SciFed Materials Research Letters

Optimization of Batch Biosorption of Cr(VI) and Cu(II) Ions from Wastewater using Bacillus subtilis

Research Article

Received on: August 26, 2017

Accepted on: September 09, 2017

Published on: September 22, 2017

Narasimhulu K

*Corresponding author: National Institute of Technology
India

Abstract

         The objective of this present study is to optimise the process parameters for batch biosorption of Cr(VI) and Cu(II) ions by Bacillus subtilis using Response Surface Methodology (RSM). Batch biosorption studies were conducted under optimum pH, temperature, biomass concentration and contact time for the removal of Cr(VI) and Cu(II) ions using Bacillus subtilis. From the studies it is noticed that the maximum biosorption of Cr(VI) and Cu(II) was by Bacillus subtilis at optimum conditions of contact time of 30 minutes, pH of 4.0, biomass concentration of 2.0 mg/mL, temperature of 320C in batch biosorption studies. Predicted percent biosorption of the selected heavy metal ions by the design expert software is in agreement with experimental results of percent biosorption. The percent biosorption of Cr(VI) and Cu(II) in batch studies is 80% and 78.4%, respectively.


Keywords


      Heavy metal ions; Response Surface Methodology; Bacillus subtilis; Biosorption; Wastewater; Optimization

FullText

Introduction
        Chromium compounds are widely used in various industries such as electroplating, leather tanning, mining, aluminium conversion coating, operation dyes and pigments [1, 2]. The indiscriminate discharge of chromium metals into water resources causes serious health effect to human and environment because of its toxic nature. Cr (VI) ions are highly toxic. Inhalation of Cr (VI) ions leads to the carcinogenetic problem. Other health effects of Cr (VI) ions are the skin allergy, liver and stomach problems [3]. Copper[Cu(II)] can be found in many wastewater sources including, printed circuit board manufacturing, electronics plating, wire drawing, copper polishing, paint manufacturing and in wood preservatives and printing operations. Typical concentrations vary from several thousand mg/L from plating bath waste to less than 1 ppm from copper cleaning operations. Copper[Cu(II)] is present in the wastewater of several industries, such as metal cleaning and plating baths, refineries, paper and pulp, fertiliser, and wood preservatives [4]. The excessive intake of copper by man leads to severe mucosal irritation, widespread capillary damage, hepatic and renal damage, central nervous problems followed by depression, gastrointestinal irritation, and possible necrotic changes in the liver and kidney [5]. Thus the removal of Cr(VI) and Cu(II) ions becomes mandatory. Design Expert is a piece of software designed to help with the design and interpretation of multi factor experiments. The software offers a wide range of designs, including factorials, fractional factorials and composite designs. Design Expert offers computer generated D-optimal designs for cases where standard designs are not applicable, or where we wish to augment an existing design - for example, to fit a more flexible model.


2. Materials and Methods


2.1 Biosorption Calculation
         The microorganism was isolated from NIT Warangal wastewater treatment plant and identified as Bacillus subtilis [6]. Biomass was harvested from the medium by centrifugation at 9000 rpm for 10 minutes. The supernatant was discarded and the cells were re-suspended in purified water for washing and again centrifuged as above to make sure that no media remain on the cell surface. The biomass was heated in a conventional hot air oven at 600C for 24 h. This biomass was used for the biosorption experiments. Both the biomasses were added in equal amounts for biosorption experiments with mixed culture. Different concentrations of biomass (pure/ mixed cultures) were combined with 100 mL of metal ion solution in 250 mL Erlenmeyer flask. The flasks were placed on a shaker with a constant speed of 300 rpm and left to equilibrate. Samples were collected at predefined time intervals, centrifuged as above and the amount of metal in the supernatant was determined.


2.2 Effect of Different Parameters on Metal Biosorption
           The metal ion sorption was monitored for pH ranging from 1.0 to 7.0. NaOH and HCL were used as pH regulators. 1 mg/mL biomass was dispersed in 100 mL of the solution containing 10 mg/L of each metal concentration. All flasks were maintained at different pH values ranging from 1.0 to 7.0 for about 12 hours. Solutions were centrifuged as above and the supernatant was analysed for the residual concentrations of the metal ions.


2.2 (b) Effect of Biomass Concentrations


         Biomass was centrifuged at 9000 rpm and different weights of the biomass ranging from 0.5 to 3.5 mg/mL were dispersed in solutions containing 10 mg/L metal ion concentration. The solutions were adjusted to the optimum pH in which maximum biosorption of the metal ion occurred. Flasks were left for equilibration. The solutions were later centrifuged at 9000 rpm and the metal ion concentrations were determined using the procedures described earlier.

2.2 (c) Effect of Temperatures
         Optimum biomass concentration with optimum pH was used to monitor the temperature effect on biosorption. Experiments were carried out at different temperatures ranging from 10 to 50oC for each culture and kept on rotary shaker at 240 rpm. The samples were allowed to attain equilibrium. The sample was collected at regular intervals and was analysed for metal ion concentration.

2.2 (d) Effect of Contact Time
           The cells were dispersed in metal ion solution of 10 mg/L concentration with a working volume of 100 mL. The experiment was carried out at the optimum pH value of the system. Flasks were allowed to attain equilibrium on rotary shaker at 240 rpm and samples were collected at regular time intervals of the range from 5-35 minutes. Centrifugation at 9000 rpm was done and the supernatant was analyzed for the residual metal ion content.

2.4 Optimisation of Biosorption parameters using Response Surface Methodology (RSM)
          Response surface methodology (RSM) is a collection of mathematical and statistical techniques useful for analyzing the effects of several independent variables on the response [7]. RSM has an important application in the process analysis and optimization as well as the improvement of existing design. Response surface methodology (RSM) is one of the experimental designing methods which can surmount the limitations of conventional methods collectively [8]. RSM is a combination of mathematical and statistical techniques used to determine the optimum operational conditions of the process or to determine a region that satisfies the operating specifications [9]. The main advantage of RSM is the reduced number of experimental trials needed to evaluate multiple parameters and their interactions [10]. The parameters pH, Biomass concentration, Temperature, and Time were optimised for batch biosorption studies and the optimised parameters of pH and temperature were used for continuous packed bed bioreactor studies. The experiments were conducted based on central composite design (CCD). The experimental design employed in the screening of each variable consists of two levels and four independent variables.


3. Results and Discussion


3.1 Optimisation of Operating Parameters in Batch Biosorption Studies using Response Surface Methodology
         From the experimental work, it is seen that the optimum parameters for batch biosorption studies are pH equal to 4.0, biomass concentration of 2.0 mg/mL, temperature of 32oC and contact time of 30 minutes. Optimisation results of Cr(VI) and Cu(II) by Bacillus subtilis from the Design Expert software were obtained as pH equal to 3.98, biomass concentration of 2.08 mg/ mL, temperature of 32.07oC and contact time of 30.24 minutes. The percent biosorption of Cr(VI) and Cu(II) is 80% and 78.4% respectively. Experimental values closely agree with the values obtained from the response surface methodology, confirming that the RSM using the statistical design of experiments could be effectively used to optimise the process parameters and to study the importance of individual, cumulative and interactive effects of the test variables in biosorption.

3.2 Optimisation of Operating Conditions for the Biosorption of Cr(VI) and Cu(II) by Bacillus Subtilis
         The experimental data obtained in batch biosorption of Cr(VI) and Cu(II) by Bacillus subtilis is used as the basis in the design of experiments using Design Expert software (shown in Table 1).

Table 1: Experimental Data of the Effect of Process Parameters on the Percent Removal of Cr(VI) and Cu(II) by Bacillus Subtilis


          Regression analysis was performed to fit the response functions, i.e. percentage biosorption of Cr(VI) and Cu(II). The regression models developed represent responses as functions of contact time(A), pH(B), biomass concentration(C) and temperature(D). An empirical relationship between the response and three input variables expressed by the following response surface reduced quadratic model equations 2 and 3 in coded terms for the percent biosorption of each heavy metal ion:

        %Cr(VI) = 67.05 + 0.22A -1.75B + 1.72C + 1.94D + 0.81AB + 0.94AC + 1.12AD + 0.87AD + 1.06BD + 0.68CD + 9.39A2- 15.35B2- 2.61C2- 9.11D2 (2)
%Cu(II) = 75.8903 + 3.8333A - 2.23611B + 0.8472C + 1.4166D + 0.5937AB + 0.9687AC + 1.375AD + 0.5937BC + 1BD + 0.5625CD - 3.6140A2 - 15.239B2 - 1.9890C2 -10 .114D2 (3)

       Positive sign in front of these terms represents synergistic effect, while negative sign represents antagonistic effect. The coefficients with one factor of contact time(A), pH(B), biomass concentration(C) and temperature(D) represent the effect of that particular factor for the preparation of biosorbent. The coefficients with two factors and others with second order terms show the interaction between the two factors and quadratic effect, respectively.

         These equations reveal how the individual variables (linear and quadratic) or double interaction affected Cr(VI) and Cu(II) biosorption from wastewater on Bacillus subtilis biomass. Negative coefficient values indicate that individual or double interaction factors negatively affect percent biosorption (i.e. removal percentage decreases), whereas positive coefficient values mean that factors increase Cr(VI) and Cu(II) removal in the tested range. For instance, among all linear factors, pH had a negative effect, while contact time, biomass concentration and temperature had a positive effect on Cr(VI) and Cu(II) biosorption (Eq. 2 and 3). The most important individual effect was the temperature (P< 0.0001) for Cr(VI) biosorption and time (P<0.0001) for Cu(II) biosorption.

         In addition, the most important double effect on Cr(VI) biosorption was the interaction between time and temperature, which was significant (P=0.0068). The second most important effect is the interaction between temperature and pH (P= 0.0096). The most important double effect on Cu(II) biosorption was the interaction between time and temperature, which was significant (P=0.0018). The second most important effect is the interaction between temperature and pH (P= 0.0149) shown in Table 2.

          A high value of the adjusted determination coefficient (Adjusted R2 = 0.9792 for Cr(VI) and 0.9902 for Cu(II)) was estimated. This result means that 97% of the total variation on Cr(VI) biosorption and 99% of the total variation on Cu(II) data (Table 3 and Table 4) can be described by the selected model. The adequate precision ratio of 35.76[Cr(VI)] and 39.12[Cu(II)], for the quadratic model, indicates an appropriated signal to noise ratio. Because the adjusted determination coefficient and adequate precision ratio exceeded 70% and 4.0, respectively, the quadratic model can be used to explore the design space and to find the optimal conditions of this process. A contour plot is a graphic representation of the relationships among three numeric variables in two dimensions. Two variables are for X and Y axes, and a third variable Z is for contour levels. The contour levels are plotted as curves; the area between curves can be color coded to indicate interpolated values. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.

        Experiments were conducted at established optimum conditions and results were reproduced. The results were in agreement with the predicted results (shown in table 5).

Table 2: Experimental Design and Results of Percent Biosorption of Cr(VI) and Cu(II) by Bacillus Subtilis



Table 3: Analysis of Variance for the Quadratic Model for Cr(VI) Biosorption by Bacillus Subtilis
 
 

Table 4: Analysis of Variance for the Quadratic Model for Cu(II) Biosorption by Bacillus subtilis



Table 5: Optimised Values Established by Design Expert for the Biosorption of Cr(VI) and Cu(II) by Bacillus subtilis   

        Adinarayana and Ellaiah [11] have reported that the 3D response surface plots as a function of two factors, with all of the other factors fixed, were helpful in understanding both the main effects and the interaction effects of these two factors. In addition to the 3D response surfaces, their corresponding contour plots facilitated the straightforward examination of the effects of the experimental variables on the response [12].

          As shown in Figures 1-3, 3D response surface plots for the measured responses were formed based on the model equation (Eq. (2)) in order to gain a better understanding of the interaction effect of these flotation variables. The relationship between the dependent and independent variables was also further elucidated through the construction of these contour plots. One variable was held at constant at the center level for each plot. Therefore, a total of three response 3D plots and three corresponding contour plots were produced for the responses.

Figure 1: Response Surface Contour Plot showing Interactive Effect of Time and pH on the removal of Cr(VI) at Constant Biomass Concentration of2.0 mg/mL and Temperature of 30oC  


Figure 2: Response Surface Contour Plot Showing Interactive Effect of Time and Biomass Concentration on the Removal of Cr(VI) at Constant pH of 4.0 and Temperature of 30oC


Figure 3: Response Surface Contour Plot Showing Interactive Effect of Time and Temperature on the Removal of Cr(VI) at Constant pH of 4.0 and Biomass Concentration 2.0 mg/mL
 

Figure 4: Response Surface 3D Plot Indicating the Effect of Interaction between pH and Biomass Concentration on Cr(VI) Removal while Holding Time at its Design Center Point of 20 minutes and Temperature at 300C by Bacillus subtilis


          Figure 4 shows the 3D response surface relationship between pH and biomass concentration (BMC) on the Cr(VI) percent biosorption at the center level of the time 20 minutes and temperature 300C by Bacillus subtilisThe percent biosorption of Cr(VI) increased as the pH increased up to 4.0, then gradually decreased. The percent biosorption of Cr(VI) was best at around 2 mg/mL of biomass concentration. The 3D response surface relationship between pH and temperature, biomass concentration and temperature is also shown in Figures 5 and 6. The same trend was observed in all these combination of variables.

Figure 5: Response Surface 3D Plot Indicating the Effect of Interaction between pH and Temperature on Cr(VI) Removal while Holding Time at its Design Center Point of 20 minutes and Biomass Concentration at 2.0 mg/mL by Bacillus subtilis


Figure 6: Response Surface 3D Plot Indicating the Effect of Interaction between Biomass Concentration and Temperature on Cr(VI) Removal while Holding Time at its Design Center Point of 20 minutes and pH at 4.0 by Bacillus subtilis

  
           The sensitive response to the pH relates likely to the nature of the cellular surface. The bacterial cell wall contains several functional groups including carboxyl, phosphate, amine and hydroxyl groups. The amine group present in the bacterial biomass surface has its pKa value at around 2 to 4. This reflects that the biomass amines are partially protonated at pH 4.0 and as the pH increases, its positive charge will decrease. As the pH increased more than 4.0 the physical adsorption of Cr(VI) onto the biomass surface may be promoted, leading to enhanced sorption performance. That is possibly why there was an optimum at around pH 4.0.

Figure 7: Response Surface Contour Plot showing Interactive Effect of Time and pH on the Removal of Cu(II) at Constant Biomass Concentration of 2.0 mg/mL and Temperature of 30oC


Figure 8:  Response Surface Contour Plot Showing Interactive Effect of Time and Biomass Concentration on the Removal of Cu(II) at Constant pH of 4.0 and Temperature of 30oC



Figure 9:  Response Surface Contour Plot Showing Interactive Effect of Time and Temperature on the Removal of Cu(II) at Constant pH of 4.0 and Biomass Concentration 2.0 mg/mL
  

Figure 10: 
Response Surface 3D Plot Indicating the Effect of Interaction Between pH and Biomass Concentration on Cu(II) Removal while 
Holding Time at its Design Center Point of 20 minutes and Temperature at 300C by Bacillus subtilis
  
 

Figure 11: Response Surface 3D Plot Indicating the Effect of Interaction between pH and Temperature on Cu(II) Removal while Holding Time at its Design Center Point of 20 minutes and Biomass Concentration at 2.0 mg/mL by Bacillus subtilis


Figure 12: Response Surface 3D Plot Indicating the Effect of Interaction between Biomass Concentration and Temperature on Cu(II) Removal while Holding Time at its Design Center Point of 20 minutes and pH at 4.0 by Bacillus subtilis

 
         From the Figures 7 to 12 it was observed that with the increase in pH from 4.0 to 7.0, the degree of protonation of the adsorbent functional group decreased gradually and hence removal was decreased. A close relationship between the surface basicity of the adsorbents and the anions is evident [13]. This is similar to the findings of others, where the interaction between oxygen-free Lewis basic sites and the free electrons of the anions, as well as the electrostatic interactions between the anions. The protonated sites of the adsorbent are the main adsorption mechanism [14].

          Experiments were carried out at established optimum conditions of contact time of 30.24 minutes, pH of 3.98, biomass concentration of 2.08 mg/mL and temperature of 32.07oC and results were reproduced and they were in agreement with the predicted results. Earlier studies showed that the biosorption of Chromium (VI) showed that 77.6% for mixed cultures of Pseudomonas aeruginosa and Bacillus subtilis [15].

4. Conclusions
            The present study showed that the maximum biosorption of Cr(VI) and Cu(II) was by Bacillus subtilis at optimum conditions of contact time of 30 minutes, pH of 4.0, biomass concentration of 2.0 mg/mL, temperature of 32oC in batch biosorption studies. In batch biosorption studies the effect of pH on the selected heavy metals was studied. Using Bacillus subtilis the biosorption of Cr(VI) and Cu(II) was found to be 84% and 80% respectively at pH of 4.0. The maximum biosorption for Cr(VI) and Cu(II) was 80% and 80% respectively at the biomass concentration of 2.0 mg/mL. The maximum biosorption for Cr(VI) and Cu(II) was 82% and 82% respectively at the temperature of 32oC.

          The equilibrium time was 30 minutes for Cr(VI) and Cu(II) at which percent biosorption was 82% and 81% respectively. From the batch biosorption experimental work, it is seen that the optimum parameters for batch biosorption studies are pH equal to 4.0, biomass concentration of 2.0 mg/ mL, temperature of 32oC and contact time of 30 minutes. Optimisation results of Cr(VI) and Cu(II) by Bacillus subtilis from the Design Expert software were obtained as pH equal to 3.98, biomass concentration of 2.08 mg/mL, temperature of 32.07oC and contact time of 30.24 minutes. The percent biosorption of Cr(VI) and Cu(II) is 80% and 78.4% respectively. Batch biosorption experiments were carried out at established optimum conditions (using Response Surface Methodology) of contact time of 30.24 minutes, pH of 3.98, biomass concentration of 2.08 mg/ mL and temperature of 32.07oC and results of biosorption of Cr(VI) and Cu(II) were reproduced and they were in agreement with the predicted results. It was observed that the Bacillus subtitles was suitable species to remove Cr(VI) and Cu(II) from wastewater.

References

  1. Rivera Utrilla JI, Bautista Toledo MA, Ferro Garcıa, et al. (2003) Bioadsorption of Pb (II), Cd (II), and Cr (VI) on activated carbon from aqueous solutions. Carbon 41: 323-330.
  2. Garg UK, Kaur MP, Dhiraj Sud, et al. (2009) Removal of hexavalent chromium from aqueous solution by adsorption on treated sugarcane bagasse using response surface methodological approach. Desalination 249: 475-479.
  3. Owlad, Mojdeh, Aroua MK, et al. (2009) Removal of hexavalent chromium-contaminated water and wastewater: a review. Water, Air, and Soil Pollution 200: 59-77.
  4. Periasamy K, Namasivayam C (1996) Removal of copper (II) by adsorption onto peanut hull carbon from water and copper plating industry wastewater. Chemosphere 32: 769-789.
  5. Kalavathy M, Helen T, Karthikeyan S, et al. (2005) Kinetic and isotherm studies of Cu (II) adsorption onto H3PO4- activated rubber wood sawdust. J Colloid Interface Sci 292: 354-362.
  6. Narasimhulu K , Rao PS, Vinod AV (2010) Isolation and Identification of Bacterial Strains and Study of their Resistance to Heavy Metals and Antibiotics. J Microbial Biochem Technol 2: 74-76.
  7. Bas D, Boyacı İH (2007) Modelling and optimization I: Usability of response surface methodology. J Food Eng 78: 836- 845.
  8. Olmez, Tugba (2009) The optimization of Cr (VI) reduction and removal by electro coagulation using response surface methodology. J Hazard Mater 162: 1371-1378.
  9. Alam, Zahangir, Suleyman AM, et al. (2007) Statistical optimization of adsorption processes for removal of 2, 4-dichlorophenol by activated carbon derived from oil palm empty fruit bunches. J Environ Sci 19: 674-677.
  10. Karacan F, Ozden U, Karacan S (2007) Optimisation of manufacturing conditions for activated carbon from Turkish lignite by chemical activation using response surface methodology. Appl Therm Eng 27: 1212-1218.
  11. Adinarayana K, Ellaiah P (2002) Response surface optimisation of the critical medium components for the production of alkaline protease by a newly isolated Bacillus sp. J Pharm Sci 5: 281-287.
  12. Wu D, Zhou J, Li Y (2009) Effect of the sulfidation process on the mechanical properties of a CoMoP/Al2O3 hydrotreating catalyst. Chem Eng Sci 64: 198-206.
  13. Leon y Leon CA, Solar JM, Calemma V, et al. (1992) Evidence for the protonation of basal plane sites on carbon. Carbon 30: 797-811.
  14. Faria PCC, Orfao JJM, Pereira MFR (2004) Adsorption of anionic and cationic dyes on activated carbons with different surface chemistries. Water Research 38: 2043-2052.
  15. Narasimhulu K, Pydi Setty Y (2012) Batch Studies on Biosorption of Chromium from Wastewater using Bacterial Cultures. IJERD 3: 50-58.

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