Removal of zinc and lead from aqueous solution by

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Journal of Molecular Liquids 211 (2015) 448–456

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Removal of zinc and lead from aqueous solution by nanostructured cedar leaf ash as biosorbent Laleh Divband Hafshejani a,⁎, Saeed Boroomand Nasab a, Roya Mafi Gholami b, Mostafa Moradzadeh a, Zahra Izadpanah a, Saeid Bibak Hafshejani c, Amit Bhatnagar d,⁎ a

Department of Irrigation and Drainage, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Khuzestan, Iran Department of Water and Waste Water, Faculty of Engineering, Islamic Azad University of Ahvaz, Khuzestan, Iran Department of Civil Engineering, Faculty of Engineering, Islamic Azad University of Dezful, Khuzestan, Iran d Department of Environmental Science, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, Finland b c

a r t i c l e

i n f o

Article history: Received 24 April 2015 Received in revised form 16 July 2015 Accepted 20 July 2015 Available online xxxx Keywords: Adsorption Metals Lead Zinc Cedar leaf ash Biosorbent

a b s t r a c t In the present study, the adsorption of zinc (Zn2+) and lead (Pb2+) from aqueous solutions by nanostructured cedar leaf ash as biosorbent was investigated in batch tests under different experimental conditions. The chemical and morphological structures of biosorbent were investigated by scanning electron microscopy (SEM), elemental analyzer (CHNSO), particle size analyzer (PSA), X-ray Fluorescence spectroscopy (XRF) and Fouriertransform infrared spectroscopy (FTIR). The effect of different parameters such as solution pH, contact time and adsorbent dosage were investigated on the biosorption of two studied metals by nanostructured cedar leaf ash. The biosorption process was found to be relatively fast and equilibrium was achieved within 30 min for Zn2+ and Pb2+. The adsorption data were analyzed using different isotherm models (Langmuir, Freundlich, Redlich–Peterson and Sips (Langmuir–Freundlich)) and kinetic models (pseudo-first-order, pseudo-secondorder and intraparticle diffusion). Results revealed that pseudo-second-order kinetic model could well describe the adsorption kinetics of Zn2+ and Pb2+ biosorption, and Sips (Langmuir–Freundlich) model was found to fit well for Zn2+ and Pb2+ adsorption. The maximum adsorption capacity from Langmuir model was calculated as 7.23 and 4.79 mg g−1 for Pb2+ and Zn2+, respectively. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Water pollution by toxic heavy metals is one of the major environmental problems, because metals are non-biodegradable and harmful to public health, even at very low concentrations [1–4]. Heavy metals are used in numerous industries such as plastics, mining, plating, power generation, pigment, electronic and batteries [5]. Lead and zinc are the most important heavy metals which are used in many industrial applications. However, both metals are well-known toxics and can find their ways to the aquatic environment through wastewater discharge [6]. Lead causes many harmful effects to human health due to its toxicity, accumulation in food chains and persistence in nature [7]. Elevated concentrations of zinc cause severe health problems e.g., vertigo, disharmony, arteriosclerosis, pancreas damage [6]. World Health Organization has determined the allowable concentration of Pb2 + (0.05 mg L− 1) and Zn2 + (4 mg L− 1) [8,9] in drinking water. Various processes exist to remove toxic heavy metal ions, including chemical precipitation/coagulation, membrane technology, electrolytic reduction, ⁎ Corresponding authors. E-mail addresses: [email protected] (L.D. Hafshejani), [email protected]fi (A. Bhatnagar).

http://dx.doi.org/10.1016/j.molliq.2015.07.044 0167-7322/© 2015 Elsevier B.V. All rights reserved.

ion exchange and adsorption [10,11]. However, most of these methods have some limitations such as, high operational cost, unaffordable on large scale metals removal from wastewater and ineffective at higher concentrations. Adsorption is generally considered as one of the most efficient technologies due to the advantages of treatment stability, easy operation, lower environmental impacts, and low cost. Various adsorbents have been used to remove Zn2+ and Pb2+ ions from water and wastewater such as natural absorbent [12,13], industrial and/or agriculture wastes [14,15]. Recently, application of nanotechnology has been developed to treat contaminated water to remove diverse pollutants. Unique characteristics of nano particles such as, large specific surface area, has increased their potential for adsorption of toxic heavy metal ions [16–18]. Cedar with the scientific name of Ziziphus spina-christi grows in Saudi Arabia, north of Africa and in Iran in provinces of Khuzestan, Fars and Hormozgan. It is used to treat blisters, bruises, chest pains, dandruff, fractures, headache, and mouth problems and of other beneficial applications that include the use of leaves as fodder, branches for fencing, wood as fuel [19]. Furthermore, this plant is adapted to hot and dry climates which make it appropriate for cultivation in an environment characterized by increasing degradation of land and water resources. Lack of research in Z. spina-christi prevents its successful improvement and promotion. Also cedar leaf is an

L.D. Hafshejani et al. / Journal of Molecular Liquids 211 (2015) 448–456

inexpensive agricultural waste. The major component of Z. spina-christi is cellulose (C6H10O5)n. The cellulose surface contains functional groups which have been found efficient to bind cations. In our previous work, the adsorption of Cd2+ by cedar leaf and cedar leaf ash (using millimeter size) was compared [20]. It was found that cedar leaf ash possesses higher surface area (20.38 m2 g−1) than cedar leaf (8.9 m2 g− 1). Also, cedar leaf ash showed better adsorption potential for Cd2 + (4.27 mg g− 1) than cedar leaf (3.91 mg g− 1). Further, equilibrium time for Cd2 + adsorption by cedar leaf ash was fast (30 min) than cedar leaf (45 min). As cedar leaf ash showed better results for Cd2+ adsorption, it was selected in this study to examine its suitability for other metals (Zn2+ and Pb2+). Also, in another research, we compared the removal of Cd2+ using nano/milli-sized particles of cedar leaf ash [21]. Result of this study showed that cedar leaf ash with nanosize has higher adsorption capacity for Cd2 + (7.85 mg g− 1) than milli-size (4.33 mg g−1). Therefore, cedar leaf ash in nano form was selected in this study. The equilibrium and kinetic data of adsorption studies were modeled using the adsorption isotherm models Langmuir, Freundlich, Redlich–Peterson and Sips (Langmuir–Freundlich) and the adsorption kinetic models (pseudo-first-order, pseudo-secondorder and intraparticle diffusion models). 2. Materials and methods 2.1. Preparation of the adsorbent Cedar leaves were collected in the area of Khuzestan province, Iran in March 2011. The collected leaves were washed thoroughly using double distilled water to remove impurities. After washing, leaves were dried in the oven at 100 °C for 1 h and then were carbonized in the Muffle Furnace (FP6-IRAN KHODSAZ model — made in Iran) at 600 °C for 40 min. The reason to select this temperature (600 °C) was to establish a balance between carbon content and specific surface area. With the increase in temperature, carbon percentage decreased extensively and the surface area increased because of the removal of volatile matter. The nanostructured cedar leaf ash was prepared by mechanical grinding in a jet mill (D-56070 KOBLENZ model — made in Germany). In this method, the size of material was changed by a mill with metal or ceramic ball. In the mechanical alloying method, no change was observed in the chemical composition of the raw material and only the internal structure and the particle size of the adsorbent was changed. 2.2. Characterization of the adsorbent A scanning electron microscope (SEM, Leo 1455 VP model, made in Germany) was used to study the morphology of the adsorbent's surface. The specific surface area of the adsorbent was determined by methylene blue method [22]. Particle size was determined using a particle size analyzer (Malvern Zetasizer 3000, UK). Infrared spectra were recorded using FTIR spectrometer (Spectrum GX, PerkinElmer). Also, elemental (C, H, N, S, O) analyses were conducted using a CHNSO analyzer (vario ELIII-elementar — made in Germany). An X-ray Fluorescence Spectroscopy (XRF, BRUKER S4 Pioneer model, made in Germany) was used to determine the metal oxides or nonmetal oxides of adsorbent. 2.3. Determination of point of zero charge (pHpzc) For the determination of pHpzc of the adsorbent, 100 mL 0.01 M NaCl solution was divided into several Erlenmeyer flasks. The initial pH of solutions was adjusted between 3 and 8 by adding 0.1 M HCl or 0.1 M NaOH. Then, 1 g of adsorbent was added to each solution, the mixtures were shaken in controlled temperature for 48 h with a speed of 150 rpm. After completion of the equilibration time, the solutions were filtered and final pH values (pHfinal) of the filtrates were measured again. The difference between the initial pH (pHi) and final pH (pHf)

449

values (ΔpH = pHi − pHf) was plotted against the pHi. The point of intersection of the resulting curve with abscissa, at which ΔpH = 0, gave the point of zero charge. 2.4. Adsorption studies Stock solutions of 1000 mg L−1 of Zn2+ and Pb2 + were prepared from their chloride salts by dissolving them in deionized water. Metals spiked samples at a required concentration range were further prepared by appropriate dilution of the stock solutions with deionized water. The pH of initial solutions was adjusted using 0.1 M NaOH and 0.1 M HCl and recorded using a Mettler Toledo 320 pH meter. The sorption of two metals (zinc and lead) on prepared adsorbent was conducted at room temperature (20 ± 2 °C) by batch experiments. One hundred milliliters of metal solution of varying initial concentrations (2–80 mg L− 1) in 250 mL capped tubes were shaken (150 rpm) with 1.0 g of adsorbent after adjusting the pH to the desired value, for a specified period of contact time (12 h) in a temperature controlled shaking assembly (THZ98A mechanical shaker). After equilibrium, the solutions were centrifuged at 12,000 rpm for 20 min and filtered. Reproducibility of the measurements was determined in duplicates and the average values are reported. The initial and the final concentrations of Zn2+ and Pb2+ in the aqueous solution were measured with an atomic absorption spectrophotometer (Varian 220 FS AA model). Removal efficiency of heavy metal ions was calculated by the following equation: Removal efficiency ð%Þ ¼

ðC i −C e Þ  100 Ci

ð1Þ

where Ci and Ce are the initial and final concentrations of Zn2+ and Pb2+ ions in the solution, respectively. For kinetic studies, metal ions having initial concentration of 10 mg L−1 were agitated for different contact times (0, 5, 10, 15, 30, 45, 60, 90, 120 min) with an adsorbent dosage of 10 g L−1 at 20 ± 2 °C. To study the effect of adsorbent dosage on adsorption of Zn2+ and Pb2+, metal solutions having initial concentration of 10 mg L−1 were agitated with varying adsorbent dosage (1, 2, 5, 10, 20, 30, 40, 50 g L−1) for 30 min at 20 ± 2 °C. Also, for isotherm studies, solutions of metal ions containing varying initial concentration (2, 10, 25, 40, 50 mg L−1) were equilibrated for 30 min with an adsorbent dosage of 10 g L−1 at 20 ± 2 °C. 2.4.1. Adsorption kinetics Different adsorption kinetic models have been developed by various researchers to analyze the adsorption kinetics data of heavy metal ions, such as pseudo-first-order, pseudo-second-order, intraparticle diffusion, Elovich and Bangham's models. In this study, adsorption data were analyzed by using three well-known kinetic models namely, pseudo-first-order, pseudo-second-order and intraparticle diffusion models. The nonlinear forms of pseudo-first-order [23] (Eq. (2)), pseudo-second-order [24] (Eq. (3)) and intraparticle diffusion model [25] (Eq. (4)) are expressed below:   qt ¼ qe 1−e−k1 t

ð2Þ

qe 2 k2 t 1 þ qe k2 t

ð3Þ

qt ¼ K p t 1=2 þ I

ð4Þ

qt ¼

where, qe and qt (mg g−1) are the amounts of metal ions adsorbed at equilibrium and at time t, k1 (min− 1) is the constant of the pseudofirst-order kinetics, k2 (g mg− 1 min− 1) is the rate constant of the pseudo-second-order kinetics, Kp is the intraparticle diffusion rate constant (mg g−1 min1/2) and I (mg g−1) is the intercept of intraparticle diffusion model.

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2.4.2. Adsorption isotherms Several isotherm models have been used in the literature to describe the adsorption equilibrium data, such as Langmuir, Freundlich, Redlich–Peterson, Dubinin–Radushkevich, Sips, and Temkin [26]. In this study, adsorption of Zn 2 + and Pb 2 + ions by nanostructured cedar leaf ash was modeled with four models (Langmuir, Freundlich, Sips (Langmuir–Freundlich) and Redlich–Peterson). The Freundlich isotherm is applicable for monolayer and multilayer adsorption onto the heterogeneous surface of an adsorbent [16]. The Langmuir isotherm is valid for monolayer adsorption onto surface of adsorbent [16,27]. The Redlich–Peterson isotherm model incorporates three parameters and can be applied either in homogenous or heterogeneous systems [28]. The Sips model is one of the empirical adsorption equations with three parameters that is a combination of Langmuir and Freundlich equations [29]. The nonlinear forms of the Freundlich (Eq. (5)), Langmuir (Eq. (6)), Redlich–Peterson (Eq. (7)) and Sips (Eq. (8)) models are represented below [30–32]: 1

ð5Þ

q ¼ KC ne bqm C e ð1 þ bC e Þ

ð6Þ

aC e  q¼ 1 þ bC ne

ð7Þ



n



qm ðbC e Þ n 1 þ ðbC e Þ

ð8Þ

N   X  Oi −O P i −P

R2 ¼

!2

i¼1

N  N  2 X X 2 Oi −O  P i −P i¼1

ð11Þ

i¼1

where: n Oi Pi Ō P

number of observations ith value of the observed measurement ith value of the predicted measurement mean of the observed values mean of the predicted values.

3. Results and discussion 3.1. Characterization of the adsorbent Fourier transform infrared spectroscopy (FTIR) is often used to examine the surface functional groups available on the surface of adsorbent and their ability for metal ions adsorption [33–36]. FTIR spectrums of cedar leaf ash before and after adsorption were recorded (Fig. 1(a)). FTIR spectrum after adsorption shows that wave numbers and the intensity of some peaks are shifted or substantially lower than those before adsorption. An absorption band around 3375.64 cm− 1 corresponding to O–H or N–H groups is shifted to 3326.37 cm−1 after adsorption of Pb2 + and 3232.51 after adsorption of Zn2 +, which may be ascribed to the complexion of OH and amide groups with metals ions [37–40]. The peaks at 1615.9 cm− 1, 1631 cm− 1 and 1649.89 cm− 1 may be attributed to C_O stretching vibration [40–44]. The peak at 1401.3 cm−1, 1376.97 cm−1 and 1416.68 cm−1 in the spectrum show C–N groups. The peak at 1145.93 cm− 1 has shifted to 1104.78 cm− 1

where q is the amount of heavy metal ions adsorbed (mg g−1) by the adsorbent at equilibrium time; Ce is the concentration (mg L− 1) of heavy metal ions at equilibrium time in solution; qm is the maximum adsorption capacity of adsorbent (mg g− 1); K (mg g−1) (L mg−1)1/n and n (g L−1) are the Freundlich equilibrium constant and exponent, respectively; b is the Langmuir constant (L mg−1); b (L mg−1) in Sips model is the affinity constant for adsorption; a (L g−1) and b (L mg−1) are Redlich–Peterson constant of adsorption. Modeling calculations were conducted using Microsoft Office Excel 2007 software. Isotherm parameters were determined by minimizing the Sum of the Squares of the Errors (ERRSQ) function across the concentration range studied: ERRSQ ¼

Xn i¼1

ðOi −P i Þ2

ð9Þ

where: n Oi Pi

number of observations. ith value of the observed measurement. ith value of the predicted measurement.

2.5. Error analysis In this study, Root Mean Square Error (RMSE) and coefficient of determination (R2) were used to evaluate the applicability of applied models. Two parameters, (R2) and (RMSE) were calculated by following equations [26]: vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u n u 1 X ðO −P i Þ2 RMSE ¼ t n−2 i¼1 i

ð10Þ Fig. 1. (a) FTIR spectra and (b) particle size distribution of nanostructured cedar leaf ash.

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451

and 1117.78 cm−1. Peaks in the range of 1000–1200 cm−1 should correspond to C–O stretching [42,43,45]. The changes appear in absorption bands in FTIR after adsorption indicates that some functional groups are involved in the sorption process, due to which either they (bands) shift or disappear. Particles size of the adsorbent was determined using a particle size analyzer. The measured size of nanostructured cedar leaf ash adsorbent was about 207.3 nm (Fig. 1(b)). SEM photographs of nanostructured cedar leaf ash before and after metals ions adsorption are shown in Fig. 2 (a–c). The surface of nanostructured cedar leaf ash was found to be smooth and soft. As can be seen from Fig. 2(a), the adsorbent possesses porous structure and some pores are also visible in the SEM images. No significant changes could be observed in metalsorbed adsorbent (Fig. 2 (b–c)). The surface area of nanostructured cedar leaf ash was found to be 33.53 m2 g−1 using a methylene blue method. CHNSO analyses were performed to determine the elemental constituents of nanostructured cedar leaf ash and results are presented in Table 1. It was found that carbon and oxygen were present in higher amounts as compared to other elements which might be due to the presence of oxygen and carbon containing functional groups such as carboxylic groups. This functional group (COO−) has negative surface charge and can increase cation exchange capacity (CEC) of the adsorbent. Also, results of XRF analysis of cedar leaf ash are presented in Table 2. It can be seen from Table 2 that calcium and potassium oxides were present in higher amounts. 3.2. Point of zero charge (pHpzc) analysis The pHpzc of cedar leaf ash biosorbent was determined and results are shown in Fig. 3(a). It was found that the pHpzc of cedar leaf ash biosorbent is about 3.76. At the pH higher than the pHpzc, the surface of the adsorbent is negatively charged, favoring the adsorption of cationic species. Also, adsorption of anionic species will be favored at pH lower than the pHpzc [46,47]. Optimum pH for both metals in this study was found to be 5 which is more than from pHpzc (3.76), Thus, it is acceptable that maximum adsorption of Zn2+ and Pb2+ by nanostructured cedar leaf ash occurred at pH 5. At this pH, surface of nanostructured cedar leaf ash is negatively charged and could adsorb positive charge species like Zn2+ and Pb2+. 3.3. Effect of pH The pH of the solution is an important parameter in the adsorption process [18,33]. Fig. 3(b) shows the effect of pH on percentage removal of heavy metal ions by nanostructured cedar leaf ash. Results revealed that with increasing the pH value from 3 to 5, adsorption efficiency increased, but at pH from 6 to 8, the white precipitate were observed in the solution, thus the adsorption experiments for Zn2 + and Pb2 + removal using nanostructured cedar leaf ash were not performed at pH higher than 5. The maximum adsorption of Zn2+ and Pb2+ by nanostructured cedar leaf ash occurred at pH 5 for both metals. Similar results have been reported by other researchers who indicated that adsorption efficiency of adsorbents was low at acidic pH and increases at higher pH values [48]. It can be explained by the fact that at low pH, there are H+ ions in the solution which compete with Zn2+ and Pb2+ ions for active sites present on the nanostructured cedar leaf ash. With the increase in pH value, the amount of H+ ions is decreased, therefore, the competition between H+ and Zn2+ and Pb2+ is also decreased. Also, with the increase in pH value, negative surface charge was increased resulting in the higher adsorption of Zn2+ and Pb2+ by nanostructured cedar leaf ash [49]. Therefore, based on these results, pH 5 was selected as for further experiments. Other researchers also selected pH 5 as optimum pH to prevent Zn2 + and Pb2 + precipitation during biosorption studies [50–52]. After determining the optimum pH as 5, 1 M NaOH was added to 50 mL acetic acid (0.1 M) in order to create a buffer with pH 5. After the adjustment of primitive pH of metal ion solution with adsorbent as 5, 5 mL present buffer was added to the solution, to

Fig. 2. SEM photograph of nanostructured cedar leaf ash, (a) before adsorption, (b) after adsorption of Zn2+, (c) after adsorption of Pb2+.

Table 1 Elemental contents of nanostructured cedar leaf ash (percentage). C

H

N

S

O

57.46

4.205

2.808

0.829

34.698

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Table 2 Metal oxides or nonmetal oxides of nanostructured cedar leaf ash (percentage). Compound

Concentration (%w/w)

Compound

Concentration (%W/W)

CaO K2O Cl MgO SO3 P2O5 SiO2 Fe2O3

57.74 19.47 7.73 3.32 2.55 2.32 2.21 1.36

SrO Na2O Al2O3 MnO CuO TiO2 ZnO Total

1.05 0.795 0.692 0.171 0.099 0.095 0.088 99.69

ensure the constant pH of 5 during the adsorption process. Finally adsorption efficiency was calculated and was defined that it was not significantly changed with or without buffer application. 3.4. Effect of contact time Contact time is an important parameter in the water and wastewater treatment systems [20]. Fig. 4 shows the effect of contact time for the adsorption of Zn2 + and Pb2 + ions by nanostructured cedar leaf ash. With increasing the contact time, the adsorption efficiency of Zn2+ and Pb2+ was found to increase and equilibrium was reached in 30 min. Results showed that at first, the adsorption rate was very fast. After 5 min, the rate of adsorption was found to reduce. This

Fig. 4. Effect of contact time on the adsorption efficiency of Zn2+ and Pb2+ by nanostructured cedar leaf ash.

phenomenon might be due to the fact that all adsorbent sites were vacant in the beginning and their capabilities were high to adsorb ions. Similar results were also reported by other researchers [9,20]. Therefore, based on the results of this study, equilibration time of 30 min was selected for further experiments. 3.5. Effect of adsorbent dosage Adsorbent dosage is an important factor that determines how much adsorbent is required to remove a definite amount of metal ions or other pollutants from the solution [53]. It was found in this study that the adsorption of heavy metals ions increased with the increase of adsorbent dosage from 1 g L−1 to 20 g L−1 (Fig. 5). The increase in adsorption efficiency was due to the accessibility of more number of adsorption active sites and functional groups for the adsorption of Pb2+ and Zn2+ ions [9,49]. Afterwards, with the increase of adsorbent dosage from 20 g L−1 to 50 g L−1, adsorption efficiency was found to decrease due to the overlapping or aggregation of active sites at higher dosage (from 20–50 g L−1) [54]. Therefore, an optimum adsorbent dosage of 20 g L− 1 was selected for further experiments. Similar results were also reported by other researchers where an adsorbent dosage of 20 g L− 1 was found to be the optimum adsorbent dosage for heavy metals adsorption [55]. It was also found that with 10 g L−1 adsorbent

Fig. 3. (a) pHpzc of nanostructured cedar leaf ash, (b) Effect of pH on the adsorption efficiency of Zn2+ and Pb2+ by nanostructured cedar leaf ash adsorbent.

Fig. 5. Effect of adsorbent dosage on the adsorption of Zn2+ and Pb2+ by nanostructured cedar leaf ash.

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dose, removal efficiency of Pb2+ and Zn2+ were 94% and 72% respectively. By doubling the adsorbent amount (20 g L−1), it was observed that only 4% and 3% of Pb2+ and Zn2+ removal efficiency was increased, respectively. This behavior might be due to the aggregation of adsorbent particles. Increasing amount of adsorbent in solution caused adsorbent particles to combine with each other and larger particles were formed. Thus their surface area and adsorption potential was decreased. 3.6. Adsorption kinetics studies Results of the adsorption kinetic models for the Zn2+ and Pb2+ are shown in Table 3, Figs. 6 and 7 (a–b). For Zn2+ and Pb2+ ions, qe(cal) determined from pseudo-first-order and pseudo-second-order models are in a good agreement with the experimental values, qe(exp). However, by comparing the RMSE and R2 values (Table 3) for Pb2+ adsorption, it was found that the pseudo-second-order model with RMSE = 0.008 and R2 = 0.999 fits better to the experimental data as compared to the other models. Also, for Zn2 + adsorption, the pseudo-second-order model appears the better-fitting model because it has the higher R2 and lower RMSE (R2 = 0.999 and RMSE = 0.006). Similar results have been reported by other researchers where pseudo-second-order model has been fitted well for metals biosorption [4,51,56]. The adsorption rate constants for both kinetics models have been calculated. The values of k1 and k2 for Zn2 + ions were 0.382 (min− 1) and 1.504 (g mg−1 min−1), while the values of these parameters were calculated as 0.665 (min− 1) and 3.690 (g mg−1 min− 1) for Pb2 + respectively. These results showed that adsorption rate is higher for Pb2 + ions as compared to Zn2 + ions. It was also found that adsorption rate and amount adsorbed is higher for Pb2 + ions as compared to Zn2 + ions (Table 3). The overall rate of adsorption can be described by the following three steps: (1) fluid transport, (2) film diffusion, (3) surface diffusion. If the intraparticle diffusion is the sole rate-limiting step, intercept of the line should pass through the origin. When the intercept of the line do not pass through the origin, this suggests that adsorption kinetics may be controlled by film diffusion and intraparticle diffusion concurrently [57]. In this study, intraparticle diffusion model (qt vs. t1/ 2 plot) showed two distinct linear portions (Figs. 6(b) and 7(b)). This would indicate further intricacy existed in the adsorption process [58]. The three stages in the plot suggest that the adsorption process occurs by surface adsorption and intraparticle diffusion [59]. Larger intercepts (I value in Table 3) indicate that surface diffusion has a significant role as the rate-limiting step. Thus surface diffusion is more distinct for the adsorption of Zn2+ as compared to the adsorption of Pb2+. 3.7. Adsorption isotherm studies Adsorption equilibrium data was fitted into different isotherm models and results are shown in Table 4, Figs. 8 and 9. Results Table 3 Parameters of kinetic models for the biosorption of Zn2+ and Pb2+ onto nanostructured cedar leaf ash. Pseudo-first-order model Metal Pb2+ Zn2+

qe(exp) (mg g−1) 0.94 0.72

k1 (min−1) 0.665 0.382

qe(cal) (mg g−1) 0.93 0.71

R2 0.999 0.998

RMSE 0.015 0.013

qe(cal) (mg g−1) 0.94 0.73

R2 0.999 0.990

RMSE 0.008 0.006

I (mg g−1) 0.862 0.563

R2 0.964 0.933

RMSE 0.006 0.020

Pseudo-second-order model Metal Pb2+ Zn2+

qe(exp) (mg g−1) 0.94 0.72

k2 (g mg−1 min−1) 3.690 1.504

Intraparticle diffusion model Metal Pb2+ Zn2+

Kp (mg g−1 min1/2) 0.013 0.031

Fig. 6. (a) Pseudo-first-order and pseudo-second-order kinetic models plots and, (b) intraparticle diffusion model plots for adsorption of Pb2+ onto nanostructured cedar leaf ash (Color figure can be seen in the online version of this article).

(Table 4) have shown that for Pb2+ adsorption, fitness values between predicted data and experimental data using all the isotherms models were good, but the Sips (Langmuir–Freundlich) isotherm model with minimum value for RMSE (0.128) and maximum value for R2 (0.999) could better represent the best fitting. Also, for Zn2 + ions, the Sips (Langmuir–Freundlich) model compared with the other models with higher R2 (0.999) and lower RMSE (0.085) provided a more consistent fit to the experimental data. Sips model at high adsorbate concentrations predicts monolayer adsorption onto surface of adsorbent like of the Langmuir isotherm, while at low adsorbate concentration, it follows Freundlich isotherm [29,60,61]. Thus, the applicability of the Sips isotherm model to the experimental values indicated that both heterogeneous surface and monolayer adsorption conditions exit in this study. Similar results have been reported by other researchers where Sips model has been fitted well for heavy metals biosorption [29,60–62]. In this study, n values of Freundlich model for two metal ions were calculated in the range of 1–10 (Table 4) suggesting that the adsorption is favorable [18,63]. Also, the isotherms with n N 1 are classified as isotherms with high affinity between adsorbate and adsorbent and it is indicative of chemisorption [64]. K values in Freundlich model is related to the bond strength. Values of this parameter for Pb2+ and Zn2+ are 1.564 and 0.581 (mg g−1) (L mg−1)1/n, receptivity which suggest that adsorption of Pb2+ has stronger affinity than Zn2+ onto nanostructured cedar leaf ash. The maximum adsorption capacity (qm) from Langmuir model

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Fig. 8. Freundlich, Langmuir, Redlich–Peterson and Sips (Langmuir–Freundlich) isotherm models plots for adsorption of Pb2+ onto nanostructured cedar leaf ash (Color figure can be seen in the online version of this article).

ionic radius, hydration energy, hydrated radius and electronegativity resulting in different adsorption capacities for different heavy metal ions [65]. Similar results have been reported by other researchers where adsorption capacity has been reported higher for Pb2+ ions as compared to Zn2+ ions by other biosorbents [51,56]. The essential characteristics of the Langmuir isotherm can be described by a dimensionless constant of separation factor or equilibrium parameter, RL, which is defined by the following equation [66,67]:

RL ¼

Fig. 7. (a) Pseudo-first-order and pseudo-second-order kinetic models plots, and (b) intraparticle diffusion model plots for adsorption of Zn2+ onto nanostructured cedar leaf ash (Color figure can be seen in the online version of this article).

were calculated as 7.23 mg g−1 and 4.79 mg g−1 for Pb2+ and Zn2+, respectively. Also qm from Sips (Langmuir–Freundlich) model for Pb2+ and Zn2 + were obtained as 8.045 mg g− 1 and 3.175 mg g− 1, respectively. Adsorption capacity for Pb2 + is approximately 2 times higher than Zn2 + which can be attributed to the lower hydration enthalpy (1485) and larger electronegativity (1.87) of Pb2 + ions than Zn2 + ions (hydration enthalpy (2047), electronegativity (1.65)). It has been reported in the literature that adsorption of heavy metal ions is largely influenced by the properties of heavy metal ions, such as

1 ð1 þ b  C i Þ

ð12Þ

where b is the Langmuir constant and Ci is the initial concentration of heavy metal ions. The value of RL indicates the type of the isotherm to be either unfavorable (RL N 1), linear (RL = 1), favorable (0 b RL b 1) or irreversible (RL = 0) [37,63]. The RL values calculated as 0.6 for Pb2+ and 0.58 for Zn2 + (between 0 and 1) indicating that Zn2 + and Pb2+ adsorption by nanostructured cedar leaf ash is favorable. 4. Conclusions The results of this study indicated that the nanostructured cedar leaf ash is a good biosorbent for the removal of Pb2+ and Zn2+ from aqueous solutions. The obtained results showed that the maximum percentage removal of heavy metals attained at pH 5, after 30 min of contact time and with a 20 g L−1 of adsorbent dose. The adsorption kinetics fitted well with pseudo-second-order kinetic model and the adsorption isotherms could be well described by the Sips model for Pb2+ and Zn2+.

Table 4 Parameters of isotherm models used for the biosorption of Zn2+ and Pb2+ onto nanostructured cedar leaf ash. Metal

Freundlich

Zn2+

K (mg g−1) (L mg−1)1/n n (g L−1) R2 RMSE – K (mg g−1) (L mg−1)1/n n (g L−1) R2 RMSE –

Pb2+

Langmuir 0.581 1.736 0.969 0.371 – 1.564 2.310 0.992 0.291 –

b (L mg−1) qm (mg g−1) R2 RMSE – b (L mg−1) qm (mg g−1) R2 RMSE –

Sips 0.097 4.788 0.986 0.245 – 0.167 7.232 0.998 0.145 –

b (L mg−1) qm (mg g−1) n R2 RMSE b (L mg−1) qm (mg g−1) n R2 RMSE

Redlich–Peterson 0.202 3.175 2.131 0.999 0.085 0.129 8.045 0.868 0.999 0.128

b (L mg−1) a (L g−1) n R2 RMSE b (L mg−1) a (L g−1) n R2 RMSE

0.001 0.318 2.278 0.995 0.117 0.231 1.343 0.936 0.998 0.142

L.D. Hafshejani et al. / Journal of Molecular Liquids 211 (2015) 448–456

Fig. 9. Freundlich, Langmuir, Redlich–Peterson and Sips (Langmuir–Freundlich) isotherm models plots for adsorption of Zn2+ onto nanostructured cedar leaf ash (Color figure can be seen in the online version of this article).

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