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Optimizing experimental binary adsorption of aniline–nitrobenzene onto granular activated carbon packed bed by Taguchi’s methodology
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Optimizing experimental binary adsorption of aniline–nitrobenzene onto granular activated carbon packed bed by Taguchi’s methodology Md Oayes Middaa,b, Vimal Chandra Srivastavaa,*, Jai Prakash Kushwahac a
Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India Department of Chemical Engineering, Malaviya National Institute of Technology, Jaipur 302017, Rajasthan, India c Department of Chemical Engineering, Thapar Institute of Engineering and Technology, Patiala 147004, Punjab, India b
ARTICLE INFO
ABSTRACT
Keywords: Column adsorption Synergistic effect Aniline Nitrobenzene Competitive adsorption
Herein a new statistical approach based on Taguchi’s methodology was developed for optimizing continuous simultaneous adsorption of aniline (AN) and nitrobenzene (NB) from their binary aqueous solution in a column packed with granular activated carbon (GAC). Effects of column design parameters such as feed flow rate (Q), bed height (Z) and bed diameter (D) were studied for the breakthrough curve performance using Taguchi’s L9 orthogonal array design. The parameters were optimized at three levels with the higher-is-better type response characteristics. Further, the Thomas model was used to predict column breakthrough curve and breakthrough time. Higher sorption affinity of NB over AN towards GAC surface implied favorable attachment of NB molecules. Quicker breakthrough attainment was observed at higher Q, lower Z and lower D owing to faster saturation of sorption sites. Maximum individual equilibrium adsorption uptake for AN and NB was found to be 0.29 mg/g and 3.91 mg/g, respectively, at Q = 0.02 L/min, Z = 60 cm and D = 2.54 cm. The average total equilibrium adsorption uptake (qtot) from the experimental runs was found to be 4.2 mg/g which is closer to the predicted qtot value of 4.17 mg/g.
1. Introduction Wastewater released from an industry consist of a number of organic and inorganic pollutants. These pollutants have some environmental effects in one or other ways. Therefore, abatement of these pollutants from wastewater is essential before being released into the water bodies. Various physical and chemical techniques can be used for controlling the concentrations of these pollutants within allowable limits set by government bodies [1–3]. Adsorption process is one of the techniques for wastewater treatment. This process has been used for water and wastewater treatment for long times, and still used in industrial wastewater treatment. Among the adsorption processes, continuous adsorption columns are widely used for wastewater treatment to control pollutant concentration levels [4–6]. Various kinds of adsorbents are used to serve this purpose. Among the adsorbents, granular activated carbon (GAC) is mostly used because of its’ high adsorption affinity towards almost all the pollutants [7–11]. Other popular adsorbents are rice husk ash [12–14], bagasse fly-ash [4,10], silica-based mesoporous materials [15–17], carbon nanotubes [11,18,19], jute fibers [2,20], and egg-shells [21]. Adsorption affinity of GAC is different for individual pollutants because of its surface functional group
⁎
properties and chemical nature of pollutants. Formation of weak and strong bonding (e.g. H-bonding, etc.) between the functional groups present on GAC surface and pollutants chemical nature controls the surface affinity. Nature of adsorption sites may also be responsible for unequal affinity towards individual pollutants. Non-conventional adsorbents, such as algae, has also been reported for heavy metals removal in a fluidized biosorption column with maximum removal efficiency of 89 % and 70 % for lead and arsenic, respectively [22]. Numerous research papers have been reported on single and multicomponent adsorption onto various adsorbents. Both batch and continuous studies have been reported to have knowledge of adsorption isotherms, properties, and parameters. Adsorption parameters such as maximum equilibrium uptake and affinity constants are reported for various pollutants and adsorbents. These parametric information and adsorption isotherms are very essential for design aspects. The present work investigates the continuous simultaneous adsorption of aniline (AN) and nitrobenzene (NB) (Fig. 1) from their binary synthetic aqueous solution in packed column packed with granular activated carbon (GAC). This is an extension of our recently published previous work which was on simultaneous batch adsorption study of AN and NB using GAC [9]. Petrochemicals, dyes and dyeing,
Corresponding author. E-mail addresses: [email protected] (M.O. Midda), [email protected], [email protected] (V.C. Srivastava), [email protected] (J.P. Kushwaha).
https://doi.org/10.1016/j.jwpe.2019.101045 Received 19 July 2019; Received in revised form 27 October 2019; Accepted 3 November 2019 2214-7144/ © 2019 Published by Elsevier Ltd.
Please cite this article as: Md Oayes Midda, Vimal Chandra Srivastava and Jai Prakash Kushwaha, Journal of Water Process Engineering, https://doi.org/10.1016/j.jwpe.2019.101045
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Nomenclature
qtot Sij t tb td Ur Vc Vb Ac Z D Nb ρBD,ads
Notations and Abbreviations C C0 C0,j EBCT Kij mc N Q q0,j qi
concentration of solute at time t[min] initial concentration of adsorbate in solution[mg/L] initial concentration of each component in solution[mg/L] empty bed contact time[min] sorption rate constant of column[L/(min-mg)] mass of adsorbent in the column[g] number of adsorbates[–] feed flowrate[L/min] the maximum solid-phase concentration of component j [mg/g] equilibrium adsorption uptake of each component in
pharmaceutical and explosive manufacturing industries are the sources of generation of AN and NB [9,23,24]. NB and AN has been reported to be carcinogenic, and if inhaled, convert hemoglobin into methemoglobin preventing oxygen uptake in the body [25]. The effect of these compounds on living species with environmental impact has been studied in detail by Wang et al. [26]. In this manuscript, we first present a new statistical approach for continuous simultaneous adsorption. Effect of column design parameters such as feed flow rate (Q), bed height (Z) and bed diameter (D) were studied for the breakthrough curve performance using Taguchi’s L9 orthogonal array design. The parameters (Q, Z, and D) were optimized at three levels with the higher-is-better type response characteristics by means of only 9 sets of experiments. Further, an empirical model based on the well-known Thomas model was proposed to predict column breakthrough curve and breakthrough time.
binary mixture[mg/g] total adsorption uptake[mg/g] competitive adsorption coefficient [–] time[min] breakthrough time[min] delayed time between the two breakthrough curves[min] adsorbent usage rate[g/L] GAC volume in the column[L] breakthrough volume[L] Column cross-sectional area[cm2] bed heightcm column diametercm number of reactor volume treated at breakthrough[L] bulk density of the GAC[kg/L]
20 L of distilled water. The solution mixture was stirred by means of mechanical stirrer at 1000 rpm for 30 min to form a fresh homogeneous synthetic solution, whenever required. Virgin and ANeNB loaded GAC was analyzed for its characteristics. The functional groups present on particle surface was identified by FTIR analysis (Thermo Nicolet, Model Magna 760). X-ray diffraction (XRD) analysis was performed using a Phillips diffraction unit (Model PW1140/90, Holland). FAC was also analyzed by ASAP 2010 Micromeritics instrument for the BET surface area and pore volume. Thermal analysis was conducted by a TG-DTA thermal analyzer (SII 6300 EXSTAR) in the oxidizing atmosphere (zero air) with a dynamic heating rate of 10 °C/min. 2.2. Experimental set-up Continuous adsorption of AN and NB were carried out in plexiglass columns of different diameters (D: 2, 2.54, and 4 cm), bed height (Z: 30, 45, and 60 cm) and feed flowrate (Q: 0.02, 0.04, and 0.06 L/min). All the experiments were conducted at room temperature (∼ 30 °C) and the AN and NB binary solution pH was maintained at ≈ 6.8 using buffer solution [9]. Fig. S1 represents a pictorial diagram of the adsorption column filled with GAC particles of size 1.5 mm. Binary solution of AN and NB was fed from the bottom of the column, and the samples were collected at 30, 45 and 60 cm height from the bottom. In order to distribute feed solution uniformly across the bed cross-section, glass beads (0.3-0.5 cm diameter) of approximately 5 cm height was filled just above the feed port of the column. A peristaltic pump (Miclins PP20) was used to maintain a constant feed flow rate. During the experiments, the treated samples were collected at various pre-decided sampling ports of the column at different time (t) interval. Further, the collected samples were analyzed by double beam UV/VIS spectrophotometer (model UV 210 A, Shimadzu, Kyoto, Japan) to determine the residual concentration of AN and NB. For this purpose, Eq.s 1 and 2, generated from the calibration of AN and NB, were applied to determine the unknown concentration of AN and NB in the binary solution [9].
2. Materials and methods 2.1. Materials and characterization Aniline (AN) and nitrobenzene (NB) of analytical grade were procured from S.D. fine chemicals Pvt. Ltd., Mumbai, India. Granular activated carbon (GAC) was provided by ZeoTech Adsorbents Pvt. Ltd., New Delhi, India. The GAC was further processed and screened to an average particle size of 1.5 mm. Column adsorption studies for AN and NB were carried from their synthetic binary solution. Binary synthetic solution of AN and NB of 1000 mg/L each was prepared by mixing their appropriate amounts in
CAN = 13.854A233
(1)
9.386A268 + 2.0792
Table 1 Process parameters with levels using Taguchi’s orthogonal arrays. Factors
A: Flow Rate (Q, L/min) B: Bed Height (Z, cm) C: Bed Diameter (D, cm)
Fig. 1. Chemical Structure of nitrobenzene and aniline. 2
Levels 1
2
3
0.02 30 2
0.04 45 2.54
0.06 60 4
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CNB =
2.099A233 + 35.4594A268
(2)
12.4272
to the release of surface-bound moisture. During the heating up to 400 °C, no phase change occurred which was confirmed by the unavailability of endothermic peak [27]. The decrease in mass loss rate was found to be 31 wt.% (within 450–640 °C) for blank GAC, 40 wt.% (within 450–650 °C) for AN-GAC, 49 wt.% (within 450–610 °C) for NBGAC, and 54 wt.% (within 450–656 °C) for (AN + NB)-GAC. The blank, AN-loaded, NB-loaded and (AN + NB)-loaded GAC get oxidized in the temperature range of 450−660 °C with gradual weight loss. A strong exothermic peak between 450−700 °C exposed the oxidative degradation followed by the carbon combustion. All the samples showed a gradual weight loss up to 1000 °C due to the evolution of CO2, CO and traces amount of NOx. The main variation in the thermal degradation behavior of blank, AN-loaded, NB-loaded and (AN + NB)-loaded GAC are: (i) quantity of mass loss in the second degradation region was found to be in the order of GAC (31 wt.%) followed by AN-GAC (∼40 wt.%), NB-GAC (49 wt. %), and (AN + NB)-GAC (54 wt.%); (ii) mass loss rate was found to be lowest for GAC (0.41 mg/min at ∼590 °C) followed by (AN + NB)-GAC (0.69 mg/min at ∼606 °C), AN-GAC (0.72 mg/min at ∼614 °C) and NB- GAC (0.76 mg/min at ∼592 °C); and (iii) finally, the ash remained after third mass degradation zone in GAC, AN-GAC, NB-GAC and (AN + NB)-GAC was found to be 65.6 %, 48.2 %, 36 %, and 38.5 %, respectively.
where, A233 and A268: Absorbances at λmax 233 and 268, respectively; CAN and CNB: Initial concentrations of AN and NB in the binary solution, respectively. 2.3. Experimental design using Taguchi’s methodology Taguchi’s optimization methodology has already been described in our previous work for batch adsorption [4,10,14]. For the optimization of various parameters in binary adsorption of AN and NB, Taguchi’s L9 (34) orthogonal array (OA) matrix was used. Three process parameters: Q, Z, and D have been considered for optimization of the simultaneous adsorption of AN and NB in continuous column adsorption. These process parameters along with their descriptions/levels are described in Table 1. Taguchi’s L9 (34) OA matrix includes three parameters each having three levels (1, 2, 3), with total degrees of freedom (DOF) being 6 [3 × (3-1)]. Column adsorption experiments and hence optimization were performed for simultaneous removal of AN and NB by GAC using the selected 9 experimental trials (as per the design matrix) with three process parameters at three levels (Table 2). Eq. (3) was used to calculate the AN/NB removal and further the total adsorption capacity of GAC at equilibrium (qtot, mg/g). 2 N =1
QC0
tb
(1
Ct / C0 ) dt
0
qtot =
D2Z 4
3.2. Column performance and parameter optimization
N
(3)
BD, ads
The column adsorption performance has been studied for the removal of AN and NB from synthetic wastewater by varying values of three parameters: Q, D, and Z. The column performance is generally represented by concentration (C/C0) vs time (t) curve, also known as breakthrough curve. Experimental plan for this binary adsorption was decided as per the design of experiment (DOE) procedure based on Taguchi’s optimization method (Table 2).
where, C0,i is the initial adsorbate concentration (mg/L), Ct is the residual adsorbate concentration at time t (mg/L), tb is the breakthrough time (min), Q is the flow rate (L/min), D is the diameter of the column (cm) and Z is the bed height (cm), ρBD,ads is the bulk density of the GAC, and N is the number of adsorbates. 3. Results and discussion
3.2.1. Effect of process parameters using Taguchi’s optimization method Total nine runs were performed as suggested by Taguchi’s L9 orthogonal array (OA) matrix (Table 2), and the binary adsorption column performance represented by breakthrough curves are presented in Fig. 2. EBCT is an important parameter in the design of adsorption column. It affects the shape of the breakthrough curve and breakthrough volume (Vb). EBCT is defined as the ratio of the volume of GAC in the column (VC) to the feed flow rate (Q) [28,29]. It is determined by Eq. (4).
3.1. Characterization The detailed characterization of GAC has been published elsewhere [9]. Only the key characteristics are presented here. The bulk density and BET surface area were found to be 661.8 kg/m3 and 183.5 m2/g, respectively. The XRD (Fig. S2) confirmed the occurrence of Akdalaite, Fersilicate, Moganite and Tamarugite [(Al2O3)4·H2O; FeSi; SiO2 and NaAl(SO4)2·6H2O], respectively. The qualitative chemical surface properties were measured by FTIR analysis. The major functional groups present on the GAC surface were carboxyl (OeC = O), hydroxyl (−OH), carbonyl (-C = O) and silanol (Si−OH) groups. The thermal analysis such as TG, DTA, and DTG of the virgin GAC, AN-loaded, NB-loaded and (AN + NB)-loaded GAC are shown in Fig. S3. The TG curves indicate that the moisture and the higher volatile compounds evolution take place (3–15 % mass loss) from 25 to 450 °C. Drying or weight loss at higher temperature (100–450 °C) may be due
EBCT =
1 2 3 4 5 6 7 8 9
Run Order
Ur =
9 4 7 8 2 1 3 5 6
B: Z (cm)
C: D (cm)
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
30 45 60 30 45 60 30 45 60
2 2.54 4 2.54 4 2 4 2 2.54
V mC = C = Vb VC Nb Nb
(5)
Table 3 shows the values of EBCT, tb, Vb, Ur, and Nb (number of reactor volume treated at breakthrough), and individual and total adsorbate uptake, qi and qtot, respectively, are shown in Table 4. These performance parameters were calculated at the breakthrough point from breakthrough curves (Fig. 2) considering the breakthrough point at C/C0 = 0.1. These experimental data show a decreasing trend of Ur in general with an increase in EBCT. The column performance as represented in Fig. 2 (a–i), implies that the breakthrough achieved earlier for higher Q, lower D, and higher Z value. The increase in the mass transfer rate at higher Q value increases the adsorbed amount of AN and NB per unit height of bed within mass transfer zone, and hence, an increase in Q leading to faster saturation. The effect of column performance is better explained by equilibrium
Factors A: Q (L/min)
(4)
Adsorbent usage rate (Ur) is defined as the saturated/exhausted adsorbent mass behind one liter of treated wastewater. The fixed-bed adsorption column performance can also be assessed for adsorbent usage rate (Ur) (Eq. 5).
Table 2 Column assignment for three factors in the Taguchi’s L9 orthogonal array. S. No.
VC A Z = C Q Q
3
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Fig. 2. Experimental and predicted breakthrough curves for AN-NB binary system as per Taguchi’s method. Table 3 Experimental column adsorption data for AN-NB binary system. S. No.
1 2 3 4 5 6 7 8 9
Co (mg/L) AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
Q (L/min)
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
D (cm)
2 2.54 4 2 2.54 4 2 2.54 4
Z (cm)
30 45 60 60 30 45 45 60 30
EBCT (min)
Aniline
4.71 11.39 37.68 4.71 3.79 14.13 2.35 5.06 6.28
Nitrobenzene
Tb (min)
Vb (L)
Nb
Ur
Tb (min)
Vb (lit)
Nb
Ur
40.05 170.21 917.49 43.44 27.92 556.14 8.55 44.09 70.42
0.8010 3.4043 18.35 1.7377 1.1169 22.24 0.5131 2.6459 4.2255
8.50 14.93 24.34 9.22 7.35 39.36 3.63 8.70 11.21
77.82 44.30 27.17 71.75 90.02 16.81 182.23 76.00 59.01
214.32 754.07 3475.19 238.75 170.42 1225.53 75.71 180.97 426.68
4.28 15.08 69.50 9.55 6.81 49.02 4.54 10.85 25.60
45.50 66.17 92.23 50.69 44.86 86.73 32.14 35.73 67.94
14.54 10.00 7.17 13.05 14.75 7.63 20.58 18.52 9.74
Table 4 Column equilibrium adsorption uptake (qtot) for the binary system. S. No.
1 2 3 4 5 6 7 8 9
Co (mg/L)
Q (L/min)
AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
D (cm)
2 2.54 4 2 2.54 4 2 2.54 4
Z (cm)
30 45 60 60 30 45 45 60 30
EBCT (min)
4.71 11.39 37.68 4.71 3.79 14.13 2.35 5.06 6.28
adsorption uptake of AN and NB, which is further correlated with saturation of sorption sites. Higher qi (individual equilibrium adsorption uptake) values are obtained for larger D and Z values as can be observed
qi
qtot (mg/g)
qAN (mg/g)
qNB (mg/g)
0.309 0.3566 0.2041 0.3228 0.2848 1.407 0.2166 0.1730 0.3374
1.992 3.390 3.228 1.963 2.222 2.504 1.942 1.930 2.160
2.301 3.746 3.433 2.286 2.507 3.911 2.158 2.103 2.497
in Tables 4 and 5. Higher D and Z values increase the number of binding sites or sorption sites due to the fact that the higher amount of adsorbent (GAC) increases the adsorption surface area. Sharper 4
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Table 5 Average and main effects of qtot values: raw data and S/N data. Raw Data Raw Data, Average Value
Main Effects
Parameter
L1
L2
L3
L2-L1
L3-L2
A: Q B: Z C: D
3.16 2.25 2.44
2.90 2.79 3.27
2.25 3.28 2.61
−0.26 0.54 0.84
−0.65 0.50 −0.66
S/N Data S/N Data, Average Value
Main Effects
Parameter
L1
L2
L3
L2-L1
L3-L2
A: Q B: Z C: D
9.81 7.03 7.72
9.00 8.64 10.00
7.03 10.17 8.12
−0.80 1.60 2.28
−1.97 1.53 −1.88
Fig. 3. Percent contribution of various factors towards column performance.
Table 6 ANOVA of qtot and S/N data. Raw Data Parameter
Sum of squares
DOF
Mean square
% Contribution
F-value
A B C Residual Model Cor. Total
31.11 33.32 33.99 0.03 98.41 98.45
2 2 2 2 6 8
9.99 10.76 10.70 0.02 31.45 31.47
31.89 38.88 28.48 0.75 99.25 100.00
42.34 51.63 37.82
Parameter
Sum of squares
DOF
Mean square
% Contribution
F-value
A B C Residual Model Cor. Total
298.76 318.28 316.55 0.29 933.59 933.89
2 2 2 2 6 8
96.19 103.41 99.99 0.15 299.59 299.74
33.90 40.76 24.53 0.81 99.19 100.00
41.69 50.13 30.17
131.79
S/N Data
Fig. 4. Effect of process parameters on qAN, qNB and qtot for binary adsorption of AN and NB in GAC packed-bed.
121.99
The effect of adsorption parameters on individual (qAN and qNB), average value of qtot and S/N (signal-to-noise) ratio for the binary system are given in Figs. 4 and 5. An increase in the levels of factors from 1 to 2 and from 2 to 3 for Q resulted in a decrease in the qNB value, however, the qAN value increased from 1 to 2 and then decreased from 2 to 3 levels. Uptake of lesser attractive molecules (AN) increased initially from level 1 to level 2 due to molecule hindrance, and thereafter from level 2 to level 3, it started decreasing owing to competition between AN and NB molecules. The overall qtot value for the binary system decreased with an increase in Q value. It was also observed that an increase in Z leads to an increase in qtot value. Further increase in D from L1 to L2, and L2 to L3, increased and decreased the qtot values, respectively. This may be due to the effect of packing efficiency. The packing efficiency is lower for a larger diameter column owing to the compaction effect of the weight of the packing material (GAC). The compaction effect reduces bed porosity leading to lower efficiency of the column. The analysis of variance (ANOVA) results for raw and signal-to-noise (S/N) data are given in Table 6. Therefore, after examining the response curves (Fig. 5), the optimal level of various parameters obtained for AN–NB binary system indicated that 1st level of parameter A, 3rd level of parameter B and 2nd level of parameter C provided the highest average value of qtot. It revealed that the average qtot value should be highest for Q (flow rate) = 0.02 L/min, Z (bed height) = 60 cm and D (diameter) = 2.54 cm. To verify the optimal levels of parameters, three confirmation experimental runs were conducted at selected optimal level. The average qtot from the experimental runs was found to be
breakthrough curves were observed for AN than NB, which is the effect of competitive adsorption. This can be further explained as the affinity of active sorption sites present on the GAC surface towards a selective component, and NB is the selective component in this case. Thus, NB molecules outsmart AN molecules in competition for a vacant site leading to sharper breakthrough curves for AN. It can also be concluded that the bed is better packed for thinner column diameter and helps in easier control of flow distribution. 3.2.2. Parameter optimization for binary column adsorption The effect of individual parameters (Q, Z, and D) on total equilibrium adsorption uptake (qtot) for the simultaneous removal of adsorbates from a binary system of AN & NB was studied. The average values of qtot for each parameter at level 1, 2, and 3 are given in Table 5. Parameter A: Q; parameter B: Z and parameter C: D has its maximum impact effect on response qtot at level 1, level 3 and level 2, respectively. The relative influence of the effect as per DOE, in general, is expressed by the difference between level 2 and level 1 (L2 − L1) of each factor. The larger the difference, the stronger is the influence. Table 6 implies that none of the single parameter has an intervening impact for the adsorption of AN and NB from the AN–NB binary system. No single parameter shows a strong influence on qtot value also. Fig. 3 represents that the bed height has slightly higher predominance (39 %) on column performance. 5
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is the volumetric flow rate (L/min), C0,j is the initial concentration of component j, C is the concentration of solute at time t (min), td,j is the delayed time between the two breakthrough curves and Sij is the adsorption competition coefficient of one component with respect to other and Sii = Sjj = 1. This term signifies the competitive adsorption of components onto the GAC surface. Estimation of adsorption parameters was performed by data validation and are reported in Table 7. Calculated breakthrough times were comparable with the experimental values as reported in Table 8. Therefore, we may conclude that the proposed model is satisfactory in predicting multicomponent breakthrough curves of a binary system well in advance for the scale-up approach. 4. Conclusions
Fig. 5. Effect of process parameters on qtot and S/N ratio for binary adsorption of AN and NB in GAC packed-bed.
Sorption affinity of NB towards GAC was observed to be higher than AN resulting in larger breakthrough time of NB over AN. Breakthrough curves for AN were observed to be sharper than NB, which was due to competitive adsorption among NB and AN. Equilibrium individual adsorption uptake (qi) was found to be higher at larger column diameter and height. This is because of increased surface area with an increased amount of adsorbent which resulted in larger binding/sorption sites. Larger diameter column decreased the packing efficiency owing to the compaction effect of the mass of packing material, i.e., GAC. Compaction effect reduced bed porosity resulting in difficult control of flow distribution. Amongst all the parameters, column height was observed to be the most predominant factor. Optimal process parameters were found to be bed diameter (D) = 2.54 cm, bed height (Z) = 60 cm and flow rate (Q) = 0.02 L/min. At this optimal condition, the average qtot from the experimental runs was found to be 4.2 mg/g, which is closer to the predicted qtot value of 4.17 mg/g. Furthermore, column breakthrough curves were well predicted by the empirical proposed model and validated with experimental data of AN–NB binary system effectively.
4.2 mg/g which is closer to the predicted qtot value of 4.17 mg/g (Tables S1 and S2). It may also be noted that these optimal values are valid within the specified range of process parameters. 3.3. Column modeling and data validation An empirical model was proposed to predict column breakthrough curve and breakthrough time for a binary adsorption (Eq. 6). This model is a modified version of the Thomas model [28–30]. Column performance in the form of breakthrough curves can be predicted by Eq. (4). Experimental and predicted breakthrough curves are well-matched as represented in Fig. 2.
C C0
= i
N exp j=1
Sij
{
1 Kij qo, j mc Q
Kij C0, j (t + td, j )
}
(6)
where N is number of components, Kij is rate constants [L/(min.mg)] of AN and NB, q0,j is the maximum solid-phase concentration of component j (mg/g), mC is the mass of adsorbent packed in the column (g), Q
Table 7 Estimation of column adsorption parameter with a proposed model for AN-NB binary system. Exp. No.
1 2 3 4 5 6 7 8 9
Co (mg/L)
mc (g)
AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
49 144 627 98.66 96.06 470.5 74.05 192.16 313.62
Aniline
Nitrobenzene
K (L/(mg.min))
q0 (mg/L)
S
td (min)
K (L/(mg.min))
q0 (mg/L)
S
td (min)
3.23 × 10-5 1.85 × 10-5 6.9 × 10-7 2.97 × 10-5 4.07 × 10-5 9.8 × 10-5 5.98 × 10-5 3.8 × 10-5 2.35 × 10-5
39.65 38.59 37.98 42.86 29.77 61.16 27.35 29.96 37.98
0.0031 0.0074 0.0107 0.0018 0.0051 0 0.0003 0.0004 0
0 0 0 0 0 7.52 0 0 0
1.18 × 10-5 6.12 × 10-6 1.28 × 10-6 1.05 × 10-5 1.52 × 10-5 2.96 × 10-6 2.36 × 10-5 1.14 × 10-5 1.25 × 10-5
120 150 210.89 160.28 131.75 126.23 107.43 103.78 110.89
0 0 0.0137 0 0 0.0210 −0.017 0 0.0134
12.51 151.22 27.34 12.51 12.60 2.89 3.367 12.6 29.63
Table 8 Comparison between experimental and predicted breakthrough time. S. No.
1 2 3 4 5 6 7 8 9
Co (mg/L)
Q (L/min)
AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
D (cm)
2 2.54 4 2 2.54 4 2 2.54 4
Z (cm)
EBCT (min)
30 45 60 60 30 45 45 60 30
4.71 11.39 37.68 4.71 3.79 14.13 2.35 5.06 6.28
6
Aniline
Nitrobenzene
Actual Tb
predicted Tb
Actual Tb
predicted Tb
40.05 170.21 917.49 43.44 27.92 556.14 8.55 44.09 70.42
30.09 159.5 871.96 31.7 17.5 470.02 4.26 38.04 103.57
214.32 754.07 3475.19 238.75 170.42 1225.53 75.71 180.97 426.68
213.1 790.25 2800.57 303.02 248.71 1215.12 92.93 246.39 483.77
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5. Declaration of interests [13]
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
[14] [15]
Appendix A. Supplementary data
[16]
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jwpe.2019.101045.
[17]
References
[18]
[1] B. Ersoy, M.S. Çelik, Uptake of aniline and nitrobenzene from aqueous solution by organo-Zeolite, Environ. Technol. 25 (2004) 341–348. [2] Priyanka, V. Subbaramaiah, V.C. Srivastava, I.D. Mall, Catalytic oxidation of nitrobenzene by copper loaded activated carbon, Sep. Purif. Technol. 125 (2014) 284–290. [3] V. Anand, V.C. Srivastava, Photocatalytic degradation of nitrobenzene and azo dye using zinc oxide nanoparticles prepared by electrochemical method, J. Sci. Ind. Res. (India) 75 (2016) 632–637. [4] V.C. Srivastava, I.D. Mall, I.M. Mishra, Multicomponent adsorption study of metal ions onto bagasse fly ash using Taguchi’s design of experimental methodology, Ind. Eng. Chem. Res. 46 (2007) 5697–5706. [5] G.Q. Wu, X. Zhang, H. Hui, J. Yan, Q.S. Zhang, J.L. Wan, Y. Dai, Adsorptive removal of aniline from aqueous solution by oxygen plasma irradiated bamboo based activated carbon, Chem. Eng. J. 185–186 (2012) 201–210. [6] M.S. Rauthula, V.C. Srivastava, Studies on adsorption/desorption of nitrobenzene and humic acid onto/from activated carbon, Chem. Eng. J. 168 (2011) 35–43. [7] A.J. Jadhav, V.C. Srivastava, Adsorbed solution theory based modeling of binary adsorption of nitrobenzene, aniline and phenol onto granulated activated carbon, Chem. Eng. J. 229 (2013) 450–459. [8] A.J. Jadhav, V.C. Srivastava, Multicomponent adsorption isotherm modeling using thermodynamically inconsistent and consistent models, AIChE J. 65 (11) (2019) e16727. [9] M.O. Midda, V.C. Srivastava, J.P. Kushwaha, Modelling single and binary adsorptive behaviour of aniline and nitrobenzene onto granular activated carbon, Phys. Chem. Liq. (2018), https://doi.org/10.1080/00319104.2018.1553240. [10] S. Suresh, V.C. Srivastava, I.M. Mishra, Adsorptive removal of phenol from binary aqueous solution with aniline and 4-nitrophenol by granular activated carbon, Chem. Eng. J. 171 (2011) 997–1003. [11] H. Yan, X. Yang, J. Chen, C. Yin, C. Xiao, H. Chen, Synergistic removal of aniline by carbon nanotubes and the enzymes of Delftia sp. XYJ6, J. Environ. Sci. China (China) 23 (2011) 1165–1170. [12] S. Chowdhury, R. Mishra, P. Saha, P. Kushwaha, Adsorption thermodynamics,
[19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30]
7
kinetics and isosteric heat of adsorption of malachite green onto chemically modified rice husk, Desalination 265 (2011) 159–168. V.C. Srivastava, I.D. Mall, I.M. Mishra, Equilibrium modeling of ternary adsorption of metal ions onto rice husk ash, J. Chem. Eng. Data 54 (2009) 705–711. V.C. Srivastava, I.D. Mall, I.M. Mishra, Optimization of parameters for adsorption of metal ions onto rice husk ash using Taguchi’s experimental design methodology, Chem. Eng. J. 140 (2008) 136–144. P.N.E. Diagboya, E.D. Dikio, Silica-based mesoporous materials; emerging designer adsorbents for aqueous pollutants removal and water treatment, Microporous Mesoporous Mater. 266 (2018) 252–267. G. Li, B. Wang, W.Q. Xu, Y. Li, Y. Han, Q. Sun, Enhanced nitrobenzene adsorption in aqueous solution by surface-silanized fly-ash-Derived SBA-15, ACS Earth Sp. Chem. 2 (2018) 246–255. X. Yang, Q. Guan, W. Li, Effect of template in MCM-41 on the adsorption of aniline from aqueous solution, J. Environ. Manage. 92 (2011) 2939–2943. H. Al-Johani, M.A. Salam, Kinetics and thermodynamic study of aniline adsorption by multi-walled carbon nanotubes from aqueous solution, J. Colloid Interface Sci. 360 (2011) 760–767. A. Mehrizad, P. Gharbani, Study of 1-Chloro-4-Nitrobenzene adsorption on Carbon nanofibers by experimental design, Int. J. Nano Dimen. 7 (2016) 77–84. D.W. Gao, Q. Hu, H. Pan, J. Jiang, P. Wang, High-capacity adsorption of aniline using surface modification of lignocellulose-biomass jute fibers, Bioresour. Technol. 193 (2015) 507–512. P.D. Saha, S. Chowdhury, M. Mondal, K. Sinha, Biosorption of direct red 28 (Congo red) from aqueous solutions by eggshells : batch and column studies, Sep. Sci. Technol. 47 (2012) 112–123. A.H. Sulaymon, A.A. Mohammed, T.J. Al-Musawi, Column biosorption of lead, cadmium, copper, and arsenic ions onto algae, J. Bioprocess. Biotech. 3 (2013) 1–7. R.T. Upson, S.E. Burns, Sorption of nitroaromatic compounds to synthesized organoclays, J. Colloid Interface Sci. 297 (1) (2006) 70–76. A. Chatterjee, T. Ebina, T. Iwasaki, F. Mizukami, Intermolecular reactivity study to scale adsorption property of para- and meta-substituted nitrobenzene over 2:1 dioctahedral smectite, J. Chem. Phys. 18 (22) (2003) 10212–10220. M.F. Khan, P.J. Boor, B.S. Kaphalia, N.W. Alcock, G.A.S. Ansari, Hematopoietic toxicity of linoleic acid anilide: importance of aniline, Fundam. Appl. Toxicol. 25 (2) (1995) 224–232. J. Wang, G. Wang, H. Ma, M.F. Khan, Enhanced expression of cyclins and cyclindependent kinases in aniline-induced cell proliferation in rat spleen, Toxicol. Appl. Pharmacol. 250 (2011) 213–220. J.C.Y. Ng, W.H. Cheung, G. McKay, Equilibrium studies of the sorption of Cu(II) ions onto chitosan, J. Colloid Interface Sci. 255 (2002) 64–74. S. Singh, V.C. Srivastava, A. Goyal, I.D. Mall, Breakthrough modeling of furfural sorption behavior in a bagasse fly ash packed bed, Int. J. Civ. Struct. Environ. Infrastruct. Eng. Res. Dev. 25 (1) (2020) 104–113. V.C. Srivastava, B. Prasad, I.M. Mishra, I.D. Mall, M.M. Swamy, Prediction of breakthrough curves for sorptive removal of phenol by bagasse fly ash packed bed, Ind. Eng. Chem. Res. 47 (2008) 1603–1613. H.C. Thomas, Heterogeneous ion exchange in a flowing system, J. Am. Chem. Soc. 66 (1944) 1664–1666.
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Journal of Water Process Engineering journal homepage: www.elsevier.com/locate/jwpe
Optimizing experimental binary adsorption of aniline–nitrobenzene onto granular activated carbon packed bed by Taguchi’s methodology Md Oayes Middaa,b, Vimal Chandra Srivastavaa,*, Jai Prakash Kushwahac a
Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India Department of Chemical Engineering, Malaviya National Institute of Technology, Jaipur 302017, Rajasthan, India c Department of Chemical Engineering, Thapar Institute of Engineering and Technology, Patiala 147004, Punjab, India b
ARTICLE INFO
ABSTRACT
Keywords: Column adsorption Synergistic effect Aniline Nitrobenzene Competitive adsorption
Herein a new statistical approach based on Taguchi’s methodology was developed for optimizing continuous simultaneous adsorption of aniline (AN) and nitrobenzene (NB) from their binary aqueous solution in a column packed with granular activated carbon (GAC). Effects of column design parameters such as feed flow rate (Q), bed height (Z) and bed diameter (D) were studied for the breakthrough curve performance using Taguchi’s L9 orthogonal array design. The parameters were optimized at three levels with the higher-is-better type response characteristics. Further, the Thomas model was used to predict column breakthrough curve and breakthrough time. Higher sorption affinity of NB over AN towards GAC surface implied favorable attachment of NB molecules. Quicker breakthrough attainment was observed at higher Q, lower Z and lower D owing to faster saturation of sorption sites. Maximum individual equilibrium adsorption uptake for AN and NB was found to be 0.29 mg/g and 3.91 mg/g, respectively, at Q = 0.02 L/min, Z = 60 cm and D = 2.54 cm. The average total equilibrium adsorption uptake (qtot) from the experimental runs was found to be 4.2 mg/g which is closer to the predicted qtot value of 4.17 mg/g.
1. Introduction Wastewater released from an industry consist of a number of organic and inorganic pollutants. These pollutants have some environmental effects in one or other ways. Therefore, abatement of these pollutants from wastewater is essential before being released into the water bodies. Various physical and chemical techniques can be used for controlling the concentrations of these pollutants within allowable limits set by government bodies [1–3]. Adsorption process is one of the techniques for wastewater treatment. This process has been used for water and wastewater treatment for long times, and still used in industrial wastewater treatment. Among the adsorption processes, continuous adsorption columns are widely used for wastewater treatment to control pollutant concentration levels [4–6]. Various kinds of adsorbents are used to serve this purpose. Among the adsorbents, granular activated carbon (GAC) is mostly used because of its’ high adsorption affinity towards almost all the pollutants [7–11]. Other popular adsorbents are rice husk ash [12–14], bagasse fly-ash [4,10], silica-based mesoporous materials [15–17], carbon nanotubes [11,18,19], jute fibers [2,20], and egg-shells [21]. Adsorption affinity of GAC is different for individual pollutants because of its surface functional group
⁎
properties and chemical nature of pollutants. Formation of weak and strong bonding (e.g. H-bonding, etc.) between the functional groups present on GAC surface and pollutants chemical nature controls the surface affinity. Nature of adsorption sites may also be responsible for unequal affinity towards individual pollutants. Non-conventional adsorbents, such as algae, has also been reported for heavy metals removal in a fluidized biosorption column with maximum removal efficiency of 89 % and 70 % for lead and arsenic, respectively [22]. Numerous research papers have been reported on single and multicomponent adsorption onto various adsorbents. Both batch and continuous studies have been reported to have knowledge of adsorption isotherms, properties, and parameters. Adsorption parameters such as maximum equilibrium uptake and affinity constants are reported for various pollutants and adsorbents. These parametric information and adsorption isotherms are very essential for design aspects. The present work investigates the continuous simultaneous adsorption of aniline (AN) and nitrobenzene (NB) (Fig. 1) from their binary synthetic aqueous solution in packed column packed with granular activated carbon (GAC). This is an extension of our recently published previous work which was on simultaneous batch adsorption study of AN and NB using GAC [9]. Petrochemicals, dyes and dyeing,
Corresponding author. E-mail addresses: [email protected] (M.O. Midda), [email protected], [email protected] (V.C. Srivastava), [email protected] (J.P. Kushwaha).
https://doi.org/10.1016/j.jwpe.2019.101045 Received 19 July 2019; Received in revised form 27 October 2019; Accepted 3 November 2019 2214-7144/ © 2019 Published by Elsevier Ltd.
Please cite this article as: Md Oayes Midda, Vimal Chandra Srivastava and Jai Prakash Kushwaha, Journal of Water Process Engineering, https://doi.org/10.1016/j.jwpe.2019.101045
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Nomenclature
qtot Sij t tb td Ur Vc Vb Ac Z D Nb ρBD,ads
Notations and Abbreviations C C0 C0,j EBCT Kij mc N Q q0,j qi
concentration of solute at time t[min] initial concentration of adsorbate in solution[mg/L] initial concentration of each component in solution[mg/L] empty bed contact time[min] sorption rate constant of column[L/(min-mg)] mass of adsorbent in the column[g] number of adsorbates[–] feed flowrate[L/min] the maximum solid-phase concentration of component j [mg/g] equilibrium adsorption uptake of each component in
pharmaceutical and explosive manufacturing industries are the sources of generation of AN and NB [9,23,24]. NB and AN has been reported to be carcinogenic, and if inhaled, convert hemoglobin into methemoglobin preventing oxygen uptake in the body [25]. The effect of these compounds on living species with environmental impact has been studied in detail by Wang et al. [26]. In this manuscript, we first present a new statistical approach for continuous simultaneous adsorption. Effect of column design parameters such as feed flow rate (Q), bed height (Z) and bed diameter (D) were studied for the breakthrough curve performance using Taguchi’s L9 orthogonal array design. The parameters (Q, Z, and D) were optimized at three levels with the higher-is-better type response characteristics by means of only 9 sets of experiments. Further, an empirical model based on the well-known Thomas model was proposed to predict column breakthrough curve and breakthrough time.
binary mixture[mg/g] total adsorption uptake[mg/g] competitive adsorption coefficient [–] time[min] breakthrough time[min] delayed time between the two breakthrough curves[min] adsorbent usage rate[g/L] GAC volume in the column[L] breakthrough volume[L] Column cross-sectional area[cm2] bed heightcm column diametercm number of reactor volume treated at breakthrough[L] bulk density of the GAC[kg/L]
20 L of distilled water. The solution mixture was stirred by means of mechanical stirrer at 1000 rpm for 30 min to form a fresh homogeneous synthetic solution, whenever required. Virgin and ANeNB loaded GAC was analyzed for its characteristics. The functional groups present on particle surface was identified by FTIR analysis (Thermo Nicolet, Model Magna 760). X-ray diffraction (XRD) analysis was performed using a Phillips diffraction unit (Model PW1140/90, Holland). FAC was also analyzed by ASAP 2010 Micromeritics instrument for the BET surface area and pore volume. Thermal analysis was conducted by a TG-DTA thermal analyzer (SII 6300 EXSTAR) in the oxidizing atmosphere (zero air) with a dynamic heating rate of 10 °C/min. 2.2. Experimental set-up Continuous adsorption of AN and NB were carried out in plexiglass columns of different diameters (D: 2, 2.54, and 4 cm), bed height (Z: 30, 45, and 60 cm) and feed flowrate (Q: 0.02, 0.04, and 0.06 L/min). All the experiments were conducted at room temperature (∼ 30 °C) and the AN and NB binary solution pH was maintained at ≈ 6.8 using buffer solution [9]. Fig. S1 represents a pictorial diagram of the adsorption column filled with GAC particles of size 1.5 mm. Binary solution of AN and NB was fed from the bottom of the column, and the samples were collected at 30, 45 and 60 cm height from the bottom. In order to distribute feed solution uniformly across the bed cross-section, glass beads (0.3-0.5 cm diameter) of approximately 5 cm height was filled just above the feed port of the column. A peristaltic pump (Miclins PP20) was used to maintain a constant feed flow rate. During the experiments, the treated samples were collected at various pre-decided sampling ports of the column at different time (t) interval. Further, the collected samples were analyzed by double beam UV/VIS spectrophotometer (model UV 210 A, Shimadzu, Kyoto, Japan) to determine the residual concentration of AN and NB. For this purpose, Eq.s 1 and 2, generated from the calibration of AN and NB, were applied to determine the unknown concentration of AN and NB in the binary solution [9].
2. Materials and methods 2.1. Materials and characterization Aniline (AN) and nitrobenzene (NB) of analytical grade were procured from S.D. fine chemicals Pvt. Ltd., Mumbai, India. Granular activated carbon (GAC) was provided by ZeoTech Adsorbents Pvt. Ltd., New Delhi, India. The GAC was further processed and screened to an average particle size of 1.5 mm. Column adsorption studies for AN and NB were carried from their synthetic binary solution. Binary synthetic solution of AN and NB of 1000 mg/L each was prepared by mixing their appropriate amounts in
CAN = 13.854A233
(1)
9.386A268 + 2.0792
Table 1 Process parameters with levels using Taguchi’s orthogonal arrays. Factors
A: Flow Rate (Q, L/min) B: Bed Height (Z, cm) C: Bed Diameter (D, cm)
Fig. 1. Chemical Structure of nitrobenzene and aniline. 2
Levels 1
2
3
0.02 30 2
0.04 45 2.54
0.06 60 4
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CNB =
2.099A233 + 35.4594A268
(2)
12.4272
to the release of surface-bound moisture. During the heating up to 400 °C, no phase change occurred which was confirmed by the unavailability of endothermic peak [27]. The decrease in mass loss rate was found to be 31 wt.% (within 450–640 °C) for blank GAC, 40 wt.% (within 450–650 °C) for AN-GAC, 49 wt.% (within 450–610 °C) for NBGAC, and 54 wt.% (within 450–656 °C) for (AN + NB)-GAC. The blank, AN-loaded, NB-loaded and (AN + NB)-loaded GAC get oxidized in the temperature range of 450−660 °C with gradual weight loss. A strong exothermic peak between 450−700 °C exposed the oxidative degradation followed by the carbon combustion. All the samples showed a gradual weight loss up to 1000 °C due to the evolution of CO2, CO and traces amount of NOx. The main variation in the thermal degradation behavior of blank, AN-loaded, NB-loaded and (AN + NB)-loaded GAC are: (i) quantity of mass loss in the second degradation region was found to be in the order of GAC (31 wt.%) followed by AN-GAC (∼40 wt.%), NB-GAC (49 wt. %), and (AN + NB)-GAC (54 wt.%); (ii) mass loss rate was found to be lowest for GAC (0.41 mg/min at ∼590 °C) followed by (AN + NB)-GAC (0.69 mg/min at ∼606 °C), AN-GAC (0.72 mg/min at ∼614 °C) and NB- GAC (0.76 mg/min at ∼592 °C); and (iii) finally, the ash remained after third mass degradation zone in GAC, AN-GAC, NB-GAC and (AN + NB)-GAC was found to be 65.6 %, 48.2 %, 36 %, and 38.5 %, respectively.
where, A233 and A268: Absorbances at λmax 233 and 268, respectively; CAN and CNB: Initial concentrations of AN and NB in the binary solution, respectively. 2.3. Experimental design using Taguchi’s methodology Taguchi’s optimization methodology has already been described in our previous work for batch adsorption [4,10,14]. For the optimization of various parameters in binary adsorption of AN and NB, Taguchi’s L9 (34) orthogonal array (OA) matrix was used. Three process parameters: Q, Z, and D have been considered for optimization of the simultaneous adsorption of AN and NB in continuous column adsorption. These process parameters along with their descriptions/levels are described in Table 1. Taguchi’s L9 (34) OA matrix includes three parameters each having three levels (1, 2, 3), with total degrees of freedom (DOF) being 6 [3 × (3-1)]. Column adsorption experiments and hence optimization were performed for simultaneous removal of AN and NB by GAC using the selected 9 experimental trials (as per the design matrix) with three process parameters at three levels (Table 2). Eq. (3) was used to calculate the AN/NB removal and further the total adsorption capacity of GAC at equilibrium (qtot, mg/g). 2 N =1
QC0
tb
(1
Ct / C0 ) dt
0
qtot =
D2Z 4
3.2. Column performance and parameter optimization
N
(3)
BD, ads
The column adsorption performance has been studied for the removal of AN and NB from synthetic wastewater by varying values of three parameters: Q, D, and Z. The column performance is generally represented by concentration (C/C0) vs time (t) curve, also known as breakthrough curve. Experimental plan for this binary adsorption was decided as per the design of experiment (DOE) procedure based on Taguchi’s optimization method (Table 2).
where, C0,i is the initial adsorbate concentration (mg/L), Ct is the residual adsorbate concentration at time t (mg/L), tb is the breakthrough time (min), Q is the flow rate (L/min), D is the diameter of the column (cm) and Z is the bed height (cm), ρBD,ads is the bulk density of the GAC, and N is the number of adsorbates. 3. Results and discussion
3.2.1. Effect of process parameters using Taguchi’s optimization method Total nine runs were performed as suggested by Taguchi’s L9 orthogonal array (OA) matrix (Table 2), and the binary adsorption column performance represented by breakthrough curves are presented in Fig. 2. EBCT is an important parameter in the design of adsorption column. It affects the shape of the breakthrough curve and breakthrough volume (Vb). EBCT is defined as the ratio of the volume of GAC in the column (VC) to the feed flow rate (Q) [28,29]. It is determined by Eq. (4).
3.1. Characterization The detailed characterization of GAC has been published elsewhere [9]. Only the key characteristics are presented here. The bulk density and BET surface area were found to be 661.8 kg/m3 and 183.5 m2/g, respectively. The XRD (Fig. S2) confirmed the occurrence of Akdalaite, Fersilicate, Moganite and Tamarugite [(Al2O3)4·H2O; FeSi; SiO2 and NaAl(SO4)2·6H2O], respectively. The qualitative chemical surface properties were measured by FTIR analysis. The major functional groups present on the GAC surface were carboxyl (OeC = O), hydroxyl (−OH), carbonyl (-C = O) and silanol (Si−OH) groups. The thermal analysis such as TG, DTA, and DTG of the virgin GAC, AN-loaded, NB-loaded and (AN + NB)-loaded GAC are shown in Fig. S3. The TG curves indicate that the moisture and the higher volatile compounds evolution take place (3–15 % mass loss) from 25 to 450 °C. Drying or weight loss at higher temperature (100–450 °C) may be due
EBCT =
1 2 3 4 5 6 7 8 9
Run Order
Ur =
9 4 7 8 2 1 3 5 6
B: Z (cm)
C: D (cm)
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
30 45 60 30 45 60 30 45 60
2 2.54 4 2.54 4 2 4 2 2.54
V mC = C = Vb VC Nb Nb
(5)
Table 3 shows the values of EBCT, tb, Vb, Ur, and Nb (number of reactor volume treated at breakthrough), and individual and total adsorbate uptake, qi and qtot, respectively, are shown in Table 4. These performance parameters were calculated at the breakthrough point from breakthrough curves (Fig. 2) considering the breakthrough point at C/C0 = 0.1. These experimental data show a decreasing trend of Ur in general with an increase in EBCT. The column performance as represented in Fig. 2 (a–i), implies that the breakthrough achieved earlier for higher Q, lower D, and higher Z value. The increase in the mass transfer rate at higher Q value increases the adsorbed amount of AN and NB per unit height of bed within mass transfer zone, and hence, an increase in Q leading to faster saturation. The effect of column performance is better explained by equilibrium
Factors A: Q (L/min)
(4)
Adsorbent usage rate (Ur) is defined as the saturated/exhausted adsorbent mass behind one liter of treated wastewater. The fixed-bed adsorption column performance can also be assessed for adsorbent usage rate (Ur) (Eq. 5).
Table 2 Column assignment for three factors in the Taguchi’s L9 orthogonal array. S. No.
VC A Z = C Q Q
3
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Fig. 2. Experimental and predicted breakthrough curves for AN-NB binary system as per Taguchi’s method. Table 3 Experimental column adsorption data for AN-NB binary system. S. No.
1 2 3 4 5 6 7 8 9
Co (mg/L) AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
Q (L/min)
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
D (cm)
2 2.54 4 2 2.54 4 2 2.54 4
Z (cm)
30 45 60 60 30 45 45 60 30
EBCT (min)
Aniline
4.71 11.39 37.68 4.71 3.79 14.13 2.35 5.06 6.28
Nitrobenzene
Tb (min)
Vb (L)
Nb
Ur
Tb (min)
Vb (lit)
Nb
Ur
40.05 170.21 917.49 43.44 27.92 556.14 8.55 44.09 70.42
0.8010 3.4043 18.35 1.7377 1.1169 22.24 0.5131 2.6459 4.2255
8.50 14.93 24.34 9.22 7.35 39.36 3.63 8.70 11.21
77.82 44.30 27.17 71.75 90.02 16.81 182.23 76.00 59.01
214.32 754.07 3475.19 238.75 170.42 1225.53 75.71 180.97 426.68
4.28 15.08 69.50 9.55 6.81 49.02 4.54 10.85 25.60
45.50 66.17 92.23 50.69 44.86 86.73 32.14 35.73 67.94
14.54 10.00 7.17 13.05 14.75 7.63 20.58 18.52 9.74
Table 4 Column equilibrium adsorption uptake (qtot) for the binary system. S. No.
1 2 3 4 5 6 7 8 9
Co (mg/L)
Q (L/min)
AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
D (cm)
2 2.54 4 2 2.54 4 2 2.54 4
Z (cm)
30 45 60 60 30 45 45 60 30
EBCT (min)
4.71 11.39 37.68 4.71 3.79 14.13 2.35 5.06 6.28
adsorption uptake of AN and NB, which is further correlated with saturation of sorption sites. Higher qi (individual equilibrium adsorption uptake) values are obtained for larger D and Z values as can be observed
qi
qtot (mg/g)
qAN (mg/g)
qNB (mg/g)
0.309 0.3566 0.2041 0.3228 0.2848 1.407 0.2166 0.1730 0.3374
1.992 3.390 3.228 1.963 2.222 2.504 1.942 1.930 2.160
2.301 3.746 3.433 2.286 2.507 3.911 2.158 2.103 2.497
in Tables 4 and 5. Higher D and Z values increase the number of binding sites or sorption sites due to the fact that the higher amount of adsorbent (GAC) increases the adsorption surface area. Sharper 4
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Table 5 Average and main effects of qtot values: raw data and S/N data. Raw Data Raw Data, Average Value
Main Effects
Parameter
L1
L2
L3
L2-L1
L3-L2
A: Q B: Z C: D
3.16 2.25 2.44
2.90 2.79 3.27
2.25 3.28 2.61
−0.26 0.54 0.84
−0.65 0.50 −0.66
S/N Data S/N Data, Average Value
Main Effects
Parameter
L1
L2
L3
L2-L1
L3-L2
A: Q B: Z C: D
9.81 7.03 7.72
9.00 8.64 10.00
7.03 10.17 8.12
−0.80 1.60 2.28
−1.97 1.53 −1.88
Fig. 3. Percent contribution of various factors towards column performance.
Table 6 ANOVA of qtot and S/N data. Raw Data Parameter
Sum of squares
DOF
Mean square
% Contribution
F-value
A B C Residual Model Cor. Total
31.11 33.32 33.99 0.03 98.41 98.45
2 2 2 2 6 8
9.99 10.76 10.70 0.02 31.45 31.47
31.89 38.88 28.48 0.75 99.25 100.00
42.34 51.63 37.82
Parameter
Sum of squares
DOF
Mean square
% Contribution
F-value
A B C Residual Model Cor. Total
298.76 318.28 316.55 0.29 933.59 933.89
2 2 2 2 6 8
96.19 103.41 99.99 0.15 299.59 299.74
33.90 40.76 24.53 0.81 99.19 100.00
41.69 50.13 30.17
131.79
S/N Data
Fig. 4. Effect of process parameters on qAN, qNB and qtot for binary adsorption of AN and NB in GAC packed-bed.
121.99
The effect of adsorption parameters on individual (qAN and qNB), average value of qtot and S/N (signal-to-noise) ratio for the binary system are given in Figs. 4 and 5. An increase in the levels of factors from 1 to 2 and from 2 to 3 for Q resulted in a decrease in the qNB value, however, the qAN value increased from 1 to 2 and then decreased from 2 to 3 levels. Uptake of lesser attractive molecules (AN) increased initially from level 1 to level 2 due to molecule hindrance, and thereafter from level 2 to level 3, it started decreasing owing to competition between AN and NB molecules. The overall qtot value for the binary system decreased with an increase in Q value. It was also observed that an increase in Z leads to an increase in qtot value. Further increase in D from L1 to L2, and L2 to L3, increased and decreased the qtot values, respectively. This may be due to the effect of packing efficiency. The packing efficiency is lower for a larger diameter column owing to the compaction effect of the weight of the packing material (GAC). The compaction effect reduces bed porosity leading to lower efficiency of the column. The analysis of variance (ANOVA) results for raw and signal-to-noise (S/N) data are given in Table 6. Therefore, after examining the response curves (Fig. 5), the optimal level of various parameters obtained for AN–NB binary system indicated that 1st level of parameter A, 3rd level of parameter B and 2nd level of parameter C provided the highest average value of qtot. It revealed that the average qtot value should be highest for Q (flow rate) = 0.02 L/min, Z (bed height) = 60 cm and D (diameter) = 2.54 cm. To verify the optimal levels of parameters, three confirmation experimental runs were conducted at selected optimal level. The average qtot from the experimental runs was found to be
breakthrough curves were observed for AN than NB, which is the effect of competitive adsorption. This can be further explained as the affinity of active sorption sites present on the GAC surface towards a selective component, and NB is the selective component in this case. Thus, NB molecules outsmart AN molecules in competition for a vacant site leading to sharper breakthrough curves for AN. It can also be concluded that the bed is better packed for thinner column diameter and helps in easier control of flow distribution. 3.2.2. Parameter optimization for binary column adsorption The effect of individual parameters (Q, Z, and D) on total equilibrium adsorption uptake (qtot) for the simultaneous removal of adsorbates from a binary system of AN & NB was studied. The average values of qtot for each parameter at level 1, 2, and 3 are given in Table 5. Parameter A: Q; parameter B: Z and parameter C: D has its maximum impact effect on response qtot at level 1, level 3 and level 2, respectively. The relative influence of the effect as per DOE, in general, is expressed by the difference between level 2 and level 1 (L2 − L1) of each factor. The larger the difference, the stronger is the influence. Table 6 implies that none of the single parameter has an intervening impact for the adsorption of AN and NB from the AN–NB binary system. No single parameter shows a strong influence on qtot value also. Fig. 3 represents that the bed height has slightly higher predominance (39 %) on column performance. 5
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is the volumetric flow rate (L/min), C0,j is the initial concentration of component j, C is the concentration of solute at time t (min), td,j is the delayed time between the two breakthrough curves and Sij is the adsorption competition coefficient of one component with respect to other and Sii = Sjj = 1. This term signifies the competitive adsorption of components onto the GAC surface. Estimation of adsorption parameters was performed by data validation and are reported in Table 7. Calculated breakthrough times were comparable with the experimental values as reported in Table 8. Therefore, we may conclude that the proposed model is satisfactory in predicting multicomponent breakthrough curves of a binary system well in advance for the scale-up approach. 4. Conclusions
Fig. 5. Effect of process parameters on qtot and S/N ratio for binary adsorption of AN and NB in GAC packed-bed.
Sorption affinity of NB towards GAC was observed to be higher than AN resulting in larger breakthrough time of NB over AN. Breakthrough curves for AN were observed to be sharper than NB, which was due to competitive adsorption among NB and AN. Equilibrium individual adsorption uptake (qi) was found to be higher at larger column diameter and height. This is because of increased surface area with an increased amount of adsorbent which resulted in larger binding/sorption sites. Larger diameter column decreased the packing efficiency owing to the compaction effect of the mass of packing material, i.e., GAC. Compaction effect reduced bed porosity resulting in difficult control of flow distribution. Amongst all the parameters, column height was observed to be the most predominant factor. Optimal process parameters were found to be bed diameter (D) = 2.54 cm, bed height (Z) = 60 cm and flow rate (Q) = 0.02 L/min. At this optimal condition, the average qtot from the experimental runs was found to be 4.2 mg/g, which is closer to the predicted qtot value of 4.17 mg/g. Furthermore, column breakthrough curves were well predicted by the empirical proposed model and validated with experimental data of AN–NB binary system effectively.
4.2 mg/g which is closer to the predicted qtot value of 4.17 mg/g (Tables S1 and S2). It may also be noted that these optimal values are valid within the specified range of process parameters. 3.3. Column modeling and data validation An empirical model was proposed to predict column breakthrough curve and breakthrough time for a binary adsorption (Eq. 6). This model is a modified version of the Thomas model [28–30]. Column performance in the form of breakthrough curves can be predicted by Eq. (4). Experimental and predicted breakthrough curves are well-matched as represented in Fig. 2.
C C0
= i
N exp j=1
Sij
{
1 Kij qo, j mc Q
Kij C0, j (t + td, j )
}
(6)
where N is number of components, Kij is rate constants [L/(min.mg)] of AN and NB, q0,j is the maximum solid-phase concentration of component j (mg/g), mC is the mass of adsorbent packed in the column (g), Q
Table 7 Estimation of column adsorption parameter with a proposed model for AN-NB binary system. Exp. No.
1 2 3 4 5 6 7 8 9
Co (mg/L)
mc (g)
AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
49 144 627 98.66 96.06 470.5 74.05 192.16 313.62
Aniline
Nitrobenzene
K (L/(mg.min))
q0 (mg/L)
S
td (min)
K (L/(mg.min))
q0 (mg/L)
S
td (min)
3.23 × 10-5 1.85 × 10-5 6.9 × 10-7 2.97 × 10-5 4.07 × 10-5 9.8 × 10-5 5.98 × 10-5 3.8 × 10-5 2.35 × 10-5
39.65 38.59 37.98 42.86 29.77 61.16 27.35 29.96 37.98
0.0031 0.0074 0.0107 0.0018 0.0051 0 0.0003 0.0004 0
0 0 0 0 0 7.52 0 0 0
1.18 × 10-5 6.12 × 10-6 1.28 × 10-6 1.05 × 10-5 1.52 × 10-5 2.96 × 10-6 2.36 × 10-5 1.14 × 10-5 1.25 × 10-5
120 150 210.89 160.28 131.75 126.23 107.43 103.78 110.89
0 0 0.0137 0 0 0.0210 −0.017 0 0.0134
12.51 151.22 27.34 12.51 12.60 2.89 3.367 12.6 29.63
Table 8 Comparison between experimental and predicted breakthrough time. S. No.
1 2 3 4 5 6 7 8 9
Co (mg/L)
Q (L/min)
AN
NB
1000 1000 1000 1000 1000 1000 1000 1000 1000
1000 1000 1000 1000 1000 1000 1000 1000 1000
0.02 0.02 0.02 0.04 0.04 0.04 0.06 0.06 0.06
D (cm)
2 2.54 4 2 2.54 4 2 2.54 4
Z (cm)
EBCT (min)
30 45 60 60 30 45 45 60 30
4.71 11.39 37.68 4.71 3.79 14.13 2.35 5.06 6.28
6
Aniline
Nitrobenzene
Actual Tb
predicted Tb
Actual Tb
predicted Tb
40.05 170.21 917.49 43.44 27.92 556.14 8.55 44.09 70.42
30.09 159.5 871.96 31.7 17.5 470.02 4.26 38.04 103.57
214.32 754.07 3475.19 238.75 170.42 1225.53 75.71 180.97 426.68
213.1 790.25 2800.57 303.02 248.71 1215.12 92.93 246.39 483.77
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5. Declaration of interests [13]
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
[14] [15]
Appendix A. Supplementary data
[16]
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jwpe.2019.101045.
[17]
References
[18]
[1] B. Ersoy, M.S. Çelik, Uptake of aniline and nitrobenzene from aqueous solution by organo-Zeolite, Environ. Technol. 25 (2004) 341–348. [2] Priyanka, V. Subbaramaiah, V.C. Srivastava, I.D. Mall, Catalytic oxidation of nitrobenzene by copper loaded activated carbon, Sep. Purif. Technol. 125 (2014) 284–290. [3] V. Anand, V.C. Srivastava, Photocatalytic degradation of nitrobenzene and azo dye using zinc oxide nanoparticles prepared by electrochemical method, J. Sci. Ind. Res. (India) 75 (2016) 632–637. [4] V.C. Srivastava, I.D. Mall, I.M. Mishra, Multicomponent adsorption study of metal ions onto bagasse fly ash using Taguchi’s design of experimental methodology, Ind. Eng. Chem. Res. 46 (2007) 5697–5706. [5] G.Q. Wu, X. Zhang, H. Hui, J. Yan, Q.S. Zhang, J.L. Wan, Y. Dai, Adsorptive removal of aniline from aqueous solution by oxygen plasma irradiated bamboo based activated carbon, Chem. Eng. J. 185–186 (2012) 201–210. [6] M.S. Rauthula, V.C. Srivastava, Studies on adsorption/desorption of nitrobenzene and humic acid onto/from activated carbon, Chem. Eng. J. 168 (2011) 35–43. [7] A.J. Jadhav, V.C. Srivastava, Adsorbed solution theory based modeling of binary adsorption of nitrobenzene, aniline and phenol onto granulated activated carbon, Chem. Eng. J. 229 (2013) 450–459. [8] A.J. Jadhav, V.C. Srivastava, Multicomponent adsorption isotherm modeling using thermodynamically inconsistent and consistent models, AIChE J. 65 (11) (2019) e16727. [9] M.O. Midda, V.C. Srivastava, J.P. Kushwaha, Modelling single and binary adsorptive behaviour of aniline and nitrobenzene onto granular activated carbon, Phys. Chem. Liq. (2018), https://doi.org/10.1080/00319104.2018.1553240. [10] S. Suresh, V.C. Srivastava, I.M. Mishra, Adsorptive removal of phenol from binary aqueous solution with aniline and 4-nitrophenol by granular activated carbon, Chem. Eng. J. 171 (2011) 997–1003. [11] H. Yan, X. Yang, J. Chen, C. Yin, C. Xiao, H. Chen, Synergistic removal of aniline by carbon nanotubes and the enzymes of Delftia sp. XYJ6, J. Environ. Sci. China (China) 23 (2011) 1165–1170. [12] S. Chowdhury, R. Mishra, P. Saha, P. Kushwaha, Adsorption thermodynamics,
[19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30]
7
kinetics and isosteric heat of adsorption of malachite green onto chemically modified rice husk, Desalination 265 (2011) 159–168. V.C. Srivastava, I.D. Mall, I.M. Mishra, Equilibrium modeling of ternary adsorption of metal ions onto rice husk ash, J. Chem. Eng. Data 54 (2009) 705–711. V.C. Srivastava, I.D. Mall, I.M. Mishra, Optimization of parameters for adsorption of metal ions onto rice husk ash using Taguchi’s experimental design methodology, Chem. Eng. J. 140 (2008) 136–144. P.N.E. Diagboya, E.D. Dikio, Silica-based mesoporous materials; emerging designer adsorbents for aqueous pollutants removal and water treatment, Microporous Mesoporous Mater. 266 (2018) 252–267. G. Li, B. Wang, W.Q. Xu, Y. Li, Y. Han, Q. Sun, Enhanced nitrobenzene adsorption in aqueous solution by surface-silanized fly-ash-Derived SBA-15, ACS Earth Sp. Chem. 2 (2018) 246–255. X. Yang, Q. Guan, W. Li, Effect of template in MCM-41 on the adsorption of aniline from aqueous solution, J. Environ. Manage. 92 (2011) 2939–2943. H. Al-Johani, M.A. Salam, Kinetics and thermodynamic study of aniline adsorption by multi-walled carbon nanotubes from aqueous solution, J. Colloid Interface Sci. 360 (2011) 760–767. A. Mehrizad, P. Gharbani, Study of 1-Chloro-4-Nitrobenzene adsorption on Carbon nanofibers by experimental design, Int. J. Nano Dimen. 7 (2016) 77–84. D.W. Gao, Q. Hu, H. Pan, J. Jiang, P. Wang, High-capacity adsorption of aniline using surface modification of lignocellulose-biomass jute fibers, Bioresour. Technol. 193 (2015) 507–512. P.D. Saha, S. Chowdhury, M. Mondal, K. Sinha, Biosorption of direct red 28 (Congo red) from aqueous solutions by eggshells : batch and column studies, Sep. Sci. Technol. 47 (2012) 112–123. A.H. Sulaymon, A.A. Mohammed, T.J. Al-Musawi, Column biosorption of lead, cadmium, copper, and arsenic ions onto algae, J. Bioprocess. Biotech. 3 (2013) 1–7. R.T. Upson, S.E. Burns, Sorption of nitroaromatic compounds to synthesized organoclays, J. Colloid Interface Sci. 297 (1) (2006) 70–76. A. Chatterjee, T. Ebina, T. Iwasaki, F. Mizukami, Intermolecular reactivity study to scale adsorption property of para- and meta-substituted nitrobenzene over 2:1 dioctahedral smectite, J. Chem. Phys. 18 (22) (2003) 10212–10220. M.F. Khan, P.J. Boor, B.S. Kaphalia, N.W. Alcock, G.A.S. Ansari, Hematopoietic toxicity of linoleic acid anilide: importance of aniline, Fundam. Appl. Toxicol. 25 (2) (1995) 224–232. J. Wang, G. Wang, H. Ma, M.F. Khan, Enhanced expression of cyclins and cyclindependent kinases in aniline-induced cell proliferation in rat spleen, Toxicol. Appl. Pharmacol. 250 (2011) 213–220. J.C.Y. Ng, W.H. Cheung, G. McKay, Equilibrium studies of the sorption of Cu(II) ions onto chitosan, J. Colloid Interface Sci. 255 (2002) 64–74. S. Singh, V.C. Srivastava, A. Goyal, I.D. Mall, Breakthrough modeling of furfural sorption behavior in a bagasse fly ash packed bed, Int. J. Civ. Struct. Environ. Infrastruct. Eng. Res. Dev. 25 (1) (2020) 104–113. V.C. Srivastava, B. Prasad, I.M. Mishra, I.D. Mall, M.M. Swamy, Prediction of breakthrough curves for sorptive removal of phenol by bagasse fly ash packed bed, Ind. Eng. Chem. Res. 47 (2008) 1603–1613. H.C. Thomas, Heterogeneous ion exchange in a flowing system, J. Am. Chem. Soc. 66 (1944) 1664–1666.