A response surface methodology approach for the optimization of cu2+ removal using rice husk– derived activated carbon - Long Giang Bach

Journal of Science and Technology 54 (4B) (2016) 123-131 A RESPONSE SURFACE METHODOLOGY APPROACH FOR THE OPTIMIZATION OF CU2+ REMOVAL USING RICE HUSK– DERIVED ACTIVATED CARBON Long Giang Bach1, Bui Thi Phuong Quynh1, Van Thi Thanh Ho2, Nguyen Thi Thuong1, Dinh Thi Thanh Tam1, Trinh Duy Nguyen1, Tran Van Thuan1, * 1NTT Institute of High Technology, Nguyen Tat Thanh University, 298–300A Nguyen Tat Thanh, Ho Chi Minh City, Vietnam 2Hochiminh City University of Natural Resources and Environment, 236B Le Van Sy, Ho Chi Minh City, Vietnam *Email: tranvt@outlook.com Received: August 2016; Accepted for publication: 10 November 2016 ABSTRACT In this study, we have used the potassium hydroxide (KOH) as an eco–friendly and favorable activating agent to develop the porous and defect structure of activated carbon. Otherwise, the response surface methodology (RSM) has been applied to investigate the effects of the adsorption parameters including initial concentration, adsorbent dosage, and pH of solution on the percentage of Cu2+ removal. The RSM–based two order regression polynomial models were found to be statistically significant by values of the coefficients of determination (R2) closer than 1.0 and the P–values < 0.0001 from analysis of variance (ANOVA). Under the predicted optimum conditions, actual experiments were confirmed to optimize the percentage of Cu2+ removal efficiency (97.5 %) and maximum adsorption capacity (24.45 mg.g–1) from Langmuir equation. Based on experimental results, a treatment process can be easily designed using rice husk for the fabrication of activated carbon to remove toxic metal ions from the polluted water. Keywords: removal of Cu2+, rice husk, response surface methodology, activated carbon. 1. INTRODUCTION Heavy metals are generally considered as one of the main causes for adverse effects on human health and ecosystems due to their high cumulative toxicity in groundwater [1]. Among the well–known elements, copper is a carcinogenic and non–biodegradable transition metal and it is commonly detected in fertilizer manufacture, mineral processing industrial effluent, the leak of chemical pollutants and tan–house [2]. The accumulation of copper accounts for typically serious infections such as neurological disorders, respiratory failure, and birth defects [3]. Traditional techniques have been developed for the elimination of copper–contaminated water, for example, chemical precipitation, oxidation/reduction and membrane filtration [4]. Long Giang Bach, et al. 124 Nevertheless, obstacles of these treatment processes could prohibit their potential applications including very high operational cost, moderate removal efficiency and the generation of hazardous sludge. Meanwhile, adsorption is recognized as an effective mechanism for the removal of pollutants because of its high performance and outstanding recyclability [5]. In recent years, adsorption onto activated carbon has been proven as a promising means of treatment for the removal of heavy metal ions from aqueous solution. However, commercial activated carbon is very expensive in the market, and hence its widespread applications are limited towards economic aspects [6]. These difficult challenges can be solved by using abundant biomass source as raw material for the fabrication strategy of activated carbon. Activated carbon (AC), a microcrystalline and non–graphitic material, could be prepared from zero–costly and locally available agricultural wastes [7]. Among the agricultural products, rice is a well–known and widespread plant and it is massively cultivated in some tropical countries. Combustion and discharge of rice husk without pretreatment can lead several environmental problems. According to the previous publication, main components of the rice husk are cellulose, hemicelluloses and lignin [8]. Hence, the transformation and conversion of non–toxic and renewable rice husk into low–cost and high–performance activated carbon has paid much attention of scientists and environmental organizations all over the world. The present work aims to investigate influential factors of the removal of Cu2+ by adsorption onto rice husk – derived activated carbons using the response surface methodology (RSM). The quadratic regression equations were established to evaluate the effect of several variables including initial Cu2+ concentration, the dosage of AC and pH of the solution on the Cu2+ removal efficiency. Otherwise, the predicted optimum conditions–based experiment was employed to find the maximum percentage of Cu2+ removal. 2. MATERIALS AND METHODS 2.1. Chemicals and instruments All chemicals for this study were commercially purchased from Merck and used as received without any further purification unless otherwise noted. All activated carbon samples were pretreated by heating at 105 oC for 3 h. The scanning electron microscope (SEM) was recorded by instrument S4800, Japan and used an accelerating voltage source of 10 kV with a magnification of 7000. The FT–IR spectra were recorded by using the Nicolet 6700 spectrophotometer instrument 2.2. Production of activated carbon from rice husk (RSAC) The rice husk was carbonized at 500 oC (10 oC/min) under N2 atmosphere (400 cm3/min). The char was soaked with KOH solution (char KOH = 1:1 by weight) for 1 day, then KOH– impregnated char was heated to 600 oC beneath N2 atmosphere. The sample was repeatedly washed with deionized water until filtered water obtained a neutral solution. Finally, the synthesized AC was slowly dried at 105 oC, and then smoothly ground for storage (27.8 % of AC yields). 2.3. Adsorption batch The activated carbon (0.8–9.2 g/L) was poured in an Erlenmeyer flask containing 50 mL of Cu2+ aqueous solution (8–92 ppm). After absorption equilibrium obtained, the adsorbent was A response surface methodology approach for the optimization of Cu2+ removal using rice 125 removed from the mixture. The residual concentrations were confirmed by AAS and Cu2+ removal was calculated as follows: ( ) C - C2 + o eCu removal % = .100 Co (1) where, Co and Ce are the Cu2+ initial and equilibrium concentrations (ppm), respectively. 2.4. Experimental design with RSM In this study, we used the RSM as a mathematical method to optimize experimental variables through second order polynomial regression equations. Central composite design (CCD) is used to establish given 20 experiments (Table 1) with five level including the low (–1), high (+1) and rotatable (±α). Table 1. Independent variables matrix and their encoded levels No Independent factors Code Levels –α –1 0 +1 +α 1 Initial concentration (ppm) x1 8 25 50 75 92 2 Adsorbent dosage (g/L) x2 0.8 2.5 5 7.5 9.2 3 pH of solution (–) x3 0.6 2 4 6 7.4 3. RESULTS AND DISCUSSION 3.1. Textural characterization of activated carbon The surface functional groups of activated carbon influences significantly on the absorbability such as ion exchange, catalysis, and adsorbent. The spectra of Fourier transform infrared spectroscopy was used to analyze the characteristics of material surface (Figure 1a). Generally, the rice husk–derived activated carbon possessed complex surface with various kinds of functional groups. In detail, the strong absorption band located at 3450 cm–1 – 3400 cm–1 was typically attributed to the –OH stretching vibrations of hydroxyl functional groups. A double peak around 2900 cm–1 was correspondent to C–H vibrations in alkane compounds. The oxygen–nitrogen asymmetric and C≡C bonding vibrations were confirmed by the presence of the peaks, which positioned at 1541 cm–1 and 2353 cm–1, respectively. The unsaturated carbon bonds (C=C) in aromatic rings or olefin were also confirmed by stretching band at 1640 cm–1. According to previous studies, KOH activation plays a crucial role in the formation of higher pore volumes and surface areas and evolution of the oxygen–containing group species [9]. Under electrostatic attraction between active sites containing a lone pair of electron and metal sites containing a positive charge, Cu2+ ions was captured by the mechanism of ion–exchange on the surface of activated carbon [10]. Moreover, the surface morphology of the as–synthesized activated carbon was recorded by a means of scanning electron microscope and micrographs (size 2 µm–100 µm) was shown in Figure 1b at a magnification of 60000. It is clear that the structure of activate carbon possesses the high porosity and amorphous surface. Long Giang Bach, et al. 126 Figure 1. FT–IR spectra (a) and SEM micrograph (b) of the activated carbon. 3.2. Assessment of experimental results with Design–Expert The percentage of Cu2+ removal from the synthetic wastewater using the response surface methodology approach was presented in Table 2. The ranges of investigation parameter were designed as follows: initial concentration from 8 ppm to 92 ppm, an adsorbent dosage from 0.8 g/L to 9.2 g/L and pH of the solution from 0.6 to 7.4. The correlation between the responses and variables was described by the following quadratic equations: 1 2 3 1 2 2 2 2 1 3 2 3 1 2 3 ( ) (%) 93.1 5.2 12.73 24.20 0.84 3.99 7.21 2.75 7.9 15.09 Cu II removal x x x x x x x x x x x x = − + + + + − − − − (2) Herein, the significance of quadratic model could be evaluated by ANOVA data obtained from the response surface methodology approach through output parameters. According to Table 3, the proposed model for Cu2+ removal was statistically significant (95 % confidence level) due to the values of probability > F were less than 0.0001 and determination of coefficient R2 was closer 1.0. The adequate precision (AP) ratio was used to measure to noise ratio. This ratio greater than 4.0 indicated an adequate signal and the proposed model could be used to navigate the design space. In addition, the predicted and actual values positioned at the straight line revealed high fitness of model (Figure 2a). Otherwise, lack of fit (LOF) value was statistically insignificant to indicate the model fitted data well. Table 2. Matrix of observed and predicted values No Variables Response (Cu2+ removal) x1 (Ci, ppm) x2 (dosage, g/L) x3 (pH) Actual (%) Predicted (%) 1 25 2.5 2 30.2 33.2 2 75 2.5 2 14.1 13.2 A response surface methodology approach for the optimization of Cu2+ removal using rice 127 Table 3. ANOVA for response surface quadratic models Response Source Sum of squares Degree of freedom Mean square F– value Prob. > F Comment Cu2+ removal (%) Model 15013.94 9 1668.22 193.37 < 0.0001s Mean = 75.47 x1 369.02 1 369.02 42.78 < 0.0001 s CV = 3.89 x2 2212.71 1 2212.71 256.49 < 0.0001 s R2 = 0.9943 x3 7996.34 1 7996.34 926.91 < 0.0001 s R2(adj.) = 0.9891 x1 x2 5.61 1 5.61 0.65 0.4387 n AP = 42.231 x1 x3 127.20 1 127.20 14.74 0.0033 s x2 x3 416.16 1 416.16 48.24 < 0.0001 s x12 109.04 1 109.04 12.64 0.0052 s x22 902.27 1 902.27 104.59 < 0.0001 s x32 3281.43 1 3281.43 380.37 < 0.0001 s Residuals 86.27 10 8.63 LOF 70.20 5 14.04 4.37 0.0658 n PE 16.07 5 3.21 Note: s significant at p 0.05, LOF: lack of fit, PE: pure error 3 25 7.5 2 69.2 71.4 4 75 7.5 2 53.7 54.7 5 25 2.5 6 86.5 88.1 6 75 2.5 6 83.6 84.0 7 25 7.5 6 93.9 97.4 8 75 7.5 6 97.1 96.7 9 8 5 4 98.9 94.0 10 92 5 4 75.3 76.5 11 50 0.8 4 50.4 49.3 12 50 9.2 4 94.6 92.1 13 50 5 0.6 11.6 9.7 14 50 5 7.4 92.8 91.1 15 50 5 4 91.1 93.1 16 50 5 4 94.9 93.1 17 50 5 4 92.8 93.1 18 50 5 4 93.0 93.1 19 50 5 4 95.1 93.1 20 50 5 4 90.9 93.1 12 3.3 do rem oth DX per bo Cu ob con con con inf ad exp sit cle wa 8 . Effect of i With P–v sage (x2) an oval. Herei er paramete Figure 2. A The optim 9 to approa centage of th adsorbent 2+ from aqu tained at a centration centration a centration luenced stro sorption of lained due es containing arly (100 % s slightly re ndependent alues < 0.0 d pH of th n, the respo r maintained ctual versus p ization of C ch the optim Cu2+ remova dosage and eous soluti higher valu (<75 ppm). nd pH of th of Cu2+ had ngly on the Cu2+ onto to the comp a lone pair ) by increas duced at a h variables o 001 referrin e solution ( nse surface at zero leve redicted plot perc u2+ remova um points f l through e initial conc on. The ma e of activat Figure 2c re e solution at a negligible Cu2+ remova the activate etition in ter of the elect ing the valu igher value o n the remov g to Table x3) influenc was plotted l (Figure 2). (a) and respo entage of Cu2 l efficiency or the opera quation (2). entration o ximum perc ed carbon d vealed the a dosage of impact on l efficiency. d carbon w m of adsorp ron [11]. M e of pH fro f pH (> 7.0 al of Cu2+ 3, the initi ed significa with a varia nse surfaces ( +) removal. was underta tional condi According f Cu2+ influe entage of C osage (> 5 dependence 5 g/L. It wa the removal At strongly as unfavor tion betwee eanwhile, Cu m 4 to 6. H ). Finally, th Lo al concentra ntly on the tion of two b–d) for regre ken using th tions and to to the obser nced slightl u2+ remova g/L) and lo of Cu2+ rem s clear that t efficiency w acidic envir able. This p n Cu2+ ions 2+ adsorptio owever, Cu2 e effect of A ng Giang Ba tion (x1), a percentage parameters w ssion model e statistical obtain the m vation in F y on the re l (100 %) wer value oval on bo he variation hile pH of onment (pH henomenon and H+ on t n could be i + removal e C dosage an ch, et al. dsorbent of Cu2+ hile the of the program aximum igure 2b, moval of could be of initial th initial of initial solution < 2), the can be he active mproved fficiency d pH on A response surface methodology approach for the optimization of Cu2+ removal using rice 129 the removal of Cu2+ was observed in Figure 2d. A wide range for the value of pH (4 – 7) and dosage (3–8 g/L) was favorable for the adsorption. To confirm the optimum points from DX9, a model experiment were employed at the following conditions: Ci = 67.1 ppm, dosage = 5.1 and pH = 5.8 (Table 4). Thereby, the experiment for the percentage of Cu2+ removal was obtained 97.5 %. This result was nearly closer to the predicted values of 100.5 %. These above results demonstrate the high compatibility of the proposed models with the experimental data. Table 4. Model confirmation Sample Ci (ppm) Dosage (g/L) pH (–) Desirability Cu2+ removal (%) Predict Test TWAC 67.1 5.1 5.8 1.00 100.5 97.5 3.4. Isotherm modeling and adsorbent recyclability Adsorption parameters can be obtained by using well–known isotherm equations, which gives crucial information about behaviors, mechanisms, and properties of adsorbent. The constants of isotherm models for the adsorption process and the respective correlation coefficient (R2) are summarized in Table 5. Based on the isotherm equations, high obtained values of R2 for adsorption models of Cu2+ are observed to be 0.9954, 0.9937 and 0.9443 for Langmuir, Freundlich, and Tempkin, respectively and the data fitness as order: Langmuir > Freundlich > Tempkin. For the Langmuir model, adsorption constant RL less than 1.0 indicates that Langmuir adsorption is recognized as a favorable process. Therefore, Langmuir model can be used to describe the adsorption behavior of Cu2+ onto the surface of activated carbon and Cu2+ adsorption process is proposed to occur mainly monolayer adsorption. The maximum adsorption in this study acquired to be 24.45 mg.g–1, which was higher than previous studies (Table 6). Table 5. Isotherm parameters for the adsorption Isotherm Equation Parameters Value of parameters Langmuir 1 1 1 1. e m L e mq q K C q = + KL (L.mg–1) qm (mg.g–1) RL R2 0.1680 24.45 0.0608 0.9954 Freundlich 1ln ln lne F eq K Cn = + KF [(mg.g–1).(L.mg–1)]1/n 1/n R2 0.2263 0.9346 0.9937 Temkin 1 1ln lne T eq B K B C= + KT (L.mg –1) B1 R2 0.1362 5.3117 0.9443 The regeneration was employed to investigate the recyclability of rice husk–derived activated carbon. The steps for this procedure as follows: 3 × 50 mL hydrochloric acid (1.4 M) was used to wash Cu2+–adsorbed activated carbon [12]. Then, desorption adsorbent was Long Giang Bach, et al. 130 completely dried at 378 K for 12 h and could be used as an adsorbent for the further study. As a result, the removal percentage of Cu2+ of the recycled RSAC was decreased from 97 % (1st) to 82.4 % (6th). Therefore, RSAC can be used for the removal of Cu2+ several times without a considerable decrease of adsorption capacity (Figure 3). The present results revealed the great potential in the use of rice husk as a raw material source for adsorption of Cu2+ from wastewater. Table 6. Comparison of absorption capacity of Cu2+ treatment by several adsorbents Source Cu2+ treatment Ref Co (ppm) Dosage (g/L) pH qm (mg/g) Sugarcane 75 5.1 6.0 4.87 [3] Coconut tree sawdust 200 4 6.0 3.89 [13] Eggshell 200 4 6.0 34.48 [13] Sugarcane bagasse 200 4 6.0 21.28 [13] Rice husk 67.1 5.1 5.8 24.45 This work Figure 3. Reuse test of the activated carbon, 4. CONCLUSIONS The present study focused on the promising of the rice husk as a zero–costly and available precursor for the fabrication of porous activated carbon for the purposes of wastewater treatment. The characteristic profiles admitted the highly porous, amorphous, various kinds of essential functional groups and defective structure of rice husk–derived active carbon. Three parameters for the adsorption process of Cu2+ onto activated carbon have been investigated including initial concentration, adsorbent dosage, and pH of the solution. The optimization of Cu2+ removal using the response surface methodology has found out the optimum points as follows: Ci = 67.1 ppm, dosage = 5.1 g/L and pH = 5.8. Moreover, isotherm models were checked and revealed the high satisfactory (R2 > 0.9) by all adsorption equations, where the Langmuir equation showed high capacity of monolayer adsorption (24.45 mg.g–1). 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