Removal of Manganese Ions (Mn2+) from a Simulated Wastewater by Electrocoagulation/ Electroflotation Technologies with Stainless Steel Mesh Electrodes: Process Optimization Based on Taguchi Approach Available online at http://ijcpe.uobaghdad.edu.iq and www.iasj.net Iraqi Journal of Chemical and Petroleum Engineering Vol.20 No.1 (March 2019) 39 – 48 EISSN: 2618-0707, PISSN: 1997-4884 Corresponding Author: Rasha H. Salman, E-mail: rasha.habeeb@coeng.uobaghdad.edu.iq IJCPE is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Removal of Manganese Ions (Mn 2+ ) from a Simulated Wastewater by Electrocoagulation/ Electroflotation Technologies with Stainless Steel Mesh Electrodes: Process Optimization Based on Taguchi Approach Rasha H. Salman Chemical Engineering Department – College of Engineering – University of Baghdad Abstract This study depicts the removal of Manganese ions (Mn 2+ ) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm 2 , time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis of variance (ANOVA) which indicates that the percentage of contribution followed the order: time (47.42%), C.D. (37.13%), Mesh number (5.73%), and Mn initial Conc. (0.05%). The electrolysis time and C.D. were the most effective operating parameters and mesh no. had a fair influence on Mn removal efficiency, while the initial conc. of Mn. had no significant effect in the studied ranges of control factors. Regression analysis (R 2 = 90.16%) showed an acceptable agreement between the experimental and the predicted values, and confirmation test results revealed that the removal efficiency of Mn at optimum conditions was higher than 99%. Keywords: Mn removal, Electrocoagulation, electroflotation, stainless steel electrodes, screens electrodes, wastewater, Taguchi method Received on 04/02/2019, Accepted on 25/02/2019, published on 30/03/2019 https://doi.org/10.31699/IJCPE.2019.1.6 1- Introduction Heavy metals from various economic activities can be considered as very influential toxic agents. Due to their great solubility and low biodegradability in the aquatic environments, aqueous solutions, and many industrial wastewaters, the presence of these components even at low concentrations causes deterioration of many ecosystems and particularly human health. Further, Heavy metals lead to serious environmental pollution ‎[1], ‎[2]. Industries including mining, electro-plating or melting operations are developed rapidly. Wastewaters discharged into the environment from these industries holding excessive concentrations of toxic metals (e.g. Mn, Cd, Zn, and Cu), so destructive effects on the organism life would take place if no handling arise ‎[3], ‎[4]. The abundance of Manganese (Mn) metal in nature is very high and it is considered as a vital metal for the human system but with trace amounts due to its ability in enzymes activation. It is used widely in many applications like primary cells, alloys industry, ceramics, and electrical coils besides its presence naturally in the atmosphere as suspended particulates due to its disposal from different sources like industrial emission and soil erosion ‎[5]. Several techniques were employed for the pollution abatement of heavy metal ions in wastewater which include: adsorption ‎[6], chemical precipitation ‎[7], ion- exchange ‎[8], biosorption ‎[9], membrane filtration ‎[10], coagulation-flocculation ‎[11], and flotation ‎[12]. Many of these techniques have disadvantages. For example, precipitation can be considered as the most economical valid, but additional treatment is required due to the production of precipitate sludge. Reverse osmosis, ion-exchange, and other membrane separation techniques can efficiently be used in metal ions removal, but there are limitations in the use of these techniques like high material, and functional cost. In addition to their operative problems, these disadvantages, together with the requirement of effective low-cost treatment, have created innovative challenges for these technologies ‎[13]. Electrocoagulation (EC) is not a new technology but it is an eco-friendly process. In this technique, there are no chemicals added as in the chemical coagulation process. https://doi.org/10.31699/IJCPE.2019.1.6 R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 04 So, there is no problem of neutralizing excess chemicals and no probability of secondary contamination initiated by chemical substances that added at high concentration. EC technique also has many advantages include: producing effluent with a less total dissolved solids content (TDS), demanding simple equipment and it is easy to operate, producing a clear, odorless and colorless discharge. Besides, low amount of sludge is formed in this technique which consists mainly of metallic oxides/hydroxides which tend to be readily settable and easy to be removed. Also, the smallest colloidal particles can be removed by this technique due to the fast motion resulted from the applied electric field that facilitating the coagulation ‎[4],‎[14], ‎[15]. The high effectiveness of the EC process in the elimination of heavy metal ions from industrial/synthesis wastewater has been proved by several studies ‎[5], ‎[16]–‎[19]. Electrocoagulation/Electroflotation (ECF) is an electrochemical process in which the wastewater would be subjected to a direct current (DC) field. So, in-situ generation of coagulants by electro-dissolution of a soluble sacrificial anode dipped in the wastewater would take place. The most sacrificial anodes are Al and Fe. Solid flat electrodes are traditionally used, but in some previous studies, cylindrical perforated ones are implemented due to better dispersal of the applied DC field onto the wastewater to be handled ‎[20], ‎[21]. The ECF has often been considered for the wastewater treatment and it has a wide area of application, for example, heavy metals, organic chemicals, oil, Textile effluents, specific organics, turbid effluent, petroleum industry, suspended particles of all sorts, fluoride, nitrate, and arsenic ‎[22]. There are complex chemical and physical changes that commonly take place in any electrocoagulation process. When a direct current or voltage is applied, positive ionic coagulants would be formed due to sacrificial anodes oxidation. Consecutively, generation of hydroxyl ions (OH - ) and some O2 and H2 gas bubbles would take place due to water reduction arising at the cathode. The formed ions is migrated to oppositely charged electrodes so destabilization of the contaminants and the particulate suspension would take place because of this movement leading to break down the emulsion. Metallic hydroxides of good adsorption properties would be formed because of interaction between the positive ion (Al 3+ or Fe 2+ ) and the hydroxyl ion (OH - ), that are capable of destabilizing any dispersed particles existing in the wastewater. Larger aggregates formed because of adsorption of Pollutants into the hydroxide structures ‎[2], ‎[15]. The formed aggregates can be carried by flotation of hydrogen and oxygen bubbles which move upwards in the liquid phase where it can be more easily concentrated, collected and removed or can be precipitated if they have a quite high density in comparison with the medium ‎[2], ‎[15]. At the anode, anodic dissolution of stainless steel electrode takes place beside water oxidation to produce oxygen gas and hydrogen ions. At the cathode, generation of hydroxyl ion (OH - ) and hydrogen gas occur due to water reduction and these hydroxyl ions would react with Fe ions to produce Fe(OH)2. The chemical reactions can be illustrated as follows ‎[1], ‎[14], ‎[21]: At the Anode: (1) ( ) + (2) At the cathode: (3) In the solution: (4) However, Fe 3+ ions can be generated in the presence of oxygen and at acidic pH, and many species can be existing in the electrolytic solution as represented in the following reactions ‎[1]: (5) (6) Also, Fe(OH)3 and Fe(OH) − 4 can exist in the electrolytic solution in more amount under alkaline conditions. It is stated that Fe(3 + ) hydroxide coagulants have higher activity than Fe(2 + ) hydroxide due to the higher stability of Fe(OH)3. So, the presence of these species gives an enhancement to the ECF process. In this case, the overall electrochemical reaction is ‎[1]: (7) There are several previous studies deals with manganese ions removal from wastewater ‎[23]–‎[25], however, there is a dramatic lack of results in case of applying different mesh no. of stainless steel screen electrodes in ECF process. The objective of this research is to examine the removal of Mn ions by ECF technique using Taguchi experimental design with L18 orthogonal array to optimize the parameters and analyze them successively. Also, the effect of the controllable parameters on the removal efficiency of Mn ions was determined, and the optimization was accomplished by applying the standard procedure proposed by the Taguchi to attain maximum Mn ions elimination. Four effective parameters that have a high influence on the removal efficiency were studied: Mn initial concentration, current density, time, and finally mesh number which has not been satisfactorily considered in previous studies. A confirmation experiment was also accomplished at the optimized conditions. 2- Experimental Work 2.1. Materials and system In each batch ECF experiment, 1.5 L of a simulated aqueous solution was prepared. Distilled water was used in the preparation of the simulated aqueous solution and all chemicals were of the reagent grade. R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 04 The reagents used were as follows: Manganese sulfate (MnSO4.H2O, 99 %), Sodium dodecylsulfate (SDS) as a collector in a stoichiometric ratio of 1:1, ethyl alcohol (C2H5OH, 0.1 vol. %) as pH regulators and bubbly agent, and Sodium sulfate (Na2SO4, 99.5 %) for preparing 0.1 M supporting electrolyte which used for growing the ionic strength, reducing the resistance between the electrodes, decreasing the oxide layer formation on the electrode which prevents or minimize the release of different ions from electrodes into the polluted solution. pH for all experiments was adjusted at 7.5. The ECF batch experiments have been conducted in a glass cell (17×12×14 cm) placed on a magnetic stirrer hot plate (JENWAY, Model 1000) at 250 rpm. Fig. 1 shows a scheme of the experimental apparatus. Two stainless steel woven wire mesh electrodes (10×10 cm) were used as anode and cathode that fixed on a handmade acrylic frame (10.5×10.5 cm) with (L) shape. The vertical part of this frame is firmed on the edge of the cell, while the horizontal part is perforated with 42 holes (0.5 cm). The cathode is firmed at the top while anode at the bottom, the distance between the two electrodes was 1 cm. Both electrodes were connected to a DC power supply (UNI-T: UTP3315TF-L). Prior to each experiment, the electrodes were rinsed with HNO3 solution (1M) in an ultrasound cleaner and then washed carefully with double-distilled water. All experiments were carried out at the laboratory temperature and performed in duplicate and the average value of the removal percentage (Re%) was taken. To follow the progress of ECF experiments, samples were taken before each experiment and at the end. The final sample was filtered using Whatman filter paper (0.15µm) to exclude the sludge generated throughout electrolysis or centrifuged if necessary. The residual concentration of Mn was measured by atomic absorption spectroscopy (Varian SpectrAA 200 spectrometer). Removal efficiency can be expressed as ‎[26]: (8) Where: C0 and Cf represent the initial and final concentration of manganese ions in ppm respectively. Fig. 1. A schematic photo of ECF cell Three types of 316-AISI stainless steel screens were used with mesh numbers 18, 24, 30 wire/inch. For each screen, the porosity ( ) was estimated by applying Eq. (9) ‎[27]: (9) Where the weight/area ratio ( of the screen was equal to 0.1334, 0.1334, and 0.1237 (g/cm 2 ) for the three screens respectively, the screen thickness equal to (l=2d), and the density of 316-AISI stainless steel is 8.027 (gm/cm 3 ) ‎[27]. The diameter (d) of the wire of each screen was measured by digital caliper, and they were 0.04, 0.034, and 0.03 cm for the three screens respectively. While the woven type of the screen was identified by using an Olympus BX51M with DP70a digital camera system and it was Plain Square. The porosity values for the three screens were 0.7907, 0.7538, and 0.7146 respectively. Then the specific surface area ( ) was estimated by Eq. (10) ‎[27]: (10) Where, r is the ratio of surface to volume of the wire forming the screen and it is equal to (4/d), and the calculated specific surface area was equal to be 20.93, 28.964, and 38.055 cm -1 for the three screens respectively. 2.2. Design of Experiments (DOE) An operative method for the analyzing of experimental results of a study and evaluating the distinct contribution of controlling parameters on the objective functions can be obtained by applying DOE methods based on the statistical techniques. Moreover, process optimization, cost minimization, quality enhancement as well as the provision of strong design solutions can be achieved by these methods. Taguchi optimization technique is known as a robust, distinctive, and prevailing optimization discipline that permits optimization with a minimum number of experiments ‎[28], ‎[29]. There are many previous studies deals with the investigation of removal of different pollutants from wastewater by applying Taguchi optimization method ‎[30]–‎[35]. Taguchi design of experimental technique was used in this study to detect the most controlling parameters on Mn ions removal, minimize the number of experiments, optimize the four studied parameters, and obtain the optimal operating conditions for Mn ions removal which have a prevailing influence on the performance of ECF process. R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 04 Four factors were investigated in this present study: initial concentration of Mn (coded A) with two levels (100, 50 ppm) corresponding to levels 1 and 2; the other factors with three levels were current density (coded B) (20, 30, 40 mA/cm 2 ), electrolysis time (coded C) (40, 80, 120 min), and mesh number (coded D) (18, 24, 30 wire/inch) corresponding to levels 1, 2, and 3. According to the Taguchi experiment design, the suitable orthogonal array which allows studying the influence of the considered parameters and the interaction between them for these mixed levels would be L18 either (3 3 × 2 1 ) array that presented in Table 1 and the experiments were conducted according to these conditions. Table 1. Coded values of L18 orthogonal array Exp. No. Coded Values A B C D 1 1 1 1 1 2 1 1 2 2 3 1 1 3 3 4 1 2 1 1 5 1 2 2 2 6 1 2 3 3 7 1 3 1 2 8 1 3 2 3 9 1 3 3 1 10 2 1 1 3 11 2 1 2 1 12 2 1 3 2 13 2 2 1 2 14 2 2 2 3 15 2 2 3 1 16 2 3 1 3 17 2 3 2 1 18 2 3 3 2 Consequently, an analysis of the signal-to-noise (S/N) ratio is needed for assessing the experimental results. In Taguchi technique, the performance characteristics (S/N) are performed into three options: “larger is the better (LB)”, “nominal the-best (NB)”, and “smaller-the-better (SB)”. The highest Mn ions removal percentage (Re%) was the objective of this study, therefore the larger is the better criteria was implemented for the present study. The S/N ratio with LB characteristics can be performed as in Eq. (11) ‎[36], ‎[37]: ∑ ] (11) Where n is the number of repetitions under the same experimental conditions, and yi is the performance results of the ith experiment. MINITAB 17 software was used for analyzing the experimental data. 3- Results and Discussion 3.1. Optimization and The Signal- to- Noise analysis The investigation of the relationship between removal percentage of Mn ions and the controllable factors can be obtained by multiple linear regression equation which was developed by using MINITAB 17 software. The mathematical model for Mn ions removal percentage through the statistical analysis is given by Eq. (12) (with the correlation coefficient R 2 being equal to 90.16%, which implicates a good fitting of the model): (12) Table 3 shows the experimental and predicted values of the L18 orthogonal array for Mn ions removal percentage. Table 2 also shows the response calculated based on Eq. (12) which represents the predicted values of Re% and the S/N ratios that determined based on Eq. (11) for all the responses of experiments. Fig. 2 shows the comparison between the experimental results and the predicted results based on Eq. (12). It is obvious that the model predicts reasonably well for Mn ions removal and Eq. (12) can be considered as a good tool for process assessment. Fig. 2. Comparison between Experimental and predicted Re% values of Mn removal 0 20 40 60 80 100 120 1 3 5 7 9 11 13 15 17 R e % Exp. No. Experimental Re% Predicted Re% R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 04 Table 2. Experimental and predicted values of Re% and S/N ratios results of all experiments Exp . No. Real Values Exp. Predicted S/N Ratio Mn Conc. (ppm) C.D. (mA/cm 2 ) Time (min) Mesh number (mm) 1 100 20 40 18 62.34 60.55 35.7609 2 100 20 80 24 71.20 69.03 36.8105 3 100 20 120 30 89.20 85.87 38.5413 4 100 30 40 18 67.98 71.85 37.0369 5 100 30 80 24 75.49 80.33 38.0865 6 100 30 120 30 95.94 97.17 39.8172 7 100 40 40 24 78.41 77.75 37.7845 8 100 40 80 30 97.30 91.50 39.2318 9 100 40 120 18 92.87 96.68 39.7352 10 50 20 40 30 62.96 66.07 36.4151 11 50 20 80 18 65.86 68.16 36.6351 12 50 20 120 24 77.85 79.73 37.9682 13 50 30 40 24 78.26 71.73 37.1494 14 50 30 80 30 82.67 85.47 38.5967 15 50 30 120 18 96.87 90.66 39.1002 16 50 40 40 30 80.90 82.90 38.2947 17 50 40 80 18 86.96 84.99 38.5147 18 50 40 120 24 93.93 96.56 39.8478 Table 3 shows the mean of the response of each factor at a certain level and it was represented graphically in Fig. 3. At each column of this table, the bold values refer to the maximum calculated mean of response (Mn Re%). It is obvious from the results of mean response that the most essential factors are in the following order: time ˃ C.D. ˃ Mesh number ˃ initial Mn concentration. Table 3. calculated mean of response for data obtained from Mn removal experiments Level Mn Conc. C.D time Mesh number 1 81.19 71.57 71.81 78.81 2 80.70 82.87 79.91 79.19 3 - 88.39 91.11 84.83 Delta 0.50 16.83 19.30 6.02 Rank 4 2 1 3 Fig. 3. Main effect plot for means values of Re% for Mn removal The response table for the calculated Signal to Noise Ratios (LB) and the ranks of the four studied factors are shown in Table 4 and which is represented graphically in Fig. 4; these ranks are based on delta statistics which compare the relative magnitude of effects. The highest average for each factor minus the lowest average for the same is the delta statistics ‎[38]. Lager the S/N ratio means higher the Mn Re%. So, in this table, the boldfaces refer to the maximum value of the S/N ratios of a certain factor among three levels for (time, C.D., and Mesh number) and for two levels of Mn Conc., It was obvious from the ranks attained for each factor that time is the most influential factor, whereas C.D., mesh size, and Mn Conc. were the least influential factors for Mn respectively. Based on the optimization of the multiple regression equation (Eq. (12)) and the results of means and S/N ratios, the optimum factors were initial Mn Conc. (A) of 100 ppm, C.D. (B) of 40mA/cm 2 , Time (C) of 120 min, and mesh number (D) of 30 wire/inch. Table 4. Response table for S/N (larger is better) Level Mn Conc. C.D time Mesh number 1 38.09 37.02 37.07 37.80 2 38.06 38.30 37.98 37.94 3 - 38.90 39.17 38.48 Delta 0.03 1.88 2.09 0.69 Rank 4 2 1 3 R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 00 Fig. 4. Main effect plots of S/N (larger is better) for Mn Re % 3.2. Analysis of Variance (ANOVA) ANOVA statistical method was implemented to evaluate the significance of the controlling parameters by estimating the percentage contribution of each factor which is the portion of a total observed variance in the experiment for each significant factor. The greater value of contribution percentage for any studied parameter means that it has a high contribution to the final results. Also, a superior understanding can be obtained by this analysis and it shows if the detected results are reliable and whether or not the conductance of experiments was at the controlled conditions. ANOVA was established based on the degree of freedom (DF), the sum of the square (SS), the percentage contribution of each parameter, the adjusted sum of squares (Adj SS), the adjusted mean of the square (Adj MS), F-value, and P- value. All these values are calculated for each controllable factor ‎[29], ‎[39]. The results of ANOVA for the present study are depicted in Table 5. It is obvious from the results that the most significant factors that affect Mn removal efficiency were as in the following order: time > C.D. > Mesh size > Mn Conc., based on their contribution %. The significance of each factor on the response is also can be determined by P-value, which is defined as a relation between the parameters’ sum of the square to the total sum of square. If the p-value is lower than 0.05 (for a confidence level of 95%), this means that the parameter is significant ‎[40]. It can be concluded from the results of P-values (which based on a confidence level of 95%) for time and C.D. that these parameters were significant, while mesh size had a fair significance and initial Mn conc. had no significance in the chosen range in this study. When F > 1 for the controllable parameters, this revealed that the error variance is lower than variances of these factors, and signifying that these controllable factors had major effects on the responses ‎[29]. So, based on the results of the present study all the studied factors were significant except initial Mn concentration. Table 5. Analysis of Variance (ANOVA) for Mn removal Source DF Seq SS Contribution% Adj SS Adj MS F- Value P- Value Mn Conc. 1 1.11 0.05 % 1.11 1.110 0.05 0.831 C.D. 2 882.74 37.13 % 882.74 441.371 19.19 0.000 Time 2 1127.22 47.42 % 1127.22 563.611 24.51 0.000 Mesh number 2 136.23 5.73 % 136.23 68.113 2.96 0.098 Error 10 229.95 9.67 % 229.95 22.995 - - Total 17 2377.25 100.00% - - - - 3.3. Confirmation experiment The confirmation experiment is an important step and is highly endorsed by the Taguchi approach to validate the experiment results. In this study, two confirmation experiments were carried out by utilizing the optimum parameters. The results showed that Mn Re% was 99.34 and 99.45% respectively.\ 3.3. Effect of Operative Factors a. Effect of initial Mn Concentration Fig. 5 was plotted by applying Eq. (12) at the optimum conditions and it shows the effect of Mn initial concentration on the removal efficiency of the ECF process. It is obvious that increasing the initial concentration of Mn leads to increase in the predicted removal efficiency and this result is in agreement with previous studies ‎[4]. However, the chosen range of Mn initial concentration had not that great influence on the removal efficiency and this was clear from the results of S/N and ANOVA when the F- value was 0.05 either less than 1 and the contribution percentage was 0.05% which means that it was not a significant factor on the process performance. Fig. 5. Effect of initial Mn Concentration on Mn Re% at C.D. = 40 mA/cm 2 and mesh number = 30 mm R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 04 b. Effect of Current Density It is well known that one of the most effective parameters in the ECF process generally is the current density. The efficiency of this process is affected directly by the value of this parameter. Flocs size and growth are affected by current density. Increasing current density leads to flocs generation with significant amounts due to more release of ferric ions by anodic dissolution (according to Faraday's law ‎[37] ( ⁄ ), and thereby more generation of iron hydroxides essential to coagulants formation. Also, the generation rate and distribution of H2 gas bubbles formed at the cathode are affected directly by the value of current density. Increasing the current density leads to an increase in bubble generation rate with a decreased in bubble size which leads to high metal removal by H2 flotation ‎[15], ‎[22], ‎[41]–‎[43]. Fig. 5 was plotted by applying Eq. (12) to examine the effect of increasing the current density on Mn Re %. Current density increased from 20 to 40(mA/cm 2 ) with 100 ppm of Mn, 120 min of electrolysis time, and using a screen with mesh number of 30 wire/inch. the removal efficiency increased from 86.734 at 20 mA/cm 2 to > 100% at 40 mA/cm 2 . Also, this was obvious from the results of S/N, increasing the current density leads to larger values of S/N which means higher Re% of Mn removal. Fig. 6. Effect of C.D. on Mn Re % at initial Mn conc. = 100 ppm and mesh number =30 wire/inch c. Effect of Electrolysis Time According to Faraday’s law mentioned previously, the amount of generated ferrous ions which is produced by anode dissolution is related to the electrolysis time of ECF process ‎[13], ‎[15], ‎[44]. In the present, study it was clear from the results of S/N and ANOVA that electrolysis time had the greatest impact on ECF performance. Increasing electrolysis time leads to an increase in flocs generation which causing an enhancement in Mn removal efficiency. The influence of electrolysis time on Mn Re % is obvious in Fig. 5 and Fig. 6 which was plotted by applying Eq. (12) at optimum conditions. It is evident that increasing electrolysis time gives an increase in Mn removal efficiency due to an increase in the number of generated ferrous hydroxide and an increase in the rate and size of H2 bubble production. For the example at 20 mA/cm 2 the removal efficiency increased from 70.158 to 86.734% by increasing electrolysis time from 40 to 120 min. d. Effect of Mesh number The mesh number of screens in the present study had the following values 14, 24, and 30 wire/inch and higher porosity and specific surface area had been attained by increasing the mesh number. Increasing mesh no. leads to an increase in the number of H2 bubbles which have a small size hence increasing the flotation efficiency and more pollutants can be removed. So, by increasing the mesh number the removal efficiency of Mn by ECF process was enhanced. This is obvious from Fig. 7 which represents the effect of different mesh number on the removal efficiency at optimum conditions. The results of S/N and ANOVA showed that changing mesh size had a fair significance on Mn Re %. Fig. 7. Effect of mesh number on Mn Re % at initial Mn conc. = 100 ppm and C.D. = 40 mA/cm 2 It is worthy to mention that in Figures (5-7), some Mn Re % values exceeded 100 %. This result is attained because these figures were plotted by applying Eq.(12), which represents the predicted values not the real one and also Minitab software does not have any sense of the figures and it makes the calculations by numerical procedure, this result is in agreement with a previous study ‎[29]. 0 20 40 60 80 100 0 20 40 60 80 100 120 R e % time (min) 20 (mA/cm^2) 30 (mA/cm^2) 40 (mA/cm^2) 0 20 40 60 80 100 0 20 40 60 80 100 120 R e % time (min) 18 wire/inch 24 wire/inch 30 wire/inch R. H. Salman/ Iraqi Journal of Chemical and Petroleum Engineering20,1 (2019) 39-48 04 5- Conclusions In the present work, the ECF batch process using stainless steel mesh sacrificial electrodes for the treatment of aqueous solution containing Mn was studied. The effect of Mn initial concentration, current density, electrolysis time, and mesh size of the screen electrodes was examined to detect their impact on the removal efficiency. Taguchi method was applied to optimize ECF operating factors. The results of S/N and ANOVA approved that the importance of operating parameters followed the order: time > C.D. > Mesh number > initial Mn Conc., with contribution percentage of 47.42, 37.13, 5.73, and 0.05 % respectively. The optimum conditions were 100 ppm of Mn concentration, 40 mA/cm 2 of current density, 120 min of electrolysis time, and 30 wire/inch of mesh number. It can be concluded from the results of the present study that electrolysis time and current density were the most influential parameters and the mesh size that has not been widely investigated in previous studies revealed a fair effect on ECF process, while Mn initial concentration had not any mentioned effect on the performance of the removal efficiency. Two confirmation tests were conducted at optimum conditions gave Mn removal efficiency higher than 99%. Consequently, it can be concluded that the ECF process with stainless steel mesh electrodes was very effective in Mn removal. 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( من مياه الصرف المصنعة بواسطة تقنيات التخثر/ التعويم +Mn2إزالة أيونات المنغنيز ) الكهربائية باستخدام أقطاب الفوالذ المشبكية: أيجاد الظروف المثمى بواسطة طريقة تاكوشي الخالصة / انصشف انصحٓ ثُاسطخ رقىٕبد انزخثشفٓ ٌزي انذساسخ ، رم انزحقق فٓ كفبءح إصانخ أُٔوبد انمىغىٕض مه مٕبي ( ، صمه انزحهٕم انكٍشثبئٓ ، .C.Dانزعُٔم انكٍشثبئٕخ. رمذ دساسخ رأثٕش رشكٕض انمىغىٕض األثزذائٓ ، كثبفخ انزٕبس ) ٕخ مه خالل رطجٕق رصمٕم ربكُشٓ الٔجبد انظشَف انمثهّ َحجم انمشجك ألقطبة انفُالر انمشجكٕخ فٓ خهٕخ دفع ٌُ ( أن انظشَف انمثهّ كبوذ, انزشكٕضاألثزذائٓ نهمىغىٕضS/Nألقصّ كفبءح إصانخ نهمىغىٕض. أظٍشد وزبئج ) َأش/أوج. 30دقٕقخ ، َشجكخ راد حجم 120، ََقذ 2مههٓ أمجٕش / سم C.D. ٌُ4 جضء فٓ انمهُٕن ، 100 ( انزْ ٔشٕش إنّ أن انىسجخ ANOVAرم ثحث األٌمٕخ انىسجٕخ نكم عبمم عه طشٔق رحهٕم انزجبٔه ) أٔضب ، ( ، َ 5.43%( ، حجم انمشجك )34.13 %) .C.D( ، 44.42%انمئُٔخ نهمسبٌمخ رزجع انزشرٕت: انُقذ ) ُامم األكثش رأثٕشاً َحجم كبوذ ٌٓ انع .C.D(. َقذ انزحهٕم انكٍشثبئٓ َ 0.05%انزشكٕضاألثزذائٓ نهمىغىٕض ٌُ ) انشجكخ نً رأثٕش مقجُل عهّ كفبءح إصانخ أُٔوبد انمىغىٕض ، فٓ حٕه أن انزشكٕضاألثزذائٓ نهمىغىٕض نم ٔكه نً رأثٕش Rمزكُس فٓ انمذِ انمذسَط. أظٍش رحهٕم االوحذاس ) 2 ( ارفبقب جٕذا ثٕه انقٕم انزجشٔجٕخ َانقٕم 90.16 = % .99%رأكٕذ أن كفبءح إصانخ انمىغىٕض فٓ انظشَف انمثهّ كبوذ أعهّ مه انمزُقعخ ، َأظٍشد انىزبئج ٓانكهمبد انذانخ: أصانخ انمىغىٕض, انزخثشانكٍشثبئٓ, انزعُٔم انكٍشثبئٓ, أقطبة انفُالر, األقطبة انمشجكٕخ, مٕبي انصشف , طشٔقخ ربكُش https://www.sciencedirect.com/science/article/pii/S1665642317300585?via%3Dihub https://www.sciencedirect.com/science/article/pii/S1665642317300585?via%3Dihub https://www.sciencedirect.com/science/article/pii/S1665642317300585?via%3Dihub https://www.sciencedirect.com/science/article/pii/S1665642317300585?via%3Dihub https://www.sciencedirect.com/science/article/pii/S1665642317300585?via%3Dihub https://link.springer.com/article/10.1007/s10098-014-0897-2 https://link.springer.com/article/10.1007/s10098-014-0897-2 https://link.springer.com/article/10.1007/s10098-014-0897-2 https://link.springer.com/article/10.1007/s10098-014-0897-2 https://link.springer.com/article/10.1007/s10098-014-0897-2 https://www.sciencedirect.com/science/article/abs/pii/S0379677914001829?via%3Dihub https://www.sciencedirect.com/science/article/abs/pii/S0379677914001829?via%3Dihub https://www.sciencedirect.com/science/article/abs/pii/S0379677914001829?via%3Dihub https://www.sciencedirect.com/science/article/abs/pii/S0379677914001829?via%3Dihub https://www.sciencedirect.com/science/article/abs/pii/S0379677914001829?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0301479713006816?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0301479713006816?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0301479713006816?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0301479713006816?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0301479713006816?via%3Dihub https://pubs.acs.org/doi/abs/10.1021/je200554z https://pubs.acs.org/doi/abs/10.1021/je200554z https://pubs.acs.org/doi/abs/10.1021/je200554z https://pubs.acs.org/doi/abs/10.1021/je200554z https://pubs.acs.org/doi/abs/10.1021/je200554z https://www.sciencedirect.com/science/article/pii/S0011916410003048?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0011916410003048?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0011916410003048?via%3Dihub https://www.sciencedirect.com/science/article/pii/S0011916410003048?via%3Dihub https://onlinelibrary.wiley.com/doi/abs/10.1002/ceat.201000091 https://onlinelibrary.wiley.com/doi/abs/10.1002/ceat.201000091 https://onlinelibrary.wiley.com/doi/abs/10.1002/ceat.201000091 https://onlinelibrary.wiley.com/doi/abs/10.1002/ceat.201000091 https://www.sciencedirect.com/science/article/pii/S0304389408011916 https://www.sciencedirect.com/science/article/pii/S0304389408011916 https://www.sciencedirect.com/science/article/pii/S0304389408011916 https://www.sciencedirect.com/science/article/pii/S0304389408011916 https://www.sciencedirect.com/science/article/pii/S0304389408011916 https://www.tandfonline.com/doi/full/10.1080/19443994.2015.1049562 https://www.tandfonline.com/doi/full/10.1080/19443994.2015.1049562 https://www.tandfonline.com/doi/full/10.1080/19443994.2015.1049562 https://www.tandfonline.com/doi/full/10.1080/19443994.2015.1049562 https://www.tandfonline.com/doi/full/10.1080/19443994.2015.1049562