Hybrid RSM–ANN Modeling for Optimization of Electrocoagulation Using Aluminum Electrodes (Al–Al) for Hospital Wastewater Treatment

Optimization of electrocoagulation process for treatment of rice mill effluent using response surface methodology

This study aimed to examine the direct applicability of Spirulina maxima as a new conceptual method for removing total dissolved solids (TDS) from artificial industrial wastewater (AIW). In this study, live microalgal cells were used in a photobioreactor for TDS removal. The effects of TDS levels, pH, light intensity, and light retention time on microalgal growth and TDS removal were investigated, and optimal conditions were determined using the response surface method and Box-Behnken Design (RSM-BBD). The calculated values of coefficient of determination (R2), adjusted R2, and predicted R2 were 0.9754, 0.9508, and 0.636, respectively, which are close to the R2 values and validated the proposed statistical model. A second-order model could optimally determine the interactions between the studied variables according to the one-way analysis of variance (ANOVA). The results showed that increasing TDS levels reduced microalgal growth and TDS removal efficiency in AIW. S. maxima reduced TDS by 76% and 47% at TDS concentrations of 2,000-4,000 mg/L, respectively, when used in AIW. Maximum biomass efficiency (1.8 g/L) was obtained at a TDS concentration of 2,000 mg/L with other parameters optimized.

Electrocoagulation removal of COD and TDS from real municipal wastewater sourced from the Euphrates River using multipole arrangement

The objective of this study was to determine the effectiveness of two-stage electro-coagulation (EC) process using multi-parameter optimization for treating bio-digested distillery spent wash by stainless steel (SS) and aluminum (Al) electrodes. Operating parameters have been optimized and treatment efficiency of SS and Al electrodes have been compared by central composite design of response surface analysis in terms of COD, color and total organic carbon (TOC) removal. Individual and interactive effects of four independent parameters namely initial pH (pHo: 2–10 and 4–10 for SS and Al electrodes, respectively), current density (j: 30.86–154.32 A m−2), inter-electrode distance (g: 0.5–2.5 cm) and electrolysis time (t: 30–150 min) on the COD, color and TOC removal efficiency were evaluated for both the electrodes. SS electrode was found to be more effective for the removal of COD, color and TOC with removal efficiencies of 70%, 93% and 72%, respectively, as compared to Al electrode, which showed respective removal efficiencies of 59%, 80% and 55%. A two-stage EC process was also conducted to study the predominance of different types of electrodes, and to increase the efficiency of EC process. Results shows that SS followed by Al electrode (with total COD, color and TOC removal efficiency of 81%, 94% and 78%, respectively) was found to be more effective than Al followed by SS electrode combination (with total COD, color and TOC removal efficiency of 78%, 89% and 76%, respectively). Present study shows that EC process can be used as an additional step to bio-methanation process so as to meet effluent discharge standards in distilleries.

The aim of this research was to evaluate the efficiency of electrocoagulation (EC) for the removal of natural organic matter (NOM) by using iron (Fe) and aluminum (Al) electrodes. The effects of several operational parameters such as initial pH (3–10), time of electrolysis (5–30 min), initial concentration of organic matter (10–50 mg NOM/L), current density (0.25–1.25 mA/cm2), type of electrode material (n = 4, 2 sides × 11 cm × 10 cm, wall thickness = 2 mm, distance between each electrode = 5 mm), and type of connection of electrodes (bipolar and monopolar configurations) were explored for the removal of NOM from synthetic humic acid solution in a 2 L laboratory-scale EC cells (A s/V = 0.110 cm−1). The optimum conditions for the process were identified as pH = 3 and 7, electrolysis time = 20 and 10 min for Fe and Al electrodes, respectively. Using both electrodes at current density = 0.25 mA/cm2 and initial concentration of organic matter = 50 mg/L, a NOM removal efficiency of almost 100% could be achieved in the bipolar mode. Based on the optimum conditions, specific reactor electrical energy consumptions were 14.90 kWh/kg Al (or 0.092 kWh/m3) and 2.88 kWh/kg Fe (or 0.11 kWh/m3). Specific electrode consumptions were obtained to be 0.0062 and 0.0382 kg/m3, and operating costs of the EC system were preliminary estimated at 0.057 and 0.119 $/m3 for Al and Fe electrodes, respectively.

This study investigated the potential of ultrafiltration technology and/or biological treatment to remove contaminants such as total dissolved solids (TDS), chemical oxygen demand (COD), total organic carbon (TOC), and resin and fatty acids (RFAs) from recirculated white water. Batch ultrafiltration experiments indicated that TDS, soluble COD, and TOC removal efficiencies were affected by membrane molecular weight (molar mass) cut‐off, but were independent of the operating temperature, in the 20 to 60°C range. Except for fatty acids, where average removals exceeded 90%, the separation efficiency of the process for all other parameters (TDS, soluble COD, TOC, and resin acids) was moderate, ranging from 10 to 41%. Biological treatment using a sequencing batch reactor (SBR) unit was very effective in removing RFAs, TOC, total and soluble COD. Furthermore, ultrafiltration of the biologically treated process water resulted in significant additional TDS, soluble COD, and TOC removal.

This study examined the modelling and optimisation of the electrocoagulation-flocculation (ECF) recovery of aquaculture effluent (AQE) using aluminium electrodes. The response surface methodology (RSM), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) were used for the modelling, while the optimisation tools were the numerical RSM and genetic algorithm (GA). Furthermore, the kinetics of the ECF process was studied to provide insight into the mechanism governing the ECF of AQE. The experimental design was performed using the central composite design (CCD) of the RSM. The ANFIS modelling was accomplished via the Grid Partition (GP) of the data set, while the ANN used the multi-layer perceptron (MLP) based feed-forward system. Statistically, the prediction accuracy of the models followed the order: ANFIS (R2: 0.9990), ANN (R2: 0.9807), and RSM (R2: 0.9790). The process optimisation gave optimal turbidity (TD) removal efficiencies of 98.98, 97.81, and 96.01% for ANFIS-GA, ANN-GA, and RSM optimisation techniques, respectively. The ANFIS-GA gave the best optimization result at optimum conditions of pH 4, current intensity (3 A), electrolysis time (7.2min), settling time (23min), and temperature (43.8°C). In the kinetics study, the experimental data was analysed using pseudo-first-order (0.8787), pseudo-second-order (0.9395), and Elovich (R2: 0.9979) kinetic models; the Elovich model gave the best correlation with the experimental data showing that the process is governed by electrostatic interaction mechanism. This study effectively demonstrated that ECF recovery of AQE can effectively be modelled using RSM, ANN, and ANFIS and be optimised using RSM, ANN-GA, and ANFIS-GA techniques, and the order of performance is ANFIS > ANN > RSM and ANFIS-GA > ANN-GA > RSM, respectively.

Treatment of real printing wastewater using electrocoagulation process with titanium and zinc electrodes

New electrocoagulation (EC) method by alternative anode–cathode Al-Al (aluminium–aluminium) electrodes was used to reduce COD in petrochemical wastewater. No report of alternative electrocoagulation using switching electrocoagulation (SEC) has been published. The effect of voltage and current density (consumption energy), switching time, total time and the number of electrodes were investigated, and the removal efficiency, isotherms and kinetic data were calculated. Then, the process was optimised with the response surface methodology (RSM) and statistically significant factors, which affect the removal efficiency identified based on the Box–Behnken design (BBD). The interactions between voltage and switching time, and total time on the COD removal were statistically significant for both, two and four Al-Al electrodes. From the analysis of variance (ANOVA), quadratic models have been employed for COD removal, showing high coefficients of determination (R 2) of 0.9692 and 0.9442 for Al-Al electrodes. The optimum conditions for voltage, switching time and total time is 5 V, 15 s and 10 min, respectively, where 98.09% of COD removal by Al-Al could be obtained. Optimised COD removal per cent per energy consumption was 8.9396%/kJ. Biodegradability improvement confirmed by COD, total dissolved solids (TDS) and surface area analysis (BET) of the raw and treated wastewater showed removal and/or demand of aluminium and metal cations and other pollutions.

One of the most polluting industries in the world is the distillery industry, which produces strong distillery wastewater that has an adverse impact on the environment since it contains high organic matter. Using various combinations of electrodes in the electrocoagulation process, to examined the operational variables, viz., total dissolved solids (TDS), electrical conductivity (EC) and turbidity from the distillery spent wash. With a constant pH of 7, an agitation speed of 500 RPM, and optimizing the operating parameters, viz., varying the electrode distance (2, 3, 4, 5, and 6 cm), voltage (5–25 volts) current density of 1.5 A/cm2, and electrolysis time (30–150 min). Aluminium (Al) electrodes were observed to perform slightly better than iron (Fe) and zinc (Zn) electrodes, with punched Al electrodes outperforming plane Al electrodes. The highest removal efficiencies were achieved with punched Al electrodes in an optimized condition of voltage 25 volts, electrode distance (2 cm), and electrolysis time 150 minutes, with removal efficiencies of 91% for TDS, 92% for EC and 92% for turbidity. This study highlights the potential of electrocoagulation with optimized parameters for improving the purification of distillery spent wash and enhancing the removal of TDS, EC, and turbidity.

Chapter 8 - ANN prognostication and GA optimization of municipal solid waste leachate treatment using aluminum electrodes via electrocoagulation-flocculation method

Comparison of electrocoagulation using iron and aluminium electrodes with chemical coagulation for the removal of a highly soluble acid dye

The desalination process consists of a set of multi-step actions, which are conducted on saline water in order to remove excess salts and other minerals. In the desalination process, water is recovered, so that it would be suitable for industrial usage. In the present study, electrodialysis (ED) was used for desalination, especially for removing chloride (Cl-) ion and total dissolved solids (TDS), in Gohar Zamin Iron Ore Concentrate Plant (GIOCP). To optimize the influential factors in the removal of chloride and TDS in ED, the response surface methodology (RSM) was utilized. To this end, the D-optimal experimental design was applied to optimize the experiments. The effects of three independent parameters, including electrolysis time (A), consumption voltage (B), and initial concentration of chloride ion (C), were assess for the removal of chloride and TDS from recovered water. In addition, interactive and linear models were applied to determine the responses of chloride and TDS removal rates, respectively. The optimal operating conditions for the removal of chloride with 51.46% efficiency were obtained at the runtime of 30 minutes, consumption voltage of 12 V, and initial concentration of 300 ppm. Similarly, optimal TDS removal with 48.03% efficiency was achieved at the runtime of 30 minutes, consumption voltage of 12 V, and initial concentration of 300 ppm. According to the findings, ED was a highly reliable method for the removal of salts from water, as well as the high-quality recycling of water from mineral industries, especially in mineral processing plants.

Industrial sectors use high volumes of water and produce huge quantities of wastewater that are full of many types of pollutants, such as phosphates, total dissolved solids (TDS), and those that involve biological oxygen demand (BOD). In this study, the integrated sonolysis and pulsed electrochemical oxidation (S-PEO) process for treating industrial wastewater was examined, with a focus on maximizing pollutant removal and reducing energy usage. Optimal conditions for maximal treatment efficiency were determined by methodically varying key operational parameters, including initial pH, electrolysis time, and current. The results showed that, when the S-PEO process was run at optimal circumstances (pH of 7, electrolysis period of 40 min, and current of 0.5 Amp), it was produced remarkable removal efficiencies. With a low power consumption of 0.19 kWh/m3, the removal efficiencies for phosphates, TDS, and BOD were about 98.70 %, 97.44 %, and 95.49 %, respectively. To assess and optimize the process parameters, a methodical approach utilizing response surface methodology (RSM) and central composite design (CCD) was utilized. At a 95 % confidence level, statistical validation using analysis of variance (ANOVA) showed that the independent variables and their interactions had a meaningful impact. Additionally, the study used a quadratic regression model to estimate power consumption and pollutant removal efficiencies with accuracy. The model’s dependability is confirmed by the high value 0.91 of the correlation coefficient. These results emphasize the S-PEO process’s potential as an efficient and environmentally friendly method of treating industrial wastewater.

In the present work, electrocoagulation process was tested in a monopolar batch reactor 0,6L using Aluminum (Al) and Iron (Fe) electrodes for the treatment of cutting oil emulsion used in the manufacture of mechanical parts of the tractor construction factory of ETRAG (Entreprise-TRactors-AGriculture), Constantine, Algeria. Different operational conditions such as initial pH, current density, spacing between electrodes and electrolysis time were examined. The optimal current density, initial pH, electrodes spacing and electrolysis time were found using a Response Surface methodology (RSM) to be 173A/m2, 6.8, 1.7 Cm, 42 min, respectively for Aluminum electrodes and 287 A/m2, 2 Cm, 44 min for iron electrodes. Under these optimal conditions, turbidity and COD reductions were respectively: (Al: 99.96%, Fe: 99.63%) and (Al: 98.08%, Fe: 96.70%). The individual and interactions effects of the independent variables on the responses were studied using a plot of three dimensional response surfaces. It was found that the most determining factors in the removal of cutting oil by EC, using aluminum and iron electrodes are the electrolysis time, current density. Moreover, Al electrodes were found to be more efficient than Fe ones in terms of COD and Turbidity reductions. It should be mentioned, according to the obtained results, that the removal levels of turbidity and COD are not sufficient to meet discharge standards; therefore, EC would be perfect as a primary treatment which can be followed by another treatment such as biological one for instance.