Acid-modified montmorillonite for sorption of heavy metals from automobile effluent

ARTICLE IN PRESS beni-suef university journal of basic and applied sciences ■■ (2016) ■■–■■

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Full Length Article

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Acid-modified montmorillonite for sorption of heavy metals from automobile effluent

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Kovo G. Akpomie a,b,*, Folasegun A. Dawodu a a

Department of Chemistry (Industrial), University of Ibadan, Ibadan, Nigeria Materials and Energy Technology Department, Projects Development Institute (PRODA), Federal Ministry of Science and Technology, Enugu, Nigeria

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A R T I C L E

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I N F O

A B S T R A C T

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Article history:

An acid treated montmorillonite was utilized as a low-cost adsorbent for the removal of

Received 11 March 2015

heavy metals from an automobile effluent. The adsorbent was characterized by the Fourier

Received in revised form 27

transform infrared spectrophotometer and scanning electron microscope. The effects of pH,

December 2015

adsorbent dose, particle size and contact time on the sorption process were determined by

Accepted 2 January 2016

batch methodology. Acid modification increased the Brunauer Emmett and Teller (BET) surface

Available online

area and total pore volume of the montmorillonite from 55.76 to 96.48 m2/g and from 0.0688

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to 0.101 cm3/g, respectively. The removal of heavy metals from the effluent followed the order:

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Keywords:

Zn > Cu > Mn > Cd > Pb > Ni, which is directly related to the concentration of metal ions in

Acid-activation

the effluents. The Freundlich isotherm was found to fit the experimental data properly than

Automobile effluent

the Langmuir, Temkin and Dubinin–Radushkevich isotherm models. Kinetic analysis was

Heavy metals

performed by the application of the pseudo-first order, pseudo-second order, intraparticle

Sorption

diffusion and liquid film diffusion model. The process was found to be physisorption, con-

Isotherm

trolled by the film diffusion mechanism. The acid treatment enhanced the adsorption capacity

Kinetic

of the montmorillonite and was suitable for the removal of heavy metals from the automobile effluent.

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© 2016 Production and hosting by Elsevier B.V. on behalf of Beni-Suef University. This is

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an open access article under the CC BY-NC-ND license (http://creativecommons.org/

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licenses/by-nc-nd/4.0/).

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1.

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Introduction

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The rapid growth of industries has resulted to an increase in discharge of wastewaters containing heavy metals, which is a serious environmental problem. These heavy metals are usually toxic at certain concentrations to living organisms,

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persistent in nature, non-biodegradable and tend to accumulate in the food chain (Ahluwalia and Goyal, 2007). It is therefore necessary to remove these metals from industrial effluents before their discharge into receiving water bodies. Well established methods for treating heavy metals contaminated effluents include ion exchange, filtration, chemical precipitation, electrochemical treatment, oxidation/reduction, solvent

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* Corresponding author. Materials and Energy Technology, Projects Development Institute (PRODA), Federal Ministry of Science and Technology, Enugu, Nigeria. Tel.: +2348037617494. E-mail address: [email protected] (K.G. Akpomie). http://dx.doi.org/10.1016/j.bjbas.2016.01.003 2314-8535/© 2016 Production and hosting by Elsevier B.V. on behalf of Beni-Suef University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

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beni-suef university journal of basic and applied sciences ■■ (2016) ■■–■■

extraction, evaporation and adsorption (Akpomie and Dawodu, 2015). However, few of these processes are accepted due to high cost, low efficiency, inapplicability to a wide range of pollutants and results in secondary contamination (Liang et al., 2010). Adsorption has been found to be the most effective technique in terms of initial cost, ease of operation, flexibility and simplicity of design, and activated carbon is known to be the most effective adsorbent (Wang and Li, 2007). The disadvantage of the high cost involved in using activated carbon led to the search for cheaper alternative adsorbents by researchers. Recently, many low cost adsorbents have been utilized for heavy metals removal, which includes biomass materials, fertilizer waste, tea waste, microorganisms, charcoal, yeast, sludge ash, date pits, laterite, red mud and clay (Dawodu and Akpomie, 2014). Montmorillonite has also been used for the removal of heavy metals from effluents (Abollino et al., 2003; Guo et al., 2011). Our previous work has showed a local Nigerian montmorillonite and its alkaline modified derivates suitable for treatment of an automobile effluent contaminated with heavy metals (Akpomie and Dawodu, 2015). Acid modifications have been reported to increase the adsorption capacity of montmorillonite for heavy metals (Bhattacharayya and Gupta, 2006). However, most studies have been focused on the removal of heavy metals from laboratory prepared solution. This study reports for the first time the use of an acid modified montmorillonite of Nigerian origin for the treatment of automobile effluent contaminated with heavy metals. The montmorillonite is present in abundant amount in Nigeria, easily accessible and can thus be used as a low cost sorbent (Akpomie and Dawodu, 2014). The influence of pH, adsorbent dose, particle size and contact time on the sorption process was investigated. Equilibrium isotherm and kinetic models were also analyzed.

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2.

Materials and methods

2.1.

Preparation of adsorbents

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The montmorillonite was collected from Ugwuoba in Oji River, a local government area of Enugu state in Nigeria, and then processed as described (Akpomie and Dawodu, 2014) to obtain the Unmodified Montmorillonite (UM). The acid treatment of the montmorillonite was performed by contacting 50 g of UM with 250 mL of H2SO4 acid at different concentrations ranging from 0.5 to 2.5 M in a glass beaker. The mixture was stirred for 30 min and left for 24 h at a room temperature of 28 °C, after which the aqueous phase was decanted. The clay residue was washed with excess distilled de-ionized water and then sundried, after which it was heated at different temperatures ranging from 50 to 300 °C using the muffle furnace at different heating times of 30 to 360 min. The samples were then pulverized and passed through mesh sieves of sizes 100 to 500 μm to obtain the Acid Modified Montmorillonite (AMM).

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2.2.

Physicochemical characterization

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The automobile effluent was collected in a pretreated plastic bottle from the discharge outlet of Innoson automobile indus-

try located in Nnewi, Anambra state, Nigeria, and stored at 4 °C in a refrigerator. The sample was collected based on the method described (Pearson et al., 1987). The physicochemical analysis of the effluent was determined using standard methods (AOAC, 2005) by the use of analytical grade chemicals obtained from Sigma Aldrich. The heavy metal concentration of the effluent was determined by the use of the Atomic Absorption Spectrophotometer (AAS) (Buck scientific model 210VGP). The chemical composition of the adsorbents was determined by the AAS after digestion of the samples with nitric acid and hydrofluoric acid. The ammonium acetate method (Rhoades, 1982) was used to determine the cation exchange capacity (CEC). The slurry pH was obtained as described (Akpomie and Dawodu, 2014), while the pH point of zero charge (pHpzc) was determined by the method explained (Onyango et al., 2004). X-ray diffraction (XRD) analysis was determined using a model MD 10 Randicon diffractometer operating at 25 kV and 20 mA. The scanning regions of the diffraction were 16–72 °C on the 2Ɵ angle. The Fouriertransform infrared spectrophotometer (FTIR; Shimadzu 8400s) was used to investigate the surface functional groups on the adsorbents, while scanning electron microscope (SEM; Hitach S4800) was utilized to access the morphology. The pore properties and Brunauer, Emmett and Teller (BET) surface area of the adsorbents were determined via nitrogen adsorption–desorption isotherms using a micrometrics ASAP 2010 model analyzer.

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2.3.

Batch adsorption studies

The adsorption experiment was performed using batch sorption technique. This was performed by adding 0.1 g of the adsorbent to 50 mL of the effluent solution in a 100 mL pretreated plastic bottle. The effect of effluent pH was studied by varying the pH of the effluent from 2.0 to 8.0 by the dropwise addition of 0.1 M HCl or 0.1 M NaOH when required, using adsorbent particle sizes of 100 μm, contact time of 180 min at a room temperature of 300 K. The influence of adsorbent dose and particle size were also studied under similar optimum experimental conditions at an effluent pH of 6.5, but by varying the adsorbent dose from 0.1 to 0.5 g and particle size from 100 to 500 μm, respectively. Also, the influence of contact time was performed under similar conditions at various contact times of 10–300 min in order to investigate the effect of a particular parameter, which was varied, while others were kept constant at the optimum conditions. At the end of the given contact time for a particular sorption, the mixed solution was filtered and the residual metal ion concentration in the filtrate was determined by the AAS. The amount of metal ions adsorbed unto the adsorbents was calculated from the mass balance equation:

qe = v [Co − Ce] m

(1)

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where qe (mg/g) is the adsorption uptake capacity of the adsorbent for metal ions at equilibrium, Co (mg/L) and Ce (mg/ L) are the initial and equilibrium concentration of metal ions in solution, respectively, m (g) is the mass of the adsorbent and v (L) is the volume of effluent used for sorption.

Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

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2.4.

Isotherm modeling

2.5.

Kinetic modeling

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The equilibrium isotherm analysis was carried out by the application of the Langmuir, Freundlich, Temkin and Dubinin– Radushkevich (D-R) isotherm models (Das and Mondal, 2011). The Langmuir isotherm describes a monolayer sorption on an adsorbent containing a finite number of identical binding sites (homogenous surface). The linear form of the Langmuir equation is expressed as (Langmuir, 1918):

The kinetic model analysis was carried out by the application of the pseudo-first order, pseudo-second order, intraparticle diffusion and liquid film diffusion models (Taffarel and Rubio, 2009). The pseudo-first order kinetic model or the Lagergren equation is given as (Lagergren, 1898):

log (qe − qt ) = log qe − (KI 2.303) t

(8)

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Ce qe = 1 qLKL + Ce qL

(2)

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where qe (mg/g) and KL (L/mg) are related to the adsorption capacity and energy of adsorption respectively. A dimensionless factor RL is used to describe the essential characteristics of the Langmuir isotherm and is given as:

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R L = 1 [1 + KLCo]

(3)

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The RL values indicate the type of adsorption to be irreversible (RL = 0), favorable (0 < RL < 1), linear (RL = 1) or unfavorable (RL > 1). The Freundlich isotherm is based on a multilayer adsorption unto a heterogeneous surface of an adsorbent. The linear form of the Freundlich equation is expressed as (Freundlich, 1906):

where qt (mg/g) and qe (mg/g) are the amounts of metal ions adsorbed at time t and equilibrium, respectively. KI (min−1) is the Pseudo first order rate constant. The pseudo-second order model is based on the assumption that the rate of occupation of adsorption sites is proportional to the square of the number of unoccupied sites and is expressed in its linear form as (Ho, 2006):

t qt = 1 h + t qe

(9)

log qe = log KF + [1 n ] log Ce

(4)

where h = K2qe2 is the initial sorption rate (mg/g min), K2 (g/ mg min) is the rate constant of Pseudo second order reaction. Metal ions are transported from the bulk solution to the surface of an adsorbent and can diffuse into the interior if possible. If that is the case the intraparticle diffusion model would be applicable and is expressed as (Taffarel and Rubio, 2009):

qt = Kdt

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+C

(10)

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where KF (L/g) and n are the Freundlich constants representing the adsorption capacity and intensity, respectively. The Temkin isotherm model unlike the Langmuir and Freundlich model takes into account the interactions between adsorbents and metal ions to be adsorbed and is based on the assumption that the free energy of sorption is a function of the surface coverage. The linear form of the Temkin equation is expressed as (Temkin and Pyzhev, 1940):

where Kd (mg/gmin1/2) is the intraparticle diffusion rate constant, and C is the intercept. The intraparticle diffusion mechanism is involved if the plot of qt versus t1/2 is linear. Furthermore, intraparticle diffusion is the sole rate controlling mechanism if the linear plot passes through the origin (C = 0). The liquid film diffusion model is applicable when the transport of metal ions from the solution to the solid phase boundary of an adsorbent plays the most significant role in adsorption and is expressed as (Taffarel and Rubio, 2009):

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qe = B ln A + B ln Ce

(5)

ln (1 − F) = −Kfdt + P

(11)

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where B (mg/g) is related to the heat of adsorption and A (L/ mg) is the equilibrium binding constant corresponding to the maximum binding energy. The D-R isotherm model does not assume a homogenous surface or a constant sorption potential as the Langmuir isotherm and is expressed in its linear form as (Dubinin et al., 1947):

ln qe = ln qm − βε 2

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Chi-square test (χ2) analysis

where qm (mg/g) is the theoretical saturation capacity, β (mol2/ J2) is a coefficient corresponding to the mean free energy of sorption, ε = RTln(1 + 1/Ce) is the Polanyi potential, R is the ideal gas constant (8.314 J/mol K) and T (K) is the absolute temperature. The energy of adsorption E (kJ/mol) was calculated from the D-R isotherm from the equation (Guler and Sarioglu, 2013):

The chi-square (χ2) statistics along with the linear regression (R2) were used to determine the best fit isotherm or kinetic model. The closer the R2 to one and the smaller the χ2 values the better the fit of the model. The chi-square test is the sum of the squares of the differences between the experimental data and the data obtained by calculating from the models. χ2 is given as (Igberase et al., 2014):

E = 1 (2β )

2 X = ∑ ⎡⎣(qeexp − qecal ) qecal ⎤⎦

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(7)

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(6)

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where F (qt/qe) represents the fractional attainment of equilibrium, Kfd (mg/g min) is the film diffusion adsorption rate constant and P is the intercept. Film diffusion mechanism is applicable If the plot of −ln(1 – F) versus t is linear, if the plot passes through the origin (P = 0) then film diffusion is the sole rate determining step.

2.6.

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2

(12)

Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

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Q5 Fig. 1 – Effect of H2SO4 concentration and heating temperature on the sorption of heavy metals from the laboratory solution.

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where qeexp (mg/g) is the equilibrium capacity obtained from experiment, and qecal (mg/g) is the equilibrium capacity obtained by calculating from the model.

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3.

Results and discussion

3.1.

Optimization studies

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In order to determine the best condition of acid modification for optimum sorption, the modified acid adsorbents at different conditions were utilized for the sorption of 100 mg/L solution of Ni (II) and Mn (II) ions from a binary prepared laboratory solution. This was prepared by dissolving appropriate amounts of NiSO4, 6H20 and MnSO4.H2O in 1 L of distilled water. The pH of the solution was adjusted to 6.0 by the dropwise addition of 0.1 M HCl or NaOH. The batch sorption was performed using 0.1 g of the adsorbent in 50 mL of solution in 100 mL plastic bottle, particle size of 100 μm, contact time of 180 min at room temperature of 300 K. The acid modification of the montmorillonite was performed using various concentrations of H2SO4 ranging from 0.5 to 2.5 M as shown in Fig. 1. An increase in the adsorption capacity of the acid modified adsorbents with increase in acid concentration from 0.5 to 1.5 M was obtained, after which it reduced gradually. An optimum H2SO4 concentration of 1.5 M was then chosen for the acid activation and heated to various temperatures ranging from 50 to 300 °C (Fig. 1). Similarly, an increase in adsorption with calcinations temperature from 50 to 150 °C and a decrease from 150 to 300 °C was recorded. An optimum activation temperature of 150 °C was then chosen in this study. The initial increase in adsorption with increase in acid concentration is due to an increase in the surface area as a result of removal of impurities, replacement of exchangeable cation with hydrogen ions and the leaching of Al3+, Fe3+ and Mg2+ from the octahedral and tetrahedral sites, which exposes the edges of platelets of the clay (Tsai et al., 2007). The later decrease at higher concentrations may be due to the reduction in the surface area, attributed to the deeper penetration of H2SO4 into the voids and excessive leaching of cations, which

results in collapse of the layered structure (Doulia et al., 2009). Thus at higher acid concentrations there are less adsorption sites available for metal ions. Steudel et al. (2009) attributed the initial increase in adsorption with temperature to be the removal of adsorbed water resulting in the formation of pores, while the decrease above 150 °C is attributed to a decrease in the number of pores as a result of the coming together of particles to form aggregates. Excessive heating may lead to the irreversible collapse of the structure, therefore thermal activation of montmorillonite has to be carried out in a particular temperature range. Furthermore, the effect of heating time on the acid activation was studied in a time range of 30 to 360 min as illustrated in Fig. 2. An increase in adsorption with time up to 180 min was recorded and a decrease was obtained with further increase in time. The initial increase has been reported to be due to an increase in the surface area attributed to the removal of molecules already present and those that were attached during acid activation and washing (Bhattacharayya and Gupta, 2006). The subsequent decrease could be attributed to reduction in porosity as a result of the coming together of the particles, or excessive removal of molecules from the

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Fig. 2 – Effect of heating time on the adsorption capacity of acid activated montmorillonite for metal ions.

Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

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Table 1 – Physicochemical properties of the automobile effluent. Parameter

Value

pH Lead (mg/L) Zinc (mg/L) Copper (mg/L) Cadmium (mg/L) Nickel (mg/L) Manganese (mg/L) Chromium (mg/L)

6.5 2.91 19.38 14.50 6.09 2.04 9.81 0.46

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surface, which could have served as potential binding sites for metal ions.

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3.2.

Physicochemical characterization

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The heavy metal concentration of the automobile effluent is presented in Table 1 and has been discussed in a previous study (Akpomie and Dawodu, 2014). The physicochemical properties of UM and AMM are shown in Table 2. A slight increase in silica and a decrease in alumina with acid treatment leading to an increase in the silica to alumina ratio from 1.83 to 2.39 were obtained. This may be due to the leaching of cations such as Al3+, Mg2+ and Fe3+ from the octahedral and tetrahedral sheets by the acids. This was indicated by the decrease in percentage concentration of MgO and Fe2O3. The octahedral Al3+ cations could be more easily leached by acid attack than the tetrahedral Si4+ cations (Steudel et al., 2009). Treatment of clay minerals with high concentrations of acid can cause excessive leaching of the Al3+ ions resulting in rupture of the lattice structure and decrease in the clay specific surface area (Kooli et al., 2014). In order to avoid these complications, an appropriate concentration of acid suitable to obtain optimum adsorption potential for the acid treated montmorillonite was determined. Acid modification led to an increase in the BET surface area (SBET) from 55.76 to 96.48 m2/g, an increase in the total pore volume (TPV) from 0.0688 to 0.101 cm3/g and a decrease in the

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409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424

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Table 2 – Physicochemical characterization of the adsorbents. Parameter SiO2 (%) Al2O3(%) Fe2O3 (%) CaO (%) K2O (%) Na2O (%) MgO (%) TiO2 (%) MnO (%) LOI (%) SBET (m2/g) TPV (cm3/g) ´˚ ) APD (A CEC (meq/100 g) pHpzc Slurry pH

UM

AMM

47.32 25.91 2.14 3.39 1.07 2.86 3.14 0.12 0.43 13.56 55.76 0.0688 49.35 90.78 3.7 4.2

50.52 21.13 2.01 4.23 1.15 2.90 3.03 0.28 0.67 14.05 96.48 0.101 41.87 79.54 2.3 2.6

5

average pore diameter from 49.35 to 41.87 Å. The increase in surface area is desirable for effective adsorption. It has been reported that acid activation of clays alters the physical properties such as enhancing the surface area, average pore volume, porosity and surface acidity (Doulia et al., 2009). It also removes impurities such as calcite and exposes the edges of platelets, thereby leading to an increase in surface area. Babaki et al. (2008) also stated that the increase in surface areas of acid activated clays is attributed to the decomposition of the smectite structure within the clay lattice. The surface area of clays increases to a large extent if acid activation is followed by thermal activation (Khenif et al., 2007). Therefore the increase in surface area may be attributed to the reasons outlined above and the calcinations of the montmorillonite after acid treatment. The cation exchange capacity (CEC), which is the maximum quantity of total cations the clay can hold at a given pH available for exchange with a given solution, decreased from 90.78 to 79.54 mEq/100 g after acid treatment. During acid treatment more H+ ions were attached to the clay, which pushes other cations from the clay into the solution, resulting in the decrease in CEC. On the other hand, our previous study on the alkaline modification of the montmorillonite led to an increase in CEC from 90.78 to 94.32 mEq/100 g (Akpomie and Dawodu, 2014). The increase was attributed to fewer H+ ions available to push cations into the solution and the negative charges introduced by the OH− groups of the base. A relationship exist between the pHpzc and adsorption capacity of an adsorbent; at pH values lower than the pHpzc the surface of the adsorbent is positive favoring the adsorption of anionic species while for pH values higher than the pHpzc the surface is negative favoring cations adsorption (Nomanbhay and Palanisamy, 2005). Acid treatments resulted in a decrease in pHpzc from 3.7 to 2.3, indicating that AMM would be effective in adsorbing metal ions at pH values (greater than 2.3).

425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460

3.3.

FTIR, XRD and SEM analysis

The FTIR analyses of the montmorillonite before and after acid modification are shown in Fig. 3. The spectrum of UM (Fig. 3a) has been discussed previously (Akpomie and Dawodu, 2014). The spectrum of the acid modified montmorillonite (Fig. 3b) showed the persistence of the inner surface −OH peaks at 3620 cm −1 and 3697 cm −1 in both UM and AMM, this suggested that modification was not effected on this position of the montmorillonite. The change in the absorption band of −OH from (3441 cm−1 to 3443 cm−1, 1627 cm−1 to 1626 cm−1 and the disappearance of the 3410 cm−1 band) indicated that modification was effected on this position. During acid activation of clay, the protons penetrate into the clay layers attacking the OH groups causing the alterations in the adsorption bands attributed to the OH vibration and octahedral cations (Ozcan et al., 2005). The acid modified clay showed a new band of absorption at 2353 cm−1 corresponding to the OH stretching vibration, which was absent in UM, this might indicate the presence of free OH sites on AMM. Similar result has been reported (Manjot, 2010). The XRD spectrum of the montmorillonite before and after acid treatment is shown in Fig. 4. The spectra of UM showed

Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

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Fig. 3 – FTIR spectra of montmorillonite (a) before and (b) after acid modification.

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the presence of montmorillonite as the major component and also the presence of kaolinite, quartz and gibbsite as minute minerals (Akpomie and Dawodu, 2014). The increase in intensity of the montmorillonite peak after acid treatment suggests that the dealumination must have been from the gibbsite phase and not the montmorillonite phase. The SEM morphologies of the unmodified and acid treated montmorillonite are shown in Fig. 5. The porous nature of the adsorbents was revealed by the SEM images with an increase in surface porosity after acid treatment. The increase in the porous nature of AMM indicates that the metal ions removal from the automobile effluent would be enhanced.

3.4. Comparison of the adsorption capacity of the adsorbents

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In order to compare the adsorption potential of UM and AMM, batch sorption of the metal ions from the automobile effluent was conducted at optimum conditions (pH 6.5, adsorbent dose 0.1 g, particle size 100 μm and contact time 180 min). Fig. 6 shows the adsorption of heavy metals from the effluent on UM and AMM. It is clear that acid treatment of the montmorillonite enhanced the adsorption capacity for all the metal ions compared to the unmodified form. This is desirable in enabling effective treatment of contaminated aqueous media.

Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

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7

Fig. 4 – XRD spectra of montmorillonite (a) before and (b) after acid modification.

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3.5.

Effect of some operating variables on sorption

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The pH of the effluent has an important effect on heavy metals sorption since the pH of the solution controls the magnitude of electrostatic charges and the degree of ionization of the adsorbate (Abdelwahab and Amin, 2013). Therefore, the amount of metal adsorbed will vary with the pH of an aqueous medium. Fig. 7 shows the effect of pH on heavy metal removal from the automobile effluent on AMM. As observed, an increase in adsorption of metal ions with increase in pH was recorded, with significant adsorption occurring at pH values greater than the pHpzc of 2.3 at which the surface of AMM is negative. The increased competition between

protons and metal ions for the available sorption sites is responsible for the low removal efficiency at low pH values, because a large number of active sites on AMM may become positively charged at very low pH (Li et al., 2011). The adsorption process increased with increase in pH up to 6.0, this is attributed to the decrease in competition between protons and metal ions leading to a higher uptake (Liang et al., 2010). At high pH values (pH > 4.0) the hydroxide forms of the metal ions in solution may be precipitated. As a result, the effluent at pH of 5.0 to 8.0 was allowed to stand for 180 min without the addition of AMM in order to determine the amount of each metal ion precipitated and calculated from:

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527 528 529 530 531 532 533 534 535 536 537 538 539

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Fig. 7 – Effect of initial pH of effluent on the sorption capacity of AMM for heavy metals from the automobile effluent.

558 559 560 561

540 541 542 543 544 545 546 547 548 549 550 551 552 553 554

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Fig. 5 – SEM morphology of montmorillonite before and after acid modification.

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%P = 100 [Co − Ce] Co

(13)

which results in the sites remaining unsaturated during adsorption (Igberase et al., 2014). It may also be attributed to a decrease in the total surface area and an increase in the diffusion path length caused by aggregation of the particles of the adsorbent (Li et al., 2011). In general the following adsorption trend was obtained: Zn > Cu > Mn > Cd > Pb > Ni, which is directly related to the concentration of metal ions in the effluent. This implies that the higher the concentration of metal ion in the effluent the higher its adsorption capacity on AMM. This is because the initial metal ion concentration plays a significant role in determining the amount of metal ions adsorbed. This is expected as higher metal concentration generates a

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562 563 564 565 566 567 568 569 570 571 572 573

where Co (mg/L) and Ce (mg/L) are the initial and equilibrium concentrations of metal ions in the effluent. Table 3 shows the percentage of metal ions precipitated. Therefore the effluent pH of 6.5 was chosen and utilized as optimum adsorption was recorded and metal precipitation was minimal. The influence of adsorbent dose on the sorption of metal ions from the effluent is shown in Fig. 8. A decrease in the adsorption capacity of AMM for all the metal ions with increase in adsorbent dose was recorded. This decrease may be due to the higher adsorbent dose providing more active sorption sites,

Table 3 – Percentage precipitation of metal ions from the automobile effluent.

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pH % Zn(II) % Cu(II) % Mn(II) % Cd(II) % Pb(II) % Ni(II)

578

5.0 6.0 7.0 8.0

579 580 581 582

2.58 6.48 7.63 18.11

3.62 4.32 7.49 10.12

1.64 3.11 5.66 12.67

1.52 2.56 4.42 11.34

0.4 2.71 5.95 12.63

0 2.89 4.32 14.72

583 555

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Fig. 6 – Comparison of the adsorption capacity of UM and AMM for metal ions sorption from the automobile effluent.

Fig. 8 – Influence of adsorbent dose on the sorption capacity of AMM for heavy metals from the automobile effluent.

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9

for Zn (II), 90 min for Cu (II), 150 min for Mn (II), 180 min for Cd (II), 180 min for Pb (II) and 90 min for Ni (II) was obtained. The different equilibrium attainment rate may be attributed to differences in the hydrated ionic radii of the metal ions, represented as follows: Ni (II) (0.69 Å) < Cu (II) (0.72 Å), < Zn (II) (0.74 Å) < Mn (II) (0.80 Å) < Cd (II) (0.97 Å) < Pb (II) (1.20 Å). The metals with smaller ionic radii tend to diffuse faster, attaining equilibrium at a faster rate than metals with larger ionic radii. An equilibrium time of 180 min was chosen to ensure that equilibrium sorption of all metal ions was achieved.

3.6.

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Fig. 9 – Effect of adsorbent particle size on the sorption capacity of AMM for heavy metals from the automobile effluent.

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greater driving force for metal ions to be fixed on the adsorbent (Barka et al., 2013). The effect of particle size of AMM on the sorption of heavy metals from the automobile effluent is shown in Fig. 9. A decrease in the removal of metal ions with increase in particle size from 100 to 500 μm was obtained. This decrease may be attributed to a decrease in the specific surface area with increasing particle size (Karthikeyan et al., 2004). In order to determine the rate of equilibrium attainment, the influence of contact time on sorption of metal ions from the effluents unto AMM was determined as shown in Fig. 10. An increase in adsorption of metal ions with increase in contact time was recorded. The fast adsorption at the initial stages is attributed to an increased availability in the number of available active sites on AMM. The sorption rapidly occurs and is controlled by the diffusion process from the bulk to the surface of the adsorbent. In the later stages the adsorption diminished and attained equilibrium due to the utilization and subsequent saturation of the active sites, the sorption in this stage is likely an attachment controlled process due to less available adsorption sites (Das and Mondal, 2011). Ni (II) ions showed a negligible adsorption due to the very low concentration in the effluent. It is observed that the metal ions attained equilibrium at different time. An equilibrium time of 120 min

Equilibrium adsorption isotherms are useful in the design of an adsorption system, in order to evaluate the equilibrium data, the Langmuir, Freundlich, Temkin and Dubinin–Radushkevich (D-R) isotherm models were applied. The isotherm constants, linear regression coefficient (R2) and chi-square (χ2) parameters are given in Table 4. As observed the lower R2 and larger χ2 values presented by the Langmuir model when compared to the other isotherms indicates that this model does not give a good fit to the adsorption data. This implies that the sorption process is not attributed to a monolayer adsorption on a homogenous surface. However, the Langmuir RL values obtained for all the metal ions is in the range of 0.657 to 0.913 indicating a favorable adsorption on AMM. Furthermore, comparing the other isotherm models, it is found that the Freundlich model gave the best fit to the equilibrium data for the metal ions due to the highest R2 and low χ2 values recorded, which indicates a multilayer adsorption unto a heterogenous surface of the adsorbent (Bhattacharayya and Gupta, 2006). Although the Temkin isotherm was also found to be applicable for the sorption of Pb (II) and Ni (II) due to the lowest χ2 values recorded by this model. The calculated energy E of the D-R isotherm helps to classify the adsorption process as either a physical or chemical adsorption. The process is attributed to physisorption if the value of E < 8 kJ/mol, while values of E between 8 and 16 kJ/ mol corresponds to chemisorptions (Guler and Sarioglu, 2013). The values of E obtained for all the metal ions are below 8 kJ/ mol indicating that the adsorption process is a physical one. This physical adsorption is desirable due to the lower energy barrier to be overcome by metal ions for easy desorption from the surface of AMM during regeneration and recycling processes (Dawodu and Akpomie, 2014).

3.7.

615

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Fig. 10 – Effect of contact time on the sorption capacity of AMM for heavy metals from the automobile effluent.

Adsorption isotherms

Kinetic model analysis

Kinetic analysis helps in the prediction of the mechanism involved in sorption and identification of the rate limiting step of the process (Das and Mondal, 2011). The pseudo-first order, pseudo-second order, intraparticle diffusion and liquid film diffusion models were applied to evaluate kinetic data (Taffarel and Rubio, 2009). The calculated kinetic parameters, linear regression (R2) and chi-square (χ2) values are presented in Table 5. From the values of R2 and χ2 obtained for the pseudo first order and pseudo second order models, it is evident that the later presented the best fit to the kinetic data for all the metal ions except for Pb (II), which conformed to the pseudo first order model. Furthermore, looking at the experimental qe (qeexp) and

Please cite this article in press as: Kovo G. Akpomie, Folasegun A. Dawodu, Acid-modified montmorillonite for sorption of heavy metals from automobile effluent, Beni-Suef University Journal of Basic and Applied Sciences (2016), doi: 10.1016/j.bjbas.2016.01.003

618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677

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Table 4 – Equilibrium isotherm parameters for the sorption process on AMM.

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Isotherm model

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Langmuir Model qL (mg/g) KL (L/mg) R2 χ2 Freundlich Model KF (L/g) 1/n R2 χ2 Temkin Model A (L/g) B (mg/g) R2 χ2 D-R Model qm (mg/g) Β (mol2/J2) E (kJ/mol) R2 χ2

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714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736

Cu (II)

Mn(II)

Cd(II)

Pb(II)

Ni(II)

76.92 0.027 0.032 1.130

2.76 0.322 0.983 32.38

2.21 0.314 0.764 15.47

0.62 0.601 0.540 24.35

1.62 0.870 0.016 3.334

4.0 0.047 0.001 30.38

2.2 1.022 0.936 0.485

1.22 0.203 0.968 0.156

0.99 1.864 0.952 0.113

1.04 2.875 0.913 0.161

4.58 1.617 0.311 0.864

2.42 1.104 0.328 0.739

1.679 4.176 0.803 1.192

1.122 6.218 0.854 0.996

1.265 3.758 0.892 0.275

1.395 3.640 0.862 0.415

7.269 0.979 0.275 0.692

15.51 0.423 0.196 0.586

6.767 3 × 10−7 1.291 0.805 1.613

9.346 7 × 10−7 0.845 0.899 0.562

6.234 6 × 10−7 0.913 0.920 0.241

7.434 6 × 10−7 0.913 0.787 0.263

2.356 1 × 10−7 2.236 0.308 0.969

1.164 5 × 10−8 3.162 0.302 0.681

the model calculated qe (qecal) values, the qecal of the pseudo second order model was also closer to the qeexp than those of the pseudo first order model. Exception was also obtained again for Pb (II) ion, which supports the deduction obtained from the R2 and χ2 values. Most studies on the sorption of heavy metals from contaminated solutions have always presented the best fit with the pseudo-second order model (Aroua et al., 2008; Khambhaty et al., 2009). In order to identify the diffusion mechanism, the intraparticle diffusion and liquid film diffusion models were

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Zn(II)

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considered. The low R2 values presented by the intraparticle diffusion model suggest that the sorption process was not controlled by intraparticle diffusion mechanism. However, the high values of R2 presented by the liquid film diffusion model indicate that the rate limiting step of sorption involves film diffusion mechanism. It has been reported that in a well agitated batch system, the external diffusion resistance is much reduced; hence intraparticle diffusion is more likely to be the rate controlling step (Piccin et al., 2012). However in this study, the adsorption was allowed to proceed in a settled condition

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Table 5 – Kinetic model parameters for the sorption process on AMM. Model

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Pseudo-first order model qeexp (mg/g) qecal (mg/g) KI (min−1) R2 χ2 Pseudo-second order model qecal (mg/g) h (mg/g min) K2 (g/mg min) R2 χ2 Intraparticle diffusion model Kd(mg/g min1/2) C R2 Film diffusion model Kfd (mg/g min) P R2

Metals Zn(II)

Cu(II)

Mn(II)

Cd(II)

Pb(II)

Ni(II)

8.19 14.79 0.032 0.951 21.72

6.05 9.55 0.035 0.909 56.34

3.81 7.33 0.025 0.920 18.41

2.45 4.37 0.021 0.977 19.623

1.31 2.35 0.012 0.921 4.418

0.92 1.23 0.018 0.915 0.482

9.43 0.299 0.003 0.987 0.266

6.85 0.275 0.006 0.979 0.427

4.81 0.088 0.004 0.957 0.217

3.32 0.037 0.003 0.979 0.033

0.07 0.0003 0.063 0.333 163.79

1.27 0.0163 0.01 0.842 0.183

0.368 3.017 0.709

0.258 2.567 0.590

0.219 0.733 0.738

0.150 0.154 0.841

0.134 0.778 0.839

0.056 0.145 0.603

0.033 0.62 0.950

0.035 0.45 0.889

0.027 0.625 0.915

0.021 0.575 0.879

0.012 0.595 0.921

0.18 0.29 0.989

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at a given contact time and not under the influence of agitation, which might be the reason why film diffusion was the rate controlling mechanism rather than the intraparticle diffusion. However, the occurrence of the intercept suggests that film diffusion is not the sole rate controlling mechanism in the sorption of heavy metals from the automobile effluent on AMM.

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4.

Conclusion

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This research work showed that the acid treatment of the montmorillonite improved its adsorption capacity for heavy metals from the automobile effluent. SEM morphology revealed an increase in porous nature of AMM. The adsorption capacity of the adsorbent for each metal ion was found to be strongly dependent on the initial concentration of the metal ions in the effluent, while the rate of sorption and equilibrium attainment was affected by the ionic radii of the metal ions. The process was found to be a physical adsorption as revealed from the energy of the Dubinin–Radushkevich isotherm, while film diffusion was found to be the rate controlling mechanism of the sorption process.

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