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Preparation of Activated Carbon From Olive StoneWaste: Optimization Study on the Removal of Cu2+,Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ From Aqueous SolutionUsing Response Surface MethodologyTamer M. Alslaibi a , Ismail Abustan b , Mohd Azmier Ahmad c & Ahmad Abu Foul da School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia , Nibong Tebal ,Pulau Pinang , Malaysiab School of Civil Engineering, Universiti Sains Malaysia, Engineering Campus , Nibong Tebal ,Pulau Pinang , Malaysiac School of Chemical Engineering, Engineering Campus, Universiti Sains Malaysia , NibongTebal , Pulau Pinang , Malaysiad Environmental Engineering, Islamic University of Gaza , PalestineAccepted author version posted online: 12 Jul 2013.

To cite this article: Journal of Dispersion Science and Technology (2013): Preparation of Activated Carbon From Olive StoneWaste: Optimization Study on the Removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ From Aqueous Solution Using ResponseSurface Methodology, Journal of Dispersion Science and Technology, DOI: 10.1080/01932691.2013.809506

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ACCEPTED MANUSCRIPT 1

Preparation of Activated Carbon From Olive Stone Waste: Optimization Study on the Removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ from Aqueous Solution Using

Response Surface Methodology

Tamer M. Alslaibi1, Ismail Abustan2, Mohd Azmier Ahmad3, Ahmad Abu Foul4

1School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Pulau Pinang, Malaysia, 2School of Civil Engineering, Universiti Sains Malaysia,

Engineering Campus, Nibong Tebal, Pulau Pinang, Malaysia, 3School of Chemical Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Pulau

Pinang, Malaysia, 4Environmental Engineering, Islamic University of Gaza, Palestine

Received 13 May 2013; accepted 25 May 2013.

Address correspondence to Ismail Abustan, School of Civil Engineering, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Pulau Pinang, Malaysia E-

mail: [email protected]

Abstract

The removal efficiencies of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ from aqueous solution

with olive stone activated carbon (OSAC) were investigated in this paper. Central

Composite Design (CCD) method was used to optimize the preparation of OSAC by

chemical activation using potassium hydroxide (KOH) as chemical agent. The optimum

conditions obtained were 715 °Cactivation temperature, 2 h activation time, and 1.53

impregnation ratio. This resulted in removal of 99.25% Cu2+, 94.98% Cd2+, 99.08% Ni2+,

99.33% Pb2+, 99.41% Fe2+, and 99.17% Zn2+, as well as 73.94% OSAC yield. The

surface characteristics of the AC prepared under optimized condition were examined by

pore structure analysis, scanning electron microscopy (SEM) and Fourier transform

infrared spectroscopy (FT-IR). The BET surface area, total pore volume and average pore

diameter of the prepared activated carbon were 886.72 m2/g, 0.507 cm3/g and 4.22 nm,

respectively. The equilibrium data of the adsorption was well fitted to the Langmuir and

the highest value of adsorption capacity (Q) on the OSAC was found for Fe2+ (57.47

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mg/g), followed by Pb2+ (22.37 mg/g), Cu2+ (17.83 mg/g), Zn2+ (11.14 mg/g), Ni2+ (8.42

mg/g), and Cd2+ (7.80 mg/g). The prepared OSAC can be used for efficient removal of

metals from contaminated wastewater.

KEYWORDS: Activated carbon, olive stone, adsorption, heavy metals, response surface

methodology (RSM)

1. INTRODUCTION

Wastewater pollution is one of the many important issues in environmental conservation.

Heavy metals, such as Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+, are toxic to human beings

and other living organisms if their concentrations exceed acceptable limits. These heavy

metals appear in wastewater discharged from hospitals [1] and different industries such as

smelting, metal plating, Cd–Ni battery production, phosphate fertilizer manufacture,

pigment mining, stabilizer production, and alloy manufacturing [2]. Regarding

environmental compartments, heavy metals constitute an ecological and human health

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issue, considering heavy metals do not undergo biological degradation, compared with

certain organic pollutants [3]. Cancer, anemia, liver, and kidney damage are among the

major human health issues that are caused by long-term exposure to heavy metals. Thus,

these toxic heavy metals should be removed from wastewater to protect the people and

the environment[4].

Activated carbons were used as adsorbent materials because of their large surface area,

microporous structure, high degree of surface reactivity, and high adsorption capacity[5].

In addition, the presence of different surface functional groups on activated carbon,

especially oxygen groups, leads to the adsorption of heavy metal ions [2]. Nevertheless,

the application fields of commercially available activated carbon are still limited due to

its high cost, given the use of a non-renewable and relatively expensive starting material

such as coal. The use of low-cost wastes and agriculture byproducts as alternative

solutions to producing activated carbon have been investigated in recent years and

continue to receive renewed attention. These alternatives include tobacco stems [6], rice

husks [7], almond shells [8], mango kernel [9], waste apricot [10], sawdust [11], and cuttlefish

bones [12].

Olive stone waste residue can be considered one of the best candidates among the

agricultural wastes as raw material for the production of activated carbon because it is

cheap and quite abundant, especially in Mediterranean countries. According to

International Olive Council [13], the world annual production of olive oil in 2012 was

more than 3 million tons, translating to approximately 15 million tons of olive cakes as

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the by-products. Middle East is one of the top olive- and olive oil-producing regions in

the world. Furthermore, about 95% of the world’s olive trees are in the Mediterranean

region[14].

The most important characteristic of activated carbon is its adsorption capacity, which is

highly affected by the preparation conditions of activated carbon, including activation

temperature, activation time, and chemical impregnation ratio[15] These conditions

influence the pore development and surface characteristics of the activated carbon

produced. Therefore, the challenge in activated carbon production is to produce very

specific carbons that are suitable for specific applications. Thus, the optimization of

preparation factors (activation temperature, activation time, and impregnation ratio) in the

performance of olive stone activated carbon (OSAC) for removing a group of heavy

metals were not investigated. In assessing the effect of treatments on quality attributes,

the use of an adequate experimental design is particularly important. Response surface

methodology (RSM) has been found to be a suitable tool for investigating the interactions

of two or more variables [16]. The optimization of experimental conditions using RSM is

widely applied in various processes. Some of the previous studies that applied RSM in

the preparation of activated carbons for dye removal used precursors such as bamboo

waste [17], waste tea [18], and rice husk[7].

The main objective of this research is to optimize the preparation conditions of OSAC for

the optimal removal of a group of metals, namely, Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+,

from aqueous solution. A central composite design (CCD) was selected to study

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simultaneously the effects of three activated carbon preparation variables (activation

temperature, activation time, and chemical impregnation ratio) on these responses.

Empirical models correlating the OSAC yield and removal of Cu2+, Cd2+, Ni2+, Pb2+,

Fe2+, and Zn2+ to the three variables were then developed. The characteristics and the

adsorption ability of the OSAC prepared under optimized conditions were investigated,

as well.

2. MATERIAL AND METHODS

2.1. Aqueous Solution

Metal solutions were prepared by dissolving appropriate amounts of NiCl2.6H2O(s),

CdCl2.H2O(s), Pb(NO3)2(s), CuCl2.2H2O(s), FeSO4.7H2O(s) and Zn(NO3)2.6H2O in

deionized water. Metal standard solutions of 1000 mg L−1 also purchased from Merck

were used for inductively coupled plasma optical emission spectroscopy (ICP-Optical

Emission Spectrometer; VARIAN 715-ES) calibration.

2.2. Preparation And Characterization Of Activated Carbon

OS waste was obtained from Gaza, Palestine. The OS waste was rinsed thrice with hot

water, thrice with cold water, and dried in an oven at 105 °C for 24 h to remove moisture

content. Once dried, they were ground and sieved for a particle size of 2.0 mm to 4.75

mm. Carbonization step was carried out at 600 °C for 1 h under purified nitrogen

(99.99%). Chemical activation method using potassium hydroxide (KOH) was used to

activate the char. Char (30 g) was impregnated by certain amount of KOH. The amount

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of KOH used was adjusted to give a certain impregnation ratio (weight of activating

agent: weight of char) of 0.5:1, 1.25:1 and 2:1. The impregnation ratio is given by:

( ) ( ) ( )Impregnation ratio IR dry weight of KOHpellets : dry weight of char=

Deionized water was then added to dissolve all the KOH pellets. Impregnation was

carried out for 24 h at room temperature, thus incorporating all the chemicals in the

interior of the particles. The activation of KOH-impregnated char was carried out at

different temperatures ranging from 400 °C to 800 °C and time 1 h to 3 h under a

nitrogen flow of 150 cm3 g−1 and at a heating rate of 10 °C min−1 in a vertical muffle

furnace. After activation, the samples were cooled down under the nitrogen flow and

were washed sequentially several times with hot deionized water (70 °C) and HCl

(0.1 M) until the pH of the washed solution was within the range 6.5 to 7. Finally,

samples were dried in an oven (LARGE 122AK3002) at 110 °C for 24 h and then stored

in containers.

The surface area, pore volume and average pore diameter of the samples were determined

by using Micromeritics ASAP 2020 volumetric adsorption analyzer. The BET surface

area was measured from the adsorption isotherm using Brunauer-Emmett-Teller equation.

The total pore volume was estimated to be the liquid volume of nitrogen at a relative

pressure of 0.98. The surface morphology of the samples was examined using a scanning

electron microscope (Quanta 450 FEG, Netherland). Chemical characteristics of surface

functional group of the activated carbon was detected by diluting in K-Br pellets were

recorded with FTIR spectroscope (IR Prestige 21 Shimadzu, Japan) in the 400-4000 cm-1

wave number range.

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2.3. Experimental Design

The parameters used in preparing the activated carbon from OS waste were studied using

the standard RSM design called the central composite design (CCD). The CCD was

chosen as the experimental design. This method is suitable for fitting a quadratic surface

and helps optimize the effective parameters based on the higher responses obtained with

a minimum and statistically significant number of experiments, in addition to analyzing

the interaction between parameters (17).The OSAC was prepared using the chemical

activation method. The variables considered were the activation temperature (X1),

activation time (X2), and chemical impregnation ratio (X3). These three variables,

together with their respective ranges, were chosen based on the literature and our

preliminary studies. The ranges and the levels -1, 0, and 1 of the variables investigated

include 400, 600, and 800 °C for activation temperature; 1, 2, and 3 h for activation time;

and 0.5, 1.25 and 2 for impregnation ratio.

The most important parameters affecting the characteristics of activated carbon include

activation temperature, activation time, and chemical impregnation ratio [19]. Generally,

the CCD consists of 2k factorial runs with 2k axial runs and kc center runs (six

replicates). For this case, a 23 full factorial CCD for the three variables, consisting of 8

factorial points, 6 axial points, and 6 replicates at the center points, were employed,

indicating that, altogether, 20 experiments were required (2k+ 2k + 6), where k is the

number of independent variables. The center points were used to determine the

experimental error and the reproducibility of the data. The independent variables were

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coded to the (−1, 1) interval where the low and high levels are coded as −1 and +1,

respectively. The six axial points are located at (± α, 0, 0), (0, ±α, 0) and (0, 0, ±α), and

the six replicates points located at the center (0, 0, 0) were run. Alpha (α) is the distance

of the axial point from the center and makes the design face-centered. The responses

were the carbon yield (Y1) and percentage removals of Cu (Y2), Cd (Y3), Ni (Y4), Pb

(Y5), Fe (Y6), and Zn (Y7).

The complete design matrixes of the experiments carried out in additionof the results

obtained are shown in Table 1. Each response was used to develop an empirical model

that correlated the response to the three activated carbon preparation variables using a

second-degree polynomial equation as given by Eq. (1):

12

1 1 1 1

k k k k

o i i ii i ij i j ii i i j i

Y b b x b x b x x e−

= = = = +

= + + + +∑ ∑ ∑∑ (1)

where Y is the predicted response, b0 the constant coefficient, bi the linear coefficients, bij

the interaction coefficients, bii the quadratic coefficients, and xi and xj the coded values of

the activated carbon preparation variables.

Design-Expert software (version 6.0.7, Stat-Ease, Inc., Minneapolis, USA) was used for

regression analysis of the experimental data to fit the second-degree polynomial equation,

as well as for analyses of variance (ANOVA) and response surface contours.

2.4. Activated Carbon Yield

The activated carbon yield was calculated based on the following equation:

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( ) % 100c

o

WYieldW

= × (2)

where Wc(g) is the dry weight of the final activated carbon, and Wo(g) is the dry weight

of the char.

2.5 Batch Equilibrium Studies

Batch adsorption was performed in 20 flasks of 250 ml Erlenmeyer flasks where 100 ml

of aqueous solution with initial Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ concentrations of

20 mg L-1 was placed in each flask. Prepared activated carbon (0.3 g) with a particle size

range of 2 mm to 4.75 mm was added to each flask and kept in an isothermal shaker of

200 rpm at 30 °C until equilibrium was reached. After agitation, the solid was removed

by filtration through a 0.45 µm pore size Whatman membrane filter paper. The final

metal concentration in the filtrates, as well as in the initial solution was determined by

inductively coupled plasma optical emission spectroscopy (ICP-Optical Emission

Spectrometer; VARIAN 715-ES) calibration. The sorbed metal concentrations were

obtained from the differences between the initial and final metal concentrations in

solution. The percentage removal at equilibrium was calculated as follows:

( ) 0

0

% 100eRemoval −= ×

(3)

where Co and Ce are the liquid-phase concentrations at the initial state and at equilibrium

(mg l-1), respectively.

The amount of metals adsorbed per unit mass of adsorbent at equilibrium conditions, qe

(mg/g), was calculated by:

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( ) o eC C VeW

q −=

(4)

Where, qe (mg/g) is the amount of solute adsorbed per unit weight of adsorbent; Co and

Ce (mg/L) are the liquid-phase concentrations of adsorbate at initial and equilibrium

conditions, respectively; V (L) is the volume of the solution; and W (g) is the mass of

adsorbent used.

The effects of pH on metals removal were tested respectively by varying the pH from 2 to

6, with initial metals concentration of 20 mg/L and adsorption temperature of 30 °C. The

initial pH of the metals solution was adjusted by addition of 0.10 M HCl or NaOH.

2.6 Adsorption Isotherm

Different models, Langmuir and Freundlich were used to investigate the equilibrium

behavior of metals adsorption on the prepared OSAC. Langmuir adsorption isotherm

assumes monolayer adsorption, with no lateral interaction and steric hindrance between

the adsorbed molecules, even on the adjacent sites. The form of the Langmuir isotherm

equation is given as:

1

ee

e

QbCqbC

=+

(5)

where Ce (mg/L) is the equilibrium liquid-phase concentration of metals, qe (mg/g) is the

equilibrium uptake capacity, Q (mg/g) is the Langmuir constant related to adsorption

capacity, and b (L/mg) is the Langmuir constant related to the energy of sorption, which

quantitatively reflects the affinity between the sorbent and the sorbate.

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Another characteristic parameter of the Langmuir isotherm is the dimensionless factor

RL, released to the shap of the isotherm. Its value indicates either unfavorable (RL> 1),

linear (RL =1), favorable (0 <RL< 1), or irreversible (RL = 0) adsorption and it is evaluated

as [20]:

1 (1 )L

o

RbC

=+

(6)

where b is the Langmuir constant and Co is the initial pollutant concentration (mg/L).

Freundlich isotherm is an empirical model describing the multilayer adsorption, with

non-uniform distribution of adsorption heat and affinities over the heterogeneous

surface.The Freundlich model is based on sorption on a heterogeneous surface of varied

affinities. The form of Freundlich model is given as:

1/ne f eq K C= (7)

where qe (mg/g) is the amount of metals adsorbed at equilibrium, Ce (mg/L) is the

adsorbate concentration, Kf (m/g)(L/mg)1/n is the Freundlich constant related to

adsorption capacity, and 1/n is the Freundlich constant related to sorption intensity of the

sorbent.

3. RESULTS AND DISCUSSION

3.1. Model Development

The whole design matrix together with the values of the responses gained from the

experimental works is given in Table 1. For the responses of the OSAC yield and

removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+, the quadratic model was selected, as

suggested by the software. The responses were correlated with the three variables studied

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by multiple regression analysis using the second-order polynomial presented in Eq. (1).

The coefficients of the model equation and their statistical significance were evaluated

using Design-Expert 6.0.7 software. In this study, insignificant model terms, which have

limited influence, were excluded from the study to improve the model. Based on the

results, the quadratic regression models for removal of Cu2+ (Y1), Cd2+ (Y2), Ni2+ (Y3),

Pb2+ (Y4), Fe2+ (Y5), and Zn2+ (Y6), and the OSAC yield (Y7) in terms of coded factors

are expressed, as follows:

Cu2+ removal (%)

=

+98.92 +5.53 X1 +5.90 X3 -6.71 X12-4.53 X1 X3

Cd2+ removal (%)

=

+92.30 +10.10 X1 +23.20 X3 -35.61 X32 -7.89 X1 X3

Ni2+ removal (%)

=

+98.09 +10.02 X1 -2.16 X2 +25.20 X3 -7.94 X12 -27.87 X3

2

-11.58 X1 X3

Pb2+ removal (%)

=

+98.97 +3.34 X1 +3.31 X3 -3.62 X12-3.01 X1 X3

Fe2+ removal (%)

=

+99.11 +1.87 X1 +1.87 X3 -1.81 X12 +0.44 X1 X2 -1.79 X1

X3

Zn2+ removal (%)

=

+97.57 +16.75 X1 -2.68 X2 +22.81 X3 -10.56 X12 -16.21

X32 -15.16 X1 X3

Yield (%) = +79.20 -5.08 X1 -2.90 X2 -8.47 X3 -3.60 X22

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where, X1, X2, and X3 are the coded values of the activation temperature, activation time,

and chemical impregnation ratio, respectively. The quality of the model developed was

evaluated based on the coefficient of determination R-squared (R2). Standard deviation

values are presented in Table 2, and its statistical significance was checked by the F-test

in the same program. In fact, the models developed seems to be the best at low standard

deviation and high R2 statistics, which is closer to unity, considering it will yield

predicted values closer to the actual values of the responses [7]. In this experiment, the

adjusted R2 values of the quadratic model to the experimental data forthe OSAC yield

and removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ranged between 0.8997 and 0.9815.

These high R2 values indicate that the predicted values for the OSAC yield and removal

of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+would be more accurate and closer to its actual

value.

3.2 Statistical Analysis

ANOVA was further carried out to justify the adequacy of the models. The results of the

second-order response surface model fitting in the form of ANOVA are given in Table 2

for removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+, as well asOSAC yield, respectively.

Data given in Table 2 demonstrate that all the models were significant at the 5%

confidence level, given that P values were less than 0.05. The values of the correlation

coefficient (R2 = 0.9421, 0.9741, 0.9874, 0.9210, 0.9594, 0.9836 and 0.9453) obtained in

the present study for removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+ and Zn2+, as well asOSAC

yield were higher than 0.80. For a good fit of model, the correlation coefficient should be

at a minimum of 0.80[21]. A high R2 value close to 1 demonstrates good agreement

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between the calculated and observed results within the range of the experiment and

shows that a desirable and reasonable agreement with adjusted R2 is necessary[22].

Diagnostic plots, such as the predicted versus actual values in Fig. 1 (a–f), help determine

the model satisfactoriness. The predicted versus actual values plots of the parameters of

removal are presented in Fig. 1 (a–f). These plots show an adequate agreement between

real data and the ones gained from the models. Hence, all predictive models can be used

to navigate the design space defined by the CCD.

The coefficient of variance (CV), as the ratio of the standard error of the estimate to the

mean value of the observed response (as a percentage), identifies the reproducibility of

the model. A model typically can be considered reproducible if its CV is not more than

10% [23]. According to Table 2, the CV values obtained for all responses studied are

relatively small with none of them exceeding 6.50%. The statistical results obtained,

show that the above models adequately predicted removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+,

and Zn2+, as well as OSAC yield within the range of variables studied.

3.3. Response Surface Contours

The use of three-dimensional plots of the regression model is highly recommended for

the graphical interpretation of the interactions[24]. Hence, the three-dimensional response

surface curves were plotted using a statistically significant model to understand the

interaction of the medium components. Three-dimensional surface graphs and contour

plots between the factors are presented in Figs. 2(a–g). The representations of the models

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simplify an investigation of the effects of the experimental factors on the responses. The

response plots display clear peaks, indicating the maximum values of the responses are

attributed to temperature (X1) and the impregnation ratio (X3) in the design space. Based

on the F-values (Table 2), the chemical impregnation ratio (X3) presented the largest

ranges of F-values (53.39-461.18), followed by activation temperature (X1) ranges

(43.46-171.13), while the activation time (X2) presented the least ranges of (3.39-19.39).

The chemical impregnation ratio and activation temperature significantly affected the

removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ removal for the prepared activated

carbon, compared with activation time (X2).

Figure 2 (a–g) displays the three-dimensional response surfaces constructed to show the

interaction effects of the activated carbon preparation variables (activation temperature

and chemical impregnation ratio) on the removal of Cu2+ (Y1), Cd2+ (Y2), Ni2+ (Y3), Pb2+

(Y4), Fe2+ (Y5), and Zn2+ (Y6), as well as the yield (Y7). For these plots, the activation

time was fixed at optimum level (t = 2 h). As shown in Fig. 2 (a–g), the removal

generally increases with increasing activation temperature and chemical impregnation

ratio.

The results obtained agreed with the findings of [17], who reported that the activation time

did not significantly affect the pore structure of activated carbon produced from bamboo

waste. Moreover, the pore characteristics changed significantly with the activation

temperature and with the KOH impregnation ratio. Similarly, [25] reported that the

activation time did not significantly affect the pore structure of activated carbon produced

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from cassava peel, whereas the activation temperature and the KOH impregnation ratio

significantly changed the pore characteristics. [26] also found that activation time did not

significantly affect the surface area obtained for activated carbons prepared from apricot

stones using steam activation. [27] similarly reported that activation time showed the least

significant effect on the Remazol Brilliant Blue R (RBBR) removal of mangosteen peel

activated carbon, whereas both the activation temperature and impregnation ratio were

found to significantly affect this response.

In this research, the increase in activation temperature increases the removal of Cu2+,

Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+Fig. 2 (a–f) and decreases the carbon yield Fig. 2 (g). The

maximum removal occurred at temperatures higher than 600 °C because the increase in

activation temperature enhanced the existing pores and created new pores in the material

by increasing the reaction rate between the precursor and the chemical impregnate [28]. At

higher activation temperatures, the activated carbon yield was lesser due to increasing

volatilization rate from the sample. Shevkoplyas and Saranchuk, [29] reported that the

impregnation of coal with KOH causes the breaking of C–O–C and C–C bonds, thereby

facilitating coal decomposition during pyrolysis, hence decreasing the carbon yield.

Ahmad and Alrozi [27] also observed the similar trend where less mangosteen peel

activated carbon yield and higher removal of RBBR obtained at higher activation

temperature. Chowdhury et al.,[30] reported that the temperature and impregnation ratio is

proportional to the removal percentages of Cu2+ and Pb2+ of activated carbon produced

from kenaf fiber up to a certain limit. Increased temperature and impregnation ratio

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enhances the reaction between KOH and the char in the presence of CO2, resulting in a

more porous structure that is suitable for adsorption.

Similarly, an increase in the KOH impregnation ratio increases the removal of Cu2+,

Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+ and decreases carbon yield, as shown in Fig. 2 (a–g). The

maximum removal occurred at an impregnation ratio between 1.25 and 2.0. Accordingly,

at a higher impregnation ratio, heavy metal removal increased as the impregnation ratio

increased from 1.25 to 2 because the impregnation ratio plays an important role in

creating and widening the pores in the activated carbon, thus contributing to the increase

in surface area and adsorption capacity [31]. The intercalation of chemicals used for the

impregnation ratio appeared to be responsible for the drastic expansion of the carbon

material and, hence, the creation of a large surface area and high pore volume. Tan et al.,

[16] mentioned that the KOH:char impregnation ratio played a decisive role in pore

formation. At a high KOH impregnation ratio, the pore development was mostly due to

the intercalation of potassium metal in the carbon structure. As the KOH:char IR

increased, the catalytic oxidation also caused the widening of pores, therefore increasing

the carbon uptake, as well [31]. The increase in KOH might accelerate the reaction rate,

thus increasing the quantity of pores. Nevertheless, a maximum point was attained for the

KOH:char impregnation ratio, beyond which, further impregnation would reduce the

carbon uptake because an excessive amount of KOH could cause further the reaction

between KOH and carbon, thereby destroying the pore structure formed in the previous

stage. Consequently, a reduction in surface area would occur [32]. In addition, at higher

impregnation ratios, the chemical will form insulating layers that cover and block the

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pores [33]. Foo and Hameed, [34] also observed similar results where the excess of K2CO3

and metallic potassium left on the carbon surface blocked the pores, thereby dramatically

decreasing the accessible area. Furthermore, the pores would be widened and burnt off.

Solution pH also affects adsorption by regulating the adsorbent surface charge as well as

degree of ionization of the adsorbate molecules. The percentages of metals removals

using OSAC were found to increase significantly with the increase in solution pH from

pH 3 to pH 6 and the highest metals removals were achieved at pH 5. According to Božić

et al. [35] at low pH<3 the minimal removal may be an effect of the higher concentration

and high mobility of the H+, which competes with metal ions on the active sites on the

sorbent surface, resulting in its preferential adsorption rather than the metal ions.

Therefore, H+ ions react with anionic functional groups on the surface of OSAC and

results in the reduction of the number of binding sites available for the adsorption of

Cu2+, Cd2+, Ni2+, Pb2+, Fe2+ and Zn2+. This increase may have been an effect of the

presence of negative charge on the surface of the adsorbent that may have been

responsible for the metal binding because solution pH can affect the charge of OSAC

surfaces [36]. In addition, at higher pH values, the lower number of H+ and greater number

of ligands with negatives charges result in greater metal adsorption. The same trend was

observed by several researchers who studied metal sorption by different biomaterials,

namely, copper by sawdust [37], and zinc, lead, and cadmium by jute fibers [38], lead and

cadmium by [39], cadmium by orange wastes [40].

3.4. Verification Of The Model And Optimum Condition

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RSM has been used successfully to optimize the parameters affecting the removal of

Cu2+, Cd2+, Ni2+, Pb2+, Fe2+,and Zn2+, as well as OSAC yield. Nevertheless, optimizing

these responses under the same conditions is difficult, considering the interest regions of

factors are different. Numerical optimization was selected as the desired goal for each

factor and response from the menu. According to the software optimization step, the

desired goal for each operational condition (activation temperature, activation time, and

impregnation ratio) was chosen “within” the range. The responses (removal of Cu2+,

Cd2+, Ni2+, Pb2+, Fe2+, and Zn2+, as well as OSAC yield) were defined as the maximum

for achieving the highest performance. The value of desirability (0.99) obtained shows

that the estimated function may represent the experimental model and desired conditions.

The predicted and experimental results for the removal of Cu2+, Cd2+, Ni2+, Pb2+, Fe2+,

and Zn2+, as well as the OSAC yield obtained at optimum conditions are listed in Table 3.

The optimum activated carbon was obtained at 715 °C activation temperature, 2 h

activation time, and 1.53 impregnation ratio resulted in 73.94% OSAC yield and removal

of 99.25% Cu2+, 94.98% Cd2+, 99.08% Ni2+, 99.33% Pb2+, 99.41% Fe2+,and 99.17% of

Zn2+. The experimental values obtained were in good agreement with the values

predicted from the models, with relatively small errors between the predicted and the

actual values as shown in Table 3. This result agrees with the work done by [30].

3.5. Characterization Of OSAC Prepared Under Optimum Conditions

The BET surface area, mesopore surface area, total pore volume and average pore

diameter of the prepared activated carbon were 886.72 m2 g−1, 740.66 m2 g−1, 0.507 cm3

g−1 and 4.22 nm, respectively. The maximum value of activated carbon yield was found

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to be 38.07%. Besides, the average pore diameter of the activated carbon was found to be

4.92 nm, indicated that the activated carbon prepared was in the mesopores region

according to the International Union of Pure and Applied Chemistry (IUPAC), pores are

classified as micropores (<2 nm diameter), mesopores (2–50 nm diameter) and

macropores (>50 nm diameter)[41]. The activated carbon resulting from OS waste

contained relatively large surface area and total pore volume compared to various

adsorbents Table 4 and also commercially available activated carbons such as F100 and

BPL from Calgon Corporation with BET surface area of 957 and 972 m2 g−1in addition to

totalpore volume of 0.526 and 0.525 cm3 g−1, respectively. According to the activation

process using KOH as chemical activating agent, the high BET surface area, total pore

volume and pore developments of the prepared activated carbon were found. The

chemical agent is dehydrating agent that penetrates deep into the structure of the carbon

causing pores to develop [42].

Figures 3(a), 3(b), 3(c) and 3(d) show the SEM images of the precursor, char, OSAC and

the exhausted OSAC, respectively. The surface texture of raw and char OS were uneven,

rough, and undulating, with very little pores available on the surface. However, after

activation treatment, large and well-developed pores were clearly found on the surface of

the OSAC, compared with the original precursor and char. The KOH and activation

process were effective in creating well-developed pores on the surfaces of the OSAC,

hence leading to activated carbon with a large surface area and good porous structure

(mesopores). Similar observations were reported by other researchers in their studies on

preparing activated carbons from coconut husk [16], mangosteen peel[27], and oil palm

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fiber [43].Therefore, after heavy metals adsorption, pores were exhausted with

contaminants.

4. CONCLUSION

In the present study, CCD method was used to optimize the preparation of activated

carbon from olive stone with KOH as activator. The impregnation ratio and activation

temperature were more highly significant factors on metals removal for the prepared AC,

compared with activation time. The impregnation ratio was the greatest impact factor on

the OSAC yield followed by activation temperature and activation time. The optimum

conditions were activation temperature of 715 °C, activation time of 2 h, and

impregnation ratio of 1.53. N2 adsorption showed BET surface area of the prepared

activated carbon was 886.72 m2 g−1. Scanning electron microscopy (SEM) and Fourier

transform infrared spectroscopy (FT-IR) investigation evidenced that the presence of

opened-pore structure and different functionalities on the carbon surfaces compared with

those of olive stone. Langmuir isotherms better fit the experimental equilibrium data of

metals adsorption on the prepared OSAC. The maximum adsorption capacity (Q) on the

OSAC was found for Fe2+ (57.47 mg/g), followed by Pb2+ (22.37 mg/g), Cu2+ (17.83

mg/g), Zn2+ (11.14 mg/g), Ni2+ (8.42 mg/g), and Cd2+ (7.80 mg/g). The prepared OSAC

can be used for efficient removal of metals from contaminated wastewater. The

optimization results obtained by RSM can be used for preparing activated carbon to be

used for heavy metals removal at large scale columns in treatment plants.

ACKNOWLEDGMENTS

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The authors wish to acknowledge the Universiti Sains Malaysia (USM) for its financial

support under the USM and TWAS Fellowship scheme and RU-PRGS grant scheme (No.

8045048) and acknowledge Ministry of Higher Education, Malaysia for providing LRGS

grant No. (203/PKT/670006) and (03-01-05-SF0502) to conduct this study.

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Table 1. Experimental factors and experimental responses

Factors Responses

Ru

n

no.

Type X1:

tem

p

(°C

)

X2:

tim

e

(h)

X3:

IR

Cu

remov

al Y1

(%)

Cd

remov

al Y2

(%)

Ni

remov

al Y3

(%)

Pb

remov

al Y4

(%)

Fe

remov

al Y5

(%)

Zn

remov

al Y6

(%)

Yiel

d Y7

(%)

1 Cent

er

600 2 1.2

5

99.60 95.45 99.06 99.37 99.27 99.51 79.1

0

2 Cent

er

600 2 1.2

5

98.33 95.24 98.54 98.34 99.24 97.82 78.1

3

3 Cent

er

600 2 1.2

5

98.69 93.99 98.48 98.18 99.21 98.76 78.5

3

4 Cent

er

600 2 1.2

5

99.81 94.47 99.06 99.62 99.27 98.87 79.0

3

5 Cent

er

600 2 1.2

5

99.02 94.52 98.92 98.94 99.29 99.34 77.8

1

6 Cent

er

600 2 1.2

5

99.80 95.58 99.43 99.59 99.27 99.70 78.8

1

7 Axia

l

400 2 1.2

5

87.71 82.94 83.76 91.73 95.86 69.72 87.3

0

8 Axia

l

800 2 1.2

5

99.59 94.58 98.61 99.71 98.94 99.36 74.7

4

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9 Axia

l

600 1 1.2

5

99.75 86.66 93.03 99.19 99.27 92.88 80.6

8

10 Axia

l

600 3 1.2

5

98.95 89.62 96.12 98.42 99.23 98.61 67.7

3

11 Axia

l

600 2 0.5

0

95.91 37.43 47.36 98.81 97.75 58.30 86.2

6

12 Axia

l

600 2 2.0

0

99.34 80.47 95.13 99.22 99.27 99.48 72.3

2

13 Fact 400 1 0.5

0

73.89 15.62 14.97 85.80 92.03 17.28 89.8

8

14 Fact 800 1 0.5

0

96.52 60.25 61.24 98.15 98.27 87.71 82.8

7

15 Fact 400 3 0.5

0

76.01 11.26 13.50 84.17 90.73 14.04 87.9

8

16 Fact 800 3 0.5

0

93.19 42.90 56.22 96.55 99.48 73.17 78.4

2

17 Fact 400 1 2.0

0

97.47 79.57 97.17 99.55 99.75 99.26 75.7

1

18 Fact 800 1 2.0

0

99.61 82.29 87.04 99.35 99.59 97.67 63.3

5

19 Fact 400 3 2.0

0

98.32 73.36 79.76 98.78 98.76 86.18 69.3

1

20 Fact 800 3 2.0 99.78 83.75 86.23 99.67 99.59 96.05 60.0

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0 5

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Table 2. ANOVA for analysis of variance and adequacy of the quadratic model for Cu2+,

Cd2+, Ni2+, Pb2+, Fe2+, Zn2+ and OSAC yield

Response Source

of data

Sum of

squares

Degree

of

freedom

Mean

square

F-

value

Prob.

>F

Comment

Cu

removal

(%)

Model 1043.13 5 260.76 61.01 <

0.0001

SD= 2.07,

CV= 2.16,

R2=

0.9421,

Adj R2 =

0.9266.

1X 305.75 1 305.75 71.53 <

0.0001

3X 348.08 1 348.08 81.44 <

0.0001

21X 225.25 1 255.25 52.70 <

0.0001

1 3X X 163.95 1 163.95 38.36 <

0.0001

Residual 64.11 15 4.27 - -

Cd

removal

(%)

Model 13297.24 5 3310.49 141.02 <

0.0001

SD= 4.85,

CV= 6.50,

R2=

0.9741,

Adj R 2 =

0.9672.

1X 1020.35 1 1020.35 43.46 <

0.0001

3X 5381.05 1 5381.05 229.22 <

0.0001

23X 6341.96 1 6341.96 270.15 <

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0.0001

1 3X X 498.60 1 498.60 21.24 0.0003

Residual 352.13 15 23.48 - -

Ni

removal

(%)

Model 14003.78 6 2333.96 169.44 <

0.0001

SD = 3.71,

CV= 4.63,

R2=

0.9874,

Adj R 2 =

0.9815.

1X 1003.74 1 1003.74 72.87 <

0.0001

2X 46.75 1 46.75 3.39 0.0884

3X 6352.57 1 6352.57 461.18 <

0.0001

21X 201.64 1 201.64 14.64 0.0021

23X 2486.34 1 2486.34 180.50 <

0.0001

1 3X X 1073.14 1 1073.14 77.91 <

0.0001

Residual 179.07 13 13.77 - -

Pb

removal

(%)

Model 361.02 5 89.76 43.73 <

0.0001

SD= 1.43,

CV= 1.47,

R2=

0.9210,

Adj R 2 =

0.9000.

1X 111.61 1 111.61 54.38 <

0.0001

3X 109.58 1 109.58 53.39 <

0.0001

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21X 65.59 1 65.59 31.96 <

0.0001

1 3X X 72.26 1 72.26 35.21 <

0.0001

Residual 30.79 15 2.05 - -

Fe

removal

(%)

Model 113.72 6 22.72 66.16 <

0.0001

SD= 0.59,

CV= 0.60,

R2=

0.9594,

Adj R 2 =

0.9449.

1X 35.15 1 35.15 102.35 <

0.0001

3X 34.97 1 34.97 101.83 <

0.0001

21X 16.35 1 16.35 47.62 <

0.0001

1 2X X 1.53 1 1.53 4.45

0.0600

1 3X X 25.60 1 25.60 74.54 <

0.0001

Residual 4.81 14 0.34 - -

Zn

removal

(%)

Model 12818.63 6 2136.44 130.32 <

0.0001

SD= 4.05,

CV= 4.81,

R2=

0.9836,

Adj R 2 =

1X 2805.37 1 2805.37 171.13 <

0.0001

2X 71.64 1 71.64 4.37 0.0568

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3X 5205.13 1 5205.13 317.51 <

0.0001

0.9761.

21X 356.60 1 356.60 21.75 0.0004

23X 840.92 1 840.92 51.30 <

0.0001

1 3X X 1838.60 1 1838.60 112.15 <

0.0001

Residual 213.12 13 26.35 - -

Model 1123.81 4 280.95 64.81 <

0.0001

SD= 2.08,

CV= 2.69,

R2=

0.9453,

Adj R 2 =

0.9307.

OSAC

yield (%)

1X 257.65 1 257.65 59.43 <

0.0001

2X 84.08 1 84.08 19.39 0.0005

3X 717.11 1 717.11 165.41 <

0.0001

22X 64.97 1 64.97 14.99 0.0015

Residual 65.03 15 4.34 - -

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Table 3. Verification of experimental and predicted values of prepared activated carbon

under the optimum conditions (715 oC, 2 h, 1.53 IR) predicted by RSM

Resbonse Experamintal Predicted Error (%) Desirability

Cu2+ removal (%) 99.25 99.99 0.74 0.99

Cd2+ removal (%) 94.98 97.61 1.05

Ni2+ removal (%) 99.08 99.99 0.91

Pb2+ removal (%) 99.33 99.99 0.66

Fe2+ removal (%) 99.41 99.96 0.55

Zn2+ removal (%) 99.17 99.99 0.82

OSAC yield (%) 73.94 74.79 1.14

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Table 4. Comparison of the BET surface area onto various adsorbents

Material Surface Area (m2

g−1)

References

Waste tea 820 (40)

Bamboo waste 988.24 (15)

Date Stone 730 (41)

Rice husk 750 (42)

Bagasse 674 (42)

Rice bran 652 (43)

Rice husk 604 (6)

Oil palm fibre 521 (44)

Olive Stone 886.72 Present work

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Table 5. Langmuir and Freundlich isotherm parameters for the adsorption of Fe2+, Pb2+,

Cu2+, Zn2+, Ni2+, and Cd2+ onto CHOS.

Paramete

r

Langmuir Isotherm Freundlich Isotherm

Q (mg/g) b (L/mg) R2 RL K (mg/g) (L/mg)1/n 1/n R2

Fe2+ 57.47 3.702 0.992 0.013 34.04 0.391 0.919

Pb2+ 22.37 2.847 0.993 0.017 12.90 0.259 0.941

Cu2+ 17.83 3.134 0.990 0.016 11.03 0.222 0.947

Zn2+ 11.14 7.184 0.982 0.007 8.83 0.141 0.947

Ni2+ 8.42 5.094 0.990 0.010 6.41 0.137 0.905

Cd2+ 7.80 3.793 0.992 0.013 6.09 0.099 0.931

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Figure 1. Design-expert plot; predicted vs. actual values plot for (a) Cu2+ removal, (b)

Cd2+ removal, (c) Ni2+ removal, (d) Fe2+ removal, (e) Pb2+ removal, and (f) Zn2+ removal

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Figure 2. Three-dimensional response surface plot: (a) Cu2+ removal, (b) Cd2+ removal,

(c) Ni2+ removal, (d) Fe2+ removal, (e) Pb2+ removal, and (f) Zn2+ removal (effect of

activation temperature and chemical impregnation ratio, t = 2 h)

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Figure 3. Scanning electron micrograph: (a) OS raw (b) OS char (c) OSAC (d) OSAC

exhausted (magnifications: 2000x)

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b journal of dispersion science and technology c...sep 30, 2013 · informa ltd registered in...

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