Hybrid Electrocoagulation with Al Electrodes Assisted by Magnet and Zeolite: How Effective Is It for Compost Wastewater Treatment?

Abstract

This study investigates an innovative hybrid treatment for compost-derived wastewater, combining aluminum-based electrocoagulation (EC), zeolite addition, and magnet assistance. Key experimental variables—presence/absence of magnet, stirring speed (250 and 350 rpm), and contact time (10–30 min)—were systematically varied to analyze process efficiency, electrode dissolution and mass loss, solid–liquid separation dynamics, and quantify energy input and Faraday efficiency (FE). Magnet-assisted processes achieved higher COD reduction at longer treatment times of 30 min and lower mixing speeds of 250 rpm, with up to 89.87%. The highest turbidity reduction of 98.59% is achieved after 20 min at 350 rpm. The magnetic field does not significantly affect the dissolution of Al electrodes, but over time, it helps reduce localized electrode damage, thereby supporting both process efficiency and electrode longevity. Magnetic fields improved sludge settling in shorter treatments by promoting faster aggregation. However, the energy input was generally higher with magnetic assistance. FE in the range of 50.89–65.82% indicates that the actual electrode loss is lower than theoretical. For the experiments conducted according to the L8 Taguchi experimental design, given the significance and contribution of factors to the process, the optimal combination is the absence of a magnet, 350 rpm, and 20 min.

1. Introduction

The increasing generation of complex and highly loaded wastewater, driven by rapid industrialization and population growth, poses a significant environmental challenge. Inadequate treatment and uncontrolled discharge of such wastewater contribute to the deterioration of the water quality of natural water systems and affect the global scarcity of clean water resources [1]. Therefore, there is a need to develop and optimize efficient, sustainable, and cost-effective treatment technologies aligned with the principles of circular water use and environmental protection [2,3]. Among the various technologies investigated, electrocoagulation (EC) has attracted attention as a promising electrochemical technique for wastewater treatment due to its simplicity of operation, short reaction time, low amount of sludge production, and efficient and wide range of pollutant removal [4,5,6,7]. In EC, metal coagulants are generated in situ by the anodic dissolution of sacrificial electrodes (typically iron or aluminum), forming hydroxide flocs and polymeric complexes that destabilize colloidal and dissolved contaminants, facilitating their removal via sedimentation or flotation [8,9,10]. However, standalone EC processes can face limitations such as electrode passivation, high energy consumption, and incomplete removal of certain dissolved species [11]. To address these challenges, hybrid approaches combining EC with sorptive or functional materials have been increasingly investigated [12,13,14]. One such approach incorporates natural zeolite (ECZ), which acts as an ion exchanger and adsorbent, improves pollutant capture, reduces electrode fouling through mechanical abrasion, and allows zeolite regeneration and reuse [15,16,17]. Another enhancement strategy involves the application of a magnetic field during EC. Magnetic fields introduce magnetohydrodynamic (MHD) effects, which modify ion transport pathways, reduce the thickness of the diffusion layer, and can enhance electrochemical reaction kinetics [18,19]. Several studies have reported improved turbidity and suspended solids removal when magnetic fields were applied [20,21,22]. Beyond that, the application of magnetic fields in water and wastewater treatment has shown broader potential benefits, including reduced formation of scale [23,24,25], as well as changes in the physico-chemical properties of water (i.e., surface tension and conductivity) [26]. Moreover, magnetized water has been reported to positively affect microbial activity and biological growth, suggesting possible applications in bio-based treatment systems [27,28].

In a previous study [29], a novel configuration combining EC, zeolite, and magnetic field assistance (ECZ-MAG) was investigated using carbon steel (Fe) electrodes for the treatment of compost leachate. While chemical oxygen demand (COD) reduction up to 91% was achieved, the magnetic field did not significantly enhance pollutant removal compared to ECZ alone and was associated with increased electrode fouling after extended treatment times. In light of these findings, the present study explores using aluminum (Al) electrodes in a similarly configured ECZ-MAG system to evaluate whether different electrode materials can mitigate fouling, improve energy efficiency, and enhance treatment performance. Compost-derived wastewater was again used as a model of high-strength wastewater, this time with a significantly higher initial organic load (high COD concentrations). The study aims to provide deeper insight into the interplay between the electrode material and magnetic field application in hybrid EC systems. The novelty of this work lies in the systematic evaluation of magnetically assisted EC with zeolite (ECZ-MAG) using aluminum electrodes for the treatment of highly loaded compost-derived wastewater. This area has not been previously explored. By focusing on the synergistic effects of electrochemical reactions, magnetic fields, and sorptive media, this study contributes to developing advanced, integrated wastewater treatment solutions. The specific objective is to assess the impact of Al-based EC on pollutant removal efficiency, electrode dissolution, and energy consumption under magnetic assistance by identifying critical parameters for optimizing EC-based hybrid technologies.

2. Materials and Methods

2.1. Materials

The compost-derived wastewater used in this study was generated from a commercial Agro compost. Its initial physico-chemical characteristics, expressed as the average values ± standard deviation, were pH 3.95 ± 0.11, electrical conductivity 1900 ± 18.88 µS/cm, turbidity 251 ± 12.72 NTU, chemical oxygen demand (COD) 1642 ± 105 mg O₂/L, and total solids (TS) concentration of 3.08 ± 0.03 g/L [30]. Electrodes used in this study were made of aluminum alloy AA2007 (2000 series), predominantly composed of aluminum (92.58%) and copper (3.84%). A detailed elemental composition of the alloy is available in previously published sources [15]. Zeolite (Z) used in this study is synthetic, obtained from Alfa Aesar and labeled as NaX. The crushed zeolite NaX was sieved on a Retsch AS 200 digit laboratory sieve shaker (Retsch GmbH, Haan, Germany), using sieves of various mesh sizes and an amplitude of 2.5 mm. In this research, particles with a size below 0.04 mm were used. XRD analysis confirmed its classification within the Faujasite (FAU) framework. Characterization data, including PXRD and SEM-EDS, were previously reported [17]. Elemental analysis of the zeolite conducted through SEM/EDS mapping and the acquisition of a map sum spectrum revealed a composition primarily comprising silicon, aluminum, and oxygen, alongside exchangeable cations such as sodium, potassium, calcium, and magnesium, yielding a Si/Al ratio of approximately 2.07 [17]. Based on elemental data obtained, the estimated cation exchange capacity (CEC) for the zeolite is approximately 6.22 meq/g. The density of the zeolite is 2.0605 g/cm³. It was measured using the Anton Paar Ultrapyc 5000 gas pycnometer (Graz, Austria), by applying Boyle’s Law and the gas displacement principle with helium as the analysis gas.

2.2. Experimental Setup and Procedure

Compost-derived wastewater was treated using a hybrid EC process enhanced with zeolite and a magnetic field (ECZ-MAG). Experiments were performed in a laboratory-scale electrochemical reactor equipped with two parallel aluminum electrodes (AA2007 alloy), submerged at a fixed interelectrode distance of 3 cm. The reactor was operated at a constant current density of 0.0182 A/cm², with no pH adjustment prior to treatment. The current density was calculated by dividing the applied current by the total active surface area, considering both sides of the fully immersed electrodes. A synthetic zeolite (15 g/L) was added as a sorptive media, and NaCl (0.5 g/L) was added to enhance conductivity. Two mixing speeds (250 rpm and 350 rpm) and three contact times (10, 20, and 30 min) were applied in Series 1, which includes a total of 12 experiments. Series 1 consists of two groups of 6 experiments each. These two groups differ in the presence of a magnet. The first group of experiments was conducted without a magnet, while the second group was conducted with a magnet. To assess the influence of the magnetic field, a cubic-shaped neodymium magnet (NdFeB, 0.55 T) was positioned beneath the reactor in selected experiments. The experimental setup used to evaluate the performance of the ECZ and ECZ-MAG process is presented in Figure 1, while experimental conditions for Series 1 are summarized in

Table 1. Overview of experimental conditions.

Exp. Mark	Magnet	Mixing Speed, rpm	Contact Time, min
ECZ, 10 min, 250 rpm	no	250	10
ECZ, 20 min, 250 rpm	no	250	20
ECZ, 30 min, 250 rpm	no	250	30
ECZ, 10 min, 350 rpm	no	350	10
ECZ, 20 min, 350 rpm	no	350	20
ECZ, 30 min, 350 rpm	yes	350	30
ECZ-MAG, 10 min, 250 rpm	yes	250	10
ECZ-MAG, 20 min, 250 rpm	yes	250	20
ECZ-MAG, 30 min, 250 rpm	yes	250	30
ECZ-MAG, 10 min, 350 rpm	yes	350	10
ECZ-MAG, 20 min, 350 rpm	yes	350	20
ECZ-MAG, 30 min, 350 rpm	yes	350	30

.

2.3. Analytical Methods and Process Evaluation

(a)

Monitoring of Physico-Chemical Parameters

The efficiency of the Al-based ECZ and ECZ-MAG processes was evaluated by monitoring key physico-chemical parameters (pH, temperature, chemical oxygen demand—COD, turbidity, total solids—TS). Temperature and pH were measured during treatment in defined time intervals, while other parameters were measured before and after treatment in order to assess the process performance. Temperature was measured using a Testo digital thermometer (Titisee-Neustadt, Germany), while pH was determined with a Mettler Toledo Seven Multi pH meter (Greifensee, Switzerland). Chemical oxygen demand (COD) was analyzed using the standard dichromate method. Turbidity was measured with a Velp turbidimeter (Usmate Velate, Italy), and total solids were quantified gravimetrically by drying the samples at 105 °C. All analyses were performed in accordance with Standard Water and Wastewater Testing [31].

(b)

Hybrid Process Efficiency

The percentage of COD and turbidity decrease was calculated using the following equation:

$$\mathrm{Decrease}\hspace{1em}\hspace{1em}\mathrm{percentage}\hspace{1em}(\%)={\displaystyle \frac{{\mathrm{c}}_0-{\mathrm{c}}_{\mathrm{f}}}{{\mathrm{c}}_0}}$$

(1)

where c₀ is the initial value (mg/L or NTU), and c_f is the final value (mg/L or NTU).

(c)

Quantifying and Electrode Loss, Faradaic Efficiency, and Energy Input

The actual mass loss of the aluminum electrodes was determined by gravimetric analysis, based on the difference in the electrode mass before and after the experiment to quantify the amount of aluminum dissolved during the EC process. Prior to the experiment, the masses of both electrodes were measured. Following each experiment, the electrodes were ultrasonically cleaned in deionized water for 10 min, dried in a laboratory oven, and subsequently weighed using an analytical balance. The actual mass loss was calculated using the following expression:

$${\mathrm{C}}_{\mathrm{actual}\hspace{1em}\mathrm{electrode}}={\displaystyle \frac{{\mathrm{m}}_{\mathrm{actual}}}{\mathrm{V}}}$$

(2)

where

m_actual—the experimentally measured electrodes mass loss (g),

V—the reactor volume (m³).

The actual mass loss was compared with the theoretical value predicted by Faraday’s law. The theoretical electrode loss based on Faraday’s law, meaning the theoretical amount of dissolved metal, was calculated as follows:

$${\mathrm{C}}_{\mathrm{theor}\hspace{1em}\mathrm{electrode}}={\displaystyle \frac{\mathrm{I}\cdot \mathrm{t}\cdot {\mathrm{M}}_{\mathrm{w}}}{\mathrm{z}\cdot \mathrm{F}\cdot \mathrm{V}}}$$

(3)

where

I—the current intensity (A),

t—the process duration (hours),

M_w—the molar mass of aluminum (g/mol),

z—the number of electrons transferred per mole of dissolved metal during the electrochemical reaction,

F—Faraday’s constant (96487 C/mol).

The Faraday efficiency is calculated by Equations (1)–(4):

$$\mathrm{FE}(\%)={\displaystyle \frac{{\mathrm{C}}_{\mathrm{actual}\hspace{1em}\mathrm{electrode}}}{{\mathrm{C}}_{\mathrm{theor}\hspace{1em}\mathrm{electrode}}}}\cdot 100$$

(4)

Faradaic efficiency values may be lower or higher than 100%. Values above 100% suggest super-faradaic dissolution, where additional electrode corrosion—beyond that predicted by Faraday’s law—is likely driven by localized chemical or electrochemical processes. Conversely, efficiencies below 100% may result from electrode passivation or surface fouling, which inhibit expected metal release. In addition, a lower efficiency can also be due to the occurrence of side reactions at the anode, especially oxygen evolution. In such cases, part of the applied current is consumed by competing reactions, reducing the proportion of current contributing to metal dissolution and resulting in an apparent Faradaic efficiency of less than 100%.

Based on Faraday low, the energy input, i.e., electrical energy consumption per unit volume, is calculated as:

$${\mathrm{C}}_{\mathrm{energy}}={\displaystyle \frac{\mathrm{U}\cdot \mathrm{I}\cdot \mathrm{t}}{\mathrm{V}}}$$

(5)

where

U—the applied voltage (V).

(d)

Surface Morphology Analysis of Electrodes

To investigate surface changes during each process, electrodes were examined using a light microscope (MXFMS-BD, Ningbo Sunny Instruments Co., Ningbo, China) at 50× magnification, and images were captured with a Canon EOS 1300D digital camera, (Ōita, Japan). Morphological changes such as surface corrosion, deposition, or passivation were assessed.

(e)

Sedimentation Behavior of Treated Suspensions

The settling behavior of the treated suspensions was evaluated using the classical Kynch method. The height of the zone containing suspended particles was recorded over time to determine the settling velocity.

3. Results

3.1. Assessment of Process Efficiency: Linking Physico-Chemical Indicators with Process Performance

In this part, the physico-chemical indicators under different process conditions of the ECZ and ECZ-MAG hybrid treatment process were analyzed to investigate how factors such as treatment duration, mixing speed, and the presence of a magnet affect the process behavior. The key parameters, including temperature, pH, chemical oxygen demand (COD), turbidity (NTU), and total solids (TS), were monitored to evaluate their interdependence and impact on process performance.

3.1.1. Comparative Temperature and pH Profiles

Figure 2 provides the temperature and pH changes during the ECZ and ECZ-MAG processes. Results show that the temperature increase during ECZ and ECZ-MAG is gradual but consistent, and attributable primarily to ohmic heating resulting from electrolyte resistance and Faradaic reactions at the electrodes. Notably, a more pronounced temperature rise is detected in ECZ-MAG systems, particularly for 20 and 30 min durations. For instance, at 250 rpm, the temperature in the ECZ-MAG system rises from 21.7 °C to 31.9 °C in 20 min and further to 35.7 °C over 30 min. This contrasts with the ECZ (non-magnetic) systems, which exhibit comparatively modest thermal increments under identical conditions. The elevated temperatures in ECZ-MAG systems can be ascribed to magnetic field-enhanced mass transport phenomena. However, previous experiments with Fe electrodes [29] showed a slightly lower temperature increase in ECZ-MAG compared to ECZ, indicating that the interaction between the magnetic field and the electrocoagulation system is electrode material-dependent.

Regarding the variations in mixing speed between 250 and 350 rpm, results showed no significant impact on temperature rise, suggesting that mixing intensity does not substantially influence heat generation in the system during short-duration treatments.

However, it is important to have in mind that excessive temperature rise is undesirable because treated wastewater with elevated temperatures cannot be discharged directly due to the risk of thermal pollution, which can harm aquatic ecosystems. In practical applications, this issue can be effectively managed through engineering controls, such as optimizing the ratio of electrode surface area to wastewater volume being treated. By carefully regulating this parameter, it is possible to limit the temperature increase during treatment while maintaining high removal efficiency, ensuring environmentally safe discharge conditions.

Figure 2b illustrates the comparative pH profile. Namely, the EC process inherently influences the pH of the treated solution due to anodic dissolution and subsequent formation of hydroxides [8], thus similarly occurring in the hybrid ECZ and ECZ-MAG process. As shown in Figure 2b, a sharp increase in pH occurs during the first 5 min across all experimental conditions, rising from an initial pH of 3.95 to around 8.85. The zeolite presence also contributes to this pH increase due to ion exchange of Na⁺ from the zeolite structure with H⁺ from the water, which may shift the balance of ions in the water, leading to a pH increase [32]. The influence of the magnetic field may accelerate the dissolution of aluminum anodes by enhancing micro-mixing and mass transfer near the electrode surfaces, which may contribute to the rise in pH. However, in our experiment, the differences in pH increase between magnetic and non-magnetic processes, as well as between different mixing speeds, become negligible. This observation slightly differed from our previous study comparing ECZ and ECZ-MAG systems using Fe electrodes for the treatment of compost wastewater with a medium organic load (COD ≈ 865 mg O₂/L) and an NdFeB magnet of 0.55 T [29], where ECZ-MAG exhibits a slightly higher increase in pH. Similarly, Ni’am et al. (2006) [33] observed a slightly higher pH increase in magnet-assisted electrocoagulation using Fe electrodes and SmCo permanent magnets (0.16 T) for treatment of wastewater prepared from milk powder. Despite differences in the initial wastewater composition and magnetic field strength, obtained results suggest that the type of electrode material has a significant influence on the pH evolution during EC. The interaction between the magnetic field and electrode material appears to affect the rate and extent of anodic dissolution and subsequent pH changes, with aluminum and iron electrodes exhibiting different responses under magnetic influence. However, conducting controlled experiments with different electrode materials is essential to clarify their specific role in magnetic field-assisted electrocoagulation.

3.1.2. Comparative COD Decrease

Figure 3 presents the results of chemical oxygen demand (COD), expressed as a percentage decrease after the ECZ and ECZ-MAG processes. The highest COD decrease was achieved in the ECZ-MAG process at a mixing speed of 250 rpm and a contact time of 30 min, amounting to 89.87%. The lowest COD decrease was recorded for the ECZ-MAG process at 350 rpm over 10 min, with a reduction of 79.88%. In all other experiments, COD decreases exceeded 80%.

The presence of the magnetic field proved to be effective only in the processes lasting 30 min, where higher COD decrease percentages were recorded compared to the non-magnetic experiments. This indicates that the magnetic field’s positive impact on pollutant removal is time-dependent. For shorter contact times (10 and 20 min), the magnetic field does not significantly enhance COD decrease, likely because these durations are insufficient for the magnetic field to induce notable improvements in micro-mixing, ion transport, or floc formation. In contrast, during longer treatment times (30 min), the magnetic field promotes better particle destabilization and aggregation through enhanced ionic movement and micro-convection, leading to improved COD decrease. Therefore, the benefits of applying a magnetic field become more apparent when the process duration allows sufficient time for these mechanisms to develop fully.

This finding contrasts with the results obtained in our previous investigation on the influence of magnetic assistance in EC processes employing Fe electrodes [29], where no notable enhancement in COD removal was observed with the application of a magnetic field. These differences suggest that the type of electrode material plays a critical role in determining the synergistic effect of magnetic fields. Specifically, it appears that in the case of Fe electrodes, the electrochemical behavior and magnetic influence may counteract each other, limiting process efficiency. Conversely, with Al electrodes, the magnetic field contributes positively to COD reduction, indicating improved synergy and enhanced pollutant removal performance.

Despite the satisfied COD decrease percentages, it is important to compare the final COD values in the treated compost-derived wastewater with the regulatory limits prescribed by the Ordinance (Official Gazette NN 26/20), especially given the initially high COD concentration (COD₀ = 1642 ± 105). The results show that the final COD values range from 166 ± 11.5 to 330 ± 22.56 mg O₂/L, which exceeds the maximum permissible limit for discharge into surface waters (125 mg O₂/L) but is below the allowed limit for discharge into the public sewer system (700 mg O₂/L).

3.1.3. Comparative Turbidity Removal

Figure 4 presents the turbidity decrease results after the ECZ and ECZ-MAG processes. The highest turbidity removal efficiency for the 20 min processes was achieved by the ECZ-MAG process at a mixing speed of 350 rpm, with a removal rate of 98.59%. For the 30 min processes, the highest turbidity removal was also observed in the ECZ-MAG process at 350 rpm, reaching 83.25%.

However, turbidity values for the 10 min processes—ECZ at 250 rpm, ECZ at 350 rpm, and ECZ-MAG at 350 rpm—were higher than the initial value, resulting in negative removal efficiencies of −289.27%, −19.4%, and −150.53%, respectively. This clearly indicates that the combination of mixing speed at a shorter process duration and the presence of the magnetic field in the ECZ process with the addition of synthetic zeolite (with particle size < 40 µm) forms a stable suspension, increasing temporarily the final turbidity values. The enhanced turbidity removal observed in the 20 and 30 min magnet-assisted ECZ-MAG processes suggests that the magnetic field promotes better aggregation and floc formation over longer treatment times. This improvement is likely due to enhanced micro-mixing and destabilization of colloidal particles, which allows more effective floc formation. Ni’am et al. (2006) [33] demonstrated that the application of a magnetic field in combination with EC and Fe electrodes enhances the turbidity removal at the longer contact time of 200 min. They achieved turbidity removal of up to 81.25%, compared to 75.16% in the absence of magnetic assistance. At a shorter contact time, turbidity oscillates, even reaching negative values, which is consistent with our previous finding for the ECZ-MAG process with Fe electrodes [29].

3.1.4. Comparative Total Solids Values

Figure 5 presents the results of total solids (TS) after the ECZ and ECZ-MAG processes at different mixing speeds of 250 and 350 rpm, categorized by contact time. Results show that TS values varied depending on the experimental conditions but were significantly lower than the initial value (the initial TS value was 3.08 g/L), which can be attributed to the effective removal and binding of pollutants during the treatment. However, the data also indicate that the magnetic field contributed to a noticeable reduction in TS only in the 10 min processes at both mixing speeds, where TS values were lower compared to experiments without the magnet. This suggests that in the early stages of treatment, the magnetic field may enhance pollutant destabilization and aggregation, leading to improved removal of suspended solids.

In contrast, for longer treatment durations (20 and 30 min), the magnetic field generally did not show a positive effect on TS reduction. This could be because, over extended processing times, other factors such as sedimentation, flocculation, and natural coagulation dominate the total solids removal and may overshadow any additional impact of the magnetic field.

3.2. Mechanistic Insights into Electrode Dissolution and Mass Loss

Understanding electrode dissolution and mass loss mechanisms is crucial for optimizing electrochemical treatment processes. These phenomena directly impact the efficiency, longevity, and maintenance costs of the electrodes used.

Figure 6 illustrates the changes in electrode mass for ECZ and ECZ-MAG processes at varying mixing speeds and durations. The consistent decrease in anode mass across all experiments clearly indicates anodic dissolution, a main EC mechanism that intensifies with longer contact times due to prolonged electrode exposure. Although most material loss occurs at the anode, dissolution of the cathode can also occur, mainly due to hydrogen evolution at the cathode. This process increases the local alkalinity and creates a high pH microenvironment that can chemically attack and dissolve the cathode surface, especially with prolonged treatment. However, the extent of cathode dissolution is significantly lower compared to anodic dissolution, confirming the dominance of anodic reactions in overall material loss. Specifically, for the 10 min experiments, the highest anode loss occurred in the ECZ-MAG process at 350 rpm, while the lowest in ECZ at 250 rpm. For 20 min experiments, the greatest anode loss was observed in ECZ-MAG at 250 rpm, and the lowest in ECZ at 350 rpm. For 30 min experiments, anode loss was highest in ECZ at 250 rpm and lowest in ECZ at 350 rpm.

This observation is consistent with the fundamentals of electrode kinetics and Faraday’s laws of electrolysis, which state that the amount of dissolved Al electrode is directly proportional to the total electrical charge passed through the system. The process is therefore kinetically controlled, i.e., it depends primarily on the rate of the electrochemical reaction (kinetic control) and not on mass transfer or diffusion of species in the solution. Although the magnetic field can improve the local conditions for mass transfer, it has no significant effect on the rate-limiting step, which is determined by the kinetics of electron transfer at the electrode surface. Therefore, the electrode loss under the tested parameters remains largely unaffected by the hydrodynamic conditions.

The results of the electrode microscopic surface analysis carried out after each processes (at magnifications 100×, in bright field) are shown in Figure 7.

Optical microscope images show progressive surface degradation of both anodes and cathodes with increasing treatment time (from 10 to 30 min) in the ECZ process at both 250 and 350 rpm. The anodes exhibit dominant general and pitting corrosion, more pronounced at longer times and at 250 rpm. The cathodes display dendritic, cracked layers at 250 rpm, while at 350 rpm, uniform dissolution occurs. Although the damage is slightly less at 350 rpm due to enhanced mixing, the overall trend indicates time-dependent deterioration in the absence of a magnetic field.

In contrast, the ECZ-MAG process, which involves magnetic field assistance, shows a less consistent pattern. At 10 min, electrode surfaces display more severe damage compared to ECZ, likely due to intensified local turbulence and accelerated reactions. However, at 20 and 30 min, surface damage is notably reduced in ECZ-MAG compared to ECZ, suggesting that the magnetic field may promote a more uniform distribution of reactants and reduced corrosion attack on the surface over extended periods.

The effect of the magnetic field in the ECZ-MAG process appears to be dual and time-dependent. In the initial phase (e.g., after 10 min), the presence of the magnetic field enhances local turbulence and mass transfer near the electrode surfaces, leading to accelerated electrochemical reactions and more pronounced electrode damage compared to the system without the magnet. However, as the treatment time increases (20 and 30 min), the magnetic field demonstrates a protective effect—likely due to flow stabilization, more uniform distribution of reactants, and reduced localized chemical and electrochemical stress on the electrode surfaces. In contrast, ECZ systems without magnetic assistance suffer from time-dependent, progressively worsening electrode damage due to uneven mass transport and localized accumulation of aggressive species, especially at a lower mixing speed. It is important to emphasize that although the magnetic field in ECZ-MAG systems does not have a significant influence on the total mass of the dissolved metal—since the dissolution of the anode is kinetically controlled—it does have a significant influence on the state of the electrode surface after the EC process. In other words, the magnetic field does not increase the overall material loss, but it can reduce localized surface damage, resulting in improved long-term stability and longevity of the electrodes. This effect can be particularly useful for the optimization of electrocoagulation (EC) processes, both in terms of removal efficiency and the longevity and cost-effectiveness of electrode materials.

A few studies can be found that support the previous observations regarding the influence of magnetic fields on electrode surface morphology and corrosion behavior in EC processes. According to Yasri et al. (2022) [18], applying a magnetic field in EC with an Al electrode effectively mitigated electrode fouling during water treatment. The authors attributed this improvement to enhanced mass transfer via Kelvin and magnetohydrodynamic (MHD) effects, which also reduced the resistivity of the accumulated fouling layer by approximately 23%. In our previous study with Fe electrodes [29], the application of a magnetic field increased electrode fouling and induced surface fractures, particularly at 20 min of treatment, which is probably driven by the dissociation and magnetic accumulation of ferromagnetic Fe species influenced by Kelvin forces and MHD convection near the electrode surface.

Compared with this study, a clear difference in the behavior of magnetic field influence is observed between systems using Al and Fe electrodes, which can be attributed to several interrelated factors. These include the intrinsic properties of the electrode materials, such as their standard electrode potentials and corrosion behavior, as well as the pH of the system, which affects the speciation and solubility of metal ions. Additionally, the nature and load of the treated wastewater play an important role. In the present study, the compost wastewater treated with Al electrodes exhibited a high organic load (COD≈1600 mg O₂/L), which probably intensifies electrochemical activity at the electrode surfaces, particularly during the initial treatment phase. In the later stages of the process (after 20 and 30 min), a stabilization phase occurs in which the magnetic field promotes a more uniform distribution of ions and flocculants. This leads to the formation of protective layers—such as Al(OH)₃—that cover micro-damages on the electrode surface. As a result, the intensity of localized corrosion decreases because the reactive zones become “saturated”, and diffusion barriers are leveled out. Consequently, surface damage becomes less pronounced, especially in terms of pitting, and the electrode surface appears more uniform and compact. In contrast, Fe electrodes, used with less loaded wastewater (COD≈865 mg O₂/L) [29], demonstrate a different corrosion profile under magnetic assistance. These differences underscore the complex interplay among electrode material, wastewater characteristics, and magnetic field effects, which together govern the extent and nature of electrode degradation.

3.3. Solid–Liquid Separation Dynamics

A settling test was performed under varying operational conditions to evaluate the effectiveness of solid–liquid separation following EC processes (Figure 8). For the first set of experiments, the most efficient settling was observed in the ECZ-MAG processes conducted for 10 min at both 250 and 350 rpm, where most of the sludge settled within the first two min. However, due to the high turbidity of the supernatant above the sludge layer, the turbidity removal percentages were negative (as shown in Figure 3). In the second set of experiments (20 min duration), the best settling performance was also achieved after hybrid ECZ-MAG processes at 250 and 350 rpm. For the experiments with a duration of 30 min, the most effective settling occurred in the ECZ process at 350 rpm. The settling curves indicate a positive impact of the magnetic field on the separation performance during the 10 and 20 min experiments, while its presence did not enhance settling efficiency in the 30 min processes.

Based on results of the treatment of compost-derived wastewater using magnet-assisted EC (ECZ-MAG) shown in Figure 7, the presence of a magnetic field demonstrated several notable effects on the process performance. While the total mass loss of the anode remained comparable to that in non-magnetic plants (Figure 6)—indicating that the magnetic field does not significantly affect the dissolution of the aluminum anode—it still led to significant changes in sludge sedimentation dynamics. In particular, shorter duration experiments (10 and 20 min) showed evidence of enhanced electrochemical activity in ECZ-MAG assemblies, not necessarily through increased anode dissolution, but likely through enhanced mass transfer and magnetically induced micro-mixing. These effects accelerate the formation and aggregation of Al³⁺ species, which are crucial for coagulation, leading to faster flake formation.

Moreover, ECZ-MAG processes led to faster sludge formation and settling, particularly evident in the first few minutes of sedimentation, where most of the sludge settled rapidly. This behavior was especially prominent in the 10 min ECZ-MAG treatments at both 250 and 350 rpm, even though the supernatant remained highly turbid—indicating fast agglomeration but incomplete clarification. Overall, the magnetic field positively influenced the EC performance for shorter treatment times, improving both coagulant availability and solid–liquid separation kinetics. However, in 30 min treatments, the magnet did not show significant advantages, possibly due to electrode passivation or the saturation of removal capacity over prolonged operation.

In contrast to our previous findings using Fe electrodes [29], where the settling curves demonstrated a clearly defined slope and efficient sludge settling at longer contact times (20 and 30 min), while showing poor settling performance at 10 min in hybrid (magnet-assisted) systems, the present results with Al electrodes exhibit an inverse trend. Here, the magnetic field notably enhanced sludge settling during shorter treatment durations (10–20 min) by promoting particle aggregation and floc formation. However, at 30 min, the settling efficiency in non-magnetic systems slightly surpassed that of magnet-assisted ones, likely due to natural floc stabilization over time. These differences highlight the crucial role of electrode material in determining the system’s response to magnetic assistance. Aluminum electrodes appear more responsive to magnetic enhancement during the early phases of treatment, whereas iron electrodes require longer contact times to reach effective settling dynamics, possibly due to differences in floc characteristics and aggregation kinetics associated with their respective coagulant species.

3.4. Quantifying Energy Input and Electrode Loss

Operational costs encompass all expenses incurred during the procurement of materials used in the process, throughout the treatment and post-treatment phases. Specifically, in the ECZ process, operational costs include the consumption of electrode materials, electrical energy, zeolite, disposal of sludge, and magnetic materials. In the following, only the costs related to electrical energy and electrodes will be considered. Electrode costs were estimated both theoretically using Faraday’s law and experimentally by measuring the electrode mass loss before and after hybrid ECZ and ECZ-MAG. Electrode loss (kg/m³), Faraday efficiency (%), and Energy input, i.e., the electrical energy requirement (kWh/m³), were determined according to Equations (2)–(5).

Table 2. Electrode loss (kg/m³), Faraday efficiency (%), energy input, i.e., electrical energy requirement (kWh/m³), for the conducted experiments of hybrid ECZ and ECZ-MAG.

Experiment Mark	U, V	Cenergy, kwh/m3	Ctheor anode, kg/m3	Cactual anode, kg/m3	FE, %
ECZ, 10 min, 250 rpm	20.81	6.03	0.24	0.13	54.23
ECZ, 20 min, 250 rpm	21.93	12.72	0.47	0.26	55.25
ECZ, 30 min, 250 rpm	21.63	18.77	0.71	0.39	55.62
ECZ, 10 min, 350 rpm	28.08	8.14	0.24	0.13	56.69
ECZ, 20 min, 350 rpm	23.99	13.91	0.47	0.26	55.25
ECZ, 30 min, 350 rpm	21.60	18.75	0.71	0.36	50.89
ECZ-MAG, 10 min, 250 rpm	23.33	6.76	0.24	0.13	57.03
ECZ-MAG, 20 min, 250 rpm	23.91	13.86	0.47	0.27	57.03
ECZ-MAG, 30 min, 250 rpm	25.41	22.06	0.71	0.39	54.88
ECZ-MAG, 10 min, 350 rpm	20.62	5.98	0.24	0.15	65.62
ECZ-MAG, 20 min, 350 rpm	22.52	13.06	0.47	0.26	54.40
ECZ-MAG, 30 min, 350 rpm	24.31	21.10	0.71	0.38	53.83

Note: standard deviation from the average value for voltage is in the range ±(0.20–1.12) V.

summarizes the Electrode loss (kg/m³), Faraday efficiency (%), and Energy input, i.e., the electrical energy requirement (kWh/m³), for the conducted experiments of hybrid ECZ and ECZ-MAG.

These observations correlate with earlier results, where enhanced removal efficiencies for COD and turbidity were found in magnet-assisted processes (ECZ-MAG) at longer durations and moderate mixing speeds. The magnetic field seems to act as a complex modulator, improving pollutant removal and settling performance in certain conditions while sometimes increasing energy input due to altered electrochemical dynamics. This trade-off between improved treatment efficiency and energy input should be carefully considered when optimizing hybrid EC processes for practical application. When comparing the theoretical electrode mass loss calculated via Faraday’s law and the actual mass loss measured during the experiments, it was observed that the values derived from Faraday’s law were consistently higher; thus, the percentage values of Faraday efficiency (FE) calculated in Table 1 according to Equations (2)–(5) are below 100% (FE in the range 50.89–65.82%). This indicates that the theoretical calculation tends to overestimate electrode consumption. Such discrepancies are often linked to factors like electrode passivation, formation of surface films, or gas evolution, which reduce the effective electrode dissolution during the process. Unlike many studies reporting Faradaic efficiencies (FE%) exceeding 100%—a phenomenon referred to as super-Faradaic efficiency [34,35,36]—our results revealed FE% values significantly below this threshold. This can be attributed to the high organic load of the initial compost-derivate wastewater. Elevated concentrations of organic matter may interfere with electrochemical surface reactions, promoting the formation of passivating layers or fouling on the electrode surface. Such effects can hinder electrode dissolution, resulting in an actual mass loss lower than that predicted by Faraday’s law.

3.5. Taguchi-Based Process Optimization: Unraveling Interactions Between Physico-Chemical Process Efficiency, Electrode Dissolution, and Settling Behavior

The Taguchi method represents an approach that enables investigation of the influence of various parameters on desired characteristics of a process or product. Orthogonal arrays for designing experiments and the signal-to-noise ratio (S/N) for quality evaluation are two key ideas that form the basis of this methodology. Orthogonal arrays represent an arrangement that allows the examination of the influence of several factors simultaneously, without the need to conduct all possible combinations of experimental conditions. An experiment designed in this way reduces the number of required experiments while keeping the results statistically relevant.

This research applied an L8 experimental design. It focused on three key controlled factors: A—the presence of magnet (not present or present), B—mixing speed (250 or 350 rpm), and C—process duration (10 or 20 min). Each of these factors was examined at two levels, which is in accordance with the principles of the L8 orthogonal array.

Table 3. Design of the experiments using Taguchi L8 and results obtained (means).

Exp. Mark	Factor			COD Reduction, %	vt, cm/min	Turbidity, NTU	Electrodes Loss, g
	A	B	C
T1	not present	250 rpm	10 min	82.06	2.250	979.67	0.0820
T2	not present	250 rpm	20 min	86.18	2.667	40.80	0.1800
T3	not present	350 rpm	10 min	82.31	2.833	183.00	0.0713
T4	not present	350 rpm	20 min	85.94	2.833	23.85	0.1581
T5	present	250 rpm	10 min	81.09	0.560	300.50	0.0785
T6	present	250 rpm	20 min	84.97	0.458	23.30	0.1465
T7	present	350 rpm	10 min	79.88	1.956	630.50	0.0843
T8	present	350 rpm	20 min	82.31	1.956	3.55	0.1478

Note: COD reduction is expressed as percentages of mean COD values. Standard deviation from the average value for COD is in the range ±(11.50–30.90) mg O₂/L, for settling velocity is in the range ±(0.023–0.142) cm/min, for turbidity is in the range ±(0.14–39.19) NTU, and for electrodes loss is in the range ±(0.0035–0.0090) g.

shows an overview of these factors and their experimental levels and results obtained.

The signal-to-noise ratio (S/N) represents a key tool in the Taguchi method. This ratio measures how the response variable varies in relation to the target value under different conditions. The Taguchi method defines three basic quality characteristics that determine the method of calculating the S/N ratio: “larger the better”—when the goal is to maximize the response variable, “nominal is best”—when the goal is to achieve a specific target value, and “smaller the better”—when the goal is to minimize the response variable.

In this research, the goal was to find optimal conditions for maximum reduction of COD, maximum settling velocity, minimum electrode consumption, and minimum turbidity. Accordingly, for the COD decrease and settling velocity, the “larger the better” characteristic was applied, while for the electrode consumption and turbidity, the “smaller the better” characteristic was applied. Used quality characteristics are expressed by the following equations:

$${\mathrm{S}/\mathrm{N}}_{\mathrm{L}\mathrm{B}}=-10 \mathrm{l}\mathrm{o}\mathrm{g}{\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}\frac{1}{{\mathrm{y}}_{\mathrm{i}}^2}}{\mathrm{n}}}$$

(6)

$${\mathrm{S}/\mathrm{N}}_{\mathrm{S}\mathrm{B}}=-10 \mathrm{l}\mathrm{o}\mathrm{g}{\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{y}}_{\mathrm{i}}^2}{\mathrm{n}}}$$

(7)

where S/N is the signal-to-noise ratio, LB is the larger-the-better subscript, SB is the smaller-the-better superscript, n is the number of repeats under the identical conditions, and y is the value determined from the experiment.

Table 4. Calculated values of S/N_LB and S/N_SB.

Exp. mark	S/NLB COD Reduction	S/NLB Settling Velocity	S/NSB Turbidity	S/NSB Electrodes Loss
T1	38.283	7.044	−59.822	21.723
T2	38.708	8.521	−32.213	14.895
T3	38.309	9.045	−45.249	22.938
T4	38.684	9.045	−27.549	16.021
T5	38.179	−5.026	−49.557	22.103
T6	38.585	−6.783	−27.347	16.683
T7	38.049	5.827	−55.994	21.483
T8	38.309	5.827	−11.005	16.607

shows the calculated values of S/N_LB and S/N_SB.

For process analysis, the S/N ratio, delta, sum of squares (SS), mean square (MF), range, contribution percentages (pC, %), and p-value were determined for each controllable factor (

Table 5. Response table for means and S/N ratio (larger the better).

Response	COD Reduction—Means			COD Reduction—S/N Ratio
Factor	A	B	C	A	B	C
Level 1	84.12	83.58	81.34	38.50	38.44	38.20
Level 2	82.06	82.61	84.85	38.28	38.34	38.57
Delta	2.06	0.97	3.52	0.22	0.10	0.37
Rank	2	3	1	2	3	1
Response	Settling velocity—means			Settling velocity—S/N ratio
Factor	A	B	C	A	B	C
Level 1	2.646	1.484	1.900	8.413	0.936	4.220
Level 2	1.232	2.394	1.978	−0.041	7.436	4.152
Delta	1.413	0.911	0.79	8.454	6.500	0.068
Rank	1	2	3	1	2	3

,

Table 6. Response table for means and S/N ratio (smaller the better).

Response	Electrode Loss—Means			Electrode Loss—S/N Ratio
Factor	A	B	C	A	B	C
Level 1	0.123	0.122	0.079	18.89	18.85	22.06
Level 2	0.114	0.115	0.158	19.22	19.26	16.05
Delta	0.009	0.007	0.079	0.32	0.41	6.01
Rank	2	3	1	3	2	1
Response	Turbidity—means			Turbidity—S/N ratio
Factor	A	B	C	A	B	C
Level 1	306.83	336.07	523.42	−41.21	−42.23	−52.66
Level 2	239.46	210.22	22.88	−35.98	−34.95	−24.53
Delta	67.37	125.84	500.54	5.98	7.29	28.13
Rank	3	2	1	3	2	1

,

Table 7. Analysis of variance for means.

Response	COD Reduction
Factor	A	B	C	Error
DF	1	1	1	4
SS	8.487	1.862	24.710	2.727
MS	8.487	1.862	24.710	0.682
pC, %	22.46	4.93	65.39	7.22
p-value	0.024	0.174	0.004	-
Significance	significant	not significant	highly significant	-
Response	Settling velocity
Factor	A	B	C	Error
DF	1	1	1	4
SS	3.995	1.659	0.012	0.655
MS	3.995	1.659	0.012	0.164
pC, %	63.20	26.25	0.20	10.36
p-value	0.008	0.033	0.797	-
Significance	highly significant	significant	not significant	-
Response	Electrode loss
Factor	A	B	C	Error
DF	1	1	1	4
SS	0.00015	0.00008	0.01251	0.00059
MS	0.00015	0.00008	0.01251	0.000147
pC, %	1.10	0.61	93.87	4.42
p-value	0.374	0.499	0.001	-
Significance	not significant	not significant	highly significant	-
Response	Turbidity
Factor	A	B	C	Error
DF	1	1	1	4
SS	9077	31,673	501,086	345,156
MS	9077	31,673	501,086	86,289
pC, %	1.02	3.57	56.49	38.91
p-value	0.762	0.577	0.074	-
Significance	not significant	not significant	marginally significant	-

and

Table 8. Analysis of variance for S/N ratio.

Response	COD Reduction
Factor	A	B	C	Error
DF	1	1	1	4
SS	0.0927	0.0205	0.2689	0.0291
MS	0.0927	0.0205	0.2689	0.0073
pC, %	22.55	4.98	65.39	7.08
p-value	0.023	0.169	0.004	-
Significance	significant	not significant	highly significant	-
Response	Settling velocity
Factor	A	B	C	Error
DF	1	1	1	4
SS	142.958	84.496	0.009	57.458
MS	142.958	84.496	0.009	14.365
pC, %	50.17	29.66	0.00	20.17
p-value	0.034	0.072	0.981	-
Significance	significant	marginally significant	not significant	-
Response	Electrode loss
Factor	A	B	C	Error
DF	1	1	1	4
SS	0.211	0.338	72.25	2.716
MS	0.211	0.338	72.25	0.679
pC, %	0.28	0.45	95.68	3.60
p-value	0.607	0.519	0.000	-
Significance	not significant	not significant	highly significant	-
Response	Turbidity
Factor	A	B	C	Error
DF	1	1	1	4
SS	54.76	106.16	1582.22	225.19
MS	54.76	106.16	1582.22	56.26
pC, %	2.78	5.39	80.39	11.43
p-value	0.380	0.242	0.006	-
Significance	not significant	not significant	highly significant	-

).

3.5.1. COD Reduction

For both the means and S/N ratio, process duration (C) is the most significant factor, with p-value < 0.01, indicating high statistical significance. The pC of this factor confirms that it is the most important factor in the process. Magnet presence (A) is also statistically significant, with a p-value < 0.05. Its pC shows that this factor is significant but considerably less than factor C. Mixing (B) has minimal impact and is not significant (p-value > 0.05). The optimal combination of factors is A1, B1, C2. The optimal combination (A1, B1, C2) is expected to have an S/N ratio of 38.73 and a mean of 86.36%. The predicted values are in good agreement with the results from the experiment T2, which has the same factor values as the optimal combination.

3.5.2. Settling Velocity

For both the means and S/N ratio, the analysis shows that factor A is the most significant factor (p-value (means) = 0.008 and p-value (S/N) = 0.034) and the most important factor (pC (means) = 63.20% and pC (S/N) = 50.17%). For mean values, factor B is significant (p-value = 0.033 and pC = 26.25%), while for S/N, it is marginally significant, with a p-value of 0.072, and its pC is 29.66%. Factor C is not statistically significant and has a negligible impact on settling velocity. The optimal combination of factors for means is A1, B2, C2, while for S/N is A1, B2, C1. It is interesting to note that there is a small difference in the optimal level of factor C between the S/N ratio analysis and the mean values analysis. However, given the negligible impact of factor C, this difference is not of practical significance. The error value is 10.36% (means) and 20.17% (S/N), which is considerably higher than in the COD analysis. The predicted S/N ratio for A1, B2, C1 is 11.6971, while the predicted means for A1, B2, C2 is 3.1405 cm/min. The obtained values are slightly higher than in experiments T3 and T4, which have the same factor values as the optimal combinations.

3.5.3. Electrode Loss

The only significant factor for both the means and S/N ratio is factor C. Its p-value is < 0.001, with a contribution pC > 92%. The optimal combination (A2, B2, C1) is expected to have a S/N Ratio of 22.4299 and a Mean 0.0716 g. The predicted values are in good agreement with the results from experiment T7, which has the same factor values as the optimal combination.

3.5.4. Turbidity

For turbidity, as for electrode loss, the only significant (marginally significant) factor is factor C. The optimal combination (A1, B1, C2) is expected to have an S/N Ratio of −18.269 and a mean of −77.73 NTU. The predicted values do not agree with the results from experiment T8, which has the same factor values as the optimal combination. The high percentage of error indicates that there might be other factors affecting turbidity that were not included in the experiment.

Given the significance and contribution of factors to the process, the optimal combination is A1, B2, and C2 (without magnet, 350 rpm, and 20 min). This combination increases the electrode loss associated with this configuration, but it is needed to achieve satisfactory outcomes in wastewater treatment.

4. Conclusions

This study presents the first application of a hybrid EC system combining Al electrodes, zeolite, and NdFeB magnet assistance for treating complex compost-derived wastewater. The pH rapidly increased in the first 5 min and stabilized, with no notable magnetic influence. The temperature increase is slightly higher in magnet-assisted treatments, enhancing reaction kinetics but requiring control to prevent thermal pollution. COD and turbidity reductions were highest in longer magnet-assisted treatments (30 min), with an up to 89.87% COD and 98.59% turbidity decrease, respectively, while shorter treatments showed limited benefits. Total solids decreased under all conditions; magnetic influence was noticeable only in short-duration experiments. General and pitting corrosion is observed on anodes, and their mass loss increased with time. The magnetic field acts as a dynamic factor that intensifies the aggressiveness of the process in the initial stages but with prolonged treatment duration contributes to the reduction of overall damage, especially localized corrosion.

The magnetic field improved sludge settling during shorter treatments (10–20 min) by enhancing particle aggregation, while longer treatments (30 min) performed better without it, likely due to natural stabilization over time. Although magnet-assisted ECZ can improve removal efficiency and settling under specific conditions, it may increase energy input. The gap between theoretical and actual electrode loss, especially in high-organic-load solutions, underscores the complexity of surface reactions. The values of Faraday efficiency are in the range of 50.89–65.82%. Taguchi’s hybrid ECZ and ECZ-MAG process optimization effectively connects the physico-chemical efficiency, electrode consumption, and phase separation dynamics. The targeted achievement of maximum COD reduction, highest deposition rate, minimum turbidity, and electrode consumption resulted in optimal processing conditions, without the use of magnets, at 350 rpm and a duration of 20 min. Although these conditions are associated with increased electrode degradation, they have proven necessary to achieve balanced and satisfactory results in wastewater treatment. Thus, magnetic fields offer potential benefits but require careful optimization to balance treatment efficiency, energy requirements, and sludge separation.

Results in this paper highlight the hybrid EC combining aluminum electrodes, zeolite, and magnetic assistance as a promising and adaptable strategy for the treatment of complex compost-derived wastewater. The performance of the system is highly influenced by operational parameters such as contact time, mixing intensity, and the application of a magnetic field. Notably, the effectiveness of magnetic assistance appears to be electrode material-dependent, with aluminum electrodes showing enhanced pollutant removal and improved sludge settling, particularly during shorter treatment durations. This contrasts with previous findings using iron electrodes, where magnetic effects were less pronounced. Thus, even the magnetic field can improve system performance; its application should be carefully optimized to balance treatment efficiency with energy consumption, solid–liquid separation dynamics, and electrode stability.