Adsorption of Phenylethyl Alcohol onto Granular Activated Carbon


Jun 10, 2016 - m2·s−1 for PEA adsorption on the GAC at 298 K. Desorption ratios of PEA from GAC were 92.2−99.9% achieved by methanol in batch mod...
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Article pubs.acs.org/jced

Adsorption of Phenylethyl Alcohol onto Granular Activated Carbon from Aqueous Solution: Kinetics, Equilibrium, Thermodynamics, and Dynamic Studies Gaoming Lei,† Longhu Wang,‡ Xuesong Liu,‡ and Anyun Zhang*,† †

College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China



S Supporting Information *

ABSTRACT: Comparative studies were performed toward adsorption kinetics and equilibrium of phenylethyl alcohol (PEA) onto three typical types (F400D, CAL, and 207CX) of granular activated carbons (GAC). The effective diffusion coefficients were of the order of 10−12 m2·s−1 for PEA adsorption on the GAC at 298 K. Desorption ratios of PEA from GAC were 92.2−99.9% achieved by methanol in batch mode at 298 K. Among the GAC employed, the carbon CAL proved to be superior in terms of physical properties as well as adsorption capacity and rate toward PEA. Dynamic adsorption was investigated using this optimal activated carbon. The maximum bed saturation capacity toward PEA was 2.471 mmol·g−1 under optimal conditions (GAC mass 10.01 g, inlet concentration 4.391 mmol·kg−1, flow rate 6.5 × 10−3 kg·min−1, temperature 298 K). The Yoon-Nelson model best described breakthrough data of PEA on GAC bed, whereas Yan and Clark models gave a relatively poor fit. The outcome of this work will facilitate adsorptive recovery of PEA from rose hydrolate byproduct using GAC.

1. INTRODUCTION Rose oil is one of the most valuable essential oils all over the world. The main byproduct of rose oil distillation is rose water. It contains a certain amount of water-soluble essential oil components, in which phenylethyl alcohol (PEA) predominates.1−3 PEA as well as minor components in rose water are regarded as valuable aroma compounds characteristic of rose flowers. Efforts have been made for PEA isolation from aqueous solutions. Among different techniques employed, the adsorption method proved efficient and effective. Until now, polymeric resins are most frequently used. Bohra et al.4 employed resins to recover PEA from its nearly saturated aqueous solution. The exhaustion capacity of XAD-4 column toward PEA was 3.9 and 2.8 mmol·g−1 with and without the presence of linalool, respectively (inlet concentration of PEA 8000 ppm, ambient temperature). Savina et al.5 described a method of PEA extraction using column of resin Dowex S-112 from distillation residues which were generated from alcohol production. Mei et al.6 investigated PEA adsorption onto macroporous resins from mixed solution of PEA and Lphenylalanine. Under conditions of batch mode (initial concentration of PEA, 41 mmol·dm−3; dosage of hydrated resin, 0.1 g·cm−3; 298 K), the capacity of resin D101 toward PEA was 1.115 mmol·g−1. Wang et al.7 utilized columns of macroporous resins to achieve continuous removal of PEA © XXXX American Chemical Society

from the fed-batch culture system. Under experimental conditions (300 g of hydrated resin; concentration of feed solution, 16−22 mmol·dm−3; flow rate 20 cm3·min−1), the capacity of resin FD0816 toward PEA was 1.6 mmol·g−1. Šimko et al.8 investigated selective adsorption of PEA over Lphenylalanine from their mixed solution using Amberlite and Macronet resins. In single-component adsorption, the maximum capacities (calculated from Langmuir equation) of resins toward PEA ranged from 3.7 to 5.6 mmol·g−1 at ambient temperature. In binary adsorption, the separation factors of PEA over L-phenylalanine ranged from 24.2 to 121. In most investigations, ethanol or 95% ethanol solution were commonly used as desorbents. In addition to polymeric resins, other adsorbent materials were also used for PEA isolation. Hu et al.9 investigated adsorption of PEA onto silica aerogel (SiO2) from PEAsaturated SC−CO2. The maximum amount of PEA adsorbed onto SiO2 was 2.7 mmol·g−1 at 313.2 K and 16.7 MPa. Carpiné et al.10 used GAC to recover PEA from wastewater of coffee production. The maximum bed saturation capacity toward PEA was 1.631 mmol·g−1 under optimal conditions (GAC mass 1 g, Received: March 7, 2016 Accepted: June 2, 2016

A

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Table 2. Physical Properties of the Three GACa

inlet concentration 1.654 mmol·dm−3, flow rate 3.34 cm3· min−1, 303 K). Adsorption using granular activated carbon (GAC) is among the most efficient methods for recovering organics from aqueous solutions.11−14 Fundamental data are necessary for method development. Although PEA adsorption onto GAC has been investigated by Carpiné et al.,10 there is still a lack of data on adsorption reversibility, diffusivity, thermodynamic parameters, and modeling of dynamic adsorption, etc. Besides, the maximum capacity of GAC toward PEA was relatively low (1.631 mmol·g−1) as reported by Carpiné et al.,10 probably due to the limitation of GAC selected. Further studies are needed on comparative adsorption using different types of GAC. The objective of this work is to investigate the influences of GAC properties (pore volume, specific surface area, and pore size) on PEA adsorption and to acquire fundamental data for method development. First, three typical types of GAC were used for comparative study. The kinetics, equilibrium, and thermodynamics of adsorption were investigated in batch mode. Desorption ratios were determined. The influences of GAC properties were evaluated. Second, dynamic adsorption was performed with the optimal GAC. Influences of flow rate, GAC mass, and inlet concentration were investigated. Parameter calculations and modeling of dynamic adsorption were performed. This work is part of our efforts to recover water-soluble essential oil components from hydrolate or distillation wastewater.3,15−18

value parameter

F400D

CAL

207CX

dp/mm SBET/m2·g−1 Smicro/m2·g−1 Smeso/m2·g−1 Vtotal/cm3·g−1 Vmicro/cm3·g−1 Vmeso/cm3·g−1 dav/nm

1.0 863.2 487.9 375.4 0.4638 0.2221 0.2418 2.15

1.0 1058 526.2 531.3 0.6515 0.2383 0.4132 2.46

1.0 921.2 722.7 198.5 0.4428 0.3338 0.1090 1.92

a

dp, average particle size; SBET, BET surface area; Smicro, micropore surface area (t-plot); Smeso, meso/macro-pore surface area (t-plot); Vtotal, total pore volume; Vmicro, micropore volume (t-plot); Vmeso, mesopore volume (Vmeso = Vtotal − Vmicro); dav, average pore diameter (dav = 4Vtotal/SBET); the standard uncertainty u is u(dp) = 0.5 mm (0.68 level of confidence).

distributions are given in Figure 1. Deionized water was prepared with Milli-Q system. HPLC grade acetonitrile was from Amethyst Chemicals (J&K Scientific). Other reagents were of analytical grade.

2. EXPERIMENTAL SECTION 2.1. Materials and Reagents. PEA of analytical standard (>99.5%, GC) and high purity (>99.0%, GC) were from Aladdin (Shanghai, China). Its molecular structure was optimized using GAMESS software19 by employing Hartree− Fock method with 6-31G basis set. The molecular size was obtained from the optimized molecular structure. These as well as other properties of PEA are given in Table 1. GAC (F400D, Table 1. Properties of PEAa

Figure 1. N2 adsorption−desorption isotherms at 77 K (a) and pore size distributions (b) of three GAC. Ads, adsorption; Des, desorption.

2.2. Pretreatment of GAC and Preparation of PEA Solution. GAC were screened for mesh size 12 × 40 (average particle size 1.0 mm). They were washed and distilled with deionized water, dried at 378 K for 48 h, and stored in a desiccator. Since the water-soluble oil in rose hydrolate is predominantly composed of PEA (usually 70−90% of the total oil by GC),1−3 the hydrolate can be regarded as a pseudosingle-solute system. The model solution was prepared by adding a certain volume of PEA (>99.0%, GC) to deionized water and being stirred at room temperature for 48 h, using a magnetic stirrer (Zhiwei Electric, Shanghai, China). For batch mode, the concentration of PEA solution was ca. 4.267 mmol·kg−1, which was close to

a

The optimized molecular structure was obtained using GAMESS software19 and Hartree−Fock method with 6-31G basis set. The molecular size was obtained from the optimized molecular structure.

CAL, and 207CX) were supplied by Calgon Carbon (Suzhou, China). F400D and CAL were made from bituminous coal, while 207CX was made from coconut shells. They were selected for comparative study because they possess relatively high adsorption capacity toward organics and pore structures suitable for a wide range of contaminant removal, as claimed by the manufacturer. Their physical properties determined with Micromeritics ASAP 2020 M are listed in Table 2. The N2 adsorption−desorption isotherms at 77 K and pore size B

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Table 3. Conditions of Dynamic Adsorptiona run

W/g

L/cm

ε

Cin/mmol·kg−1

103·f/kg·min−1

v/cm·min−1

1 2 3 4 5

7.509 7.505 4.993 10.01 5.020

9.3 9.1 5.9 12.3 6.2

0.43 0.41 0.40 0.42 0.42

4.256 4.365 4.261 4.391 2.203

6.5 13.6 6.6 6.5 6.7

3.25 6.77 3.28 3.24 3.34

a W, mass of GAC inside the column; L, length of fixed bed; ε, bed void fraction (ε = 1 − ρb/ρp, where ρb is bulk density and ρp is particle density); Cin, inlet concentration of PEA solution; f, mass flow rate; v, superficial velocity; the activated carbon was CAL; the temperature was 298 K; the standard uncertainties u are u(T) = 0.1 K, u(W) = 1 × 10−4 g, u(L) = 0.1 cm (0.68 level of confidence); the combined uncertainties U are U(ε) = 0.02, U(Cin) = 1 × 10−3 mmol·kg−1, U(f) = 2 × 10−4 kg·min−1, U(v) = 0.1 cm·min−1 (0.68 level of confidence).

that of real rose hydrolate.2,3 For dynamic adsorption, the concentrations of model solutions are given in Table 3. 2.3. HPLC Analysis. HPLC conditions were from our previous work.3 Briefly an Agilent 1200 HPLC system was employed, and the analytical standard of PEA (>99.5%, GC) was used for calibration. 2.4. Kinetic Experiments. GAC of different amounts (ca. 0.05, 0.25, and 1.2 g, accurately weighed using Mettler XS105 balance) were placed into 250 cm3 conical flasks and PEA solution of 250 cm3 was added. PEA solution without the addition of GAC served as a control. The flasks were sealed and shaken at 120 rpm for 72 h at 298 K, using a DKZ-2 thermostatic water bath shaker (Jinghong Equipment, Shanghai, China). A volume of 2.0 cm3 was withdrawn from the bulk solution at certain time intervals and filtered immediately with 0.45 μm membrane filters. It was subjected to HPLC analysis. Analysis of control solution (without the addition of GAC) indicated that the PEA concentration underwent no changes during shaking. The dosage of GAC (dGAC, g·kg−1) is presented as

irreversibility, i.e., the fraction of irreversible adsorption.20,21 GAC of 0.25 and 1.0 g were in contact with PEA solution of 250 cm3 under shaking conditions for 72 h at 298 K. The GAC and solution in equilibrium were separated by filtration. The solution was subjected to HPLC. The experiments were repeated as necessary. Loaded GAC equivalent of 1.0 g (dry weight) was brought into contact with methanol of 200 cm3 and shaken for 8 h at 298 K.20,21 Desorption solution was sampled and filtered for HPLC analysis. The desorption ratio D (%) is calculated as

D=

W (1) M where W and M are the masses of GAC (g) and solution (kg), respectively. The amounts of PEA adsorbed (mmol·g−1) at time t (min) and at equilibrium are designated as Qt and Qe, respectively:

(C0 − Ct )M W

(2)

Qe =

(C0 − Ce)M W

(3)

where C0 is the initial concentration of PEA in solution (mmol· kg−1). Ct and Ce are concentrations of PEA (mmol·kg−1) at time t and at equilibrium, respectively. The fractional attainment of equilibrium (%) is designated as F(t): F (t ) =

(5)

where Cd and Md are the concentration (mmol·kg−1) and mass (kg) of desorption solution, respectively. 2.7. Dynamic Experiments. Different masses of activated carbon CAL (5.0, 7.5, and 10 g, accurately weighed using FA2004 balance, Yueping Apparatus, China) were soaked in deionized water overnight and packed into a glass column (1.6 cm i.d. × 50 cm i.l.). In order to obtain uniform flow distribution and to avoid possible end effects, glass beads of 1.0 mm were packed inside the column to height of 4.0 and 3.0 cm below and above the GAC bed, respectively.15,22,23 The fixed bed of GAC with water was settled overnight. The column was fitted with a jacket connected to a thermostatic water bath circulator DC-1006 (Dawei Equipment, Hangzhou, China). The temperature was set at 298 K. The solution of PEA was then passed through the bed in down-flow mode. The flow rate was controlled by a peristaltic pump (Longer Pump, Baoding, China) fitted at outlet at the bottom of the column. The effluent was collected using a fraction collector and analyzed by HPLC. The experimental setup is shown in Figure 2. Detailed conditions of each run are listed in Table 3. Breakthrough

dGAC =

Qt =

CdMd Q eW

Qt Qe

(4)

2.5. Equilibrium Experiments. Different masses of GAC (ca. 0.02−0.6 g) accurately weighed were brought into contact with PEA solution of 100 cm3, respectively. PEA solution without the addition of GAC served as a control. They were shaken for 72 h at 298, 308, and 318 K, respectively. The solutions in equilibrium were sampled and filtered for HPLC analysis. The equilibrium adsorption capacity was calculated using eq 3. 2.6. Desorption Experiments. Desorption experiments were performed in order to test the extent of adsorption

Figure 2. Experimental setup of dynamic adsorption. C

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Figure 3. Effects of contact time and GAC dosage on PEA adsorption onto F400D (a), CAL (b), and 207CX (c) at 298 K.

curves (Cout/Cin vs Meff) were plotted as the ratio of outlet to inlet concentrations against mass of effluent solution (kg). 2.8. Error Analysis. Experimental data of kinetics, equilibrium, and breakthrough curves were fitted using the nonlinear method. Fitting results were evaluated using adjusted R-square (Adj. R2) and average relative deviation (ARD, %): ARD =

1 N

N

∑ i=1

pore blockage effects. Mesoporous GAC, however, tends to be unaffected.26 These demonstrate the importance of mesopores. 3.2. Effects of Contact Time and GAC Dosage. Effects of contact time and GAC dosage on PEA adsorption onto three GAC at 298 K were first investigated. As dGAC was 4.8 g·kg−1, kinetic curves of three GAC were similar to each other (Figure 3). The fractional attainment of equilibrium reached 50% within 2 h and 98% within 15 h. The difference between three GAC was not significant because the interior surfaces of GAC were not fully covered at relatively high dosages. As dGAC was 1.0 or 0.2 g·kg−1, the three GAC showed difference. CAL reached equilibrium (F(t) = 98%) within 10 h while F400D reached equilibrium (F(t) = 97%) within 18 h. On the other hand, it took 32 h for 207CX to reach equilibrium (F(t) = 98%). CAL possessed superior kinetic characteristics mainly due to its mesoporosity. In contrast, the adsorption of PEA onto 207CX was relatively slow. This can be explained by the fact that mesopores were in only a small proportion in 207CX. Based on these results, the contact time of 72 h was selected for kinetic and equilibrium studies to ensure the attainment of equilibrium. At dGAC of 4.8 g·kg−1, the equilibrium amounts of PEA adsorbed by three GAC ranged from 0.9078 to 0.9186 mmol· g−1, which were relatively small. Meanwhile, the excess amounts of GAC led to almost complete removal of PEA (98.0−99.5%) from aqueous phase. On the other hand, the equilibrium adsorption amounts were relatively large (1.989−2.433 mmol· g−1) at dGAC of 0.2 g·kg−1. In this case, the removal percentages of PEA were rather low (9.4−11.7%) although the GAC were almost fully saturated. In addition, the equilibrium adsorption amounts of three GAC ranged from 1.837 to 2.130 mmol·g−1 at dGAC of 1.0 g·kg−1, with PEA removal of 43.5−51.1%. In order to perform effective comparative investigation among three GAC, the dosage of 1.0 g·kg−1 was selected for kinetics study. 3.3. Kinetic Modeling. The pseudo-first-order rate equation of Langergren27 based on adsorption capacity is widely used for description of kinetic data. It is presented as

yexp − ycalc yexp

(6)

where N is the number of data points and parameters (yexp and ycalc) are experimental and calculated values for each data point, respectively.

3. RESULTS AND DISCUSSION 3.1. Properties of PEA and the GAC. Since PEA is the predominant component of rose hydrolate volatiles,1−3 this study focused on this compound. As listed in Table 1, the optimized molecular size of PEA was 0.91 nm × 0.53 nm × 0.34 nm. As shown in Table 2 and Figure 1, the three GAC were representative of three types of activated carbons: microporous (207CX) and mesoporous (CAL) types, and the type with comparable micropores and mesopores (F400D). They possessed relatively high specific surface areas (863.2− 1058 m2·g−1) and relatively large pore volumes (0.4428−0.6515 cm3·g−1). Their average pore diameters ranged from 1.92 to 2.46 nm. The match between pore diameter of adsorbents and molecular size of adsorbates is a main factor that influences adsorption.24 It can be noted that the pore sizes of all three GAC match PEA molecule well (Tables 1 and 2). In addition, micropores mainly provide adsorption sites, while mesopores serve as difussion paths. Consequently the presence of mesopores not only improves adsorption rate but also increases the coverage of micropores and hence adsorption capacity.25 Moreover, real aqueous solution to be processed generally contains a certain amount of natural organic matters (NOM), which may reduce the capacity of microporous GAC due to D

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Figure 4. Kinetic modeling of PEA adsorption onto F400D (a), CAL (b), and 207CX (c) at 298 K. GAC dosage 1.0 g·kg−1.

Q t = Q e(1 − exp(−k1t ))

(Adj. R2 0.9958−0.9976, ARD 2.76−3.74%) fitted experimental data better than the pseudo-second-order equation (Adj. R2 0.9642−0.9908, ARD 5.02−9.68%). Moreover, the values of Qe calculated based on pseudo-first-order equation agreed well with experimental values (Qexp). The values of rate constant k1 were (3.930, 5.280, and 2.560) × 10−3 min−1 for PEA adsorption onto F400D, CAL and 207CX, respectively. These indicated that the carbon CAL presented relatively higher adsorption rate toward PEA. 3.4. Diffusivity Determination. Although fitting with pseudo-first-order or pseudo-second-order equations can provide information on adsorption capacity and adsorption rate, it gives no insight into adsorption mechanisms.11,12 Regarding adsorption from aqueous phase, there are generally three sequential steps: external surface adsorption, intraparticle diffusion, and adsorption onto sites. Many investigators found that the overall adsorption process on activated carbon is controlled by external surface adsorption (macropore diffusion) followed by intraparticle diffusion (micropore diffusion).11,13,29−31 In order to determine the diffusivity, the equation proposed by Boyd et al.32 was widely used.12,14,31 The equation considers adsorption on spherical adsorbent particles which is controlled by a diffusion mechanism. It assumes that the equilibrium concentration in the aqueous phase does not vary much from the initial concentration and that the temperature gradients between adsorbent particles and the surrounding aqueous phase are negligible. It is presented as

(7)

where k1 is pseudo-first-order rate constant (min−1). On the other hand, the pseudo-second-order rate equation which is based on adsorption capacity and describes chemisorption was proposed by Ho and McKay.28 It is presented as Qt =

Q et 1/k 2Q e + t

(8)

where k2 is the pseudo-second-order rate constant (g·mmol−1· min−1). The two equations were employed to fit experimental data. Results are shown in Figure 4 and fitting parameters are listed in Table 4. As it turned out, the pseudo-first-order equation Table 4. Kinetic Parameters of PEA Adsorption onto Three GAC at 298 Ka value parameter experimental pseudo-firstorder

pseudosecond-order

diffusivity

Qexp/mmol·g−1 Qe/mmol·g−1 103·k1/min−1 Adj. R2 ARD/% Qe/mmol·g−1 103·k2/g·mmol−1·min−1 Adj. R2 ARD/% 1012·De/m2·s−1

F400D

CAL

207CX

1.837 1.830 3.930 0.9958 3.74 2.012 2.713 0.9802 5.08 1.193

2.118 2.118 5.280 0.9972 2.76 2.299 3.286 0.9642 9.68 1.788

2.130 2.107 2.560 0.9976 3.74 2.394 1.331 0.9908 5.02 0.7001

F (t ) = 1 −

The GAC dosage is 1.0 g·kg−1; Qexp, experimental adsorption amount at equilibrium (72 h); Qe, calculated adsorption amount at equilibrium; k1 and k2, pseudo-first-order and pseudo-second-order rate constants, respectively; Adj. R2, adjusted R-square; ARD, average relative deviation; De, effective diffusion coefficient; the standard uncertainty u(T) is u(T) = 0.1 K (0.68 level of confidence); the combined uncertainties U are U(dGAC) = 1 × 10−3 g·kg−1, U(Qexp) = 1 × 10−3 mmol·g−1 (0.68 level of confidence). a

6 π2



∑ n=1

⎛ −n2π 2D t ⎞ 1 e ⎜ ⎟ exp n2 ⎝ ro 2 ⎠

(9)

where t is time of contact (s) and n is an integer. Parameter r0 is the average radius (m) of adsorbent particles, and De is effective diffusion coefficient (m2·s−1). Furthermore, a close approximation to eq 9 made by Vermeulen33 which fits the whole range of (0 < F(t) < 1) were commonly used for De calculation:13,30,31,34 E

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Figure 5. Adsorption isotherms of PEA onto three GAC. Freundlich (a) and Langmuir (b) fit for F400D; Freundlich (c) and Langmuir (d) fit for CAL; Freundlich (e) and Langmuir (f) fit for 207CX.

Table 5. Equilibrium Parameters of PEA Adsorption onto Three GACa Freundlich model GAC

T/K

F400D

298 308 318 298 308 318 298 308 318

CAL

207CX

a

KF/mmol

·kg ·g

1−1/n

1.434 1.342 1.272 1.681 1.558 1.495 1.743 1.639 1.568

1/n

−1

Langmuir model 2

1/n

Adj. R

0.2263 0.2347 0.2393 0.2184 0.2273 0.2318 0.2047 0.2140 0.2211

0.9896 0.9968 0.9896 0.9808 0.9918 0.9843 0.9863 0.9956 0.9861

ARD/% 2.98 1.59 2.65 4.95 3.11 3.94 4.00 2.35 3.86

−1

Qmax/mmol·g 1.907 1.788 1.758 2.162 2.019 1.990 2.160 2.049 2.022

KL/kg·mmol−1

Adj. R2

ARD/%

5.606 5.205 4.163 7.795 6.677 5.663 10.99 8.965 7.330

0.9223 0.8840 0.9382 0.9355 0.9013 0.9439 0.9081 0.8663 0.9287

8.31 10.2 6.68 8.58 10.5 7.08 9.95 12.4 8.22

Adj. R2, adjusted R-square; ARD, average relative deviation; The standard uncertainty u(T) is u(T) = 0.1 K (0.68 level of confidence). 1/2 ⎡ ⎛ −π 2D t ⎞⎤ e ⎥ ⎟ F(t ) = ⎢1 − exp⎜ 2 ⎢⎣ ⎝ ro ⎠⎥⎦

was comparable to that of F400D, but higher than that of 207CX (P < 0.05, Tukey’s HSD). This indicated that the carbon CAL possessed relatively higher overall diffusivity. 3.5. Adsorption Equilibrium and Thermodynamic Parameters. The adsorption isotherms of PEA onto three GAC at 298, 308, and 318 K are shown in Figure 5. Freundlich and Langmuir models are widely used for description of adsorption equilibrium. The Freundlich model assumes the adsorption onto heterogeneous surface of adsorbents and is presented as35

(10)

The values of De can be calculated from the slope of the plot obtained with the linear form of eq 10:13,31 ⎞ π 2Det ⎛ 1 ln⎜ ⎟= 2 ro 2 ⎝ 1 − F (t ) ⎠

(11)

Under experimental conditions, De values were (1.193, 1.788, and 0.7001) × 10−12 m2·s−1 for PEA adsorption on F400D, CAL, and 207CX, respectively (Table 4). The De value of CAL

Q e = KFCe1/ n F

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where KF is the Freundlich constant (mmol1−1/n·kg1/n·g−1) indicating adsorption capacity and 1/n is a constant about adsorption intensity. On the other hand, the Langmuir equation describes monolayer adsorption onto the surface of adsorbents:36 Q e = Q max

KLCe 1 + KLCe

of irreversible adsorption was very small and that PEA adsorption onto three GAC was mainly reversible.20 Considering physical characteristics of the GAC as well as adsorption capacity and rate toward PEA, CAL was selected as the optimal activated carbon for further study. 3.7. Influences of Process Conditions on Breakthrough Curves. Influences of process conditions on breakthrough curves are shown in Figures 6−8. As the flow

(13)

where KL is a constant related to adsorption affinity (kg· mmol−1) and Qmax is maximum adsorption capacity (mmol· g−1). The two models are employed to fit the isotherm data. Results are shown in Figure 5, and fitting parameters are listed in Table 5. Freundlich (Adj. R2 0.9808−0.9968, ARD 1.59− 4.95%) was better than Langmuir (Adj. R2 0.8663−0.9439, ARD 6.68−12.4%) for describing adsorption isotherm data. The Freundlich model, however, gave no information on maximum adsorption capacity. The Langmuir equation can provide this information, but the calculated values of adsorption amounts exhibited relatively large deviations from experimental values (Figure 5). Consequently the parameter Qmax from Langmuir cannot give an accurate prediction of maximum adsorption capacity (Table 5). On the other hand, the Freundlich constant 1/n ranged from 0.2047 to 0.2393 under experimental conditions, indicating that the adsorption tended to happen easily.21 Thermodynamic parameters were calculated including entropy change (ΔS°, J·mol−1·K−1), enthalpy change (ΔH°, KJ·mol−1) and change of Gibbs free energy (ΔG°, KJ·mol−1). The parameter calculation was presented in Supporting Information (eqs S1−S3, Figure S1). The values are listed in Table S1 in Supporting Information. As it turned out, the adsorption of PEA onto three GAC was exothermic (ΔH° < 0) and was physical adsorption (|ΔH°| < 40 kJ·mol−1).37 It was thermodynamically favorable (ΔS° > 0). The positive values of entropy change may be due to the increasing randomness with adsorption onto the heterogeneous surface of GAC.38 The adsorption was a spontaneous process (ΔG° < 0). 3.6. Desorption Ratios. The desorption ratios of PEA from three GAC with different initial loadings are listed in Table 6. Methanol was selected as desorbent because it is a strong solvent for PEA. Desorption ratios under experimental conditions (batch mode, single cycle, 298 K) were ≥92.2%. The values showed no significant difference among three GAC and different initial loadings. These indicated that the fraction

Figure 6. Influences of flow rate on PEA breakthrough on GAC bed at 298 K: plots of Cout/Cin against t (a) and Meff (b). The activated carbon was CAL, GAC mass 7.5 g, inlet concentration 4.256−4.365 mmol·kg−1, Meff = ft.

rate increased from (6.5 to 13.6) × 10−3 kg·min−1, the breakthrough occurred earlier (Figure 6a). However, the curves of Cout/Cin vs Meff showed a very small variation (Figure 6b). This was because the increase of flow rate resulted in higher mass transfer rate and hence faster breakthrough and saturation of GAC bed.39,40 As the mass of GAC increased from 5.0 to 7.5 g and from 7.5 to 10 g, the time of breakthrough extended (Figure 7). This was due to more adsorption sites inside the column.39,40 As the inlet concentration increased from 2.203 to 4.261 mmol·kg−1, the

Table 6. Desorption Ratios of PEA from GAC Achieved by Methanol at 298 Ka GAC

initial loading/mmol·g−1

D/%

F400D

1.051 1.765 1.068 2.002 1.084 1.982

96.6 99.9 94.8 96.1 92.2 94.3

CAL 207CX

a

D, desorption ratios achieved in batch mode and single cycle (liquid− solid phase ratio 200 cm3·g−1); the standard uncertainty u is u(T) = 0.1 K (0.68 level of confidence); the combined uncertainties U are U(initial loading) = 1 × 10−3 mmol·g−1, U(D) = 0.5% (0.68 level of confidence).

Figure 7. Influences of GAC mass on PEA breakthrough on GAC bed at 298 K. The activated carbon was CAL, inlet concentration 4.256− 4.391 mmol·kg−1, flow rate 6.5−6.6 × 10−3 kg·min−1. G

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10−3 kg·min−1, 298 K), the values of qb ranged from 1.190 to 1.705 mmol·g−1, whereas those of qe ranged from 2.150 to 2.471 mmol·g−1. The saturation capacities of fixed bed were comparable to those achieved in batch studies with the same activated carbon CAL (2.118 and 2.430 mmol·g−1 at GAC dosages of 1.0 and 0.2 g·kg−1, respectively, at 298 K). In addition, the bed saturation capacities achieved in this investigation were higher than those reported in literature (1.082−1.631 mmol·g−1) under similar conditions.10 This explained the importance of selection of suitable type of GAC with favorable properties. For dynamic operation, the efficiency and effectiveness of fixed bed are both important. At time t, the utilization efficiency of fixed bed, i.e., the fraction of length of equilibrium section, is designated as f rLES (%): q LES frLES = = t L qe (17)

breakthrough curve became steeper (Figure 8). This can be explained by the increase of mass transfer driving force and hence sharpening of mass transfer zone (MTZ).39

Figure 8. Influences of inlet concentration on PEA breakthrough on GAC bed at 298 K. The activated carbon was CAL, GAC mass 5.0 g, flow rate 6.6−6.7 × 10−3 kg·min−1.

where LES and L are lengths (cm) of equilibrium section and fixed bed, respectively. On the other hand, the effectiveness of fixed bed was evaluated by the removal percentage of PEA from aqueous phase, which is designated as pcrem (%):

3.8. Parameter Calculation for Dynamic Adsorption. The time of breakthrough (Cout/Cin = 0.05), half-breakthrough (Cout/Cin = 0.5), and exhaustion (Cout/Cin = 0.99) was designated as tb, t0.5 and te (min), respectively. On the other hand, the stoichiometric time of breakthrough is presented as ts (min): ts =

∫0

te

t

pcrem =

C int

(18)

Values of f rLES and pcrem at different time of dynamic adsorption are listed in Table 8.

⎛ C ⎞ ⎜1 − out ⎟dt C in ⎠ ⎝

(14)

Table 8. Utilization Efficiency of Fixed Bed (f rLES) and Removal Percentage of PEA from the Aqueous Phase (pcrem) at Different Times of Dynamic Adsorptiona

where Cin and Cout are inlet and outlet concentrations (mmol· kg−1), respectively. Values of these parameters are listed in Table 7. It was noted that ts agreed well with t0.5, indicating that the breakthrough curves were symmetrical S-shaped ones. The PEA loading on the GAC bed at time t (min) is designated as qt (mmol·g−1):

f rLES/%

t

qt =

∫0 (Cin − Cout)dt

f ∫ (C in − Cout)dt 0

(15) W where f is the mass flow rate (kg·min−1) of feed solution. The loadings of PEA on the bed at tb, t0.5, and te are designated as qb, q0.5, and qe (mmol·g−1), respectively. According to eqs 14 and 15, the saturation loading qe is also presented as

pcrem/%

run

tb

t0.5

te

tb

t0.5

te

1 2 3 4 5

62.5 56.0 59.1 69.0 55.4

91.8 88.3 89.7 92.2 89.7

100 100 100 100 100

98.9 98.8 98.5 99.2 98.8

90.1 88.5 88.7 92.4 88.8

52.2 51.6 53.4 54.8 58.4

a

The activated carbon was CAL; the temperature was 298 K; the standard uncertainties u are u(tb) = u(t0.5) = u(te) = 1 min (0.68 level of confidence); the combined uncertainties U are U( f rLES) = 0.5%, U(pcrem) = 0.5% (0.68 level of confidence).

fC ints (16) W Values of qb, q0.5, and qe are included in Table 7. Under experimental conditions (GAC mass 4.993−10.01 g, inlet concentration 2.203−4.391 mmol·kg−1, flow rate 6.5−13.6 × qe =

At time of breakthrough (tb), the values of f rLES ranged from 55.4% to 69.0% under experimental conditions. It was mainly influenced by GAC mass. As mass of GAC increased from 4.993 to 10.01 g, the values of frLES at tb increased from 59.1%

Table 7. Parameters for Dynamic Adsorption of PEA on GAC Bed at 298 Ka run

tb/min

t0.5/min

te/min

ts/min

qb/mmol·g−1

q0.5/mmol·g−1

qe/mmol·g−1

1 2 3 4 5

403 169 245 606 410

648 297 417 870 735

1219 578 769 1584 1249

637 298 412 871 728

1.463 1.325 1.356 1.705 1.190

2.149 2.090 2.058 2.279 1.929

2.342 2.368 2.294 2.471 2.150

a The activated carbon was CAL; tb, t0.5, and te, time of breakthrough (Cout/Cin = 0.05), half-breakthrough (Cout/Cin = 0.5) and exhaustion (Cout/Cin = 0.99), respectively; ts, stoichiometric time; qb, q0.5, and qe, PEA loadings on GAC bed at tb, t0.5, and te, respectively; the standard uncertainties u are u(T) = 0.1 K, u(tb) = u(t0.5) = u(te) = 1 min (0.68 level of confidence); the combined uncertainties U are U(qb) = U(q0.5) = U(qe) = 2 × 10−3 mmol· g−1 (0.68 level of confidence).

H

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Table 9. Fitting Parameters of PEA Breakthrough on GAC Bed at 298 Ka Yoon-Nelson model run 1 2 3 4 5

10 ·kYN /min 2

−1

τ/min

1.277 2.448 1.715 1.076 0.9862

qYN/mmol·g

640 308 422 879 741

2.373 2.436 2.376 2.512 2.185

−1

Yan model 2

Adj. R

ARD/%

aY

0.9984 0.9743 0.9938 0.9920 0.9894

4.86 23.8 6.31 12.4 13.4

3.340 3.555 3.332 3.495 3.175

qY/mmol·g 2.633 2.346 2.358 3.066 2.246

−1

Adj. R

Clark model 2

0.8402 0.9224 0.8805 0.7508 0.8829

ARD/% 62.9 41.1 31.8 156 51.9

10

−10

·AC

63.76 5.937 1.971 5701 2.968

10 ·rC /min−1

Adj. R2

ARD/%

3.699 6.836 4.736 3.184 2.780

0.9683 0.9046 0.9445 0.9729 0.9367

18.0 44.4 15.9 22.8 30.1

2

The activated carbon was CAL; kYN, Yoon-Nelson rate constant; τ, time of half-breakthrough (Cout/Cin = 0.5); qYN, bed saturation capacity calculated by Yoon-Nelson model; Adj. R2, adjusted R-square; ARD, average relative deviation; aY, rate constant of Yan model; qY, bed saturation capacity calculated by Yan model; AC and rC, constants of Clark model.

a

Figure 9. Comparison of Yoon-Nelson (a), Yan (b), and Clark (c) models for fitting PEA breakthrough on GAC fixed bed at 298 K. The activated carbon was CAL, GAC mass 10.01 g, inlet concentration 4.391 mmol·kg−1, flow rate 6.5 × 10−3 kg·min−1.

At t0.5, frLES ranged from 88.3% to 92.2%, while pcrem ranged from 88.5% to 92.4% under experimental conditions (Table 8). 3.9. Modeling Breakthrough Curves. Yoon-Nelson, Yan, and Clark are well-established models which are widely used for description of breakthrough curves. The Yoon-Nelson model41−43 is a relatively simple model assuming that the rate of decrease in the probability of adsorption for each adsorbate molecule is proportional to the probability of adsorbate adsorption and adsorbate breakthrough on the adsorbent. It generally fits experimental data over the range of 0−100% breakthrough. It is presented as

to 69.0%. This was due to the increasing ratio of bed length to the length of MTZ. As dynamic adsorption proceeded from breakthrough (tb) to exhaustion (te), the values of f rLES increased, finally up to 100%. In contrast, the values of pcrem were relatively high (98.5−99.2%) at breakthrough and then decreased with time. That is, f rLES and pcrem changed in opposite directions with elapse of time. In order to achieve relatively high values of f rLES and pcrem simultaneously, time of half-breakthrough (t0.5) was preferred. Moreover, since ts and t0.5 agreed well with each other (Table 7), the values of f rLES and pcrem at t0.5 were basically equal: frLES(t 0.5) =

Cout exp(k YNt − k YNτ ) = C in 1 + exp(k YNt − k YNτ )

q0.5 qe

where kYN is the rate constant (min−1) and τ is the time of halfbreakthrough (min). According to the definition of τ, the bed saturation capacity (qYN, mmol·g−1) can be calculated using eq 16.44 The Yan model45,46 is a modified dose−response model for the description of breakthrough curves. Its nonlinear form is presented as

t

=

∫0 0.5 (Cin − Cout)dt C ints t 0.5



∫0 (Cin − Cout)dt C int0.5

= pcrem(t 0.5)

(20)

(19) I

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Journal of Chemical & Engineering Data Cout =1− C in

Article

1 ⎛ Cinft ⎞aY 1 + ⎜q W ⎟ ⎝Y ⎠

waters. Further studies will focus on desorption under supercritical conditions and validation with real rose hydrolate.



(21)

where qY is the bed saturation capacity (mmol·g ) and aY is a constant. Clark model47,48 is based on generalized logistic function in combination with Freundlich isotherm equation: ⎛ ⎞1/(n − 1) Cout 1 =⎜ ⎟ C in ⎝ 1 + A C exp( −rCt ) ⎠

ASSOCIATED CONTENT

S Supporting Information *

−1

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jced.6b00205. Calculation of thermodynamic parameters (eqs S1−S3), thermodynamic parameters (Table S1), and plots of ln Kd vs T−1 (Figure S1) for PEA adsorption onto GAC (PDF)

(22)



where AC and rC (min−1) are constants. Parameter n is the constant of Freundlich isotherm equation (eq 12). The three models above were employed to fit breakthrough data of PEA. Fitting parameters are listed in Table 9. The comparison of fitting with three models was presented in Figure 9, taking Run 4 (Table 3) as an example. As it turned out, the Yoon-Nelson model best described the breakthrough behavior of PEA on GAC bed. The Adj. R2 of fitting were more close to unity (0.9743−0.9984), and the ARD values was relatively low (4.86−23.8%). In contrast, the breakthrough curves calculated by Yan model exhibited significant deviations (ARD 31.8− 156%) from experimental data. The Clark model also exhibited certain deviations (ARD 15.9−44.4%) from experimental values. These indicated that Yan and Clark models were not suitable for description of PEA breakthrough on GAC bed. The values of Yoon-Nelson parameters, i.e., half-breakthrough time τ and bed saturation capacity qYN, were close to experimental values of t0.5 and qe, respectively (Tables 9 and 7). These confirmed the suitability of Yoon-Nelson model. The rate constant kYN ranged from (0.9862 to 2.448) × 10−2 min−1 under experimental conditions. It was also noted that, with the flow rate increasing from (6.5 to 13.6) × 10−3 kg·min−1, kYN increased from (1.277 to 2.448) × 10−2 min−1 (Tables 3 and 9). This explained the result that the breakthrough and saturation occurred faster at a higher flow rate (Figure 6). In addition, with the inlet concentration increasing from (2.203 to 4.261) mmol·kg−1, kYN increased from (0.9862 to 1.715) × 10−2 min−1 (Tables 3 and 9). This explained the result that the breakthrough curves became steeper with a higher inlet concentration (Figure 8).

AUTHOR INFORMATION

Corresponding Author

*E-mail (A. Zhang): [email protected] Funding

This work was supported by the Foundation of Fuli Institute of Food Science, Zhejiang University (KY201406). Notes

The authors declare no competing financial interest.



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4. CONCLUSIONS For adsorptive recovery of water-soluble fraction of rose oil components from the hydrolate byproduct using GAC, fundamental data are needed. Since PEA is the predominant component of rose hydrolate volatiles, this study focused on this compound. Comparative studies were performed toward kinetics and equilibrium of PEA adsorption onto three types of GAC. The activated carbon CAL proved to be superior to F400D and 207CX in terms of physical properties as well as adsorption capacity and rate toward PEA. Dynamic adsorption toward PEA was investigated using the optimal carbon CAL. The breakthrough curves can be influenced by flow rate, GAC mass, and inlet concentration. The maximum bed saturation capacity toward PEA was 2.471 mmol·g−1 under optimal conditions (GAC mass 10.01 g, inlet concentration 4.391 mmol·kg−1, flow rate 6.5 × 10−3 kg·min−1, 298 K). The YoonNelson model best described the breakthrough data of PEA on GAC bed, whereas Yan and Clark models gave a relatively poor fit. This work is part of our efforts for recovering water-soluble essential oil components from hydrolates or distillation waste J

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