isotherm and kinetic modeling of adsorption...

Journal of Chemical Technology and Metallurgy, 51, 2, 2016

188

Journal of Chemical Technology and Metallurgy, 51, 2, 2016, 188-201

ISOTHERM AND KINETIC MODELING OF ADSORPTION OF DYESTUFFS ONTO KOLA NUT (Cola acuminata) SHELL ACTIVATED CARBON

Nwabanne T. Joseph, Okpe Emmanuel Chinonye, Igbokwe K. Philomena, Asadu C. Christian, Onu Chijioke Elijah

Department of Chemical EngineeringNnamdi Azikiwe University, P. M. B. 5025 AwkaAnambra State, NigeriaE-mail: [email protected]

ABSTRACT

Kola nut shell activated carbon (KNS-AC) as a cost effective adsorbent for the removal of dyes from industrial waste-water effluents was investigated in this work. The chemical method of activation using zinc chloride (ZnCl2), was used to prepare the carbon. The sample was carbonized in a muffle furnace for 1 hour at 5000C. Some physical properties of the carbon such as surface area, pH, moisture content, ash content, bulk density were determined. Both the activated and non-activated carbons were characterized using the Fourier Transform Infrared (FTIR) spectroscopy to determine the functional groups, and Scanning Electron Microscopy (SEM) to examine the surface morphology of the carbon. Batch adsorption studies were carried out by studying the effects of pH, initial ion concentration, contact time, adsorbent dosage and temperature, on the adsorption process. Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models were used to describe the adsorption mechanism. The experimental data was found to fit very well to the Freundlich iso-therm model. Kinetic models, such as Pseudo second-order, Intra-particle diffusion, Elovich and Power function models were used to fit the experimental data. The results showed that the Pseudo second-order model best described the kinetics of the adsorption process. The thermodynamic factors were evaluated. The negative values of free energy change (-7.182 KJ mol-1 and -7.693 KJ mol-1 and enthalpy change -27.57 KJ mol-1 and -21.31 KJ mol-1) indicate that the adsorption pro-cess is spontaneous and exothermic.

Keywords: adsorption, dyestuffs, isotherm, kinetics, thermodynamics.

Received 07 May 2015Accepted 07 November 2015

INTRODUCTION

The over-dependence of local industries on imported raw materials is currently the ban of the economy of developing countries. Thus the search and exploitation of a close substitute to such raw materials is attracting global attention. Our nation, Nigeria, is gifted and en-dowed with many mineral resources and biomass, which include; crude oils, palm oil, palm kernel shell, coal, clay, rubber, kola nuts etc. Some of these natural mineral materials are exported, while some at times are refined for the purpose of foreign exchange. The release of large

quantities of dyes into water bodies by textile industries poses serious environmental problems due to the persistent and recalcitrant nature of some of these dyes. According to one estimate, over 7 x 105 tonnes and approximately 10,000 different types of dyes and pigments, are produced worldwide annually [1]. Untreated or partially treated effluents from other industries, namely paper, plastics, leather, cosmetics, food, woolen, etc., also contribute to the pollution load. The colouration of the water by the presence of dyes, even in small concentrations, is easily detectable [2] and it might have an inhibitory ef-fect on the process of photosynthesis and thus affecting


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the land flora and the aquatic ecosystem. The anaerobic break down of some dyes in the sediments and / or their incomplete bacterial degradation often produces toxic amines [3].

Consequently, the removal of colour from effluents is one of the major environmental problems. In this concern the adsorption process has been found to be more effective method for the treatment of dye con-taining wastewater. The most efficient and commonly used adsorbent is commercially activated carbon which is expensive and has regeneration problems. Recent investigations focused on the effectiveness of low cost adsorbents, like pearl millet husk [4], wheat straw [5, 6], sewage sludge [7], perlite [8], in the removal of dyes from wastewater effluent.

Adsorption is a physico-chemical process that offers great potential for treating effluents containing undesir-able components and render them safe and reusable [9, 10]. The major advantage of an adsorption system for water pollution control, are low investment in terms of both initial and land cost, simple design, easy operation and no effects by toxic harmful substances [11].

Thus, the present work was undertaken to explore the feasibility of finding a low cost effective adsorbent kola nut shell activated carbon, for the treatment of wastewater, containing phenol red and orange G dyes, respectively, from aqueous solution. The main advan-tage is that this material is an agricultural solid waste, available freely, locally and abundantly, easy to prepare in large scale. The effect of various parameters such as adsorbent dosage, agitation time, pH, initial concentra-tion of dye solution and temperature were investigated in batch experiments. Also, isotherm, kinetic and ther-modynamic studies were investigated for the chosen dyes for applicability in a controlled system.

MATERIALS AND METHODS

AdsorbentThe kola nut shells were ground into small pieces

and dried in sunlight, until the moisture was evaporated. The dried material was mixed with ZnCl2 in the ratio 1:1 and kept in an oven at 383K for 24 hours. The sample was washed many times with dionized water and leached with warm water to remove any trace of metal. It was placed in a muffle furnace at temperature of 773K for one hour. After cooling, it was ground by using mortar

and pistil and then sieved to particle size of 75µm. Thereafter, the activated sample was preserved in an air tight container for further use.

Adsorbates0.1 gram of the dye was accurately weighed and

made up to 1000 ml of distilled water. The phenol red and orange G used in the present study were procured from Onitsha main market, Nigeria. The structure of the phenol red and orange G are shown in Fig. 1 and Fig. 2, re-spectively. All chemicals used were of analytical grades.

Properties of the AdsorbentThe physical properties of the kola nut shell, before

and after activation were determined using standard methods. The ash content, moisture content and pH were estimated using ASTM D 28866-70, ASTMD 2867-70 and ASTM D 3838-80, respectively. The surface area was determined with the Sears method [12, 13]. The carbon was also characterized by Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) to examine its surface morphology and functional groups.

The Batch Adsorption StudiesThe dye solution was prepared by dissolving 0.1g

of each dye in 1000 ml of distilled water each to get a solution of 100 mg L-1. After the adsorption, the solution was allowed to settle, filtered with Whatman filter paper and the absorbance was measured at the wavelengths of 478 nm and 435 nm for orange G and phenol Red,

Fig. 1. Molecular structure of Phenol Red.

Fig. 2. Molecular structure of Orange G.


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respectively. The amount of equilibrium adsorption, qe (mg g-1) was calculated as given in eq. 1.

(1) where, Co and Ce (mg L-1) are the liquid phase initial and equilibrium concentrations of dye, respectively. V is the volume of the solution (L) and m is the mass of carbon used (g). The effects of various parameters such as pH, initial ion concentration, contact time, adsorbent dosage and temperature were investigated.

RESULTS AND DISCUSSION

Physical Properties and Characterization of AdsorbentThe observed physical properties of the carbon, before

and after activation with zinc chloride, are shown in Table 1. The results show that the surface area of the kola nut shell activated carbon (KNS-AC) was greater than the surface area of the unactivated kola nut shell (UKNS). The unactivated carbon has a surface area of 279 m2 g-1 while the activated kolanut shell has a surface area of 570.2 m2

g-1. The surface area was within the range reported by [14] for used activated carbon adsorbents - specific surface area on the order 500 to 1500 m2 g-1. The change in the surface area between activated carbon and unactivated carbon was due to the chemical effect of the activation of the carbon at a given temperature. The activation causes reaction that takes place on all the internal surfaces of the carbons, removing carbon from the pore walls and thereby enlarging them [15].

Characterization of the adsorbent using FTIR The FTIR technique is an important tool for iden-

tifying the characteristic functional groups, which are instrumental in adsorption of organic compounds [16].

The FTIR spectra of carbons, before and after activation, were used to determine the vibration frequency changes in the functional groups in the adsorbent.

The peaks between 3117.2 and 3953.7 cm-1, in FTIR of unactivated cola nut shell indicate the presence of free hydroxyl groups. The C-H stretching vibration around 2007.7 to 2940.5 cm-1 indicates the presence of alkenes. The peaks between 1742.2 and 1853.9 cm-1 correspond to the C=O stretching that may be attributed to the hemicel-lulose and lignin arene group [17]. The bands between 3314.3 - 3471 cm-1 from the FTIR of ZnCl2 activated carbon indicate the existence of free hydroxyl groups [18], while the peaks between 1419.9 and 1916.6 cm-1 indicate the presence of alkenes and aromatic functional groups [16]. The presence of these bands show that the functional groups contributed to the adsorption of dyes on the surface of the adsorbents [19, 20].

Characterization of adsorbent using SEM Fig. 3 and Fig. 4 show the morphological features

of unactivated kola nut shell (UKNS) and the kola nut shell activated carbon (KNS-AC), using ZnCl2 as acti-vating agent. Large pores of different shapes could be observed for the activated carbon. This may be attributed to the fact that the activating agents promote the contact area between the carbon and the activating agent, and thereby, increase the surface area and porosity of carbon. The zinc chloride activation produces a well-developed porosity besides high carbon yield, since it degrades the cellulose, hemicelluloses and lignin. It seems that the cavities on the surfaces resulted from the evaporation of the activating agent during carbonization, leaving void the space it previously occupied [21].

Batch Adsorption Dye adsorption was investigated changing different

parameters, such as pH, initial ion concentration, contact time, adsorbent dosage and temperature.

Effect of pHThe effect of pH on the percentage of the dye ions

removed, was studied over the pH range of 2.0 to 10.0. It was observed that with the increase of the pH of the solution, the extent of the dye removal increased. The maximum removal of orange G was recorded at pH of 2.0, decreases as the pH was increased up to pH 10.0. This is because at low pH (acidic condition), the degree

Property UKNS KNS-AC

Surface area, m2 g-1

279 570.2

pH 5.6 7.3

Moisture content, %

5.8 0.31

Ash content, % - 26.0

Bulk density - 0.7

Table 1. Physical properties of the carbon.


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of protonation of the surface of the activated carbon will be higher. This results in increase in diffusion and subsequent increase in adsorption, due to electrostatic attraction [22]. The reverse was the case for Phenol Red. The lower adsorption of Phenol Red at low pH value is due to the presence of excess H+ ions, competing with dye cations for the adsorption sites of the adsorbent, which is in agreement with [23, 24]. The extent of dye removal is graphically shown in Fig. 5.

Effect of initial concentrationThe effect of initial ion concentration shows a decrease

in percentage adsorbed, with the increase of the initial ion concentration of dyes, as seen in Figs. 6 and 7. This is because at lower concentration, the ratio of the initial number of the dye molecules to the available surface area was low [25]. For a fixed number of active sites remaining constant, the number of substrate ions, ac-commodated in the interlayer space, increased so that the removed ions were decreased. Similar results were obtained by [26 - 29].

Fig. 3. SEM analysis of unactivated kola nut shell at 75 µm particle size.

Fig. 4. SEM analysis of KNS -AC at 75 µm particle size (Mag.= 5000x).

Fig. 5. Effect of pH on adsorption of Phenol Red and Orange G on KNS-AC.

Fig. 6. Effect of concentration on the removal of Phenol Red by KNS-AC.

Fig. 7. Effect of concentration on the removal of Orange G by KNS-AC.

Effect of Contact TimeThe results showed that as the time increased, the

percentage adsorbed increased, until equilibrium was reached at about 60 min for both Phenol Red and Orange


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G, as shown in Figs. 8 and 9. The initial rapid adsorption was due to the availability of positively charged surface of the adsorbents for the adsorption of Phenol Red and Orange G [30]. The increase in the extent of removal of the dyes with increasing time was because the adsorb-ate generally formed a monolayer on the surface of the adsorbent. Thus, the removal of dyes from aqueous solution was controlled by the rate of the transport of the adsorbate species from the outer sites to the inner sites of adsorbent. Many other researchers have reported a similar trend [29, 31].

Effect of Adsorbent DosageThe effect of dosage was studied for adsorbent dos-

ages in the range of 0.1 g to 0.5 g. It can be seen that the rate of dye removal increases with increase in amount of adsorbent (Fig. 10).

The result shows that the adsorbent was efficient for maximum removal of dyes at the level of adsorbent dos-age. The increase in the percentage removal of dyes with the increase in adsorbent dosage was due to the increased surface area with more active functional groups which also gave rise to availability of more adsorption sites [22, 25]. It was also observed that the amount adsorbed per unit mass of the adsorbent decreased, as the adsorbent dosage increased. This decrease in unit adsorption with increasing the adsorbent amount, was mainly due to ad-sorption sites, remaining saturated during the adsorption reaction [32]. A similar result was obtained by another researcher [33].

Effect of Temperature The temperature effect of the adsorption process

was investigated in the temperature range of 303K to 333K. It was observed that with increase in temperature, the percentage removal decreased, as shown in Fig. 11. This was because as the temperature increased, the rate of diffusion of adsorbate molecules across the external boundary layer and internal pores of the adsorbent particles increased thereby reduced the amount of ad-sorbate removed [34]. Temperature affects the rate of removal of dyes by altering the molecular interactions and the solubility of the dyes. The removal of dyes with temperature would increase the mobility of the ions of dyes and produce a swelling effect within the internal structure of the adsorbent. This is in agreement with the result of other researchers [28, 33].

ADSORPTION ISOTHERMSThe adsorption isotherm is a relationship between

the amount of a substance removed from liquid phase by unit mass of adsorbent, and its concentration at a constant temperature. The adsorption isotherm is the basic requirement for designing any adsorption system

Fig. 8. Effect of time on adsorption of Phenol Red on KNS-AC.

Fig. 9. Effect of time on adsorption of Orange G on KNS-AC.

Fig. 10. Effect of dosage on adsorption of Phenol Red and Orange G on KNS-AC.


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Fig. 11. Effect of temperature on the removal of dyes by KNS-AC.

[23]. The Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models were used to study the adsorption process.

Langmuir Isotherm ModelThis is an isotherm model that assumes that uptake

of dye molecules occurs on a homogeneous surface by monolayer adsorption according to Sharma. The linear form of the Langmuir isotherm is

cqqqc

e

mme

e

b

+=

11 (2)

where qe is equilibrium amount of solute adsorbed per unit mass of adsorbent in (mg g-1); Ce is equilibrium concentration in aqueous phase (mg L-1); qm is the maxi-mum amount adsorbed per unit mass of adsorbent for a complete monolayer (mg g-1); b is a constant related to the affinity of the binding sites and the energy of adsorption (L mg-1). Hence, plotting the values of qe

-1 against Ce

-1, the constants qm and b were calculated from the intercept and the slope, respectively, and presented in Tables 2 and 3.

The effect of the isotherm shape has been discussed with a view to predict whether an adsorption system is ‘favorable’ or ‘unfavorable’. A dimensionless separa-tion factor, RL, as an essential feature of the Langmuir isotherm is defined as:

Lref

1R1 bC

=+

(3)

where, Cref is the reference fluid-phase concentration of adsorbate (mg L-1) and b is the Langmuir constant. For a single adsorption system, Cref is usually the highest

fluid-phase concentration encountered. The value of RL

indicates whether the adsorption isotherm is unfavorable (RL>1), linear (RL=1), favourable (0<RL<1), or irrevers-ible (RL = 0). Therefore, the values of RL were calculated and presented in Table 2 and Table 3, respectively. For the adsorption of both Phenol Red and Orange G on the adsorbent, the RL values were less than 1 and greater than zero, showing that the adsorption was favorable.

Freundlich Isotherm ModelThe Freundlich isotherm model describes the ad-

sorption of a solute on the surface of the adsorbent. It is commonly used to study the heterogeneity and surface energies. The Freundlich isotherm can be expressed as Eq. 4:

qe = KFCe1/n (4)

where, KF is the constant, related to overall adsorption capacity (mg g-1); n-1 is the constant related to surface heterogeneity (dimensionless). The plotting of qe ver-sus Ce yields a non-regression line which permits the determination of n-1 and KF values. The values of the Freundlich constants KF and n were calculated from the intercept and the slope, respectively, and shown in Tables 2 and 3. For beneficial adsorption, the value of n will be between 1 and 10 [22]. In this work, the values of n range from 1 to 3 showing beneficial adsorption of Phenol Red and Orange G on the carbons, respectively. The correlation coefficient R2 ranges from 0.93 to 0.99 for both Phenol Red and Orange G adsorption, indicat-ing that the adsorption followed Freundlich isotherm model very well.

Temkin Isotherm ModelThe Temkin isotherm model suggests a linear de-

crease of the sorption energy, as the degree of comple-tion of the adsorption centres of the adsorbent increases. The heat of adsorption of all the molecules in the layer decrease linearly with coverage, due to adsorbent-ad-sorbate interactions [35]. Temkin’s isotherm can be expressed as:

ln lne eRT RTq A Cb b

= + (5)

where RT Bb

=


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Table 2. Calculated isotherm parameters for the adsorption of Phenol Red on KNS-AC. Isotherm Temperature K

model 303 313 323 333 Langmuir Q (mg g-1) b (L mg-1) RL R2

24.272 0.0222 0.0825 0.8822

25.510 0.0158 0.1124 0.88

26.881 0.0105 0.1601 0.8408

25.974 0.0085 0.1899 0.8605

Freundlich n Kf (L g-1) R2

3.766 4.247 0.927

3.642 3.982 0.9252

3.534 3.658 0.917

3.489 3.388 0.9137

Temkin b (J mg-1) A (L g-1) R2

880.33 2.288 0.7581

904.51 2.026 0.7547

946.64 1.786 0.7375

1027.41 1.722 0.7508

Dubinin-Radushkevich qD (mg g-1) β (mol2 J-2) E (KJ mol-1) R2

13.643 4.0 x 10-7 1118.03 0.5867

13.294 4.0 x 10-7 1118.03 0.5780

12.648 4.0 x 10-7 1118.03 0.5648

11.866 4.0 x 10-7 1118.03 0.5486

Table 3. Calculated isotherm parameters for the adsorption of Orange G on KNS-ACIsotherm Temperature K

model 303 313 323 333 Langmuir Q (mg g-1) b (L mg-1) RL R2

33.113 0.0212 0.0862 0.9528

28.011 0.0237 0.0778 0.9715

25.510 0.0233 0.0791 0.9648

24.390 0.0195 0.0929 0.9394

Freundlich n Kf (L g-1) R2

2.3191 2.7065 0.9813

2.3776 2.7221 0.9805

2.4361 2.7428 0.9806

2.4649 2.6928 0.9816

Temkin b (J mg-1) A (L g-1) R2

466.38 0.4705 0.8935

516.71 0.5098 0.907

563.21 0.5381 0.9103

606.83 0.5465 0.9068

Dubinin-Radushkevich qD (mg g-1) β (mol2J-2) E (KJ mol-1) R2

16.530 2.0 x 10-6 500 0.6182

15.932 2.0 x 10-6 500 0.6262

15.388 2.0 x 10-6 500 0.626

14.804 2.0 x 10-6 500 0.6258

T is the absolute temperature in K, R is the universal gas constant, 8.314 J mol-1 K-1, B is related to the heat of adsorption [36, 37].

The constants for the Temkin’s isotherm were de-termined from the plot of qe against ln Ce and presented in Table 2 and Table 3. The R2 values indicated that the Temkin’s isotherm did not fit this adsorption process well.

Dubinin – Radushkevich Isotherm ModelThe linear form of Dubinin-Radushkevich Isotherm

model [28] is:lnqe = lnqm - βε2 (6)

where qm is the Dubinin-Radushkevich model monolayer capacity (mmol g-1), β a constant related to sorption energy, and ε is the Polanyi potential which is related to the equilibrium concentration as follows:

ε = RTln (1+ 1

eC ) (7)

where R is the gas constant (8.314 J mol-1 K-1) and T is the absolute temperature. The constant β gives the mean free energy, E, of sorption per molecule of the sorbate, when it is transferred to the surface of the solid, from infinity into the solution and can be computed using the


195

relationship [38].

E = β2

1 (8)

This model involves temperature effects and quite fairly predicts the experimental data, over a wide concen-tration range [39]. The constants were calculated from the plot of ln qe versus Ԑ2 and presented in Tables 2 and 3. From the values of R2 obtained, the result showed that both Phenol Red and Orange G adsorption did not follow Dubinin-Radushkevich Isotherm model as much. The results of E greater than 8 KJ mol-1 obtained indicate that the adsorption is predominantly chemisorption [40].

Isotherm Statistical Analysis for the Batch Ad-

sorption Statistical analysis using Root Mean Square Devia-

tion (RMSD), Coefficient of Variance (CV), Variance and Mean was done. The RMSD, also called Root-Mean-Square Error (RMSE), is a frequently used measure of the differences between values predicted by a model or an estimator and the values actually observed. The RMSD served to aggregate the magnitudes of the errors in predictions for various times into a single measure of predictive power. The variance of a data is the square of the RMSD. The CV was defined as the RMSD normal-ized to the mean of the observed values. The smaller the values of Variance and RMSD, the more correlated is the set of data. The Adjusted R-squared compares the explanatory power of regression models, that contain

different numbers of predictors. Adjusted R-squared is a modified version of R-squared that has been adjusted for the number of predictors in the model. The isotherm sta-tistical analysis and the isotherm equations obtained from the experimental data were presented in Tables 4 and 5. Hence, the results of the statistical analysis showed that the Freundlich isotherm fits the adsorption very well. KINETIC STUDIES OF THE ADSORPTION

In other to investigate the mechanism of the process and the potential rate controlling steps, such as mass transport, pore diffusion and chemical reaction process-es, kinetic models have been used to fit experimental data [23]. The Pseudo-second order, Elovich, Intra-particle diffusion and Power function kinetic models were used to test the experimental data.

Pseudo-second order kinetic modelThe adsorption kinetics may be described by a

pseudo-second order equation [33, 34]:

22( )t

e t

d

dtq q qk= − (9)

Integrating the equation and applying the boundary condition t = 0 to t = t and qt = qt, gives

2

1 1

e t e

tkq q q= +

− (10)

Eq. 10 can be rearranged to obtain a linear form:

Table 4. Isotherm statistical analysis for Phenol Red using KNS-AC.

Isotherm Model R2 Adj R2 Mean RMSD Variance CV Langmuir 𝐶𝐶𝑒𝑒𝑞𝑞𝑒𝑒

=1

0.539+ (

124.27

)𝐶𝐶𝑒𝑒

0.882 0.8427 6.087 4.718 22.26 0.7750

Freundlich log𝑞𝑞𝑒𝑒= log 4.25 + �

13.77

� 𝑙𝑙𝑙𝑙𝑙𝑙𝐶𝐶𝑒𝑒

0.927 0.9027 1.045 0.2607 0.0680 0.2495

Temkin 𝑞𝑞𝑒𝑒= �

𝑅𝑅𝑅𝑅880.3

� 𝑙𝑙𝑙𝑙2. + �𝑅𝑅𝑅𝑅

880.3� 𝑙𝑙𝑙𝑙𝐶𝐶𝑒𝑒

0.758 0.6773 12.71 7.154 51.18 0.5629

Dubinin-Radushkevich 𝑙𝑙𝑙𝑙𝑞𝑞𝑒𝑒 = 𝑙𝑙𝑙𝑙13.64− 4 𝑥𝑥 10−7𝜀𝜀2

0.587 0.4493 2.406 0.6003 0.36034 0.2495


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2

2

1 1

t ee

t tq qqk

= + (11)

where qe - amount of dye adsorbed (mg g-1 at equi-librium), qt - amount of dye adsorbed (mg g-1 at time t), and K2 is the equilibrium constant rate constant of pseudo-second order (g mg-1 min-1) adsorption. At dif-ferent temperatures, the plot of t/qe versus t was used to demonstrate the pseudo-second order. The correlation coefficient R2 has very high values of between 0.99 and above that for the adsorption of Phenol Red and Orange G on the adsorbent, as can be seen in Tables 6 and 7. Equally, the values of the calculated equilibrium adsorp-tion capacity (qe) were very close to the experimental values. Therefore, the Pseudo-second order model is satisfactorily applicable to the adsorption of Phenol Red and orange G on the adsorbent. Similar results were also obtained by [43 - 45].

Elovich kinetic modelThe Elovich model equation is generally expressed as:

tdq qdt

τ−β

= α (12)

Integrating this equation for the boundary condi-tions, gives [36]:

qt = 1 ln( ln tαββ β

1) + (13)

where, α is the initial adsorption rate (mg min-1) and β is related to the extent of surface coverage and the activated energy for chemisorption (g mg-1). The Elovich equation has been shown to be useful in describing chemisorption

on highly heterogeneous adsorbents. The initial adsorp-tion rate, α and the extent of coverage, β were calculated from the slope and the intercept of the plot of qt against lnt, respectively, and presented in Tables 6 and 7 for the two dyes, respectively. The values of the correlation coefficient R2 (> 0.90) for both Phenol Red and Orange G indicate that the adsorption of Phenol Red and Orange G conform to the Elovich model. The small values of β obtained in most cases are in reasonable agreement with that obtained by [46].

Intra-particle DiffusionThere is a possibility of the adsorbate diffusing into

the interior pores of the adsorbent after initially being adsorbed on the surface o the adsorbent [35].

Hence, the kinetic model propounded Weber Morris is used to investigate the adsorption for intra-particle diffusion [47]:

qt = Kd t1/2 + δ (14)

where Kd is the intra-particle diffusion constant, δ is the intercept of the line which is proportional to the boundary layer thickness. The most commonly used technique in indentifying the mechanism involved in an adsorption process, is the intra-particle diffusion plot, which expresses the relationship between the adsorption capacity (qt) and time t1/2 [48]. The plot of qt against t1/2 gives a slope, which is the intra-particle diffusion con-stant, Kd and an intercept, δ. If the linear plot of qt versus t1/2 passes through the origin, then the intra-particle dif-fusion will be the sole rate-limiting process [46]. The values of the correlation coefficient, R2 for most of the

Table 5. Isotherm statistical analysis for Orange G using KNS-AC.Isotherm Model R2 Adj R2 Mean RMSD Variance CV Langmuir 𝐶𝐶𝑒𝑒𝑞𝑞𝑒𝑒

=1

0.702+ (

133.11

)𝐶𝐶𝑒𝑒

0.953 0.9373 3.760 2.6671 7.113 0.7094

Freundlich

log 𝑞𝑞𝑒𝑒 = log 2.707 + �1

2.319� 𝑙𝑙𝑙𝑙𝑙𝑙𝐶𝐶𝑒𝑒

0.981 0.9747 1.103 0.313 0.0979 0.2837

Temkin

𝑞𝑞𝑒𝑒 = �𝑅𝑅𝑅𝑅

466.4� 𝑙𝑙𝑙𝑙0.4 + �

𝑅𝑅𝑅𝑅466.4

� 𝑙𝑙𝑙𝑙𝐶𝐶𝑒𝑒

0.894 0.8587 15.27 9.4611 89.51 0.6195

Dubinin-Radushkevich 𝑙𝑙𝑙𝑙𝑞𝑞𝑒𝑒 = 𝑙𝑙𝑙𝑙16.53 − 2 𝑥𝑥 10−6𝜀𝜀2

0.618 0.4907 2.540 0.7206 0.5193 0.2837


197

adsorption indicated that the adsorption of Phenol Red and Orange G followed the intra-particle diffusion, as shown in Tables 6 and 7 but, since the linear plot did not pass through the origin, the intra-particle diffusion is not the rate-controlling step. Similar results were obtained by [45].

Power Function ModelThe power function equation is given by [22]:

tlog q log a b log t= + (15)where qt is the quantity of dye adsorbed (mg g-1) at time t (min). a and b are the power function constants. The power function model was demonstrated by plotting ln qt against lnt and the constants a and b were determined from the slope and the intercept and presented in Tables 6 and 7 for the two dyes, respectively, where b represents the specific sorption rate at unit time, i.e. t = 1 [24]. The high values of the correlation coefficient, R2 indicated that the adsorption of Phenol Red and Orange G on these carbons conforms to the power function model.

Adsorption ThermodynamicsThe mechanism of adsorption was determined

through thermodynamic quantities such as change in free

energy (ΔG), change in enthalpy (ΔH), and change in entropy (ΔS). The thermodynamic equilibrium constant, KL for the sorption was determined from the intercept of the plots of In (qe/Ce) versus qe of Langmuir isotherm. Then, the ΔG, ΔH and ΔS are calculated from the Van’t Hoff equations.

LG RT ln K∆ = − (16)

ln S HKR RT∆ ∆

= − (17)

where R is the universal gas constant, T is the tempera-ture (K), KL is the Langmuir equilibrium constant. The thermodynamic parameters were calculated from the values of the thermodynamic equilibrium constant, K by plotting of In KL versus T-1 (Fig. 12). Then the slope and intercept were used to determine ΔH and ΔS, and Eq. 16 was used to calculate ΔG. The values of ΔH, ΔS and ΔG are given in Table 8.

The negative values of ΔG indicate the feasibility of the adsorption process at room temperature and also the spontaneity of the adsorption reaction [30]. The negative values of ΔH indicate the exothermic nature of the adsorption in accordance with the decreasing adsorption capacity, associated with increasing adsorp-

Table 6. Calculated kinetic parameters for the adsorption of Phenol Red on KNS-AC.

Kinetic model Temperature K

303 313 323 333 Pseudo second order K2 (g mg-1 min-1) qe (mg g-1) R2

0.0746 9.990 0.9993

0.0789 9.671 0.9993

0.0774 9.533 0.9998

0.0575 9.416 0.999

Intraparticle diffusion Kd (mg g-1 min-1/2) ∂ R2

0.1999 8.3002 0.9696

0.2116 7.9391 0.9742

0.2395 7.6201 0.9619

0.2588 7.2359 0.9900

Elovich α (mg g-1 min-1) 𝛽𝛽 (g mg-1) R2

40079170

2.2999 0.9225

4009771 2.1119 0.9814

303574 1.8471 0.9893

98049 1.7721 0.9473

Power function a b R2

8.054 0.0469 0.9285

7.644 0.0531 0.9849

10 1 1

6.952

0.0665 0.955


198

tion temperature. This also confirms the possibility of physical adsorption with the increase in temperature of the system [49]. The positive value of ΔS means the increased randomness with adsorption of Orange G on KNS-AC [1]. This is because the number of water molecules surrounding the dyes decreased during the adsorption process and thus, the degree of freedom of the water molecules increased, indicating that the degree of randomness at the solid-solution interface of the adsorption increased [50]. The negative value

of ΔS for adsorption Phenol Red on KNS-AC cor-responds to a decrease in degree of freedom of the adsorbed species.

Activation EnergyThe activation energy of adsorption was calculated

using the Arrhenius equation, defined as:

exp( )EaK aRT

= − (18)

Table 7. Calculated kinetic parameters for the adsorption of Orange G on PKS-AC.

Kinetic model Temperature K

303 313 323 333

Pseudo second order K2 (g mg-1 min-1) qe (mg g-1) R2

0.1447 9.124

1

0.100 9.158

0.9999

0.0673 9.191

1

0.062 9.083

0.9997

Intraparticle diffusion Kd (mg g-1min-

1/2) ∂ R2

0.1936 7.7008 0.6681

0.2402 7.351

0.7391

0.3226 6.726

0.8569

0.3119 0.635

0.9003

Elovich α (mg g-1min-1) 𝛽𝛽 (g mg-1) R2

2052331

2.1146 0.8017

76791 1.7364 0.8548

2123.34 1.3173 0.9545

2863.63 1.3829 0.9736

Power function a b R2

7.288

0.0565 0.7887

6.896

0.0699 0.8382

6.232

0.0944 0.9419

6.190 0.091

0.9632

Table 8. Thermodynamics parameters for the adsorption of Phenol Red and Orange G on adsorbent.

Adsorbate T (K) ∆G (KJ mol-1) ∆S (J mol-1 K-1) ∆H (KJ mol-1) Phenol Red 303 -7.810 313 -7.182 -65.25 -27.57 323 -6.314 333 -5.925 Orange G 303 -7.693 313 -8.237 23.09 -21.31 323 -8.455 333 -8.224


199

On linearizing the Arrhenius equation gives:

ln ln aEK ART

= − (19)

where A is the frequency factor (g mg-1 min-1), K - rate constant value for second-order kinetics (g mg-1 min-1), Ea - activation energy in kJ mol-1. T is temperature (K) and R is the gas constant 8.314 KJ mol-1 K-1. The value of Ea can be calculated by the slope of graph lnK versus T-1, shown in Fig. 13. The activation energy is -59.28 KJ mol-1 and -119.42 KJ mol-1 for Phenol Red and Orange G, respectively. The values are in corroboration of the values, obtained by [51].

CONCLUSIONS

The activated carbon prepared from kola nut shell as an adsorbent, was effective for the removal of Phenol Red and Orange G dyes from aqueous solutions. Opera-tional parameters, such as pH, initial ion concentration, contact time, adsorbent dosage and temperature were studied. The percentage removal of dye is concentration dependent, decreasing with an increase in dye concen-tration. Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models were used to interpret the adsorption phenomenon of the adsorbate. The equilib-rium adsorption data for the dyes was represented by the Freundlich isotherm. The RL values have been calculated using the Langmuir constants b and Co; the values were greater than 1, which showed that KNS-AC was an ef-ficient adsorbent for the dye removal. The kinetic studies showed that the adsorption followed a pseudo-second order kinetic model. The negative values of ∆G and ∆H

Fig. 12. Van’t Hoff plot for the adsorption of Phenol Red and Orange G on adsorbent.

Fig. 13. Activation energy plot for the adsorption of Phenol Red and Orange G on the Adsorbent.

indicate that the adsorption process is spontaneous and exothermic in nature. The negative value of ∆S shows decreased randomness with adsorption of the dyes on the adsorbent. The kola nut shell is a low cost natural and abundant adsorbent material in Nigeria. Therefore, a conclusion can be drawn that KNS-AC may be used, as an alternative to more costly adsorbent materials, for the removal of Phenol Red and Orange G.

REFERENCES

1. N.D. Pragnesh, K. Satindar, K. Ekta, Removal of eriochrome black-T by adsorption onto eucalyptus bark using green technology, Chemical Technology, 18, 2011, 53-60.

2. P. Nigam, G. Armour, I. Banat, D. Singh, R. Marchant, Physical Removal of Textile Dyes and Solid State Fermentation of Dye-adsorbed Agricultural Residues, Bioresour. Technol., 72, 2000, 219-226.

3. E. Weber, N.L. Wolfe, Kinetics Studies of reduction of aromatic azo compounds in anaerobic sediment/water systems, Environ. Toxicol. Chem., 6, 1987, 11-20.

4. K. Selverani, Studies on low cost adsorbents for the removal of organics and inorganic from wastewater, Ph.D. Thesis, REC, Tiruchirapalli, India, 2000.

5. T. Robinson, B. Chandaran, P. Nigam , Removal of dyes from a synthetic dye effluent by biosorption on wheat straw, Water Res., 36, 2002, 2830-2842.

6. V.K. Verma, A.K. Mishra, Removal of dyes by the wheat straw carbon, Ecol. Environ. & Conservation, 12, 4, 2006, 755-757.

7. M. Otero, M. Rozada, L.F. Calvo, A.I. Garcia, A. Moran, Kinetic and Equilibrium modeling of meth-


200

ylene blue from solution by adsorbent materials produced from sewage sludges, Biochem. Eng. J., 15, 2003, 59-68.

8. M. Dogan, M. Alkan, Y. Onganer, Adsorption of methylene blue from aqueous solution onto perlite, Water Air & Soil Pollution, 120, 2000, 229-248.

9. G.S. Gupta, G. Prasad, V.N. Singh, Removal of chrome dye from aqueous solutions on Fly ash, Water, Air, Soil Poll., 37, 1988b, 13-24.

10. Annadurai, Krishnan, Adsorption of basic dye using chitin, Ind. Jr. of Environ. Protection, 16, 6, 1996, 444-449.

11. Annadurai, Krishnan, Batch kinetic studies of ad-sorption of reactive dye using chitosan, Ind. Jr. of Environ. Protection, 17, 5, 1997, 328-333.

12. A.S. Alzaydian, Adsorption of methylene blue from aqueous solution onto a low cost Natural Jordanian clay, Applied Sci., 6, 6, 2009, 1047-1058.

13. Z. Al-Qadah, R. Shawabkah, Production and characterization of granular activated carbon from activated sludge, Chem. Eng., 26, 1, 2009, 6-17.

14. R.C. Bansal, M. Goyal, Activated carbon adsorption, Taylor Francis Publishers, New York, 2005.

15. V.R. Elwood, Process Water Treatment Carbons for Barnebey & Suitcliffe Corporation, Columbus, Ohio, 2000.

16. H.S. Cherifi, Haninia, F. Bentahar, Adsorption of phenol from wastewater using Vegetal cords as a new adsorbent, Desalination, 244, 2009, 177-187.

17. Y. Safa, H.N. Bhatti, Adsorptive Removal of Direct Dyes by Low Cost Rice Husk, Effect of Treatments and Modification, Biotechnology, 10, 16, 2011, 28-3142.

18. K.F. Al-Sultani, F.A. Al-Seroury, Characterization of the Removal of Phenol from Aqueous Solution Fluidized Bed Column by Rice Husk Adsorbent, Recent Sciences, 1, 2011, 145-151.

19. I.D. Mall, V.C. Srivastavan, I.M. Mishre, Characteri-zation of Mesoporous Rice Husk Ash (RHA) and Adsorption Kinetics of Metal Ions from Aqueous Solution onto RHA, J. Hazard. Mater., 134, 2006, 257-267.

20. V.K. Garg, M. Bansal, U. Garg, D. Singh, Removal of Cr (VI) from aqueous Solutions using pre consumer processing Agricultural waste, A case study of Rice Husk, Hazard Materials, 162, 2009, 3125-3320.

21. P.Y. Devarly, N. Kartika, Indraswati, S. Ismadji, Activated carbon from jackfruit peel waste by H3PO4 chemical activation: Pore structure and surface chemistry characterization, Chem. Eng. J., 140, 2008, 32-42.

22. U.V. Ladhe, S.K. Wankhede, V.T. Patil, P.R. Patil, Adsorption of eriochrome black-T from aqueous so-lutions on activated carbon prepared from mosambi peel, Appl. Sci.Environ.Sanit., 6, 2, 2011, 149-154.

23. R. Rajeshkannan, M. Rajasimman, N. Rajamohan, Decolourisation of malachite green using tama-rind seed: Optimisation, isotherm and kinetic stud-ies, Chemical Industry and Chemical Engineering Quarterly, 17, 1, 2011, 67-79.

24. R. Venckatesh, T. Amudha, S. Rajeshwari, M. Chandramohan, M. Jambulingam, Kinetics and equilibrium studies of adsorption of direct red-28 onto Punica granatum carbon, Int. J. Eng. Technol., 2, 6, 2010, 2040-2050.

25. S. Arivoli, M. Hema, P.D. Martin, Adsorption of malachite green onto carbon prepared from boras-sus bark, Science and Engineering, 34, 2009, 31-43.

26. D.S. Shirsath, V.S. Shrivastava, Removal of haz-ardous dye ponceaus by using chitin: an organic bioadsorbent, African J. Env. Sci. Technol., 6, 2, 2012, 115-124.

27. R.W. Gaikwad, S.A. Misal, Sorption studies of methylene blue on silica gel, Chem. Eng. Applic., 1, 4, 2010, 111-115.

28. V.K. Verma, A.K. Mishra, Kinetic and isotherm modeling of adsorption of dyes onto rice husk car-bon, Global Nest Journal, 10, 10, 2010, 1-7.

29. V.K. Vikrant, S.K. Deshmukh, Kinetic parameters and evaluation performance for decolorization us-ing low cost adsorbent, International conference on future environment and energy 28, 2012, 95-99.

30. S. Goswami, U.C. Ghosh, Studies on adsorption behavior of Cr (VI) onto synthetic hydrous stanniz oxide, Water S.A., 31, 4, 2005, 597-602.

31. A.K. Tabrez, V. Singh, D. Kumar, Removal of some basic dyes from artificial textile wastewater by adsorption on Akash Kinari coal, Scientific and Industrial Research, 63, 2004, 353-364.

32. Y. Bulut, H. Aydin, A Kinetic and Thermodynamic study of methylene blue adsorption on wheat shells, Desalination, 194, 2006, 259-267.

33. S. Rashmi, B. Bhattacharya, Adsorption-coagulation


201

for the decolorisation of textile dye solutions, Water Qual. Res. J. Canada, 38, 3, 2003,553-562.

34. T. Shahwan, H.N. Erten, Thermodynamic parame-ters of Cs+ sorption on natural clays, Radioanalytical and Nuclear Chemistry, 253, 1, 2002, 115-120.

35. P. Sivakumar, P.N. Palanisamy, Adsorption Studies of basic red 29 by a non- Conventional activated car-bon prepared from Euphorbia Antiquorum, Chem. Tec. Research, 1, 3, 2009, 502-510.

36. E. Bulut, M. Ozcar, I.S. Ayhan, Adsorption of mala-chite green onto bentonite: Equilibrium and Kinetics studies and process design, Micro porous and Meso porous Materials, 115, 2008, 234-246.

37. S.J. Allen, G. McKay, J.F. Porter, J. Colloid Interface Sci., 280, 2004, 322-333.

38. V.J. Inglezakis, S.G. Poulopoulos, Adsorption ion exchange and catalysis: Design of Operation and Experimental Applications, 1st ed., Elsevier Publishers, Amsterdam, 16, 17, 2006, 66-75.

39. S.H. Lin, R.S. Juang, Heavy metal removal from water by sorption using surfactant-modified mont-morillonite, Hazard Materials, 92, 2002, 315-326.

40. C. Arh-Hwang, H.Yao-Yi, Adsorption of Ramazol Black 5 from aqueous solution by the template crosslinked-chitosans, Hazardous Material, 177, 2010, 668-675.

41. M.S. Chiou, H.Y. Li, Equilibrium and Kinetic mod-eling of adsorption of reactive dyes on cross-linked Chitosan bead, Hazard. Mater, 93, 2, 2002, 233-248.

42. J.T. Nwabanne, P.K. Igbokwe, Kinetics and equi-librium modeling of nickel adsorption by cassava peel, Engineering and Applied Science, 3, 11, 2008, 829-834.

43. P. Xiangliang, Z. Daoyong, Removal malachite green from water by firmiana simplex wood fiber, Electronic Journal of Biotechnology, 12, 4, 2009, 1-10.

44. J.I. Muhammad, N.A. Muhammad, Thermodynamics and kinetics of adsorption of dyes from aqueous media onto alumina, Chem. Soc. Pak., 32, 4, 2010, 419-428.

45. S.A. Ateff, M. Waleed, Equilibrium, Kinetic and Thermodynamics studies on the adsorption of phenol unto activated phosphate rock, Physical Sciences, 4, 4, 2009, 1-9.

46. G. Ozer, A.O. Safa, O. Adnan, Adsorption kinetics of naphthalene onto organo-sepiolite from aqueous so-lutions, Elsevier on Desalination 220, 2008, 96-107.

47. N.A. Oladoja, I.O. Asia, Studies on the sorption of basic dye by rubber (Hevea brasiliensis) seed Shell, Turkish J. Eng. Env. Sci., 32, 2008, 143-152.

48. E. Guibal, C. Milot, J.M. Tabin, Continuous fixed bed bisorption of Cu2+ ions:Application of simple two parameter mathematical model, Ind. Eng. Chem. Res., 37, 1998, 1454-1464.

49. Y.C. Sharma, B. Singh, Uma, Fast removal of malachite green by adsorption on rice husk acti-vated carbon, The Open Environment Pollution and Toxicology Journal, 1, 2009, 74-78.

50. J.I. Muhammad, N.A. Muhammad, Adsorption of dyes from aqueous solutions on activated char-coal, Elsevier B. V., 6, 7, 2006, 1-11.

51. S. Jiwan, B. Sushmita, G. Deepak, C.S. Yogesh, Equilibrium Modeling and Thermodynamics of removal of orange G from its aqueous solutions, Applied Sciences in Environmental Sanitation, 6, 3, 2011, 317-326.

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