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Article

Iron Sludge-Derived Photo-Fenton Reaction for Laundry Wastewater Effluent Oxidation and Process Optimization into Industrial Ecology Symbiosis

1
Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
2
Department of Physics, College of Science, King Faisal University, Al-Ahsa 31982, Saudi Arabia
3
College of Science and Humanities in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
4
Advanced Materials/Solar Energy and Environmental Sustainability (AMSEES) Laboratory, Basic Engineering Science Department, Faculty of Engineering, Menoufia University, Shebin El-Kom 32511, Egypt
5
Planning & Construction of Smart Cities Program, Faculty of Engineering, Menoufia National University, Menoufia 32651, Egypt
*
Author to whom correspondence should be addressed.
Catalysts 2025, 15(7), 669; https://doi.org/10.3390/catal15070669
Submission received: 20 May 2025 / Revised: 2 July 2025 / Accepted: 5 July 2025 / Published: 10 July 2025
(This article belongs to the Special Issue Advanced Catalytic Processes for Wastewater Treatment)

Abstract

Controlled iron extraction from iron-based sludge (Fe-Sludge) drainage and its use as a Fenton’s reagent is investigated in the current study for eliminating organics from launderette discharge stream. The influences of the iron dosage, hydrogen peroxide concentration, and pH are assessed as treatment factors for their direct impact on the oxidation of organic compounds. Additionally, optimal oxidation conditions are determined using the response surface methodology (RSM) technique, and the ranges of treatment variables are analyzed. The optimum values of a pH of 2.0, Fe sludge concentration of 99 mg/L, and H2O2 content of 402 mg/L resulted in optimal organics removal of up to 98%, expressed as Chemical Oxygen Demand (COD) removal. The oxidation efficacy attained from the design is confirmed and the model validation is assessed, and the suggestive model is accepted since it possesses a correlation coefficient of 97.7%. The thermodynamic and kinetic models are also investigated, and the reaction showed that the temperature increases resulted in the oxidation efficiency being reduced. The oxidation efficiency expressed as COD reduction is clearly characterized by first-order reaction kinetics. The thermodynamic characteristics indicated that the oxidation reaction was exothermic and not spontaneous.

Graphical Abstract

1. Introduction

Due to modernization and technical advances, the amount of global water essential for industry and domestic needs is incredibly increasing [1,2,3]. But supreme consumed water is transformed into wastewater [4,5]. Therefore, a great volume of wastewater is discharged from both domestic and industrial sectors [6,7,8]. In high-income industrialized feature countries, the perceived indoor domestic water requirement could reach up to 70% of the total urban water demand [5]. Such waters can be categorized as laundry or black water [9,10]. Laundry water is the domestic or commercial wastewater that is not combined with toilet waste and is presented as daily discharge according to human activities [11,12,13,14]. Laundry water comprises leftover water from bathtubs, sinks, showers, dishwashers, and laundry machines, which represent almost 60% of the in-house water demand [15,16].
Launderette wastewater is one of the laundry water types, and its main constituent is detergents; as a result, the water comprises high loads of phosphate and sodium quantities in addition to organic and suspended matters such as oil and grease [17,18]. Thus, this type of wastewater generates major ecological drawbacks, poses a risk to creatures, and causes serious damage to the ecosystem [19]. In this regard, essential treatments and the successful cleaning of such water is required prior to its final discharge into the ecosystem. Also, water reuse is a reliable method to overcome water deficiency [20,21,22]. But selecting an economic and efficient treatment method is a research topic leading many scientists to search for a more effective system. Various conventional techniques, including physical [19,23,24,25,26], biological [27], and chemical [28,29,30] treatments, have previously been used to treat wastewater from toxic materials [14]. Nonetheless, conventional techniques exhibit several limitations, including elevated treatment costs and the potential for merely transforming pollutants from one phase to another without achieving their mineralization [31,32,33,34]. Thus, emerging advanced oxidation processes (AOPs) are a good option for wastewater treatment that could yield harmless end products [35,36].
UV/O3 is a strong oxidizing AOP with high oxidation potential that is used as a homogenous AOP technology for wastewater remediation, whilst O3 generates an indirect complex mechanism besides its high operating cost [37,38,39]. Moreover, titanium dioxide (TiO2), amongst the various types of semiconductors, is gaining much attention in wastewater remediation technology [40,41]. However, according to the literature, such technique could not be signified as an efficient system due the high cost of TiO2. More recently, Fenton systems emerged as AOPs with their complete mineralization ability, but it is essential to enhance them through ultraviolet (UV/Fenton) [42], electro (electro-Fenton) [43,44], and ultrasonic techniques (US/Fenton) [45,46], which makes them remain costly [47]. Thus, determining system modifications is a popular research topic [48,49,50]. Hence, the pursuit of cost-effective sophisticated treatments may facilitate greater water management in a sustainable manner [51].
Ultimately, among the available and simple-to-manage AOPs, the Fenton reaction has been proven as a promising technology and has been vastly applied over the past two decades due to its rapid oxidation and efficient mineralization [50,52,53]. Using Fenton-based iron catalysts produced from natural or waste resources is a promising approach to deal with pollutants from aqueous discharge in a cost-effective manner as well as to achieve industrial–ecological symbiosis [39,40]. Moreover, such treatment could meet the water reclamation criteria in simple managing facilities [41]. The efficiency of this procedure relies on the generation of robust hydroxyl radicals (˙OH) and the oxidation of Fe2+ to Fe3+. Both Fe2+ and Fe3+ ions serve as coagulants; thus, the Fenton reaction can perform dual functions, namely oxidation and coagulation, in wastewater treatment operations.
On the other hand, wastewater from mining areas is still highly contaminated with pyrite. Globally, wastewater streams contaminated with heavy metals represent a significant environmental hazard. In addition to their natural presence, heavy metals can infiltrate the environmental system via mining operations [45]. While metal extraction and mining activities provide a high contribution to the worldwide economy, they cause severe damage to the aquatic environment through freshwater pollution [46]. Global wastewater streams contaminated with heavy metals represent a significant environmental hazard [12,47]. Such water is oxidized due to atmospheric oxygen to form ferric ions [48,49,50]. Thus, water loaded with ferric ions should be eliminated prior to final disposal [51]. According to the author’s understanding and published data, there is a gap in the literature about the use of mine wastewater as a photocatalyst in the Fenton reaction system [52]. Hence, using waste iron sludge to treat another aqueous effluent with a photo-oxidation technique is a relatively novel trend in achieving sustainability goals.
Hence, the current study is based on the introduction of a Fenton system to cope with organics from launderette wastewater as a win–win strategy. Unavoidable iron sludge (Fe sludge) from mining is introduced as a cost-effective photo-Fenton treatment source. Response surface methodology (RSM) is a numerical optimization technique that applies mathematical and statistical principles to describe and optimize parameters in multi-effect systems. The kinetic order and thermodynamic variables are eventually evaluated using experimental results.

2. Results and Discussion

2.1. Comparative Oxidation Systems and Operating Time

The oxidation of organics in launderette wastewater using a photo-Fenton reaction with a Fe sludge catalyst activated by H2O2 was analyzed and compared to other standalone treatment methods. The pristine treatment systems named Fe sludge, H2O2, Fenton, and photo-Fenton reactions are evaluated. According to the experimental data displayed in Figure 1, the organics concentration assessed through the COD reduction declined rapidly with the oxidation time. After 60 mins, COD reduction only reached 30, 25, and 40% for the Fe sludge, H2O2, and Fenton systems, respectively, whereas it reached 96% when the photo-Fenton reaction was applied. It is noteworthy that a rapid reaction occurred in the initial oxidation time, and then the COD% slowly declined with time. As a result, 60 min was determined to be the system’s optimal reaction time. The high quantity of organics in the wastewater at the start of the reaction causes an increase in the oxidation rate. As a result, both direct and free radical oxidation occur at overly high levels during the early stages of the process.
When comparing pristine systems for organics oxidation and the dual treatment, it was found that the dual treatment is more efficient. This might be demonstrated by the fact that the formation of ˙OH radicals is significantly higher in the dual treatment compared to when only solo oxidation systems are used. Consequently, the intensity of ˙OH radicals created in the reaction medium is insufficient for organics oxidation and removal. Furthermore, it is significant to note that the presence of UV radiation is likely associated with the production of ˙OH radicals, as evidenced by the increased accumulation of ·OH radicals resulting from UV illumination, which initiates a greater yield of ˙OH and consequently enhances the oxidation rate [18].

2.2. Fenton’s Multiple Parameters (Fe-Sludge, H2O2, and pH Effect)

  • Fe Sludge
The breakdown of H2O2 in the presence of an Fe sludge catalyst generates strong oxidative radicals (˙OH radicals), which are primarily responsible for the oxidation process via sequential reactions (Equations (1)–(3)) [22]. In this regard, variation in the catalyst concentration as well as H2O2 dosage might affect the oxidation yield. Thus, the effect of the catalyst concentration in the range of 20 to 200 mg/L, while keeping the other parameters constant (H2O2 400 mg/L and pH 3.0), is assessed in order to investigate the maximum COD reduction efficiency.
F e 3 + + H 2 O 2 F e 2 + + O H 2 ˙ + H +
F e 3 + + O H 2 ˙ F e 2 + + O 2 + H +
F e 2 + + H 2 O 2 F e 3 + + O H + O H ˙
Figure 2 shows a series of experiments used to evaluate the different Fe sludge concentrations. As exhibited in Figure 2, the elimination of COD increases with the augmentation of the catalyst concentration from 20 to 100 mg/L, achieving a 96% decrease in oxidized organics. However, the continued increase in this reagent causes a reduction in oxidation efficiency by up to 100 mg/L. This may be linked to the detrimental effects of an elevated iron concentration in the aqueous reaction media as the additional iron species in the solution impedes the efficacy of ˙OH radicals, as demonstrated in Equations (4) and (5) [44]. Thus, 100 mg/L is recognized as the optimal catalyst concentration required for the oxidation of organic compounds. Prior investigations verified this trend that was observed in the treatment of several types of wastewaters using Fenton oxidation [13].
F e 2 + + O H ˙ F e 3 + + O H
F e 2 + + O H 2 ˙ F e 3 + + O H 2
  • H2O2 concentration
Figure 3 illustrates the oxidation of organics through COD reduction at different concentrations of 100, 200, 400, and 800 mg/L of H2O2. The catalyst concentration was maintained at 40 mg/L, with the pH held at 3.0. The elimination of COD rose from 58% to 96% as the H2O2 dosage escalated from 100 mg/L to 400 mg/L, respectively. The increase in H2O2 dosage is anticipated to achieve a high output of ˙OH radicals, subsequently resulting in an elevated oxidation rate of organic COD. Nonetheless, a rise in reagent concentration beyond 400 mg/L leads to a decrease in organic oxidation, as indicated by COD reduction. This may be associated with the extra H2O2 disrupting the generation of ˙OH radicals, hence diminishing the oxidation of organic compounds. Overall, there is a reduction in the ˙OH species beyond such limiting point, which may be attributed to the preferential reactivity between the peroxide (H2O2) reagent and ˙OH radicals rather than their generation. This reaction produces additional species, specifically HO2 radicals (Equation (6)) [28]. The HO2 species are characterized as being less reactive than the ˙OH species, therefore indicating a minimal contribution to the oxidation reaction [43]. Additionally, the newly generated HO2 radicals can interact with the residual ˙OH radicals, as seen in Equation (7). This analysis aligns with the findings documented in the literature [8,22].
H 2 O 2 + H O ˙ H O 2 ˙ + H 2 O
H O 2 ˙ + H O ˙ H 2 O + O 2
  • pH
Prior research data [41,42] indicate that effluent pH significantly influences the production of ˙OH radicals, hence impacting the total yield of the photo-Fenton oxidation cycle. Therefore, this study significantly examines such pH effect. The impact of the initial effluent pH on the oxidation potential of organics utilizing an Fe sludge-modified photo-Fenton reaction is analyzed across a pH spectrum from acidic (3.0) to alkaline (8.0), with the experimental results exhibited in Figure 4.
The data indicates that pH significantly affects the Fe sludge-modified photo-Fenton oxidation reaction, especially under acidic conditions. Figure 4 illustrates that COD removal increased from 57% to 96% as the pH value was modified from the original value of 8.1 to 3.0. The underlying cause of this tendency is that Fe sludge-based photo-Fenton reactions behave differently at varying solution pHs due to the formation of ˙OH radical species. This indicates that the speciation of Fe sludge and the breakdown of H2O2 are influenced by pH levels. Additionally, according to the previous work available in the literature [33,52], the rate of ˙OH radicals’ generation is strongly improved at the acidic pH medium.

2.3. Experimental Box–Behnken Design

  • Regression model fitting
RSM was applied to determine the optimum reaction parameters for the most significant operational variables in the suggestive Fe sludge-based photo-Fenton reaction, including the catalyst concentration, hydrogen peroxide dose, and pH. The specified matrix illustrating the Box–Behnken design is presented later in Table 1. The average of the triplicate experimental COD removal (%) responses of the treated water is systematically arranged and compared with the anticipated model delineated by the polynomial equation (Equation (8)).
The second-order model equation is presented in coded levels and describes the coded variables for COD elimination (Equation (8)). All model parameters, including the sum of squares (SS), mean squares (MS), estimated coefficients, standard errors (SEs), and the associated F-values and p-values, were assessed using an ANOVA (analysis of variance) t-test. The ANOVA parameters are presented in Table 1. Statistically, a model is determined to be positively suggestive when it attains a high value superior to the unity of the F-value with a minimal p-value that is less than 0.005. Moreover, the fitness of the model is also evaluated by the high magnitude of the regression coefficient (R2), which is acceptable when it is greater than 80% [21,26]. Generally, the quality of the model is well fitted, and the model is accepted when the regression coefficient (R2) is suggested to be at least 80% [4].
ζ % = 84.66 + 1.93 ε 1 2.95 ε 2 14.36 ε 3 22.34 ε 1 2 3.024 ε 1 ε 2 + 13.7 ε 1 ε 3 36.22 ε 2 2 5.11 ε 2 ε 3 14.73 ε 3 2
  • Statistical ANOVA testing
The determination coefficient (R2 = 97.7%) displayed in Table 2 indicates that the derived quadratic model is appropriate, signifying that 97.7% of the variability in the proposed response (COD, %) is accounted for. Furthermore, the ANOVA test value reveals a strong association between the response variable and the independent parameters. Moreover, the comparison of the experimentally derived values with the anticipated responses for COD removal efficiency reveals a robust association, as depicted in Figure 5.
A response surface analysis assists in determining the type of interactions between the suggestive parameters. In this regard, the 3D response surface and its corresponding 2D contour plots of CDO removal are presented in Figure 6, Figure 7 and Figure 8 for the three couples of parameters in terms of their coded levels. According to Figure 6, Figure 7 and Figure 8, the COD removal efficiency was steadily enhanced with the enlarged modified photo-Fenton reagent doses for both Fe sludge and hydrogen peroxide, as seen in Figure 6 and Figure 7 for 3D (A) and 2D (B) plots. The main motivation behind such trend is linked to the highly oxidizing intermediate ˙OH radicals in the medium, which are amplified with the reagent’s concentrations. But at a specific catalyst concentration and after a certain limit, COD removal is reduced. The reason for this could be related to the catalyst concentration being higher than the optimal level, acting as a ˙OH radical scavenger rather than a generator. Additionally, as can be seen from the figures (Figure 7 and Figure 8 for 3D (A) and 2D (B) plots), the COD reduction efficiency is extremely highly sensitive to the pH alteration in comparison to the other examined variables. Such data is verified and in accordance with the ANOVA results of probability values of the p-values.
In summary, to identify the optimal values of independent variables, a numerical optimization technique utilizing Mathematica (V 5.2) is employed. The primary objective of this optimization is to reduce the last COD concentration of laundry water as an indicator of organic oxidation. The maximal estimated COD removal is 98% at a photo-Fenton catalyst dosage of 99 for Fe sludge and 402 for H2O2, achieved at an ideal pH of 2.0. Additionally, to assess model appropriateness, supplementary duplicate experiments are performed utilizing the suggestions for validation through experimental trials. The experimental COD removal percentage under ideal conditions is 98%, indicating a satisfactory correlation with the projected COD percentage. Consequently, the Box–Behnken design identified the ideal prediction, which is corroborated by the trials, underscoring that the system is an effective instrument for maximizing COD oxidation from laundry wastewater.

2.4. Temperature Influence, Kinetics, and Thermodynamic Investigations

Next, optimizing the influencing Fenton parameters, the second set of experiments deals with the temperature effect assessment. Such investigation might involve studying its effect on the overall reaction kinetics and calculating the Arrhenius-type dependency of such kinetic constant model. In this regard, the effect of temperature on the COD organics oxidation of laundry water using the photo-Fenton oxidation reaction (using 40 mg/L of Fe sludge catalyst and 400 mg/L of H2O2 at 3.0 pH) is studied by varying the operating temperature from room temperature to 60 °C. The data displayed in Figure 9 shows a negative impact of organics removal through COD reduction (%) with a rising temperature.
The COD removal efficacy declines from 96% to 82% as the temperature increases from 32 to 60 °C. Thus, higher operating temperatures restrict the reaction from being completed efficiently. This may be ascribed to the enhanced production of ˙OH radicals at low temperatures. It is noteworthy that an efficient oxidation rate at a minimal temperature may be explained by the increase in temperature accelerating the decomposition nature of hydrogen peroxide as the initiator and oxidizing agent in the photo-Fenton test onto O2 and H2O. Consequently, the hydrogen peroxide reagent in the reaction medium acts as a ˙OH free radical scavenger instead of a generator [43]. Accordingly, overall, the COD oxidation rate in laundry wastewater is reduced. Previous investigators [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,54] have reported using various types of wastewaters and provided experimental evidence of the need to determine the effect of catalytic oxidation on temperature.
The photo-Fenton process is characterized by complex reactions in nature as it involves many reactive species and the simultaneous occurrence of oxidation and coagulation processes. Consequently, the assessment of photo-Fenton reaction kinetics is complex [52]. Thus, to study this test, the overall COD oxidation value is used for the evaluation of the reaction’s kinetics. The experimental data obtained from oxidation at different operating temperatures of 32, 40, 50, and 60 °C are utilized to calibrate the reaction kinetics models of zero-, first-, and second-order, and the corresponding kinetic constants (ko, k1, and k2) are assessed. Table 2 presents the regression coefficients (R2) for each model, utilized to determine the most suitable kinetic sequence that aligns with the experimental data. The data shown in Table 2 indicates that the process predominantly adheres to first-order kinetics. This conclusion aligns with the previously documented literature examining homogenous Fenton systems for the treatment of polluted water [51].
To fully understand the photo-Fenton reaction, thermodynamics based on the first-order kinetics model is assessed. The first-order rate coefficients are characterized as a function of temperature by the use of the Arrhenius equation. The temperature dependency of the kinetic factors of the photo-Fenton reaction is evaluated via Equation (9). Additionally, the additional thermodynamic parameters, including the Gibbs free energy (∆G′), enthalpy (∆H′), and entropy (∆S′) for the system, are obtained using Equations (10)–(12) [55]:
k 1 = A e ( E a R T )
G = R T l n k 1
H = E a R T
S = ( H G ) / T
where A is the Arrhenius constant, T is the laundry water temperature, Ea is the activation energy of the photo-Fenton reaction, and R is the universal gas constant. The thermodynamic variables attained from such equations for COD oxidation in laundry water using a photo-Fenton reagent are tabulated in Table 3.
The results listed in Table 3 elucidate that the changes in the ∆G′ value are in a positive range, which signifies the possibility of the oxidation process meeting non-spontaneity criteria. Furthermore, the positive results of the ∆H′ reaction reveal the exothermic nature of oxidation. Additionally, the negative values of ∆S′ verify the non-spontaneity of the system. Such data confirms the reduction in the degree of freedom of COD oxidation in the treated laundry wastewater and thereby supports a high oxidation yield. In addition, the data recorded in the table exhibits that COD oxidation via the photo-Fenton reaction could predictably progress with minimal energy levels (36.99 kJ/mol). Previous reports in the literature support such an investigation [56,57].

2.5. Catalyst Stability Investigation

To investigate the effect of catalyst sustainability and stability, the recovery and reuse of Fe sludge are assessed, and the data is illustrated in Figure 9. Initially, the material is collected after use and subjected to filtration for recovery; thus, it is exposed for regeneration with three successive replicates of washing with distilled water to eliminate any organic molecules within the material. Subsequently, the Fe sludge is tested using five cycles of oxidation through a Fenton reaction. As exhibited in Figure 10, the organics removal efficiency in terms of COD is changed from 98% to 75%. But it is noteworthy that the substance is maintained well since the removal efficiency is still above 60% after five cycles of oxidation compared to 98% when using fresh Fe sludge. This verifies that material sustainability is an ideal candidate for launderette wastewater in aqueous effluent treatment applications. Also, it is essential to confirm that the material can achieve a win–win situation since it treats other wastes even through cyclic use.

2.6. Error in COD Values of Launderette Wastewater Due to H2O2

Commonly, it is known that H2O2 reagent interferes with COD analysis by consuming oxidation agents, i.e., potassium dichromate, thereby leading to the overestimation of the measured COD values [25,57,58]. In this regard, the real COD values were determined by correlating the extent of overestimation with the concentration of H2O2 present during treatment. Various concentrations of hydrogen peroxide reagent were added to the wastewater in the range of 50–800 mg/L, and the COD of the samples was measured; the comparative estimated data is displayed in Figure 11. The results exhibited in Figure 11 show that the increase in COD for the sample embedded with hydrogen peroxide is larger than the solo wastewater samples without hydrogen peroxide. It is also noteworthy that the variation is related to the amount of hydrogen peroxide added since the increase in the amount of added H2O2 to launderette wastewater results in a higher variation in the COD value. Thus, the COD overestimation is proportional to the amount of H2O2 in wastewater. ΔCOD was in a low range when 50 to 400 mg/L of hydrogen peroxide was used (0.31 to 0.59 mg-COD/L for every 1 mg/L of hydrogen peroxide), whereas a ΔCOD value of 0.88 was observed for every 1 mg of hydrogen peroxide when 800 mg/L of such reagent was added to wastewater. Such data verifies that the residual hydrogen peroxide reacts with the potassium dichromate in the COD reagent, as determined through the COD evaluation [59]. The magnitude of interference found in such experiments is about 30% and depends on the hydrogen peroxide in the studied range. Also, it is essential to mention that according to the data in Figure 3, the COD reduction decreases when the amount of hydrogen peroxide added is increased to 800 mg/L in the case of the Fenton reaction when it is augmented with the catalyst. This verifies the role of the Fenton reaction in the COD reduction that should be in the optimal value (400 mg/L). Hence, the effect of the Fenton reaction is more pronounced in the COD reduction compared to the solo addition of hydrogen peroxide. More research is required to investigate how the residual hydrogen peroxide oxidant might affect the COD measurement in various concentrations in order to develop correction methods for an appropriate interpretation of the data.
Notably, a COD analysis was conducted immediately after hydrogen peroxide addition in the launderette wastewater samples. But the combination of hydrogen peroxide and Fe sludge led to the generation of the Fenton reaction. Also, it is essential to mention that the presence of Fe sludge in the sample consumed a certain amount of hydrogen peroxide, and the variation in the COD results is diminished and could be neglected. However, further research is required to ensure that the remaining hydrogen peroxide is present after oxidation occurs.

3. Experimental Procedure

3.1. Laundry Wastewater and Fe Sludge

Launderette wastewater was collected and sampled from a local launderette facility, and the effluent was rich with organics and powder detergent. The powder detergent comprises three main ingredients, including pH control/salts, water softeners, and surfactant cleansers. The main chemical composition of the detergent includes small amounts of alcoholethoxylate, citric acid, disodium disilicate, and 2-propenoic acid, 2,5-furandione polymer, which are each present in the range of 1 to 5%; along with about 25% of sodium carbonate; 8% of sodium carbonate peroxide; and 10% of linear alkyl benzene sulfonates. Thus, the launderette wastewater contains these residual laundry agents. The effluent used in this study was transferred to the laboratory after being collected and kept at 4 °C according to standard methods [25]. Physiochemical properties of this effluent were analyzed according to the standard methods of examining water [25] and wastewater, and the laundry wastewater was loaded with suspended solids at a concentration of 97 mg/L and had a Chemical Oxygen Demand (COD) of 1341 mg-COD/L with pH 8.1.
Also, mining discharge sludge (Fe sludge) was collected from the mining industry and analyzed, and its iron content was 2879 mg-Fe/L with a pH of less than 3.0. Furthermore, the contents of elements in the sludge were characterized; the retained Fe sludge contained four main elements, namely O, Al, Si, and Fe, and the data are exhibited in Figure 12. It is worth mentioning that according to the data in the inset of Figure 12, the Fe content of more than 33% represents the highest metal content, which facilitates the oxidation reaction and is thereby the cause of the reduction in the pollutant’s efficiency. The presence of Al supports the catalytic reaction of the Fenton process since it also helps in the oxidation process [4]. This iron-based sludge (Fe sludge) serves as a source of iron to facilitate the Fenton reaction.

3.2. Oxidation System

An amount of 100 mL of launderette wastewater was poured into a 250 mL glass beaker to prepare for the jar test. Subsequently, the pH was adjusted (when needed) to a specific value, the iron sludge was added, and the oxidation reaction was initiated by the addition of H2O2 reagent; thus, the mixture was exposed to stirring for the experiment. The pH of the solution was monitored and altered to the desired values through the use of H2SO4 or NaOH (Sigma-Aldrich, St. Louis, MO, USA) with a digital pH meter (AD1030, Adwa Instrument, Szeged, Hungery). An ultraviolet (UV) source of 253.7 nm wavelength with a power of 15 W was used to conduct the ultraviolet photo-Fenton reaction by emitting UV light. The lamp was encased in a protective silica tube jacket, allowing UV light to permeate the wastewater solution. The sleeved UV light was submerged in the wastewater reservoir containing the solution. Afterwards, the samples were periodically taken and successively filtered using a micro-filter prior to analyses. The organics were measured in terms of COD via the use of a Lovibond Checkit direct COD photometer. Also, to assess the thermodynamic characteristics, oxidation was carried out at different temperatures ranging from RT to 60 °C. All experiments were carried out in triplicate. A schematic illustration of the experimental set-up is displayed in Figure 13.

3.3. Factorial Design and Statistical Validation

A Box–Behnken design, utilizing a 3-level factorial approach with triplicates of the central values, was employed to comprehensively evaluate the influence of major independent parameters on the oxidation of organics, quantified as COD (%), the dependent parameter. The selected independent parameters were identified based on the most significant elements in the photo-Fenton process, which are described below: (i) the level of H2O2; (ii) the level of Fe sludge; and (iii) the pH measurement. The values and levels of independent parameters, as determined by preliminary tests that informed the selection of each Box–Behnken factor, are presented in Table 4.
The complete factorial Box–Behnken experimental design matrix of 15 runs was consistent with the statistical analysis software (SAS Institute, Inc., SAS v.6.06, Cary, NC, USA, 1990) [50]. The detailed design matrix in the study is tabulated in Table 5 as coded parameters. The experimental data were analyzed using the RSM system to fit the following second-order empirical polynomial model that was developed in correlation with the response:
ζ = β o + Σ β o ε i + Σ β i i ε i 2 + Σ Σ β i j ε i ε j
SAS and Matlab (version 7.11.0.584) were utilized for statistical and graphical representations. Additionally, the ANOVA (analysis of variance) test was employed to evaluate the impact of the statistical demonstration.

4. Conclusions

A photo-Fenton system based on iron sludge waste was identified as a viable and cost-effective photo-oxidation system and was utilized to treat laundry wastewater, which is a real pollution source. COD is used as an indication criterion of the oxidation of organics in such wastewater to evaluate the treatment efficiency. The experimental results revealed that the system is sensitive regarding the operating parameters, including hydrogen peroxide, catalyst, and pH. The best operating conditions of such parameters were determined via the use of a numerical design using the response surface methodology (RSM) technique. The optimal values were recorded as pH 2.0 with reagent concentrations of 402 and 99 mg/L of H2O2 and catalyst, respectively. The experimental and predicted responses show a high correlation coefficient, corresponding to 97.7%, which verifies the adequacy of the proposed model. Finally, the kinetics and thermodynamics parameters were investigated and revealed that the reaction follows the first-order model and is exothermic and non-spontaneous in nature. Such data needs a full-scale investigation to be verified. Also, the material’s recyclability was verified, meaning it is sustainable. Not only does the current study present a potential method for laundry wastewater oxidation, but it also provides a way to realize the resource valorization of Fe sludge as a by-product of mining processes to fulfill the goal of industrial ecology. However, the process can be made more economic, and the technology’s potential in real applications when utilizing renewable solar energy as an activation source should be tested.

Author Contributions

All authors (A.B.G.T., F.H.A., S.A.M., A.F.A.N., A.A., N.R., M.M.N. and M.A.T.) designed and performed the experiments, analysis, and calculations and helped shape the research and the final manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU251877]. This work was also supported by Princess Nourah bint Abdulrahman University Researchers supporting project number PNURSP2025R223, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Also, this work was supported by Prince Sattam bin Abdulaziz University for funding this research work through the project number 2025/R/1446.

Data Availability Statement

All data generated or analyzed during this study are included in this published article.

Acknowledgments

The authors express their gratitude to Princess Nourah bint Abdulrahman University Researchers supporting project number PNURSP2025R223, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through the project number 2025/R/1446. This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU251877].

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Effect of reaction time on different systems for launderette wastewater oxidation.
Figure 1. Effect of reaction time on different systems for launderette wastewater oxidation.
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Figure 2. Influence of Fe sludge catalyst (H2O2, 400 mg/L; pH 3.0) on COD removal from laundry wastewater.
Figure 2. Influence of Fe sludge catalyst (H2O2, 400 mg/L; pH 3.0) on COD removal from laundry wastewater.
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Figure 3. Influence of H2O2 (Fe sludge, 40 mg/L; pH 3.0) on COD removal from laundry wastewater.
Figure 3. Influence of H2O2 (Fe sludge, 40 mg/L; pH 3.0) on COD removal from laundry wastewater.
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Figure 4. Influence of pH (H2O2, 400 mg/L; Fe sludge catalyst, 3.0400 mg/L) on COD removal from laundry wastewater.
Figure 4. Influence of pH (H2O2, 400 mg/L; Fe sludge catalyst, 3.0400 mg/L) on COD removal from laundry wastewater.
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Figure 5. A Box–Behnken response surface design illustrating the relationship between the actual experimental responses and predicted responses (the red dashed line is y = x).
Figure 5. A Box–Behnken response surface design illustrating the relationship between the actual experimental responses and predicted responses (the red dashed line is y = x).
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Figure 6. Graphical representations of the Box–Behnken design for the percentage of COD removal from laundry water as a function of (A) the three-dimensional surface and (B) two-dimensional contour graphic of the coded Fe sludge and H2O2 concentrations.
Figure 6. Graphical representations of the Box–Behnken design for the percentage of COD removal from laundry water as a function of (A) the three-dimensional surface and (B) two-dimensional contour graphic of the coded Fe sludge and H2O2 concentrations.
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Figure 7. Graphical representations of the Box–Behnken design for the percentage of COD removal from laundry water, depicted as (A) a 3D surface plot and (B) a 2D contour plot, based on the coded concentrations of H2O2 and pH levels.
Figure 7. Graphical representations of the Box–Behnken design for the percentage of COD removal from laundry water, depicted as (A) a 3D surface plot and (B) a 2D contour plot, based on the coded concentrations of H2O2 and pH levels.
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Figure 8. Graphical representations of the Box–Behnken design for the percentage of COD removal from laundry water as a function of (A) the three-dimensional surface and (B) the two-dimensional contour graphic of the coded Fe sludge concentration and pH.
Figure 8. Graphical representations of the Box–Behnken design for the percentage of COD removal from laundry water as a function of (A) the three-dimensional surface and (B) the two-dimensional contour graphic of the coded Fe sludge concentration and pH.
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Figure 9. Temperature effect on COD removal from laundry wastewater (H2O2, 400 mg/L; Fe sludge catalyst, 3.0400 mg/L).
Figure 9. Temperature effect on COD removal from laundry wastewater (H2O2, 400 mg/L; Fe sludge catalyst, 3.0400 mg/L).
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Figure 10. Regeneration for successive use of Fe sludge composite.
Figure 10. Regeneration for successive use of Fe sludge composite.
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Figure 11. COD variation in measurements under different combinations of H2O2 with launderette wastewater.
Figure 11. COD variation in measurements under different combinations of H2O2 with launderette wastewater.
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Figure 12. Elemental analysis of Fe sludge.
Figure 12. Elemental analysis of Fe sludge.
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Figure 13. Schematic representation of experimental technique.
Figure 13. Schematic representation of experimental technique.
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Table 1. ANOVA test for COD reduction model regression analysis using modified Fe sludge-based photo-Fenton oxidation.
Table 1. ANOVA test for COD reduction model regression analysis using modified Fe sludge-based photo-Fenton oxidation.
Source of VariantDegrees of FreedomSSMSF-Valuep-Value
Regression99335.0721037.2324.181080.001331
Linear31745.853871745.8538740.7013110.700913
Quadratic32631.56612631.566161.3500390.407857
Cross Product35767.43845767.4384134.4570.187558
Error5214.471442.89429
Total149549.544
Table 2. Comparison of different kinetic models for laundry water oxidation using modified photo-Fenton process.
Table 2. Comparison of different kinetic models for laundry water oxidation using modified photo-Fenton process.
T (°C)0-Order Reaction *1st-Order Reaction **2nd-Order Reaction ***
ko
(min−1)
t1/2 (min)R2k1
(min−1)
t1/2 (min)R2k2, (L·mg−1min−1)t1/2 (min)R2
3211.5857.910.770.03940.760.940.00023.730.66
4011.6857.410.970.01426.650.970.0000710.650.78
5017.7837.720.920.02649.570.960.0000174.570.95
6014.5546.080.930.01717.760.980.0000324.850.87
* ( d c d t ) = k o , ** ( d c d t ) = k 1 C , *** ( d c d t ) = k 2 C 2 where C is the COD of laundry water.
Table 3. Thermodynamic properties of laundry water oxidation using modified photo-Fenton process.
Table 3. Thermodynamic properties of laundry water oxidation using modified photo-Fenton process.
Thermodynamic ParametersTemperature (°C)
32405060
∆G′ (kJmol−1) 82.9286.9689.8294.61
∆H′ (kJ mol−1)34.4634.3934.3134.22
∆S′ (J mol−1)−158.87−167.95−171.87−181.32
Ea (kJ mol−1)36.99
Table 4. Behnken design of coded levels and natural independent parameters for launderette wastewater oxidation.
Table 4. Behnken design of coded levels and natural independent parameters for launderette wastewater oxidation.
Experimental FactorSymbolCoded Levels
LowMiddleHigh
NaturalCoded−101
H2O2 concentration (mg/L) E 1 ε 1 350400450
Fe sludge concentration (mg/L) E 2 ε 2 80100120
pH E 3 ε 3 234
Table 5. Box–Behnken design matrix of Fenton reaction for assessing RSM describing influence parameters of launderette wastewater oxidation.
Table 5. Box–Behnken design matrix of Fenton reaction for assessing RSM describing influence parameters of launderette wastewater oxidation.
Run No.Codified VariablesNatural Variables
E1E2E3 ε 1 ε 2 ε 3
1−1−10350803
2−1103501203
31−10450803
41104501203
50−1−1400802
60−11400804
701−14001202
80114001204
9−10−13501002
1010−14501002
11−1013501004
121014501004
130004001003
140004001003
150004001003
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Trabelsi, A.B.G.; Alkallas, F.H.; Mansour, S.A.; Al Naim, A.F.; Alshoaibi, A.; Rekik, N.; Nour, M.M.; Tony, M.A. Iron Sludge-Derived Photo-Fenton Reaction for Laundry Wastewater Effluent Oxidation and Process Optimization into Industrial Ecology Symbiosis. Catalysts 2025, 15, 669. https://doi.org/10.3390/catal15070669

AMA Style

Trabelsi ABG, Alkallas FH, Mansour SA, Al Naim AF, Alshoaibi A, Rekik N, Nour MM, Tony MA. Iron Sludge-Derived Photo-Fenton Reaction for Laundry Wastewater Effluent Oxidation and Process Optimization into Industrial Ecology Symbiosis. Catalysts. 2025; 15(7):669. https://doi.org/10.3390/catal15070669

Chicago/Turabian Style

Trabelsi, Amira Ben Gouider, Fatemah H. Alkallas, Shehab A. Mansour, Abdullah F. Al Naim, Adil Alshoaibi, Najeh Rekik, Manasik M. Nour, and Maha A. Tony. 2025. "Iron Sludge-Derived Photo-Fenton Reaction for Laundry Wastewater Effluent Oxidation and Process Optimization into Industrial Ecology Symbiosis" Catalysts 15, no. 7: 669. https://doi.org/10.3390/catal15070669

APA Style

Trabelsi, A. B. G., Alkallas, F. H., Mansour, S. A., Al Naim, A. F., Alshoaibi, A., Rekik, N., Nour, M. M., & Tony, M. A. (2025). Iron Sludge-Derived Photo-Fenton Reaction for Laundry Wastewater Effluent Oxidation and Process Optimization into Industrial Ecology Symbiosis. Catalysts, 15(7), 669. https://doi.org/10.3390/catal15070669

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