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Statistical optimization of process parameters for the simultaneous adsorption of Cr(VI) and phenol onto Fe-treated tea waste biomass

Statistical optimization of process parameters for the simultaneous adsorption of Cr(VI) and... Appl Water Sci (2017) 7:4361–4374 https://doi.org/10.1007/s13201-017-0582-9 ORIGINAL ARTICLE Statistical optimization of process parameters for the simultaneous adsorption of Cr(VI) and phenol onto Fe-treated tea waste biomass 1 1 Ankur Gupta Chandrajit Balomajumder Received: 5 January 2016 / Accepted: 14 June 2017 / Published online: 24 June 2017 The Author(s) 2017. This article is an open access publication Abstract In this study, simultaneous removal of Cr(VI) some important methods which have been used to remove and phenol from binary solution was carried out using Fe- the heavy metal ion and phenolic contents together. These treated tea waste biomass. The effect of process parameters components are generally present in the effluents of various such as adsorbent dose, pH, initial concentration of Cr(VI) industries such as leather tanning, electroplating, and (mg/L), and initial concentration of phenol (mg/L) was alloying extra (Gladysz-Plaska et al. 2012). Cr(VI) and its optimized. The analysis of variance of the quadratic model copollutants such as phenol, naphthalene, and tri- demonstrates that the experimental results are in good chloroethylene discharge from these industries contaminate agreement with the predicted values. Based on experi- ground water aquifers, lake, river sediments, and soil (Yen- mental design at an initial concentration of 55 mg/L of Hui et al. 2009). Much research has been carried out on the Cr(VI), 27.50 mg/L of phenol, pH 2.0, 15 g/L adsorbent adsorption of a single pollutant nevertheless the fact that dose, 99.99% removal of Cr(VI), and phenol was achieved. organic pollutants also exist with multiple metallic species (Repo et al. 2011; Gupta and Balomajumder 2015); Keywords Binary solution  Cr(VI)  Phenol  Response therefore, in the recent year, simultaneous removal of surface methodology  Fe-treated tea waste biomass heavy metals and organic compounds has gained a great attention in wastewater treatment processes (Mani et al. 2015). Adsorption of pollutant using commercial granular Introduction activated carbon is conventional method, but due to its high cost, this method is not economical (Suresh et al. 2011). Heavy metals are generally present with phenolic com- Adsorption is proved to be most promising conventional or pounds in the environment cause adverse effects on flora traditional methods for the simultaneous removal of and fauna, including human beings (Aksu and Akpinar organic compound and heavy metal ions from wastewater 2001). Precipitation/coagulation (Wang et al. 2011), in comparison with other treatment methods such as pre- chemical oxidation (Dittert et al. 2014), biodegradation cipitation, ion exchange, catalytic reaction, etc. (Quintelas (Annadurai et al. 2008), adsorption (Jain et al. 2011), ion et al. 2006; Aksu and Akpinar 2001). Modification of exchange (Cavaco et al. 2007), membrane processing (Lin biosorbent by metal impregnation (Talreja et al. 2014) and et al. 2014), electrolytic methods (Hamdan and El-Naas acid treatment (Garg et al. 2009) improves the percentage 2014), carbon nanomaterial (Salam et al. 2012), etc. are removal of pollutants (Kuo and Bembenek 2008; Fonseca- Correa et al. 2013; Owlad et al. 2010; Cronje et al. 2011). Chromium is found in the environment predominantly in & Ankur Gupta two forms Cr(III) and Cr(VI) out of which Cr(VI) is most guptaankur599@gmail.com mutagenic and carcinogenic to the living organism (Acar Chandrajit Balomajumder and Malkoc 2004; Baral et al. 2009). Chromium sulfate chandfch@iitr.ernet.in [Cr(III)] is used as a tanning agent which can be converted to Cr(VI) and causes severe contamination of ground water Department of Chemical Engineering, Indian Institute of (El-Sherif et al. 2013). Phenol is highly toxic and Technology Roorkee, Roorkee, India 123 4362 Appl Water Sci (2017) 7:4361–4374 recalcitrant organic compound used as a biocide in the water. To avoid photo-oxidation of phenol, stock solution leather tanning process (Srivastava et al. 2007; Hank et al. was stored in brown glass bottle (Chaudhary and Balo- 2014). According to WHO, the maximum permissible limit majumder 2014). Based on industrial wastewater such as of Cr(VI) in drinking water is 0.05 mg/L (Bansal et al. tannery and electroplating, 2:1 ratio of Cr(VI) and phenol 2009). According to the US environmental protection were taken for conducting the present experiments, because agency, the maximum permissible limit of discharge of these components are generally present in the wastewater phenol by various process industries is 0.005 mg/L (Ban- in this composition (Aksu and Akpinar 2001; Gupta and erjee and Ghoshal 2011). The aim of this work is to opti- Balomajumder 2015). mize the process parameters such pH, contact time, adsorbent dose for the simultaneous removal of Cr(VI), and phenol in a multicomponent simulated synthetic wastewa- Batch experiments ter using Box–Behnken design of response surface methodology (RSM). Characterization of Fe-treated tea Batch adsorption studies were carried out in 250 mL round waste biomass before and after adsorption was also carried bottom flasks with working volume of 100 mL. The syn- out to confirm the simultaneous adsorption of Cr(VI) and thetic, simulated binary wastewater was prepared in the phenol using various techniques such as FTIR, FE-SEM, laboratory by mixing the necessary amount of K Cr O and 2 2 7 EDX, and BET surface area. phenol in 2:1 ratio (Anupam et al. 2011). RSM (response surface methodology) using Box–Behnken design was used for the optimization of process parameters. Box–Behnken Materials and methodology design does not contain any corner point in the design; therefore, number of experimental run generated is com- Preparation of biosorbent paratively less than CCD. A range of process parameters was selected as pH (2–8), adsorbent dose (0.5–1.5 g), ini- Tea waste biomass was collected from local tea stall tial concentration of Cr(VI) (10–100 mg/L), and initial Roorkee. A soluble sugar and dirt present in tea waste concentration of phenol (5–50 mg/L). The experiments biomass was removed by boiling in distilled water about were carried out in an incubator shaker at temperature for 30 min. After boiling, tea waste biomass was washed 30 C until the equilibrium condition was achieved. The with distilled water in triplicate and then dried in hot air pH of binary solution was controlled by adding 0.1 N HCl oven at 50 C for 12 h. Furthermore, the dried biomass was and 0.1 N NaOH. When equilibrium was attained, the sieved to the desired particle size 0.5–2 mm (Gupta and sample was filtered using the standard Whatman filter Balomajumder 2015). paper (Cat No. 1001 125). Thereafter, concentration of 5 g of tea waste biomass was added to 50 mL solution Cr(VI) and phenol in the filtrate was analyzed using a UV of 2 M FeSO 7H O in 500 mL conical flask. It was kept spectrophotometer. 4 2 on a magnetic stirring plate at 100 C for the impregnation The percentage removal of phenol and Cr(VI) was cal- of Fe ions onto the surface of tea waste. 0.1 M of NaOH culated by the following equation: was added dropwise to the conical flask by the help of C  C i t Percentage removal ¼  100; ð1Þ burette to increase the pH 4–5 for the precipitation of ferrous sulfate. This process was carried out continuously where C and C are the initial and final concentrations of i t 3–4 h. Upon cooling, the tea waste biomass was covered the pollutant, respectively. with a thick layer of orange color iron oxide. Then, tea waste biomass was washed with distilled water to remove Analytical method extra quantity of precipitate. Finally, this Fe-treated tea waste biomass was dried in an oven at 50 C for 2 h and The residual concentration of Cr(VI) and phenol in the then sieved to obtain homogeneous particle size (Nethaji filtrate was analyzed using UV spectrophotometer made of et al. 2013). Hach (model no: DR 5500). The residual concentration of Cr(VI) was measured by reacting 10 mL of filtrate with a Preparation of solutions 200 lL diphenyl carbazide solution and 500 lLH SO and 2 4 let them stand for 10 min for full color development and its All chemicals used for the experimentation purpose absorbance was noted at 540 nm. For the analysis of phe- including potassium dichromate and phenol were AR grade nol, 10 mL of phenol sample was mixed with 0.7 mL of having more than 99% purity. Stock solutions of Cr(VI) sodium bicarbonate (pH 8), 0.1 mL of 4-amino antipyrine and phenol were prepared by dissolving known quantity of (20.8 mM), and 0.1 mL of potassium ferricyanide phenol and potassium dichromate in 1 L of Millipore 123 Appl Water Sci (2017) 7:4361–4374 4363 (83.4 mM) and let them stand for full color development respectively. The composition of various elements present and its absorbance was noted at 510 nm (Srihari and Das onto the surface of tea waste biomass was obtained by EDX 2008). Both phenol and K Cr O7 do not interact with each analysis. It is clear from SEM analysis that (Fig. 2a), before 2 2 other as there was no effect on the absorbance of both the surface modification, surface was highly porous and components and can be measured for the same filtrate in homogeneous as large number of pores was observed. The UV spectrophotometer at 510 and 540 nm, respectively. surface morphology of tea waste biomass after surface modification was different from before surface modification. After surface modification, it was covered with a layer of Fe Characterization of biosorbent ions. After simultaneous adsorption of Cr(VI) and phenol onto the surface of Fe-treated tea waste biomass, the surface FTIR of tea waste biomass became rough and bulky, which was due to the fact that all before and after adsorption the active pores were filled with Cr(VI) and phenol anion. The adsorption of Cr(VI) and phenol anions was due to The FTIR spectrum is an important tool used for the iden- strong electrostatic force between negatively charged Cr(VI) tification of characteristic functional groups responsible for and phenol anions and positively charged tea waste biomass the adsorption of Cr(VI) and phenol onto the surface of Fe- surface (Zuo and Balasubramanian 2013). The EDX of tea treated tea waste biomass. The FTIR spectrum of tea waste waste biomass before surface modification, after surface biomass before surface modification, after surface modifi- modification, and after simultaneous adsorption of Cr(VI) cation, and after simultaneous adsorption of Cr(VI) and and phenol is shown in Fig. 3a–c, respectively. The results of phenol is shown in Fig. 1a–c, respectively. FTIR study the EDX analysis showed a sharp peak of elements such as C, suggested that functional groups such as N–H, O–H, C=O, O, and Ca before surface modification, but after surface and C–O were present onto the surface of tea waste biomass modification, a peak of Fe in K and L shell of tea waste (Golbaz et al. 2014). The FTIR spectrum of tea waste bio- biomass was observed which confirms that iron was mass before adsorption (Fig. 1a) indicates the strong band of impregnated onto the surface of tea waste biomass. After -1 O–H functional groups at 3612.29 cm wavelength simultaneous adsorption of Cr(VI) and phenol, a peak of Cr (Kamsonlian et al. 2011; Srivastava et al. 2015). Adsorption in K and L shell was observed which confirms the adsorption -1 band at around 1989–1654.67 cm indicates the C=O of Cr(VI). The changes in the peaks of carbon and oxygen in group (Moussavi and Barikbin 2010). Furthermore, peaks at the EDX spectrum before and after adsorption confirm the -1 1396.67 and 1095.67 cm were significance of C–O and adsorption of phenol. The weight % of elements present onto N–H stretching (Mohan et al. 2006). After surface modifi- the surface of tea waste biomass before surface modification, cation of tea waste biomass shown in Fig. 1b, there is a after surface modification, and after simultaneous adsorption change in the vibration of the O–H functional group at of Cr(VI) and phenol is given in Tables 1, 2, and 3, respec- -1 3443.04 cm which became broad after simultaneous tively. From Tables 1, 2, and 3, it is clear that after surface adsorption of Cr(VI) and phenol, as shown in Fig. 1c. A peak modification with FeSO 7H O, the weight % of C was 4 2 -1 of the C–H functional group at 2923.82 cm was observed decreased, while weight % of O was increased. After after surface modification of tea waste biomass (Quintelas simultaneous adsorption of Cr(VI) and phenol, a peak of 4.87 et al. 2009). Furthermore, the shift in the functional groups weight % of Cr and changes in the weight % of C and O were such as C=O, C–O, and N–H was observed after surface observed in the EDX spectra which confirm the simultaneous modification and after simultaneous adsorption of Cr(VI) adsorption of Cr(VI) and phenol (Kumar et al. 2012). and phenol, as shown in Fig. 1b, c, respectively. Changes in the peak of functional group after surface modification BET surface area analysis shown in Fig. 1b depict that the surface of tea waste biomass was modified as iron was impregnated. Furthermore, the BET surface area and total pore volume of the tea waste bio- changes in the peak of functional group shown in Fig. 1c mass before and after surface modification, and after simulta- confirm the simultaneous adsorption of Cr(VI) and phenol neous adsorption of Cr(VI) and phenol are given in Table 4. onto the surface of Fe-treated tea waste biomass. The surface area of tea waste biomass was calculated using surface area analyzer ASAP 2010 Micrometrics, USA). The SEM and EDX analysis surfaceareaoftea wastebiomass was(23.658 m /g). After surface modification, the surface area was slightly decreased FE-SEM shows the morphology of tea waste biomass before (20.196 m /g), because iron was impregnated onto the surface surface modification, after surface modification, and after of tea waste biomass. After simultaneous adsorption of Cr(VI) simultaneous adsorption of Cr(VI) and phenol onto the sur- and phenol, the surface area was reduced (2.456 m /g), because face of Fe-treated tea waste biomass, as shown in Fig. 2a–c, all the pores were filled by Cr(VI) and phenol anions. 123 4364 Appl Water Sci (2017) 7:4361–4374 Fig. 1 a FTIR of tea waste a 100 biomass before surface modification, b FTIR of tea 90 waste biomass after surface modification, and c FTIR of tea waste biomass after simultaneous adsorption of Cr(VI) and phenol 1095.67 1989.89 1396.97 1654.67 3612.29 4000 3500 3000 2500 2000 1500 1000 500 -1 Wavelength (cm ) b 60 708.41 1739.87 40 604.44 1380.44 2923.82 1051.12 1638.76 1239.92 3443.04 4000 3500 3000 2500 2000 1500 1000 500 -1 Wavelength (cm ) 1987.54 1098.65 1299.89 1694.66 3190.76 -10 4000 3500 3000 2500 2000 1500 1000 500 -1 Wavelength (cm ) Experimental design and procedure suggested by Box–Behnken design for the construction of quadratic equation model for the two responses Y [per- The Box–Behnken design matrix has been applied for the centage removal of Cr(VI)] and Y (percentage removal of phenol). An orthogonal 2 Box–Behnken design (BBD) simultaneous adsorption of Cr(VI) and phenol using the design expert software 6.0.8. The interactive effects of with five replicates at the center point was used to opti- mize the selected key variables (X , X , X and X ) four most important operating variables, pH (X ), adsor- 1 1 2 3, 4 (Singh et al. 2013). The coded values of the process bent dose (X ), initial concentration of Cr(VI) (X ), and 2 3 parameters were determined by the following equation initial concentration of phenol (X ), were determined onto (Rajasimman et al. 2009; Satapathy and Das 2014;De the percentage removal of Cr(VI) and phenol. A total of Sales et al. 2013): 29 experiments was carried out in the present study as % Transmittance % Transmittance % Transmittance Appl Water Sci (2017) 7:4361–4374 4365 that the experimental data are close to the predicted value (Park et al. 2011). Model and statistical analysis The experimental data were analyzed using ANOVA (Analysis of variance) and validated for two responses of interest percentage removal of Cr(VI) (Y ) and percentage removal of phenol (Y ). A second-order polynomial equation was developed to study the interactive effect of four process parameters (X , X , X and X ) onto the percentage removal 1 2 3, 4 of Cr(VI) (Y ) and Y (percentage removal of phenol) 1 2 (Chaudharyand Balomajumder 2014; Abigail et al. 2015). n n1 n X X X X Y ¼ a þ a x þ a x a x x ; ð3Þ i o i i ii i ij i j i¼1 i¼1 j¼iþ1 where Y is the predicted value of the response of interest, a i o is intercept coefficient, a is linear coefficient, a is quadratic i ii regression coefficient, and a is regression coefficients of ij interaction. Some insignificant terms of the above model can be neglected based on the statistical analysis for the accurate prediction of response (Cao et al. 2014). Results and discussion The effect of process variable on response of interest was investigated by conducting a total of 29 experiments sug- gested by the Box–Behnken design of design expert soft- ware (Ferreira et al. 2007). Batch experiments were conducted for visualizing the effects of independent vari- ables on responses of interest. Multiple regression analysis using response surface methodology was carried out to generate the following regression equation for the two responses of interest Y and Y (Xu et al. 2013): 1 2 YðÞ Percentage removal of CrðÞ VI ¼ 123:22342 11:94269 X þ 3:94889 X  0:68007 X 1 2 3 2 2 Fig. 2 a SEM image of tea waste biomass before surface modifica-  0:44198 X þ 0:69796 X þ 14:13167 X 1 2 tion, b SEM image of tea waste biomass after surface modification, 2 2 þ 0:00421379 X þ 0:00945021 X  2:33167 X X 1 2 3 4 and c SEM image of tea waste biomass after simultaneous adsorption of Cr(VI) and phenol 0:024093 X X  0:025926 X X þ 0:011111 X X 1 3 1 4 2 3 0:20000 X X þ 0:00592593 X X ; 2 4 3 4 X  X i o x ¼ ; ð2Þ Dx YðÞ Percentage removal of Phenol ¼ 60:80  22:17 X þ 8:42 X  2:25 X  12:33 X where x is the coded value of the ith variable, X is the 1 2 3 4 i i 2 2 2 2 uncoded value of the ith test variable, and X is the o þ 3:97 X  0:40 X  2:15 X þ 6:73 X 1 2 3 4 uncoded value of the ith test variable at center point. The 3:75 X X  2:75 X X  4 X X 1 2 1 3 1 4 range and level of individual variables selected are given in þ 1:25 X X  1:75 X X  4:25 X X : 2 3 2 4 3 4 Table 5. The Box–Behnken experiment design for the simultaneous adsorption of Cr(VI) and phenol onto the Fe- The regression equation coefficients were calculated and treated tea waste biomass is given in Table 6 which shows the data fitted to a second-order polynomial equation for 123 4366 Appl Water Sci (2017) 7:4361–4374 Fig. 3 a EDX image of tea waste biomass before surface modification, b EDX image of tea waste biomass after surface modification, and c EDX image of tea waste biomass after simultaneous adsorption of Cr(VI) and phenol simultaneous removal of Cr(VI) and phenol. The results of Aksu 2009). Values of ‘‘P [ F’’ less than 0.05 indicate that ANOVA for the response Y [percentage removal of model terms are significant for the simultaneous removal of Cr(VI)] and Y (percentage removal of phenol) are given in Cr(VI) and phenol (Pavlovic et al. 2014). The value of the Tables 7 and 8, respectively. The significance of the mean squares is calculated by dividing the sum of squares second-order quadratic equation developed depends upon of each variable by their respective degree of freedom. The the coefficient of determination (R ) and F test (Gonen and F (Fishers’ variance ratio) value is calculated by taking the 123 Appl Water Sci (2017) 7:4361–4374 4367 Table 1 Various elements present onto the tea waste biomass surface before surface modification Element Weight (%) Atomic (%) Net int. Error (%) C K 80.62 87.27 294.02 3.95 O K 13.2 10.73 16.77 16.42 Ca K 6.18 2.01 25.21 13.89 Table 2 Various elements present onto the tea waste biomass after surface modification Element Weight (%) Atomic (%) Net int. Error (%) C K 60.86 67.8 222.57 5.44 O K 38.24 31.98 87.14 11.26 Ca K 0.9 0.22 1.5 66.77 Table 3 Various elements present onto the tea waste biomass after simultaneous adsorption of Cr(VI) and phenol Element Weight (%) Atomic (%) Net int. Error (%) C K 51.48 63.98 184.44 6.84 O K 34.48 32.17 107.46 10.32 Cr K 4.87 1.4 16.18 6.36 Fe K 9.17 2.45 18.32 6.27 Table 4 Surface properties of tea waste biomass Biosorbent BET surface area Monolayer volume Total pore volume 2 3 3 (m /g) (cm /g) (m /g) Tea waste biomass before surface modification 23.658 5.187 0.0355 Tea waste biomass after surface modification 20.196 1.467 0.0230 Tea waste biomass after simultaneous adsorption of Cr(VI) and phenol 2.456 0.578 0.00245 Table 5 Different levels of process variables selected for the simultaneous adsorption of Cr(VI) and phenol Independent variables Range and levels -10 ?1 pH 2 5 8 Adsorbent dose (mg/g) 0.5 1 1.5 Initial concentration of Cr(VI) (mg/L) 10 55 100 Initial concentration of phenol (mg/L) 5 27.50 50 ratio of the mean square owing to regression and the mean and a very low probability value (P B 0.0001) was square owing to error. F values show the variation in the obtained for both responses Y and Y (Cao et al. 2014). 1 2 experimental and predicted values of the variables about The lack of fit F value for response Y (147.32) and Y 1 2 the mean. Here, the ANOVA of the regression model for (185.22) depicts that the lack of fit is significant. There is response Y [percentage removal of Cr(VI)] and response only a 0.01% chance of ‘‘Lack of Fit F value’’ (Kumar Y (percentage removal of phenol) shows that the model is et al. 2009). The predicted R for response Y (0.9285) is in 2 1 highly significant which is confirmed by the calculated reasonable agreement with the adjusted R of 0.9752. F value for response Y (79.53) and response Y (50.11) Similarly, for response Y the predicted R (0.8873) is in 1 2 2, 123 4368 Appl Water Sci (2017) 7:4361–4374 Table 6 Experimental design matrix developed by Box–Behnken design for removal of chromium Standard order Run no. Actual variables Removal efficiency (%) Cr(VI) Removal efficiency (%) Phenol X X X X Experimental Predicted Experimental Predicted 1 2 3 4 14 1 5 1.5 10 27.5 76 78.5 68 67.67 11 2 2 1.0 55 50 90 94.08 84 85.33 24 3 5 1.5 55 50 69 67.17 60 61.46 19 4 2 1 100 27.50 90 90.33 86 85.29 5 5 5 1 10 5 78 76.58 80 75.71 23 6 5 0.5 55 50 56 56 50 48.13 3 7 2 1.5 55 27.50 99.99 100 99.99 98.70 29 8 5 1 55 27.50 52 51.60 63 63 8 9 5 1 100 50 68 65.25 44 46.54 28 10 5 1 55 27.50 52 51.60 63 63 12 11 8 1 55 50 30 34.58 38 33 9 12 2 1 55 5 89 87.25 98 100 27 13 5 1 55 27.50 52 52 63 63 25 14 5 1 55 27.50 52 52 63 63 20 15 8 1 100 27.50 25 27.83 30 35.46 1 16 2 0.5 55 27.50 80 78.08 75 74.38 18 17 8 1 10 27.50 48 49 42 45.46 7 18 5 1 10 50 72 67.92 58 59.54 22 19 5 1.5 55 5 67 68.33 85 89.62 13 20 5 0.5 10 27.50 60 63.42 51 53.33 2 21 8 0.5 55 27.50 34 29.02 38 37.54 4 22 8 1.5 55 27.50 40 37.75 48 46.88 10 23 8 1 55 5 36 34.75 68 65.67 15 24 5 0.5 100 27.50 48 48.25 47 46.33 16 25 5 1.5 100 27.50 65 64.42 69 65.67 26 26 5 1 55 27.50 52 52 63 63 21 25 5 0.5 55 5 45 48.17 68 69.29 6 28 5 1 100 5 50 49.92 83 79.71 17 29 2 1 10 27.50 99.99 98.49 87 84.29 good agreement with adjusted R (0.9606) (Sahu et al. Table 5, which is confirmed by high F values and low 2009). ‘‘Adequate Precision’’ measures the signal-to-noise P value (P\ 0.0001) (Fereidouni et al. 2009; Singh et al. ratio, and a ratio greater than 4 is desirable (Gonen and 2013), but the effect of X (initial concentration of phenol) Aksu 2009). Here, the ratio of 31.253 for response Y and was not highly significant as the P values obtained were 26.376 for response Y indicates an adequate signal. P [ 0.005. Similarly, the linear effects of process variables (X , X , X , and X ) were examined onto the percentage 1 2 3 4 Interaction effects of independent variables (X , X , removal of phenol (response Y ) given in Table 6 which 1 2 2 X , and X on responses Y and Y ) shows that effect of pH (X ), adsorbent dose (X ), and initial 3 4 1 2 1 2 concentration of phenol (X ) was highly significant. The RSM is a statistical method for the analysis of interactive effect of process variable X [initial concentration of Cr(VI)] effects of operating variables onto the response of interest. onto the percentage removal of phenol was not highly sig- The effects of independent process variables were evaluated nificant. Therefore, the percentage removal of Cr(VI) and by 3D plots shown in Fig. 4a, b for response Y [percentage phenol in the binary mixture using Fe-treated tea waste removal of Cr(VI)] and Fig. 5a, b for response Y (percent- biomass was not affected by the presence of each other. It can age removal of phenol). For response Y the linear effects of be concluded that Cr(VI) and phenol can be easily removed 1, the process variables X (pH), X (adsorbent dose), X (initial from binary mixture using Fe-treated tea waste biomass. The 1 2 3 2 2 2 2 concentration of Cr(VI) are highly significant, given in effects of X , X , X , and X onto the responses Y and Y were 1 2 3 4 1 2 123 Appl Water Sci (2017) 7:4361–4374 4369 Table 7 Results of ANOVA for the percentage removal of Cr(VI) using Fe-treated tea waste biomass Source Sum of squares DF Mean square F value P [ F Model 11,716.44 14 836.89 79.53 \0.0001 significant X 9406.88 1 9406.88 893.96 \0.0001 X 736.18 1 736.18 69.96 \0.0001 X 645.19 1 645.19 61.31 \0.0001 X 33.33 1 33.33 3.17 0.0968 X 239.91 1 239.91 22.80 0.0003 X 72.05 1 72.05 6.85 0.0203 X 450.41 1 450.41 42.80 \0.0001 X 136.31 1 136.31 12.95 0.0029 X X 48.93 1 48.93 4.65 0.0489 1 2 X X 42.32 1 42.32 4.02 0.0647 1 3 X X 12.25 1 12.25 1.16 0.2988 1 4 X X 0.25 1 0.25 0.024 0.8797 2 3 X X 20.25 1 20.25 1.92 0.1871 2 4 X X 144.00 1 144.00 13.68 0.0024 3 4 Residual 147.32 14 10.52 Lack of fit 147.32 10 14.73 Pure error 0.000 4 0.000 Cor total 11,863.76 28 Table 8 Results of ANOVA for the percentage removal of phenol using Fe-treated tea waste biomass Source Sum of squares DF Mean square F value P [ F Model 9281.24 14 662.95 50.11 \0.0001 significant X 5895.89 1 5895.89 445.64 \0.0001 X 849.92 1 849.92 64.24 \0.0001 X 60.75 1 60.75 4.59 0.0502 X 1825.33 1 1825.33 137.97 \0.0001 X 53.58 1 53.58 4.05 0.0638 X 14.61 1 14.61 1.10 0.3111 X 68.50 1 68.50 5.18 0.0391 X 205.27 1 205.27 15.51 0.0015 X X 56.18 1 56.18 4.25 0.0584 1 2 X X 30.25 1 30.25 2.29 0.1528 1 3 X X 64.00 1 64.00 4.84 0.0452 1 4 X X 6.25 1 6.25 0.47 0.5031 2 3 X X 12.25 1 12.25 0.93 0.3523 2 4 X X 72.25 1 72.25 5.46 0.0348 3 4 Residual 185.22 14 13.23 Lack of fit 185.22 10 18.52 Pure error 0.000 4 0.000 Cor total 9466.46 28 also appreciated. The combined effects of adsorbent dose L, and 99.99% removal of both Cr(VI) and phenol was and pH (X X ), initial concentration of Cr(VI), and initial obtained. The response surface curves were plotted, as 1 2 concentration of phenol (X X ) onto the responses Y and Y shown in Fig. 4a, b which depicts the effect of independent 3 4 1 2 were also observed. Based on the response surface design, it variables onto the percentage removal of Cr(VI). Figure 5a, is evident that at an initial concentration of 55 mg/L of b shows the effects of independent variables onto the per- Cr(VI), 27.50 mg/L of phenol, pH 2.0, adsorbent dose 15 g/ centage removal of phenol. The circular nature of the contour 123 4370 Appl Water Sci (2017) 7:4361–4374 Fig. 4 a 3D response surface plots showing the effects of (a) pH (b) adsorbent dose onto the percentage removal of Cr(VI). b 3D response surface plots showing the effects of (a) initial concentration of Cr(VI) and (b) initial concentration of phenol onto the percentage removal of Cr(VI) signifies that the effect of initial concentration of phenol onto were observed. The percentage removal of Cr(VI) and phe- the percentage removal of Cr(VI) and initial concentration of nol was decreased with increasing pH and increases with Cr(VI) onto the percentage removal of phenol was not sig- increase in adsorbent dose. The possible reason of these nificant, as shown in Figs. 4b and 5b, respectively. The phenomena is given below. percentage removal of Cr(VI) decreases with the increase in the initial concentration of Cr(VI) and percentage removal of Effect of pH onto the percentage removal of Cr(VI) phenol decreases with the increase in the initial concentra- and phenol tion of phenol. The effects of adsorbent dose, pH, and initial concentration of Cr(VI) onto the percentage removal of pH is an important parameter for the simultaneous Cr(VI) were found significant. Similar effects of these removal of Cr(VI) and phenol. At low pH value, the independent variables onto the percentage removal of phenol percentage removal of Cr(VI) and phenol was maximum, 123 Appl Water Sci (2017) 7:4361–4374 4371 Fig. 5 a 3D response surface plots showing the effects of (a) adsorbent dose and (b) pH onto the percentage removal of phenol. b 3D response surface plots showing the effects of (a) initial concentration of Cr(VI) and (b) initial concentration of phenol onto the percentage removal of phenol because at low pH value, the surface of Fe-treated tea this pH, the surface of biosorbent becomes negatively waste biomass becomes more protonated. At low pH, charged which repel the Cr(VI) and phenol anions. 2- - Cr(VI) was in the form of Cr O and HCrO , while Favorable adsorption occurs between pH (2–5). There was 2 7 4 phenol was present in the form of C H O (Chaudhary also a competition between negatively charged phenolate 6 5 and Balomajumder 2014). Therefore, there is a strong and chromate anions for adsorption to the vacant posi- electrostatic interaction between negatively charge chro- tively charged active sites. When all the vacant active mate, dichromate, and phenolate anions to the positively sites are filled, equilibrium was established between charged surface of Fe-treated tea waste biomass. At high negatively charged chromate and phenolate anions present pH value, after pH 6, a rapid decrease in the percentage in the synthetic binary solution and positively charged removal of Cr(VI) and phenol was observed, because at surface. 123 4372 Appl Water Sci (2017) 7:4361–4374 optimization, equilibrium, kinetics and thermodynamic studies. Effects of adsorbent dose onto the percentage removal J Taiwan Inst Chem Eng 49:156–164 of Cr(VI) and phenol Acar F, Malkoc NE (2004) The removal of chromium(VI) from aqueous solutions by Fagus orientalis L. Bioresour Technol Fe-treated tea waste biomass is used as a adsorbent for the 94:13–15 Aksu Z, Akpinar D (2001) Competitive biosorption of phenol and simultaneous adsorption of Cr(VI) and phenol. The chromium (VI) from binary mixtures onto dried anaerobic simultaneous adsorption of both Cr(VI) and phenol from a activated sludge. Biochem Eng J 7:183–193 binary mixture increases with the increase in adsorbent Annadurai G, Ling LY, Lee JF (2008) Statistical optimization of dose (mg/g) due to increase in possible active sites and medium components and growth conditions by response surface methodology to enhance phenol degradation by Pseudomonas surface area for adsorption. After reaching optimum putida. J Hazard Mater 151:171–178 adsorbent dose, simultaneous removal of both Cr(VI) and Anupam K, Dutta S, Bhattacharjee C, Datta S (2011) Adsorptive phenol becomes constant and then decreases. The decrease removal of chromium (VI) from aqueous solution over powdered in percentage removal after reaching the optimum dose was activated carbon: optimisation through response surface method- ology. Chem Eng J 173:135–143 due to all the vacant seats which were filled (Garg et al. Banerjee A, Ghoshal AK (2011) Phenol degradation performance by 2004). isolated Bacillus cereus immobilized in alginate. Int J Biodete- rior Biodegrad 65:1052–1060 Bansal M, Singh D, Garg VK (2009) A comparative study for the removal of hexavalent chromium from aqueous solution by Conclusion agriculture wastes’ carbons. J Hazard Mater 171:83–92 Baral SS, Das N, Chaudhury GR, Das SN (2009) A preliminary study In this study, Fe-treated tea waste biomass was used for the on the adsorptive removal of Cr(VI) using seaweed, Hydrilla simultaneous removal of Cr(VI) and phenol from binary verticillata. J Hazard Mater 171:358–369 Cao J, Wu J, Jin Y, Yilihan P, Huang W (2014) Response surface mixture using Fe-treated tea waste biomass. Impregnation methodology approach for optimization of the removal of of Fe ions onto the surface of tea waste biomass improves chromium(VI) by NH -MCM-41. J Taiwan Inst Chem Eng the morphology of adsorbent and thus the percentage 45:860–868 removal of Cr(VI) and phenol. Response surface method- Cavaco SA, Fernandes S, Quina MM, Ferreira LM (2007) Removal of chromium from electroplating industry effluents by ion exchange ology (RSM) using Box–Behnken design was used for the resins. J Hazard Mater 144:634–638 determination of optimum conditions for adsorption of Chaudhary N, Balomajumder C (2014) Optimization study of Cr(VI) and phenol from binary mixture. The experimental adsorption parameters for removal of phenol on aluminum and predicted values were in good agreement for both impregnated fly ash using response surface methodology. J Taiwan Inst Chem Eng 45:852–859 responses Y [percentage removal of Cr(VI)] and Y (per- 1 2 Cronje KJ, Chetty K, Carsky M, Sahu JN, Meikap BC (2011) centage removal of phenol). A second-order quadratic Optimization of chromium(VI) sorption potential using devel- equation was developed to predict the effects of indepen- oped activated carbon from sugarcane bagasse with chemical dent variables onto the percentage removal of Cr(VI) and activation by zinc chloride. Desalination 275:276–284 De Sales PF, Magriotis ZM, Rossi MALS, Resende RF, Nunes CA phenol from binary mixture. The application of statistical (2013) Optimization by response surface methodology of the design using RSM for the adsorption of Cr(VI) and phenol adsorption of Coomassie Blue dye on natural and acid-treated from a binary mixture reduces the time and overall cost, clays. J Environ Manag 130:417–428 and improved the efficiency of the process. 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Statistical optimization of process parameters for the simultaneous adsorption of Cr(VI) and phenol onto Fe-treated tea waste biomass

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Earth Sciences; Hydrogeology; Water Industry/Water Technologies; Industrial and Production Engineering; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution; Nanotechnology; Private International Law, International & Foreign Law, Comparative Law
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Appl Water Sci (2017) 7:4361–4374 https://doi.org/10.1007/s13201-017-0582-9 ORIGINAL ARTICLE Statistical optimization of process parameters for the simultaneous adsorption of Cr(VI) and phenol onto Fe-treated tea waste biomass 1 1 Ankur Gupta Chandrajit Balomajumder Received: 5 January 2016 / Accepted: 14 June 2017 / Published online: 24 June 2017 The Author(s) 2017. This article is an open access publication Abstract In this study, simultaneous removal of Cr(VI) some important methods which have been used to remove and phenol from binary solution was carried out using Fe- the heavy metal ion and phenolic contents together. These treated tea waste biomass. The effect of process parameters components are generally present in the effluents of various such as adsorbent dose, pH, initial concentration of Cr(VI) industries such as leather tanning, electroplating, and (mg/L), and initial concentration of phenol (mg/L) was alloying extra (Gladysz-Plaska et al. 2012). Cr(VI) and its optimized. The analysis of variance of the quadratic model copollutants such as phenol, naphthalene, and tri- demonstrates that the experimental results are in good chloroethylene discharge from these industries contaminate agreement with the predicted values. Based on experi- ground water aquifers, lake, river sediments, and soil (Yen- mental design at an initial concentration of 55 mg/L of Hui et al. 2009). Much research has been carried out on the Cr(VI), 27.50 mg/L of phenol, pH 2.0, 15 g/L adsorbent adsorption of a single pollutant nevertheless the fact that dose, 99.99% removal of Cr(VI), and phenol was achieved. organic pollutants also exist with multiple metallic species (Repo et al. 2011; Gupta and Balomajumder 2015); Keywords Binary solution  Cr(VI)  Phenol  Response therefore, in the recent year, simultaneous removal of surface methodology  Fe-treated tea waste biomass heavy metals and organic compounds has gained a great attention in wastewater treatment processes (Mani et al. 2015). Adsorption of pollutant using commercial granular Introduction activated carbon is conventional method, but due to its high cost, this method is not economical (Suresh et al. 2011). Heavy metals are generally present with phenolic com- Adsorption is proved to be most promising conventional or pounds in the environment cause adverse effects on flora traditional methods for the simultaneous removal of and fauna, including human beings (Aksu and Akpinar organic compound and heavy metal ions from wastewater 2001). Precipitation/coagulation (Wang et al. 2011), in comparison with other treatment methods such as pre- chemical oxidation (Dittert et al. 2014), biodegradation cipitation, ion exchange, catalytic reaction, etc. (Quintelas (Annadurai et al. 2008), adsorption (Jain et al. 2011), ion et al. 2006; Aksu and Akpinar 2001). Modification of exchange (Cavaco et al. 2007), membrane processing (Lin biosorbent by metal impregnation (Talreja et al. 2014) and et al. 2014), electrolytic methods (Hamdan and El-Naas acid treatment (Garg et al. 2009) improves the percentage 2014), carbon nanomaterial (Salam et al. 2012), etc. are removal of pollutants (Kuo and Bembenek 2008; Fonseca- Correa et al. 2013; Owlad et al. 2010; Cronje et al. 2011). Chromium is found in the environment predominantly in & Ankur Gupta two forms Cr(III) and Cr(VI) out of which Cr(VI) is most guptaankur599@gmail.com mutagenic and carcinogenic to the living organism (Acar Chandrajit Balomajumder and Malkoc 2004; Baral et al. 2009). Chromium sulfate chandfch@iitr.ernet.in [Cr(III)] is used as a tanning agent which can be converted to Cr(VI) and causes severe contamination of ground water Department of Chemical Engineering, Indian Institute of (El-Sherif et al. 2013). Phenol is highly toxic and Technology Roorkee, Roorkee, India 123 4362 Appl Water Sci (2017) 7:4361–4374 recalcitrant organic compound used as a biocide in the water. To avoid photo-oxidation of phenol, stock solution leather tanning process (Srivastava et al. 2007; Hank et al. was stored in brown glass bottle (Chaudhary and Balo- 2014). According to WHO, the maximum permissible limit majumder 2014). Based on industrial wastewater such as of Cr(VI) in drinking water is 0.05 mg/L (Bansal et al. tannery and electroplating, 2:1 ratio of Cr(VI) and phenol 2009). According to the US environmental protection were taken for conducting the present experiments, because agency, the maximum permissible limit of discharge of these components are generally present in the wastewater phenol by various process industries is 0.005 mg/L (Ban- in this composition (Aksu and Akpinar 2001; Gupta and erjee and Ghoshal 2011). The aim of this work is to opti- Balomajumder 2015). mize the process parameters such pH, contact time, adsorbent dose for the simultaneous removal of Cr(VI), and phenol in a multicomponent simulated synthetic wastewa- Batch experiments ter using Box–Behnken design of response surface methodology (RSM). Characterization of Fe-treated tea Batch adsorption studies were carried out in 250 mL round waste biomass before and after adsorption was also carried bottom flasks with working volume of 100 mL. The syn- out to confirm the simultaneous adsorption of Cr(VI) and thetic, simulated binary wastewater was prepared in the phenol using various techniques such as FTIR, FE-SEM, laboratory by mixing the necessary amount of K Cr O and 2 2 7 EDX, and BET surface area. phenol in 2:1 ratio (Anupam et al. 2011). RSM (response surface methodology) using Box–Behnken design was used for the optimization of process parameters. Box–Behnken Materials and methodology design does not contain any corner point in the design; therefore, number of experimental run generated is com- Preparation of biosorbent paratively less than CCD. A range of process parameters was selected as pH (2–8), adsorbent dose (0.5–1.5 g), ini- Tea waste biomass was collected from local tea stall tial concentration of Cr(VI) (10–100 mg/L), and initial Roorkee. A soluble sugar and dirt present in tea waste concentration of phenol (5–50 mg/L). The experiments biomass was removed by boiling in distilled water about were carried out in an incubator shaker at temperature for 30 min. After boiling, tea waste biomass was washed 30 C until the equilibrium condition was achieved. The with distilled water in triplicate and then dried in hot air pH of binary solution was controlled by adding 0.1 N HCl oven at 50 C for 12 h. Furthermore, the dried biomass was and 0.1 N NaOH. When equilibrium was attained, the sieved to the desired particle size 0.5–2 mm (Gupta and sample was filtered using the standard Whatman filter Balomajumder 2015). paper (Cat No. 1001 125). Thereafter, concentration of 5 g of tea waste biomass was added to 50 mL solution Cr(VI) and phenol in the filtrate was analyzed using a UV of 2 M FeSO 7H O in 500 mL conical flask. It was kept spectrophotometer. 4 2 on a magnetic stirring plate at 100 C for the impregnation The percentage removal of phenol and Cr(VI) was cal- of Fe ions onto the surface of tea waste. 0.1 M of NaOH culated by the following equation: was added dropwise to the conical flask by the help of C  C i t Percentage removal ¼  100; ð1Þ burette to increase the pH 4–5 for the precipitation of ferrous sulfate. This process was carried out continuously where C and C are the initial and final concentrations of i t 3–4 h. Upon cooling, the tea waste biomass was covered the pollutant, respectively. with a thick layer of orange color iron oxide. Then, tea waste biomass was washed with distilled water to remove Analytical method extra quantity of precipitate. Finally, this Fe-treated tea waste biomass was dried in an oven at 50 C for 2 h and The residual concentration of Cr(VI) and phenol in the then sieved to obtain homogeneous particle size (Nethaji filtrate was analyzed using UV spectrophotometer made of et al. 2013). Hach (model no: DR 5500). The residual concentration of Cr(VI) was measured by reacting 10 mL of filtrate with a Preparation of solutions 200 lL diphenyl carbazide solution and 500 lLH SO and 2 4 let them stand for 10 min for full color development and its All chemicals used for the experimentation purpose absorbance was noted at 540 nm. For the analysis of phe- including potassium dichromate and phenol were AR grade nol, 10 mL of phenol sample was mixed with 0.7 mL of having more than 99% purity. Stock solutions of Cr(VI) sodium bicarbonate (pH 8), 0.1 mL of 4-amino antipyrine and phenol were prepared by dissolving known quantity of (20.8 mM), and 0.1 mL of potassium ferricyanide phenol and potassium dichromate in 1 L of Millipore 123 Appl Water Sci (2017) 7:4361–4374 4363 (83.4 mM) and let them stand for full color development respectively. The composition of various elements present and its absorbance was noted at 510 nm (Srihari and Das onto the surface of tea waste biomass was obtained by EDX 2008). Both phenol and K Cr O7 do not interact with each analysis. It is clear from SEM analysis that (Fig. 2a), before 2 2 other as there was no effect on the absorbance of both the surface modification, surface was highly porous and components and can be measured for the same filtrate in homogeneous as large number of pores was observed. The UV spectrophotometer at 510 and 540 nm, respectively. surface morphology of tea waste biomass after surface modification was different from before surface modification. After surface modification, it was covered with a layer of Fe Characterization of biosorbent ions. After simultaneous adsorption of Cr(VI) and phenol onto the surface of Fe-treated tea waste biomass, the surface FTIR of tea waste biomass became rough and bulky, which was due to the fact that all before and after adsorption the active pores were filled with Cr(VI) and phenol anion. The adsorption of Cr(VI) and phenol anions was due to The FTIR spectrum is an important tool used for the iden- strong electrostatic force between negatively charged Cr(VI) tification of characteristic functional groups responsible for and phenol anions and positively charged tea waste biomass the adsorption of Cr(VI) and phenol onto the surface of Fe- surface (Zuo and Balasubramanian 2013). The EDX of tea treated tea waste biomass. The FTIR spectrum of tea waste waste biomass before surface modification, after surface biomass before surface modification, after surface modifi- modification, and after simultaneous adsorption of Cr(VI) cation, and after simultaneous adsorption of Cr(VI) and and phenol is shown in Fig. 3a–c, respectively. The results of phenol is shown in Fig. 1a–c, respectively. FTIR study the EDX analysis showed a sharp peak of elements such as C, suggested that functional groups such as N–H, O–H, C=O, O, and Ca before surface modification, but after surface and C–O were present onto the surface of tea waste biomass modification, a peak of Fe in K and L shell of tea waste (Golbaz et al. 2014). The FTIR spectrum of tea waste bio- biomass was observed which confirms that iron was mass before adsorption (Fig. 1a) indicates the strong band of impregnated onto the surface of tea waste biomass. After -1 O–H functional groups at 3612.29 cm wavelength simultaneous adsorption of Cr(VI) and phenol, a peak of Cr (Kamsonlian et al. 2011; Srivastava et al. 2015). Adsorption in K and L shell was observed which confirms the adsorption -1 band at around 1989–1654.67 cm indicates the C=O of Cr(VI). The changes in the peaks of carbon and oxygen in group (Moussavi and Barikbin 2010). Furthermore, peaks at the EDX spectrum before and after adsorption confirm the -1 1396.67 and 1095.67 cm were significance of C–O and adsorption of phenol. The weight % of elements present onto N–H stretching (Mohan et al. 2006). After surface modifi- the surface of tea waste biomass before surface modification, cation of tea waste biomass shown in Fig. 1b, there is a after surface modification, and after simultaneous adsorption change in the vibration of the O–H functional group at of Cr(VI) and phenol is given in Tables 1, 2, and 3, respec- -1 3443.04 cm which became broad after simultaneous tively. From Tables 1, 2, and 3, it is clear that after surface adsorption of Cr(VI) and phenol, as shown in Fig. 1c. A peak modification with FeSO 7H O, the weight % of C was 4 2 -1 of the C–H functional group at 2923.82 cm was observed decreased, while weight % of O was increased. After after surface modification of tea waste biomass (Quintelas simultaneous adsorption of Cr(VI) and phenol, a peak of 4.87 et al. 2009). Furthermore, the shift in the functional groups weight % of Cr and changes in the weight % of C and O were such as C=O, C–O, and N–H was observed after surface observed in the EDX spectra which confirm the simultaneous modification and after simultaneous adsorption of Cr(VI) adsorption of Cr(VI) and phenol (Kumar et al. 2012). and phenol, as shown in Fig. 1b, c, respectively. Changes in the peak of functional group after surface modification BET surface area analysis shown in Fig. 1b depict that the surface of tea waste biomass was modified as iron was impregnated. Furthermore, the BET surface area and total pore volume of the tea waste bio- changes in the peak of functional group shown in Fig. 1c mass before and after surface modification, and after simulta- confirm the simultaneous adsorption of Cr(VI) and phenol neous adsorption of Cr(VI) and phenol are given in Table 4. onto the surface of Fe-treated tea waste biomass. The surface area of tea waste biomass was calculated using surface area analyzer ASAP 2010 Micrometrics, USA). The SEM and EDX analysis surfaceareaoftea wastebiomass was(23.658 m /g). After surface modification, the surface area was slightly decreased FE-SEM shows the morphology of tea waste biomass before (20.196 m /g), because iron was impregnated onto the surface surface modification, after surface modification, and after of tea waste biomass. After simultaneous adsorption of Cr(VI) simultaneous adsorption of Cr(VI) and phenol onto the sur- and phenol, the surface area was reduced (2.456 m /g), because face of Fe-treated tea waste biomass, as shown in Fig. 2a–c, all the pores were filled by Cr(VI) and phenol anions. 123 4364 Appl Water Sci (2017) 7:4361–4374 Fig. 1 a FTIR of tea waste a 100 biomass before surface modification, b FTIR of tea 90 waste biomass after surface modification, and c FTIR of tea waste biomass after simultaneous adsorption of Cr(VI) and phenol 1095.67 1989.89 1396.97 1654.67 3612.29 4000 3500 3000 2500 2000 1500 1000 500 -1 Wavelength (cm ) b 60 708.41 1739.87 40 604.44 1380.44 2923.82 1051.12 1638.76 1239.92 3443.04 4000 3500 3000 2500 2000 1500 1000 500 -1 Wavelength (cm ) 1987.54 1098.65 1299.89 1694.66 3190.76 -10 4000 3500 3000 2500 2000 1500 1000 500 -1 Wavelength (cm ) Experimental design and procedure suggested by Box–Behnken design for the construction of quadratic equation model for the two responses Y [per- The Box–Behnken design matrix has been applied for the centage removal of Cr(VI)] and Y (percentage removal of phenol). An orthogonal 2 Box–Behnken design (BBD) simultaneous adsorption of Cr(VI) and phenol using the design expert software 6.0.8. The interactive effects of with five replicates at the center point was used to opti- mize the selected key variables (X , X , X and X ) four most important operating variables, pH (X ), adsor- 1 1 2 3, 4 (Singh et al. 2013). The coded values of the process bent dose (X ), initial concentration of Cr(VI) (X ), and 2 3 parameters were determined by the following equation initial concentration of phenol (X ), were determined onto (Rajasimman et al. 2009; Satapathy and Das 2014;De the percentage removal of Cr(VI) and phenol. A total of Sales et al. 2013): 29 experiments was carried out in the present study as % Transmittance % Transmittance % Transmittance Appl Water Sci (2017) 7:4361–4374 4365 that the experimental data are close to the predicted value (Park et al. 2011). Model and statistical analysis The experimental data were analyzed using ANOVA (Analysis of variance) and validated for two responses of interest percentage removal of Cr(VI) (Y ) and percentage removal of phenol (Y ). A second-order polynomial equation was developed to study the interactive effect of four process parameters (X , X , X and X ) onto the percentage removal 1 2 3, 4 of Cr(VI) (Y ) and Y (percentage removal of phenol) 1 2 (Chaudharyand Balomajumder 2014; Abigail et al. 2015). n n1 n X X X X Y ¼ a þ a x þ a x a x x ; ð3Þ i o i i ii i ij i j i¼1 i¼1 j¼iþ1 where Y is the predicted value of the response of interest, a i o is intercept coefficient, a is linear coefficient, a is quadratic i ii regression coefficient, and a is regression coefficients of ij interaction. Some insignificant terms of the above model can be neglected based on the statistical analysis for the accurate prediction of response (Cao et al. 2014). Results and discussion The effect of process variable on response of interest was investigated by conducting a total of 29 experiments sug- gested by the Box–Behnken design of design expert soft- ware (Ferreira et al. 2007). Batch experiments were conducted for visualizing the effects of independent vari- ables on responses of interest. Multiple regression analysis using response surface methodology was carried out to generate the following regression equation for the two responses of interest Y and Y (Xu et al. 2013): 1 2 YðÞ Percentage removal of CrðÞ VI ¼ 123:22342 11:94269 X þ 3:94889 X  0:68007 X 1 2 3 2 2 Fig. 2 a SEM image of tea waste biomass before surface modifica-  0:44198 X þ 0:69796 X þ 14:13167 X 1 2 tion, b SEM image of tea waste biomass after surface modification, 2 2 þ 0:00421379 X þ 0:00945021 X  2:33167 X X 1 2 3 4 and c SEM image of tea waste biomass after simultaneous adsorption of Cr(VI) and phenol 0:024093 X X  0:025926 X X þ 0:011111 X X 1 3 1 4 2 3 0:20000 X X þ 0:00592593 X X ; 2 4 3 4 X  X i o x ¼ ; ð2Þ Dx YðÞ Percentage removal of Phenol ¼ 60:80  22:17 X þ 8:42 X  2:25 X  12:33 X where x is the coded value of the ith variable, X is the 1 2 3 4 i i 2 2 2 2 uncoded value of the ith test variable, and X is the o þ 3:97 X  0:40 X  2:15 X þ 6:73 X 1 2 3 4 uncoded value of the ith test variable at center point. The 3:75 X X  2:75 X X  4 X X 1 2 1 3 1 4 range and level of individual variables selected are given in þ 1:25 X X  1:75 X X  4:25 X X : 2 3 2 4 3 4 Table 5. The Box–Behnken experiment design for the simultaneous adsorption of Cr(VI) and phenol onto the Fe- The regression equation coefficients were calculated and treated tea waste biomass is given in Table 6 which shows the data fitted to a second-order polynomial equation for 123 4366 Appl Water Sci (2017) 7:4361–4374 Fig. 3 a EDX image of tea waste biomass before surface modification, b EDX image of tea waste biomass after surface modification, and c EDX image of tea waste biomass after simultaneous adsorption of Cr(VI) and phenol simultaneous removal of Cr(VI) and phenol. The results of Aksu 2009). Values of ‘‘P [ F’’ less than 0.05 indicate that ANOVA for the response Y [percentage removal of model terms are significant for the simultaneous removal of Cr(VI)] and Y (percentage removal of phenol) are given in Cr(VI) and phenol (Pavlovic et al. 2014). The value of the Tables 7 and 8, respectively. The significance of the mean squares is calculated by dividing the sum of squares second-order quadratic equation developed depends upon of each variable by their respective degree of freedom. The the coefficient of determination (R ) and F test (Gonen and F (Fishers’ variance ratio) value is calculated by taking the 123 Appl Water Sci (2017) 7:4361–4374 4367 Table 1 Various elements present onto the tea waste biomass surface before surface modification Element Weight (%) Atomic (%) Net int. Error (%) C K 80.62 87.27 294.02 3.95 O K 13.2 10.73 16.77 16.42 Ca K 6.18 2.01 25.21 13.89 Table 2 Various elements present onto the tea waste biomass after surface modification Element Weight (%) Atomic (%) Net int. Error (%) C K 60.86 67.8 222.57 5.44 O K 38.24 31.98 87.14 11.26 Ca K 0.9 0.22 1.5 66.77 Table 3 Various elements present onto the tea waste biomass after simultaneous adsorption of Cr(VI) and phenol Element Weight (%) Atomic (%) Net int. Error (%) C K 51.48 63.98 184.44 6.84 O K 34.48 32.17 107.46 10.32 Cr K 4.87 1.4 16.18 6.36 Fe K 9.17 2.45 18.32 6.27 Table 4 Surface properties of tea waste biomass Biosorbent BET surface area Monolayer volume Total pore volume 2 3 3 (m /g) (cm /g) (m /g) Tea waste biomass before surface modification 23.658 5.187 0.0355 Tea waste biomass after surface modification 20.196 1.467 0.0230 Tea waste biomass after simultaneous adsorption of Cr(VI) and phenol 2.456 0.578 0.00245 Table 5 Different levels of process variables selected for the simultaneous adsorption of Cr(VI) and phenol Independent variables Range and levels -10 ?1 pH 2 5 8 Adsorbent dose (mg/g) 0.5 1 1.5 Initial concentration of Cr(VI) (mg/L) 10 55 100 Initial concentration of phenol (mg/L) 5 27.50 50 ratio of the mean square owing to regression and the mean and a very low probability value (P B 0.0001) was square owing to error. F values show the variation in the obtained for both responses Y and Y (Cao et al. 2014). 1 2 experimental and predicted values of the variables about The lack of fit F value for response Y (147.32) and Y 1 2 the mean. Here, the ANOVA of the regression model for (185.22) depicts that the lack of fit is significant. There is response Y [percentage removal of Cr(VI)] and response only a 0.01% chance of ‘‘Lack of Fit F value’’ (Kumar Y (percentage removal of phenol) shows that the model is et al. 2009). The predicted R for response Y (0.9285) is in 2 1 highly significant which is confirmed by the calculated reasonable agreement with the adjusted R of 0.9752. F value for response Y (79.53) and response Y (50.11) Similarly, for response Y the predicted R (0.8873) is in 1 2 2, 123 4368 Appl Water Sci (2017) 7:4361–4374 Table 6 Experimental design matrix developed by Box–Behnken design for removal of chromium Standard order Run no. Actual variables Removal efficiency (%) Cr(VI) Removal efficiency (%) Phenol X X X X Experimental Predicted Experimental Predicted 1 2 3 4 14 1 5 1.5 10 27.5 76 78.5 68 67.67 11 2 2 1.0 55 50 90 94.08 84 85.33 24 3 5 1.5 55 50 69 67.17 60 61.46 19 4 2 1 100 27.50 90 90.33 86 85.29 5 5 5 1 10 5 78 76.58 80 75.71 23 6 5 0.5 55 50 56 56 50 48.13 3 7 2 1.5 55 27.50 99.99 100 99.99 98.70 29 8 5 1 55 27.50 52 51.60 63 63 8 9 5 1 100 50 68 65.25 44 46.54 28 10 5 1 55 27.50 52 51.60 63 63 12 11 8 1 55 50 30 34.58 38 33 9 12 2 1 55 5 89 87.25 98 100 27 13 5 1 55 27.50 52 52 63 63 25 14 5 1 55 27.50 52 52 63 63 20 15 8 1 100 27.50 25 27.83 30 35.46 1 16 2 0.5 55 27.50 80 78.08 75 74.38 18 17 8 1 10 27.50 48 49 42 45.46 7 18 5 1 10 50 72 67.92 58 59.54 22 19 5 1.5 55 5 67 68.33 85 89.62 13 20 5 0.5 10 27.50 60 63.42 51 53.33 2 21 8 0.5 55 27.50 34 29.02 38 37.54 4 22 8 1.5 55 27.50 40 37.75 48 46.88 10 23 8 1 55 5 36 34.75 68 65.67 15 24 5 0.5 100 27.50 48 48.25 47 46.33 16 25 5 1.5 100 27.50 65 64.42 69 65.67 26 26 5 1 55 27.50 52 52 63 63 21 25 5 0.5 55 5 45 48.17 68 69.29 6 28 5 1 100 5 50 49.92 83 79.71 17 29 2 1 10 27.50 99.99 98.49 87 84.29 good agreement with adjusted R (0.9606) (Sahu et al. Table 5, which is confirmed by high F values and low 2009). ‘‘Adequate Precision’’ measures the signal-to-noise P value (P\ 0.0001) (Fereidouni et al. 2009; Singh et al. ratio, and a ratio greater than 4 is desirable (Gonen and 2013), but the effect of X (initial concentration of phenol) Aksu 2009). Here, the ratio of 31.253 for response Y and was not highly significant as the P values obtained were 26.376 for response Y indicates an adequate signal. P [ 0.005. Similarly, the linear effects of process variables (X , X , X , and X ) were examined onto the percentage 1 2 3 4 Interaction effects of independent variables (X , X , removal of phenol (response Y ) given in Table 6 which 1 2 2 X , and X on responses Y and Y ) shows that effect of pH (X ), adsorbent dose (X ), and initial 3 4 1 2 1 2 concentration of phenol (X ) was highly significant. The RSM is a statistical method for the analysis of interactive effect of process variable X [initial concentration of Cr(VI)] effects of operating variables onto the response of interest. onto the percentage removal of phenol was not highly sig- The effects of independent process variables were evaluated nificant. Therefore, the percentage removal of Cr(VI) and by 3D plots shown in Fig. 4a, b for response Y [percentage phenol in the binary mixture using Fe-treated tea waste removal of Cr(VI)] and Fig. 5a, b for response Y (percent- biomass was not affected by the presence of each other. It can age removal of phenol). For response Y the linear effects of be concluded that Cr(VI) and phenol can be easily removed 1, the process variables X (pH), X (adsorbent dose), X (initial from binary mixture using Fe-treated tea waste biomass. The 1 2 3 2 2 2 2 concentration of Cr(VI) are highly significant, given in effects of X , X , X , and X onto the responses Y and Y were 1 2 3 4 1 2 123 Appl Water Sci (2017) 7:4361–4374 4369 Table 7 Results of ANOVA for the percentage removal of Cr(VI) using Fe-treated tea waste biomass Source Sum of squares DF Mean square F value P [ F Model 11,716.44 14 836.89 79.53 \0.0001 significant X 9406.88 1 9406.88 893.96 \0.0001 X 736.18 1 736.18 69.96 \0.0001 X 645.19 1 645.19 61.31 \0.0001 X 33.33 1 33.33 3.17 0.0968 X 239.91 1 239.91 22.80 0.0003 X 72.05 1 72.05 6.85 0.0203 X 450.41 1 450.41 42.80 \0.0001 X 136.31 1 136.31 12.95 0.0029 X X 48.93 1 48.93 4.65 0.0489 1 2 X X 42.32 1 42.32 4.02 0.0647 1 3 X X 12.25 1 12.25 1.16 0.2988 1 4 X X 0.25 1 0.25 0.024 0.8797 2 3 X X 20.25 1 20.25 1.92 0.1871 2 4 X X 144.00 1 144.00 13.68 0.0024 3 4 Residual 147.32 14 10.52 Lack of fit 147.32 10 14.73 Pure error 0.000 4 0.000 Cor total 11,863.76 28 Table 8 Results of ANOVA for the percentage removal of phenol using Fe-treated tea waste biomass Source Sum of squares DF Mean square F value P [ F Model 9281.24 14 662.95 50.11 \0.0001 significant X 5895.89 1 5895.89 445.64 \0.0001 X 849.92 1 849.92 64.24 \0.0001 X 60.75 1 60.75 4.59 0.0502 X 1825.33 1 1825.33 137.97 \0.0001 X 53.58 1 53.58 4.05 0.0638 X 14.61 1 14.61 1.10 0.3111 X 68.50 1 68.50 5.18 0.0391 X 205.27 1 205.27 15.51 0.0015 X X 56.18 1 56.18 4.25 0.0584 1 2 X X 30.25 1 30.25 2.29 0.1528 1 3 X X 64.00 1 64.00 4.84 0.0452 1 4 X X 6.25 1 6.25 0.47 0.5031 2 3 X X 12.25 1 12.25 0.93 0.3523 2 4 X X 72.25 1 72.25 5.46 0.0348 3 4 Residual 185.22 14 13.23 Lack of fit 185.22 10 18.52 Pure error 0.000 4 0.000 Cor total 9466.46 28 also appreciated. The combined effects of adsorbent dose L, and 99.99% removal of both Cr(VI) and phenol was and pH (X X ), initial concentration of Cr(VI), and initial obtained. The response surface curves were plotted, as 1 2 concentration of phenol (X X ) onto the responses Y and Y shown in Fig. 4a, b which depicts the effect of independent 3 4 1 2 were also observed. Based on the response surface design, it variables onto the percentage removal of Cr(VI). Figure 5a, is evident that at an initial concentration of 55 mg/L of b shows the effects of independent variables onto the per- Cr(VI), 27.50 mg/L of phenol, pH 2.0, adsorbent dose 15 g/ centage removal of phenol. The circular nature of the contour 123 4370 Appl Water Sci (2017) 7:4361–4374 Fig. 4 a 3D response surface plots showing the effects of (a) pH (b) adsorbent dose onto the percentage removal of Cr(VI). b 3D response surface plots showing the effects of (a) initial concentration of Cr(VI) and (b) initial concentration of phenol onto the percentage removal of Cr(VI) signifies that the effect of initial concentration of phenol onto were observed. The percentage removal of Cr(VI) and phe- the percentage removal of Cr(VI) and initial concentration of nol was decreased with increasing pH and increases with Cr(VI) onto the percentage removal of phenol was not sig- increase in adsorbent dose. The possible reason of these nificant, as shown in Figs. 4b and 5b, respectively. The phenomena is given below. percentage removal of Cr(VI) decreases with the increase in the initial concentration of Cr(VI) and percentage removal of Effect of pH onto the percentage removal of Cr(VI) phenol decreases with the increase in the initial concentra- and phenol tion of phenol. The effects of adsorbent dose, pH, and initial concentration of Cr(VI) onto the percentage removal of pH is an important parameter for the simultaneous Cr(VI) were found significant. Similar effects of these removal of Cr(VI) and phenol. At low pH value, the independent variables onto the percentage removal of phenol percentage removal of Cr(VI) and phenol was maximum, 123 Appl Water Sci (2017) 7:4361–4374 4371 Fig. 5 a 3D response surface plots showing the effects of (a) adsorbent dose and (b) pH onto the percentage removal of phenol. b 3D response surface plots showing the effects of (a) initial concentration of Cr(VI) and (b) initial concentration of phenol onto the percentage removal of phenol because at low pH value, the surface of Fe-treated tea this pH, the surface of biosorbent becomes negatively waste biomass becomes more protonated. At low pH, charged which repel the Cr(VI) and phenol anions. 2- - Cr(VI) was in the form of Cr O and HCrO , while Favorable adsorption occurs between pH (2–5). There was 2 7 4 phenol was present in the form of C H O (Chaudhary also a competition between negatively charged phenolate 6 5 and Balomajumder 2014). Therefore, there is a strong and chromate anions for adsorption to the vacant posi- electrostatic interaction between negatively charge chro- tively charged active sites. When all the vacant active mate, dichromate, and phenolate anions to the positively sites are filled, equilibrium was established between charged surface of Fe-treated tea waste biomass. At high negatively charged chromate and phenolate anions present pH value, after pH 6, a rapid decrease in the percentage in the synthetic binary solution and positively charged removal of Cr(VI) and phenol was observed, because at surface. 123 4372 Appl Water Sci (2017) 7:4361–4374 optimization, equilibrium, kinetics and thermodynamic studies. Effects of adsorbent dose onto the percentage removal J Taiwan Inst Chem Eng 49:156–164 of Cr(VI) and phenol Acar F, Malkoc NE (2004) The removal of chromium(VI) from aqueous solutions by Fagus orientalis L. 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J Taiwan Inst Chem Eng 45:852–859 responses Y [percentage removal of Cr(VI)] and Y (per- 1 2 Cronje KJ, Chetty K, Carsky M, Sahu JN, Meikap BC (2011) centage removal of phenol). A second-order quadratic Optimization of chromium(VI) sorption potential using devel- equation was developed to predict the effects of indepen- oped activated carbon from sugarcane bagasse with chemical dent variables onto the percentage removal of Cr(VI) and activation by zinc chloride. Desalination 275:276–284 De Sales PF, Magriotis ZM, Rossi MALS, Resende RF, Nunes CA phenol from binary mixture. The application of statistical (2013) Optimization by response surface methodology of the design using RSM for the adsorption of Cr(VI) and phenol adsorption of Coomassie Blue dye on natural and acid-treated from a binary mixture reduces the time and overall cost, clays. J Environ Manag 130:417–428 and improved the efficiency of the process. Dittert IM, Brandao HDL, Pina F, da Silva EAB, de Souza SMAGU, de Souza AAU, Botelho CMS, Boaventura RAR, Vilar VJP (2014) Integrated reduction/oxidation reactions and Acknowledgements The author is thankful to Chemical Engineering sorption processes for Cr(VI) removal from aqueous solutions department IIT Roorkee for the facility provided for research work using Laminaria digitata macro-algae. Chem Eng J and MHRD INDIA for financial support. 237:443–454 El-Sherif IY, Tolani S, Ofosu K, Mohamed OA, Wanekaya AK Open Access This article is distributed under the terms of the (2013) Polymeric nanofibers for the removal of Cr(III) from Creative Commons Attribution 4.0 International License (http:// tannery wastewater. 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Journal

Applied Water Science – Springer Journals

Published: Jun 24, 2017

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