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Multicomponent Adsorption and Desorption of BTX Compounds Using Coconut Shell Activated Carbon: Experiments, Mathematical Modeling, and Numerical ...
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Multicomponent Adsorption and Desorption of BTX Compounds Using Coconut Shell Activated Carbon: Experiments, Mathematical Modeling, and Numerical Simulation Adriana Dervanoski Luz,* Selene Maria de Arruda Guelli Ulson de Souza, Cleuzir da Luz, Ricardo Vicente de Paula Rezende, and Antônio Augusto Ulson de Souza Chemical Engineering Department, Federal University of Santa Catarina, Laboratory of Numerical Simulation of Chemical Systems, Campus Universitário, 88040-900 Florianópolis, Santa Catarina, Brazil ABSTRACT: A numerical and experimental study of the monocomponent and multicomponent adsorption and desorption of BTX compounds (benzene, toluene, and o-xylene) in a batch reactor and fixed-bed column was carried out in aqueous solution at 23 °C, using coconut shell activated carbon as the adsorbent. The monocomponent Langmuir isotherm model best represented the experimental results (average R2 = 0.9952) and the multicomponent Langmuir model, using the multicomponent parameters, represented the multicomponent data obtained in a fixed-bed column better than the monocomponent model. The equations which describe the phenomenology were discretized using the Finite Volumes Method with the WUDS and CDS formulations. The results for the monocomponent breakthrough curves obtained through simulation showed good agreement when compared with the experimental data (maximum error of 11.52%). For the monocomponent breakthrough curves the greatest deviation was observed for the compound which had the least affinity for the solid phase (benzene). The best results for the desorption of the BTX compounds from the adsorbent were obtained using ethanol as the desorbent solvent, and the average removal percentages in three cycles of regeneration in the column were 90% for benzene, 82% for toluene, and 78% for o-xylene.

1. INTRODUCTION The contamination of natural resources, mainly water resources, has increased the general public’s awareness of the need for environmental preservation. Environmental legislation, monitoring tools, and economic implications have been fundamental instruments of environmental policy with regard to the discharge of effluents. Thus, studies are being directed toward the treatment of contaminated streams at the source (integrated approach) and the treatment of final effluents (endof-pipe approach).1−4 In industry, the search for new technologies is focused on the need for more efficient processes for the removal of contaminants, seeking less demanding processes with low installation and operation costs, and more compact units which operate with greater flexibility and with good performance in the removal of toxic compounds.5 The BTX compounds, benzene, toluene, and xylenes, present in petroleum industry effluents, are hydrocarbons which have a high contamination potential.6−9The United States Environmental Protection Agency (USEPA) has classified these compounds as priority chemical contaminants.10,11They are powerful depressors of the central nervous system and have chronic toxicity and potential mutagenicity, even in low concentrations. Benzene is the most toxic of the BTX compounds, due to its confirmed carcinogenic action, and it can cause leukemia and tumors in multiple organs. Acute exposure by inhalation or ingestion can even lead to death.1,10,11 According to Lin and Huang,12 there are several treatment technologies available for the removal of these organic compounds from aqueous effluents, such as biological processes, incineration, oxidation, and adsorption. Each of © XXXX American Chemical Society

these processes has its advantages and disadvantages; however, adsorption is the most effective method for effluent treatment. Also, the other processes are generally more expensive and are not able to reach the concentration limits established for effluents discharged to water bodies. A commonly used and low-cost adsorbent which has a great affinity for organic compounds is granulated activated carbon. This is recommended as an adsorbent for the elimination of volatile organic compounds. According to Leitão and Rodrigues,13 Chatzopoulos et al.,14 and Wibowo et al.,15 adsorption with activated carbon is a proven and reliable technology for the industrial removal of small quantities of organic compounds which are soluble in water and industrial effluents. According to Wibowo et al.,15 activated carbon is one of the most important microporous adsorbents from the industrial point of view, and it can be regenerated and reused for several adsorption cycles. However, the regeneration of adsorbents saturated with organic compounds, particularly in aqueous solutions, has received relatively little attention.14 Most studies available in the literature have centered on the efficiency of the adsorbate extraction using organic solvents16 or supercritical CO2.17 In this context, the aim of this study was to investigate the monocomponent and multicomponent adsorption and desorption of BTX compounds under different operational conditions using thermally activated vegetal carbon (coconut shell). The Received: October 18, 2012 Revised: May 15, 2013 Accepted: May 24, 2013

A

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pH range of 2 ± 0.5 to 12 ± 0.5 and with different proportions of ethanol/water and methanol/water, according to studies by Yu et al.,18 Su et al.,19 Villacanãs et al.,20 and Garoma and Skidmore.21 All of the experiments were carried out at a temperature of 23 ± 1 °C and at 120 rpm, with 1.0 g of adsorbent, using glass Erlenmeyer flasks (250 mL) sealed with polytetrafluoroethylene lids. The equilibrium time was 15 h for each experiment. 2.2.1.3. Adsorption Kinetics in Fixed-Bed Column. The feed solutions of the monocomponent and multicomponent BTX compounds were prepared in 4 L glass flasks under similar shaking conditions for each batch. In order to maintain a homogeneous and soluble effluent, a magnetic stirrer was used to allow a reproducible concentration, which was normally maintained at within 2−3% of its average value during the adsorption experiments, measured at the point of entrance into the column, before the activated carbon bed. A Gilson peristaltic pump was employed to transfer the feed solution to the column. The glass column had 10 cm length, 1.2 cm internal diameter and three sampling points. Before the bed of activated carbon, a sampling point allowed liquid samples to be removed with the use of glass syringes in order to monitor the concentration of the contaminant at the entrance to the bed. A porous plate was placed at a point after the column input in order to suspend the activated carbon bed, as shown in Figure 1.

experimental monocomponent adsorption isotherms were obtained. They were then fitted to models found in the literature, and the parameters were determined; these were then used for the simulation of the monocomponent and multicomponent breakthrough curves for the fixed-bed column. The desorption of contaminants from the active site of the adsorbent was also investigated by applying various conditions such as different pH values and different proportions of solutions of methanol/water and ethanol/water. The finite volumes method was used in the discretization of the equations with the WUDS and CDS formulations, and the algorithm was implemented in the FORTRAN programming language. The results for the breakthrough curves obtained by the simulation presented good agreement with the experimental data.

2. MATERIALS AND METHODS 2.1. Materials. The adsorbent used was vegetal carbon produced from coconut shell and was activated thermally with vapor and carbon dioxide at temperatures of 800−1000 °C. The solvents used were distilled water to prepare the solutions of BTX compounds, benzene (Fluka) for high performance liquid chromatography (HPLC), toluene (VETEC) for UV/ HPLC spectroscopy, and 98% o-xylene (Sigma Aldrich) for ́ HPLC, and 95% ethanol P.A. (Lafan Quimica Fina). For use in the HPLC Milli-Q water and Gold series methanol (Carlo Erba) were used. HCl and 1 M NaOH were used to adjust the pH, and readings were taken with a Quimis pH meter (model Q-400M2). 2.2. Methods. 2.2.1. Experimental Procedure. Before the laboratory tests the samples passed through a pretreatment which consisted of adjusting the granulometry of the activated carbon (18/20 mesh)to approximately 0.85 mm, washing for a period of 10 days and drying at 110 °C for 3 h. In order to determine the concentration of BTX compounds a high performance liquid chromatography (HPLC) gas chromatograph connected to a UV/vis detector (model CG 437-B) and a Nucleosil C18 reverse-phase column of 250 mm, with an internal diameter of 4.6 mm, were used. The mobile phase employed in the HPLC, composed of methanol and Milli-Q water (80:20),was used at a flow rate of 0.8 mL/min. The BTX compounds were identified at a wavelength of 254 nm. All of the experiments were carried out in triplicate, adopting an average error of less than 5%. 2.2.1.1. Characterization of Adsorbent. The characterization of the adsorbent was based on the following parameters: particle size, hardness, moisture content, volatile matter, ash content, and fixed carbon. The BET (Brunauer, Emmett, and Teller) and BJH (Barrett, Joyner, and Halenda) tests were carried out in order to determine the surface area, pore volume, pore size and distribution, and particle irregularity of the material. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDAX) were carried out to obtain micrographs of the physical structure and determine some of the chemical elements contained in the sample. 2.2.1.2. Adsorption and Desorption Isotherms in Batch Reactor. A study on the thermodynamic equilibrium between the adsorbent and adsorbate was carried out with the aim of determining the maximum capacity of the adsorbent for the monocomponent adsorption of BTX compounds. The solutions were prepared in the following concentrations: 30, 50, 70, 90, 110, 130, and 150 mg of BTX/L and distilled water. The initial pH of the adsorption was approximately 6.4. For the desorption tests the influence of the pH was investigated in a

Figure 1. Schematic diagram of the configuration used to study the adsorption of BTX compounds in a fixed-bed column of activated carbon.

The activated carbon was packed into the column between the porous plate and the zone of glass beads which were used to support the activated carbon bed and vary the height studied. A sample point was placed in the middle of the column, at a height of 5 cm, in order to evaluate the variation in the concentration along the bed. Before beginning the adsorption experiments, a certain quantity of activated carbon was placed in distilled water in an Erlenmeyer flask under gentle stirring in a shaking bath, to remove the air from the pores of the adsorbent. The activated carbon was packed into the glass column together with some water in order to reduce the porosity of the bed. Distilled water was then pumped for around 10 min, and the volumetric flow was measured with the aid of a beaker and a chronometer. The flow of the solution during the experiments was from the base of the column upward, adjusting the feed solution to the desired flow rate. In order to minimize the effects of the B

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condition employed to describe the model for the solid phase imposes that, at ∀r and ∀z along the bed, at time zero, the solidphase concentration is equal to zero for the adsorption. In the case of desorption, an irreversible factor known as f rev = qorev/ qsat is considered to be responsible for the quantity of contaminant not desorbed from the adsorbent in each cycle carried out. The boundary conditions employed in the model are symmetry and equal flows. In the absence of axial dispersion of the solute in the bed, the mass balance in the fluid phase together with the initial and boundary conditions is expressed by eq 3, where eqs 3a and 3b are the initial and boundary conditions, respectively, for this equation:

axial dispersion, the relation between the bed length and the particle diameter (L/dp) was greater than 20 for all experiments and, in fact, in most cases it was above 50. The concentrations of the BTX compounds at the inlet, in the middle, and at the outlet of the column were monitored over time by collecting liquid samples which were analyzed immediately by HPLC. The experiments performed to determine the adsorption kinetics in the fixed bed were carried out in triplicate at 23 ± 1 °C based on an error of less than 5%. 2.2.2. Numerical Methodology. This methodology is based on the mathematical model described by Chatzopoulos and Varma,22 who carried out a process of toluene removal by adsorption in a fixed-bed column using activated carbon as the adsorbent. The mathematical model is a cluster model of pore diffusion which considers the internal and external resistances to mass transfer to the adsorbent particles. The mathematical model of this process involves the equations of conservation of chemical species for the liquid and solid phases, which describe the variation in the solute concentration in the column and inside the particle as a function of time and position, as well as the initial and boundary conditions. The diffusion coefficient for the particle surface increases exponentially with the coating of the surface according to the following expression: ⎡ ⎛ ⎤ q ⎞⎥ ⎟⎟ Ds(q) = D0 exp⎢k ⎜⎜ ⎢⎣ ⎝ qsat ⎠⎥⎦

v ∂C ∂C 3 (1 − εL) − k f (C − Cs) =− s ∂t εL ∂z R εL CI: t = 00 ≤ z ≤ L C i = 0; adsorption C i = C in ; desorption

(3a)

CC:t > 0, z = 0, C i = C in(t )

(3b)

where νs is the superficial velocity of the liquid in the bed, εL is the bed porosity, and R is the radius of the adsorbent particle. The time-variable boundary condition at the entrance of the bed in eq 3b was employed mainly to give more flexibility to the model, in order to deal with experiments under conditions of variable input concentration. The solute concentrations in the liquid and solid phases, at the solid−liquid interface, can be related through an equilibrium isotherm. The isotherm models used in this study are expressed in Table 1.

(1)

The variable D0 represents the diffusion on the surface at q = 0, k is a parameter of eq 1, q is the solute concentration in the solid phase, and qsat is the saturation concentration of solute on the surface. Equation 1 was incorporated into the adsorption model to take into account the variation in the diffusion coefficient at the surface, Ds, according to the experimental time and the position within the particle.22 In this case, the solute concentration in the liquid phase, C, varies with the axial position, z, and time, t, while the solid phase concentration, q, is a function of the radial position, r, within the particle. Assuming an isothermal process due to the high calorific capacity of water, spherical adsorbent particles and rapid adsorption kinetics, the mass balance of the solute in the solid phase is given by eq 2: ∂q ∂q ⎫ D ∂⎧ = 20 ⎨r 2 exp[k(q/qsat)] ⎬ ⎩ ∂t ∂r ⎭ r ∂r

(3)

Table 1. Textural Characteristics of the Adsorbent under Study textural characteristics surface area pore volume average pore diameter micropore volume micropore area pore distribution

(2)

724 m2/g 0.39 cm3/g 21.35 Ǻ 0.31 cm3/g 614 m2/g min. value: 18 Ǻ ; max. value: 400 Ǻ

with the following initial and boundary conditions: CI: t = 0, 0 ≤ r ≤ R , 0 ≤ z ≤ L

The finite volumes method23is used to discretize the conservation equations. This model was chosen since it ensures the conservation of the variables involved, at both the elemental and global levels. Many authors have used this method for the discretization of phenomenological equations.5,7,24,25In this study an explicit formulation and a one-dimensional structured mesh to store the discrete points are used. In the computational mesh the colocalized arrangement of variables will be used, where all of the variables are stored in the center of the control volumes. In order to determine the variables and their derivatives at the faces of the control volumes, the interpolation functions Weight Upstream Differencing Scheme (WUDS) along the column and the Central Differences Scheme (CDS) along the particles are used.

qi = 0; adsorption qi = qorev = frev qsat ; desorption CC1: t > 0, 0 ≤ z ≤ L ,

∂q ∂r

(2a)

=0 r=0

CC2: t > 0, 0 ≤ z ≤ L ⎡ ⎛ ⎤ q ⎞⎥ ∂q ⎟⎟ = k f (C − Cs) Doρs exp⎢k ⎜⎜ ⎢⎣ ⎝ qsat ⎠⎥⎦ ∂r r = R

(2b)

(2c)

where ρs is the apparent density of the solid, kf is the external mass transfer coefficient and Cs is the solute concentration in the liquid phase at the solid−liquid interface. The initial C

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Figure 2. Micrographs of the vegetal activated carbon obtained from coconut shell at magnifications of (a) 250×; and (b) 1000×; and (c) EDAX spectrum.

Table 2. Adsorption Isotherm Models for the BTX Compounds isotherm model monocomponent

qe =

qmax bLCe 1 + bLCe

(5a)

multicomponent Langmuir (Sulaymon and Ahmed29) qmax ib1Ce1 qei = n 1 + ∑i = 1 biCei

(5b)

26

Freundlich (Ruthven )

qe = kFCe1/ nF

(6a)

qe1 =

3. RESULTS AND DISCUSSION

a1Ce1b1 + b11 b11 Ce1 + a12Ce2b12

qe2 =

Ce2

a 2Ce2 b22

b2 + b22

+ a 21Ce1b21

(6b)

It can be observed in a and b of Figures 2 that there is a large number of pores, as shown in Table 1. The pore size distribution varies between 18 and 400 Ǻ , with a predominance of micropores and mesopores (average diameter of around 21 Ǻ ). According to Ruthven,26the adsorption occurs intensely in the micropores, but the mesopores and macropores are very important for the movement of the adsorbate to the inside of the adsorbent particle. The elemental analysis results (Figure 2c) verified that elemental carbon is present in the greatest percentage, the second element in terms of quantity being oxygen, with around 9% by mass. Small quantities of Mg, Al, Si, K, and Fe are also found. According to Grant and King,27 both the oxygenated functional groups and different metals (e.g., Mn, Fe, Zn) at the adsorbent surface may be responsible for the irreversible

3.1. Characterization of Activated Carbon. It was verified by way of the physical and chemical analysis that the activated carbon used in the adsorption of the BTX compounds had a low moisture content (0.03% dry basis) and ash content (1.4% dry basis) and a high quantity of fixed carbon (94.99% dry basis). The results for the textural characterization of the adsorbent, which include the determination of the surface area, microporosity and pore size distribution, are given in Table 1. Panels a and b of Figure 2 show the scanning electron microscopy (SEM) results for the activated carbon using magnifications of 250 and 1000 times, respectively. In Figure 2c the spectrum for the activated carbon samples obtained by energy dispersive X-ray spectroscopy (EDAX) can be observed. D

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Figure 3. Monocomponent adsorption isotherm for (a) benzene, (b) toluene, and (c) o-xylene adsorption onto activated carbon.

adsorption isotherm models for benzene, toluene, and o-xylene, respectively. The model parameters are expressed in Table 3.

adsorption promoting chemical reactions between the adsorbate and the surface. In addition, according to Grant and King,27 the presence of molecular oxygen dissolved in solution can also influence the irreversibility of the adsorption onto activated carbon through the participation of catalyzed oxidation reactions at the surface. 3.2. Equilibrium Study. 3.2.1. Adsorption Isotherms of BTX Compounds. The quantity of BTX adsorbed at equilibrium, qe(mg/g), for each test, was calculated through the following mass balance, considering that the contaminant which is not found in solution is adsorbed in the solid phase.

qe =

V (Co − Ce) M

Table 3. Equilibrium Parameters of Adsorption Isotherms for Monocomponent BTX Compounds benzene qmax(mg/g) bL (L/g) RL R2 nF kF R2

(4)

where V(L) is the initial solution volume, Co (g/L) is the initial solution concentration, Ce (g/L) is the solution concentration obtained at equilibrium, and M (g) is the adsorbent mass present in each experiment. All of the results obtained experimentally for the adsorption equilibrium of the BTX compounds were fitted using the leastsquares method with the software STATISTICA 7.0, applying the Langmuir (eq 5a) and Freundlich (eq 6a) adsorption isotherm models to the monocomponent compounds (Table 2). The confidence limit adopted to fit the experimental data to the models was 95%. The multicomponent isotherm models (eqs 5b and 6b) were used in the computational algorithm employing the monocomponent parameters for the simulation of the concentration profiles of the mixture. Parts a−c of Figure 3 show the results for the experimental adsorption isotherms, fitted using the two monocomponent

Langmuir 124.77 0.049 0.1198 0.9988 Freundlich 1.47 7.71 0.9887

toluene

o-xylene

150.42 0.0497 0.1182 0.9897

165.07 0.0405 0.1413 0.9971

1.49 9.62 0.9932

1.43 9.58 0.9954

In order to evaluate the essential characteristics of an isotherm and determine its form, the adimensional separation factor,RL, and Freundlich model parameter, nF, were calculated. The adimensional separation factor, commonly referred to as the Langmuir equilibrium parameter, RL, varied from 0.1198 to 0.1413. The nF parameter (Freundlich), had values of between 1 and 10. These results indicate favorable adsorption for all of the adsorption tests. This favorable behavior of the isotherms can also be observed in a−c of Figure 3. The parameters obtained for the adsorption of the BTX compounds shown in Table 3 verify that the greatest adsorption capacity was observed for o-xylene, which had a larger structure, greater molar mass and lower water solubility. E

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Figure 4. Effect of (a) pH, (b) different ethanol concentrations, and (c) different methanol concentrations on the desorption of BTX compounds from activated carbon.

in a fixed-bed column. The Langmuir model is characterized by homogeneous surfaces which contain a finite number of identical adsorption sites, with no interaction between the adsorbed molecules, and the adsorption maximum corresponds to a single monolayer saturated with adsorbate molecules on the adsorbent surface and the adsorption energy is constant. The Freundlich model is an empirical equation used to describe heterogeneous systems, where kF and nF are the empirical Freundlich parameters, which are dependent on several experimental factors and are related to the adsorption capacity of the adsorbent and to the adsorption intensity, respectively.26 Since no good fits for the experimental results were obtained for the multicomponent isotherm models,8 for the simulation of the breakthrough curves of the multicomponent experiments in a fixed-bed column the monocomponent equilibrium parameters were used, as also carried out by Sulaymon and Ahmed,29 Hu and Do,30 and Fritz et al.31 According to Fritz et al.,31 the fitting of multicomponent isotherms is complicated, mainly at high concentrations. 3.2.2. Desorption Isotherms for BTX Compounds. Parts a− c of Figure 4 show the influence of the pH and different proportions of water/ethanol and water/methanol on the desorption of BTX compounds from the adsorbent. It can be verified in Figure 4a that, within the wide range of values studied, the pH had no influence on the desorption of BTX compounds from the adsorbent surface, a high concentration (qmaxB= 122 mg/g; qmaxT = 149 mg/g; qmaxX = 164 mg/g) remaining on the surface after the desorption process. According to Villacañas et al.,20 most aromatic

In terms of maximum adsorption capacity this compound was followed by toluene and benzene. According toYu et al.,18 Su et al.,19 and Daifullah and Girgis,28 the adsorption of BTEX compounds is favored with a reduction in solubility (B, 790 mg/L > T, 530 mg/L > o-X, 175 mg/L) and an increase in the molar mass (B, 78 g < T, 92 g < o-X, 106 g). These authors also reported that an increase in the acidity of the activated carbon surface reduces the efficiency of the adsorption of BTEX compounds. In this case the adsorption is hindered by the hydration of the BTEX groups, since the water together with the BTEX compounds on the carbon surface blocks the pore entrance and thus the adsorbent loses part of its adsorption surface. The release of electrons from the carbon surface also occurs, reducing its adsorption capacity.28 The values obtained for R 2 indicate that the two monocomponent adsorption isotherm models showed good fits with the experimental data, and the best average R2 value for the compounds was obtained with the Langmuir isotherm. According to Ruthven,26 in 1945 Brunauer classified this type of isotherm as a type I - Langmuir, which is characterized by a monotonic approximation toward the limit of the adsorption capacity which corresponds to the formation of a complete layer. This type of isotherm has been observed for microporous adsorbents in which the capillaries have a width of only a few molecular diameters. Since the Langmuir model provided the best results for the fitting of the experimental data for the adsorbent−adsorbate set, this model was selected for the adsorption study carried out F

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contaminants are found in solution in the molecular state within a wide pH range. In this case, the dispersive interactions are predominant, mainly caused by the attraction between the π orbitals of basal carbon and the electronic density of the aromatic ring of the adsorbate π−π interactions.15,18 However, when the solution pH is very high or very low, ions may be present, and electrostatic interactions between the functional groups and the carbon surface may be significant, which was not the case in this study. Similar results have been reported by Wibowo et al.15 and Yu et al.18 It can be observed in Figure 4 b and c that the desorption rate increases with an increase in alcohol (ethanol or methanol) concentration, a better desorption rate being obtained with 100% ethanol (qmaxB = 4.0 mg/g; qmaxT = 5.75 mg/g; qmaxX = 10.57 mg/g) compared with 100% methanol (qmaxB = 49.11 mg/g; qmaxT = 58.90 mg/g; qmaxX = 56.15 mg/g). Garoma and Skidmore21 investigated the influence of ethanol on the capacity of adsorbents composed of the clays kaolin and bentonite in the adsorption and desorption of benzene and toluene (BT) in the aqueous phase. The results showed that the adsorption capacity of the soils decreased when the quantity of ethanol was increased from 0 to 50%. In the case of bentonite, the maximum adsorption capacity for benzene and toluene was reduced by 85 and 99.5%, respectively, while the maximum adsorption capacity of kaolin for these compounds was 86.5% and 98.2%, respectively. According to the abovementioned authors, the decrease in the adsorption capacity with the addition of ethanol may be explained by the cosolvent effect. In the presence of ethanol, there is a decrease in the polarity of the water. Hydrophobic compounds, such as benzene, toluene, and xylenes, are highly nonpolar, and a reduction in the polarity of water can considerably alter the stability of the molecules in solution. In the case of desorption, the rates for benzene and toluene for both adsorbents decreased by an order of magnitude with increases in ethanol from 0 to 25% and 0 to 50%, respectively. 3.3. Validation and Results. In order to validate the proposed mathematical model and the numerical methodology developed, the equations which describe the toluene adsorption process in a fixed-bed column were resolved. The results obtained from the numerical simulation were compared with three different situations studied experimentally by Chatzopoulos and Varma.22 The column used to obtain the experimental data had a length of 7.5 cm and an internal diameter of 2.54 cm, filled with activated carbon. A more detailed description of the experiment can be found in Chatzopoulos and Varma.22 The model input parameters used in the three cases under study to determine the toluene concentration profiles are given in Table 4. The numerical solution is obtained in this study using a mesh with 30 control volumes in the axial direction, z, and 25 control volumes in the radial position, r, since the solution obtained with this mesh is in agreement with that obtained with more refined meshes. Figure 5 shows the adimensional breakthrough curves for toluene (C/Cin), employing the mathematical model, using the parameters given in Table 1, where Cin is the initial mass concentration of toluene, as a function of time, for the three cases studied. On analyzing the results in Figure 5 it can be observed that the results obtained numerically show good agreement with the experimental results obtained by Chatzopoulos and Varma,22

Table 4. Parameters Used To Obtain the Breakthrough Curves for Toluene (Chatzopoulos and Varma22) parameters Cin εL k Ds Dm qsat ρs dp Dc kf Q L α1 α2 β1 β2

(mg/L) (adim.) (adim.) (cm2/s) (cm2/s) (mg/g) (g/L) (mm) (cm) (cm/s) (mL/min) (cm) (mg/g)(mg/L) (mg/L) −β2 (adim) (adim)

−β1

case 1

case 2

case 3

10.70 0.423 5.086 3.59 × 10−5 9.8 × 10−6 241.93 600 1.295 2.54 10.1 × 10−3 345 7.5 120.03 0.306 0.5675 0.5955

24.90 0.423 5.086 3.59 × 10−5 8.6 × 10−6 241.93 600 1.295 2.54 10.1 × 10−3 345 7.5 120.03 0.306 0.5675 0.5955

50.30 0.423 5.086 3.59 × 10−5 8.4 × 10−6 241.93 600 1.295 2.54 10.1 × 10−3 345 7.5 120.03 0.306 0.5675 0.5955

Figure 5. Experimental and simulated breakthrough curves for toluene (Chatzopoulos and Varma22) obtained with different initial concentrations.

verifying the mathematical model used and the numerical method employed and demonstrating that these represent the real adsorption process with good precision, allowing other situations to be simulated. The maximum error obtained numerically in relation to the experimental data was 11.52%. 3.3.1. Adsorption Kinetics of Fixed-Bed Column. On the basis of the computational code and the preliminary tests it was possible to determine the best dimensions for the fixed-bed column employed in the adsorption experiments, which consist of 10 cm of length and 1.2 cm of internal diameter, with three collection points equally spaced, providing a reasonable residence time for the contaminants in the bed and minimizing the axial dispersion and the experiment time. The adsorbent used was thermally activated carbon originating from coconut shell. The average diameter of the adsorbent was 0.85 mm with an average particle mass of 4.62 × 10−4 g. The apparent specific mass was 1.44 g/cm3 and the real specific mass of the bed was 0.49 g/cm3. The value obtained for the bed porosity was 0.41. Table 5 reports the conditions and the parameters required for the determination of the experimental and numerical breakthrough curves for the BTX compounds, using the equilibrium parameters determined experimentally. The isotherm used to describe the equilibrium data obtained experimentally was the Langmuir isotherm, which presented the best average for the correlation coefficients. G

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Parts a−c of Figure 6 show the experimental and numerical results for the breakthrough curves for the BTX compounds. The average mass of carbon used in the bed was approximately 5.28 g. It can be observed in parts a−c of Figure 6 that, under the same operational conditions for the BTX compounds, the adsorbent is saturated within ∼18 h for toluene, while the corresponding times for benzene and o-xylene were 38 and 23 h, respectively. The results for the breakthrough curves revealed a good agreement between the experimental and numerical data for the monocomponent adsorption of BTX compounds. In Figure 7 the experimental and numerical concentrations of BTX compounds in the fluid phase along the bed can be observed (Figure 7a,c,e) together with the concentration profiles for the BTX compounds (numerical) in the solid phase along the particle radius (Figure 7b,d,f), both for different adsorption times. The profiles were obtained at the column outlet for a feed concentration of Cin = 75 mg/L and flow rate of Q = 40 mL/min and the other parameters were as shown in Table 5 for each component. It can be observed in Figure 7b that there is a variation in the benzene concentration in the radial direction inside the particle. This occurs when the internal resistance to mass transfer is

Table 5. Conditions and Parameters Required for the Determination of the Breakthrough Curves and Concentration Profiles for the BTX Compounds parameters

benzene

toluene

o-xylene

Cin (mg/L) εL (adim.) Ds (cm2/s) Dm (cm2/s) ρs (g/L) dp (cm) Dc (cm) kf (cm/s) Q (mL/min) L (cm) b (L/g) qmax (mg/g)

75 0.41 8.12 × 10−9 9.8 × 10−6 1850 0.085 1.20 6.3107 × 10−3 40 10 0.0490 124.77

75 0.41 7.17 × 10−8 8.6 × 10−6 1850 0.085 1.20 6.3107 × 10−3 40 10 0.0497 150.42

75 0.41 2.4 × 10−8 8.4 × 10−6 1850 0.085 1.20 6.3107 × 10−3 40 10 0.0405 165.07

In Table 5, Dm is the molecular diffusivity of the BTX compounds,22 Ds is the effective diffusivity obtained from the fitting of the experimental breakthrough curves, and kf is the mass transfer coefficient in the liquid film obtained from the correlation of Wilson and Geankoplis.32

Figure 6. Monocomponent breakthrough curves for the BTX compounds, (a) benzene, (b) toluene, and (c) xylene, Cin = 75 mg/L, Q = 40 mL/min, and L = 10 cm. H

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Figure 7. Concentration profiles for monocomponent BTX compounds, experimental and simulated, in the liquid phase, along position z in the column for (a) benzene, (c) toluene, and (e) xylene, and simulated, in solid phase, along the particle radius for (b) benzene, (d) toluene, and (f) xylene.

high, which means that the concentration at the particle center differs from that at the surface. The variation in the toluene and o-xylene concentrations inside the particle is lower than that of benzene. It can also be observed that the longer the adsorption

time the greater the concentration of BTX compounds inside the particle. This means that the particle will saturate over time, and for an adsorption time of approximately 15 h, under these conditions, the particle was partially saturated with toluene and I

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Figure 8. Breakthrough curves for BTX compounds (a) benzene, (b) toluene, and (c) o-xylene, for different initial concentrations (Cin); Q = 30 mL/ min, and L = 7.0 cm.

benzene and o-xylene in 40 h the column was 95% and 98% saturated, respectively. This occurred due to the greater concentration of BTX compounds at the input in the feed stream, which occupied more rapidly the active sites available on the adsorbent compared with the situation when the feed concentration is lower. It can be verified in Figure 9 that the higher the feed flow rate of the BTX compounds the shorter the saturation time of the column. This is because the column receives a greater load with a higher flow rate, and thus the active sites are occupied in a shorter time. For a feed flow rate of Q = 40 mL/min, the saturation times on the breakthrough curves are 40 h for benzene, 19 h for toluene, and 25 h for o-xylene. In parts a−c of Figure 10 it can be observed that for a lower bed, for example, L = 5 cm, the saturation time of the adsorbent is shorter. This is due to the fact that with a lower bed height there are less adsorbent particles in the column and thus the column saturates earlier, compared with a higher bed, for example, L = 10 cm. Thus, the greater the bed height, the longer the breakthrough time will be. The bed height is an important parameter in the adsorption process since it is related to the quantity of active carbon in the adsorption column; therefore, with a greater height a higher quantity of solute is adsorbed. It can be observed in parts a and b of Figure 10 that the adimensional concentration surpassed the value of 1.0 for benzene and toluene. This is because the bed is very short (L = 5 cm) and the volumetric flow rate is high (40 mL/min) which

o-xylene which showed a higher intraparticle adsorption rate, and the mass transfer from the liquid to the solid phase ceases when the particle is saturated (this phenomenon can also be seen in the breakthrough curves in Figure 6). When the particle is saturated, the concentration of BTX compounds inside it, and at any point of the column in the liquid phase, is equal to the concentration of the compound at the column input, Cin. This verifies the saturation of the solid phase and, consequently, the saturation of the column. In order to determine the influence of the process variables on the adsorption capacity of the bed, some experiments were carried out with modifications of the operating conditions of the system. The breakthrough curves were constructed on the basis of the output composition versus sample time. Figures 8, 9, and 10 show the effect of the feed concentration, feed flow rate, and packed bed height on the adsorption process for the three contaminants studied. The feed concentration taken as a reference was 50 mg/L, that is, the concentration chosen for the multicomponent analysis, considering that the sum of the concentrations of the three contaminants cannot surpass the oxylene solubility limit of 175 mg/L. It can be observed in Figure 8 that the column saturation, for the highest feed concentration, in this case Cin = 70 mg/L, occurred within a shorter time, approximately 40 h for benzene, 17 h for toluene, and 24 h for o-xylene, when compared with the lowest concentration Cin = 30 mg/L. In the latter case, the column was saturated in 35 h in the case of toluene, while for J

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Figure 9. Breakthrough curves for the BTX compounds, (a) benzene, (b) toluene, and (c) o-xylene, for different feed flow rates (Q); Cin = 50 mg/L for each contaminant and L = 7 cm.

cm2/s, and 9.50 × 10−7 cm2/s for benzene, toluene, and oxylene, respectively. For the first desorption cycle, a rapid drop in the concentration occurred during the first hour, and after 11 h of the experiment the concentrations remaining in the fluid phase were 1.15 mg/L for benzene, 3.48 mg/L for toluene, and 1.82 mg/L for o-xylene. It can be observed that in the second adsorption/desorption cycle, although the adsorption of the BTX compounds did not begin at zero, the adsorbent is rapidly saturated at around 0.8 h for benzene, 1 h for toluene, and 2.5 h for o-xylene. The results for the desorption of the contaminants in the second cycle were similar to those reported above; that is, after 11 h of desorption the concentrations remaining were 0.28 mg/L for benzene, 2.13 mg/L for toluene, and 1.99 mg/L for o-xylene. In the third adsoption/desorption cycle rapid saturation was observed at around 0.7 h for benzene, 0.9 h for toluene, and 2.0 h for o-xylene. The desorption of contaminants in the third cycle also showed results similar to those observed previously, where after 11 h of desorption the concentrations remaining were 0.39 mg/L for benzene, 2.20 mg/L for toluene, and 1.94 mg/L for o-xylene. The fraction of reversible adsorption for BTX compounds on the adsorbent surface was determined from the desorption breakthrough curves. The fractions of reversibly adsorbed benzene, toluene, and o-xylene ( f rev = qorev/qsat) in the model are assumed to be 70, 25, and 25% from the first to the second

means that, after the bed saturation, the compounds are partially desorbed, resulting in a high concentration in the fluid phase. This behavior was not observed for o-xylene, which is the contaminant with the greatest affinity for the solid phase. 3.3.2. Regeneration of Adsorbent in the Fixed Bed. 3.3.2.1. Regeneration Using Water. In a−c of Figure 11 the experimental and simulated results can be observed for the three successive cycles of adsorption and desorption of the BTX compounds using a concentration of Cin = 50 mg/L of each contaminant in the tricomponent mixture for the adsorption, and the saturation concentration (qsat) of each contaminant for the desorption. The adsorption isotherm model employed was the multicomponent Langmuir model, using the parameters obtained from the fitting of the monocomponent isotherms. The solvent used to test the adsorbent efficiency over several adsorption/desorption cycles was distilled water at a temperature of T = 23 °C. Figure 11a shows the first cycle of the adsorption/desorption process for the BTX compounds using distilled water as the solvent. It can be observed that the adsorption process in the first cycle had the same behavior observed previously in which o-xylene is the contaminant with the highest degree of adsorption on the adsorbent surface. After 11 h of adsorption the column was saturated with o-xylene, while for benzene saturation occurred in 2.5 h, and for toluene, in 4 h. The effective diffusivity values were 9.30 × 10−11 cm2/s, 9.70 × 10−9 K

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Figure 10. Breakthrough curves for BTX compounds (a) benzene, (b) toluene, and (c) o-xylene, for different bed heights (L), Q = 30 mL/min, and Cin = 50 mg/L of each contaminant.

these chemical reactions at the surface, where part of the contaminant is retained at the adsorbent surface (irreversible adsorption), hindering the complete desorption of these contaminants. For the multicomponent breakthrough curves the numerical results showed greater deviation than the experimental data, mainly for the compounds which present lower affinity for the solid phase, that is, benzene and toluene (compared with oxylene). This deviation can also be explained by the short bed and high flow rate, which mean that the compounds adsorbed at the top of the bed are desorbed with greater facility. According to Sulaymon and Ahmed,29 a plausible explanation for the deviation in the adimensional concentration of the points on the breakthrough curve, mainly for compounds which are weakly adsorbed, is related to the Biot number (BiMi = kfLc/ Deff). The Biot number is an adimensional number, and it represents the relation between the resistance to internal mass transfer by diffusion and the resistance to external mass transfer by convection. In this study the following Biot numbers were found for the BTX compounds BiMB = 4.7499 × 108, BiMT = 4.5541 × 106 and BiMX = 4.6499 × 104. Also, according to Sulaymon and Ahmed,29 as the average Biot number increases for each solute, the competitive adsorption rate will decrease and the form of the breakthrough curves will be flatter and there will be a lower break point. This is due to the low intraparticle resistance and also the reduction in the contact time required to reach saturation. With an increase in the bed

cycle and 70, 25, and 15% from the second to the third cycle, respectively. The fraction of reversibly adsorbed toluene ( f rev = qorev/qsat), on activated carbon F-300 using distilled water as the desorbent solvent, determined previously by Chatzopoulos et al.22 at a temperature of T = 25 °C and with a flow rate of Q = 330 mL/min, was found to be 95% for 250 h of desorption. It is clear in Figure 11 that, in the case of desorption, the global desorption rate is determined by the internal resistance to mass transfer. These results are similar to those obtained by Chatzopoulos and Varma.22 Considering the time required for the saturation of the bed at the same flow rate (around 11 h, Figure 11a), the results in b and c of Figure 11 suggest that the volume of water required even for 90−95% of bed regeneration is 4 times greater than the volume of solution required for saturation. In a study carried out by Grant and King27 the adsorption of apolar organic compounds was observed to be totally reversible. For a particular adsorbate the irreversibility of the adsorption process can vary considerably for different adsorbents. Both the oxygenated functional groups and different metals (e.g., Mn, Fe, Zn) on the adsorbent surface can be responsible for the irreversible adsorption, promoting chemical reactions between the adsorbate and the surface.27The presence of molecular oxygen dissolved in solution can also influence the irreversibility of the adsorption onto activated carbon through the participation of catalyzed oxidation reactions at the surface.27 For the adsorbent under study, the elemental analysis revealed small quantities of Mg, Al, Si, K, and Fe, which may promote L

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Figure 11. Influence of three adsorption/desorption cycles in a tricomponent BTX mixture using distilled water as the desorbent solvent: (a) first cycle, (b) second cycle, and (c) third cycle (Q = 40 mL/min and L = 7.0 cm).

is the number of mass transfer units in the film (Nf = (3τkf(1 − εL))/(εLR)), according to Dı ́ez et al.34 The values for the number of intraparticle mass transfer units obtained for the BTX compounds in the multicomponent mixture were NDB = 2.5069 × 10−7, NDT = 2.5933 × 10−5 and NDX = 2.5556 × 10−3, and the number of mass transfer units in the film was Nf = 3.12. In this case, the value for Nf is much higher than the values obtained for NDi, verifying that the adsorption was controlled by the internal diffusion rather than mass transfer. In case of the desorption there was a good agreement between the numerical and experimental results. 3.3.2.2. Regeneration Using Ethanol. Parts a−c of Figure 12 show the experimental and simulated results obtained for the three successive adsorption cycles and experimental results for the three successive desorption cycles with ethanol for the

height the competitive adsorption rate will increase, and the shift of the weak components will be greater, leading to a breakthrough curve with a higher break point. A higher Biot number can be observed for benzene and toluene in the BTX mixture, these contaminants having a lower intraparticle diffusivity compared with that of o-xylene. According to Cooney et al.16 the external mass transfer is totally dominating at Bi < 0.5, while the adsorption process is limited by intraparticle diffusion for Bi > 30. Clearly, the relative part of intraparticle diffusion is dominant during the entire adsorption process; however, the role of external mass transfer cannot be totally neglected.33 In this study, the number of units of intraparticle mass transfer (NDi = τDeff/R2) was also evaluated, where τ (s) is defined as the spatial time in the columns (τ = LεL/vs), and Nf M

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Figure 12. Influence of several adsorption and desorption cycles for a tricomponent BTX mixture, using ethanol as the desorbent solvent: (a) first cycle, (b) second cycle, and (c) third cycle (Q = 40 mL/min and L = 7.0 cm).

BTX compounds using an initial concentration of Cin = 50 mg/ L of each contaminant in the tricomponent mixture for the adsorption and the saturation concentration (qsat) of each contaminant for the desorption. In Figure 12a (first adsorption/desorption cycle) it can be observed that the adsorption process showed the same behavior observed previously, in which o-xylene was the contaminant with the highest degree of adsorption at the adsorbent surface. After 11 h of adsorption the column was saturated with o-

xylene, whereas for benzene saturation occurred in 2.5 h, and for toluene, in 4 h. In the first desorption cycle, after 15 min of the experiment a maximum concentration of BTX compounds was verified in the fluid phase (CB = 332.98 mg/L; CT = 603.35 mg/L; CX = 647.29 mg/L) due to the higher affinity toward BTX of ethanol over water as a desorbent, the concentration gradually decreasing for up to 2 h of the experiment. The concentrations remaining after 2 h of desorption were CB = 6.39 mg/L, CT = 12.00 mg/L and CX = 13.01 mg/L. N

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monocomponent system, the model used to describe the equilibrium was the Langmuir model, and for the mixture the multicomponent Langmuir model was used, applying the parameters of the monocomponent equilibrium. The desorption isotherms for the contaminants at the adsorbent surface were investigated under different pH conditions and at various water/ethanol and water/methanol concentrations. The pH did not influence the desorption of the BTX compounds from the adsorbent surface. For different proportions of water/ethanol and water/methanol an increase in the desorption was observed with an increase in the alcohol concentration (ethanol and methanol). The best result for the desorption of the BTX compounds at the adsorbent surface was obtained with 100% ethanol, which provided very good averages for the regeneration cycles in the fixed-bed column (90% for benzene, 82% for toluene, and 78% for o-xylene), and 5 times less volume was required compared with using water as the solvent. The results for the breakthrough curves when compared with the experimental data allowed other situations to be simulated.

For multicomponent systems, at the beginning of adsorption, there is a large quantity of active sites available on the adsorbent and all of the compounds in the mixture are easily adsorbed. Over time the compounds which have a lower affinity for the solid phase are desorbed from the particle and replaced by compounds with a higher affinity (in this case benzene and toluene are desorbed, and o-xylene is adsorbed at these sites). The result of this is that the sum of the desorbed and input concentration for each contaminant (benzene and toluene) becomes an adimensional concentration (one). This has been observed in other studies on multicomponent adsorption reported in the literature.29 Another possible explanation, which also contributes to the high concentration of these contaminants in the fluid phase, is the use of a high flow rate and small bed height. This could also result in the contaminants adsorbed at the top of the column being desorbed by the effect of the high flow rate. The adsorption results for the second and third cycles were similar and can been seen in b and c of Figure 12. For the second desorption cycle the concentrations of BTX compounds in the fluid phase were CB = 372.78 mg/L, CT = 572.83 mg/L, and CX = 428.01 mg/L; the concentrations remaining were CB = 5.07 mg/L, CT = 13.00 mg/L, and CX = 6.01 mg/L. For the third cycle the desorption concentrations in the fluid phase were CB = 350.00 mg/L, CT = 539.82 mg/L, and CX = 416.00 mg/L, and the concentrations remaining were CB = 4.00 mg/L, CT = 4.13 mg/L, and CX =13.5 mg/L. The simulation results for each adsorption cycle were the same as the result used for the first adsorption cycle, representing also the different adsorption cycles when the column was regenerated with ethanol. After the column saturation, the deviation between the experimental result and that obtained with the adsorption model was high, mainly for the compounds which were weakly adsorbed. This deviation may have occurred due to the low bed and high flow rate applied. This could mean that a higher quantity of compounds, which are more weakly adsorbed, desorb more easily due to the effect of the flow rate, increasing even further the concentration in the fluid phase at the column outlet. This effect was also observed slightly in the monocomponent breakthrough curves with the effect of high feed flow rates and a high bed. The effective diffusivities remained at 9.30 × 10−11, 9.70 × 10−9, and 9.50 × 10−7 for benzene, toluene, and o-xylene, respectively. The volume of ethanol used in 2 h of regeneration of the column was 4.8 L, obtaining average percentages of 90% for benzene, 82% for toluene, and 78% for o-xylene in the regeneration cycles. This volume is less than 5 times the volume spent with water as the solvent, and in addition, the regeneration with water was not efficient for the second and third regeneration cycles, as can be seen in Figure 12. When the regeneration of the bed was carried out with ethanol, the BTX compounds were easily recovered with one or several unit operations. According to Wibowo et al.,15 these aromatic compounds, which are associated with high cost, are important consumables in industrial chemical processes, being commonly used as raw materials and often also as solvents in a wide variety of manufacturing processes.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: (+55) (48) 3721-9448. Fax: (+55) (48) 3721-9687. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS



REFERENCES

We thank ANP/MECPETRO for financial support and UFSC/ LABSIN-LABMASSA for the infrastructure provided for this study.

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P

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