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J Environ Health Sustain Dev 2022, 7(1): 1561-1570 |
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Dolatabadi M, Hajebrahimi Z, Malekahmadi R, Ahmadzadeh S. Electrochemical Oxidation Approach towards the Treatment of Acetamiprid Pesticide from Polluted Water. J Environ Health Sustain Dev 2022; 7 (1) :1561-1570
URL: http://jehsd.ssu.ac.ir/article-1-419-en.html
URL: http://jehsd.ssu.ac.ir/article-1-419-en.html
Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
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| Abstract (HTML) (879 Views)
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Figure 1: Structure of AP as a neonicotinoid pesticide
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Figure 2: The effect of reaction time on the AP removal efficiency
Table 2: Designed matrix and experimental result of AP removal using EF process
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Figure 3: Statistical analysis of the AP removal efficiency model (a) the actual vs. predicted value, (b) normal% probability vs. internally studentized residual
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Figure 4: 3D plot of the current density vs. AP concentration (H2O2 dosage of 60 µL, pH solution of 5.0, and reaction time of 12 min)
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Figure 5: Contour diagram of the current density vs. H2O2 dosage (AP concentration of 5.5 mg L-1, pH solution of 5.0, and reaction time of 12 min)
Table 4: Parameters of kinetic models for the AP removal
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Electrochemical Oxidation Approach towards the Treatment of Acetamiprid Pesticide from Polluted Water
Maryam Dolatabadi 1,2, Zahra Hajebrahimi 3,4, Roya Malekahmadi 2, Saeid Ahmadzadeh 5, 6*
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.
3Vice-chancellor for Health of Sirjan School of Medical Sciences, Sirjan, Iran.
4 Department of Food Hygiene and Safety, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
5 Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
6 Pharmaceutical Sciences and Cosmetic Products Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Maryam Dolatabadi 1,2, Zahra Hajebrahimi 3,4, Roya Malekahmadi 2, Saeid Ahmadzadeh 5, 6*
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.
3Vice-chancellor for Health of Sirjan School of Medical Sciences, Sirjan, Iran.
4 Department of Food Hygiene and Safety, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
5 Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
6 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: Acetamiprid (AP) is one of the most widely used pesticides in the neonicotinoid class. AP residues in the environment have received considerable due to their potential toxicity to humans. Therefore, it is important to remove AP from the aqueous solution. Materials and Methods: In the current study, response surface methodology (RSM) was used as an efficient approach to optimize the removal of AP using the electro-Fenton (EF) process. The effects of the main variables, including reaction time, AP concentration, current density, and H2O2 dosage were investigated and optimized. ANOVA technique was also used to identify the Fisher’s value (F-value) and P-value of the model. Results: The predicted AP removal efficiency by the model was in good agreement with the obtained experimental results with correlation regression of 0.98. The ANOVA test proved that the developed quadratic model was significant with very low P-values less than 0.05, the high F-value of 240.1, and regression coefficients close to 1 at a 95% confidence level. The optimum condition for AP removal efficiency of 99.02% was attained at the reaction time of 12 min, AP concentration of 3.5 mg L-1, the current density of 12 mA cm-2, and H2O2 dosage of 86 µL. Conclusion: RSM was employed as a suitable method to optimize the operating condition and maximize the AP removal. Herein, the EF process as an eco-friendly electrochemical advanced oxidation process (EAOP) successfully applied to remove AP from the water and wastewater. |
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Article History: Received: 16 December 2021 Accepted: 20 February 2022 |
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*Corresponding Author: Saeid Ahmadzadeh Email: chem_ahmadzadeh@yahoo.com Tel: +983431325241 |
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Keywords: Acetamiprid, Advanced Oxidation Process, Pesticide, Water Purification. |
Citation: Dolatabadi M, Hajebrahimi Z, Malekahmadi R, et al. Electrochemical Oxidation Approach towards the Treatment of Acetamiprid Pesticide from Polluted Water. J Environ Health Sustain Dev. 2021; 7(1): 1561-70.
Introduction
Introduction
The lives of all biota, including humans, animals, and plants, are affected by the quantity and quality of water. Also, health, agricultural, industrial, and welfare activities are affected by water resources. Due to the importance of water in the life of organisms, in recent decades, emerging pollutants (Eps) (even in low concentrations) have been detected in water resources, which have caused a decrease in water quality and subsequent occurrence of diseases and environmental hazards 1-3. Eps include surfactants, personal care products, pharmaceutical compounds, and pesticides 4-6.
The presence of Eps in water resources has caused many concerns in human societies. Today, due to increasing population growth, the need for food has increased. The use of pesticides in agricultural activities to increase crop production and pest control has found special and inevitable applications. Researchers have frequently detected the residues of various pesticides in surface water, groundwater, soil, and sediments. Pesticide residues in the environment pose a serious threat to the living biota, since they have the potential for bio-accumulation, bio-magnification, and remain in the environment for a long time without decomposition 7-9. Acetamiprid (AP) is one of the most widely used insecticides and belongs to neonicotinoid pesticides (Figure 1). In particular, AP has attracted the attention of many farmers due to its affordable price, availability, and ability to deal with a wide range of plant pests 10-12.
The presence of Eps in water resources has caused many concerns in human societies. Today, due to increasing population growth, the need for food has increased. The use of pesticides in agricultural activities to increase crop production and pest control has found special and inevitable applications. Researchers have frequently detected the residues of various pesticides in surface water, groundwater, soil, and sediments. Pesticide residues in the environment pose a serious threat to the living biota, since they have the potential for bio-accumulation, bio-magnification, and remain in the environment for a long time without decomposition 7-9. Acetamiprid (AP) is one of the most widely used insecticides and belongs to neonicotinoid pesticides (Figure 1). In particular, AP has attracted the attention of many farmers due to its affordable price, availability, and ability to deal with a wide range of plant pests 10-12.
Figure 1: Structure of AP as a neonicotinoid pesticide
The presence of AP in the environment causes health problems, such as tremors, nausea, headaches, decreased or lost memory, weakened nervous system, and endocrine disruptors. In addition, studies have shown that AP presumably adversely affects the beneficial biota, including earthworms and bees 10.
Therefore, its removal from water sources is of utmost importance. One of the most common environmental bottlenecks is focusing on designing efficient processes. Among the recent technologies, the electrochemical advanced oxidation processes (EAOPs) have proved to be a powerful oxidative approach for the degradation and removal of several organic pollutants. The electro-Fenton (EF) process is one of the most widely used EAOPs, which has shown good performance for treating resistant and refractory pollutants 3. The basis of the EF process is the generation of hydroxyl radicals (•OH) through electrochemical reactions 13-15.
In EF, H2O2 (hydrogen peroxide) and Fe2+ ion promote a tremendous and fast generation of •OH according to Fenton’s reaction based on Eq. 1.
The •OH species generated during the EF process attack the organic pollutants molecules, transforming them into more safe products, such as water and carbon dioxide. In this process, the Fe2+ ions are regenerated from Fe3+ owing to their cathode reduction, according to Eq. 2. This confirms the generation of •OH if the H2O2 is available 16-18.
H2O2 + Fe2+ + H+ →Fe3+ + H2O + •OH (1)
Fe3++ e- → Fe2+ (2)
In the present study, response surface methodology (RSM) was used as an efficient approach to optimize the removal of AP using the EF process. The important operational parameters, including reaction time, AP concentration, current density, and H2O2 dosage, were considered. Finally, first-order and second-order kinetic models were investigated.
Materials and Methods
Chemicals
Analytical grade AP (C10H11ClN4) was obtained from Sigma-Aldrich Company. Acetonitrile (CH3CN) HPLC grade, sodium sulfate (Na2SO4), sulfuric acid (H2SO4), sodium hydroxide (NaOH), and hydrogen peroxide (H2O2, 30% w/w) were purchased from Merck Company.
EF reactor setup
A cylindrical glass cell was used as the reactor. Two iron plates as anode and cathode electrodes with the same dimensions (4.0 × 0.8 × 0.1 cm) were placed parallel and at a constant distance (3.0 cm) from each other in the electrochemical reactor. The sample volume of 0.25 L with 0.05 M of Na2SO4 as supporting electrolyte and pH solution of 5.0 was constant in all the experiments. The pH of samples was adjustment adding NaOH or H2SO4 solutions. The current density was regulated using a DC power supply during the EF process. After the electrochemical treatment process, the AP concentration was measured using the KNAUER Smartline HPLC system (C18-250 × 4.6, 0.5 mm). The wavelength was set at 242 nm. The mobile phases were acetonitrile (MeCN) and water (H2O) in the ratio (30:70 v/v).
Experimental design
Central composite design (CCD) was applied to optimize variables, such as AP concentration, current density, and H2O2 dosage. The levels of independent variables for the AP removal using the EF process are summarized in Table 1.
Therefore, its removal from water sources is of utmost importance. One of the most common environmental bottlenecks is focusing on designing efficient processes. Among the recent technologies, the electrochemical advanced oxidation processes (EAOPs) have proved to be a powerful oxidative approach for the degradation and removal of several organic pollutants. The electro-Fenton (EF) process is one of the most widely used EAOPs, which has shown good performance for treating resistant and refractory pollutants 3. The basis of the EF process is the generation of hydroxyl radicals (•OH) through electrochemical reactions 13-15.
In EF, H2O2 (hydrogen peroxide) and Fe2+ ion promote a tremendous and fast generation of •OH according to Fenton’s reaction based on Eq. 1.
The •OH species generated during the EF process attack the organic pollutants molecules, transforming them into more safe products, such as water and carbon dioxide. In this process, the Fe2+ ions are regenerated from Fe3+ owing to their cathode reduction, according to Eq. 2. This confirms the generation of •OH if the H2O2 is available 16-18.
H2O2 + Fe2+ + H+ →Fe3+ + H2O + •OH (1)
Fe3++ e- → Fe2+ (2)
In the present study, response surface methodology (RSM) was used as an efficient approach to optimize the removal of AP using the EF process. The important operational parameters, including reaction time, AP concentration, current density, and H2O2 dosage, were considered. Finally, first-order and second-order kinetic models were investigated.
Materials and Methods
Chemicals
Analytical grade AP (C10H11ClN4) was obtained from Sigma-Aldrich Company. Acetonitrile (CH3CN) HPLC grade, sodium sulfate (Na2SO4), sulfuric acid (H2SO4), sodium hydroxide (NaOH), and hydrogen peroxide (H2O2, 30% w/w) were purchased from Merck Company.
EF reactor setup
A cylindrical glass cell was used as the reactor. Two iron plates as anode and cathode electrodes with the same dimensions (4.0 × 0.8 × 0.1 cm) were placed parallel and at a constant distance (3.0 cm) from each other in the electrochemical reactor. The sample volume of 0.25 L with 0.05 M of Na2SO4 as supporting electrolyte and pH solution of 5.0 was constant in all the experiments. The pH of samples was adjustment adding NaOH or H2SO4 solutions. The current density was regulated using a DC power supply during the EF process. After the electrochemical treatment process, the AP concentration was measured using the KNAUER Smartline HPLC system (C18-250 × 4.6, 0.5 mm). The wavelength was set at 242 nm. The mobile phases were acetonitrile (MeCN) and water (H2O) in the ratio (30:70 v/v).
Experimental design
Central composite design (CCD) was applied to optimize variables, such as AP concentration, current density, and H2O2 dosage. The levels of independent variables for the AP removal using the EF process are summarized in Table 1.
Table 1: Level of independent variables for the AP removal using EF process
| Variables (Xi) | Level | ||||
| -α | -1 | 0 | +1 | +α | |
| X1 = AP concentration (mg L-1) | 1 | 2.5 | 5.5 | 8.5 | 10 |
| X2 = Current density (mA cm-2) | 6 | 7.5 | 10 | 13.5 | 15 |
| X3 = H2O2 dosage (µL) | 20 | 34 | 60 | 87 | 100 |
The following equation was applied to evaluate and investigate the experimental results of CCD and to model the AP removal process using the EF process as follows 19:
Y = β 0 + i =1 n β i X i + i =1 n β ii X i 2 + i =1 n - 1 j = i +1 n β ij X i X j + ε
Where, Y (the removal percentage of AP using the EF process as a response), βi (intercept of the developed model), βi (linearity effects), βij (interaction effects), βii (quadratics effects), and ε denotes the error. The ANOVA was conducted at a (95% confidence level) for validating the model and significance of investigated variables using statistical parameters, such as the sum of squares, mean square, degree freedom (df), probability level (P-value), Fisher's test (F-value), determination coefficient (R2), and lack of fit 20-22.
Ethical issue
The current study was conducted in the spring and summer of 2020, after receiving approval from the ethics committee of Kerman University of Medical Sciences [IR.KMU.REC.1398.674].
Results
Effect of reaction time on the AP removal efficiency
The effect of reaction time was investigated from 2 to 15 min on AP removal. The AP concentration, pH solution, current density, and H2O2 dosage were kept constant at 4.0 mg L-1, 5.0, 9 mA cm-2, and 50 µL, respectively, the results of which are shown in Figure 2. After 10 min of EF process, the AP removal efficiency significantly increased, but after 12 min, the AP removal efficiency reached the constant value of about 83%. Thus, the optimum reaction time was determined to be 12 min.
RSM model fitting
The designed matrix and experimental result of AP removal using the EF process are shown in Table 2.
Where, Y (the removal percentage of AP using the EF process as a response), βi (intercept of the developed model), βi (linearity effects), βij (interaction effects), βii (quadratics effects), and ε denotes the error. The ANOVA was conducted at a (95% confidence level) for validating the model and significance of investigated variables using statistical parameters, such as the sum of squares, mean square, degree freedom (df), probability level (P-value), Fisher's test (F-value), determination coefficient (R2), and lack of fit 20-22.
Ethical issue
The current study was conducted in the spring and summer of 2020, after receiving approval from the ethics committee of Kerman University of Medical Sciences [IR.KMU.REC.1398.674].
Results
Effect of reaction time on the AP removal efficiency
The effect of reaction time was investigated from 2 to 15 min on AP removal. The AP concentration, pH solution, current density, and H2O2 dosage were kept constant at 4.0 mg L-1, 5.0, 9 mA cm-2, and 50 µL, respectively, the results of which are shown in Figure 2. After 10 min of EF process, the AP removal efficiency significantly increased, but after 12 min, the AP removal efficiency reached the constant value of about 83%. Thus, the optimum reaction time was determined to be 12 min.
RSM model fitting
The designed matrix and experimental result of AP removal using the EF process are shown in Table 2.
Figure 2: The effect of reaction time on the AP removal efficiency
Table 2: Designed matrix and experimental result of AP removal using EF process
| Run | Actual value | Coded value | AP removal (%) | ||||
| X1 | X2 | X3 | X1 | X2 | X3 | ||
| 1 | 8.50 | 7.50 | 86 | 1 | -1 | 1 | 75.9 |
| 2 | 2.50 | 13.50 | 86 | -1 | 1 | 1 | 98.1 |
| 3 | 5.50 | 6.00 | 60 | 0 | -1.5 | 0 | 70.5 |
| 4 | 1.00 | 10.50 | 60 | -1.5 | 0 | 0 | 94.4 |
| 5 | 8.50 | 13.50 | 86 | 1 | 1 | 1 | 91.2 |
| 6 | 10.0 | 10.50 | 60 | 1.5 | 0 | 0 | 78.3 |
| 7 | 5.50 | 15.00 | 60 | 0 | 1.5 | 0 | 85.6 |
| 8 | 5.50 | 10.50 | 60 | 0 | 0 | 0 | 86.8 |
| 9 | 2.50 | 7.50 | 86 | -1 | -1 | 1 | 84.8 |
| 10 | 5.50 | 10.50 | 60 | 0 | 0 | 0 | 86.1 |
| 11 | 8.50 | 13.50 | 33 | 1 | 1 | -1 | 76.7 |
| 12 | 5.50 | 10.50 | 100 | 0 | 0 | 1.5 | 93.1 |
| 13 | 5.50 | 10.50 | 60 | 0 | 0 | 0 | 85.8 |
| 14 | 5.50 | 10.50 | 60 | 0 | 0 | 0 | 85.6 |
| 15 | 5.50 | 10.50 | 20 | 0 | 0 | -1.5 | 80.1 |
| 16 | 8.50 | 7.50 | 33 | 1 | -1 | -1 | 72.6 |
| 17 | 5.50 | 10.50 | 60 | 0 | 0 | 0 | 85.3 |
| 18 | 5.50 | 10.50 | 60 | 0 | 0 | 0 | 85.4 |
| 19 | 2.50 | 13.50 | 33 | -1 | 1 | -1 | 84.9 |
| 20 | 2.50 | 7.50 | 33 | -1 | -1 | -1 | 81.3 |
The relevance between the AP removal efficiency as the response and the significant variables demonstrated by a quadratic model is as follows:
In this equation, Y is the AP removal (%), and X1 to X3 denote the coded independent factors of AP concentration, the current density, and H2O2 dosage, respectively. The adequacy of the proposed model was investigated using the ANOVA test and summarized in Table 3. The correlation coefficient between the predicted and actual values of AP removal efficiency was computed to be 0.98, indicating that the developed model could not describe only 1.15% of the total variance in the response. Moreover, the observed variation of less than 0.20 between the adjusted R2 (Adj. R2 = 0.98) and the predicted R2 (Pred. R2 = 0.97) confirmed the significance of the model.
In this equation, Y is the AP removal (%), and X1 to X3 denote the coded independent factors of AP concentration, the current density, and H2O2 dosage, respectively. The adequacy of the proposed model was investigated using the ANOVA test and summarized in Table 3. The correlation coefficient between the predicted and actual values of AP removal efficiency was computed to be 0.98, indicating that the developed model could not describe only 1.15% of the total variance in the response. Moreover, the observed variation of less than 0.20 between the adjusted R2 (Adj. R2 = 0.98) and the predicted R2 (Pred. R2 = 0.97) confirmed the significance of the model.
Table 3: ANOVA results of the developed model
| Source | Sum of squares | df | Mean square | F-value | p-value | ||
| Model | 942.13 | 5 | 188.43 | 240.10 | < 0.0001 | ||
| X1 | 258.55 | 1 | 258.55 | 329.46 | < 0.0001 | ||
| X2 | 278.01 | 1 | 278.01 | 354.25 | < 0.0001 | ||
| X3 | 233.28 | 1 | 233.28 | 297.26 | < 0.0001 | ||
| X2 X3 | 54.60 | 1 | 54.60 | 69.58 | < 0.0001 | ||
| X22 | 117.69 | 1 | 117.69 | 149.96 | < 0.0001 | ||
| Residual | 10.99 | 14 | 0.78 | - | - | ||
| Lack of Fit | 9.45 | 9 | 1.05 | 3.43 | 0.0943 | ||
| Pure Error | 1.53 | 5 | 0.31 | - | - | ||
| Cor Total | 953.12 | 19 | - | - | - | ||
| R2 = 0.9885 | Adjusted R2 (Adj. R2) = 0.98 | Predicted R2 (Pred. R2 ) = 0.97 | |||||
In Figure 3-a, the obtained experimental
values for the removal efficiency of AP were compared to the predicted values by the model. Also, the data were investigated to assess the normality of the residuals. The normal probability plots of the internally studentized residuals are presented in Figure 3-b. The adequate agreement between the actual (experimental values) and the predicted values confirmed the normality of the results.
values for the removal efficiency of AP were compared to the predicted values by the model. Also, the data were investigated to assess the normality of the residuals. The normal probability plots of the internally studentized residuals are presented in Figure 3-b. The adequate agreement between the actual (experimental values) and the predicted values confirmed the normality of the results.
Figure 3: Statistical analysis of the AP removal efficiency model (a) the actual vs. predicted value, (b) normal% probability vs. internally studentized residual
Effect of significant parameters on the removal efficiency of AP
Figure 4 shows a 3D response surface plot of removal as a function of AP concentration and the current density at the constant values of H2O2 dosage of 60 µL, pH solution of 5.0, and reaction time of 12 min. The result shows that the AP removal decreased from 92.7% to 79.4% by increasing the AP concentration from 1 mg L-1 to 10 mg L-1.
Figure 4 shows a 3D response surface plot of removal as a function of AP concentration and the current density at the constant values of H2O2 dosage of 60 µL, pH solution of 5.0, and reaction time of 12 min. The result shows that the AP removal decreased from 92.7% to 79.4% by increasing the AP concentration from 1 mg L-1 to 10 mg L-1.
Figure 4: 3D plot of the current density vs. AP concentration (H2O2 dosage of 60 µL, pH solution of 5.0, and reaction time of 12 min)
The removal efficiency of AP increased by increasing the current density. In contrast, the current density was raised from 6 to 12 mA cm-2, the removal efficiency rose from 71.2% to 88.6%. However, by increasing the current density from 12 to 16, the removal efficiency decreased from 88.6 % to 85.4%.
H2O2 dosage played a critical role in the AP removal efficiency throughout the EF process. Usually, the removal efficiency of pollutants increases by increasing H2O2 concentration. Herein, the removal efficiency increased from 79.2 to 92.8 % by increasing the H2O2 dosage from 20 to 100 µL (Figure 5).
H2O2 dosage played a critical role in the AP removal efficiency throughout the EF process. Usually, the removal efficiency of pollutants increases by increasing H2O2 concentration. Herein, the removal efficiency increased from 79.2 to 92.8 % by increasing the H2O2 dosage from 20 to 100 µL (Figure 5).
Figure 5: Contour diagram of the current density vs. H2O2 dosage (AP concentration of 5.5 mg L-1, pH solution of 5.0, and reaction time of 12 min)
Kinetics study
To find out the exact mechanism of the AP removal, kinetics investigations were carried out using first and second-order models. The obtained experimental results are displayed in Table 4, which indicates that the first-order model with the satisfactory correlation coefficient of 0.99 best fitted to the achieved results 23-26.
To find out the exact mechanism of the AP removal, kinetics investigations were carried out using first and second-order models. The obtained experimental results are displayed in Table 4, which indicates that the first-order model with the satisfactory correlation coefficient of 0.99 best fitted to the achieved results 23-26.
Table 4: Parameters of kinetic models for the AP removal
| Kinetics model | Equation | kapp | R2 |
| First-order | 0.174 min-1 | 0.99 | |
| Second-order | 0.0925 L.mg-1min-1 | 0.91 |
Discussion
Statistical analysis
The results of ANOVA are presented in Table 3. The model was significant and can be applied successfully for estimating the AP removal efficiency using the EF process. The regression coefficient (R2 = 0.98) agrees well with the adjusted regression coefficient (Adj.R2 = 0.98). The Adeq precision describes the signal-to-level noise ratio, where the ratio of 56.66 is greater than 4, indicating the adequacy of the developed model 27, 28. In Figure 3, the appropriate and close distribution of data points around a straight line proved the potential and ability of the model to suitably predict values and normally distribute experimental data.
Effect of significant parameters
The influence of AP concentration in the range of 2 to 10 mg L-1 was investigated. The obtained results showed that the AP removal efficiency decreased by increasing the AP concentration, which can be ascribed to the limited number of •OH radicals compared to the increasing number of AP molecules 29-31.
The results of the investigation of current density showed that increasing the current density causes an improvement in the AP removal efficiency. By increasing the current density, the amount of anodic dissolution of iron increased, resulting in a much great generation of Fe2+. The increasing concentration of Fe2+ iron could enhance the Fenton reaction, which produced the •OH radical as a favorable driving force of the treatment process. Moreover, by increasing the current density, the level of H2 bubble generation increased, and the bubble size decreased, which both benefited the treatment process through the flotation mechanism. However, beyond the optimal concentration of Fe2+, the slight reduction in the removal efficiency was observed, which is probably due to the following reaction. In the high concentration of iron cations, the •OH radicals are trapped by Fe2+ as described
below 32-34.
To obtain the maximum AP removal efficiency, the optimal dosage of H2O2 should be employed. Although increasing the dosage of H2O2 enhanced the AP removal efficiency due to accelerating the generation of •OH (see reaction 1), it cannot be added without any limitation. The excessive H2O2 not only increases the costs of operation, but also increases the scavenging effect of •OH by H2O2 (reaction 4), which has a negative effect on the removal efficiency of AP 35-37.
Racar et al., 38 studied the removal of various CECs, including AP, from municipal wastewater (MWW) using membrane bioreactor (MBR). In a mixture of CECs and at a concentration of 2.32 ± 3.22 mg L-1 of AP in the influent, a removal percentage of 39.36% was obtained for MBR 38. Many CECs are effectively degraded using UV radiation and ozonation techniques. However,
the irradiation experiments using marketed mixtures containing AP resulted in a variety of photoproducts, which were also toxic for vertebrates and non-target species 9.
Cruz-Alcalde et al., 10 reported that the toxicity of transformation products (TPs) in the solution increased with increasing the ozone dose and then decreased. Similar toxic TPs were observed during photo-Fenton treatment of AP in race-way ponds 12. Yao et al., 39 fabricated ytterbium (Yb) doped- PbO2 electrodes for electrochemical oxidation of AP. All the degradation products were decontaminated into CO2 and H2O.
Process optimization
In optimizing the AP removal process by design expert software, the desired ranges for each factor and response were selected as the final goal. The numerical optimization provided an opportunity to find a treatment condition with the maximum desirability function. Herein, the main goal was to maximize the removal of AP by the EF process. The optimum AP removal efficiency of 99.02% was attained at the 3.5 mg L-1 AP concentration, the 12 mA cm-2 current density, and 86 µL H2O2 dosage.
Conclusion
In the current study, the RSM was used to assay the effects of important parameters of the AP removal using the EF process using iron electrodes. The maximum removal efficiency of AP (99.02%) was achieved in the condition of 3.5 mg L-1 AP concentration, 12 min reaction time, 86 µL H2O2 dosage, and 12 mA cm-2 current density. According to the developed model, the current density was identified as the most effective parameter in the removal AP using the EF process.
The first-order model well fitted the kinetics data obtained from the batch experiments.
Acknowledgments
The authors would like to express their appreciation to the Student Research Committee of Kerman University of Medical Sciences for supporting the current study.
Funding
This study received a grant from the Kerman University of Medical Sciences [Grant number 98001096].
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.
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10. Cruz-Alcalde A, Sans C, Esplugas S. Priority pesticides abatement by advanced water technologies: the case of acetamiprid removal by ozonation. Sci Total Environ. 2017;599:1454-61.
11. Fasnabi PA, Madhu G, Soloman PA. Removal of acetamiprid from wastewater by fenton and photo‐fenton processes–optimization by response surface methodology and kinetics. Clean–Soil, Air, Water. 2016;44(6):728-37.
12. Carra I, Sirtori C, Ponce-Robles L, et al. Degradation and monitoring of acetamiprid, thiabendazole and their transformation products in an agro-food industry effluent during solar photo-Fenton treatment in a raceway pond reactor. Chemosphere. 2015;130:73-81.
13. Zhou Z, Liu X, Sun K, et al. Persulfate-based advanced oxidation processes (AOPs) for organic-contaminated soil remediation: A review. Chem Eng J. 2019;372:836-51.
14. Mahamuni NN, Adewuyi YG. Advanced oxidation processes (AOPs) involving ultrasound for waste water treatment: a review with emphasis on cost estimation. Ultrason Sonochemistry. 2010;17(6):990-1003.
15. An T, Yang H, Li G, et al. Kinetics and mechanism of advanced oxidation processes (AOPs) in degradation of ciprofloxacin in water. Appl Catal B: Environ. 2010;94(3):288-94.
16. Zhao H, Zhang Q. Performance of electro-Fenton process coupling with microbial fuel cell for simultaneous removal of herbicide mesotrione. Bioresour Technol. 2020:124244.
17. Moradi M, Elahinia A, Vasseghian Y, et al. A review on pollutants removal by Sono-photo-Fenton processes. J Environ Chem Eng. 2020: 104330.
18. Zhang C, Ren G, Wang W, et al. A new type of continuous-flow heterogeneous electro-Fenton reactor for Tartrazine degradation. Sep Purif Technol. 2019;208:76-82.
19. Gadekar MR, Ahammed MM. Modelling dye removal by adsorption onto water treatment residuals using combined response surface methodology-artificial neural network approach. J Environ Manage. 2019;231:241-8.
20. Barisci S, Turkay O, editors. Applications of response surface methodology (RSM) for the optimization of ciprofloxacin removal by electrocoagulation. Proceedings of the IWA Balkan Young Water Professionals Conference; 2015.
21. Bashir MJ, Aziz HA, Yusoff MS, et al. Application of response surface methodology (RSM) for optimization of ammoniacal nitrogen removal from semi-aerobic landfill leachate using ion exchange resin. Desalination. 2010;254(1):154-61.
22. Hosny NM, Huddersman K, Atia NN, et al. Novel heterogeneous fenton’s-like catalysis for degradation of colchicine coupled with extraction of its biologically active metabolite. J Mol Liq. 2019;295:111870.
23. Wang S, Wu J, Lu X, et al. Removal of acetaminophen in the Fe2+/persulfate system: Kinetic model and degradation pathways. Chem Eng J. 2019;358:1091-100.
24. Oturan N, Aravindakumar CT, Olvera-Vargas H, et al. Electro-Fenton oxidation of para-aminosalicylic acid: degradation kinetics and mineralization pathway using Pt/carbon-felt and BDD/carbon-felt cells. Environ Sci Pollut Res. 2018;25(21):20363-73.
25. Barhoumi N, Olvera-Vargas H, Oturan N, et al. Kinetics of oxidative degradation/ mineralization pathways of the antibiotic tetracycline by the novel heterogeneous electro-Fenton process with solid catalyst chalcopyrite. Appl Catal B: Environ. 2017;209:637-47.
26. Fouladgar M, Ahmadzadeh S. Application of a nanostructured sensor based on NiO nanoparticles modified carbon paste electrode for determination of methyldopa in the presence of folic acid. Appl Surf Sci. 2016;379:150-5.
27. Bazaria B, Kumar P. Optimization of spray drying parameters for beetroot juice powder using response surface methodology (RSM). J Saudi Soc Agric Sci. 2018;17(4):408-15.
28. Barışçı S, Turkay O. Optimization and modelling using the response surface methodology (RSM) for ciprofloxacin removal by electrocoagulation. Water Sci Technol. 2016;73(7):1673-9.
29. Gamaralalage D, Sawai O, Nunoura T. Degradation behavior of palm oil mill effluent in Fenton oxidation. J Hazard Mater. 2019;364:791-9.
30. Liu X, Zhou Y, Zhang J, et al. Insight into electro-Fenton and photo-Fenton for the degradation of antibiotics: mechanism study and research gaps. Chem Eng J. 2018;347:379-97.
31. Nidheesh P, Gandhimathi R. Trends in electro-Fenton process for water and wastewater treatment: an overview. Desalination. 2012;299:1-15.
32. Vasudevan S. An efficient removal of phenol from water by peroxi-electrocoagulation processes. J Water Process Eng. 2014;2:53-7.
33. Arienzo M, Chiarenzelli J, Scrudato R. Remediation of metal-contaminated aqueous systems by electrochemical peroxidation: an experimental investigation. J Hazard Mater. 2001;87(1):187-98.
34. Ozyonar F, Karagozoglu B. Treatment of pretreated coke wastewater by electrocoagulation and electrochemical peroxidation processes. Sep Purif Technol. 2015;150:268-77.
35. Görmez F, Görmez Ö, Gözmen B, et al. Degradation of chloramphenicol and metronidazole by electro-Fenton process using graphene oxide-Fe3O4 as heterogeneous catalyst. J Environ Chem Eng. 2019;7(2):102990.
36. Chen S, Tang L, Feng H, et al. Carbon felt cathodes for electro-Fenton process to remove tetracycline via synergistic adsorption and degradation. Sci Total Environ. 2019;670:921-31.
37. Yu Q, Jin X, Zhang Y. Sequential pretreatment for cell disintegration of municipal sludge in a neutral Bio-electro-Fenton system. Water research. 2018;135:44-56.
38. Racar M, Dolar D, Karadakić K, et al. Challenges of municipal wastewater reclamation for irrigation by MBR and NF/RO: Physico-chemical and microbiological parameters, and emerging contaminants. Sci Total Environ. 2020;722:137959.
39. Yao Y, Teng G, Yang Y, et al. Electrochemical oxidation of acetamiprid using Yb-doped PbO2 electrodes: Electrode characterization, influencing factors and degradation pathways. Sep Purif Technol. 2019;211:456-66.
Statistical analysis
The results of ANOVA are presented in Table 3. The model was significant and can be applied successfully for estimating the AP removal efficiency using the EF process. The regression coefficient (R2 = 0.98) agrees well with the adjusted regression coefficient (Adj.R2 = 0.98). The Adeq precision describes the signal-to-level noise ratio, where the ratio of 56.66 is greater than 4, indicating the adequacy of the developed model 27, 28. In Figure 3, the appropriate and close distribution of data points around a straight line proved the potential and ability of the model to suitably predict values and normally distribute experimental data.
Effect of significant parameters
The influence of AP concentration in the range of 2 to 10 mg L-1 was investigated. The obtained results showed that the AP removal efficiency decreased by increasing the AP concentration, which can be ascribed to the limited number of •OH radicals compared to the increasing number of AP molecules 29-31.
The results of the investigation of current density showed that increasing the current density causes an improvement in the AP removal efficiency. By increasing the current density, the amount of anodic dissolution of iron increased, resulting in a much great generation of Fe2+. The increasing concentration of Fe2+ iron could enhance the Fenton reaction, which produced the •OH radical as a favorable driving force of the treatment process. Moreover, by increasing the current density, the level of H2 bubble generation increased, and the bubble size decreased, which both benefited the treatment process through the flotation mechanism. However, beyond the optimal concentration of Fe2+, the slight reduction in the removal efficiency was observed, which is probably due to the following reaction. In the high concentration of iron cations, the •OH radicals are trapped by Fe2+ as described
below 32-34.
To obtain the maximum AP removal efficiency, the optimal dosage of H2O2 should be employed. Although increasing the dosage of H2O2 enhanced the AP removal efficiency due to accelerating the generation of •OH (see reaction 1), it cannot be added without any limitation. The excessive H2O2 not only increases the costs of operation, but also increases the scavenging effect of •OH by H2O2 (reaction 4), which has a negative effect on the removal efficiency of AP 35-37.
Racar et al., 38 studied the removal of various CECs, including AP, from municipal wastewater (MWW) using membrane bioreactor (MBR). In a mixture of CECs and at a concentration of 2.32 ± 3.22 mg L-1 of AP in the influent, a removal percentage of 39.36% was obtained for MBR 38. Many CECs are effectively degraded using UV radiation and ozonation techniques. However,
the irradiation experiments using marketed mixtures containing AP resulted in a variety of photoproducts, which were also toxic for vertebrates and non-target species 9.
Cruz-Alcalde et al., 10 reported that the toxicity of transformation products (TPs) in the solution increased with increasing the ozone dose and then decreased. Similar toxic TPs were observed during photo-Fenton treatment of AP in race-way ponds 12. Yao et al., 39 fabricated ytterbium (Yb) doped- PbO2 electrodes for electrochemical oxidation of AP. All the degradation products were decontaminated into CO2 and H2O.
Process optimization
In optimizing the AP removal process by design expert software, the desired ranges for each factor and response were selected as the final goal. The numerical optimization provided an opportunity to find a treatment condition with the maximum desirability function. Herein, the main goal was to maximize the removal of AP by the EF process. The optimum AP removal efficiency of 99.02% was attained at the 3.5 mg L-1 AP concentration, the 12 mA cm-2 current density, and 86 µL H2O2 dosage.
Conclusion
In the current study, the RSM was used to assay the effects of important parameters of the AP removal using the EF process using iron electrodes. The maximum removal efficiency of AP (99.02%) was achieved in the condition of 3.5 mg L-1 AP concentration, 12 min reaction time, 86 µL H2O2 dosage, and 12 mA cm-2 current density. According to the developed model, the current density was identified as the most effective parameter in the removal AP using the EF process.
The first-order model well fitted the kinetics data obtained from the batch experiments.
Acknowledgments
The authors would like to express their appreciation to the Student Research Committee of Kerman University of Medical Sciences for supporting the current study.
Funding
This study received a grant from the Kerman University of Medical Sciences [Grant number 98001096].
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.
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11. Fasnabi PA, Madhu G, Soloman PA. Removal of acetamiprid from wastewater by fenton and photo‐fenton processes–optimization by response surface methodology and kinetics. Clean–Soil, Air, Water. 2016;44(6):728-37.
12. Carra I, Sirtori C, Ponce-Robles L, et al. Degradation and monitoring of acetamiprid, thiabendazole and their transformation products in an agro-food industry effluent during solar photo-Fenton treatment in a raceway pond reactor. Chemosphere. 2015;130:73-81.
13. Zhou Z, Liu X, Sun K, et al. Persulfate-based advanced oxidation processes (AOPs) for organic-contaminated soil remediation: A review. Chem Eng J. 2019;372:836-51.
14. Mahamuni NN, Adewuyi YG. Advanced oxidation processes (AOPs) involving ultrasound for waste water treatment: a review with emphasis on cost estimation. Ultrason Sonochemistry. 2010;17(6):990-1003.
15. An T, Yang H, Li G, et al. Kinetics and mechanism of advanced oxidation processes (AOPs) in degradation of ciprofloxacin in water. Appl Catal B: Environ. 2010;94(3):288-94.
16. Zhao H, Zhang Q. Performance of electro-Fenton process coupling with microbial fuel cell for simultaneous removal of herbicide mesotrione. Bioresour Technol. 2020:124244.
17. Moradi M, Elahinia A, Vasseghian Y, et al. A review on pollutants removal by Sono-photo-Fenton processes. J Environ Chem Eng. 2020: 104330.
18. Zhang C, Ren G, Wang W, et al. A new type of continuous-flow heterogeneous electro-Fenton reactor for Tartrazine degradation. Sep Purif Technol. 2019;208:76-82.
19. Gadekar MR, Ahammed MM. Modelling dye removal by adsorption onto water treatment residuals using combined response surface methodology-artificial neural network approach. J Environ Manage. 2019;231:241-8.
20. Barisci S, Turkay O, editors. Applications of response surface methodology (RSM) for the optimization of ciprofloxacin removal by electrocoagulation. Proceedings of the IWA Balkan Young Water Professionals Conference; 2015.
21. Bashir MJ, Aziz HA, Yusoff MS, et al. Application of response surface methodology (RSM) for optimization of ammoniacal nitrogen removal from semi-aerobic landfill leachate using ion exchange resin. Desalination. 2010;254(1):154-61.
22. Hosny NM, Huddersman K, Atia NN, et al. Novel heterogeneous fenton’s-like catalysis for degradation of colchicine coupled with extraction of its biologically active metabolite. J Mol Liq. 2019;295:111870.
23. Wang S, Wu J, Lu X, et al. Removal of acetaminophen in the Fe2+/persulfate system: Kinetic model and degradation pathways. Chem Eng J. 2019;358:1091-100.
24. Oturan N, Aravindakumar CT, Olvera-Vargas H, et al. Electro-Fenton oxidation of para-aminosalicylic acid: degradation kinetics and mineralization pathway using Pt/carbon-felt and BDD/carbon-felt cells. Environ Sci Pollut Res. 2018;25(21):20363-73.
25. Barhoumi N, Olvera-Vargas H, Oturan N, et al. Kinetics of oxidative degradation/ mineralization pathways of the antibiotic tetracycline by the novel heterogeneous electro-Fenton process with solid catalyst chalcopyrite. Appl Catal B: Environ. 2017;209:637-47.
26. Fouladgar M, Ahmadzadeh S. Application of a nanostructured sensor based on NiO nanoparticles modified carbon paste electrode for determination of methyldopa in the presence of folic acid. Appl Surf Sci. 2016;379:150-5.
27. Bazaria B, Kumar P. Optimization of spray drying parameters for beetroot juice powder using response surface methodology (RSM). J Saudi Soc Agric Sci. 2018;17(4):408-15.
28. Barışçı S, Turkay O. Optimization and modelling using the response surface methodology (RSM) for ciprofloxacin removal by electrocoagulation. Water Sci Technol. 2016;73(7):1673-9.
29. Gamaralalage D, Sawai O, Nunoura T. Degradation behavior of palm oil mill effluent in Fenton oxidation. J Hazard Mater. 2019;364:791-9.
30. Liu X, Zhou Y, Zhang J, et al. Insight into electro-Fenton and photo-Fenton for the degradation of antibiotics: mechanism study and research gaps. Chem Eng J. 2018;347:379-97.
31. Nidheesh P, Gandhimathi R. Trends in electro-Fenton process for water and wastewater treatment: an overview. Desalination. 2012;299:1-15.
32. Vasudevan S. An efficient removal of phenol from water by peroxi-electrocoagulation processes. J Water Process Eng. 2014;2:53-7.
33. Arienzo M, Chiarenzelli J, Scrudato R. Remediation of metal-contaminated aqueous systems by electrochemical peroxidation: an experimental investigation. J Hazard Mater. 2001;87(1):187-98.
34. Ozyonar F, Karagozoglu B. Treatment of pretreated coke wastewater by electrocoagulation and electrochemical peroxidation processes. Sep Purif Technol. 2015;150:268-77.
35. Görmez F, Görmez Ö, Gözmen B, et al. Degradation of chloramphenicol and metronidazole by electro-Fenton process using graphene oxide-Fe3O4 as heterogeneous catalyst. J Environ Chem Eng. 2019;7(2):102990.
36. Chen S, Tang L, Feng H, et al. Carbon felt cathodes for electro-Fenton process to remove tetracycline via synergistic adsorption and degradation. Sci Total Environ. 2019;670:921-31.
37. Yu Q, Jin X, Zhang Y. Sequential pretreatment for cell disintegration of municipal sludge in a neutral Bio-electro-Fenton system. Water research. 2018;135:44-56.
38. Racar M, Dolar D, Karadakić K, et al. Challenges of municipal wastewater reclamation for irrigation by MBR and NF/RO: Physico-chemical and microbiological parameters, and emerging contaminants. Sci Total Environ. 2020;722:137959.
39. Yao Y, Teng G, Yang Y, et al. Electrochemical oxidation of acetamiprid using Yb-doped PbO2 electrodes: Electrode characterization, influencing factors and degradation pathways. Sep Purif Technol. 2019;211:456-66.
Type of Study: Original articles |
Subject:
Water quality and wastewater treatment and reuse
Received: 2021/12/16 | Accepted: 2022/02/20 | Published: 2022/03/16
Received: 2021/12/16 | Accepted: 2022/02/20 | Published: 2022/03/16
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