorption.Figure 4
Effect of contact time on the adsorption of lead from aqueous solution, using ACS and ACL (T=25°C).


### 3.3. Adsorption Kinetics Study

The adsorption data obtained from the experiments on the effect of contact time were applied to three different kinetic models to study the kinetics of Pb(II) adsorption by ACL and ACS. Figures5(a), 5(b), and 5(c) show the fitting in three models, pseudo-first-order, pseudo-second-order, and intraparticle diffusion model, respectively. The experimental and calculated parameters of the pseudo-first-order and pseudo-second-order models have also been summarized in Table 2.Table 2
Calculated kinetic parameters for pseudo-first-order, second-order, and intraparticle diffusion models for the adsorption of Pb(II).
Samples Pseudo-first-order Pseudo-second-order Intraparticle diffusion model q e ,  e x p q e ,  c a l c k 1 R 2 q e ,  c a l c k 2 R 2 k i C R 2 (mg·g−1) (mg·g−1) (min−1) (mg·g−1) (g·mg−1·min−1) (mg·g−1·min1/2) (mg·g−1) ACL 36.01 18.71 1.9 × 10 - 2 0.88 38.46 2.2 × 10 - 3 0.99 0.55 28.32 0.98 ACS 32.24 18.17 0.9 × 10 - 2 0.79 34.48 2.7 × 10 - 3 0.99 0.52 25.36 0.99Figure 5
Kinetic analysis of adsorption capacity as a function of time (min−1), using three different models: (a) pseudo-first-order, (b) pseudo-second-order, and (c) intraparticle diffusion model (T=25°C).
(a) (b) (c)According to the data presented in this table, the calculated linear regression correlation coefficients for the pseudo-first-order model are relatively small (Figure5(a)), and the experimental qe values differ significantly from the values obtained from the linear plots. Therefore, it could be said that the pseudo-first-order equation is not suitable for lead adsorption on ACL and ACS system. As is evident from Figure 5(b) and Table 2, the fitting of experimental data to the pseudo-second-order model is reasonably good, R2>0.99, and the calculated qe values agree well with the experimental values. This shows that Pb(II) ions uptake via both of the ACL and ACS can be estimated with the pseudo-second-order kinetics model.The intraparticle diffusion model is among the most commonly used techniques for the prediction of the rate-controlling step of the adsorption process. Figure5(c) shows q versus t0.5 plot for Pb(II) ions adsorption onto the ACL and ACS. The plot shows two distinct kinetic steps which suggest the existence of at least two stages in the Pb(II) ions sorption process. It is likely that, in the sharper first portion, the adsorbate ions get bound or anchored with the active sites on the adsorbent surface while the second step was governed by the rate of intraparticle diffusion. In the first stage, due to the larger adsorbent surface area of the ACL sample, the adsorption rate onto this adsorbent was considerably higher than that for ACS sample. Considering the second stage, again the computed intraparticle diffusion parameters show a higher adsorption rate constant for ACL as compared to ACS. The remarkably slow diffusion into the intrapores of the ACS samples may have been due to lack of microporosity in the sample that could have facilitated diffusion of adsorbate ions in the rate determination step.


### 3.4. Effect of pH

The pH of adsorbate solution determines the surface charge of adsorbents, the speciation of adsorbate species, and the degree of ionization and that is why it is one of the most important variables in adsorption investigations [5]. It is also directly related to precipitation conditions, particularly in the case of heavy metals, where it plays a critical role in the removal of heavy metal ions from aqueous solutions. The effect of solution pH on the % precipitation of the lead is shown in Figure 6. It was found that there is precipitation of the metal throughout the pH range examined. However, at pH > 5.0 over 30% precipitation was observed, which would modify the adsorption result if such pH values were applied in the tests. This precipitation occurs due to Pb(II) ion association with OH-ions of the basic solution to form lead hydroxides. At pH < 3.0, it is possible that the lead is present in the form of PbOH+, even in small amounts, which may explain the low precipitation in this pH range.Figure 6
Effect of pH on the adsorption capacity and % removal of ACL and ACS sample (T=25°C).The difference between the total removal percentage of Pb(II) ions and the percentage removed by precipitation yields the adsorption percentage of lead, which is also given in Figure6. It shows an increase in the removal of lead ions with increases in solution pH up to 5, after which a gradual and then fast decrease were observed up to pH 10. Maximum lead removal values were obtained at pH values of 5-6. The reduced metal uptake witnessed at low pH values may have been due to excessive protonation (H+ ions) of the carbon surface, which render the adsorption of Pb(II) ions [37]. At higher pH values, the concentration of H+ becomes low, and the surface becomes negatively charged carbon surface (see Section 3.1 and Figure 3) that causes further attraction of metal cations. Nonetheless, at alkaline conditions, a decrease in adsorption was observed which is because of the formation of several hydroxide species by Pb(II) ions which are precipitated and lead to the decrease in free metal ions available in solution and [38] reported an optimum pH of 5 for lead adsorption. Bhattacharyya and Sharma obtained a good retention of lead in the pH 7 and noted that at pH < 4.5 there was excessive protonation of the carbon surface, resulting in a decrease in the adsorption of Pb(II) [39]. Considering the interference due to precipitation during the adsorption experiments with AC, the pHPZC value, and the lead speciation diagram, the pH selected for subsequent tests in this study was 5.0.


### 3.5. Adsorption Isotherms and Modeling of Isotherm Data

Figure7 displays the experimental data of Pb(II) adsorption isotherms on both ACL and ACS at three different temperatures (25, 35, and 45°C) and nonlinear fitting of Langmuir and Freundlich models on experimental values. Table 3 shows the model specific constants at different temperatures, which were calculated from the fitting parameters. The relative difference in adsorption amounts at different temperature shows that, with both the activated carbon samples, the adsorption increases with a decrease in temperature. It is likely due to increasing in surface energy of the activated carbon samples, which would render the interaction of adsorbing Pb(II) ions with the surface [40]. The Langmuir and Freundlich adsorption models were used for fitting the experimental data (Figure 7). A quick comparison in the fitting pattern shows that the Freundlich model shows better fitting on adsorption data by ACL. However, in contrast, ACS-adsorption data shows better fitting with Langmuir model and qmax calculated from this model (37.93 mg·g−1) is close to qexpt (37.6 mg·g−1) values. The application of the Langmuir model is based on the assumption that the binding of the adsorbate onto the surface of the adsorbent occurs primarily through a chemical reaction and that all sites have equal affinity for the metal. The Freundlich isotherm model is an empirical equation based on adsorption onto heterogeneous surfaces (Li et al. 2010). Most assumptions related to the Langmuir model (such as adsorption onto a homogenous surface, with an identical fixed number of adsorption sites) are invalid for the heterogeneous surface of activated carbon. Thus, it is appropriate to use the Langmuir equation for qualitative and descriptive, rather than quantitative, purposes.Table 3
Parameters of Langmuir and Freundlich adsorption models obtained from fitting of adsorption data at a different temperature.
Sample Temp Langmuir Freundlich (°C) q m a x b R 2 K f 1 / n R 2 mg·g−1 L·mg−1 (mg·g−1) (L·mg−1)1/n ACL 25 45.79 0.12 0.9639 13.92 0.23 0.995 35 42.08 0.07 0.9716 10.81 0.25 0.9948 45 38.08 0.06 0.9653 9.36 0.25 0.9896  ACS 25 37.93 0.19 0.999 14.74 0.18 0.9106 35 32.75 0.13 0.999 12.12 0.18 0.899 45 28.14 0.12 0.998 11.13 0.17 0.855Figure 7
Adsorption isotherm of Pb(II) ions on ACL and ACS at different temperatures and fitting of adsorption data on Langmuir and Freundlich models.
(a) (b)


### 3.6. Regeneration and Reuse Study

Figure8 shows a comparison in desorption% of the lead with six different desorbing agents in both the samples. None of the desorbing solutions caused apparent physical alterations or impairment to the samples, enabling its reuse. For both the samples HCl showed maximum effectiveness, with approximately 66.1% and 55.6% removal from ACL and ACS, respectively. The efficiency of the rest of the desorbents follows a common order of HNO3 > H3PO4 ≫ NaOH > NaCl > H2O. The H+ from an acidic medium may actively replace the metal ions (Pb ion) adsorbed on the carbon. Therefore, considering these results the HCl was used as a desorbing agent because it is of low cost compared to other materials and offers better desorbing efficiency.Figure 8
Lead desorption from activated carbon samples using several desorbent chemical agents (T=25°C).The results of reuse experiments obtained from both activated carbon samples were of contrast to each other. The % of Pb(II) adsorption and desorption falls steeply in the case of ACL samples, which makes it almost unsuitable for reuse after two cycles (figure not given). On the other hand, the ACS sample shows reasonably good results of % adsorption and desorption up to four successive cycles; see Figure9. It shows that during first cycle 90% adsorption and 66% desorption were achieved with respect to the value of C0 = 200 mg·L−1. For the second, third, and fourth cycles 80%, 67.5%, and 50% for adsorption and 56.2%, 40.7%, and 20% desorption, respectively, were observed. The 50% loss in adsorption capacity during four cycles could be due to cumulative effect of the inadequate desorption. It may be crucial to use an acid solution with a higher strength or larger amounts of desorbent solutions.Figure 9
Percentage of Pb(II) adsorbed-desorbed per cycle (T=25°C), with ACS sample.In the view of sustainability, the desorbed lead from ACS samples could be reutilized and reverted to factories as a raw material, in spite of being deposited in sanitary landfills as waste. Electrolysis is one of the key processes for its recovery and can be useful to transform lead solution into the elemental lead (using stainless steel electrode).


### 3.7. Comparison of Adsorption Capacity with Other Adsorbents

The adsorption capacities of ACL and ACS were compared (Table4) with other reported studies on activated carbon for lead removal. These studies have used a variety of starting materials like nutshells, pulp, seeds, and animal bones for activated carbon preparation. The comparison shows that adsorption capacities of the present materials are better than some of the reported studies. It shows thatLantana camaraL. can be used as a lucrative source of activated carbon.Table 4
Comparison between adsorption capacities of several adsorbents, obtained from natural organic materials, for Pb(II) ions.
S o r b e n t ∗ Adsorption capacity Optimum pH Equilibrium time Reference q m a x T (mg·g−1) (min) Cashew nut shell AC 28.9 6.0–6.5 30 [17] Hazelnut husk AC 13.05 5.7 60 [18] Coconut shell AC 26.5 4.5 35 [19] Apricot Stone AC 22.85 4 300 [20] Van apple pulp AC 15.96 5 50 [21] Polygonum orientale AC 98.39 5 30 [22] Pine cone AC 27.53 5 60 [23] Cow bone AC 32.1 4 360 [24] Dehydrated hazelnut husks carbon 133.3 4.5 60 [25] Hazelnut husks AC 109.9 5 1200 [26] ACL 48.1 5.0–6.0 180 This study ACS 37.6 5.0–6.0 180 This study ∗AC = activated carbon.


## 3.1. Textural and Structural Characterization

Both the samples of prepared activated carbon were characterized for their surface and other adsorption related physicochemical properties. Porosity and surface area of prepared activated carbon samples were assessed by nitrogen adsorption at −196°C (Figure1). The isotherm of activated carbon prepared from leaf (ACL) as well as stem (ACS) shows similar shape, which is of type I and slightly type IV with H1 loop, which are the characteristics of micro- and mesoporous materials [28]. Both the isotherms have slow condensation step at a relative pressure (p/p0 = 0.8–0.99) which corresponds to the capillary condensation of N2 within uniform mesopores. These results show the essential micro- and mesoporous nature of the prepared activated carbon samples. However, a decrease in adsorption amount in ACS sample is noted, as compared to ACL sample. From N2 adsorption data the specific surface area, ABET, was determined through BET model (within p/p0 0.05–0.15) [29]; likewise the micropore volume Vmicro and total pore volume Vtotal of the materials are listed in Table 1. The anatomical differences in leaves and stem give rise to a change in their structural composition. The same difference has been translated into their surface area and pore volume properties after activation. The specific surface areas of ACL and ACS are 634 and 523 m2/g, respectively. It is evident that chemical activation has produced large numbers of new pores in the samples by continuous devolatilization of the char and carbon burn-off. The dried leaves contain spongy mesophyll as compared to cortex and pith in the stem [30]. The total pore volume of ACL is higher compared to ACS; both the activated carbon samples are microporous in nature which is confirmed by fraction of their micropore volume with respect to their total pore volume.Table 1
The surface properties of prepared activated carbon samples obtained from low-temperature nitrogen adsorption isotherm data.
Sample Specific Surface areaABET Total pore volumeVtotal Micropore volumeVμ m2/g cm3/g cm3/g ACL 634 0.31 0.22 ACS 523 0.26 0.19Figure 1
Low-temperature nitrogen adsorption isotherms, at −196°C, obtained from ACL and ACS samples.SEM technique has been used to observe the change in samples morphology, before and after the treatment. The changes can be observed in Figure2, where SEM images of raw materials (Lantana leaf and stem dust) are compared with, respectively, activated carbons (ACL and ACS). The surface of leaf sample seems uniform before activation and after activation it shows emergence of porous structure on the surface. Likewise, the stem sample surface also shows variation before and after activation; however, this variation is not as noticeable as in the case of leaves sample. It is likely due to the variation in the biochemical composition of leaves and stem [31]. In brief, it is evident from the SEM images that the surface of raw materials gets changed after acid treatment, though the extent of change is different for each sample.Figure 2
SEM images of different magnification ofL. camara (stem and leaves) samples before and after acidic treatment.
(a) (b) (c) (d)In the chemical as well as physical activation method, the variation in original chemical composition resulted in the difference in surface functionality, because different compounds present in the surface and matrix of the sample give rise to different charge group (cationic or anionic) on the surface after carbonization and activation [32]. To observe this phenomenon in the context of the present samples pHPZC analysis has been carried out and the results are presented in Figure 3. It shows that pHPZC is approximately 5.0 for both the samples, which means at pH > 5.0 the activated carbons would have predominantly a negative charge at the surface while below this value the surface is positively charged. Typically, the pH at the point of zero charges on activated carbon is approximately 7 [33, 34]. However, this was not observed from the AC samples prepared in the present study. The value of 5.0 can be explained by acid treatment to raw material which was used to prepare activated carbon. The H+ ions present on the surface after treatment will be released into the solution which resulted in lowering of pH. The adsorption of cations, such as metal ions, is favored at pH > pHPZC while the adsorption of anions is favored at pH < pHPZC [35, 36]. Thus, the lead adsorption process should be carried out at pH equal to or greater than 5.0, to identify the optimal pH range.Figure 3
Determination ofpHZPC of ACL and ACS samples (T=25°C).


## 3.2. Effect of Contact Time

The effect of contact time on the amount of adsorption by ACL and ACS is shown in Figure4. It was observed that after more than 3 h at 25°C ACL and ACS adsorb approximately 90% and 81%, respectively, from 200 mg·L−1 Pb(II) solution. It also shows the maximum adsorption capacity of ACL and ACS as 36.3 and 32.2 mg·g−1, respectively. Beyond 3 h up to 24 h, there was a small variation <2% in the remaining concentration of Pb(II), which indicate adsorption equilibrium point. Hence, a minimum contact time of 3 h was adopted in all the subsequent tests. The data shows that >50% of adsorption takes place in the initial 15 mins. During initial 10 mins of adsorption both ACS and ACL show the same rate of adsorption, but, subsequently, the rate of ACS system gets slightly slower compared to ASL system. This is possibly due to the higher surface area in the latter sample (ACL), as the rate of adsorption is influenced by the fraction of surface area available for adsorption.Figure 4
Effect of contact time on the adsorption of lead from aqueous solution, using ACS and ACL (T=25°C).


## 3.3. Adsorption Kinetics Study

The adsorption data obtained from the experiments on the effect of contact time were applied to three different kinetic models to study the kinetics of Pb(II) adsorption by ACL and ACS. Figures5(a), 5(b), and 5(c) show the fitting in three models, pseudo-first-order, pseudo-second-order, and intraparticle diffusion model, respectively. The experimental and calculated parameters of the pseudo-first-order and pseudo-second-order models have also been summarized in Table 2.Table 2
Calculated kinetic parameters for pseudo-first-order, second-order, and intraparticle diffusion models for the adsorption of Pb(II).
Samples Pseudo-first-order Pseudo-second-order Intraparticle diffusion model q e ,  e x p q e ,  c a l c k 1 R 2 q e ,  c a l c k 2 R 2 k i C R 2 (mg·g−1) (mg·g−1) (min−1) (mg·g−1) (g·mg−1·min−1) (mg·g−1·min1/2) (mg·g−1) ACL 36.01 18.71 1.9 × 10 - 2 0.88 38.46 2.2 × 10 - 3 0.99 0.55 28.32 0.98 ACS 32.24 18.17 0.9 × 10 - 2 0.79 34.48 2.7 × 10 - 3 0.99 0.52 25.36 0.99Figure 5
Kinetic analysis of adsorption capacity as a function of time (min−1), using three different models: (a) pseudo-first-order, (b) pseudo-second-order, and (c) intraparticle diffusion model (T=25°C).
(a) (b) (c)According to the data presented in this table, the calculated linear regression correlation coefficients for the pseudo-first-order model are relatively small (Figure5(a)), and the experimental qe values differ significantly from the values obtained from the linear plots. Therefore, it could be said that the pseudo-first-order equation is not suitable for lead adsorption on ACL and ACS system. As is evident from Figure 5(b) and Table 2, the fitting of experimental data to the pseudo-second-order model is reasonably good, R2>0.99, and the calculated qe values agree well with the experimental values. This shows that Pb(II) ions uptake via both of the ACL and ACS can be estimated with the pseudo-second-order kinetics model.The intraparticle diffusion model is among the most commonly used techniques for the prediction of the rate-controlling step of the adsorption process. Figure5(c) shows q versus t0.5 plot for Pb(II) ions adsorption onto the ACL and ACS. The plot shows two distinct kinetic steps which suggest the existence of at least two stages in the Pb(II) ions sorption process. It is likely that, in the sharper first portion, the adsorbate ions get bound or anchored with the active sites on the adsorbent surface while the second step was governed by the rate of intraparticle diffusion. In the first stage, due to the larger adsorbent surface area of the ACL sample, the adsorption rate onto this adsorbent was considerably higher than that for ACS sample. Considering the second stage, again the computed intraparticle diffusion parameters show a higher adsorption rate constant for ACL as compared to ACS. The remarkably slow diffusion into the intrapores of the ACS samples may have been due to lack of microporosity in the sample that could have facilitated diffusion of adsorbate ions in the rate determination step.


## 3.4. Effect of pH

The pH of adsorbate solution determines the surface charge of adsorbents, the speciation of adsorbate species, and the degree of ionization and that is why it is one of the most important variables in adsorption investigations [5]. It is also directly related to precipitation conditions, particularly in the case of heavy metals, where it plays a critical role in the removal of heavy metal ions from aqueous solutions. The effect of solution pH on the % precipitation of the lead is shown in Figure 6. It was found that there is precipitation of the metal throughout the pH range examined. However, at pH > 5.0 over 30% precipitation was observed, which would modify the adsorption result if such pH values were applied in the tests. This precipitation occurs due to Pb(II) ion association with OH-ions of the basic solution to form lead hydroxides. At pH < 3.0, it is possible that the lead is present in the form of PbOH+, even in small amounts, which may explain the low precipitation in this pH range.Figure 6
Effect of pH on the adsorption capacity and % removal of ACL and ACS sample (T=25°C).The difference between the total removal percentage of Pb(II) ions and the percentage removed by precipitation yields the adsorption percentage of lead, which is also given in Figure6. It shows an increase in the removal of lead ions with increases in solution pH up to 5, after which a gradual and then fast decrease were observed up to pH 10. Maximum lead removal values were obtained at pH values of 5-6. The reduced metal uptake witnessed at low pH values may have been due to excessive protonation (H+ ions) of the carbon surface, which render the adsorption of Pb(II) ions [37]. At higher pH values, the concentration of H+ becomes low, and the surface becomes negatively charged carbon surface (see Section 3.1 and Figure 3) that causes further attraction of metal cations. Nonetheless, at alkaline conditions, a decrease in adsorption was observed which is because of the formation of several hydroxide species by Pb(II) ions which are precipitated and lead to the decrease in free metal ions available in solution and [38] reported an optimum pH of 5 for lead adsorption. Bhattacharyya and Sharma obtained a good retention of lead in the pH 7 and noted that at pH < 4.5 there was excessive protonation of the carbon surface, resulting in a decrease in the adsorption of Pb(II) [39]. Considering the interference due to precipitation during the adsorption experiments with AC, the pHPZC value, and the lead speciation diagram, the pH selected for subsequent tests in this study was 5.0.


## 3.5. Adsorption Isotherms and Modeling of Isotherm Data

Figure7 displays the experimental data of Pb(II) adsorption isotherms on both ACL and ACS at three different temperatures (25, 35, and 45°C) and nonlinear fitting of Langmuir and Freundlich models on experimental values. Table 3 shows the model specific constants at different temperatures, which were calculated from the fitting parameters. The relative difference in adsorption amounts at different temperature shows that, with both the activated carbon samples, the adsorption increases with a decrease in temperature. It is likely due to increasing in surface energy of the activated carbon samples, which would render the interaction of adsorbing Pb(II) ions with the surface [40]. The Langmuir and Freundlich adsorption models were used for fitting the experimental data (Figure 7). A quick comparison in the fitting pattern shows that the Freundlich model shows better fitting on adsorption data by ACL. However, in contrast, ACS-adsorption data shows better fitting with Langmuir model and qmax calculated from this model (37.93 mg·g−1) is close to qexpt (37.6 mg·g−1) values. The application of the Langmuir model is based on the assumption that the binding of the adsorbate onto the surface of the adsorbent occurs primarily through a chemical reaction and that all sites have equal affinity for the metal. The Freundlich isotherm model is an empirical equation based on adsorption onto heterogeneous surfaces (Li et al. 2010). Most assumptions related to the Langmuir model (such as adsorption onto a homogenous surface, with an identical fixed number of adsorption sites) are invalid for the heterogeneous surface of activated carbon. Thus, it is appropriate to use the Langmuir equation for qualitative and descriptive, rather than quantitative, purposes.Table 3
Parameters of Langmuir and Freundlich adsorption models obtained from fitting of adsorption data at a different temperature.
Sample Temp Langmuir Freundlich (°C) q m a x b R 2 K f 1 / n R 2 mg·g−1 L·mg−1 (mg·g−1) (L·mg−1)1/n ACL 25 45.79 0.12 0.9639 13.92 0.23 0.995 35 42.08 0.07 0.9716 10.81 0.25 0.9948 45 38.08 0.06 0.9653 9.36 0.25 0.9896  ACS 25 37.93 0.19 0.999 14.74 0.18 0.9106 35 32.75 0.13 0.999 12.12 0.18 0.899 45 28.14 0.12 0.998 11.13 0.17 0.855Figure 7
Adsorption isotherm of Pb(II) ions on ACL and ACS at different temperatures and fitting of adsorption data on Langmuir and Freundlich models.
(a) (b)


## 3.6. Regeneration and Reuse Study

Figure8 shows a comparison in desorption% of the lead with six different desorbing agents in both the samples. None of the desorbing solutions caused apparent physical alterations or impairment to the samples, enabling its reuse. For both the samples HCl showed maximum effectiveness, with approximately 66.1% and 55.6% removal from ACL and ACS, respectively. The efficiency of the rest of the desorbents follows a common order of HNO3 > H3PO4 ≫ NaOH > NaCl > H2O. The H+ from an acidic medium may actively replace the metal ions (Pb ion) adsorbed on the carbon. Therefore, considering these results the HCl was used as a desorbing agent because it is of low cost compared to other materials and offers better desorbing efficiency.Figure 8
Lead desorption from activated carbon samples using several desorbent chemical agents (T=25°C).The results of reuse experiments obtained from both activated carbon samples were of contrast to each other. The % of Pb(II) adsorption and desorption falls steeply in the case of ACL samples, which makes it almost unsuitable for reuse after two cycles (figure not given). On the other hand, the ACS sample shows reasonably good results of % adsorption and desorption up to four successive cycles; see Figure9. It shows that during first cycle 90% adsorption and 66% desorption were achieved with respect to the value of C0 = 200 mg·L−1. For the second, third, and fourth cycles 80%, 67.5%, and 50% for adsorption and 56.2%, 40.7%, and 20% desorption, respectively, were observed. The 50% loss in adsorption capacity during four cycles could be due to cumulative effect of the inadequate desorption. It may be crucial to use an acid solution with a higher strength or larger amounts of desorbent solutions.Figure 9
Percentage of Pb(II) adsorbed-desorbed per cycle (T=25°C), with ACS sample.In the view of sustainability, the desorbed lead from ACS samples could be reutilized and reverted to factories as a raw material, in spite of being deposited in sanitary landfills as waste. Electrolysis is one of the key processes for its recovery and can be useful to transform lead solution into the elemental lead (using stainless steel electrode).


## 3.7. Comparison of Adsorption Capacity with Other Adsorbents

The adsorption capacities of ACL and ACS were compared (Table4) with other reported studies on activated carbon for lead removal. These studies have used a variety of starting materials like nutshells, pulp, seeds, and animal bones for activated carbon preparation. The comparison shows that adsorption capacities of the present materials are better than some of the reported studies. It shows thatLantana camaraL. can be used as a lucrative source of activated carbon.Table 4
Comparison between adsorption capacities of several adsorbents, obtained from natural organic materials, for Pb(II) ions.
S o r b e n t ∗ Adsorption capacity Optimum pH Equilibrium time Reference q m a x T (mg·g−1) (min) Cashew nut shell AC 28.9 6.0–6.5 30 [17] Hazelnut husk AC 13.05 5.7 60 [18] Coconut shell AC 26.5 4.5 35 [19] Apricot Stone AC 22.85 4 300 [20] Van apple pulp AC 15.96 5 50 [21] Polygonum orientale AC 98.39 5 30 [22] Pine cone AC 27.53 5 60 [23] Cow bone AC 32.1 4 360 [24] Dehydrated hazelnut husks carbon 133.3 4.5 60 [25] Hazelnut husks AC 109.9 5 1200 [26] ACL 48.1 5.0–6.0 180 This study ACS 37.6 5.0–6.0 180 This study ∗AC = activated carbon.


## 4. Conclusions

The results of this study show that valorization ofLantana CamaraL. can be achieved by converting it into an activated carbon with the moderate surface area, by using H2SO4 impregnation method. The compositional differences in leaf and stem of plant give rise to a difference in textural and surface properties of resulting activated carbon. Therefore, the surface area and adsorption capacity of activated carbon obtained from its leaf samples are higher than those from stem samples. The acid treatment increases the negative charge on the surface in both the samples. Consequently, the pH becomes a critical factor in the lead adsorption, at pH > 5.0. For both the activated carbon samples, the pseudo-second-order kinetic model best represented the adsorption kinetics data. ACL-adsorption equilibrium system was best described by Langmuir model, whereas ACS system was better explained by Freundlich model. The adsorbed lead on the samples can be efficiently desorbed with the help of HCl. The reusability of ACL samples is not satisfactory as compared to ACS samples. Concluding this study, it may be mentioned that although ACS has <12% less adsorption capacity compared to ACL, but it shows better reusability and thereby shows the better potential of a new low-cost adsorbent. This study opens the route to further studies where the selectivity of thisLantana camaraL. based activated carbon can be investigated for other emerging pollutants like endocrine disruptors and pharmaceuticals.



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*Source: 5612594-2017-02-26.xml*