Optimization and modeling of solar photocatalytic degradation of raw textile wastewater dyes using green ZnO-ED NPs by RSM

Wastewater-containing dyes from the textile, paper, and paint industries have attracted great attention due to their harmful impacts on human well-being and the environment since 10–15% of the dyes are discharged into natural water resources (Maruthupandy et al. 2020). Treatment of dye wastewater by physical, chemical, and biological methods has many limitations, such as high costs and frequent ineffectiveness (Alharthi et al. 2021; Shindhal et al. 2021). There is much interest in advanced oxidation processes (AOPs), such as the photocatalytic destruction of dyes, because of its green, sustainable, low-cost, and high-efficiency technology that achieves almost total mineralization of organic pollutants such as dyes (Raizada et al. 2020). Using various catalysts (TiO₂, MnO₂, CuO, ZnO, etc.), external oxidants (H₂O₂, air, O₃, persulfate, etc.), and additives (NaCl, surfactants, etc.) can significantly increase the efficiency of accelerating the degradation process when employing AOPs (Mohod et al. 2023). One of the key substances found in the raw textile wastewater matrix during AOPs is carbonates, which promote the breakdown of several newly emerging organic contaminants, such as dyes and drugs (Rayaroth et al. 2023). The high band gap of semiconductors makes them unsuitable for use as photocatalysts. Alternatively, ZIF-8/BiFeO₃, BiOBr, and ZnO can be used as new photocatalysts to overcome these limitations. Instead, metal selenides such as polycationic selenides (PCS) can be employed as a photocatalyst for the degradation of dyes (Nawaz et al. 2023). Effective photocatalytic wastewater treatment can be achieved using BiOBr due to its suitable and narrow band structure (Saddique et al. 2023). The ZIF-8/BiFeO₃ photocatalyst manufactured using ultrasonic conversion was reported to completely remove RhB dye in 50 min at pH 5 (Bethi et al. 2023), efficiently treating complex model wastewater. TiO₂ was shown to be a financially viable option for use in TiO₂/UV/H⁠₂O⁠₂ and TiO₂/UV/O⁠₃/H⁠₂O⁠₂ photocatalytic technologies for the effective and quick (100 min) breakdown of volatile organic compounds with notably low chemical concentrations (Fernandes et al. 2019).

ZnO photocatalysts are an excellent option for processing water dyes because they are non-toxic, economically viable, chemically stable, and highly efficient. They also have a broad absorption spectrum and are widely available (Wetchakun et al. 2019). ZnO photocatalysts used in wastewater treatment have disadvantages; the wide band gap and fast recombination of the photo-induced charge carrier restrict their usage (Hernández-Carrillo et al. 2020). These drawbacks create the urgent need to synthesize a new, improved ZnO photocatalyst by tailoring the particle size and modifying the surface area. ZnO nanoparticles manufactured by chemical and physical methods are associated with toxic residues and environmentally harmful compounds (Mohd Yusof et al. 2020). Meanwhile, the green synthesized ZnO nanoparticles have high purity, low cost, large surface area-to-volume ratios, and thermal, electrical, and other characteristics that encourage catalysis.

To enhance different initial operating parameters, including catalyst load, pH, temperature, wavelength, reaction time, and pollutant concentration, as well as effects on photocatalytic efficacy, response surface methodology (RSM) is a useful tool in experimental studies. RSM's central composite design (CCD) has demonstrated exceptional efficiency in determining a model's relationship coefficient (R²), lowering test errors, and guaranteeing data completeness for design, modeling, and process optimization (Garg et al. 2020; Tetteh et al. 2020). As the most popular approach, CCD is used to regulate the optimization parameters and the impact of each independent variable. This approach is considered the primary benefit of this statistical technique (Nasiri et al. 2021). Several studies have obtained the highest deterioration efficiencies using this approach. For example, Yashni et al. (2021) optimized the Congo red (CR) photodegradation using CCD-RSM. The maximum degradation occurred (96%) at CR concentrations of 5–20 mg/L, pH values of 3–11, and ZnO NPs of (0.05–0.2 g). Nur et al. (2019) recorded a fast degradation of methyl orange (MO) degradation efficiency of 86% by using CCD-RSM at (5–11) pH, (0.2–1.0 g) catalyst (CuO/ZnO) dose with (5–30 mg/L) dye. Kee & Wei (2017) recorded the best degradation of MO and methyl green (MG) and real textile wastewater by using ZnO PVP-12.5 at 93.83% of MO, 100% of MG and 94.14% of COD at 2.5 mg/L of MO and 5 mg/L of MG, pH of 6.5 and 240 min. Most previous studies focused on the degradation of textile dyes in aqueous solutions of single dyes. This does not show the actual situation because dyes with similar spectra may behave differently during photodegradation, restricting the possibility of the results being applied to raw samples. Consequently, there remains a need and a research demand for raw textile wastewater for study.

This study aims to determine the finest operating variables for solar photocatalytic degradation (SPD) of raw textile wastewater colors utilizing green ZnO-ED NPs prepared in our previous study (Quan et al. 2023), based on the independent variables such as ZnO-ED NPs (0.1–2 g), pH (4–9), contact time (60–200 min), and textile wastewater concentrations (10–100%) to optimize the SPD activity by the CCD-RSM, and this emphasizes the novelty of this study to fill the gap in research demand on raw textile wastewater and using sunlight available in Malaysia in large quantities throughout the year.

All chemicals employed were of analytical grade. Table 1 lists every substance used in this study.

The synthesis of ZnO-ED NPs from E. dulcis extract and the collection of raw textile wastewater samples was conducted as described in Quan et al. (2023).

ZnO-ED NPs solutions' optical characteristics were examined using a UV–Visible absorption spectrophotometer (HACH, DR6000) between 190 and 1,100 nm in the wavelength range (Sharma et al. 2018). The surface morphology and elemental composition of ZnO-ED NPs were determined using a field emission energy-dispersive X-ray scanning electron microscope (FESEM/EDX; Quanta 450, USA). ZnO-ED NPs were prepared by placing 100% ethanol on 1 g of ZnO NPs on silicon wafers, which were then dried in an oven at 60 °C overnight (Zarrabi et al. 2018). X-ray diffraction (XRD) XRD-7000 (Shimadzu, Japan) was utilized to decide the atomic or nuclear structure of the crystal ZnO NPs samples. ZnO NPs sample was inserted within a 2 × 5 cm measure of foil. Then, place the ZnO NPs foil sample into a purge test holder and squeeze it delicately with a glass slide (Behravan et al. 2019). Attenuated total reflection (ATR) method (Fahimmunisha et al. 2020), using Fourier transform infrared (FTIR) spectroscopy (Nicolet iS50 (Thermo Scientific, USA)). Five milligrams of sample were put on the sample holder and cleaned with acetone. After that, the sample was pressed using a metallic pressing device and scanned to get the IR spectrum. ZnO-ED NPs size distribution and surface morphology were done using non-contact AFM mode (Park System XE-100, Park System Inc, South Korea). The magnetic sample handle was placed over the sample. NX Chains SPM and Smart Scan TM Data Acquisition were used to analyze the collected data (Tan et al. 2017). The ordered and disordered crystal structure of ZnO-ED NPs, using Raman spectroscopy, deposited 1 g of ZnO NPs particles on the glass plate, investigated at 25 ± 2 °C (Bonon et al. 2016).

In this study, the photodegradation of color in the presence of direct solar radiation using ZnO-ED NPs synthesized in E. dulcis extract was optimized using CCD-RSM, Design Expert Software 11, to improve the best operating parameters for color and COD removal. CCD at 3 × 4 × 2 was carried out to test the independent variables that affect the photocatalytic degradation of color and COD. The data were analyzed using ANOVA, and the optimal value of color and COD degradation was represented using a three-dimensional (3D) response surface plot analysis of the variables. The experimental levels of independent variables for color removal are shown in Table 2. There are four independent variables in this study, including ZnO-ED NPs catalyst dosage (x₁: 0.1–2 g), pH (x₂: 4–9), contact time (x₃: 60–200 min), and textile wastewater concentration (x₄: 10–100%) with three points for each factor and two dependent variables, coded as low and high in the central cluster. In total, 30 runs were performed to study the effectiveness of the selected variables on color degradation and COD, as shown in Table 3.

The study examined the linear effects and interactions of independent factors on photocatalysis efficiency with ZnO-ED NPs, using ANOVA and a 3D graphical presentation.

Design Expert 11.1.2.0 version software was used for the optimization, response surface modeling, and statistical analysis. The effect of the four independent variables was investigated by the CCD of 30 sets of experiments, as in Table 3. Data were analyzed using analysis of variance (ANOVA) and the optimal value for color removal and COD were estimated using 3D response surface analysis variables. The highest color degradation efficiency rate at 2 g of ZnO-ED NPs, pH = 7, 10% of textile wastewater concentration, and a contact time of 60 min was 87.34% of color and 100% of COD.

Linear, 2-factor (2F), quadratic, and cubic models were assessed for their ability to predict outcomes with sufficient power levels to choose models and regression equations for color light degradation performance. Concordance was observed for each model. Based on the results presented in Table 4, a quadratic model is proposed in this study as a suitable model for predicting the photodegradation performance of colors with an F-number of 4.22. This is higher than the tertiary model (1.83) and its 2FI model (2.59).

Determination of R² and adjusted R² were used in this study to assess how robust the model is, with a difference of less than 0.2 (Tables 5 and 6). According to the fit statistics, the predicted R² values for color and COD were −0.2376 and –NA had reasonably adjusted R² values of 0.5726 and 0.1745. It was somewhat agreeable, with a difference of 0.3. R² values for color (0.7789) and COD (0.7248). R² becomes more significant when it is near 1 when considering the appropriate value of R², which must be equal to or more than 0.8 (Chaker et al. 2021a). A negatively predicted R² implies that the overall mean may better predict your response than the current model.

Tables 5 and 6 show that R², R² adj, and R² pred for the removal of color were 0.7789, 0.5726, and −0.2376, respectively. R², R² adj, and R² pred for the removal of COD were 0.7248, 0.1745, and NA, respectively. The correlation coefficients were found to be close to each other. This suggests that the regression model explains the connection between the independent variables and the response very well. ANOVA confirmed this study on the quadratic model of color photodegradation, and a quadratic model was proposed.

After evaluation, ANOVA demonstrates the model's validity and statistical significance (p 0.05) (Tables 7 and 8). Since the models' p-values were less than 0.05, the F-values and Prob > F-values for the models and their independent parameters were deemed significant. The F-value of the pattern is 3.77, implying that the pattern makes sense. The probability of such a high F-value being caused by noise is merely 0.76%. Model terms with a p-value of less than 0.0500 are considered significant. C, aB, BD, and C2 are the significant model values in this instance. A value greater than 0.1000 indicates a lack of significance for the model terms. The nonconformity's F-value of 1.89 suggests that it is not very significant. Such a big nonconforming F-value has a 19.66% probability of being caused by noise. A negligible mismatch is a good thing. The F-value of the COD response of 1.32 means that the model has no statistical significance for noise. There is a 38.49% opportunity that such a large F-value will be caused by noise. Furthermore, the probability of noise causing such a high F-value is extremely low (0.01%). Terms with a p-value >0.05 (not significant) in the model were not taken into consideration because they are not required to uphold the model hierarchy (Tetteh et al. 2020).

Figure 3(a) and 3(b) shows the interaction between initial textile wastewater concentration and ZnO-ED NPs loading at constant pH and irradiation time. The effect of ZnO NPs loading on color and COD degradation was statistically significant (p < 0.05) at 0.0076. The highest color degradation efficiency was achieved at 78 and 100% of COD degradation when the initial color concentration was at its lowest of 10% and the ZnO-ED NPs concentration was at its highest of 2 g/L. The color degradation efficiency increased with increasing ZnO-ED NPs loading and decreasing textile wastewater concentration. The rate of degradation of color (78%) and COD (100%) increased as the amount of ZnO NPs increased to the optimum limit (2 g/L of ZnO-ED NPs). This is also due to the increased active sites as ZnO NPs increase (Eskizeybek et al. 2012). The interaction between textile wastewater and ZnO-ED NPs lowers the color and COD photodegradation efficiency caused by the increasing initial concentration of textile wastewater. The higher the concentration of decomposition in the dye textile wastewater, the higher the concentration of the intermediate, and the lower the photocatalytic rate due to the absorption of these materials on the surface of the photocatalyst. These intermediates adsorb on the catalyst surface and reduce the photocatalysis rate (Lam et al. 2012). In Figure 3(a), as the color concentration increased to 50%, the COD removal rate decreased to the minimum due to the increase in intermediates resulting from color degradation. The high COD removal rate at 100% color concentration is due to the low production of intermediates resulting from low color decomposition caused by the obstruction of light penetration and the blockage of the active sites for interaction with the catalyst.

Figure 3(c) and 3(d) shows the effect of initial ZnO-ED NPs loading and exposure time to sunlight. With an initial concentration of 2 g ZnO-ED NPs and an irradiation time of 60 min, the degradation rate reached 79% color and 100% COD. Figure 3(d) shows that the rate of color degradation gradually decreases with increasing duration of solar light irradiation, observed when color degradation progressively decreased as contact duration increased from 60 to 180 min due to the competition between the intermediates produced from decomposition and the reactants for the decomposition time (Dihom et al. 2022). The degradation gradually increased to 60% at 200 min with decreasing catalyst loading ZnO-ED NPs from 2 to 0.1 g/L. When the compound to be degraded is exposed to ultraviolet rays for a long time, the degradation rate will increase as the oxidation process in the existence of hydroxyl radical rises (Malakootian et al. 2019). The optimal ZnO-ED NP loading on the plot is the maximum at 0.1 g/L; the shorter the contact time, the bigger the color degradation efficiency. As mentioned earlier, the reduced color photodegradation of ZnO NPs under high loading occurred because overflow catalysts can prevent light transmission and cause light dispersion (AIK 2018). The COD removal increased with increasing ZnO-ED NPs from 0.1 to 2 g, with a decreasing contact time. Based on the findings of this study, COD and color removal improved by increasing ZnO-ED NPs from 0.1 to 2 g, with little effect on the color concentration.

Figure 3(e) and 3(f) shows 3D surface plots of the relationship between pH values, ZnO-ED NPs, and color and COD photodegradation efficiency rate at constant initial textile wastewater concentration and contact time. The photodegradation efficiency rate of the color increased with the increase in the pH of the solution and the increase in ZnO-ED NPs loadings. The photodegradation efficiency of the color increased with increasing ZnO-ED NPs dose but decreased when ZnO-ED NPs loading exceeded the optimal level because ZnO NPs partially absorb light at high ZnO NPs suspension loading (Dihom et al. 2022). In contrast, OMs photodegradation efficiency increased with decreasing pH, decreasing color contaminant concentration, and increasing amounts of photocatalyst (Abbas & Trari 2021; Chaker et al. 2021a; Rafiq et al. 2021). COD removal increased with increasing ZnO-ED NPs (0.1–2 g) at pH values (6–4). The highest COD photodegradation efficiency rate was achieved at 100%. Based on the findings of this study, COD and color removal improved by increasing ZnO-ED NPs from 0.1 to 2 g, with an increased pH value. This is because the dye has a positive charge at low pH as a result of the adsorption of hydrogen ions (H⁺) in a protonated form and the presence of a catalyst, where the photodegradation rate increases at pH 4–8 (Alsohaim & Aldawsari 2019).

As shown in Figure 3(g) and 3(h), at an initial concentration of 10% solution color and an irradiation time of 60 min, the photodegradation rate reached 78%, with the COD removal percentage increasing as the color concentration decreased and contact time increased. The removal rate of color has dropped significantly with the increase in irradiation period and textile wastewater concentration. The decrease in interaction performance with contact time is due to the consumption of the photocatalyst as a result of competition for degradation between intermediates and starting materials. In addition, the interaction of short chains of aliphatic molecules with OH groups is responsible for the dye's gradual degradation over time (Salama et al. 2021). In contrast, high textile wastewater concentration (100%) and high reaction time (200 min) reduced the degradation rate of color (20%). This could be due to the bulk of dye molecules obstructing light transmission, the sluggish and low formation of active species, and the short interaction period between active species and the molecules in textile wastewater. Consistent with Aik (2018), the degradation of dye percentage achieved 50% of the 10 ppm SSY concentration at 180 min. Furthermore, with an increase in the initial concentration of SSY, the photodegradation rate of SSY decreased significantly, regardless of whether the irradiation time was 60 or 180 min.

The reaction between textile wastewater concentration and pH values is observed in Figure 3(i) and 3(j) for a constant catalyst dose and contact time. The degradation efficiency of the color reached its highest value at 78% when the solution concentration decreased and the pH increased. However, color degradation significantly reduced at low initial concentrations as the pH increased toward a higher pH. This result was studied in experiments with only one parameter at a time, and the maximum photodegradation performance was at pH 4 due to the electrostatic gravitation between the positively charged ZnO-ED NPs at low pH 4–8 and the anionic dyes, which accelerated the photodegradation of the color due to the adsorption some of the hydrogen ions (Alsohaim & Aldawsari 2019). The presence of ions such as carbonate anions in the raw textile effluent matrix promotes the decomposition of several newly emerging organic contaminants, such as phenol derivatives, aniline, bisphenol A, Rhodamine B, acid orange 7, and naphthalene (Rayaroth et al. 2023). However, it was shown that the high initial effluent concentration of the fabric and the low pH reduced the dye degradation efficiency. The COD photodegradation rate increased with an increased initial solution concentration and decreased pH. Similarly, the photocatalysis rate reduced with increasing pH 3–11 from 98.67 to 83.67% at pH 11 (150 mg of ZnO NPs and 5 mg/L of BR51) because ZnO NPs having a positive charge due to their adsorption of hydrogen ions (H⁺). ZnO NPs have a positive charge since they adsorb hydrogen (H⁺) (Gopalakrishnan et al. 2021).

In Figure 3(k) and 3(l), the percentage of color removal was approximately 78% at pH 9 and 60 min contact time. The efficiency of color photolysis increases when pH is increased and contact time decreases. The efficiency of color photodegradation at pH 4 increased with increasing contact time. This may be explained by the anionic dispersion of dyes and the electrostatic gravity of the positively charged ZnO-ED NPs. The longer time results in persistent electrostatic attraction, and the generated active species could decompose color molecules on the surface of ZnO-ED NPs (AIK 2018). In contrast, at high solution pH, the electrostatic repulsion of the deprotonated ZnO-ED NPs and the anionic arrangement of the color hinder the color degradation rate (Vidya et al. 2016; Dihom et al. 2022). The repulsive force makes it difficult for the color to adhere to the surface of the ZnO-ED NPs, regardless of whether the reaction time is long or short. Therefore, the color separation efficiency does not change significantly from 60 to 200 min. Hence, the degradation efficiency of the COD increased to 100%, both at low and high pH values. At the same time, the effect of contact time on color photodegradation performance shows a similar trend regardless of whether the solution pH is low or high.

Additionally, other researchers noticed similarities in the present study's results: as pH decreased, the concentration of dye pollutants decreased, and the dosage of photocatalyst increased, the photodegradation efficiency of color and COD in textile wastewater increased (Abbas & Trari 2021; Chaker et al. 2021a; Rafiq et al. 2021). Similarly, the effectiveness of electro-oxidation (EO) treatment for real textile wastewater employing a Ti electrode coated with RuO₂ (Ti/RuO₂) was investigated; actual COD and color removal values were discovered to be 97.25 and 80.0%, respectively (Kaur et al. 2017). The optimization using RSM for textile wastewater treatment resulted in 82.8, 96.2, and 75.6% efficiencies for COD, color, and TOC removal using the Fenton process (Ilhan et al. 2019).

Moreover, the optimum conditions obtained for color degradation were confirmed in Table 10 and verified by closer laboratory experiments (70.48%), and 98% of COD had a deviation of less than 2.7. This is consistent with previous research showing that RSM makes economic sense for experimental optimization due to its predictive ability and accuracy (Garg et al. 2020; Chaker et al. 2021b).

The external morphologies, functional groups, and thermal decomposition of ZnO-ED NPs photocatalysts after tissue wastewater SPD were studied by FESEM/EDX, AFM, FTIR, and Raman spectroscopy analyses.

The photodegradation process is promising for the degradation of dyes and the improvement of water quality. However, it may produce more toxicity than the parent dyes. Hence, biological evaluation of the toxicity of textile wastewater dyes is required before discharge into water bodies. Tables 11 and 12 show the lengths of shoots and roots (cm) after 5 days for Raphanus sativus (radish) seedlings after exposure to different raw and treated textile wastewater. Compared to untreated samples, most treated samples exhibited a significant increase in germination percentage, average root length, and shoot length. The germination rate of R. sativus seed-treated samples increased from 52.94 to 80.43%, 65.71 to 71.18%, and 62.50 to 72.22% for textile wastewater (10%), textile wastewater (55%), and textile wastewater (100%), respectively. Because the products were created after degradation, poisonous dyes, and other pollutants in untreated wastewater resulted in stronger germination inhibition than in treated wastewater. Aromatic amine degradation is most likely the cause of non-toxic breakdown (Jaison & Sebastian 2023). In conclusion, Tables 11 and 12 show that the roots and shoot lengths of R. sativus seeds in raw and treated textile wastewater do not differ significantly from their germination in water. This ensures less deathly degradation of metabolites in textile wastewater.

The various organics, such as dyes, coupling agents, polishing and coating agents, fabric softeners, anti-wrinkle agents, and cleaning fluids, contribute to the TDS of textile wastewater. Talouizte et al. (2020) showed very high values for the main pollution parameters in Fez, Morocco, and revealed the presence of organic compounds were alkanes, aromatic amines, aromatic carboxylic acids, phthalates, aliphatic carboxylic acids, and linear aliphatic alcohols. GC-MS analysis showed the presence of 3,5-bis (ethoxycarbonyl) benzoic acid (a coloring component of basic dye) and tetracosamethyl-cyclododecasiloxane (a component of fluorescent dye) in raw textile wastewater (Kaur et al. 2017).

Photocatalytic color removal depends on chemicals used in dyeing, with oxidation rates influenced by water matrix elements like salts, metals, and ions. Fe-TNT photocatalyst shows low photodegradation of CR dye in polluted water due to the interference of dissolved organic matter and metals, and it was much higher in deionized water. The decolorization effect was minimal, with iron, aluminum chloride, magnesium sulfate, and sodium carbonate inhibiting decolorization (Zafar et al. 2021).

The degradation of textile dyes begins via the breaking of the C–S⁺ bond by the aggression of OH radicals between the aromatic ring and sulfonate members, also ─N = N─, C─N, or C─C bonds, as well as the decarboxylation. Aromatic intermediates are produced for many textile dyes like aromatic amines or phenolic compounds and then lead to the complete conversion of nitrogen, carbon, and sulfur heteroatoms NH⁺⁴, ⁠, ⁠, and mineralization ions. Lastly, CO₂ and H₂O are produced from the mineralization of aliphatic products (Bhoi et al. 2020). For instance, the CR degradation pathway suggests that the generated azo radical replaced 4,4-dihydroxy biphenyl and 4-amino naphthalene sulfonic acid. Subsequently, the naphthalene alternative was further broken down to replace the dihydroxy with an analog of benzene. By removing the ─NH₂ group as NH₂OH, which may be formed as a result of the synthesis of phenol, the ensuing amino naphthol generates diol. The loss of as sulfuric acid and the vanishing of the azo group as and ions result in the creation of 1,4-naphthalenediol. The oxidation of dihydroxy-substituted naphthalene, followed by the beating of an ethylene molecule, maybe what forms naphthoquinone. The complete mineralization of the dye is ensured by the production of CO₂ (Yashni et al. 2021).

This study investigated the solar photodegradation performance of raw textile wastewater from aqueous solutions using green ZnO-ED NPs as photocatalysts under sunlight irradiation. The CCD-RSM method was used to study the interaction effects between different variables. Based on the results of the ANOVA analysis, achieved a maximum photodegradation efficiency of 87.34% for color and 95.34% for COD with an overall chance of 0.883 under the conditions: pH of 7, 2 g/L of ZnO-ED NPs, and 10% of color concentration at 60 min. The researchers found that the effects of pH value and color concentration on the effectiveness of pollutant removal were plausible, and the suggested models were suitable based on the statistical metrics, such as the R² coefficient (0.78, p < 0.05), coefficient of determination, adjusted R², anticipated R², and sufficient accuracy. The results suggest that the synthesized ZnO-ED NPs can be crucial in raw textile wastewater treatment. They also found that the possibility of reusability of ZnO-ED NPs in the photocatalytic degradation of raw textile wastewater decreased with each cycle in decreasing order. The results demonstrated the detoxification of dyes and their by-products following treatment using phytotoxic assays for evaluating toxicity. The optimal conditions were validated and tested in the laboratory and had less than a 2.7% deviation. This confirms the usefulness of using CCD-RSM to optimize and model photocatalytic degradation processes in textile wastewater treatment.

This research was supported by the Ministry of Higher Education (MOHE) through the Fundamental Research Grant Scheme (FRGS/1/2023/WAB02/UTHM/03/2).

The study's design, proposal development, findings interpretation, statistical analysis, article drafting, and revision before submission, and final manuscript reading and approval were all done by the two authors.

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

The authors declare there is no conflict.