Special Issue "Advanced Applications of Electrocoagulation in Water and Wastewater"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Wastewater Treatment and Reuse".

Deadline for manuscript submissions: closed (31 December 2020).

Special Issue Editors

Prof. Dr. Rafid Alkhaddar
E-Mail Website
Guest Editor
Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool, UK
Interests: water and wastewater treatment; water resources and conservation
Special Issues and Collections in MDPI journals
Dr. Patryk Kot
E-Mail Website
Guest Editor
Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool, UK
Interests: sensor development; water quality; non-destructive testing; water quality monitoring
Special Issues and Collections in MDPI journals
Dr. Khalid Hashim
E-Mail Website
Guest Editor
Built Environment and Sustainable Technologies (BEST) Research Institute, Liverpool John Moores University, Liverpool, UK
Interests: electrocoagulation applications in water and wastewater treatment; advanced water treatment methods; water quality monitoring
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Advanced Applications of Electrocoagulation in Water and Wastewater (AAEWW) is a Special Issue of Water devoted to the interdisciplinary subject of electrocoagulation and all apsects related to water and wastewater, both theoretical and applied. AAEWW focuses on the publication of both original work and reviews in the field of electrocoagulation treatment. AAEWW provides fast dissemination of original articles, reviews, short communications, and full communications covering the whole field of electrocoagulation applications in water and wastewater. Short communications are limited to a maximum of 21,000 characters (including spaces) whereas full communications are limited to 26,000 characters (including spaces). We aim to be the fastest-published Special Issue in the journal.

AAEWW welcomes the research fields covered by the following areas:

  • Fundamental electrocoagulation,
  • Mechanisms of electrode reaction,
  • Computational and theoretical electrocoagulation,
  • Morphology of electrodes,
  • Green energy and electrocoagulation,
  • Interference between pollutants,
  • Combining electrocoagulation with other technologies, and
  • Application of sensors in electrocoagulation.

The editors would like to draw particular attention to the quality and the scientific content of submissions. Papers must be presented in a way that is accessible to the readers. The presentation and discussion must be at a level that meets the global status of Water.

The AAEWW will not publish papers that have been partially or completely published in other journals, or papers that plagiarize other works. All submitted papers are screened for similarity with published works. High similarity will result in rejection without review.

Prof. Rafid Alkhadar
Dr. Patryk Kot
Dr. Khalid Hashim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electrocoagulation
  • water
  • wastewater
  • sensors

Published Papers (10 papers)

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Research

Article
Arsenic Removal from Highly Contaminated Groundwater by Iron Electrocoagulation—Investigation of Process Parameters and Iron Dosage Calculation
Water 2021, 13(5), 687; https://doi.org/10.3390/w13050687 - 03 Mar 2021
Viewed by 632
Abstract
Electrocoagulation (EC) is gaining increased attention for water treatment as it efficiently removes various water contaminants. Therefore, EC was applied to remove arsenic from groundwater of a highly contaminated site in Hamburg, Germany. Groundwater containing 3250 and 14,600 µg/L arsenic, mainly as Arsenite [...] Read more.
Electrocoagulation (EC) is gaining increased attention for water treatment as it efficiently removes various water contaminants. Therefore, EC was applied to remove arsenic from groundwater of a highly contaminated site in Hamburg, Germany. Groundwater containing 3250 and 14,600 µg/L arsenic, mainly as Arsenite (As(III)), was treated in three different EC batch reactors using a monopolar parallel electrode-configuration. This study focused on iron EC with constant current densities and variable voltage, to investigate the influence of current density, surface to volume ratio, initial arsenic concentration and water volume on the removal of arsenic and the influences on the groundwater composition. Arsenic removal >99.9% was achieved for configurations with high iron dosage after four hours of EC treatment. German drinking water standard for arsenic (<10 µg/L) was obtained after around two hours depending on the applied current densities. Arsenic removal efficiency shows independence from current density, surface to volume ratio, initial concentration and water volume, with respect to the calculated iron dosage. Consequently, the dimensioning and regime of efficient operation of the EC reactor for arsenic removal from groundwater can be calculated solely from the iron dosage determined by the applied current. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Adsorption of Organic Pollutants from Cold Meat Industry Wastewater by Electrochemical Coagulation: Application of Artificial Neural Networks
Water 2020, 12(11), 3040; https://doi.org/10.3390/w12113040 - 29 Oct 2020
Viewed by 576
Abstract
The cold meat industry is considered to be one of the main sources of organic pollutants in the wastewater of the meat sector due to the complex mixture of protein, fats, and dyes present. This study describes electrochemical coagulation (EC) treatment for the [...] Read more.
The cold meat industry is considered to be one of the main sources of organic pollutants in the wastewater of the meat sector due to the complex mixture of protein, fats, and dyes present. This study describes electrochemical coagulation (EC) treatment for the adsorption of organic pollutants reported in cold meat industry wastewater, and an artificial neural network (ANN) was employed to model the adsorption of chemical oxygen demand (COD). To depict the adsorption process, the parameters analyzed were current density (2–6 mA cm−2), initial pH (5–9), temperature (288–308 K), and EC time (0–180 min). The experimental results were fit to the Langmuir and Freundlich isotherm equations, while the modeling of the adsorption kinetics was evaluated by means of pseudo-first and pseudo-second-order rate laws. The data reveal that current density is the main control parameter in EC treatment, and 60 min are required for an effective adsorption process. The maximum removal of COD was 2875 mg L−1 (82%) when the following conditions were employed: pH = 7, current density = 6 mA cm−2, and temperature of 298 K. Experimental results obey second-order kinetics with values of the constant in the range of 1.176 × 10−5k2 (mg COD adsorbed/g-Al.min) ≤ 1.284 × 10−5. The ANN applied in this research established that better COD removal, 3262.70 mg L−1 (93.22%) with R2 = 0.98, was found using the following conditions: EC time of 30.22 min, initial pH = 7.80, and current density = 6 mA cm−2. The maximum adsorption capacity of 621.11 mg g−1 indicates a notable affinity between the organic pollutants and coagulant metallic ions. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Ecologically Non-Invasive Decontamination of Natura 2000 Locality from Old Deposits of Hexavalent Chromium and Bivalent Nickel by Modular Electrocoagulation Combined with Ca(OH)2 Addition
Water 2020, 12(10), 2894; https://doi.org/10.3390/w12102894 - 16 Oct 2020
Viewed by 467
Abstract
A modular electrocoagulation unit, supported by Ca(OH)2 addition to treated water, was operated in the vicinity of a Natura 2000 site for the removal of Cr6+ or Ni2+ from contaminated groundwater. The process was performed at a constant flow rate [...] Read more.
A modular electrocoagulation unit, supported by Ca(OH)2 addition to treated water, was operated in the vicinity of a Natura 2000 site for the removal of Cr6+ or Ni2+ from contaminated groundwater. The process was performed at a constant flow rate of 350 L/h. Day 0 concentrations of Cr6+ and Ni2+ started at 91.6 mg/L for Ni2+ and 43 mg/L for Cr and during testing, were decreased by 15%–25%. Residual concentrations of Crtot. and Ni2+ below the required limits of 0.5 mg/L for Crtot. and 0.8 mg/L for Ni2+ can be achieved with the electrocoagulation unit and total removal efficiencies often exceeded 98%. The overall economic assessment showed its feasible application for removal of Cr6+ and Ni2+ on sites with requirements of high environmental protection standards. The polluted area was about 150 × 150 m (22,500 m2), and it contained approximately 78,750 m3 of water contaminated with Cr6+ and Ni2+ (over 41 and 91 mg/L, respectively). The modular arrangement might allow a scaling up. The process’ output could be thus increased according to the number of EC modules in operation. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Energy Efficient Rapid Removal of Arsenic in an Electrocoagulation Reactor with Hybrid Fe/Al Electrodes: Process Optimization Using CCD and Kinetic Modeling
Water 2020, 12(10), 2876; https://doi.org/10.3390/w12102876 - 16 Oct 2020
Cited by 10 | Viewed by 870
Abstract
Threats due to insufficient, inadequate and costlier methods of treating contaminants such as arsenic have emphasized the significance of optimizing and managing the processes adopted. This study was aimed at the complete elimination of arsenic from an aqueous medium with minimum energy consumption [...] Read more.
Threats due to insufficient, inadequate and costlier methods of treating contaminants such as arsenic have emphasized the significance of optimizing and managing the processes adopted. This study was aimed at the complete elimination of arsenic from an aqueous medium with minimum energy consumption using the electrocoagulation process. Arsenic removal around 95% was rapidly attained for optimized conditions having a pH of 7, 0.46 A current intensity, 10 mg/L initial concentration and only 2 min of applied time duration using the energy of 3.1 watt-hour per gram of arsenic removed. Low values of applied current for longer durations resulted in the complete removal of arsenic with low energy consumption. Various hydroxide complexes including ferrous hydroxide and ferric hydroxide assisted in the removal of arsenic by adsorption along with co-precipitation. Surface models obtained were checked and found with a reasonably good fit having high values of coefficient of determination of 0.933 and 0.980 for removal efficiency and energy consumption, respectively. Adsorption was found to follow pseudo-first-order kinetics. Multivariate optimization proved it as a low-cost effective technology having an operational cost of 0.0974 Indian rupees (equivalent to USD 0.0013) per gram removal of arsenic. Overall, the process was well optimized using CCD based on response surface methodology. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Hybridised Artificial Neural Network Model with Slime Mould Algorithm: A Novel Methodology for Prediction of Urban Stochastic Water Demand
Water 2020, 12(10), 2692; https://doi.org/10.3390/w12102692 - 26 Sep 2020
Cited by 34 | Viewed by 1095
Abstract
Urban water demand prediction based on climate change is always challenging for water utilities because of the uncertainty that results from a sudden rise in water demand due to stochastic patterns of climatic factors. For this purpose, a novel combined methodology including, firstly, [...] Read more.
Urban water demand prediction based on climate change is always challenging for water utilities because of the uncertainty that results from a sudden rise in water demand due to stochastic patterns of climatic factors. For this purpose, a novel combined methodology including, firstly, data pre-processing techniques were employed to decompose the time series of water and climatic factors by using empirical mode decomposition and identifying the best model input via tolerance to avoid multi-collinearity. Second, the artificial neural network (ANN) model was optimised by an up-to-date slime mould algorithm (SMA-ANN) to predict the medium term of the stochastic signal of monthly urban water demand. Ten climatic factors over 16 years were used to simulate the stochastic signal of water demand. The results reveal that SMA outperforms a multi-verse optimiser and backtracking search algorithm based on error scale. The performance of the hybrid model SMA-ANN is better than ANN (stand-alone) based on the range of statistical criteria. Generally, this methodology yields accurate results with a coefficient of determination of 0.9 and a mean absolute relative error of 0.001. This study can assist local water managers to efficiently manage the present water system and plan extensions to accommodate the increasing water demand. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Removal of Cadmium from Contaminated Water Using Coated Chicken Bones with Double-Layer Hydroxide (Mg/Fe-LDH)
Water 2020, 12(8), 2303; https://doi.org/10.3390/w12082303 - 17 Aug 2020
Cited by 2 | Viewed by 741
Abstract
Occurrence of heavy metals in freshwater sources is a grave concern due to their severe impacts on public health and aquatic life. Cadmium (Cd2+) is one of the most dangerous heavy metals, and can cause serious diseases even at low concentrations. [...] Read more.
Occurrence of heavy metals in freshwater sources is a grave concern due to their severe impacts on public health and aquatic life. Cadmium (Cd2+) is one of the most dangerous heavy metals, and can cause serious diseases even at low concentrations. Hence, a wide range of treatment technologies exist, such as nanofiltration and biological reactors. In this context, the present investigation aims at the development of a new adsorption medium, made from chicken bones coated with iron (Fe) and magnesium (Mg) hydroxides, to remove cadmium from water. This novel chicken bone functional substance was manufactured by applying layered double hydroxides (LDH) into the chicken bones. Initially, the new adsorption medium was characterized using Fourier-transform infrared spectroscopy (FTIR technology), then it was applied to remove cadmium from water under different conditions, including pH of water (3–7.5), agitation speed (50–200 rpm), adsorbent dose (1–20 g per 100 mL), and contact time (30–120 min). Additionally, the reaction kinetics were studied using a pseudo-first order kinetic model. The results obtained from the present study proved that the new adsorption medium removed 97% of cadmium after 120 min at an agitation speed of 150 rpm, pH of 5, and adsorption dose of 10 g per 100 mL. The results also showed that the new adsorption medium contains a significant number of functional groups, including hydroxyl groups. According to the outcomes of the kinetic study, the mechanism of removing metal is attributed to surface precipitation, ion exchange, complexation, hydrogen binding between pollutants, and the LDH-chicken bone substance. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study
Water 2020, 12(7), 1885; https://doi.org/10.3390/w12071885 - 01 Jul 2020
Cited by 43 | Viewed by 2189
Abstract
The proper management of a municipal water system is essential to sustain cities and support the water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. This paper applies a novel methodology that [...] Read more.
The proper management of a municipal water system is essential to sustain cities and support the water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. This paper applies a novel methodology that includes data pre-processing and an Artificial Neural Network (ANN) optimized with the Backtracking Search Algorithm (BSA-ANN) to estimate monthly water demand in relation to previous water consumption. Historical data of monthly water consumption in the Gauteng Province, South Africa, for the period 2007–2016, were selected for the creation and evaluation of the methodology. Data pre-processing techniques played a crucial role in the enhancing of the quality of the data before creating the prediction model. The BSA-ANN model yielded the best result with a root mean square error and a coefficient of efficiency of 0.0099 mega liters and 0.979, respectively. Moreover, it proved more efficient and reliable than the Crow Search Algorithm (CSA-ANN), based on the scale of error. Overall, this paper presents a new application for the hybrid model BSA-ANN that can be successfully used to predict water demand with high accuracy, in a city that heavily suffers from the impact of climate change and population growth. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Optimization of Electrocoagulation Conditions for the Purification of Table Olive Debittering Wastewater Using Response Surface Methodology
Water 2020, 12(6), 1687; https://doi.org/10.3390/w12061687 - 12 Jun 2020
Cited by 4 | Viewed by 821
Abstract
In the present study, the optimization of electrocoagulation (EC) conditions for the purification of olive debittering wastewater (ODW) was investigated by response surface methodology (RSM). For this purpose, a central composite design (CCD) was employed to optimize the process variables including current density [...] Read more.
In the present study, the optimization of electrocoagulation (EC) conditions for the purification of olive debittering wastewater (ODW) was investigated by response surface methodology (RSM). For this purpose, a central composite design (CCD) was employed to optimize the process variables including current density (3.0–30.0 mA/cm2) and EC time (10.0–60.0 min). The results showed a significant effect of current density and EC time on the removal efficiency of total phenolic compounds (TPC) and chemical oxygen demand (COD). The best models obtained using the central composite design were quadratic polynomial for TPC (R2 = 0.993), COD (R2 = 0.982), and the inverse square root of turbidity (R2 = 0.926). Additionally, the square root of electrode consumption and energy consumption were appropriately fitted to the two-factor interaction (2FI) model (R2 = 0.977) and quadratic polynomial (R2 = 0.966) model, respectively. The predicted optimum conditions based on the highest removal efficiency for TPC were a current density of 21.1 mA cm−2 and an EC time of 58.9 min, in which the obtained model predicted 82.6% removal for TPC. This prediction was in agreement with the laboratory result (83.5%). The amount of energy consumption and the operating cost in these conditions was estimated to be 14.92 kWh and USD 6.49 m−3 per ODW, respectively. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
A Novel Methodology for Prediction Urban Water Demand by Wavelet Denoising and Adaptive Neuro-Fuzzy Inference System Approach
Water 2020, 12(6), 1628; https://doi.org/10.3390/w12061628 - 06 Jun 2020
Cited by 44 | Viewed by 1288
Abstract
Accurate and reliable urban water demand prediction is imperative for providing the basis to design, operate, and manage water system, especially under the scarcity of the natural water resources. A new methodology combining discrete wavelet transform (DWT) with an adaptive neuro-fuzzy inference system [...] Read more.
Accurate and reliable urban water demand prediction is imperative for providing the basis to design, operate, and manage water system, especially under the scarcity of the natural water resources. A new methodology combining discrete wavelet transform (DWT) with an adaptive neuro-fuzzy inference system (ANFIS) is proposed to predict monthly urban water demand based on several intervals of historical water consumption. This ANFIS model is evaluated against a hybrid crow search algorithm and artificial neural network (CSA-ANN), since these methods have been successfully used recently to tackle a range of engineering optimization problems. The study outcomes reveal that (1) data preprocessing is essential for denoising raw time series and choosing the model inputs to render the highest model performance; (2) both methodologies, ANFIS and CSA-ANN, are statistically equivalent and capable of accurately predicting monthly urban water demand with high accuracy based on several statistical metric measures such as coefficient of efficiency (0.974, 0.971, respectively). This study could help policymakers to manage extensions of urban water system in response to the increasing demand with low risk related to a decision. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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Article
Chromium Removal from Tannery Wastewater by Electrocoagulation: Optimization and Sludge Characterization
Water 2020, 12(5), 1374; https://doi.org/10.3390/w12051374 - 13 May 2020
Cited by 8 | Viewed by 1175
Abstract
The treatment of tannery effluent is of great interest as it contains a complex mixture of pollutants, primarily chromium. The disposal of this wastewater can have adverse effects on the environment and aquatic life, which is an emerging problem for the environment. In [...] Read more.
The treatment of tannery effluent is of great interest as it contains a complex mixture of pollutants, primarily chromium. The disposal of this wastewater can have adverse effects on the environment and aquatic life, which is an emerging problem for the environment. In this work, electrocoagulation is used to remove chromium from real tannery wastewater, focusing on performance optimization and sludge characterization. Electrocoagulation experiments were conducted using an electrochemical cell with iron electrodes immersed in a specific volume of tannery wastewater. Operating parameters, such as the initial chromium concentration, pH and current density as well as power consumption were evaluated to determine optimum chromium removal. The optimization was performed using Response Surface Methodology combined with central composite design. Analysis of variance (ANOVA) was used to determine the response, residual, probability, 3D surface and contour plots. The maximum chromium removal was 100% at the optimum values of 13 mA/cm2, 7 and 750 ppm for current density, pH and concentration, respectively. Full article
(This article belongs to the Special Issue Advanced Applications of Electrocoagulation in Water and Wastewater)
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