Optimizing Fenton-like process, homogeneous at neutral pH for ciprofloxacin degradation: Comparing RSM-CCD and ANN-GA

Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach

Antibiotics, as a class of environmental pollutants, pose a significant challenge due to their persistent nature and resistance to easy degradation. This study delves into modeling and optimizing conventional Fenton degradation of antibiotic sulfamethoxazole (SMX) and total organic carbon (TOC) under varying levels of H2O2, Fe2+ concentration, pH, and temperature using statistical and artificial intelligence techniques including Multiple Regression Analysis (MRA), Support Vector Regression (SVR) and Artificial Neural Network (ANN). In statistical metrics, the ANN model demonstrated superior predictive accuracy compared to its counterparts, with lowest RMSE values of 0.986 and 1.173 for SMX and TOC removal, respectively. Sensitivity showcased H2O2/Fe2+ ratio, time and pH as pivotal for SMX degradation, while in simultaneous SMX and TOC reduction, fine tuning the time, pH, and temperature was essential. Leveraging a Hybrid Genetic Algorithm-Desirability Optimization approach, the trained ANN model revealed an optimal desirability of 0.941 out of 1000 solutions which yielded a 91.18% SMX degradation and 87.90% TOC removal under following specific conditions: treatment time of 48.5 min, Fe2+: 7.05 mg L-1, H2O2: 128.82 mg L-1, pH: 5.1, initial SMX: 97.6 mg L-1, and a temperature: 29.8 °C. LC/MS analysis reveals multiple intermediates with higher m/z (242, 270 and 288) and lower m/z (98, 108, 156 and 173) values identified, however no aliphatic hydrocarbon was isolated, because of the low mineralization performance of Fenton process. Furthermore, some inorganic fragments like NH4+ and NO3- were also determined in solution. This comprehensive research enriches AI modeling for intricate Fenton-based contaminant degradation, advancing sustainable antibiotic removal strategies.

Biodegradation of ciprofloxacin using machine learning tools: Kinetics and modelling

Recently, the rampant administration of antibiotics and their synthetic organic constitutes have exacerbated adverse effects on ecosystems, affecting the health of animals, plants, and humans by promoting the emergence of extreme multidrug-resistant bacteria (XDR), antibiotic resistance bacterial variants (ARB), and genes (ARGs). The constraints, such as high costs, by-product formation, etc., associated with the physico-chemical treatment process limit their efficacy in achieving efficient wastewater remediation. Biodegradation is a cost-effective, energy-saving, sustainable alternative for removing emerging organic pollutants from environmental matrices. In view of the same, the current study aims to explore the biodegradation of ciprofloxacin using microbial consortia via metabolic pathways. The optimal parameters for biodegradation were assessed by employing machine learning tools, viz. Artificial Neural Network (ANN) and statistical optimization tool (Response Surface Methodology, RSM) using the Box-Behnken design (BBD). Under optimal culture conditions, the designed bacterial consortia degraded ciprofloxacin with 95.5% efficiency, aligning with model prediction results, i.e., 95.20% (RSM) and 94.53% (ANN), respectively. Thus, befitting amendments to the biodegradation process can augment efficiency and lead to a greener solution for antibiotic degradation from aqueous media.

A Box-Behnken design-based chemometric approach to optimize the sono-photodegradation of hydroxychloroquine in water media using the Fe(0)/S2O82-/UV system

The huge utilization of hydroxychloroquine in autoimmune infections led to an abnormal increment in its concentration in wastewater, which can pose a real risk to the environment, necessitating the development of a pretreatment technique. To do this, we are interested in researching how hydroxychloroquine degrades in contaminated water. The main goal of this investigation is to optimize the operating conditions for the sono-photodegradation of hydroxychloroquine in water using an ultrasound-assisted Fe(0)/S 2 O 8 2 - /UV system. To get adequate removal of HCQ, a chemometric method based on the Box-Behnken design was applied to optimize the influence of the empirical parameters selected, including Fe(0) dose,S 2 O 8 2 - concentration, pH, and initial HCQ concentration. The quadratic regression model representing the HCQ removal rate (η(%)) was evolved and validated by ANOVA. The optimal conditions as a result of the above-mentioned trade-off between the four input variables, with η(%) as the dependent output variable, were captured using RSM methodology and the composite desirability function approach. For HCQ full decomposition, the optimal values of the operating factors are as follows:S 2 O 8 2 - dose, 194.309 mg/L; Fe(0) quantity, 198.83 mg/L; pH = 2.017, and HCQ initial dose of 296.406 mg/L. Under these conditions, the HCQ removal rate, achieved after 60 min of reaction, attained 98.95%.

Review on Moringa oleifera, a green adsorbent for contaminants removal: characterization, prediction, modelling and optimization using Response Surface Methodology (RSM) and Artificial Neural Network (ANN)

Moringa oleifera utilization in water treatment to eliminate emerging pollutants such as heavy metal ions, pesticides, pharmaceuticals, and pigments has been extensively evaluated. The efficacy of Moringa oleifera biosorbent has been investigated in diverse research work using various techniques, including its adsorption capacity kinetic, thermodynamic evaluation, adsorbent modifications, and mechanism behind the adsorption process. The Langmuir isotherm provided the most remarkable experimental data fit for batch adsorption investigations, whereas the best fit was obtained with the pseudo-second order kinetic model. Furthermore, only a few papers that combined batch adsorption with fixed-bed column investigations were examined. In the latter articles, the scientists modified the adsorbent to increase the material's adsorption capacity as determined by analytical methods, including IR spectroscopy, scanning electronic microscope (SEM), and X-ray diffraction (XRD). However, the raw material can show appreciable adsorption capacity values, proving moringa's potency as a biosorbent. Hydrogen bonds, electrostatic interaction, and van der Waals forces were the main processes in the found and reported adsorbent-adsorbate interactions. These mechanisms could change depending on the physiochemical nature of adsorption. Although frequently employed for heavy metal ions and dye adsorption, Moringa oleifera can still be explored in pesticide and medication adsorption investigations due to the few publications in this comprehensive review. This study, therefore, examined different Adsorbents from the Moringa oleifera plant, as well as parameters and models for enhancing the adsorption process.

Adsorption of copper from water using TiO2-modified activated carbon derived from orange peels and date seeds: Response surface methodology optimization

This study evaluated the application and efficiency of modified activated carbon in the removal of copper (Cu) from synthetic aquatic samples. The surface of activated carbon derived from orange peel (AC-OP) and date seeds (AC-DS) have been modified by Titanium dioxide nanoparticles (TiO2 NPs) (1:10 wt% mixing ratio) and used in a series of experiments designed by Response Surface Methodology (RSM) incorporating Central Composite Design (CCD). The Brunauer-Emmett-Teller (BET) test demonstrated that the modification has increased the surface area of AC-OP from 2.40 to 6.06 m2 g-1 and AC-DS from 51.10 to 81.37 m2 g-1. Effects of pH (1-7), ion initial concentration (10-60 mg L-1), adsorbent dose (0.5-8 g L-1), and contact time (0.4-6 h) have been investigated. The results showed that the optimum conditions for TiO2-modified AC-OP (OP-TiO2) are pH 5, initial concentration of 24.6 mg L-1, adsorbent dose of 4.9 g L-1, and contact time of 3.6 h. The optimum conditions for TiO2-modified AC-DS (DS-TiO2) are pH 6.4, initial concentration of 21.2 mg L-1, adsorbent dose of 5 g L-1, and contact time of 3.0 h. The modified quadratic models represented the results well with regression coefficients of 0.91 and 0.99 for OP-TiO2 and DS-TiO2, respectively. The maximum Cu removal for OP-TiO2 and DS-TiO2 were 99.90 % and 97.40 %, and the maximum adsorption capacity was found to be 13.34 and 13.96 mg g-1, respectively. Kinetic data have been fitted to pseudo first-order, pseudo second-order, intra-particle diffusion, and Elovich models. The pseudo second-order showed a better fit to the experimental data (R2 > 98 %). This study demonstrates the successful development of modified activated carbon derived from orange peels and date seeds, modified by TiO2 nanoparticles, for efficient adsorption of copper ions from water. The findings contribute to understanding the adsorption mechanism and provide valuable insights for designing environmentally friendly adsorbents.

Epsilon-MnO2 simply prepared by redox precipitation as an efficient catalyst for ciprofloxacin degradation by activating peroxymonosulfate

Four kinds of manganese oxides were successfully prepared by hydrothermal and redox precipitation methods, and the obtained oxides were used for CIP removal from water by activating PMS. The microstructure and surface properties of four oxides were systematically characterized. The results showed that ε-MnO2 prepared by the redox precipitation method had large surface area, low crystallinity, high surface Mn(III)/Mn(Ⅳ) ratio and the highest activation efficiency for PMS, that is, when the concentration of PMS was 0.6 g/L, 0.2 g/L ε-MnO2 could degrade 93% of CIP within 30 min. Multiple active oxygen species, such as sulfate radical, hydroxyl radical and singlet oxygen, were found in CIP degradation, among which sulfate radical was the most important one. The degradation reaction mainly occurred on the surface of the catalyst, and the surface hydroxyl group played an important role in the degradation. The catalyst could be regenerated in situ through the redox reaction between Mn4+ and Mn3+. The ε-MnO2 had the advantages of simple preparation, good stability and excellent performance, which provided the potential for developing new green antibiotic removal technology.

Response surface optimization of chemical coagulation for solid-liquid separation of dairy manure slurry through Box-Behnken design with desirability function

Discharging livestock manure slurry without proper treatment causes various environmental and sociological problems. Chemical coagulation is a widely used and easily applicable method for treating such wastewater. However, the technique requires optimization to enhance coagulation efficiency while minimizing chemical usage. In this study, we propose an efficient, low-cost, and environmentally safe chemical coagulation method for solid-liquid separation of dairy manure slurry. Experiments were conducted in laboratory jar tests using dairy manure slurry to investigate the impact of coagulants, specifically polyaluminum chloride (PAC) and cationic polyacrylamide (CPAM), as well as pH, on the process of solid-liquid separation. Preliminary ranges of PAC, CPAM, and pH were estimated through single-factor experiments. Coagulation optimization and modeling were performed using the response surface methodology (RSM) with the Box-Behnken design (BBD), wherein the desired goal of each parameter was set to maximize solid-liquid separation efficiency while reducing chemical dosage to maintain residual aluminum (Al) concentrations below water quality standards. Numerical optimization predicted that the optimal dosages were 75 mg/L of PAC and 35 mg/L of CPAM at pH 7. Under these conditions, removal efficiencies of 99% for turbidity and 97% for chemical oxygen demand (COD) were achieved, with a minimal residual Al concentration of 0.045 mg/L. Positive zeta potential values in the treated water confirmed complete separation of negatively charged solids in the dairy manure slurry. The response values predicted by BBD aligned with the experimental results, and the analysis of variance (ANOVA) demonstrated the predictability and accuracy of the response models. Consequently, this study highlights the practical application of RSM with BBD in optimizing chemical coagulation using PAC and CPAM to achieve efficient solid-liquid separation in livestock wastewater while maintaining low residual Al concentrations.

Mechanistic insight into the degradation of ciprofloxacin in water by hydroxyl radicals

Ciprofloxacin (CIP), an effective antibacterial drug, is widely used to treat bacterial infections in humans and animals. However, drug pollution from residues and the development of resistant genes may pose serious ecological risks. Among the known methods of CIP degradation, advanced oxidation technology initiated by hydroxyl radicals exhibits great potential. However, an in-depth study of the degradation mechanism is difficult because of the limitations of the testing methods. In this study, CIP oxidation by hydroxyl radicals was evaluated using density functional theory (DFT), and the thermodynamics, kinetics, and toxicity were investigated. The results show that CIP oxidation occurs mainly through the piperazine ring, benzene ring, and CC. High reactivity is achieved in the initial reactions, where only five reactions are not thermodynamically spontaneous. Reactions involving direct hydrogen abstraction by oxygen in this system are superior to the indirect reactions. Some theoretically predicted products, such as P6 and P11, are consistent with those reported in previous experiments, indicating that the theoretical study can provide supplementary information about the oxidation paths. The branching ratios for the hydrogen atom abstraction and addition reactions were 37. 45% and 62.55%, respectively. Finally, this reaction system is completely nontoxic based on toxicity assessment.

Degradation of ciprofloxacin by persulfate activated with pyrite: mechanism, acidification and tailwater reuse

Residues of ciprofloxacin (CIP) in the environment pose a threat to human health and ecosystems. This study investigated the degradation of CIP by persulfate (PS) activated with pyrite (FeS₂). Results showed that when [CIP] = 30 μM, [FeS₂] = 2.0 g L^-1, and [PS] = 1 mM, the CIP removal rate could reach 94.4% after 60 min, and CIP mineralization rate reached 34.9%. The main free radicals that degrade CIP were SO₄˙^- and HO˙, with contributions of 34.4% and 35.7%, respectively. Additionally, compared to the control (ultrapure water), CIP in both tap water and river water was not degraded. However, acidification could eliminate the inhibition of CIP degradation in tap water and river water. Furthermore, acidic tailwater from CIP degradation could be utilized to adjust the pH of untreated CIP, which could greatly promote the degradation of CIP and further reduce disposal costs. The reaction solution was not significantly biotoxic and three degradation pathways of CIP were investigated. Based on the above results and the characterization of FeS₂, the mechanism of CIP degradation in the FeS₂/PS system was that FeS₂ activated PS to generate Fe(iii) and SO₄˙^-. The sulfide in FeS₂ reduced Fe(iii) to Fe(ii), thus achieving an Fe(iii)/Fe(ii) cycle for CIP degradation.