Abstract

The hydrogen peroxide role in photocatalytic degradation of an anionic azo dye, Acid Orange 7 (AO7), was investigated in a slurry reactor. Commercial ZnO nanoparticles with an average size between 10 to 30 nm were used as catalysts. Optimum conditions for different parameters, including dye concentration (10–100 mg/L), catalyst concentration (0.1–0.5 g/L), and pH (5–10), were determined first in the absence of H2O2. Changes in the COD were measured for the optimum condition. The impact of adding hydrogen peroxide at different concentrations to the system operating at optimum conditions was investigated. It was observed that 0.416 mM hydrogen peroxide increased the system's efficiency and decreased reaction time by 40 min. The reaction followed first-order kinetic. Hydrogen peroxide alone did not contribute to oxidizing the contaminant, and its positive impact was attributed to decreasing electron-hole recombination in the photocatalytic process. Not only can the hydrogen peroxide-assisted photocatalytic process decrease retention time in treatment units, but it can also result in more contaminant degradation. Therefore, it can reduce the treatment cost.

HIGHLIGHTS

  • Improving the efficiency of the slurry photocatalytic process by adding H2O2.

  • Promoting the process's rate and reaction kinetics’ constants four times by adding 2.5 mM of H2O2.

  • Determining optimum concentration using energy consumption reaction in order to conduct the research in the minimum energy usage condition.

Graphical Abstract

Graphical Abstract
Graphical Abstract

INTRODUCTION

Dyes are used in various industries such as textiles, leather, printing, and paper production, to name a few. The presence of these recalcitrant compounds in aqueous bodies can have a negative impact on the environment (Naushad et al. 2016). They can also form trihalomethanes, reduce the water's clarity, and interfere with the absorption and reflection of sunlight radiation, consequently threatening aquatic life and plants' photosynthesis (Chen et al. 2019; Ghalebizade & Ayati 2020). Among different dye compounds, acid orange 7 (AO7) (C16H11N2NaO4S) is a toxic substance that is widely used due to its low cost and high solubility in water. Its low biodegradability makes it last for a long time in the environment (Nourmoradi et al. 2015). Various methods have been used for treating these wastewaters, including physical (adsorption and membrane methods), biological (biofilters and SBR), and chemical methods (coagulation and flocculation, electrochemical processes, traditional, and advanced oxidation process), and all the mentioned methods have some specific disadvantages (Paz et al. 2017; Sarvajith et al. 2018; Ghalebizade & Ayati 2019; Ranjbar et al. 2019; Jain et al. 2020; Khouni et al. 2020; Yun et al. 2020). For instance, biological processes produce huge amounts of sludge and are incapable of degrading complex structures; or some adsorbents agglomerate easily and lose their efficiency. But, they are low-cost and remove a wide range of pollutants (Albadarin et al. 2017; Ahmed et al. 2020). Besides, many common methods, such as coagulation and flocculation, only transfer the contaminant from one phase to another (Crini & Lichtfouse 2019). However, advanced oxidation processes have received much attention due to their high degradation rate and ability to remove recalcitrant compounds. These methods are based on the generation of hydroxyl radicals (extremely powerful oxidants), which can destroy organic structures and change them to less harmful materials, namely water and carbon dioxide (Wang et al. 2020). Using nano-scaled materials has attracted researchers' attention due to the unique charecteristics that these materials possess in nano scale condition. These types of materials have been used for different applications such as catalytic hydrogen and oxygen evolution processes (Ahsan et al. 2021a; Puente Santiago et al. 2021), and advanced oxidation processes (Ahsan et al. 2020, 2021b; Nayebi & Ayati 2021), more specifically photocatalytic degradation of organic pollutants (Islam et al. 2020).

Photocatalysts and photocatalytic composites used for organic pollutant degradation are among the advanced oxidation processes (AOPs) used for dye removal in many studies (Naushad et al. 2019). The photocatalytic method is based on accelerating a photochemical conversion using a catalyst. Photocatalysts have been widely used in the degradation of various contaminants, among which pharmaceutical, acid orange 7, methyl orange, arsenic, and triclosan are the most conspicuous ones (Di et al. 2017; Kosera et al. 2017; Mohapatra et al. 2017). Catalysts are often used in two forms, immobilized and slurry, of which the removal efficiency of the slurry system has been proved to be higher than the immobilized system. It is noteworthy to mention that using nanoparticles as catalysts, instead of microparticles, including ZnO, improves the efficiency of the process due to increasing the specific surface area and active sites for adsorption and their potential for the degradation of pollutant chemicals (Satheshkumar et al. 2020).

The degradation route in this method is also important. In photocatalytic reactions, the catalyst's particles absorb photons with energy greater than their energy gap, and the photon-excited electron is transferred from the valance band (VB) to the conduction band (CB), forming a positive hole (hVB+) and an electron (eCB) at the catalyst particle surface. The generated electrons and holes generate active radicals in the solution that eventually destroy the contaminant molecules. Different photocatalysts have been widely used for organic compounds removal. For example, in a study, methyl red, alizarin, crocein orange, congo red, and methyl blue have been removed within 120 minutes using TiO2 photocatalysts (Anwer et al. 2019). In another study, various reactive dyes were degraded utilizing ZnO nanoparticles, and this material shows a promising performance for dye degradation (Anwer et al. 2019). In a comparative study, antibiotics degradation was conducted using ZnO and TiO2 nanoparticles. Although the degradation rate was faster using TiO2, ZnO nanoparticles showed higher degradation performance, less toxicity, and better dispersion (Ambrosetti et al. 2015).

Despite the various advantages of the photocatalytic process, this method suffers from some drawbacks, such as the recombination of electrons and holes in the conduction band and release of heat (Lee et al. 2016). Therefore, various methods have been proposed to address this issue, among which doping metals and adding electron acceptors are the widely accepted remedies. Electron acceptors are chemical compounds that react with electrons produced in photocatalytic processes to prevent electron-hole recombination. Hydrogen peroxide is one of these materials, which has been used in various researches. Tseng et al. (2012), for example, have investigated the effect of hydrogen peroxide and oxygen on the photocatalytic degradation of monochlorobenzene using TiO2 suspension irradiated with a black light. This substance showed a better removal efficacy due to the higher oxidation potential and electrophilicity of hydrogen peroxide than oxygen. By adding electron acceptors, the degradation efficiency and reaction rate constant increased. However, adding more hydrogen peroxide (exceeding the optimal condition) reduced efficiency. Also, adding hydrogen peroxide from 5.6 to 45 mg/L increased the TOC removal efficiency from 44.4 to 74.1 percent in 240 minutes, respectively (Tseng et al. 2012). In another study, Armakovic et al. have analyzed the photocatalytic degradation of metoprolol using TiO2 suspension. The effect of different electron acceptors, including molecular oxygen, hydrogen peroxide, potassium bromate, and ammonium persulfate, on the process efficiency, was investigated, and molecular oxygen outperformed the rest (Armaković et al. 2015). Silva et al. (2017) synthesized d-FeOOH nanoparticles and used them for photocatalytic degradation of rhodamine B with 20 mg/L initial concentration. After one hour, only 59% of rhodamine B was degraded, while adding hydrogen peroxide improved the process's efficiency by 87% (Silva et al. 2017). Kang et al. (2017) improved the photocatalytic ability of TiO2 nanoparticles with hydrogen peroxide, which increased the efficiency even under visible light. Besides, about 60% of the dye was removed when they used hydrogen peroxide for 210 minutes (Kang et al. 2017). In another study, Azim et al. (2018) analyzed the photocatalytic performance of graphene oxide in methylene blue removal under sunlight irradiation. They investigated the effectiveness of two different electron acceptors (hydrogen peroxide and oxygen) on the removal rate. Using hydrogen peroxide improved the kinetic coefficient from 0.035 to 0.062 per minute (Azim et al. 2018).

In this study, degradation of an anionic azo dye, Acid Orange 7, using a photocatalytic process in a slurry reactor was investigated. An electron acceptor's role in reducing electron-hole recombination and increasing efficiency was studied. The study was aimed to determine a cost-effective method to combat a drawback of the photocatalytic process; thus, promoting the degradation rate and decreasing the reaction time. Also, to the best of our knowledge, such a system has not been used to remove an anionic azo dye. Besides, other studies focus on the maximum efficiency while we wanted to find the minimum amount of chemicals needed to get the highest removal rate in a shorter time. Considering this aspect would result in a monetary benefit in practical applications too.

MATERIALS AND METHODS

In order to make synthetic wastewater, AO7 manufactured by Alvan Sabet company was purchased. Photocatalyst nanoparticles were ZnO (10 to 30 nanometers, 99% purity) US-NANO brand, and for pH adjustment, NaOH (Merck, ≥95% purity) and HCl (Merck, 37% purity) were applied. Besides, AgSO4 (Merck, 99% purity) and H2SO4 (Merck, ≥95% purity) to make the COD catalyst solution, and HgSO4 (Merck, ≥98% purity) and K2Cr2O7 (Merck, 99% purity) to make the COD digestion solution was also used. Hydrogen peroxide (Merck, Germany) as an electron acceptor, distilled water to make the sample, and dilution were used in this experiment.

The pilot was a glass cylinder with a volume of 1.75 liters (Figure 1), and a UV-C light was located in the center of the reactor covered by a quartz sleeve. ZnO nanoparticles were added to the reactor (slurry), and the pilot was equipped with an aeration system to mix the solution and increase the contact between nanoparticles and dye.

Figure 1

The pilot used in the study.

Figure 1

The pilot used in the study.

In this experiment, the effect of various parameters, including initial contaminant concentration, nanoparticle concentration, solution pH, and radiation wavelength, was studied, the range of which is presented in Table 1.

Table 1

Range of investigated parameters in the experiments

ParametersRange
Initial concentration (mg/L) 10, 25, 50, 100 
Nanoparticles concentration(g/L) 0.1, 0.2, 0.5 
(W) UV-C lamps power 15 
pH 5, natural (8.3), 10 
ParametersRange
Initial concentration (mg/L) 10, 25, 50, 100 
Nanoparticles concentration(g/L) 0.1, 0.2, 0.5 
(W) UV-C lamps power 15 
pH 5, natural (8.3), 10 

The 500 mg/L stock solution of synthetic wastewater was prepared daily using the dissolution of AO7 in municipal water, and the desired concentrations were prepared from this stock. Samples were taken at 20-minute intervals. Finally, samples were centrifuged, and changes in their concentrations were examined by spectroscopy.

The dye absorption spectrum had a maximum absorption at 485 nm, and this wavelength was used to analyze changes in samples' concentrations. After determining the optimal values of the parameters affecting the process, the effect of hydrogen peroxide on the process was also studied. All the experiments were conducted at room temperature (25 ± 3 °C) and were repeated three times, in which the acceptable error range was less than 5 percent. The energy consumption was calculated through Equation (1).
formula
(1)
where EC/C is consumed electrical energy per mg of the pollutant removed (kWh/mg), V is solution volume (L), W is lamp consumption or electrical power (kW), C0 and Ct are initial concentrations and concentrations in time t (Damodar et al. 2010).

The main equipment used in the study is listed hereunder:

Ultrasonic cleaner (Fungilab, UE-6SFD) to disperse nanoparticles, UV/Vis spectrophotometer (Hach, DR4000) to determine dye concentration and COD, digital pH meter (Metrohm, 691) to adjust pH, Centrifuge (Sigma, 101) to separate nanoparticles before putting in the spectrophotometer, COD reactor (Hach, DRB200) to investigate Chemical Oxygen Demand, digital balance (Mettler, PJ 300), aeration pump (Dolphin, EP-30) to provide the system with homogenous mixing and aeration, 15 W UV-C lamps (TUV 15 W 1SL) with 253.7 nm wavelength, 15 W UV-A lamps (Master Actinic BL TL-D 15 W/10 1SL) with 370 nm to irradiate the mixture and activate nanoparticles.

RESULTS AND DISCUSSION

Determination of optimum dye concentration

The removal efficiency was analyzed for different dye concentrations under constant conditions to determine the optimum concentration and is illustrated in Figure 2. According to results, dye removal for 10, 25, 50, and 100 mg/L after 40 minutes was 91.4, 64.7, 45.1, and 17.3 percent, respectively. As can be seen, the reaction rate was higher at lower concentrations, and after twenty minutes, 76.1% of the dye (C0 = 10 mg/L) was removed. However, less than 10 percent of the AO7 with the initial concentration of 100 mg/L was removed. The reason is that at higher dye concentrations, the number of contaminant molecules around the catalyst surface increases, which means more oxidizing species (hydroxyl radicals and superoxide radicals) are required. Due to the limited number of active sites, the amount of oxidizing agents in the solution is insufficient to absorb hydroxyl ions and oxygen molecules (Moradi et al. 2017). Therefore, by increasing the dye's initial concentration, the chance of the reaction between dye molecules and oxidizing species decreases. It is noteworthy to mention that intermediates produced during the process may lead to secondary reactions and consume solution free radicals (such as hydroxyl radicals). This competition between dye molecules and intermediates for free radicals also reduces the process efficiency as dye concentration increases. The results are similar to those reported in previous studies (Moradi et al. 2017).

Figure 2

The effect of initial dye concentration on the photocatalytic process's efficiency ([ZnO] = 0.5 g/L, pH0 = 8.3, PUV-C = 15 W).

Figure 2

The effect of initial dye concentration on the photocatalytic process's efficiency ([ZnO] = 0.5 g/L, pH0 = 8.3, PUV-C = 15 W).

Energy consumption is a significant factor affecting the process in advanced oxidation processes. Therefore, to determine the optimal concentration in which energy consumption is minimized, Equation (1) was used. In this regard, energy consumption to achieve removal efficiencies of 90, 95, and 97 percent was calculated. The minimum condition occurred at 25 mg/L in 120 minutes, as illustrated in Figure 3. Thus, this was used as an optimal condition for the rest of the research.

Figure 3

Energy consumption per initial dye concentration ([ZnO] = 0.5 g/L, pH0 = 8, PUV-C = 15 W).

Figure 3

Energy consumption per initial dye concentration ([ZnO] = 0.5 g/L, pH0 = 8, PUV-C = 15 W).

Determination of optimum ZnO concentration

Experiments were performed with various catalysts concentrations to determine the optimum ZnO nanoparticles' concentration, and the result is depicted in Figure 4. As can be seen, increasing the nanoparticle concentration from 0.1 to 0.5 g/L increased the process efficiency. Dye removal efficiency with an initial concentration of 25 mg/L using ZnO nanoparticles with 0.1, 0.2, and 0.5 g/L for 100 minutes is 81.34, 92.5 And 95.5 percent, respectively. The reaction at higher concentrations of nanoparticles was short, and the process performed faster. After twenty minutes, dye removal efficiency in the presence of 0.5 and 0.1 g/L nanoparticles was 24 and 42 percent, respectively. In general, increasing the nanoparticle concentration increases the number of active sites, which gives rise to generating more reactive radicals. Besides, ZnO would have more adsorption capacity, which increases the probability of photocatalytic removal through holes and hydroxyl radicals (Chen et al. 2005; Liu et al. 2018). However, the excessive increase in ZnO concentrations dwindles the process efficiency because the turbidity (caused by the high concentration of nanoparticles) culminates in less UV penetration and will be scattered more by nanoparticles. Therefore, nanoparticles are not stimulated well, and a smaller volume of suspension is activated by photons, reducing removal (Rani & Karthikeyan 2020). It is worth noting that in higher ZnO concentrations, the agglomeration of nanoparticles is more probable, decreasing the number of active sites and removal efficiency (Lee et al. 2016). Besides, due to economic consideration, consuming smaller amounts of nanomaterials is desirable, so it was also considered when selecting optimum conditions. According to Figure 4, increasing the ZnO concentration from 0.1 to 0.2 g/L increased the removal efficiency from 85.2 to 95.6 percent in 120 minutes. However, more increase in ZnO concentration (up to 0.5 g/L) only increased efficiency by about 2 percent, and thus 0.2 g/L of ZnO was considered as the optimum concentration.

Figure 4

The effect of ZnO concentration on the photocatalytic process efficiency ([AO7] = 25 mg/L, pH0 = 8.3, PUV-C = 15 W).

Figure 4

The effect of ZnO concentration on the photocatalytic process efficiency ([AO7] = 25 mg/L, pH0 = 8.3, PUV-C = 15 W).

Determination of optimum pH

After determining the optimal values of the initial dye and ZnO concentration, the solution's pH was changed to determine the optimal condition. pH plays a crucial role in photocatalytic reactions. This parameter affects the surface charge of nanoparticles and the conduction and valance bands' location in the semiconductor (Chong et al. 2010). As shown in Figure 5, the highest and lowest photocatalytic efficiencies were obtained at pH = 10 and pH = 5, 97.3 and 41 percent.

Figure 5

The effect of initial pH on the photocatalytic process efficiency ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, PUV-C = 15 W).

Figure 5

The effect of initial pH on the photocatalytic process efficiency ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, PUV-C = 15 W).

At pH = 10, the dye removal rate in the early stages of the process was higher than neutral pH = 8.3 and acidic pH = 5. After 20 minutes, dye removal in basic, neutral, and acidic conditions were 53.2, 34, and only 5.9 percent, respectively. Since the pHPZC of the ZnO nanoparticles is 9.4, when the pH is higher than the pHPZC, the nanoparticle's surface becomes negatively charged. Similarly, if the pH is less than the mentioned value, nanoparticles have a positive surface charge (Omar et al. 2014; Reinders et al. 2017). Besides, AO7 molecules have a negative charge at pH between 3 and 11. Therefore, at pH higher than these values, dye molecules are not well absorbed by nanoparticles (Liu et al. 2018). However, because at more alkaline pHs more hydroxyl radicals are generated, in this experiment, at pH = 10, a slight increase in removal efficiency was still observed (Daneshvar et al. 2007). Therefore, after two hours in solution with initial pH = 5 (41.5%), the rate of dye removal was much less compared to neutral and alkaline pH. It is also important to mention the final pH was around 8 in all experiments. This circumstance may happen due to hydroxyl radicals generating in the process and alkalinization of the environment and scavenging species produced due to ZnO nanoparticles reactions at different pHs (Omar et al. 2014).

As time passed and the reaction progressed, dye removal efficiency in the final stages at pH = 10 and 8.3 did not differ much. Therefore, neutral pH was selected as the optimal pH condition (pH = 8.3).

Investigating COD removal efficiency in the optimal condition

Since dye removal by itself does not mean that the treated wastewater is suitable for discharging into the environment, COD was also measured under optimal process conditions, the result of which is presented in Figure 6. As can be seen, the COD decreased by 50% in the first 20 minutes; then, it increased for 60 minutes. Finally, COD reduction continued steadily, and after 270 minutes, COD was degraded completely. It goes without mentioning that AO7 contains a ring structure and is recalcitrant. Therefore, at the beginning of the test, potassium dichromate cannot break these rings in the COD test, and the initial COD value of the test does not indicate its actual value (Delnavaz et al. 2008). The decrease in COD in the early stages of the process is probably due to breaking the dye molecule's simpler bonds. T increase in COD in the next step may also be due to the breaking of the rings in the AO7 structure, which may be oxidized by potassium dichromate. Therefore, the measured COD has increased so much that after 80 minutes, the amount of COD is not much different from the initial soluble COD. After 80 minutes, the dye molecule structure is completely broken, and since then, the amount of organic compounds in the solution has decreased over time. Hence, after four hours, COD removal efficiency increased so that 91% of COD was removed, and after 270 minutes, complete COD removal was observed.

Figure 6

COD changes over time under optimum condition ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH0 = 8.3, PUV-C = 15 W).

Figure 6

COD changes over time under optimum condition ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH0 = 8.3, PUV-C = 15 W).

Investigating the effect and determining the appropriate concentration of H2O2

Hydrogen peroxide is one of the most common electron acceptors, which improves the photocatalytic process by increasing hydroxyl radicals' production in the environment (Armaković et al. 2015; Govindan et al. 2017; Monteagudo et al. 2020). When introduced to the solution, it competes with other species to capture electrons. However, since it is a strong agent, it is more probable for electrons to be captured by this compound. Thus, the electron-hole recombination will be reduced, and the process's efficiency will be increased. H2O2 in three different concentrations was added to the photocatalytic reactor under optimum conditions to investigate its impact (Figure 7). According to the results, by adding H2O2, the process efficiency increased, and the dye removal time decreased. At 0.208, 0.416, and 1.25 mM, 97.1, 98.9, and 99.1 percent of dye removal were obtained after 80, 80, and 60 minutes. It should be mentioned that dye removal efficiency without adding H2O2 was 95 percent in 120 minutes. Besides, the reaction rate improved when H2O2 concentration increased so that after 20 minutes, 64.8, 68.6, and 78.9 percent of dye were removed in solutions with the mentioned initial H2O2 concentration, respectively. However, in the absence of H2O2, dye removal was only 34 percent.

Figure 7

Investigating the effect of H2O2 concentration on photocatalytic process efficiency ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH0 = 8.3, PUV-C = 15 W).

Figure 7

Investigating the effect of H2O2 concentration on photocatalytic process efficiency ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH0 = 8.3, PUV-C = 15 W).

H2O2 captures electrons and prevents electron-hole recombination through reactions (2) to (4) (Armaković et al. 2015; Monteagudo et al. 2020).
formula
(2)
formula
(3)
formula
(4)
According to these reactions, the better performance of the reaction in the presence of H2O2 is due to the increase in the production of hydroxyl radicals in the solution. In other words, H2O2 can increase the concentration of hydroxyl radicals in different ways, three of which are elaborated: (a) direct H2O2 photolysis by UV irradiation (reaction (2)); (b) the reaction between H2O2 and electrons that leads to the production of hydroxyl radicals and hydroxide ions (reaction (3)); (c) reaction with superoxide radicals and hydroxyl radicals produced (reaction (4)) (Armaković et al. 2015). Nevertheless, according to reactions (5) and (6), adding an excessive amount of H2O2 can trap hydroxyl radicals and produce HO2°, a weaker oxidant than hydroxyl radicals. Hence, the extra amount of hydrogen peroxide in the system can reduce the effectiveness (Monteagudo et al. 2020).
formula
(5)
formula
(6)

Although hydrogen peroxide can oxidize the contaminant directly, based on the control experiments, low concentrations of hydrogen peroxide alone (i.e. 0.416 and 0.208 mM) had a negligible impact on degradation, and higher concentrations (i.e. 1.25 mM) resulted in less than 10% degradation. Consequently, hydrogen peroxide's effect on this process was primarily attributed to increasing the photocatalytic process's efficiency through capturing electrons.

A concentration is selected as the optimal condition that improves the efficiency with the least possible H2O2 consumption. Because the difference between final efficiency and the time required to achieve this efficiency between the two concentrations of 0.416 and 1.25 mM was not significant, the former concentration (0.416 mM) was chosen as the optimal value.

Investigating process kinetics

Kinetics study was done for the optimum condition with and without electron acceptor. To do so, zero, first, and second-order kinetic models were calculated, and the best one was selected through best fit and the highest regression coefficient (R2). Results are presented in Figure 8. Based on this figure, neither zero-order nor second-order kinetics diagrams had a linear trend, meaning neither of them were the case for this process. However, data fitted well the first-order kinetics and had a high R2 both in the absence and presence of hydrogen peroxide. The reaction rate for each condition was 0.25 and 0.56 min−1, respectively. Although the amount of hydrogen peroxide added to the system was not significant, the reaction rate with H2O2 in the system was more than twice that of reaction without hydrogen peroxide, which is significant. Considering this impact can lead to saving money and time for real-life applications.

Figure 8

Kinetic study of the photocatalytic process in optimum conditions ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH0 = 8.3, PUV-C = 15 W).

Figure 8

Kinetic study of the photocatalytic process in optimum conditions ([AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH0 = 8.3, PUV-C = 15 W).

CONCLUSION

According to the experiments, the photocatalytic process under optimal conditions (i.e. [AO7] = 25 mg/L, [ZnO] = 0.2 g/L, pH = 8.3, and UV-C = 15 W) reached 95.6 percent dye degradation after 120 minutes, and after 270, complete degradation of COD was achieved. Since electron-hole recombination is known to decrease the photocatalytic process's efficiency, hydrogen peroxide as an electron acceptor was added at different concentrations to address this issue. Although the optimum concentration selected for hydrogen peroxide was not significant (0.416 mM), it promoted the degradation. It decreased the reaction time by 40 min, which is notable (more than 30% reduction in reaction time) and 0.416 mM was selected as the optimum concentration. H2O2 as an electron acceptor with an optimum concentration of 0.416 mM significantly increased dye removal rate and process efficiency (98.9%) and reduced the reaction time to 80 minutes. This was because of trapping electrons by hydrogen peroxide and preventing hole-electron recombination, thus generating hydroxyl radicals in the reaction solution. The reaction in optimum conditions, both with and without electron acceptor, followed first-order kinetics. However, adding an electron acceptor increased the reaction rate more than two times. It is important to note that adding only a slight amount of hydrogen peroxide contributed to this process modification. Considering this impact when designing a photocatalytic system treatment unit can save time, money, and energy. For future studies, the role of different electron acceptors on the photocatalytic process can be evaluated, and based on the life cycle assessment, and the best one can be selected for practical purposes.

DATA AVAILABILITY STATEMENT

All relevant data are included in the paper or its Supplementary Information.

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