Aniline Removal from Aqueous

Article pubs.acs.org/jced

Binary Fixed Bed Modeling of Phenol/Aniline Removal from Aqueous Solutions onto Hyper-Cross-Linked Resin (Macronet MN200) César Valderrama,*,† Jordi Poch,‡ Joan I. Barios,§ Adriana Farran,† and José Luis Cortina†,§ †

Departament d'Enginyeria Química, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain Departament d'Informàtica i Matemàtica Aplicada, Universitat de Girona, 17071 Girona, Spain § Water Technology Center CETaqua, 08034 Barcelona, Spain ‡

ABSTRACT: The sorption performance of hyper-cross-linked Macronet resin (MN200) to remove phenol and aniline from aqueous solution has been evaluated. Fixed bed column experiments were undertaken to obtain the breakthrough curves in both single and binary solutions. The film-surface diffusivity model has been used to predict the single (phenol and aniline) fixed bed breakthrough curves by using the Langmuir and Freundlich single isotherm data to represent the equilibrium. A good description of the experimental data has been obtained by both isotherms, and the mass transfer coefficient and the surface diffusivity have been obtained as optimized parameters for both solutes. The binary breakthrough curve prediction has been performed by the film surface diffusion model, incorporating an equilibrium relationship defined by the extended Langmuir isotherm model and the ideal sorbed solution theory (IAST). The sum of square errors (SSE) obtained for the IAST approach confirms the good agreement between the experimental and the predicted breakthrough data and the deviation obtained for the extended Langmuir model. The surface diffusivities in binary sorption reported a significant difference to those obtained in a single system, indicating that binary sorption is mainly controlled by the intraparticle diffusion.

1. INTRODUCTION Phenol and aniline are priority contaminants in many countries and can be found in the effluents from chemical, pharmaceutical, and different industries.1−4 Taking into account their toxicity and reactivity, their removal from waste streams has increasingly become of significant environmental concern.4,5 In the past two decades, polymeric sorbents have been postulated as an alternative to activated carbon for efficient removal of organic pollutants from wastewater in industrial applications.3,6−8 A significant issue related to the polymeric sorbents is that the bonding forces between the sorbent and the solute are usually weaker than those encountered in conventional sorbents. Regeneration of the resin can be accomplished by a simple process, such as solvent washing, thus providing the potential capacity for solute recovery.9−11 In previous studies, the sorption equilibrium,12 kinetics,13 and fixed-bed column14 of phenol and aniline in single and binary systems have been investigated. These studies demonstrated that due to the repulsive or attractive action between phenol and aniline and the surface of sorbents, binary sorption is rationally expected to be competitive or synergistic. The synergistic sorption was found on activated carbon and the competitive sorption was found on the resin MN200.12−14 From the view of sorption modeling, the dynamic behavior of a fixed-bed column is described in terms of the breakthrough curve.15 To properly design and operate fixed-bed sorption © 2012 American Chemical Society

processes, the sorption isotherm and the pollutant breakthrough curves must be known. Although the removal of phenolic compounds from water effluents through sorption on different types of sorbents has been the object of many studies,16 only a few of them addressed the simulation or prediction of the pattern of the phenol− aniline breakthrough curves in a binary system. Understanding of the dynamics of fixed bed sorption column for modeling is a demanding task due to the strong nonlinearities in the equilibrium isotherms, interference effects of competition of solute for sorbent sites, mass transfer resistance between fluid phase and solid phase, and fluid-dynamics dispersion phenomena. The interplay of these effects produces steep concentration fronts, which moves along the column during the sorption process.17 Therefore, the objective of present work is the development of a mathematical model, which considers the effects mentioned above and their interaction for the prediction of lumped concentration of phenol and aniline removed by resin MN200 from industrial wastewater in a fixed-bed column in binary system. The film-surface diffusivity model has been used to predict the single fixed-bed breakthrough curves by applying Received: January 11, 2012 Accepted: April 14, 2012 Published: April 24, 2012 1502

dx.doi.org/10.1021/je3001415 | J. Chem. Eng. Data 2012, 57, 1502−1508

Journal of Chemical & Engineering Data

Article

2.4. Fixed-Bed Modeling. The fixed-bed film-surface diffusion model was proposed by Ko et al.,19 and it is based on the presumption that the external film diffusion and the surface diffusion determine the solute penetration rate. In accordance with this assumption and mass transport mechanisms, the following set of mathematical equations can be derived. The overall mass balance for each component in the column is expressed in the following equation:

the Langmuir and Freundlich isotherms to describe the equilibrium relationship for phenol and aniline onto resin MN200. The binary breakthrough curve prediction has been performed by a multicomponent mass transport model based on film-surface diffusion and applying the extended Langmuir isotherm and the ideal sorbed solution theory (IAST).

2. MATERIALS AND METHODS 2.1. Materials. Macronet resin MN200 sample was provided by Purolite Ltd. The polymer matrix structure is a cross-linked poly(styrene). The elemental analysis of resin (given as mass %) reported: 85.61 % of carbon; 6.87 % of hydrogen; 1.09 % of chlorine and 6.43 % of oxygen (determined by residual).18 Previous to the sorption experiments, the resin samples were treated in methanol−hydrochloric acid mixtures and then rinsed in water. A proper characterization of the sorbent was performed and reported in previous published studies.11−14,18 Some selected parameters are summarized in Table 1. The aqueous solutions were

⎡ ∂C ⎤ ⎡ ∂C ⎤ ⎛ 1 − ε ⎞⎡ ∂qi ⎤ ⎟⎢ ν ⎢ i ⎥ + ⎢ i ⎥ + ρ⎜ ⎥ =0 ⎝ ε ⎠⎣ ∂t ⎦ ⎣ ∂Z ⎦t ⎣ ∂t ⎦Z Z

where ν is the linear flow rate in the column, Z is the bed depth, t is the service time, ρ is the particle density of the resin MN200, ε is the porosity of the bed, C is the liquid-phase concentration, and q is the solid-phase concentration. For a spherical particle, the mass transfer through the stagnant liquid film for each component is defined by eq 2 as: ⎡ ∂q ⎤ 3k fi (Ci − Csi) ρ⎢ i ⎥ = R ⎣ ∂t ⎦Z

Table 1. Physical Characterization of Resin MN200 parameter

resin MN200

BET surface area/m2·g−1 Langmuir surface area/m2·g−1 t-plot micropore area/m2·g−1 micropore volume/cm3·g−1 % micropores average pore diameter/nm particle size/mm

793 1058 543 0.25 68 3.7 0.5−0.7

(1)

(2)

where kfi is the external film transport coefficient, Csi is the liquid-phase concentration at the particle surface, and R is the radius of resin MN200. Substitute eq 2 into eq 1, thus obtaining: ⎡ ∂C ⎤ ⎡ ∂C ⎤ ⎛ 1 − ε ⎞ 3k fi ⎟ (Ci − Csi) = 0 ν⎢ i ⎥ + ⎢ i ⎥ + ⎜ ⎣ ∂Z ⎦t ⎣ ∂t ⎦Z ⎝ ε ⎠ R

(3)

Considering that the cross diffusion effect is small and thus the cross diffusivities Ds,ij i ≠ j contribution to the overall diffusion is negligible, the Fickian diffusion equation for each component can be expressed as:19

prepared by dissolving phenol (IUPAC: benzenol) and aniline (IUPAC: phenylamine) (both purchased from Merck with a mole fraction purity of 0.99) into deionized water (Milli-Q, Millipore) without further pH adjustment. The solute initial concentration in single experiments was 0.52 mmol·L−1 approximately. 2.2. Sorption Column Experiments. Sorption experiments were performed as reported in previous published works: “All column experiments were conducted in duplicate in glass columns of 72 mm length and 10 mm internal diameter (Omnifit), uniformly packed with (1.45 to 1.50) g of sorbent treated as explained above. During the column sorption operation, the aqueous solution containing constant inlet concentration of solute or bi-solute (single and binary system, respectively) was pumped upwards through the column at a constant flow rate 0.008 cm3·s−1. Samples were collected from the outlet of the column by a fraction collector (Gilson FC204) at pre-set time intervals”.12−14 The reproducibility of the results was greater than 95 % after two replicates for each experiment. 2.3. Phenol and Aniline Analysis. The solute determination was performed as described in previous published works: “Phenol and aniline concentration were determined spectrophotometrically (Hewlett Packard, model HP-8453). In a single solute experiment the absorbance values, before and after treatment were measured at their respective maximum wavelength, 269 nm and 284 nm for the phenol and aniline, respectively. To determine the single component concentration on the phenol and aniline mixtures, a two equation system was resolved for both compounds using the two overlapping signals from the UV spectra. The equation system was used and reported in previous published studies”.12−14

∂qi ∂t

=

1 ∂ ⎡ 2⎛ ∂qi ⎞⎤ ⎢r ⎜Ds , ii ⎟⎥ ∂r ⎠⎥⎦ r 2 ∂r ⎢⎣ ⎝

(4)

which following boundary conditions at the center and surface of the resin: ∂qi ∂r

Ds, ii

=0 (5)

r=0

∂qi ∂r

= r=R

k f, i ρ

(Ci − Cs, i) (6)

The boundary condition at the input column: Ci = C0, i

for t ≥ 0 and Z = 0

(7)

and the following initial conditions qi = 0

for t = 0 and 0 ≤ r ≤ R

Ci(Z = 0) = C0 Ci(Z > 0) = 0

for t > 0 for t = 0

(8) (9) (10)

The accuracy of model prediction in the single and binary system was evaluated quantitatively based on the sum of square errors (SSE) and also by the mean square of errors (MSE), which were calculated based on the sum of the difference between the experimental results and the theoretical data:20 1503



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n

SSE =

∑ (Ci ,exp − Ci ,theo)2 i=1

MSE =

SSE N

(11)

(12)

where N is the number of data points

3. RESULTS AND DISCUSSION 3.1. Single Sorption of Phenol and Aniline in a FixedBed Column. The following equation describes the concentration-dependent surface diffusivity:21 Ds = Ds0

∂ ln C ∂ ln q

Figure 1. Experimental (□, phenol; ○, aniline) and predicted breakthrough for ---, phenol and , aniline single sorption onto resin MN200 based on the film-surface diffusion model.

(13)

where Ds0 and Ds are the surface diffusivity at zero loading and the surface diffusion coefficient and are also independent and dependent on the sorbed concentration, respectively; this amount sorbed is determined from the sorption isotherm relationship. Furthermore Ds is expected to increase with an increase in the amount sorbed (q).21 The Langmuir and Freundlich isotherms were selected to evaluate the applicability of the concentration-dependent surface diffusion model. The Langmuir isotherm was considered since sorption equilibrium is commonly described by this model and the Freundlich isotherm due to the better fit to the isotherm data in the phenol and aniline/resin MN200 systems, as was reported in previous equilibrium batch experiments.12 The sorption loadings (q) for both models are described by the eqs 14 and 15 as follows: q=

The sorption of aromatic compounds in a nonfunctionalized support as MN200 is in principle a combination of two forces: van der Waals forces and a thermodynamic gradient determined by the hydrophobicity driving them out of the aqueous solution. Polystyrene−divinylbenzene sorbents, including hyper-cross-linked polystyrene, usually have a high hydrophobic surface. MN200 has a high affinity for solutes such as phenol or aniline with phenyl groups.22 It was also reported in Table 2 that this sorption capacity was higher for aniline than phenol on resin MN200. This fact was also observed in a previous equilibrium batch study, which reported a higher sorption capacity for aniline than phenol. It can be explained by the hydrophobic difference between phenol and aniline and also by the fact that aniline molecule has a greater electron density in the ring which supplies more π-electrons to the solid interaction (resulting in a larger sorption capacity).14 No significant differences were observed for the mass transfer coefficient kf (also reported in Table 2) between both solutes and slight increase in the aniline surface diffusivity was observed; thus a relative faster movement of aniline than phenol can be correlated to the higher hydrophobicity and the greater electron density. 3.2. Binary Sorption of Phenol/Aniline in a Fixed-Bed Column. For binary sorption studies, a molar fraction of 0.5 ± 0.01 was defined for both solutes. The breakthrough curves obtained in single and binary sorption system onto the resin MN200 are compared in Figure 2. As can be seen, the breakthrough curves for both solutes in binary system reported an earlier breakpoint and exhaustion/saturation point (0.01 and 0.48 molar fraction) than the single one. Parameters in the binary system follow the same trend that those previously reported in single one, thus, aniline reported higher sorption capacity than phenol for resin MN200. The binary breakthrough curves were predicted throughout the film-surface diffusion model and extended Langmuir isotherm, which can be defined in a binary system as follows:17,23

qmbCe 1 + KLCe

q = KCe1/ n

(14) (15)

where qm is the maximum loading of the sorbent, KL is the Langmuir isotherm constant, b is the Langmuir sorption constant, K is the sorption Freundlich constant, and n is the Freundlich exponent; values of n > 1 represent favorable sorption. Isotherm parameters in single sorption experimental data were determined from the linearized forms of the Freundlich and Langmuir isotherm equations (eqs 14 and 15) and are also reported in Table 2. The results of fixed bed experiments were used to obtain the breakthrough curves for both solutes onto resin MN200 and are shown in Figure 1. The simulation based on the film-surface diffusion model incorporating both Freundlich and Langmuir isotherms was performed to predict the breakthrough curves for both solutes in single system as can be seen in Figure 1. Film-surface diffusion model describes properly the experimental breakthrough curve experiment for phenol and aniline onto resin MN200 as can be seen in Figure 1. The predicted results, including the optimized kf and Ds0, the minimized SSE, for the film-surface diffusion model using the Freundlich and the Langmuir isotherms are summarized in Table 2. On the other hand, no significant differences were observed for the film-surface diffusion model incorporating Langmuir or Freundlich isotherms for breakthrough prediction; in fact the theoretical line in Figure 1 is almost identical for both isotherms, and the SSE and MSE parameters (Table 2) are in the same order of magnitude.

qe,1 =

qe,2 = 1504

qmax ,1b1Ce,1 1 + b1Ce,1 + b2Ce,2

(16)

qmax ,2b2Ce,2 1 + b1Ce,1 + b2Ce,2

(17)



Article

Table 2. Film-Surface Diffusion Model Optimized Parameters in Single Phenol and Aniline Sorption onto Resin MN200 Incorporating Langmuir and Freundlich Isotherms model

Langmuir

Freundlich

parameter/solute

phenol

aniline

parameter/solute

phenol

aniline

b/L·mmol−1 qmax/mmol·g−1 kf/cm·s−1 Ds0/cm2·s−1 SSE MSE

0.37 2.88 6.84·10−4 3.14·10−6 7.74·10−4 4.30·10−5

0.29 3.77 1.37·10−3 1.24·10−6 4.33·10−4 2.88·10−5

K/(mmol·g−1)·(mmol·L−1)−1/n n kf/cm·s−1 Ds0/cm2·s−1 SSE MSE

0.68 1.75 2.11·10−4 8.98·10−7 3.48·10−4 2.32·10−5

0.65 2.39 2.21·10−4 9.09·10−7 1.07·10−3 5.94·10−5

Figure 2. Experimental breakthrough curves of phenol and aniline in ○, single and □, binary sorption onto resin MN200.

Figure 3. Experimental (○, single; □, binary) and predicted (, single; ---, binary) breakthrough for phenol and aniline sorption onto resin MN200 based on the film-surface diffusion model and extended Langmuir multicomponent isotherm.

where bi and qmax,i are the Langmuir isotherm model parameters reported in previous section (Table 2) for a single-solute system. The simulation model based on the incorporation of the extended Langmuir multicomponent isotherm into the kinetic film-surface diffusion model (eqs 1 to 10) used for breakthrough curves prediction of a binary system is shown in Figure 3. The numerical solutions (written in Matlab R2008b) for the fluid and solid phase partial differential equations (PDEs) were coupled and solved by applying a forward difference scheme to the fluid phase PDE and the Crank−Nicolson method to the solid phase PDE.21 The poor description of the experimental breakthrough curves by the film-surface diffusion model incorporating the extended Langmuir multicomponent isotherm can be related to the fact that the Langmuir isotherm is derived based on a monolayer homogeneous surface sorption process, whereas the resin MN200 presented a complex sorbent surface, thus introducing heterogeneity onto the surface and violating the

assumption of the Langmuir isotherm equation. Similar results were obtained for Ko et al.24,25 The binary sorption data can be predicted using single component isotherm relationships by the ideal sorbed solution theory (IAST). The IAST model determines that the spreading pressure (π) for each solute should be constant at equilibrium.26 It means that π is defined as the interfacial tension difference between the pure solvent−solid and solution−solid interface at the same temperature. The spreading pressure of solute will remain invariable when it is mixed with other solutes in a multicomponent sorption system. Thus, the pressure of sorbate (πi) is equal to that of each single component and to that of the mixture, (πm), and can be written as:27 πmA = RT

∫0

qi0

d(ln Ci0) d(ln qi0)

dqi0 =

πieA = (i = 1 − N ) R gasT (18)

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Figure 4. Experimental (○, single; □, binary) and predicted (, single; ---, binary) breakthrough for phenol and aniline sorption onto resin MN200 based on the film-surface diffusion model-IAST approach.

By incorporating the IAST model (eq 26) into the kinetic filmsurface diffusion model (eqs 1 to 10), the effluent concentration of the both solutes (phenol and aniline) onto resin MN200 in the binary sorption system can be predicted. The numerical solutions for the fluid and solid phase PDEs were solved by using a finite difference method. A forward difference scheme was applied to the fluid phase PDE and the Crank−Nicolson method to the solid phase PDE.21 The phenol and aniline experimental data and the predicted breakthrough curves by the film-surface diffusion model-IAST approach are shown in Figure 4. The film-surface diffusion model-IAST approach describes properly the experimental breakthrough curves for phenol and aniline binary sorption onto the resin MN200 as can be seen in Figure 4. The Freundlich parameters obtained in single solute sorption and reported in Table 2 were used with 95 % confidence to determine the optimized parameters kf and Ds0 for both solutes in binary system (Table 3).

where Rgas is the universal gas constant, A is the surface area of the sorbent, Ci0 is the initial liquid-phase concentration of sorbate i, qi0 is the solid-phase surface loading corresponding to Ci0, and πie is the spreading pressure of sorbate i at equilibrium. On the basis of the Freundlich isotherm (eq 15), a relationship for predicting multicomponent sorption can be expressed28 as follows: d(ln Ci0) d(ln qi0)

= ni (19)

Equation 18 is simplified by the substitution of eq 19 as follows: n1q10 = n2q20 = ... = njqj0

(20)

the total solid-phase loading (qT) and the mass fraction of sorbate i, Zmi, are expressed: N

qT =

∑ qi i=1

Zmi =

qi qT

(21)

Table 3. Film-Surface Diffusion Model Optimized Parameters in Binary Phenol and Aniline Sorption onto Resin MN200 Incorporating Langmuir and IAST-Freundlich Approach

(i = 1 − N ) (22)

Ci = ZmiCi0(i = 1 − N )

model

(23)

By combining eqs 21 to 23, the following is obtained: 1 = qT

N

∑ i=1

Zmi qi0

(24)

By substitution of eq 20 onto eq 24, the following is obtained: qi0 =

(25)

By combining eqs 15 and 25 with eq 23, the IAST based on the Freundlich isotherm is obtained. The equilibrium concentration of solute i in the presence of other solutes (Csi) is expressed in terms of the solid-phase loading of solute i (qi) on the resin MN200 particle at r = R through the Freundlich parameters of Ki and ni.26 ⎛ ∑2 n q ⎞ni ⎜ j=1 j j ⎟ Cs , i = 2 ∑ j = 1 qj ⎜⎝ niK i ⎟⎠

IAST-Freundlich

phenol

aniline

phenol

aniline

kf/cm·s−1 Ds0/cm2·s−1 SSE MSE

9.45·10−4 2.86·10−6

1.10·10−3 1.71·10−7

2.25·10−4 5.15·10−8 3.16·10−3 7.34·10−5

2.12·10−4 2.22·10−7

0.570 0.013

The SSE and MSE parameters obtained for the IAST approach confirms the good agreement between the experimental and the predicted breakthrough and the significant deviation for the extended Langmuir model. On the other hand, the mean optimized surface diffusivities, Ds, for phenol and aniline where the smaller of those obtained in a single system, and further, the mass transfer coefficient, did not report significant differences between binary and single sorption systems. This fact can indicate that the intraparticle diffusion step is the controlling mechanism in binary sorption as was determined in a previous batch kinetic study.13 However, further developments in terms of the model should be performed, for instance, the use of concentration-dependent diffusivities or the incorporation of the cross diffusivity terms to describe the mass transport behavior within the sorbent.

N ∑ j = 1 njqj

ni

Langmuir

parameter/solute

qi

(26) 1506



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(7) Oh, C.-G.; Ahn, J.-H.; Ihm, S.-K. Adsorptive removal of phenolic compounds by using hypercrosslinked polystyrenic beads with bimodal pore size distribution. React. Funct. Polym. 2003, 57, 103−111. (8) Kujawski, W.; Warszawski, A.; Ratajczak, W.; Porebski, T.; Capała, W.; Ostrowska, I. Application of pervaporation and adsorption to the phenol removal from wastewater. Sep. Purif. Techol. 2004, 40, 123. (9) Busca, G.; Berardinelli, S.; Resini, C.; Arrighi, L. Technologies for the removal of phenol from fluid streams: A short review of recent developments. J. Hazard. Mater. 2008, 160, 265−288. (10) Lin, S. H.; Juang, R. S. Adsorption of phenol and its derivatives from water using synthetic resins and low-cost natural adsorbents: A review. J. Environ. Manage. 2009, 90, 1336−1349. (11) Streat, M.; Sweetland, L. A. Physical and adsorptive properties of Hypersol-Macronet polymers. React. Funct. Polym. 1997, 35, 99− 109. (12) Valderrama, C.; Barios, J. I.; Farran, A.; Cortina, J. L. Evaluating binary sorption of phenol/aniline from aqueous solutions onto granular activated carbon and hypercrosslinked polymeric resin (MN200). Water, Air, Soil Pollut. 2010, 210, 421−434. (13) Valderrama, C.; Barios, J. I.; Caetano, M.; Farran, A.; Cortina, J. L. Kinetic evaluation of phenol/aniline mixtures adsorption from aqueous solutions onto activated carbon and hypercrosslinked polymeric resin (MN200). React. Funct. Polym. 2010, 70, 42−150. (14) Valderrama, C.; Barios, J. I.; Farran, A.; Cortina, J. L. Evaluation of Phenol/Aniline (Single and Binary) Removal from Aqueous Solutions onto Hyper-cross-linked Polymeric Resin (Macronet MN200) and Granular Activated Carbon in Fixed-Bed Column. Water, Air, Soil Pollut. 2011, 215, 285−297. (15) Chu, K. H. Improved fixed bed models for metal biosorption. Chem. Eng. J. 2004, 97, 233−239. (16) Richard, D.; Delgado Núñez, M. L.; Schweich, D. Adsorption of complex phenolic compounds on active charcoal: Breakthrough curves. Chem. Eng. J. 2010, 158, 213−219. (17) Sulaymon, A. H.; Ahmed, K. W. Competitive Adsorption of Furfural and Phenolic Compounds onto Activated Carbon in Fixed Bed Column. Environ. Sci. Technol. 2008, 42, 392−397. (18) Streat, M.; Sweetland, L. A. Removal of pesticides from water using hypercrosslinked polymer phases: Part 1 - Physical and chemical characterization of adsorbents. Process Safety Environ. Prot. 1998, 76, 115−126. (19) Ko, D. C. K.; Porter, J. F.; McKay, G. Multicomponent Mass Transport Model for the Sorption of Metal Ions on Bone Char. AIChE J. 2004, 50, 2130−2141. (20) Vazquez, G.; Alonso, R.; Freire, S.; Gonzalez-Alvarez, J.; Antorrena, G. Uptake of phenol from aqueous solutions by adsorption in a Pinus pinaster bark packed bed. J. Hazard. Mater. 2006, B133, 61− 67. (21) Ko, D. C. K.; Porter, J. F.; McKay, G. Effect of concentration dependent surface diffusivity on simulation on fixed bed sorption systems. Trans. IChemE Part A 2003, 81, 1323−1332. (22) Caetano, M.; Valderrama, C.; Farran, A.; Cortina, J. L. Phenol removal from aqueous solution by adsorption and ion exchange mechanisms onto polymeric resins. J. Colloid Interface Sci. 2009, 338, 402−409. (23) Vilar, V. J. P.; Loureiro, J. M.; Botelho, C. M. S.; Boaventura, R. A. R. Continuous biosorption of Pb/Cu and Pb/Cd in fixed-bed column using algae Gelidium and granulated agar extraction algal waste. J. Hazard. Mater. 2008, 154, 1173−1182. (24) Ko, D. C. K.; Cheung, C. W.; Porter, J. F.; McKay, G. Sorption equilibria of metal ions on bone char. Chemosphere 2004, 54, 273−281. (25) Ko, D. C. K.; Porter, J. F.; McKay, G. Application of the concentration-dependent surface diffusion model on the multicomponent fixed-bed adsorption systems. Chem. Eng. Sci. 2005, 60, 5472−5479. (26) Ahmad, A. L.; Chong, M. F.; Bhatia, S. Prediction of Breakthrough Curves for Adsorption of Complex Organic Solutes Present in Palm Oil Mill Effluent (POME) on Granular Activated Carbon. Ind. Eng. Chem. Res. 2006, 45, 6793−6802.

4. CONCLUSIONS The results show that resin MN200 can be used as sorbent for the removal of phenol and aniline from aqueous solutions in a fixed-bed column configuration. The experimental breakthrough curves can be properly described by the film-surface diffusivity model and applying the Freundlich and Langmuir isotherms. A fairly good agreement between the predicted and the experimental breakthrough data for single system was reported for both equilibrium models. The binary breakthrough curves followed the same trend observed in the single system; thus, sorption capacity was higher for aniline than for phenol due to the greater electron density in the ring of the aniline molecule. A model was developed and applied by incorporating the extended Langmuir and the IAST approaches to the filmsurface diffusivity model to describe the equilibrium relationship for the sorption of binary phenol/aniline system on resin MN200 in fixed bed configuration. The IAST-film-surface diffusivity model described properly the breakthrough data, and a good agreement between experimental and predicted curves was obtained. Furthermore, based on the optimized parameters obtained, the intraparticle diffusion step is the mechanism which controls the sorption of phenol and aniline in the binary system.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel.: 93 4011818. Mailing address: Universitat Politècnica de Catalunya, Departá ment d’Enginyeria Quimica, Av. Diagonal 647, Edifici H Planta 4a, Barcelona 08028, Spain. Funding

We acknowledge the contribution of MEC Projects CTQ200806842-C02-01/PPQ and CTM2008-06776-C02-01 (Spanish Ministry of Education and Science) and the Catalan government (project ref 2009SGR905). We would also like to thank Purolite Ltd. for the MN200 samples. Notes

The authors declare no competing financial interest.

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REFERENCES

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(27) Lo, I. M. C.; Alok, P. A. Computer simulation of activated carbon adsorption for multicomponent systems. Environ. Int. 1996, 22, 239−252. (28) Crittenden, J. C.; Luft, P.; Hand, D. W.; Oravltz, J. L.; Loper, S. W.; Arl, M. Prediction of multicomponent adsorption equilibria using ideal adsorbed solution theory. Environ. Sci. Technol. 1995, 19, 1037− 1043.

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