Techno-economical optimization of Reactive Blue 19 removal by combined electrocoagulation/coagulation process through MOPSO using RSM and ANFIS models

Advances in Nanohybrid Membranes for Dye Reduction: A Comprehensive Review

Separating valuable materials such as dyes from wastewater using membranes and returning them to the production line is a desirable environmental and economical procedure. However, sometimes, besides filtration, adsorption, and separation processes, pollutant destruction also can be suitable using photocatalytic membranes. The art of producing nanohybrid materials in contrast with nanocomposites encompasses nanomaterial synthesis as a new product with different properties from raw materials for nanohybrids versus the composition of nanomaterials for nanocomposites. According to the findings of this research, confirming proper synthesis of nanohybrid is one challenge that can be overcome by different analyses, other researchers' reports, and the theoretical assessment of physical or chemical reactions. The application of organic-inorganic nanomaterials and frameworks is another challenge that is discussed in the present work. According to the findings, Nanohybrid Membranes (NHMs) can achieve 100% decolorization, but cannot eliminate salts and dyes, although the removal efficiency is notable for some salts, especially divalent salts. Hydrophilicity, antifouling properties, flux, pressure, costs, usage frequency, and mechanical, chemical, and thermal stabilities of NHMs should be considered.

Removal of chromium from tannery industry wastewater using iron-based electrocoagulation process: experimental; kinetics; isotherm and economical studies

Chromium is a hazardous compound from industrial processes, known for its toxicity, mutagenicity, teratogenicity, and carcinogenicity. Chemical methods are efficient but cost-effective alternatives with reduced sludge are sought. Electro-coagulation, utilizing low-cost iron plate electrodes, was explored for factual tannery wastewater treatment in this manuscript. Operating parameters such as initial chromium concentration, voltage, electrode number, operating time, agitation speed and current density has been studied to evaluate the treatment effeciency. Under optimal conditions (15 V, 0.4 mA/cm2, 200 rpm, 330 ppm chromium, 8 iron electrodes with a total surface area of 0.1188 m2, 3 h), chromium elimination was 98.76%. Iron anode consumption, power use, and operating cost were 0.99 gm/L, 0.0143 kW-h/L, and 160 EGP/kg of chromium eliminated, respectively. Kinetics studies were pursued first-order reaction (97.99% correlation), and Langmuir isotherms exhibited strong conformity (Langmuir R2: 99.99%). A predictive correlation for chromium elimination (R2: 97.97%) was developed via statistical regression. At HARBY TANNERY factory in Egypt, industrial sewage treatment achieved a final chromium disposal rate of 98.8% under optimized conditions.

Modeling and optimization of the coagulation/flocculation process in turbidity removal from water using poly aluminum chloride and rice starch as a natural coagulant aid

The application of the coagulation/flocculation process is very important due to its simplicity in removing turbidity. Due to the disadvantages of using chemical coagulants in water and the lack of sufficient effect of natural materials alone in removing turbidity for proper performance, the simultaneous use of chemical and natural coagulants is the best way to reduce the harmful effects of chemical coagulants in water. In this study, the application of poly aluminum chloride (PAC) as a chemical coagulant and rice starch as a natural coagulant aid to remove turbidity from aqueous solutions was investigated. Effects of the above coagulants on the four main factors, coagulant dose (0-10 mg/L), coagulant adjuvant dose (0-0.1 mg/L), pH (5-9), turbidity (NTU 0-50), and each five levels were assessed using a central composite design (CCD). Under the optimized conditions, the maximum turbidity elimination efficiency was found to be 96.6%. The validity and adequacy of the proposed model (quadratic model) were confirmed by the corresponding statistics (i.e., F-value of 23.3, p-values of 0.0001, and lack of fit of 0.877 for the model, respectively, R2 = 0.88, R2adj. = 0.84, R2 pred = 0.79, AP = 22.04).

The role of the current waveform in mitigating passivation and enhancing electrocoagulation performance: A critical review

Electrocoagulation (EC) can be an efficient alternative to existing water and wastewater treatment methods due to its eco-friendly nature, low footprint, and facile operation. However, the electrodes applied in the EC process suffer from passivation or fouling, an issue resulting from the buildup of poorly conducting materials on the electrode surface. Indeed, such passivation gives rise to various operational problems and restricts the practical implementation of EC on a large scale. Therefore, it has been suggested that using pulsed direct current (PDC), alternating pulse current (APC), and sinusoidal alternating current (AC) waveforms in EC as alternatives to conventional direct current (DC) can help mitigate passivation and alleviate its associated detrimental effects. This paper presents a critical review of the impact of the current waveform on the EC process towards the capabilities of the PDC, APC, and AC waveforms in de-passivation and performance enhancement while comparing them to the conventional DC. Additionally, current waveform parameters influencing the surface passivation of electrodes and process efficiency are elaborately discussed. Meanwhile, the performance of the EC process is evaluated under different current waveforms based on pollutant removal efficiency, energy consumption, electrode usage, sludge production, and operating cost. The proper current waveforms for treating various water and wastewater matrices are also explained. Finally, concluding remarks and outlooks for future research are provided.

Comparison of high-concentration azo dye removal by long HRT in MSBRs' bioaugmented with GAC and sponge media

The present study assessed the performance and fouling of adding granular activated carbon (GAC) and sponge (BioCube), as two different media, to a membrane sequencing batch reactor (MSBR) system in wastewater treatment containing Acid Red 18 (AR 18). Anaerobic phase, aerobic phase, and hydraulic retention times (HRTs) of 24 h, 12 h, and 72 h were considered for 500 mg/L AR 18 removal at a sludge retention time (SRT) of 20 days by separately adding up to 35% BioCube volume and 8 g/L GAC to the reactors. Based on the kinetic study, 63 mg/L (87% removal) and 115 mg/L (77% removal) remaining dye were reported in the GAC and BioCube membrane sequencing batch reactors (GAC-MSBR and BioCube-MSBR), respectively. A gradual oxidation-reduction potential decline toward -416 mV confirmed better dye removal in GAC-MSBR than BioCube-MSBR, observing a sudden drop to -354 mV. The morphology can explain better biological treatment in GAC-MSBR in addition to the adsorption process. Soluble microbial products (SMPs) of 126.92 mg/L and 395.18 mg/L were obtained for GAC-MSBR and BioCube-MSBR, respectively. Chemical oxygen demand (COD) and SMP indicated that the GAC-MSBR water quality is better than that of the other reactor.

Artificial intelligence techniques in electrochemical processes for water and wastewater treatment: a review

In recent years, artificial intelligence (AI) techniques have been recognized as powerful techniques. In this work, AI techniques such as artificial neural networks (ANNs), support vector machines (SVM), adaptive neuro-fuzzy inference system (ANFIS), genetic algorithms (GA), and particle swarm optimization (PSO), used in water and wastewater treatment processes, are reviewed. This paper describes applications of the mentioned AI techniques for the modelling and optimization of electrochemical processes for water and wastewater treatment processes. Most research in the mentioned scope of study consists of electrooxidation, electrocoagulation, electro-Fenton, and electrodialysis. Also, ANNs have been the most frequent technique used for modelling and optimization of these processes. It was shown that most of the AI models have been built with a relatively low number of samples (< 150) in data sets. This points out the importance of reliability and robustness of the AI models derived from these techniques. We show how to improve the performance and reduce the uncertainty of these developed black-box data-driven models. From the perspectives of both experiment and theory, this review demonstrates how AI techniques can be effectively adapted to electrochemical processes for water and wastewater treatment to model and optimize these processes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-022-00835-w.

Electrocoagulation of Corrugated Box Industrial Effluents and Optimization by Response Surface Methodology

The electrocoagulation method using stainless steel anodes was applied to a corrugated cardboard box manufacturing plant's wastewater with high COD content. The effects of current density, processing time and stirring speed on response functions were studied using the Response Surface Methodology (RSM). The removal efficiency of chemical oxygen demand (COD) and energy consumption were selected as response functions. The Central Composite Design (CCD) was chosen to explain the single and combined effects of independent variables on response functions. The COD concentration of the real industrial wastewater used in the experiments was 9130 mg L-1. The maximum COD removal efficiency of 91.6% is obtained with 19.78 Wh g-1 energy consumption. Current density and treatment time were effective parameters for both COD removal and energy consumption. Optimization for maximum COD removal with minimum energy consumption showed 80.9% of COD removal with 6.7 Wh g-1 of energy consumption at 15 mA cm-2, 700 rpm, and 28 min treatment time. The variables are optimized with a few experiments using the response surface method.

Graphical abstract

Predicting coagulation-flocculation process for turbidity removal from water using graphene oxide: a comparative study on ANN, SVR, ANFIS, and RSM models

Three artificial intelligence (AI) data-driven techniques, including artificial neural network (ANN), support vector regression (SVR), and adaptive neuro-fuzzy inference system (ANFIS), were applied for modeling and predicting turbidity removal from water using graphene oxide (GO). Based on partial mutual information (PIM) algorithm, pH, GO dosage, and initial turbidity were selected as the input variables for developing the models. The prediction performance of the AI-based models was compared with each other and with the response surface methodology (RSM) model, previously reported by the authors, as well. The models' estimation accuracy was assessed through statistical measures, including mean-squared error (MSE), root-mean-square error (RMSE), mean absolute error (MAE), and coefficient of determination (R²). Among the evaluated models, ANN had the highest estimation accuracy as it showed the highest R² for the validation data (0.949) and the lowest MSE, RMSE, and MAE values. Furthermore, ANN predicted 76.1% of data points with relative errors (RE) less than 10%. In contrast, the weakest prediction performance belonged to the SVR model with the lowest R² for both calibration (0.712) and validation (0.864) data. Besides, only 57.1% of the SVR's predictions were characterized by RE < 10%. The ANFIS and RSM models exhibited a more or less similar performance in terms of R² for the validation data (0.877 and 0.871, respectively) and other statistical parameters. According to the results, the ANN technique is proposed as the best option for modeling the process. Nevertheless, as the RSM technique provides valuable information about the contribution of the independent operational parameters and their complex interaction effects using the least number of experiments, simulating the process by this technique before modeling by ANN is inevitable.

Modeling defluoridation of real-life groundwater by a green adsorbent aluminum/olivine composite: Isotherm, kinetics, thermodynamics and novel framework based on artificial neural network and support vector machine

The kinetic, isotherm, and thermodynamics of adsorptive removal of fluoride from the real-life groundwater was evaluated to assess the applicability of a green adsorbent, aluminum/olivine composite (AOC). The isotherm and kinetics were demonstrated by the Freundlich and Elovich model indicating significant surface heterogeneity of AOC in favouring the fluoride sorption. The fluoride removal efficiency of AOC was achieved as 87.5% after 240 min of contact time. The diffusion kinetic model exhibited that both the intra-particle and film diffusion together control the rate-limiting step of fluoride adsorption. A negative value of ΔG⁰ (-19.919 kJ/mol) at 303 K confirmed the spontaneous adsorption reaction of fluoride, and its endothermic nature was supported by the negative value of ΔH⁰ (39.504 kJ/mol). A novel framework for a predictive model by artificial neural network (ANN), and support vector machine (SVM) considering the real and synthetic fluoride-containing water was developed to assess the efficiency of adsorbent under different scenarios. ANN model was observed to be statistically significant (RMSE: 1.0955 and R²: 0.9982) and the proposed method may be instrumental in a similar area for benchmarking the synthetic and real-life samples. The low desorption potential of the spent adsorbent exhibited safe disposal of sludge and the secondary-pollutant-free treated water by the efficient and green adsorbent AOC enhanced the field-scale applicability of the green technology.

Combined electrocoagulation processes as a novel approach for enhanced pollutants removal: A state-of-the-art review

A novel approach using the integration of electrocoagulation, with one or more treatment processes has been recently practiced to improve the removal of colloidal and non-biodegradable pollutants. Several treatment processes including adsorption, chemical coagulation, magnetic field, reverse osmosis, and membrane filtration have been combined with electrocoagulation treatment step to improve pollutants removal efficiency. These combined systems showed the potential to improve the performance of the treatment process. This paper presents a state-of-the-art review for the recent processes available in the literature that combine treatment electrocoagulation with one of the previously mentioned treatment processes. It is found that the removal efficiency of any combined processes is higher than that of any single treatment process and the combined process has up to 20% higher removal efficiency compared to electrocoagulation alone. However, most reported studies were conducted at bench-scale level with synthetic wastewater instead of real wastewater. The main aspects of these combined systems including process mechanism, kinetic models, cost and the scale up of combined processes were discussed and summarized. Finally, several concluding remarks were drawn in view of the literature investigations and the gaps that suggest more studies and insights for future development were addressed.

Spectral deconvolution associated to the Gaussian fit as a tool for the optimization of photovoltaic electrocoagulation applied in the treatment of textile dyes

The objective of this study was to investigate the color removal in a binary mixture of azo dyes from the photovoltaic electrocoagulation (EC) technique, using spectral deconvolution and the Gaussian fit for qualitative and quantitative determination of the physical color parameter. Initially, a conventional energy source was used to feed the EC reactor and the experimental design was conducted according to the Rotational Central Compound Design (RCCD). The spectral deconvolution method associated to the Gaussian fit aided in the description of the composition of the sample matrix, In the first step, through the Analysis of Variance, the RCCD and the three-dimensional surface response graphs, the optimized operating conditions were identified, which corresponded to 1320 A m^-2 with an reaction time of 16.6 min, and an expected removal of 98.40% for Scarlet Red (SR) dye and 1160 A m^-2 with a run time of 15.7 min and 97.9% removal for Turquoise Blue (TB) dye. Using the photovoltaic module as the power source of the EC reactor, a maximum removal of 97 ± 0.43% for TB dye and 98% ± 0.81 for SR was obtained. The results encourage the applicability of photovoltaic module-fed EC technology as a promising alternative for the treatment of effluents containing textile dyes, as well as the use of the spectral deconvolution method associated with the Gaussian fit, for the reliability and precision of the results.

Wastewater treatment from the biodiesel production using waste cooking oil by electrocoagulation: a multivariate approach

This study mainly focuses on the process of electrocoagulation (EC) for the wastewater treatment from biodiesel production using waste cooking oil. The effects of current density, initial pH and electrolysis time on the EC process using aluminum (Al) and iron (Fe) electrodes were investigated for removal of chemical oxygen demand (COD). The COD removal efficiencies were found to be 62.7% and 63.4% at optimum conditions for Al (current density: 43 mA/cm², pH: 5, time: 21 min) and Fe (current density: 47 mA/cm², pH: 7.7, time: 30 min) electrodes, respectively. At these optimum conditions, the removal efficiencies of oil & grease, total phosphorus (TP), orthophosphate (PO4-P) and total suspended solids (TSS) were determined respectively to be above 89.9%, 98.9%, 99.5%, 86.7% for Al electrodes and 90.8%, 98.5%, 97.6%, 89.6% for Fe electrodes. Total operating costs were also found to be 6.43 €/m³ and 7.01 €/m³ for Al and Fe electrodes, respectively. The results indicate that the EC process using both types of electrodes seems to ensure an efficient treatment of biodiesel wastewater in terms of oil & grease and TP.

Application of Red Mud in Wastewater Treatment

Red mud (RM) is an industrial waste produced in large amounts during alumina extraction from bauxite. Its disposal generates serious environmental pollution due to high alkalinity. Therefore, a strategy for the effective utilization of RM must be developed. For instance, RM may be transformed into useful products, such as adsorbents. Given its high concentrations of aluminum oxides, iron oxides, titanium oxides, silica oxides, and hydroxides, RM may be developed as a cheap adsorbent for the removal of various ions from aqueous solution and soils (e.g., metal and non-metal ions, phenolic compounds, and dyes) and waste gas purification (sulfide and carbide). This review summarizes the background, properties, and applications of RM as an adsorbent. Proper approaches of removing metal and non-metal elements from wastewater are also systematically reviewed and compared. Emphasis is placed on the surface modification of RM to obtain high adsorption. Finally, the scope for future research in this area for RM is discussed in depth.

TiO2 coated on PVDF membrane for dye wastewater treatment by a photocatalytic membrane

This work investigated the membrane modification to increase hydrophilicity aiming for application in a photocatalytic membrane. The modified poly(vinylidene fluoride) (PVDF) flat sheet membrane was coated with titanium dioxide (TiO₂). The chemical and physical changes of membranes were characterized by contact angle, scanning electron microscopy and porosity. The results found that TiO₂ successfully modified the PVDF membrane by decreasing the contact angle from 127.1° to 114.3° on increasing the TiO₂ concentration from 0.1 to 1.0 g/L. The contact angles were decreased with the increase of coating time. The water permeation after PVDF membrane modification decreased compared with the original membrane, whereas water fluxes increased with the increase of TiO₂ concentration. TiO₂ particles were observed on the membrane surface while the porosity of the membrane coated with TiO₂ decreased. The optimum condition of membrane coating was obtained at 1.0 g/L of TiO₂ and 60 min of coating time. The decolorization of RB 19 by photolysis and photolysis followed by filtration was less than 10%; in contrast, the decolorization of RB 19 by photocatalytic oxidation was as good as a photocatalytic membrane for 60 min. The TiO₂ photocatalytic membrane is a feasible technology for RB 19 decolorization in wastewater.

Application of response surface methodology in physicochemical removal of dyes from wastewater: A critical review

Response surface methodology (RSM) is a powerful tool in designing the experiments and optimizing different environmental processes. However, when it comes to wastewater treatment and specifically dye-containing wastewater, two questions arise; "Is RSM being used correctly?" and "Are all capabilities of RSM being exploited properly?". The current review paper aims to answer these questions by scrutinizing different physicochemical processes that utilized RSM in dye removal. The literature that applied RSM to adsorption, advanced oxidation processes, coagulation/flocculation and electrocoagulation processes were critically reviewed in this paper. The common errors in applying RSM to physicochemical removal of dyes are identified and some suggestions are made for future studies.

Electrocatalytic degradation and minimization of specific energy consumption of synthetic azo dye from wastewater by anodic oxidation process with an emphasis on enhancing economic efficiency and reaction mechanism

This work focused on the knowledge-based methodology for the development of an electrochemical system, enabling simultaneous optimization of various operating parameters such as current density (j), initial dye concentration (C_o), NaCl concentration (C_N) for the mineralization of Reactive Violet 2 (RV-2) and Acid Brown 14 (AB-14) dye on the efficiency of removal, energy consumption (EC), Chemical Oxygen Demands (COD), apparent rate constants (k_app) and Electrical Energy per Order (E_EO) all of which have been examined. The relationship between k_app and E_EO is also discussed. The degradation efficiency and k_app always rising at higher j and lower C_o and C_N while EC, E_EO, and operating cost increased at higher j, C_o and C_N. On the other hand, The COD increased with decrease j, Co and higher C_N. Due to the strong formation of hydroxyl radicals from water discharge, the graphite electrode possesses a strong power of electro-generation rate and competitive wasting reactions of organic compounds. The results demonstrated that the relatively high dye removal, COD and low specific energy consumption are obtained simultaneously only if the various parameters are regulated to a plausible value j of 79Am^-2, Co of 100mg/L and C_N of 1g/L within 60min of electrolysis. The color removal efficiency is much faster for RV-2 compared to AB-14 due to the contribution of azo bond in the dye molecule. Also, the EC and k_app are higher for RV-2 than AB-14 while is lower in terms of E_EO and COD. A comprehensive reaction sequence of RV-2 and AB-14 mineralization involving all oxidation products was proposed. Formation and evolution of aromatic and aliphatic (short-chain carboxylic acids) intermediates during the treatment and a mineralization pathway is proposed. The estimated cost of operation for degradation at optimum conditions is calculated as 1.54 and 1.29 USD m^-3/g dye for complete degradation RV-2 and AB-14, respectively.

Relationship of cellulose and lignin contents in biomass to the structure and RB-19 adsorption behavior of activated carbon

Activated carbon microspheres prepared from biomass resources serve as green, highly efficient, and reusable adsorbents for reactive blue 19.

Adaptive Neuro-Fuzzy Inference system analysis on adsorption studies of Reactive Red 198 from aqueous solution by SBA-15/CTAB composite

In this study, the Mesoporous material SBA-15 were synthesized and then, the surface was modified by the surfactant Cetyltrimethylammoniumbromide (CTAB). Finally, the obtained adsorbent was used in order to remove Reactive Red 198 (RR 198) from aqueous solution. Transmission electron microscope (TEM), Fourier transform infra-red spectroscopy (FTIR), Thermogravimetric analysis (TGA), X-ray diffraction (XRD), and BET were utilized for the purpose of examining the structural characteristics of obtained adsorbent. Parameters affecting the removal of RR 198 such as pH, the amount of adsorbent, and contact time were investigated at various temperatures and were also optimized. The obtained optimized condition is as follows: pH=2, time=60min and adsorbent dose=1g/l. Moreover, a predictive model based on ANFIS for predicting the adsorption amount according to the input variables is presented. The presented model can be used for predicting the adsorption rate based on the input variables include temperature, pH, time, dosage, concentration. The error between actual and approximated output confirm the high accuracy of the proposed model in the prediction process. This fact results in cost reduction because prediction can be done without resorting to costly experimental efforts. SBA-15, CTAB, Reactive Red 198, adsorption study, Adaptive Neuro-Fuzzy Inference systems (ANFIS).

Parametric and energy consumption optimization of Basic Red 2 removal by electrocoagulation/egg shell adsorption coupling using response surface methodology in a batch system

In this study, response surface methodology (RSM) model was applied for optimization of Basic Red 2 (BR2) removal using electrocoagulation/eggshell (ES) coupling process in a batch system. Central composite design was used to evaluate the effects and interactions of process parameters including current density, reaction time, initial pH and ES dosage on the BR2 removal efficiency and energy consumption. The analysis of variance revealed high R(2) values (≥85%) indicating that the predictions of RSM models are adequately applicable for both responses. The optimum conditions when the dye removal efficiency of 93.18% and energy consumption of 0.840 kWh/kg were observed were 11.40 mA/cm(2) current density, 5 min and 3 s reaction time, 6.5 initial pH and 10.91 g/L ES dosage.

Optimization of material and energy consumption for removal of Acid Red 14 by simultaneous electrocoagulation and electroflotation

Decolorization of wastewater of industries which consume dye is an environmental priority. Electrocoagulation and electroflotation methods are appropriate for treatment of these wastewaters. This study investigates the effect of four parameters, electrical conductivity, current density, initial dye concentration, and initial pH, on the performance of a simultaneous electrocoagulation/electroflotation system for removal of Acid Red 14. The optimum values of these parameters were determined based on the amount of electrical energy and aluminum consumption and the best performance of coagulation and bubble generation. The optimum condition was revealed to be electrical conductivity=1,600 μS/cm, current density=60 mA/cm2, initial dye concentration=185 mg/L and initial pH=7. After less than 180 min of electrolysis, 90% dye removal was achieved with a specific energy consumption=102 kWh/kg dyeremoved, anode dissolution=2.09 kg Al/kg dyeremoved and sludge total suspended solids=15,050 mg/L. Liquid chromatography-UV-mass spectroscopy analyses were conducted on samples of raw and treated wastewater. Results showed that intermediate compounds formed from the breaking of the dye molecules. The advantages of this method are a low material and energy consumption. The amount of produced sludge was low; consequently sludge disposal and management costs would be reduced. This method should be used cautiously for treatment of textile wastewater due to the formation of intermediate compounds.