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Breakthrough curves for oleic acid removal from ethanolic solutions using a strong anion exchange resin
Separation and Purification Technology 69 (2009) 1–6
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Review
Breakthrough curves for oleic acid removal from ethanolic solutions using a strong anion exchange resin Érika C. Cren a , L. Cardozo Filho b , Edson A. Silva c , Antonio J.A. Meirelles a,∗ a Laboratory EXTRAE, Department of Food Engineering, Faculty of Food Engineering, University of Campinas, UNICAMP, P.O. Box 6121, Zip Code 13083-970, Campinas, São Paulo, Brazil b Department of Chemical Engineering, State University of Maringá, UEM, Zip Code 87020-900, Maringá, Paraná, Brazil c School of Chemical Engineering, West Paraná State University, UNIOESTE, Zip Code 85903-000, Toledo, Paraná, Brazil
a r t i c l e
i n f o
Article history: Received 26 December 2008 Received in revised form 22 June 2009 Accepted 26 June 2009 Keywords: Breakthrough curves Fatty acids Ion exchange resin Oleic acid Adsorption
a b s t r a c t Breakthrough curves for the uptake of oleic acid from azeotropic ethanol solutions, using an anion exchange resin (Amberlyst 26A OH), were determined at (298.15 ± 0.10) K. The breakthrough data were obtained using an experimental factorial design (22 ), so that the observed behavior could be investigated as a function of operational conditions using surface response analysis. Two factors were investigated: flow rate (16.5–33 mL min−1 ) and oleic acid concentration in the ethanolic solutions (3.5–6.5 mass%). The breakthrough curves indicated that a favorable process of oleic acid removal from ethanolic solutions was possible using anion exchange resin. A model that describes the dynamics of oleic acid adsorption in the column was obtained from the mass balances in the fluid and resin phases. The model parameter, namely the mass transfer coefficient (Ks , min−1 ), was fitted to the experimental data. A good agreement between experimental and adjusted data was obtained. © 2009 Elsevier B.V. All rights reserved.
Contents 1. 2.
3.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Breakthrough experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Mathematical model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Breakthrough experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Mathematical model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction The deacidification step is the most important one in the refining process of crude vegetable oils. In fact, it defines the economic feasibility of the whole refining process, since it is usually in this step that large amounts of neutral oil are lost during the traditional refining methods. Solvent extraction of free fatty acids is suggested
∗ Corresponding author at: UNICAMP, Cidade Universitária Zeferino Vaz, Faculdade de Engenharia de Alimentos, Departamento de Engenharia de Alimentos, Laboratório EXTRAE, Rua Monteiro Lobato, 80, Caixa Postal 6121, CEP: 13083-862, Campinas, SP, Brazil. Tel.: +55 19 3788 4037; fax: +55 19 3788 4027. E-mail address: [email protected] (A.J.A. Meirelles). 1383-5866/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.seppur.2009.06.027
1 2 3 3 4 4 5 6 6
in the literature as an alternative deacidification method that uses mild operational conditions and can minimize the oil losses in the deacidification step, especially in case of crude oils with high acidity [1–6]. A drawback of the solvent extraction method is the requirement of recovering the solvent from the two outlet streams, raffinate and extract. Solvent recovery can be performed by processes such as distillation, stripping or evaporation, but especially for the extract stream the large amount of solvent to be evaporated also means a large requirement of energy. In this work an alternative approach for recovering the solvent from the extract stream was investigated. The extract stream is composed by solvent, free fatty acids and low amounts of neutral oil. The most appropriate solvent for the liquid–liquid extraction
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Nomenclature b C CF EXP Cout MOD Cout
Ks q qm Q mR t u X1 X¯ 1 X2 X¯ 2 z
Langmuir’s isotherm parameter (L g−1 ) concentration of oleic acid in the fluid phase (g L−1 ) feed concentration of oleic acid in the fluid phase (g L−1 ) experimental concentration of oleic acid in the effluent (g L−1 ) concentration of oleic acid in the effluent calculated by the model (g L−1 ) mass transfer coefficient (min−1 ) average concentration of oleic acid in the resin (g acid g resin−1 ) Langmuir’s isotherm parameter (g acid g resin−1 ) volumetric flow rate (L min−1 ) mass of dry resin (g) time (min) interstitial velocity of the fluid phase (cm min−1 ) volumetric flow rate in experimental design (mL min−1 ) coded variable for volumetric flow rate in experimental design oleic acid concentration in experimental design (mass%) coded variable for oleic acid concentration in experimental design bed height (cm)
Greek symbols ε column void fraction b bulk density of the bed (g L−1 )
method is ethanolic solutions containing 6–10 mass% of water. The addition of water increases the solvent selectivity and minimizes the loss of neutral oil, so that the oil concentration in the extract stream can be in fact very low. The fatty acid concentration of the extract stream depends on its initial content in the crude oil and on the proportion of solvent to oil used in the deacidification step. For crude oils with high acidity, such as rice bran, palm or corn oils, and for solvent to oil mass ratios close to 1.0, the fatty acid concentration in the extract stream will be not larger than 6.0–7.0 mass%. This kind of solution, composed mainly by free fatty acids dissolved in a polar environment, may allow the use of ion exchange resins for adsorbing the extracted free acidity and recovering the solvent, so that it can be used again in the deacidification step. The use of adsorbents and ion exchange resins for processing natural extracts and food solutions is steadily increasing [7–9]. Some prior works also report the use of adsorbents or ion exchange resins for processing fatty systems. For example, it can be mentioned the use of resins for separating unsaturated and saturated compounds, like methylic fatty esters [10], for recovering carotene from crude palm oil [11], for separating mixtures containing fatty acids, fatty esters, and triacylglyerols [12] and for purifying polyunsaturated fatty acids [13]. Ion exchange behavior in organic media is also nowadays a topic of intense investigation. The following research works can be mentioned: the determination of adsorption isotherms for oleic acid removal from ethanolic solutions [14], the removal of potassium from water–methanol–polyol mixtures using cationic resins [15,16], and the separation of alkylphenols from toluene solutions [17]. Organic media can influence ion exchange capacity and also the mass transfer efficiency, mainly because it affects resin swelling.
Resin swelling in aqueous media is mainly caused by the hydration tendency of the fixed ionic groups and the counter-ions. The swelling behavior in polar solvents is quite similar. In nonpolar media swelling could be impaired and it can occur only due to the possible affinity between resin matrix and the organic solvent molecule. In the present investigation the swelling effect is still favorable, since aqueous solutions of a polar component (ethanol) were used as solvent and in this media oleic acid, the substance to be adsorbed, is still well solubilized, avoiding any risk of liquid phase splitting. In fact, Helfferich [18] notes that ion exchange rates in organic media can be increased by the addition of water, since the presence of this substance guarantees ionic dissociation and, at least, a moderate swelling. The use of ion exchange for separating fatty acids from alcoholic solutions in a continuous way, a possible complement of the edible oil deacidification by solvent extraction, is a topic not yet investigated in the literature. In a prior work the ion exchange equilibrium of ethanolic solutions containing oleic acid and the anionic resin Amberlyst A26 OH was investigated [14]. A very favorable uptake of oleic acid was observed, but no influence of water content in the solutions (0–7 mass% of water) and of system temperature (298.15–313.15 K) was verified. In the present work this process is investigated by determining breakthrough curves in a fixed bed. In the fixed bed investigation an experimental design with response surface analysis was used in order to evaluate the influence of operational conditions, such as flow rate and solute concentration, on the column performance. Besides allowing a systematic and more appropriate variation of the experimental conditions, this statistical approach also makes possible the determination of optimal process conditions within the range of values investigated in the experimental work. On the other hand, mathematical modeling based on the equilibrium and mass transfer phenomena represents a more comprehensive approach that can be used for predicting the system behavior in a wide range of process conditions, even in conditions that extrapolate those tested in the experimental runs. For this reason, the experimental data for breakthrough curves were also modeled and the corresponding mass transfer coefficient (Ks , min−1 ) obtained. 2. Materials and methods The anionic resin Amberlyst A26 OH was kindly supplied by Rohm and Haas. According to the manufacturer it has the following characteristics: spherical beads with mean size in the range 0.56–0.7 mm, average pore diameter 290 Å, adsorption capacity ≥ 0.8 equiv. L−1 and bulk density 675 g L−1 . Commercial oleic acid was supplied by Merck and has an average molecular mass of 280.43 g mol−1 . Hydrated ethanol (7.06 ± 0.03) mass%, and sodium hydroxide, used as titration reagent, were also supplied by Merck. Amberlyst A26 OH was further characterized by measuring its capacity and original moisture. The capacity was measured according to the following procedure: resin active sites were saturated by contacting the solid phase with an excess of chloridric acid aqueous solution (0.1 equiv. L−1 ) and the residual acidity was determined by titration. The resin capacity was calculated by mass balance. Original moisture was determined by drying the sample in a convective oven under atmospheric pressure and 383.15 K until constant weight. The following results were obtained: resin capacity equal to (0.85 ± 0.01) equiv. L−1 and original moisture equal to (73.7 ± 0.1) mass%. The water content in aqueous ethanol was determined by Karl Fisher titration using a Methrom device (model 701 Kf Titrino and 703 Ti Stand). The commercial grade oleic acid was analyzed by gas chromatography according to the AOCS official method (1-62) [19]. Its composition was reported in our previous work [14].
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Table 1 Experimental design parameters. Parameters −1
Flow rate (mL min ) (X1 ) Oleic acid concentration (mass%) (X2 )
−˛ = 1,41
−1
0
+1
+˛ = 1,41
16.5 3.5
19 4
25 5
31 6
33 6.5
2.1. Breakthrough experiments Breakthrough curves were determined using a factorial design 22 for varying the feed flow rate (X1 , mL m−1 ) and the initial oleic acid concentration (X2 , mass%). Each factor was changed in 5 different levels according to the experimental design given in Table 1, resulting in a total of 11 experiments. These experiments were carried out in a glass column of 3 cm internal diameter and 66.5 cm length (ACE Glass Inc.) at (298.15 ± 0.10) K. The column was charged with a previously weighed amount of pre-conditioned resin, corresponding to a resin volume of 250 mL. The resin was pre-conditioned in hydrated ethanol for 30 min in order to remove the excess of moisture and to cause the swelling of the porous media. Oleic acid solution was then pumped through the resin bed at the selected flow rate. Samples of the effluent solution were periodically taken and analyzed for oleic acid content by titration (modified AOCS method Ca 5a-40) [19] with an automatic burette (Metrohm, model Dosimat 715). Analytical measurements were made at least in triplicate, with standard deviation less than 0.03 mass%. The experiments were conducted until resin saturation and this saturation was monitored by the measurement of the collected samples’ pH. A new batch of anionic resin was used in each experimental run, since the resin regeneration step was not an aim of the present investigation. Nevertheless, resin regeneration can be easily performed in the present case by contacting the saturated solid bed with an ethanolic solution of sodium hydroxide. Such a procedure was already tested in our prior work, performed for measuring adsorption isotherms in the same kind of physical–chemical system [14]. The change in solution concentration along the experiments, expressed as oleic acid dimensionless concentration, gives the breakthrough curve. The total amount of removed oleic acid per mass of dry resin up to the saturation can be calculated from each breakthrough curve using the following equation: q=
CF Q mR
tend
1−
0
Cout CF
dt
(1)
In order to evaluate the process efficiency the breakthrough curves were divided in different areas associated with the resin uptake capacity, as indicated in Fig. 1. A1 is associated with the resin capacity used before the breakthrough point, defined as the instant tbreak for which Cout /CF = 0.1, A2 is related to the solute amount that leaves the column before the breakthrough point, without being adsorbed, and A3 is related to the resin capacity not efficiently used, since this part of the adsorption process occurs after the breakthrough point but before tend , the first instant corresponding to Cout /CF ∼ = 1.0. On the basis of these areas two different efficiencies can be evaluated: εr is the efficiency of solute removal and εf is the efficiency of resin utilization, defined by Eqs. (2) and (3). Using the calculated efficiency values a statistical analysis of the results was developed, which allowed the evaluation of the process performance.
εr =
Q · CF · tbreak −
0
(Cout /CF )dt
Q · CF · tbreak
εf =
tbreak
Q · CF · tbreak −
Q · CF · tend −
=
tbreak (Cout /CF )dt = 0tend 0
(Cout /CF )dt
A1 A1 + A2
(2)
A1 A1 + A3
(3)
Fig. 1. Areas A1 , A2 and A3 along a breakthrough curve.
2.2. Mathematical model A phenomenological model was developed using the following assumptions: (i) the description of the adsorption process should take into account intraparticle mass transfer limitations; (ii) a linear driving force is used to describe the concentration profile inside the particle pores; (iii) process conditions are isothermal and isobaric; (iv) column void fraction is constant; (v) physical properties of resin and fluid phases are constant; (vi) axial and radial dispersions are negligible in the fixed bed column; (vii) the adsorption equilibrium is described with a Langmuir isotherm. The mathematical model was obtained by means of mass balance equations applied to an element of volume in the liquid and solid phases. The mass balance equation for the fluid phase is: ∂C 1 ∂q ∂C + b = −u ε ∂t ∂t ∂z
(4)
With the following initial and boundary conditions: C(0, z) = 0,
C(t, 0) =
0 CF
(5) t=0 t>0
in z = 0,
(6)
The mechanism for oleic acid removal in the column involves mass transfer of the solute within the liquid solution around the resin beads, diffusion inside the resin pores and the ion exchange reaction. The very favorable shape of the isotherm suggests a fast reaction. On the other hand, the mass transfer mechanism can be modeled combining a film coefficient and the intraparticle diffusivity. The ion exchange resin Amberlyst A 26OH is a rigid crosslinked polymeric structure with pores (macroreticular solid) sufficiently wide to permit diffusion, but mass transfer resistance inside the pores plays probably the dominant role because diffusivity-values in the resin phase are necessarily lower than the solute diffusivity in the liquid phase. In fact, solute diffusion inside the crosslinked structure of the resin matrix is more difficult, but the migration of the counter-ions is exactly oriented to find the active sites fixed in this resin internal structure [18]. Assuming that the resistance in the resin phase is the dominant one, the diffusion inside the pores described by Fick’s law was replaced by a simplified kinetic expression in order to make easier the resolution of the differential equation system [20,21]. This approach assumes that the mass transfer driving force is linear with
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the concentration for the solid phase, so that the adsorption rate can be represented by the following equation: ∂q = −KS (q − qeq ) ∂t
(7)
This approach, called LDF (linear driving force) model, has the following initial condition: q(z, 0) = 0
(8)
The equilibrium concentration of oleic acid in the resin phase was calculated by the Langmuir isotherm represented in Eq. (9): qeq =
qm bCeq 1 + bCeq
(9)
where qm and b are the Langmuir isotherm constants. The constant of equilibrium b is related to the free energy of adsorption that corresponds to the affinity between the surface of adsorbent and the adsorbate and qm is the constant that represents the maximum capacity of adsorption by mass of adsorbent. Such an approach based on the LDF approximation was already used by other authors for modeling adsorption in ion exchange resins and other adsorbents [21–23]. To solve the system of partial differential equations formed by Eqs. (4) and (7), together with the initial and boundary conditions given by Eqs. (5), (6) and (8) and the equilibrium relation, Eq. (9), the method of lines was used. Initially the domain of the problem was discretized in (ne) elements. This procedure transforms the problem of solving the system of partial differential equations into an ordinary differential equation system, which was solved using the subroutine DASSL developed by Petzold [24], coded in FORTRAN. This code solves systems of algebraic/differential equations and uses backward differentiation formulae to advance the solution from one time step to the next. By this procedure the mass transfer coefficient in the adsorbent (KS ) was estimated using the experimental data of the breakthrough curves and the following objective function was minimized: F=
np
EXP MOD (Cout − Cout )
2
(10)
i=1 EXP is the experimental concentration of oleic acid in the where Cout MOD is the corresponding concentration of oleic acid outlet stream; Cout calculated by the model; and np is the number of experimental data points.
3. Results and discussion 3.1. Breakthrough experiments Fig. 2 shows the experimental breakthrough curves. As expected the results indicated that for higher flow rates and higher solute concentrations in the feed stream the breakthrough time (tbreak ) and the saturation time (tend ) are achieved faster. The efficiencies calculated according to Eqs. (2) and (3) and the corresponding experimental conditions are given in Table 2. Note that Table 2 indicates the actual flow rates and concentrations used in the experimental runs. In comparison to the planned values given in Table 1, the actual values exhibit a relative difference not larger than 5.5%. A very high efficiency of solute removal was obtained for all experiments (approximately 98%), what confirms the resin’s capacity for removing oleic acid and indicates that the fatty acid has a good affinity for the resin active sites. The εr -values were almost constant for all experiments, indicating that both parameters flow rate and concentration of solute do not influence the efficiency of its removal, at least in the range of values investigated in the present work.
Fig. 2. The experimental breakthrough curves. (*) 3.5 mass% and 25 mL min−1 . () 5 mass% and 16.5 mL min−1 . (×) 6.5 mass% and 25 mL min−1 . () 5 mass% and 33 mL min−1 . (䊉) 4 mass% and 19 mL min−1 . () 5 mass% and 25 mL min−1 . () 5 mass% and 25 mL min−1 . (♦) 5 mass% and 25 mL min−1 . () 6 mass% and 31 mL min−1 . () 6 mass% and 19 mL min−1 . (+) 4 mass% and 31 mL min−1 .
The efficiency of resin utilization (εf ) varied within the range 48–69%. This shows that the resin bed had at least half of its potential capacity used in an efficient way. These results also show that a decrease of the solution flow rate increases the efficiency of resin utilization. On the other hand, the influence of the initial solution concentration is not so clear. The experiment with best performance (εf = 0.687) is the one conducted at 5 mass% of oleic acid concentration and 16.5 mL min−1 , values that correspond to the central point concentration and to the lowest flow rate, respectively. In order to use the experimental breakthrough curves for process optimization the following response function is suggested: Response function =
εr · εf tbreak
(11)
Note that this response function takes into account both efficiencies, since it is important to maximize the solute removal as well as the efficient use of the resin capacity. Although in the present investigation the efficiency of solute removal εr has almost not varied, it should be considered that, in case a wider range of operational conditions would be used, the εr -values will probably change, so that a generic formulation for the response function including this variable is more appropriate. This formulation also considers the breakthrough time because it is important for the process productivity to reduce to a minimum the time period of maximum solute removal, since a new cycle of resin regeneration and adsorption can be initiated earlier and larger amounts of solution will be processed. In fact, this response function seems to be the best form for representing the process performance because it combines both efficiencies and the required time interval in terms of oleic acid removal (i.e., the period before breakthrough time). The statistical analysis generates the coded model presented in Eq. (12), which describes the response function in terms of the two investigated parameters, with determination coefficient of 97% and an average error of 10% (significance level of 95%). It should be noted that this statistical analysis was developed on the basis of the actual flow rates and concentrations given in Table 2. This means that the oscillations of the actual factors around the intended ones (Table 1) were incorporated in the results of the statistical analysis. εr .εf tbreak
= 0.0159 + 0.0039(X¯ 1 ) + 0.0035(X¯ 2 )
(12)
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Table 2 Efficiencies for the experimental breakthrough curves. Experimental run
X2 (mass%)
X1 (mL min−1 )
tbreak (min)
1 2 3 4 5 6 7 8 9 10 11
4.12 6.13 4.22 6.34 4.90 4.90 3.59 6.50 5.19 5.26 5.18
19.4 19.5 30.0 30.0 16.7 33.2 26.3 24.5 24.9 24.0 24.3
55 38 31 22 63 22 55 26 36 32 33
Both coded operational parameters, flow rate (X¯ 1 ) and oleic acid concentration (X¯ 2 ), have a positive influence upon the response function. This means that, in terms of the chosen response function, a lower efficiency of resin utilization (εf ) can be more than compensated by a reduction in the breakthrough time (tbreak ). In fact, the efficiency of resin utilization decreases as the flow rate increases because the residence time of the solution in the resin bed and, consequently, the time for mass transfer, becomes lower in this case. On the other hand, the throughput is larger and the resin bed is used for processing larger amounts of solution, an effect that has predominated in the present experimental results. For instance, if one compares the results for the first and third experiments given in Table 2, it can be seen that the efficiency of resin utilization decreases less than 10%, but the breakthrough time diminishes more than 30%. For this reason the net effect is the increase of the response function. Naturally such a result is valid only within the range of values investigated in the present work, since at very high flow rates the decrease in the efficiency of resin utilization will probably be more significant. Fig. 3 presents the response surface obtained for Eq. (12) and illustrates the behavior discussed above. 3.2. Mathematical model The breakthrough curves were also correlated using the mathematical model already described and the experimental conditions given in Table 2. The mass transfer coefficient Ks was used as the fit-
± ± ± ± ± ± ± ± ± ± ±
1 1 1 1 1 1 1 1 1 1 1
tend (min) 198 155 136 95 180 120 176 124 135 133 132
± ± ± ± ± ± ± ± ± ± ±
2 2 2 2 2 2 2 2 2 2 2
εr
εf
εr ·εf /tbreak
0.977 0.983 0.978 0.982 0.981 0.979 0.977 0.982 0.985 0.978 0.979
0.581 0.579 0.525 0.525 0.687 0.482 0.642 0.548 0.606 0.520 0.553
0.010 0.015 0.017 0.024 0.011 0.021 0.011 0.021 0.016 0.016 0.016
Fig. 4. () Experimental curve for experiment 10 in Table 2, (–) adjusted curve (qm = 1.329 g acid g dry resin−1 , b = 492.5 L g acid−1 and Ks = 2.54 × 10−2 min−1 ); (- - -) simulated curve (qm = 1.292 g acid g dry resin−1 , b = 460.0 L g acid−1 and Ks = 2.41 × 10−2 min−1 ).
ting parameter. The Langmuir isotherm obtained from equilibrium data measured in batch experiments by Cren and Meirelles [14] was incorporated into the mathematical modeling. The following Langmuir parameters were used: qm = (1.329 ± 0.037) g acid g dry resin−1 and b = (492.5 ± 32.5) L g acid−1 . Fig. 4 compares an experimental breakthrough curve and the corresponding calculated one. As can be seen the model described the dynamics of oleic acid removal in a very satisfactory way. A unique mass transfer coefficient Ks = 2.54 × 10−2 min−1 was adjusted for all 11 experiments. This parameter was estimated by minimization of the objective function given by Eq. (10). The experimental values for the resin capacity, as well as the corresponding values obtained according to the modeled breakthrough curves, were calculated by Eq. (1). As can be seen in Table 3 Table 3 Capacities calculated for the experimental and fitted breakthrough curves.
Fig. 3. Response surface for the model obtained according to the experimental design (Eq. (11)).
X2 (mass%)
X1 (mL min−1 )
qexp (g acid g dry resin−1 )
qmod (g acid g dry resin−1 )
4.12 6.13 4.22 6.34 4.90 4.90 3.59 6.50 5.19 5.26 5.18
19.4 19.5 30.0 30.0 16.7 33.2 26.3 24.5 24.9 24.0 24.3
1.23 1.29 1.17 1.22 1.18 1.13 1.13 1.22 1.23 1.24 1.18
1.29 1.32 1.22 1.31 1.25 1.27 1.17 1.30 1.30 1.27 1.24
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both values of resin capacity are close to each other. In fact, the deviations between the capacity values calculated according to the experimental curves and the corresponding ones calculated using the fitted curves varied within the range 2.3 and 12.4%. Comparing the experimental values given in Table 3 and the maximal capacity of oleic acid removal according to the batch equilibrium experiments (qm = 1.329 g oleic acid g dry resin−1 ), one can conclude that more than 85% of the resin capacity was used in the breakthrough runs. The resin capacity in equiv. L−1 (0.85) can be converted in g oleic acid g dry resin−1 by using the fatty acid molar mass (280.43 g mol−1 ), the resin bulk density (675 g L−1 ) and moisture (73.7 mass%). The obtained value is 1.343 g oleic acid g dry resin−1 , a result very close to the qm -value and to the capacities reported in Table 3. As indicated in a prior work [14], these capacity values correspond mainly to an adsorption mechanism by ion exchange. By washing several times the saturated solid phase with acid-free ethanolic solutions and afterwards regenerating it with an excess of sodium hydroxide alcoholic solution, Cren and Meirelles [14] concluded that more than 98.4% of the reported capacity value is due to the ion exchange mechanism. In order to evaluate the model sensitivity to the equilibrium parameters and mass transfer coefficient, breakthrough curves for the experimental run 10 were also calculated taking into account the uncertainties of the Langmuir parameters given above and a variation of ±5% in the adjusted Ks -value. Fig. 4 shows one of those calculated curves together with the adjusted one. As can be seen, variations in the values of the equilibrium and mass transfer parameters do not influence significantly the calculated breakthrough curves. In fact, the change in the calculated capacity values with the modified parameters, considering all the possible combinations of those parameters, was always less than 1.3%. The largest deviation was obtained for the lower limits of the parameter values. The low sensitivity of the model is a consequence of the almost rectangular isotherm that characterizes the present system and which causes a very favorable uptake of oleic acid from the alcoholic solutions. According to Table 3, the experimental capacity values increase to some extent as a consequence of increasing oleic acid concentration and decreasing flow rate, so that in the case of the second experiment 97% of the total resin capacity is used. The present work indicates the feasibility of recovering fatty acids from ethanolic solutions by means of ion exchange in a fixed resin bed. This kind of process can be used as a complement of edible oil deacidification by solvent extraction, since it makes possible the recovering of the solvent present in the extract stream for a new deacidification step by liquid–liquid extraction. The efficiency of solute removal was always close to 98% and the values obtained for the efficiency of resin utilization were, in most cases, larger than 52%. The experimental approach based on factorial design allowed the evaluation of the process performance and can contribute to its optimization. The mathematical model developed on the basis of the linear driving force approximation was able to represent correctly the experimental breakthrough curves. The experimental results, the investigation of the operational conditions’ effects by the surface response methodology and the successful modeling of the breakthrough curves can surely guarantee an appropriate design of this complementary process. Nevertheless, further investigations, mainly on the resin regeneration step, are necessary in order to check the viability of this process in an industrial scale.
Acknowledgments E.C. Cren thanks CNPq (140487/2005) for the PhD scholarship and FAPESP (02/11794-3) for the MS scholarship. The authors are grateful to FAPESP (05/53095-2 + 08/56258-8) and CNPq (306250/2007-1) for the financial support. References [1] C.B. Gonc¸alves, A.J.A. Meirelles, Liquid–liquid equilibrium data for the system palm oil + fatty acids + ethanol + water at 318.2 K, Fluid Phase Equilibr. 221 (2004) 139–150. [2] C.E.C. Rodrigues, R. Antoniassi, A.J.A. Meirelles, Equilibrium data for the system rice bran oil + fatty acids + ethanol + water at 298.2 K, J. Chem. Eng. Data 48 (2003) 367–373. [3] C.B. Gonc¸alves, E. Batista, A.J.A. Meirelles, Liquid–liquid equilibrium data for the system corn oil + oleic acid + ethanol + water at 298.15 K, J. Chem. Eng. Data 47 (2002) 416–420. [4] C.G. Pina, A.J.A. Meirelles, Deacidification of corn oil by solvent extraction in a perforated rotating disc column, J. Am. Oil Chem. Soc. 77 (2000) 553–559. [5] C.E.C. Rodrigues, A. Filipini, A.J.A. Meirelles, Phase equilibrium for systems composed by high unsaturated vegetable oils + linoleic acid + ethanol + water at 298.2 K, J. Chem. Eng. Data 51 (2006) 15–21. [6] C.E.C. Rodrigues, E.C.D. Peixoto, A.J.A. Meirelles, Phase equilibrium for systems composed by refined soybean oil + commercial acid + ethanol + water, at 323.2 K, Fluid Phase Equilibr. 261 (2007) 122–128. [7] E.M. Silva, D.R. Pompeu, Y. Larondelle, H. Rogez, Optimisation of the adsorption of polyphenols from Inga edulis leaves on macroporous resins using an experimental design methodology, Sep. Purif. Technol. 53 (2007) 274–280. [8] J.A.G. Agudo, M.T.G. Cubero, G.G. Benito, M.P. Miranda, Removal of coloured compounds from sugar solutions by adsorption onto anionic resins: equilibrium and kinetic study, Sep. Purif. Technol. 29 (2002) 199–205. [9] R.L. Johnson, B.V. Chandler, Ion exchange and adsorbent resins for removal of acids and bitter principles from citrus juices, J. Sci. Food Agric. 36 (2006) 480–484. [10] W.J. DeJarlais, R.O. Adlof, E.A. Emken, Acetonitrile as eluent in silver resin column chromatography, J. Am. Oil Chem. Soc. 60 (1983) 83–85. [11] R.A. Latip, B.S. Baharin, Y.B. Che Man, R.A. Rahman, Effect of adsorption and solvent extraction process on the percentage of carotene extracted from crude palm oil, J. Am. Oil Chem. Soc. 78 (2001) 83–85. [12] R.O. Adlof, E.A. Emken, Partial argentation resin chromatography (PARC). III. The effect of sodium ion incorporation and solvent on the separation of mixture of fatty acids, of fatty esters, and of triglycerides, J. Am. Oil Chem. Soc. 2 (1981) 99–101. ˜ [13] M.J. Ibánez González, A. Robles Medina, L. Esteban Cerdán, B. Camacho Páez, A. Gimenez Gimenez, E. Molina Grima, Adsorption equilibria of fatty acids between methanol/water and reversed phase chromatographic adsorbents, J. Am. Oil Chem. Soc. 78 (2001) 277–283. [14] E.C. Cren, A.J.A. Meirelles, Adsorption isotherms for oleic acid removal from ethanol + water solutions using the strong anion-exchange resin Amberlyst A26 OH, J. Chem. Eng. Data 50 (2005) 1529–1534. ˜ [15] J.L. Antonio de Lucas, P. Canizares, J.F. Rodriguez, I. Garcia, Potassium removal from water–polyol mixtures by ion exchange on Amberlite 252, Chem. Eng. J. 66 (1997) 137–147. ˜ [16] J.L. Antonio de Lucas, P. Canizares, J.F. Rodriguez, Ion-exchange kinetics for the removal of potassium from crude polyols on strong acid resins, Sep. Sci. Technol. 32 (1997) 1805–1820. [17] H.M. Anasthas, V.G. Gaikar, Adsorptive separation of alkylphenols using ion exchange resins, React. Funct. Polym. 39 (1999) 227–237. [18] F. Helfferich, Ion Exchange, McGraw-Hill Book Company Inc., New York, 1962. [19] Official and Tentative Methods of the American Oil Chemists Society, 3rd ed., AOCS Press, Champaign, IL, 1988. [20] E. Glueckauf, Theory of chromatography, Trans. Faraday Soc. 51 (1955) 1235–1241. [21] M.A.S.D. Barros, E.A. Silva, P.A. Arroyo, C.R.G. Taveres, R.M. Schneider, M. Suszek, E.F. Sousa-Aguiar, Removal of Cr(III) in the fixed bed column and batch reactors using as adsorbent zeolite NaX, Chem. Eng. Sci. 59 (2004) 5959–5966. [22] I. Pedruzzi, E.A. Borges da Silva, A.E. Rodrigues, Selection of resins, equilibrium and sorption kinetics of lactobionic acid, fructose, lactose and sorbitol, Sep. Purif. Technol. 63 (2008) 600–611. [23] I.C. Ostroski, M.A.S.D. Barros, E.A. Silva, J.H. Dantas, P.A. Arroyo, O.C.M. Lima, A comparative study for the ion exchange of Fe(III) and Zn(II) on zeolite NaY, J. Hazard. Mater. 161 (2009) 1404–1412. [24] L.R. Petzold, A Description of DASSL: A Differential/algebric Equation System Solver, STR, SAND 82-8637, Livermore, 1982.
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Separation and Purification Technology journal homepage: www.elsevier.com/locate/seppur
Review
Breakthrough curves for oleic acid removal from ethanolic solutions using a strong anion exchange resin Érika C. Cren a , L. Cardozo Filho b , Edson A. Silva c , Antonio J.A. Meirelles a,∗ a Laboratory EXTRAE, Department of Food Engineering, Faculty of Food Engineering, University of Campinas, UNICAMP, P.O. Box 6121, Zip Code 13083-970, Campinas, São Paulo, Brazil b Department of Chemical Engineering, State University of Maringá, UEM, Zip Code 87020-900, Maringá, Paraná, Brazil c School of Chemical Engineering, West Paraná State University, UNIOESTE, Zip Code 85903-000, Toledo, Paraná, Brazil
a r t i c l e
i n f o
Article history: Received 26 December 2008 Received in revised form 22 June 2009 Accepted 26 June 2009 Keywords: Breakthrough curves Fatty acids Ion exchange resin Oleic acid Adsorption
a b s t r a c t Breakthrough curves for the uptake of oleic acid from azeotropic ethanol solutions, using an anion exchange resin (Amberlyst 26A OH), were determined at (298.15 ± 0.10) K. The breakthrough data were obtained using an experimental factorial design (22 ), so that the observed behavior could be investigated as a function of operational conditions using surface response analysis. Two factors were investigated: flow rate (16.5–33 mL min−1 ) and oleic acid concentration in the ethanolic solutions (3.5–6.5 mass%). The breakthrough curves indicated that a favorable process of oleic acid removal from ethanolic solutions was possible using anion exchange resin. A model that describes the dynamics of oleic acid adsorption in the column was obtained from the mass balances in the fluid and resin phases. The model parameter, namely the mass transfer coefficient (Ks , min−1 ), was fitted to the experimental data. A good agreement between experimental and adjusted data was obtained. © 2009 Elsevier B.V. All rights reserved.
Contents 1. 2.
3.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Breakthrough experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Mathematical model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Breakthrough experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Mathematical model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction The deacidification step is the most important one in the refining process of crude vegetable oils. In fact, it defines the economic feasibility of the whole refining process, since it is usually in this step that large amounts of neutral oil are lost during the traditional refining methods. Solvent extraction of free fatty acids is suggested
∗ Corresponding author at: UNICAMP, Cidade Universitária Zeferino Vaz, Faculdade de Engenharia de Alimentos, Departamento de Engenharia de Alimentos, Laboratório EXTRAE, Rua Monteiro Lobato, 80, Caixa Postal 6121, CEP: 13083-862, Campinas, SP, Brazil. Tel.: +55 19 3788 4037; fax: +55 19 3788 4027. E-mail address: [email protected] (A.J.A. Meirelles). 1383-5866/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.seppur.2009.06.027
1 2 3 3 4 4 5 6 6
in the literature as an alternative deacidification method that uses mild operational conditions and can minimize the oil losses in the deacidification step, especially in case of crude oils with high acidity [1–6]. A drawback of the solvent extraction method is the requirement of recovering the solvent from the two outlet streams, raffinate and extract. Solvent recovery can be performed by processes such as distillation, stripping or evaporation, but especially for the extract stream the large amount of solvent to be evaporated also means a large requirement of energy. In this work an alternative approach for recovering the solvent from the extract stream was investigated. The extract stream is composed by solvent, free fatty acids and low amounts of neutral oil. The most appropriate solvent for the liquid–liquid extraction
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Nomenclature b C CF EXP Cout MOD Cout
Ks q qm Q mR t u X1 X¯ 1 X2 X¯ 2 z
Langmuir’s isotherm parameter (L g−1 ) concentration of oleic acid in the fluid phase (g L−1 ) feed concentration of oleic acid in the fluid phase (g L−1 ) experimental concentration of oleic acid in the effluent (g L−1 ) concentration of oleic acid in the effluent calculated by the model (g L−1 ) mass transfer coefficient (min−1 ) average concentration of oleic acid in the resin (g acid g resin−1 ) Langmuir’s isotherm parameter (g acid g resin−1 ) volumetric flow rate (L min−1 ) mass of dry resin (g) time (min) interstitial velocity of the fluid phase (cm min−1 ) volumetric flow rate in experimental design (mL min−1 ) coded variable for volumetric flow rate in experimental design oleic acid concentration in experimental design (mass%) coded variable for oleic acid concentration in experimental design bed height (cm)
Greek symbols ε column void fraction b bulk density of the bed (g L−1 )
method is ethanolic solutions containing 6–10 mass% of water. The addition of water increases the solvent selectivity and minimizes the loss of neutral oil, so that the oil concentration in the extract stream can be in fact very low. The fatty acid concentration of the extract stream depends on its initial content in the crude oil and on the proportion of solvent to oil used in the deacidification step. For crude oils with high acidity, such as rice bran, palm or corn oils, and for solvent to oil mass ratios close to 1.0, the fatty acid concentration in the extract stream will be not larger than 6.0–7.0 mass%. This kind of solution, composed mainly by free fatty acids dissolved in a polar environment, may allow the use of ion exchange resins for adsorbing the extracted free acidity and recovering the solvent, so that it can be used again in the deacidification step. The use of adsorbents and ion exchange resins for processing natural extracts and food solutions is steadily increasing [7–9]. Some prior works also report the use of adsorbents or ion exchange resins for processing fatty systems. For example, it can be mentioned the use of resins for separating unsaturated and saturated compounds, like methylic fatty esters [10], for recovering carotene from crude palm oil [11], for separating mixtures containing fatty acids, fatty esters, and triacylglyerols [12] and for purifying polyunsaturated fatty acids [13]. Ion exchange behavior in organic media is also nowadays a topic of intense investigation. The following research works can be mentioned: the determination of adsorption isotherms for oleic acid removal from ethanolic solutions [14], the removal of potassium from water–methanol–polyol mixtures using cationic resins [15,16], and the separation of alkylphenols from toluene solutions [17]. Organic media can influence ion exchange capacity and also the mass transfer efficiency, mainly because it affects resin swelling.
Resin swelling in aqueous media is mainly caused by the hydration tendency of the fixed ionic groups and the counter-ions. The swelling behavior in polar solvents is quite similar. In nonpolar media swelling could be impaired and it can occur only due to the possible affinity between resin matrix and the organic solvent molecule. In the present investigation the swelling effect is still favorable, since aqueous solutions of a polar component (ethanol) were used as solvent and in this media oleic acid, the substance to be adsorbed, is still well solubilized, avoiding any risk of liquid phase splitting. In fact, Helfferich [18] notes that ion exchange rates in organic media can be increased by the addition of water, since the presence of this substance guarantees ionic dissociation and, at least, a moderate swelling. The use of ion exchange for separating fatty acids from alcoholic solutions in a continuous way, a possible complement of the edible oil deacidification by solvent extraction, is a topic not yet investigated in the literature. In a prior work the ion exchange equilibrium of ethanolic solutions containing oleic acid and the anionic resin Amberlyst A26 OH was investigated [14]. A very favorable uptake of oleic acid was observed, but no influence of water content in the solutions (0–7 mass% of water) and of system temperature (298.15–313.15 K) was verified. In the present work this process is investigated by determining breakthrough curves in a fixed bed. In the fixed bed investigation an experimental design with response surface analysis was used in order to evaluate the influence of operational conditions, such as flow rate and solute concentration, on the column performance. Besides allowing a systematic and more appropriate variation of the experimental conditions, this statistical approach also makes possible the determination of optimal process conditions within the range of values investigated in the experimental work. On the other hand, mathematical modeling based on the equilibrium and mass transfer phenomena represents a more comprehensive approach that can be used for predicting the system behavior in a wide range of process conditions, even in conditions that extrapolate those tested in the experimental runs. For this reason, the experimental data for breakthrough curves were also modeled and the corresponding mass transfer coefficient (Ks , min−1 ) obtained. 2. Materials and methods The anionic resin Amberlyst A26 OH was kindly supplied by Rohm and Haas. According to the manufacturer it has the following characteristics: spherical beads with mean size in the range 0.56–0.7 mm, average pore diameter 290 Å, adsorption capacity ≥ 0.8 equiv. L−1 and bulk density 675 g L−1 . Commercial oleic acid was supplied by Merck and has an average molecular mass of 280.43 g mol−1 . Hydrated ethanol (7.06 ± 0.03) mass%, and sodium hydroxide, used as titration reagent, were also supplied by Merck. Amberlyst A26 OH was further characterized by measuring its capacity and original moisture. The capacity was measured according to the following procedure: resin active sites were saturated by contacting the solid phase with an excess of chloridric acid aqueous solution (0.1 equiv. L−1 ) and the residual acidity was determined by titration. The resin capacity was calculated by mass balance. Original moisture was determined by drying the sample in a convective oven under atmospheric pressure and 383.15 K until constant weight. The following results were obtained: resin capacity equal to (0.85 ± 0.01) equiv. L−1 and original moisture equal to (73.7 ± 0.1) mass%. The water content in aqueous ethanol was determined by Karl Fisher titration using a Methrom device (model 701 Kf Titrino and 703 Ti Stand). The commercial grade oleic acid was analyzed by gas chromatography according to the AOCS official method (1-62) [19]. Its composition was reported in our previous work [14].
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3
Table 1 Experimental design parameters. Parameters −1
Flow rate (mL min ) (X1 ) Oleic acid concentration (mass%) (X2 )
−˛ = 1,41
−1
0
+1
+˛ = 1,41
16.5 3.5
19 4
25 5
31 6
33 6.5
2.1. Breakthrough experiments Breakthrough curves were determined using a factorial design 22 for varying the feed flow rate (X1 , mL m−1 ) and the initial oleic acid concentration (X2 , mass%). Each factor was changed in 5 different levels according to the experimental design given in Table 1, resulting in a total of 11 experiments. These experiments were carried out in a glass column of 3 cm internal diameter and 66.5 cm length (ACE Glass Inc.) at (298.15 ± 0.10) K. The column was charged with a previously weighed amount of pre-conditioned resin, corresponding to a resin volume of 250 mL. The resin was pre-conditioned in hydrated ethanol for 30 min in order to remove the excess of moisture and to cause the swelling of the porous media. Oleic acid solution was then pumped through the resin bed at the selected flow rate. Samples of the effluent solution were periodically taken and analyzed for oleic acid content by titration (modified AOCS method Ca 5a-40) [19] with an automatic burette (Metrohm, model Dosimat 715). Analytical measurements were made at least in triplicate, with standard deviation less than 0.03 mass%. The experiments were conducted until resin saturation and this saturation was monitored by the measurement of the collected samples’ pH. A new batch of anionic resin was used in each experimental run, since the resin regeneration step was not an aim of the present investigation. Nevertheless, resin regeneration can be easily performed in the present case by contacting the saturated solid bed with an ethanolic solution of sodium hydroxide. Such a procedure was already tested in our prior work, performed for measuring adsorption isotherms in the same kind of physical–chemical system [14]. The change in solution concentration along the experiments, expressed as oleic acid dimensionless concentration, gives the breakthrough curve. The total amount of removed oleic acid per mass of dry resin up to the saturation can be calculated from each breakthrough curve using the following equation: q=
CF Q mR
tend
1−
0
Cout CF
dt
(1)
In order to evaluate the process efficiency the breakthrough curves were divided in different areas associated with the resin uptake capacity, as indicated in Fig. 1. A1 is associated with the resin capacity used before the breakthrough point, defined as the instant tbreak for which Cout /CF = 0.1, A2 is related to the solute amount that leaves the column before the breakthrough point, without being adsorbed, and A3 is related to the resin capacity not efficiently used, since this part of the adsorption process occurs after the breakthrough point but before tend , the first instant corresponding to Cout /CF ∼ = 1.0. On the basis of these areas two different efficiencies can be evaluated: εr is the efficiency of solute removal and εf is the efficiency of resin utilization, defined by Eqs. (2) and (3). Using the calculated efficiency values a statistical analysis of the results was developed, which allowed the evaluation of the process performance.
εr =
Q · CF · tbreak −
0
(Cout /CF )dt
Q · CF · tbreak
εf =
tbreak
Q · CF · tbreak −
Q · CF · tend −
=
tbreak (Cout /CF )dt = 0tend 0
(Cout /CF )dt
A1 A1 + A2
(2)
A1 A1 + A3
(3)
Fig. 1. Areas A1 , A2 and A3 along a breakthrough curve.
2.2. Mathematical model A phenomenological model was developed using the following assumptions: (i) the description of the adsorption process should take into account intraparticle mass transfer limitations; (ii) a linear driving force is used to describe the concentration profile inside the particle pores; (iii) process conditions are isothermal and isobaric; (iv) column void fraction is constant; (v) physical properties of resin and fluid phases are constant; (vi) axial and radial dispersions are negligible in the fixed bed column; (vii) the adsorption equilibrium is described with a Langmuir isotherm. The mathematical model was obtained by means of mass balance equations applied to an element of volume in the liquid and solid phases. The mass balance equation for the fluid phase is: ∂C 1 ∂q ∂C + b = −u ε ∂t ∂t ∂z
(4)
With the following initial and boundary conditions: C(0, z) = 0,
C(t, 0) =
0 CF
(5) t=0 t>0
in z = 0,
(6)
The mechanism for oleic acid removal in the column involves mass transfer of the solute within the liquid solution around the resin beads, diffusion inside the resin pores and the ion exchange reaction. The very favorable shape of the isotherm suggests a fast reaction. On the other hand, the mass transfer mechanism can be modeled combining a film coefficient and the intraparticle diffusivity. The ion exchange resin Amberlyst A 26OH is a rigid crosslinked polymeric structure with pores (macroreticular solid) sufficiently wide to permit diffusion, but mass transfer resistance inside the pores plays probably the dominant role because diffusivity-values in the resin phase are necessarily lower than the solute diffusivity in the liquid phase. In fact, solute diffusion inside the crosslinked structure of the resin matrix is more difficult, but the migration of the counter-ions is exactly oriented to find the active sites fixed in this resin internal structure [18]. Assuming that the resistance in the resin phase is the dominant one, the diffusion inside the pores described by Fick’s law was replaced by a simplified kinetic expression in order to make easier the resolution of the differential equation system [20,21]. This approach assumes that the mass transfer driving force is linear with
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the concentration for the solid phase, so that the adsorption rate can be represented by the following equation: ∂q = −KS (q − qeq ) ∂t
(7)
This approach, called LDF (linear driving force) model, has the following initial condition: q(z, 0) = 0
(8)
The equilibrium concentration of oleic acid in the resin phase was calculated by the Langmuir isotherm represented in Eq. (9): qeq =
qm bCeq 1 + bCeq
(9)
where qm and b are the Langmuir isotherm constants. The constant of equilibrium b is related to the free energy of adsorption that corresponds to the affinity between the surface of adsorbent and the adsorbate and qm is the constant that represents the maximum capacity of adsorption by mass of adsorbent. Such an approach based on the LDF approximation was already used by other authors for modeling adsorption in ion exchange resins and other adsorbents [21–23]. To solve the system of partial differential equations formed by Eqs. (4) and (7), together with the initial and boundary conditions given by Eqs. (5), (6) and (8) and the equilibrium relation, Eq. (9), the method of lines was used. Initially the domain of the problem was discretized in (ne) elements. This procedure transforms the problem of solving the system of partial differential equations into an ordinary differential equation system, which was solved using the subroutine DASSL developed by Petzold [24], coded in FORTRAN. This code solves systems of algebraic/differential equations and uses backward differentiation formulae to advance the solution from one time step to the next. By this procedure the mass transfer coefficient in the adsorbent (KS ) was estimated using the experimental data of the breakthrough curves and the following objective function was minimized: F=
np
EXP MOD (Cout − Cout )
2
(10)
i=1 EXP is the experimental concentration of oleic acid in the where Cout MOD is the corresponding concentration of oleic acid outlet stream; Cout calculated by the model; and np is the number of experimental data points.
3. Results and discussion 3.1. Breakthrough experiments Fig. 2 shows the experimental breakthrough curves. As expected the results indicated that for higher flow rates and higher solute concentrations in the feed stream the breakthrough time (tbreak ) and the saturation time (tend ) are achieved faster. The efficiencies calculated according to Eqs. (2) and (3) and the corresponding experimental conditions are given in Table 2. Note that Table 2 indicates the actual flow rates and concentrations used in the experimental runs. In comparison to the planned values given in Table 1, the actual values exhibit a relative difference not larger than 5.5%. A very high efficiency of solute removal was obtained for all experiments (approximately 98%), what confirms the resin’s capacity for removing oleic acid and indicates that the fatty acid has a good affinity for the resin active sites. The εr -values were almost constant for all experiments, indicating that both parameters flow rate and concentration of solute do not influence the efficiency of its removal, at least in the range of values investigated in the present work.
Fig. 2. The experimental breakthrough curves. (*) 3.5 mass% and 25 mL min−1 . () 5 mass% and 16.5 mL min−1 . (×) 6.5 mass% and 25 mL min−1 . () 5 mass% and 33 mL min−1 . (䊉) 4 mass% and 19 mL min−1 . () 5 mass% and 25 mL min−1 . () 5 mass% and 25 mL min−1 . (♦) 5 mass% and 25 mL min−1 . () 6 mass% and 31 mL min−1 . () 6 mass% and 19 mL min−1 . (+) 4 mass% and 31 mL min−1 .
The efficiency of resin utilization (εf ) varied within the range 48–69%. This shows that the resin bed had at least half of its potential capacity used in an efficient way. These results also show that a decrease of the solution flow rate increases the efficiency of resin utilization. On the other hand, the influence of the initial solution concentration is not so clear. The experiment with best performance (εf = 0.687) is the one conducted at 5 mass% of oleic acid concentration and 16.5 mL min−1 , values that correspond to the central point concentration and to the lowest flow rate, respectively. In order to use the experimental breakthrough curves for process optimization the following response function is suggested: Response function =
εr · εf tbreak
(11)
Note that this response function takes into account both efficiencies, since it is important to maximize the solute removal as well as the efficient use of the resin capacity. Although in the present investigation the efficiency of solute removal εr has almost not varied, it should be considered that, in case a wider range of operational conditions would be used, the εr -values will probably change, so that a generic formulation for the response function including this variable is more appropriate. This formulation also considers the breakthrough time because it is important for the process productivity to reduce to a minimum the time period of maximum solute removal, since a new cycle of resin regeneration and adsorption can be initiated earlier and larger amounts of solution will be processed. In fact, this response function seems to be the best form for representing the process performance because it combines both efficiencies and the required time interval in terms of oleic acid removal (i.e., the period before breakthrough time). The statistical analysis generates the coded model presented in Eq. (12), which describes the response function in terms of the two investigated parameters, with determination coefficient of 97% and an average error of 10% (significance level of 95%). It should be noted that this statistical analysis was developed on the basis of the actual flow rates and concentrations given in Table 2. This means that the oscillations of the actual factors around the intended ones (Table 1) were incorporated in the results of the statistical analysis. εr .εf tbreak
= 0.0159 + 0.0039(X¯ 1 ) + 0.0035(X¯ 2 )
(12)
É.C. Cren et al. / Separation and Purification Technology 69 (2009) 1–6
5
Table 2 Efficiencies for the experimental breakthrough curves. Experimental run
X2 (mass%)
X1 (mL min−1 )
tbreak (min)
1 2 3 4 5 6 7 8 9 10 11
4.12 6.13 4.22 6.34 4.90 4.90 3.59 6.50 5.19 5.26 5.18
19.4 19.5 30.0 30.0 16.7 33.2 26.3 24.5 24.9 24.0 24.3
55 38 31 22 63 22 55 26 36 32 33
Both coded operational parameters, flow rate (X¯ 1 ) and oleic acid concentration (X¯ 2 ), have a positive influence upon the response function. This means that, in terms of the chosen response function, a lower efficiency of resin utilization (εf ) can be more than compensated by a reduction in the breakthrough time (tbreak ). In fact, the efficiency of resin utilization decreases as the flow rate increases because the residence time of the solution in the resin bed and, consequently, the time for mass transfer, becomes lower in this case. On the other hand, the throughput is larger and the resin bed is used for processing larger amounts of solution, an effect that has predominated in the present experimental results. For instance, if one compares the results for the first and third experiments given in Table 2, it can be seen that the efficiency of resin utilization decreases less than 10%, but the breakthrough time diminishes more than 30%. For this reason the net effect is the increase of the response function. Naturally such a result is valid only within the range of values investigated in the present work, since at very high flow rates the decrease in the efficiency of resin utilization will probably be more significant. Fig. 3 presents the response surface obtained for Eq. (12) and illustrates the behavior discussed above. 3.2. Mathematical model The breakthrough curves were also correlated using the mathematical model already described and the experimental conditions given in Table 2. The mass transfer coefficient Ks was used as the fit-
± ± ± ± ± ± ± ± ± ± ±
1 1 1 1 1 1 1 1 1 1 1
tend (min) 198 155 136 95 180 120 176 124 135 133 132
± ± ± ± ± ± ± ± ± ± ±
2 2 2 2 2 2 2 2 2 2 2
εr
εf
εr ·εf /tbreak
0.977 0.983 0.978 0.982 0.981 0.979 0.977 0.982 0.985 0.978 0.979
0.581 0.579 0.525 0.525 0.687 0.482 0.642 0.548 0.606 0.520 0.553
0.010 0.015 0.017 0.024 0.011 0.021 0.011 0.021 0.016 0.016 0.016
Fig. 4. () Experimental curve for experiment 10 in Table 2, (–) adjusted curve (qm = 1.329 g acid g dry resin−1 , b = 492.5 L g acid−1 and Ks = 2.54 × 10−2 min−1 ); (- - -) simulated curve (qm = 1.292 g acid g dry resin−1 , b = 460.0 L g acid−1 and Ks = 2.41 × 10−2 min−1 ).
ting parameter. The Langmuir isotherm obtained from equilibrium data measured in batch experiments by Cren and Meirelles [14] was incorporated into the mathematical modeling. The following Langmuir parameters were used: qm = (1.329 ± 0.037) g acid g dry resin−1 and b = (492.5 ± 32.5) L g acid−1 . Fig. 4 compares an experimental breakthrough curve and the corresponding calculated one. As can be seen the model described the dynamics of oleic acid removal in a very satisfactory way. A unique mass transfer coefficient Ks = 2.54 × 10−2 min−1 was adjusted for all 11 experiments. This parameter was estimated by minimization of the objective function given by Eq. (10). The experimental values for the resin capacity, as well as the corresponding values obtained according to the modeled breakthrough curves, were calculated by Eq. (1). As can be seen in Table 3 Table 3 Capacities calculated for the experimental and fitted breakthrough curves.
Fig. 3. Response surface for the model obtained according to the experimental design (Eq. (11)).
X2 (mass%)
X1 (mL min−1 )
qexp (g acid g dry resin−1 )
qmod (g acid g dry resin−1 )
4.12 6.13 4.22 6.34 4.90 4.90 3.59 6.50 5.19 5.26 5.18
19.4 19.5 30.0 30.0 16.7 33.2 26.3 24.5 24.9 24.0 24.3
1.23 1.29 1.17 1.22 1.18 1.13 1.13 1.22 1.23 1.24 1.18
1.29 1.32 1.22 1.31 1.25 1.27 1.17 1.30 1.30 1.27 1.24
6
É.C. Cren et al. / Separation and Purification Technology 69 (2009) 1–6
both values of resin capacity are close to each other. In fact, the deviations between the capacity values calculated according to the experimental curves and the corresponding ones calculated using the fitted curves varied within the range 2.3 and 12.4%. Comparing the experimental values given in Table 3 and the maximal capacity of oleic acid removal according to the batch equilibrium experiments (qm = 1.329 g oleic acid g dry resin−1 ), one can conclude that more than 85% of the resin capacity was used in the breakthrough runs. The resin capacity in equiv. L−1 (0.85) can be converted in g oleic acid g dry resin−1 by using the fatty acid molar mass (280.43 g mol−1 ), the resin bulk density (675 g L−1 ) and moisture (73.7 mass%). The obtained value is 1.343 g oleic acid g dry resin−1 , a result very close to the qm -value and to the capacities reported in Table 3. As indicated in a prior work [14], these capacity values correspond mainly to an adsorption mechanism by ion exchange. By washing several times the saturated solid phase with acid-free ethanolic solutions and afterwards regenerating it with an excess of sodium hydroxide alcoholic solution, Cren and Meirelles [14] concluded that more than 98.4% of the reported capacity value is due to the ion exchange mechanism. In order to evaluate the model sensitivity to the equilibrium parameters and mass transfer coefficient, breakthrough curves for the experimental run 10 were also calculated taking into account the uncertainties of the Langmuir parameters given above and a variation of ±5% in the adjusted Ks -value. Fig. 4 shows one of those calculated curves together with the adjusted one. As can be seen, variations in the values of the equilibrium and mass transfer parameters do not influence significantly the calculated breakthrough curves. In fact, the change in the calculated capacity values with the modified parameters, considering all the possible combinations of those parameters, was always less than 1.3%. The largest deviation was obtained for the lower limits of the parameter values. The low sensitivity of the model is a consequence of the almost rectangular isotherm that characterizes the present system and which causes a very favorable uptake of oleic acid from the alcoholic solutions. According to Table 3, the experimental capacity values increase to some extent as a consequence of increasing oleic acid concentration and decreasing flow rate, so that in the case of the second experiment 97% of the total resin capacity is used. The present work indicates the feasibility of recovering fatty acids from ethanolic solutions by means of ion exchange in a fixed resin bed. This kind of process can be used as a complement of edible oil deacidification by solvent extraction, since it makes possible the recovering of the solvent present in the extract stream for a new deacidification step by liquid–liquid extraction. The efficiency of solute removal was always close to 98% and the values obtained for the efficiency of resin utilization were, in most cases, larger than 52%. The experimental approach based on factorial design allowed the evaluation of the process performance and can contribute to its optimization. The mathematical model developed on the basis of the linear driving force approximation was able to represent correctly the experimental breakthrough curves. The experimental results, the investigation of the operational conditions’ effects by the surface response methodology and the successful modeling of the breakthrough curves can surely guarantee an appropriate design of this complementary process. Nevertheless, further investigations, mainly on the resin regeneration step, are necessary in order to check the viability of this process in an industrial scale.
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