Modeling and Optimization of p-Benzoquinone Degradation via Flow-By Electro-Oxidation on Boron-Doped Diamond Electrodes

Abstract

The electro-oxidation of p-Benzoquinone (p-BQ) was investigated in a flow-by reactor (FM01-LC) without separation, with two boron-doped diamond (BDD) electrodes as both the anode and cathode, in batch recirculation mode. The optimal operating conditions were determined using response surface methodology, specifically a face-centered central composite design. The initial pH (pH₀) and applied current density (j) were evaluated as factors, while the p-BQ (η (%)) served as the response variable. The optimal conditions, a pH₀ of 6.52 and a j of 0.124 A/cm², achieved a maximum removal efficiency of 97.32% after 5 h of electrolysis. The specific energy consumption and total operating cost were 127.854 kWh/m³ and USD 3.7 USD/L, respectively.

1. Introduction

With the growing global population and rapid industrial advancement, hazardous substances in water, such as recalcitrant contaminants, pose a considerable threat to human health and aquatic ecosystems. These contaminants, also known as “contaminants of emerging concern” (CECs), are characterized by high toxicity and long-term environmental persistence, representing a significant risk to ecological safety and human health, even at very low concentrations. Typically, CECs exhibit hydrophobicity and low molecular weight, which promote their bioaccumulation and delay their elimination. Although all animals possess xenobiotic elimination mechanisms, such as metabolic enzymes, transporter proteins, and conjugation systems, these systems can be ineffective in preventing CEC bioaccumulation [1]. Among the various CECs, p-Benzoquinone (p-BQ) is a well-known occupational and environmental pollutant. It is extensively used in the pharmaceutical, leather, and polymer industries, as well as in the production of hydroquinone, insecticides, fungicides, and tannin agents and as a precursor to various dyes. However, p-BQ exposure has been linked to adverse health conditions, such as eye and respiratory tract irritation, erythema, localized tissue necrosis, and induced mutagenic effects [2,3,4,5].

Considering these challenges, chemical water treatment using electro-oxidation methods in advanced oxidation processes (AOPs) has shown promise in effectively mineralizing various CECs [6,7,8]. Specifically, AOPs produce reactive oxygen species (ROS), such as ¹O₂, SO₄^•−, and ^•OH, through metal-catalyzed decomposition oxidants like O₃, persulfate, and H₂O₂ [9,10]. Research has shown that during catalytic decomposition, ROS facilitate the oxidative degradation of CECs in water due to their relatively high redox potentials (e.g., SO₄^•−, 2.5–3.1 V vs. NHE; ^•OH, 1.9–2.7 V vs. NHE) [11,12,13]. Moreover, AOPs can convert CECs into CO₂ and H₂O or achieve complete mineralization [14].

The degradation of p-BQ has been extensively studied using various AOPs in both batch and flow cells. For example, Ozge et al. [15] performed the electro-Fenton process in a batch reactor with a treated volume of 350 mL and an initial p-BQ concentration of 50 mg/mL, resulting in the complete removal of p-BQ within 30 min. Ajeel et al., 2015 [4], investigated the electrochemical oxidation of p-BQ in a batch reactor equipped with a carbon black diamond (CBD) composite anode, attaining 96% removal of p-BQ under the following conditions: initial p-BQ concentration of 200 mg/mL, initial pH of 6, current density of 45 mA/cm², 120 min of treatment, treatment volume of 100 mL, and a CBD composition of 20. Furthermore, Yu et al. [16] conducted anodic oxidation of a 500 mL aqueous p-BQ solution (100 mg/L) in a batch reactor, resulting in 96.1% p-BQ removal and 68.2% COD removal within 3 h. The process operated at an initial pH of 6.5, a current density of 10 mA/cm2, room temperature, and with 0.1 mol/L NaCl as the supporting electrolyte, using stainless steel and Ti/ Pb-TiO_xNWs/PbO₂ as the cathode and anode, respectively. Despite the high removal efficiency, possible dissolution of Pb ions from the PbO₂ electrode was observed after 3 h of treatment, raising concerns about pollution issues.

Given the mass transfer limitations of batch cells, flow cells have emerged as an efficient reactor configuration, offering high mass transference coefficients and easy temperature control. Regarding the degradation of p-BQ in flow cells, only two studies have been reported. In the first study, Yoon et al. [17] utilized a flow-through cell equipped with a carbon fiber anode to perform the electrochemical degradation of p-BQ, achieving a removal efficiency of 99.23%. This result was obtained under the following conditions: an initial p-BQ concentration of 0.01 M, a volumetric flow rate of 0.0016 L/min, a current of 175 mA, and an initial pH of 7, with a total treatment time of 12 h, for a 25 mL solution. In the second study, Panizza et al. [3] examined the anodic degradation of p-BQ using a single-compartment flow cell with a boron-doped diamond (BDD) anode under galvanostatic conditions. The study authors observed 98% degradation efficiency under optimal operating conditions, with a volumetric flow rate of 5 L/min, a temperature of 45 °C, and a current of 1 over 150 min of electrolysis time. This research highlights the potential of BDD anodes under mass-transfer control, particularly at high p-BQ concentrations with low current and high volumetric flow rates.

Notably, BDD anodes have been proven to be exceptional materials for AOP applications [18,19,20]. They possess outstanding electrochemical properties, including a wide potential window, corrosion resistance, low background current, and high durability. These properties enable these BDD anodes to generate physiosorbed ^•OH radicals, facilitating the rapid and efficient mineralization of CECs [21]. Additionally, boron concentration considerably influences the electrochemical performance of BDD anodes, suggesting that controlling boron concentration could lead to the design of BDD anode materials with improved electrochemical properties [22,23,24]. Moreover, ^•OH radicals are weakly adsorbed on the BDD anode surface, allowing them to immediately and non-selectively attack and oxidize CECs, through reactions (1) and (2) [25,26,27].

$$DDB+H_{2}O\to DDB\left({}^{•}OH\right)+H^{+}+e^{-}$$

(1)

$$DDB\left({}^{•}OH\right)+R\to DDB+m{H}_{2}O+nC{O}_2$$

(2)

To enhance the mineralization of CECs, researchers have explored BBD anodic degradation using various cathode materials, such as platinum coated with titanium (Pt/Ti) [28], stainless steel [3,28], copper (Cu) [29], and zirconium (Zr) [30]. However, to the best of our knowledge, there have been no studies assessing the optimization of p-BQ mineralization using BDD electrodes as both the cathode and anode. Therefore, this study focused on the maximization of the electrochemical oxidation of p-BQ in an aqueous solution using an electrochemical flow reactor equipped with BDD electrodes as both the anode and cathode. Additionally, we calculated the operating cost of the electrochemical process as a function of electrolysis time and energy consumption. Response surface methodology with central composite design (RSM-CCD) was used to design the experiments and optimize the process parameters, including initial pH (pH₀) and current density (j). The results of this study provide a foundation for scaling up the process and reproducing the results in larger systems [3].

2. Materials and Methods

2.1. Reagents

A 2.5 L freshly prepared aqueous solution of p-BQ (CAS: 106-51-4, molar mass: 108.09 g/mol, purity ≥98%) was used for each experiment at an initial concentration ([C]₀) of 1 × 10⁻³ M in 0.15 M Na₂SO₄. To adjust the pH according to the experimental design, we prepared 2 M solutions of NaOH (97% purity) and H₂SO₄ (95% purity) before each experiment. All reagents were purchased from Sigma-Aldrich (Toluca, Mexico) and employed without any previous treatment.

2.2. Equipment

A Hanna HI2210 pH meter was used to measure the pH of the solutions, and electrode energization was performed with a GW Instek GPR-351OHD power supply. The degradation efficiency of p-BQ (η) was determined using a Perkin Elmer Lambda 365 UV-Vis spectrophotometer [31]. The electrochemical flow reactor consisted of BBD electrodes serving as both the anode and cathode supported on niobium (Nb) and was purchased from Metakem™. Each electrode measured 20 cm in length and 1.6 cm in height, 32 cm² in area, and had a thickness of 5 µm. The BDD electrodes feature an sp³-hybridized orbital structure like that of a diamond, which weakens the adsorption of intermediates and offers high corrosion resistance during long-term cycling from hydrogen to oxygen evolution, even in strongly acidic environments. More details of the electrochemical flow reactor can be found in our previous study [31].

2.3. Analytical Procedures

The efficiency of p-BQ degradation was calculated using Equation (3) [32]. The absorbance (A) of the p-BQ solution samples was measured at a wavelength (λ) of 246 nm at both the start and the end of each experiment.

$$\eta \left(\%\right)={\displaystyle \frac{A_0-A_t}{A_0}}\times 100$$

(3)

where A₀ represents initial absorbance, while A_t denotes the final absorbance

Additionally, the η of p-BQ under optimal operating conditions was calculated using Equation (4),

$$\eta \left(\%\right)={\displaystyle \frac{C_0-C_t}{C_0}}\times 100$$

(4)

where C₀ represents the absorbance at the start of the experiment and C_t denotes the absorbance at the end.

2.4. Operating Cost

The operating cost (OC) was calculated using Equations (5) to (9), considering the energy price and the cost of the supporting electrolyte. The total energy consumption (EC) includes the energy used by the electrodes, the flow pump, and the heat exchanger pump [33].

$$E_{\mathrm{electrode}}=U\times i\times t$$

(5)

$$E_{\text{pump-flow}}=P_n\times t$$

(6)

$$E_{\text{pump-heat}\mathrm{exchanger}}=P_m\times t$$

(7)

$$EC=E_{\mathrm{electrode}}+E_{\text{pump-flow}}+E_{\text{pump-heat-exchanger}}$$

(8)

$$OC=\xi EC+\varphi m_{\mathrm{electrolyte}}$$

(9)

where EC is the total energy consumption (kWh), U is the mean electric potential (V), i is the current intensity (A), t is the electrolysis time (h), E_electrode is the energy consumption by the electrode (kWh), E_pump-flow is the energy consumption by the flow pump in kWh, E_{pump-exchanger} is the energy consumption by the heat exchanger pump (kWh), P_n and P_m are the pump power for the flow pump and the heat exchanger pump (0.198 and 0.123 kW, respectively), OC is the total operating cost (USD), ξ is the electricity price (0.21USD kW/h) for Tariff1B in Mexico, provided by the CFE, ϕ is the electrolyte price (168.57) in USD/kg, and m_electrolyte is the mass of electrolyte consumed (kg).

The specific energy consumption (SEC) at a constant current intensity (i) was calculated using Equation (10) [34]:

$$SEC\left({\displaystyle \frac{kWh}{m^3}}\right)={\displaystyle \frac{U\times i\times t}{V_t}}$$

(10)

where V_t is the volume treated (2.5 L).

2.5. Experimental Design

The electrooxidation process was carried out based on a face-centered central composite design with two key operating parameters, initial pH (pH₀) and current density (j). These variables were selected because they significantly influence the electrooxidation process [35]. The values and levels of the operating parameters are presented in

Table 1. Levels and values of the operating variables.

Operating Variables	Levels
	−α	−1	0	+1	+α
X1: pH0	2.71	3.00	5.00	7.00	7.83
X2: j (A/cm2)	0.0872	0.0937	0.1094	0.1250	0.1315

. Additionally, the operating variables were coded using Equation (11).

$$X_i={\displaystyle \frac{x_i-x_0}{\Delta x_i}}$$

(11)

where X_i represents the coded value of each operating variable, x_i denotes the actual value of each operating variable, x₀ refers to the actual value of each operating variable at the center point, and Δxi indicates the increment between levels of each operating variable. The low and high levels were represented by −1, and +1, respectively.

The experimental design matrix included 10 runs, consisting of 2k factorial points, 2k axial points, and k central points, where k = 2 and α = 2^k/4. The response variable was η (p-BQ removal efficiency). Additionally, three extra experiments were conducted to validate the optimal operating conditions and determine the kinetic parameters for the electrochemical degradation of p-BQ.

2.6. Modeling and Optimization Process

The modeling and optimization of the electro-oxidation process were conducted using response surface methodology (RSM), as outlined in Section 2.5. This approach was applied to evaluate the effect of the independent variables, initial pH (pH₀) and applied current density (j), and the effect of the interactions between these variables on the response (η). RSM was also used to identify the optimal operating conditions for the process.

After the experimental design matrix was completed, a second-order polynomial regression model (as described in Equation (12)) was fitted to the data.

$$\eta ={\beta }_0+{\displaystyle \sum _{i=1}^2{\beta }_i{X}_i+{\displaystyle \sum _{i=1}^2{\beta }_{ii}{X}_i^2+{\displaystyle \sum _{i=1}^2{\displaystyle \sum _{j=1}^2{\beta }_{ij}{X}_i{X}_j}}}}+\epsilon$$

(12)

where β_i is the polynomial constants, X_i is the coded variables, and ε is the error.

The accuracy and significance of the adjusted polynomial regression model were assessed with an analysis of variance (ANOVA) test [36]. Additionally, all data analyses, modeling, ANOVA and parity, contour, and 3D surface plots were performed using the Design Expert Software package (V.10.0) [35]. The optimal operating conditions were determined by applying the steepest descent method to Equation (12).

3. Results and Discussion

3.1. Polynomial Model

Based on the experimental matrix presented in

Table 2. Experimental design matrix for p-BQ removal at a volumetric flow rate of 1 L/min.

Run	Factor		Response
	pH0	j (A/cm2)	η (%)
1	7.00	0.0937	82.22
1	7.00	0.1250	98.78
3	5.00	0.0872	97.04
4	2.17	0.1094	60.10
5	3.00	0.0937	81.17
6	5.00	0.1094	89.97
7	5.00	0.1315	95.49
8	5.00	0.1094	87.49
9	3.00	0.1250	61.50
10	7.83	0.1094	90.63

, the p-BQ removal efficiency ranged from a capacity of 60.10 to 98.78%. The reduced second-order polynomial regression model representing p-BQ removal (η) is denoted by Equation (13). In the second-order polynomial regression model (Equation (14)), X₁ and X₂ are linear terms, X₁X₂ is the interaction term, and $X_1^2$ is the quadratic term.

Uncoded mathematical model

$$\eta \left(\%\right)=172.9379-4.1051pH-1489.5744j+289.4370pH\times j-2.2459p{H}^2$$

(13)

Coded mathematical model

$$\eta \left(\%\right)=91.6300+10.1700X_1-0.6634X_2+9.0600X_1{X}_2-8.9800X_1^2$$

(14)

3.2. Interaction Effect Between Variables

In the coded regression model in Equation (13), the sign of each coefficient indicates the nature of the variable’s effect on p-BQ removal. A positive sign indicates a synergetic effect, while a negative sign indicates an antagonistic effect [37]. In Equation (13), X₁ (pH₀) and X₁X₂ (pH₀ × j) exhibit a synergetic effect, while X₂ shows an antagonistic effect.

3.3. ANOVA Test

The results of the ANOVA test for p-BQ removal are shown in

Table 3. Analysis of variance for p-BQ removal.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	1615.09	4	403.77	24.11	0.0018	Significant
X1	828.07	1	828.07	49.45	0.0009
X2	3.52	1	3.52	0.2104	0.6257
X1X2	328.29	1	328.29	19.60	0.0068
X12	452.82	1	452.82	27.04	0.0035
Residual	83.73	5	16.75
Lack of Fit	80.66	4	20.16	6.56	0.2839	Not significant
Pure Error	3.08	1	3.08
Cor Total	1698.83	9
$R^2=0.950;$ $R_{Adj}^2=0.911;$ $R_{\mathrm{Pr}ed}^2=0.813$; adequate precision = 14.516; coefficient of variance = 4.85

. The analysis indicated that the second-order polynomial regression model was significant, evidenced by the F-value (24.11) being higher than the p-value (0.0018), confirming that the fitted model accurately represented the experimental data [38]. Additionally, a p-value lower than 0.05 indicated a significant term. For the individual model terms, X₁, X₁X₂, and X₁² (p = 0.0009, 0.0068, and 0.0035, respectively) were significant, while X₂ was not (p = 0.6657).

The lack-of-fit test yielded a p-value of 0.2839, suggesting good model fit, as a p-value less than 0.1 indicates that the lack-of-fit is not significant [39,40]. Additionally, the model’s R² value of 0.950 indicated an excellent fit to the experimental data [41]. The difference between $R_{Adj}^2$ and $R_{\mathrm{Pr}ed}^2$ (0.098) was lower than 0.2, indicating a high level of concordance.

The adequate precision value of 14.516 suggests that the model had a sufficient signal-to-noise ratio, as values greater than 4 indicate that the model can effectively navigate the design space [42]. Furthermore, the coefficient of variance of 4.85% was lower than 10%, indicating the model’s high reproducibility and suitability for assessing the optimal operating variables.

As seen in Figure 1a, the predicted and actual p-BQ removal values are highly correlated, demonstrating the model’s adequacy in predicting p-BQ removal based on Equation (13). Figure 1b illustrates the perturbation plot, showing that the initial pH (pH₀) significantly influenced p-BQ removal more than the applied current density (j), as it exhibits a distinct curvature and notable changes in slope.

Pareto analysis was conducted to evaluate the importance of each term in the fitted model Equation (13) using Equation (15),

$$P_i=\left({\displaystyle \frac{{\beta }_i^2}{{\displaystyle \sum _{i=1}^4{\beta }_i^2}}}\right)$$

(15)

As shown in Figure 1c, the terms β₁, β₁₂, and β₁₁ significantly impacted p-BQ removal, contributing 38.79%, 30.78%, and 30.24%, respectively. In contrast, β₂ had a minimal effect, contributing only 0.16%. These results, consistent with those observed in the perturbation diagram, highlight the important role of initial pH in hydroxyl radical production on the BDD anode surface. This effect depends on both the supporting electrolyte used and the organic compound under study [43].

3.4. Optimization of p-BQ Removal (η)

After establishing the experimental design matrix provided (Table 2) and the fitted regression model (Equation (13)), the optimal conditions for p-BQ removal could be determined. To identify the variable values that maximize η (%), the optimization criteria (

Table 4. Optimization criteria and constraints.

Response	Objective	Limits
		Min	Max	Unit	Importance
pH0	Within range	3	7	Dimensionless	+++
j	Within range	0.0937	0.125	A/cm2	+++
η	Maximized	60.1	98.78	%	+++

) were input into the Design Expert^® v10 software package [35], ensuring that all variables and the response (η [%]) were assigned equal importance (+++). The steepest ascent method was used to find the optimal process variables.

Figure 2 shows the optimization ramps for the initial pH (pH₀) and applied current density (j). The results indicate that the optimal operating conditions for maximizing p-BQ removal (99.96%) were a pH₀ of 6.52 and a j of 0.124 A/cm².

The 3D surface plot (Figure 3a) illustrates the interaction effect between pH₀ and j within the studied range. The plot forms a hyperbolic function, as indicated by the hyperbolic contour lines. Figure 3a also reveals that the applied current density has relatively minimal influence on p-BQ removal, whereas the initial pH exerts a more significant effect, with a notable shift in slope as pH_o increases from low to high values (1–10). Specifically, as the initial pH_o rises from 1 to 6, p-BQ removal improves, but from 6.7 to 10, it decreases. However, when the initial pH rises from 6.7 to 10, the removal of p-BQ declines. This decline is likely attributed to the accumulation of by-products in the aqueous solution at higher pH levels. Consequently, p-BQ mineralization (CO₂ formation in aqueous solution) is more effective at lower initial pH values [4]. Furthermore, the supporting electrolyte used (Na₂SO₄) promotes the formation of other oxidative species (e.g., $S_2{O}_8^{-2}$(Reaction (16)) and $S{O}_4^{•-}$ (Reaction (17)), which have lower oxidation potentials than hydroxyl radicals (^•OH). Moreover, Reaction (17) indicates that $S{O}_4^{-2}$ can act as a scavenger for ^•OH, reducing the p-BQ removal rate [44].

$$2S{O}_4^{-2}⥂S_2{O}_8^{-2}+2e^{-}$$

(16)

$$2S{O}_4^{-2}+{}^{•}OH\to S_4{O}^{•-}+O{H}^{-}$$

(17)

Figure 3b depicts the overlay plot, which is bounded by a pH₀ range of 1–10 and a j range of 0.08–0.13 A/cm². The black lines denote the optimization criteria, the yellow area represents the feasible region, and the gray area indicates conditions that do not meet operational requirements. According to the overlay plot, the maximum p-BQ removal achieved was 99.96% under the optimal conditions of a pH₀ of 6.52 and j of 0.124 A/cm², with a treatment duration of 5 h.

3.5. Model Validation

Three additional experiments were performed to validate the fitted regression model (Equation (17)) under optimal operating conditions. The mean p-BQ removal was 97.32%. Comparing the predicted (99.96%) and experimental (97.32%) values revealed a discrepancy of 2.64%, indicating that the model accurately represented the electrochemical degradation process. Figure 4a displays the UV-Vis spectra, showing the progression of p-BQ degradation under optimal conditions, while Figure 4b shows p-BQ removal efficiency over time.

The pH during electrolysis (initial pH of 6.52, current density of 0.124 A/cm², and treatment period of 5 h) is shown in Figure 5. The solution pH remained relatively stable throughout the experiment, consistent with prior studies [45,46]. The slight increase in pH is attributed to the formation of carboxylic acids such as fumaric, succinic, oxalic, oxamic, maleic, formic, and acetic acids, aligning with previous findings [47]. It is important to note that no pH control mechanism was implemented in the experimental setup. This absence of pH adjustment is advantageous for industrial-scale treatments, as it eliminates the associated need for pH adjustment. Additionally, the final pH of the treated solution remained close to neutral, suggesting that the effluent could be discharged directly to sewage systems or other water bodies without further treatment.

The total operating cost was estimated at USD 3.07/L (1 USD = MXN 20.22), which includes both energy expenses and the cost of the supporting electrolyte consumed. The energy cost alone was USD 0.02/L. In industrial applications, the SEC is crucial because of its direct impact on operational costs. As shown in Figure 6, the SEC exhibits a linear trend from 0% to 70% p-BQ removal efficiency; however, after reaching 70% p-BQ removal, the SEC increases exponentially. This observation trend aligns with findings reported in the literature [3,44] and can be attributed to the formation of by-products that are more resistant to degradation, such as carboxylic acids (e.g., fumaric, succinic, oxalic, oxamic, maleic, formic, and acetic acids) [44]. Additionally, the exponential rise in SEC is influenced by the decreasing concentration of p-BQ in the aqueous solution as the reaction progresses [3]. At the end of the electrolysis process, the SEC reached 127.854 kWh/m³. Notably, the electrochemical treatment proposed in this study is environmentally friendly, as it generates no sludge, and maintains relatively low energy consumption, making the method compatible with renewable energy sources such as solar panels.

3.6. Kinetic Model

Figure 7 shows the p-BQ concentration decay for three kinetic reaction models, all of which exhibit asymptotic behavior (see Equation (18)). This pattern suggests that the electrochemical degradation of p-BQ functions under mass transfer control [43]. The apparent kinetic constants and corresponding determination coefficients (R²) for the three models are summarized in

Table 5. Parameters for the three kinetic reaction models.

Orders (n)	kapp	Unit	R2
Pseudo-zero-order	1.7307 × 10−4	M/h	0.7179
Pseudo-first-order	0.9660	1/h	0.9737
Pseudo-second-order	18879.4745	1/(M h)	0.8465

. Based on the R², values, the electrochemical degradation of p-BQ followed a pseudo-first-order kinetic model, consistent with previous reports [3].

$$-r_{p-BQ}=k_{app}{C}_{p-BQ}^n$$

(18)

Based on the regression analysis, the apparent kinetic constant (k_app) was 0.966 1/h with an R² of 0.9737, indicating a strong correlation with the experimental data. The pseudo-first-order kinetic observed in this study align with the typical degradation of aromatic organic compounds through AOPs such as electrolysis; similar kinetics have been found for the degradation of beta-blockers [48,49,50], chloroquine [51], ibuprofen [36], and 2-chlorophenol [31]. This pattern is due to the constant generation of hydroxyl radicals (^•OH) on the BDD anode surface. Moreover, these ^•OH cannot accumulate on the anode or in the bulk solution because of their short lifetimes [46].

Table 6. p-BQ removal using electrochemical flow reactors.

Op	NOp	An/Cat	V (L)	DE (%)	DQO (%)	SEC (kWh/m3)	OC (USD/L)	Ref.
Q = 1.0 L/min, [C6H4O2]0 = 0.001 M, pH0 = 6.52, j = 0.124 A/cm2, t = 5 h		BDD/BDD	2.500	97.32	---	127.85	3.07	This work
	Q = 0.0016 L/min, [C6H4O2]0 = 0.01 M, [H2SO4] = 0.5 M, i = 0.124 A, pH = 7, t = 12 h	Pt/Carbon fiber	0.025	99.23	---	---	---	[17]
	Q = 5 L/min, [C6H4O2]0 = 0.0092 M [HClO4] = 0.5 M, j = 0.02 A/cm2, t = 2.5 h	BDD/stainless steel	0.400	100.00	80	49.50	---	[3]

DE: degradation efficiency; Op: optimized; NOp: not optimized; An: anode; Cat: cathode.

compares different methods for p-BQ degradation in electrochemical flow reactors. Notably, this study is the first to optimize the electrochemical degradation process of p-BQ while estimating the overall operating cost. Although previous studies have achieved higher degradation efficiency (99.23% and 100%, respectively) than that of the current study (97.32%), they used reactor volumes that were considerably smaller (0.0025 and 0.4 L) than those used in this work (2.5 L) [3,17]. Additionally, Yoon, J. et al. [17] achieved 99.3% p-BQ removal but required a reaction time of 12 h, longer than the 5 h method in this study. These results suggest that the electrochemical treatment proposed herein offers an effective method for treating wastewater containing recalcitrant compounds like p-BQ.

4. Conclusions

This study reports on the optimization of the electrochemical degradation of p-BQ using BDD electrodes in a batch recirculation model. The effects of pH and current density on p-BQ degradation were assessed using RSM by employing a CCD. According to the ANOVA results, an effective degradation efficiency of 97.32% was attained at a pH of 6.52 and a current density of 0.14 A/cm² over a 5 h period. The experimental results are in line with the predictions of the reduced second-order fitted model, demonstrating the model’s strong predictive capacity for p-BQ removal efficiency. In our kinetic analysis, we found that p-BQ degradation followed pseudo-first-order kinetics, with an R² value of 0.9737. Lastly, the total operating cost of the electrochemical treatment was USD 3.07 per liter, which includes both energy consumption and the cost of the supporting electrolyte. Our findings highlight the potential of the electrochemical treatment used in this study as an effective and scalable method for removing p-BQ from wastewater.