Volume 6, Issue 2 (June 2021)
J Environ Health Sustain Dev 2021, 6(2): 1275-1283 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Dolatabadi M, Malekahmadi R, Ghorbanian A, Ahmadzadeh S. Investigation of Electrocoagulation Process for Efficient Removal of Bisphenol A from the Aqueous Environment: Promising Treatment Strategy. J Environ Health Sustain Dev 2021; 6 (2) :1275-1283
URL: http://jehsd.ssu.ac.ir/article-1-333-en.html
URL: http://jehsd.ssu.ac.ir/article-1-333-en.html
Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
Keywords: Bisphenol A, Electrocoagulation Process, Aqueous Environment, Response Surface Methodology, Treatment.
Full-Text [PDF 1069 kb]
(461 Downloads)
| Abstract (HTML) (1281 Views)
.png)
Figure 1: (A) Predicted values versus actual values and (B) normal probability plot of studentized residuals' model for the proposed model
.png)
Figure 2: Contour and 3D surface plot for the combined effect of BPA concentration and current density
.png)
Figure 3: 3D surface plot for the combined effect of BPA concentration and pH.
.png)
Figure 4: Contour and 3D surface plot for the combined effect of current density and reaction time Optimization process
Full-Text: (439 Views)
Investigation of Electrocoagulation Process for Efficient Removal of Bisphenol A from the Aqueous Environment: Promising Treatment Strategy
Maryam Dolatabadi 1,2, Roya Malekahmadi 2, Akram Ghorbanian 3, Saeid Ahmadzadeh 4, 5*
1 Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran.
2 Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
3 Department of Environmental Health, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
4 Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
5 Pharmaceutical Sciences and Cosmetic Products Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Maryam Dolatabadi 1,2, Roya Malekahmadi 2, Akram Ghorbanian 3, Saeid Ahmadzadeh 4, 5*
1 Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran.
2 Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
3 Department of Environmental Health, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
4 Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
5 Pharmaceutical Sciences and Cosmetic Products Research Center, Kerman University of Medical Sciences, Kerman, Iran.
| A R T I C L E I N F O | ABSTRACT | |
| ORIGINAL ARTICLE | Introduction: Endocrine disruptive compounds as a class of organic contaminants in the aquatic environment received severe attention in the last decades. The release of bisphenol A (BPA) as a hazardous organic chemical into the environment has caused high health and environmental concerns. Therefore, its removal from aquatic environments is strongly recommended. The present study deals with BPA removal efficiency from an aqueous environment using the electrocoagulation process (ECP). Materials and Methods: The effects of parameters including BPA concentration (1-10 mg L-1), current density (3-15 mA cm-2), pH (4-10), and reaction time (5-30 min) on the treatment process were investigated. Response surface methodology (RSM) was employed for optimization of the ECP. The significance of the developed model was investigated by the obtained F-value and P-value. Results: The maximum BPA removal of 98.2% was attained at pH of 8.5, BPA concentration of 3.25 mg L-1, the current density of 12.0 mA cm-2, and reaction time of 23 min. The significance of the developed model was confirmed by the high F-value of 46.69 and the very low P-value of < 0.0001. Furthermore, the electrical energy consumption of the process was found to be 0.308 kWh m-3 in the optimum condition. Conclusion: The obtained experimental results revealed that the co-precipitation and the adsorption process through the electrostatic interactions as the main removal mechanisms controlled the treatment process. |
|
| Article History: Received: 10 March 2021 Accepted: 20 April 2021 |
||
| *Corresponding Author: Saeid Ahmadzadeh Email: chem_ahmadzadeh@yahoo.com saeid.ahmadzadeh@kmu.ac.ir Tel: +983431325241 |
||
| Keywords: Bisphenol A, Electrocoagulation Process, Aqueous Environment, Response Surface Methodology, Treatment. |
Citation: Dolatabadi M, Malekahmadi R, Ghorbanian A. Investigation of Electrocoagulation Process for Efficient Removal of Bisphenol A from the Aqueous Environment: Promising Treatment Strategy. J Environ Health Sustain Dev. 2021; 6(2): 1275-83.
Introduction
Recently, new chemical compounds have entered the environment through industrial, agricultural, and other human activities, which caused disruption of the endocrine and subsequently several emerging diseases in human societies. Bisphenol A (BPA) is a well-known one of the emerging pollutants produced and consumed in large volumes annually (38×105 tons per year). BPA is used in various industries to produce polysulfones, polycarbonates, plastic precursors, and epoxy resins 1-3. The US environmental protection agency (EPA) and the European Chemical Agency (ECHA) have identified BPA as a hazardous compound with a very high-risk threat to human health and the environment 1.
The excessive use of BPA in industrial activities has led to its widespread distribution in various environments, including soil, water, air, sediments, human tissues, and others 4, 5. Some studies have reported the amount of BPA in the river waters and coastal waters (≥ 1 μg L-1), stored water (915–1415 μg L-1), groundwater (96.5–170 μg L-1), and landfill leachates (≥ 17 mg L-1) 6, 7. Studies have revealed that BPA may cause some diseases and disturb hormone function, such as increased sexual dysfunction, sperm count reduction, premature puberty, obesity prevalence, diabetes, brain function disorder, immunodeficiency, hypothyroidism, and hyperthyroidism, breast and prostate cancer, and others. 8-10.
Due to the widespread use of BPA in industrial activities and its essential role in the global market, it seems impossible to prevent its production. Therefore, one of the approaches to prevent and reduce the effects of BPA on human’s health and the environment is to effectively treat BPA-contaminated wastewater before discharging it to the environment 4. During the ECP, coagulation agents are generated by connecting the electric current between the anode and cathode electrodes (iron or aluminum) in electrolytic cell 11, 12. The coagulation agents (metal hydroxides) generated during the ECP in the electrolytic cell, through flotation and precipitation, removed pollutants. Hydrolysis, electrolysis (formation of the coagulant), and ionization are the relevant reactions that pollutants can experience at this stage 13, 14. It is recognized that three stages are involved in ECP formation of the coagulant by oxidation of the metal at the anode, destabilization of pollutants and emulsions, and finally, forming of flocs by either aggregation of contaminant particles or adsorption of the contaminant on the coagulant 15, 16.
ECP has extensively been employed due to its efficient treatment of various types of wastewater, including wastewater containing dyes 17, heavy metals 18, and pharmaceutical compounds 19, 20. The ECP has several advantages, including simple operation, less waste sludge, low use of chemicals, short purification time, low capital costs, and considerable efficiency in wastewater treatment 21. In the current work, great attempts were made to develop an efficient treatment procedure. The effects of various parameters, including BPA initial concentration, the current density, pH, and reaction time, on the BPA removal efficiency, were investigated.
Materials and Methods
Bisphenol A ((CH3)2C(C6H4OH)2) was obtained from Sigma-Aldrich. Sodium hydroxide (NaOH), potassium chloride (KCl), hydrochloric acid (HCl), and HPLC grade methanol (CH3OH) were obtained from Merck. All solutions were prepared with double-distilled water.
Treatment procedure
Plexiglas reactor with a useful volume of 250 mL and two aluminum electrodes with immersed dimensions of 4 cm × 2 cm × 1 mm were employed. By applying the direct current (Megatek power supply 30D5), the desired current density was adjusted. The constant electrode inter distance of 2.5 cm and 50 mM KCl electrolyte were considered during the treatment process. The pH of the samples was adjusted using NaOH and HCl. The residual of BPA in the treated samples was evaluated using HPLC system (Knauer Smartline) by C18 column (250 mm × 4.6 mm × 5.0 μm) and employing isocratic elution of methanol and water (30:70) with a flow rate of 1.2 mL min-1, the temperature of 30 °C, and wavelength set at 276 nm. The removal of the BPA and the electrical energy consumption were calculated using Eq. 1 and Eq. 2, respectively 22-24:
Where CI and CF (mg L‒1) denote the BPA concentration before and after the ECP, respectively. U, I, t, and V denote the applied voltage (V), electrical current (A), reaction time (h), and the volume of sample (L), respectively.
Process variables and experimental design
The design of the treatment process was performed by design expert software. Response surface methodology (RSM) was employed to evaluate the association between the variables. The BPA concentration (X1), current density (X2), pH (X3), and reaction time (X4) were considered as the independent variables. Also, the removal efficiency of BPA was considered as the response of the developed model. The level of -α, -1, 0, + 1, and + α for all variables was demonstrated in table 1.
Recently, new chemical compounds have entered the environment through industrial, agricultural, and other human activities, which caused disruption of the endocrine and subsequently several emerging diseases in human societies. Bisphenol A (BPA) is a well-known one of the emerging pollutants produced and consumed in large volumes annually (38×105 tons per year). BPA is used in various industries to produce polysulfones, polycarbonates, plastic precursors, and epoxy resins 1-3. The US environmental protection agency (EPA) and the European Chemical Agency (ECHA) have identified BPA as a hazardous compound with a very high-risk threat to human health and the environment 1.
The excessive use of BPA in industrial activities has led to its widespread distribution in various environments, including soil, water, air, sediments, human tissues, and others 4, 5. Some studies have reported the amount of BPA in the river waters and coastal waters (≥ 1 μg L-1), stored water (915–1415 μg L-1), groundwater (96.5–170 μg L-1), and landfill leachates (≥ 17 mg L-1) 6, 7. Studies have revealed that BPA may cause some diseases and disturb hormone function, such as increased sexual dysfunction, sperm count reduction, premature puberty, obesity prevalence, diabetes, brain function disorder, immunodeficiency, hypothyroidism, and hyperthyroidism, breast and prostate cancer, and others. 8-10.
Due to the widespread use of BPA in industrial activities and its essential role in the global market, it seems impossible to prevent its production. Therefore, one of the approaches to prevent and reduce the effects of BPA on human’s health and the environment is to effectively treat BPA-contaminated wastewater before discharging it to the environment 4. During the ECP, coagulation agents are generated by connecting the electric current between the anode and cathode electrodes (iron or aluminum) in electrolytic cell 11, 12. The coagulation agents (metal hydroxides) generated during the ECP in the electrolytic cell, through flotation and precipitation, removed pollutants. Hydrolysis, electrolysis (formation of the coagulant), and ionization are the relevant reactions that pollutants can experience at this stage 13, 14. It is recognized that three stages are involved in ECP formation of the coagulant by oxidation of the metal at the anode, destabilization of pollutants and emulsions, and finally, forming of flocs by either aggregation of contaminant particles or adsorption of the contaminant on the coagulant 15, 16.
ECP has extensively been employed due to its efficient treatment of various types of wastewater, including wastewater containing dyes 17, heavy metals 18, and pharmaceutical compounds 19, 20. The ECP has several advantages, including simple operation, less waste sludge, low use of chemicals, short purification time, low capital costs, and considerable efficiency in wastewater treatment 21. In the current work, great attempts were made to develop an efficient treatment procedure. The effects of various parameters, including BPA initial concentration, the current density, pH, and reaction time, on the BPA removal efficiency, were investigated.
Materials and Methods
Bisphenol A ((CH3)2C(C6H4OH)2) was obtained from Sigma-Aldrich. Sodium hydroxide (NaOH), potassium chloride (KCl), hydrochloric acid (HCl), and HPLC grade methanol (CH3OH) were obtained from Merck. All solutions were prepared with double-distilled water.
Treatment procedure
Plexiglas reactor with a useful volume of 250 mL and two aluminum electrodes with immersed dimensions of 4 cm × 2 cm × 1 mm were employed. By applying the direct current (Megatek power supply 30D5), the desired current density was adjusted. The constant electrode inter distance of 2.5 cm and 50 mM KCl electrolyte were considered during the treatment process. The pH of the samples was adjusted using NaOH and HCl. The residual of BPA in the treated samples was evaluated using HPLC system (Knauer Smartline) by C18 column (250 mm × 4.6 mm × 5.0 μm) and employing isocratic elution of methanol and water (30:70) with a flow rate of 1.2 mL min-1, the temperature of 30 °C, and wavelength set at 276 nm. The removal of the BPA and the electrical energy consumption were calculated using Eq. 1 and Eq. 2, respectively 22-24:
Where CI and CF (mg L‒1) denote the BPA concentration before and after the ECP, respectively. U, I, t, and V denote the applied voltage (V), electrical current (A), reaction time (h), and the volume of sample (L), respectively.
Process variables and experimental design
The design of the treatment process was performed by design expert software. Response surface methodology (RSM) was employed to evaluate the association between the variables. The BPA concentration (X1), current density (X2), pH (X3), and reaction time (X4) were considered as the independent variables. Also, the removal efficiency of BPA was considered as the response of the developed model. The level of -α, -1, 0, + 1, and + α for all variables was demonstrated in table 1.
Table 1: Level of independent variables for the BPA removal
| Variables (Xi) | Level | ||||
| -α | -1 | 0 | +1 | +α | |
| (A), X1 = BPA concentration (mg L-1) | 1.0 | 3.2 | 5.5 | 7.7 | 10.0 |
| (B), X2 = Current density (mA cm-2) | 3.0 | 6.0 | 9.0 | 12.0 | 15.0 |
| (C), X3 = Solution pH | 4.0 | 5.5 | 7.0 | 8.5 | 10.0 |
| (D), X4 = Reaction time (min) | 5.0 | 11.2 | 17.5 | 23.7 | 30.0 |
The polynomial regression equation of Eq. 3 was employed to predict the removal efficiency of contaminant by considering the input variables 23, 24.
Where Y denotes the predicted response of contaminant removal efficiency. The parameters of Xi and Xj denote the coded values of independent factors. The coefficient parameters of β0 (the intercept parameter), βi (the linear coefficients), βii (the quadratic coefficients), and βij (the interaction coefficients) expressed in the mentioned equation. The parameters of n and ɛ denote the investigated independent variables and the experimental error, respectively.
Ethical issue
The current work was conducted in the spring of 2018, after receiving approval from the ethics committee of Kerman University of Medical Sciences [IR.KMU.REC.1397.385].
Results
Fit Model Analysis and Analysis of variance (ANOVA)
According to the experimental design, 30 experiments were conducted to find out the optimum treatment condition and to understand the effect of the main operating parameters of X1 (BPA concentration), X2 (current density), X3 (solution pH), and X4 (reaction time) on the removal efficiency of BPA. The obtained results are given in table 2.
Where Y denotes the predicted response of contaminant removal efficiency. The parameters of Xi and Xj denote the coded values of independent factors. The coefficient parameters of β0 (the intercept parameter), βi (the linear coefficients), βii (the quadratic coefficients), and βij (the interaction coefficients) expressed in the mentioned equation. The parameters of n and ɛ denote the investigated independent variables and the experimental error, respectively.
Ethical issue
The current work was conducted in the spring of 2018, after receiving approval from the ethics committee of Kerman University of Medical Sciences [IR.KMU.REC.1397.385].
Results
Fit Model Analysis and Analysis of variance (ANOVA)
According to the experimental design, 30 experiments were conducted to find out the optimum treatment condition and to understand the effect of the main operating parameters of X1 (BPA concentration), X2 (current density), X3 (solution pH), and X4 (reaction time) on the removal efficiency of BPA. The obtained results are given in table 2.
Table 2: Experimental results of BPA removal
| Run | Actual value | Coded value | Experimental removal (%) | Experimental removal (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| A (mg L-1) |
B (mA cm-2) |
C | D (min) |
X1 | X2 | X3 | X4 | |||
| 1 | 5.5 | 9 | 7 | 17 | 0 | 0 | 0 | 0 | 71.6 | 70.8 |
| 2 | 3.25 | 12 | 5.5 | 23 | -1 | 1 | -1 | 1 | 79.4 | 80.1 |
| 3 | 7.75 | 12 | 8.5 | 23 | 1 | 1 | 1 | 1 | 85.2 | 84.7 |
| 4 | 7.75 | 6 | 5.5 | 23 | 1 | -1 | -1 | 1 | 58.2 | 58.9 |
| 5 | 3.25 | 6 | 8.5 | 11 | -1 | -1 | 1 | -1 | 76.5 | 75.8 |
| 6 | 7.75 | 6 | 5.5 | 11 | 1 | -1 | -1 | -1 | 54.7 | 54.5 |
| 7 | 5.5 | 3 | 7 | 17 | 0 | -2 | 0 | 0 | 64.8 | 64.1 |
| 8 | 7.75 | 6 | 8.5 | 11 | 1 | -1 | 1 | -1 | 66.1 | 66.7 |
| 9 | 5.5 | 9 | 10 | 17 | 0 | 0 | 2 | 0 | 84.2 | 85.1 |
| 10 | 7.75 | 12 | 8.5 | 11 | 1 | 1 | 1 | -1 | 75.8 | 76.3 |
| 11 | 5.5 | 9 | 7 | 17 | 0 | 0 | 0 | 0 | 71.1 | 70.5 |
| 12 | 5.5 | 15 | 7 | 17 | 0 | 2 | 0 | 0 | 83.4 | 83.7 |
| 13 | 1 | 9 | 7 | 17 | -2 | 0 | 0 | 0 | 89.7 | 88.3 |
| 14 | 3.25 | 12 | 8.5 | 23 | -1 | 1 | 1 | 1 | 94.3 | 94.8 |
| 15 | 3.25 | 6 | 5.5 | 23 | -1 | -1 | -1 | 1 | 65.2 | 65.1 |
| 16 | 10 | 9 | 7 | 17 | 2 | 0 | 0 | 0 | 60.1 | 60.5 |
| 17 | 5.5 | 9 | 4 | 17 | 0 | 0 | -2 | 0 | 56.1 | 55.4 |
| 18 | 3.25 | 12 | 8.5 | 11 | -1 | 1 | 1 | -1 | 75.7 | 57.1 |
| 19 | 3.25 | 6 | 5.5 | 11 | -1 | -1 | -1 | -1 | 65.0 | 65.7 |
| 20 | 7.75 | 6 | 8.5 | 23 | 1 | -1 | 1 | 1 | 71.9 | 72.4 |
| 21 | 5.5 | 9 | 7 | 5 | 0 | 0 | 0 | -2 | 47.2 | 47.8 |
| 22 | 3.25 | 12 | 5.5 | 11 | -1 | 1 | -1 | -1 | 69.2 | 69.7 |
| 23 | 7.75 | 12 | 5.5 | 23 | 1 | 1 | -1 | 1 | 69.1 | 69.4 |
| 24 | 5.5 | 9 | 7 | 30 | 0 | 0 | 0 | 2 | 67.5 | 67.1 |
| 25 | 3.25 | 6 | 8.5 | 23 | -1 | -1 | 1 | 1 | 84.5 | 84.0 |
| 26 | 7.75 | 12 | 5.5 | 11 | 1 | 1 | -1 | -1 | 61.3 | 61.9 |
| 27 | 5.5 | 9 | 7 | 17 | 0 | 0 | 0 | 0 | 72.1 | 72.5 |
| 28 | 5.5 | 9 | 7 | 17 | 0 | 0 | 0 | 0 | 71.4 | 72.0 |
| 29 | 5.5 | 9 | 7 | 17 | 0 | 0 | 0 | 0 | 72.8 | 71.6 |
| 30 | 5.5 | 9 | 7 | 17 | 0 | 0 | 0 | 0 | 71.2 | 71.6 |
Based on the performed runs, the following model was developed by RSM as a function of main operating parameters within the designated range.
In this equation, Y is the removal rate of BPA (%), and X1 to X4 represents the coded independent factors of BPA concentration, the current density, pH, and reaction time, respectively. The adequacy of the proposed model was investigated using the analysis of variance (ANOVA) test and summarized in table 3.
In this equation, Y is the removal rate of BPA (%), and X1 to X4 represents the coded independent factors of BPA concentration, the current density, pH, and reaction time, respectively. The adequacy of the proposed model was investigated using the analysis of variance (ANOVA) test and summarized in table 3.
Table 3: ANOVA results for the developed quadratic model
| Source | Sum of squares | df | Mean square | F-value | p-value Prob > F | |||
| Model | 3102.21 | 1 | 517.03 | 46.69 | <0.0001 | |||
| X1 | 668.87 | 1 | 668.87 | 60.40 | <0.0001 | |||
| X2 | 460.25 | 1 | 460.25 | 41.56 | <0.0001 | |||
| X3 | 1122.03 | 1 | 1122.03 | 101.33 | <0.0001 | |||
| X4 | 451.53 | 1 | 451.53 | 40.78 | <0.0001 | |||
| X5 | 50.77 | 1 | 50.77 | 4.58 | <0.0001 | |||
| X2 X4 | 348.75 | 23 | 348.75 | 31.50 | 0.0431 | |||
| X42 | 668.87 | 18 | 11.07 | 46.69 | <0.0001 | |||
| Residual | 254.68 | 5 | 13.25 | - | - | |||
| Lack of Fit | 238.58 | 29 | 3.22 | 4.12 | 0.0621 | |||
| Pure Error | 16.10 | 1 | 517.03 | - | - | |||
| Cor Total | 3356.89 | 1 | - | - | - | |||
| R2 = 0.9741 | Adjusted R2= 0.9543 | Predicted R2 = 0.9022 | Adequate precision = 25.96 | |||||
The correlation between the predicted values versus the experimental values of BPA removal efficiency and the normal probability versus the externally studentized residuals of the developed model was demonstrated in figure 1 The observed satisfactory agreement between the actual and the predicted values confirmed the normality of the obtained results and
the applicability of the developed polynomial model.
the applicability of the developed polynomial model.
Figure 1: (A) Predicted values versus actual values and (B) normal probability plot of studentized residuals' model for the proposed model
The effect of investigated parameters on the BPA removal
The obtained results showed that the initial BPA concentration had a negative effect on the removal of BPA so that by increasing the initial BPA concentration from 1 to 10 mg L-1, the removal efficiency of BPA was decreased from 84.6 to 63.5, where other variables, including the current density, pH, and reaction time kept constant at their central points of 9.0 mA cm-2, 7.0, 17 min, respectively. According to the results, the current density revealed a positive effect on the BPA removal efficiency. Accordingly, under the constant condition of central points for other variables, including the initial BPA concentration of 5.5 mg L-1, pH of 7.0, and reaction time of 17 min, the current density of 3 mA cm-2 resulted in the removal efficiency of 65.1%. While by increasing the current density to the value of 15 mA cm-2, the removal efficiency of 82.3% was achieved. The contour plot and 3D plot of BPA removal efficiency as a function of BPA concentration and current density were demonstrated in figure 2.
The obtained results showed that the initial BPA concentration had a negative effect on the removal of BPA so that by increasing the initial BPA concentration from 1 to 10 mg L-1, the removal efficiency of BPA was decreased from 84.6 to 63.5, where other variables, including the current density, pH, and reaction time kept constant at their central points of 9.0 mA cm-2, 7.0, 17 min, respectively. According to the results, the current density revealed a positive effect on the BPA removal efficiency. Accordingly, under the constant condition of central points for other variables, including the initial BPA concentration of 5.5 mg L-1, pH of 7.0, and reaction time of 17 min, the current density of 3 mA cm-2 resulted in the removal efficiency of 65.1%. While by increasing the current density to the value of 15 mA cm-2, the removal efficiency of 82.3% was achieved. The contour plot and 3D plot of BPA removal efficiency as a function of BPA concentration and current density were demonstrated in figure 2.
Figure 2: Contour and 3D surface plot for the combined effect of BPA concentration and current density
Figure 3 demonstrates the 3D plot of BPA removal efficiency as a function of BPA concentration and pH. As seen, the pH solution showed a significant effect on the removal efficiency of BPA, so that, if other parameters were kept constant at their center points BPA concentration of 5.5 mg L-1, current density of 9.0 mA cm-2, and the reaction time of 17 min), by increasing the pH level from –α to +α (4 to 10), the removal efficiency of BPA increased from 60.1% to 77.8%.
Figure 3: 3D surface plot for the combined effect of BPA concentration and pH.
Figure 4 illustrates the contour and 3D plot of BPA removal efficiency as a function of the reaction time and the current density. As seen, the reaction time revealed a significant effect on the BPA removal efficiency. If other operating parameters were fixed at their center points, including BPA concentration of 5.5 mg L-1, the current density of 9.0 mA cm-2, and pH of 7, the removal efficiency was increased from 51.4% to 69.0%, while the reaction time increased from –α (5 min) to +α (30 min). Moreover, according to the quadratic effect of reaction time (X42), by increasing the reaction time from 5 min to 23 min, the removal efficiency of BPA was improved from 20% to 73%. However, by a further increase in reaction time from 23 min onwards, the removal efficiency was decreased to 61.1%.
Figure 4: Contour and 3D surface plot for the combined effect of current density and reaction time Optimization process
RSM provides a fast, is cost-effective, and efficient treatment process by optimizing the values of operating variables to the desired level. The level of all main parameters was set on the maximum desirability within the investigated range. The best operating condition with a satisfactory removal efficiency of 98.2% was achieved under the BPA concentration of 3.25 mg L-1, the current density of 12.0 mA cm-2, pH of 8.5, and reaction time of 23 min. The electrical energy consumption (EEC) under optimum conditions for the treatment process was found to be 0.308 kWh m-3.
Discussion
Statistical analysis
The obtained results confirmed that the proposed model was significant at a confidence level of 95%. The correlation coefficient between the predicted and actual values of BPA removal efficiency was computed to be 0.9741, implying that the model could not explain only 2.6% of the total variance in the response. Moreover, the observed variation of less than 0.20 between the adjusted R2 (0.9543) and the predicted R2 (0.9022) indicates the significance of the model. The obtained value of 25.96 for adequate precision represents a desirable signal-to-noise ratio.
Effect of independent variables
According to the obtained results, increasing the initial BPA concentration revealed a diverse effect on the BPA removal efficiency. It could be attributed to the constant amount of adsorption sites provided by the constant quantity mass of produced coagulant agents. The generated flocs at higher concentrations of BPA were not enough to adsorb and coagulate all the BPA molecules. Therefore, BPA removal efficiency was decreased 25, 26. The amount of generated coagulant agents as the key parameter of ECP is directly related to the reaction time and current density.
It is confirmed that the current density strongly affected the coagulant agents and gas bubble generation rate and floc distribution 27, 28. The higher removal efficiency at higher current density was likely because of the more intensive release of aluminum cations from the anode surface, which resulted in the formation of a greater amount of insoluble form of aluminum precipitates 29-31. Moreover, based on Faraday's law, reaction time affected the number of aluminum cations released into the treatment reactor.
Furthermore, one more important parameter that was affected the removal of BPA was the pH level of the treated samples. It was reported that the pH of the treated samples could be decreased or increased due to the reactions involved in the ECP 32, 33. In the current work, the pH of the treatment condition was investigated in the range of 4 to 10. The obtained results confirmed that the pH of the sample revealed a significant effect on the BPA removal. Reaction (1) and (2) describes the release of aluminum ions from the anode electrode (oxidation reaction), and hydrolysis of H2O molecules, and production of hydrogen gas from the cathode electrode (reduction reaction), respectively. The released aluminum ions from the anode electrode convert to aluminum hydroxide (main coagulants agents) throughout a series of reactions with the H2O and the generated products of its hydrolysis, as shown in reaction (3) 15, 28.
(Anode) (1)
(Cathode) (2)
(Overall reaction) (3)
The dominant mechanisms of BPA removal are attributed to co-precipitation, adsorption, or concurrent co-precipitation and adsorption processes. The generated complexes of aluminum polyhydroxides in the alkaline pH range of 8 to 10 revealed efficient behavior as the coagulant agents. The aluminum ions released from the anode electrode during the ECP could be converted into the low soluble form of Al(OH)3, which is finally polymerized in Aln(OH)3n forms and resulted in the formation of dense flocs.
Conclusion
The current work revealed that ECP successfully eliminated the BPA contaminant from the aqueous environments. The obtained lack of fit of 0.0620 confirmed that the model was significant, and the obtained experimental results were accurate and reliable. The impact of the variables and their interactions were evaluated by ANOVA. The obtained results confirmed that BPA initial concentration and solution pH revealed a greater influence on the removal efficiency of the process. The optimum condition for BPA removal of 98.2% was attained at pH of 8.5, BPA concentration of 3.25 mg L-1, the current density of 12.0 mA cm-2, and reaction time of 23 min. The electrical energy consumption of the ECP was found to be 0.308 kWh m-3.
Acknowledgments
The authors would like to express their appreciation to the student research committee of Kerman University of Medical Sciences for supporting the current work.
Funding
This work received a grant from the Kerman University of Medical Sciences [Grant number 97000714].
Conflict of interest
The authors declare that they have no conflict of interest regarding the publication of the current paper.
This is an Open-Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work for commercial use.
References
Discussion
Statistical analysis
The obtained results confirmed that the proposed model was significant at a confidence level of 95%. The correlation coefficient between the predicted and actual values of BPA removal efficiency was computed to be 0.9741, implying that the model could not explain only 2.6% of the total variance in the response. Moreover, the observed variation of less than 0.20 between the adjusted R2 (0.9543) and the predicted R2 (0.9022) indicates the significance of the model. The obtained value of 25.96 for adequate precision represents a desirable signal-to-noise ratio.
Effect of independent variables
According to the obtained results, increasing the initial BPA concentration revealed a diverse effect on the BPA removal efficiency. It could be attributed to the constant amount of adsorption sites provided by the constant quantity mass of produced coagulant agents. The generated flocs at higher concentrations of BPA were not enough to adsorb and coagulate all the BPA molecules. Therefore, BPA removal efficiency was decreased 25, 26. The amount of generated coagulant agents as the key parameter of ECP is directly related to the reaction time and current density.
It is confirmed that the current density strongly affected the coagulant agents and gas bubble generation rate and floc distribution 27, 28. The higher removal efficiency at higher current density was likely because of the more intensive release of aluminum cations from the anode surface, which resulted in the formation of a greater amount of insoluble form of aluminum precipitates 29-31. Moreover, based on Faraday's law, reaction time affected the number of aluminum cations released into the treatment reactor.
Furthermore, one more important parameter that was affected the removal of BPA was the pH level of the treated samples. It was reported that the pH of the treated samples could be decreased or increased due to the reactions involved in the ECP 32, 33. In the current work, the pH of the treatment condition was investigated in the range of 4 to 10. The obtained results confirmed that the pH of the sample revealed a significant effect on the BPA removal. Reaction (1) and (2) describes the release of aluminum ions from the anode electrode (oxidation reaction), and hydrolysis of H2O molecules, and production of hydrogen gas from the cathode electrode (reduction reaction), respectively. The released aluminum ions from the anode electrode convert to aluminum hydroxide (main coagulants agents) throughout a series of reactions with the H2O and the generated products of its hydrolysis, as shown in reaction (3) 15, 28.
(Anode) (1) (Cathode) (2) (Overall reaction) (3)The dominant mechanisms of BPA removal are attributed to co-precipitation, adsorption, or concurrent co-precipitation and adsorption processes. The generated complexes of aluminum polyhydroxides in the alkaline pH range of 8 to 10 revealed efficient behavior as the coagulant agents. The aluminum ions released from the anode electrode during the ECP could be converted into the low soluble form of Al(OH)3, which is finally polymerized in Aln(OH)3n forms and resulted in the formation of dense flocs.
Conclusion
The current work revealed that ECP successfully eliminated the BPA contaminant from the aqueous environments. The obtained lack of fit of 0.0620 confirmed that the model was significant, and the obtained experimental results were accurate and reliable. The impact of the variables and their interactions were evaluated by ANOVA. The obtained results confirmed that BPA initial concentration and solution pH revealed a greater influence on the removal efficiency of the process. The optimum condition for BPA removal of 98.2% was attained at pH of 8.5, BPA concentration of 3.25 mg L-1, the current density of 12.0 mA cm-2, and reaction time of 23 min. The electrical energy consumption of the ECP was found to be 0.308 kWh m-3.
Acknowledgments
The authors would like to express their appreciation to the student research committee of Kerman University of Medical Sciences for supporting the current work.
Funding
This work received a grant from the Kerman University of Medical Sciences [Grant number 97000714].
Conflict of interest
The authors declare that they have no conflict of interest regarding the publication of the current paper.
This is an Open-Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work for commercial use.
References
- Lassouane F, Aït-Amar H, Amrani S, et al. A promising laccase immobilization approach for Bisphenol A removal from aqueous solutions. Bioresour. Technol. 2019;271:360-7.
- Zhang Y, Chen Z, Wu P, et al. Three-dimensional heterogeneous Electro-Fenton system with a novel catalytic particle electrode for Bisphenol A removal. J Hazard Mater. 2020;393:120448.
- Thoene M, Dzika E, Gonkowski S, et al. Bisphenol S in food causes hormonal and obesogenic effects comparable to or worse than Bisphenol A: A literature review. Nutrients. 2020;12(2):532.
- Dolatabadi M, Ahmadzadeh S. A rapid and efficient removal approach for degradation of metformin in pharmaceutical wastewater using electro-Fenton process; optimization by response surface methodology. Water Sci Technol. 2019;80(4):685-94.
- Fang Z, Gao Y, Wu X, et al. A critical review on remediation of bisphenol S (BPS) contaminated water: Efficacy and mechanisms. Crit Rev Environ Sci Technol. 2020;50(5):476-522.
- Sadeghzadeh S, Nejad ZG, Ghasemi S, et al. Removal of bisphenol A in aqueous solution using magnetic cross-linked laccase aggregates from Trametes hirsuta. Bioresour. Technol. 2020;306:123169.
- den Braver-Sewradj SP, van Spronsen R, Hessel EV. Substitution of bisphenol A: a review of the carcinogenicity, reproductive toxicity, and endocrine disruption potential of alternative substances. Crit Rev Toxicol. 2020;50(2):128-47.
- Kyrila G, Katsoulas A, Schoretsaniti V, et al. Bisphenol A removal and degradation pathways in microorganisms with probiotic properties. J Hazard Mater. 2021;401:125363.
- Qian Y, Jia X, Ding T, et al. Occurrence and removal of bisphenol analogues in wastewater treatment plants and activated sludge bioreactor. Sci Total Environ. 2021;758:143606.
- Abdollahi Y, Abdullah AH, Gaya UI, et al. Photocatalytic degradation of 1, 4-benzoquinone in aqueous ZnO dispersions. J Braz Chem Soc. 2012;23(2):236-40.
- Moradi M, Vasseghian Y, Arabzade H, et al. Various wastewaters treatment by sono-electrocoagulation process: A comprehensive review of operational parameters and future outlook. Chemosphere. 2021;263:128314.
- Sandoval MA, Fuentes R, Thiam A, et al. Arsenic and fluoride removal by electrocoagulation process: A general review. Sci Total Environ. 2021;753:142108.
- Al-Qodah Z, Tawalbeh M, Al-Shannag M, et al. Combined electrocoagulation processes as a novel approach for enhanced pollutants removal: A state-of-the-art review. Sci Total Environ. 2020;744:140806.
- Peng H, Guo J. Removal of chromium from wastewater by membrane filtration, chemical precipitation, ion exchange, adsorption electrocoagulation, electrochemical reduction, electrodialysis, electrodeionization, photocatalysis and nanotechnology: a review. Environ Chem Lett. 2020;18:2055-68.
- Mena V, Betancor-Abreu A, González S, et al. Fluoride removal from natural volcanic underground water by an electrocoagulation process: Parametric and cost evaluations. J Environ Manage. 2019;246:472-83.
- Ghernaout D, Elboughdiri N. Electrocoagulation Process Intensification for Disinfecting Water-A Review. Appl Eng. 2019; 3:140-7.
- Kalivel P, Singh RP, Kavitha S, et al. Elucidation of electrocoagulation mechanism in the removal of Blue SI dye from aqueous solution using Al-Al, Cu-Cu electrodes-A comparative study. Ecotoxicol Environ Saf. 2020;201:110858.
- Kim T, Kim T-K, Zoh K-D. Removal mechanism of heavy metal (Cu, Ni, Zn, and Cr) in the presence of cyanide during electrocoagulation using Fe and Al electrodes. J Water Process Eng. 2020;33:101109.
- Chen L, Xu Y, Dong X, et al. Removal of Intracellular and Extracellular Antibiotic Resistance Genes in Municipal Wastewater Effluent by Electrocoagulation. Environ Eng Sci. 2020;37(12):783-9.
- Xiao K, Huang D, Kang C, et al. Removal of tetracyclines from aqueous solutions by electrocoagulation/pecan nutshell coupling processes: synergistic effect and mechanism. Water Sci Technol. 2020;82(4):683-94.
- Chen M, Dollar O, Shafer-Peltier K, et al. Boron removal by electrocoagulation: Removal mechanism, adsorption models and factors influencing removal. Water Res. 2020;170: 115362.
- Abdollahi Y, Abdullah AH, Gaya UI, et al. Photocatalytic degradation of 1, 4-benzoquinone in aqueous ZnO dispersions. J Braz Chem Soc. 2012;23(2):236-40.
- Najafpoor A, Alidadi H, Esmaeili H, et al. Optimization of anionic dye adsorption onto Melia azedarach sawdust in aqueous solutions: effect of calcium cations. Asia-Pac J Chem Eng. 2016;11(2):258-70.
- Jamali‐Behnam F, Najafpoor AA, Davoudi M, et al. Adsorptive removal of arsenic from aqueous solutions using magnetite nanoparticles and silica‐coated magnetite nanoparticles. Environ Prog Sustain Energy. 2018;37(3):951-60.
- Nandi BK, Patel S. Effects of operational parameters on the removal of brilliant green dye from aqueous solutions by electrocoagulation. Arab J Chem. 2017;10:S2961-S8.
- Khandegar V, Saroha AK. Electrocoagulation for the treatment of textile industry effluent–a review. J Environ Manage. 2013;128:949-63.
- Tahreen A, Jami MS, Ali F. Role of electrocoagulation in wastewater treatment: A developmental review. J Water Process Eng. 2020;37:101440.
- Kobya M, Soltani RDC, Omwene PI, et al. A review on decontamination of arsenic-contained water by electrocoagulation: Reactor configurations and operating cost along with removal mechanisms. Environ Technol Inno. 2020;17:100519.
- da Silva Ribeiro T, Grossi CD, Merma AG, et al. Removal of boron from mining wastewaters by electrocoagulation method: Modelling experimental data using artificial neural networks. Miner Eng. 2019;131:8-13.
- Mohammadi A, Khadir A, Tehrani RM. Optimization of nitrogen removal from an anaerobic digester effluent by electrocoagulation process. J Environ Chem Eng. 2019;7(3):103195.
- Bao J, Yu WJ, Liu Y, et al. Removal of perfluoroalkanesulfonic acids (PFSAs) from synthetic and natural groundwater by electrocoagulation. Chemosphere. 2020;248: 125951.
- Isik Z, Arikan EB, Ozay Y, et al. Electrocoagulation and electrooxidation pre-treatment effect on fungal treatment of pistachio processing wastewater. Chemosphere. 2020;244: 125383.
- Sadik MA. A review of promising electrocoagulation technology for the treatment of wastewater. Adv Chem Eng Sci. 2019;9(01): 109.
Type of Study: Original articles |
Subject:
Environmental pollution
Received: 2021/03/10 | Accepted: 2021/04/20 | Published: 2021/06/30
Received: 2021/03/10 | Accepted: 2021/04/20 | Published: 2021/06/30
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
