Heterogeneous photocatalysis is a promising advanced oxidation process for the degradation of emerging contaminants. In this regard, Hematite (α-Fe2O3) doped TiO2 nanocomposite catalyst was synthesized via sol-gel method. The catalyst was prepared in large quantities (225 g) comparatively with other studies and characterized by X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Energy-dispersive X-ray (EDX), and nitrogen gas physisorption studies. The bandgap of the synthesized catalyst was determined using UV-vis diffused reflectance spectroscopy (DRS), and the point of zero charge (PZC) was identified by measuring the zeta potential (ζ-potential) of the nanoparticles. A large-scale study was conducted using a modified Compound Parabolic Collector Reactor (CPCR) for the degradation of paracetamol under natural sunlight irradiations. The operating parameters including the initial concentration of paracetamol, initial pH of the solution, and catalyst loading were optimized using face-centered central composite design (FCCD) based on response surface method (RSM) to obtain the maximum degradation efficiency of paracetamol. •The simplified and direct sol-gel method described helps in the synthesis of a novel nanocomposite catalyst (Fe2O3/TiO2) in large quantities while maintaining good characteristics compared to other methods.•The described treatment method using the modified CPCR will allow the degradation of paracetamol in a more sustainable and green manner.•Optimizing the operating parameters that have a significant influence on the degradation of paracetamol will contribute towards higher degradation rates.
In this approach, a batch reactor was employed to study the degradation of pollutants under natural sunlight using TiO2 as a photocatalyst. The effects of photocatalyst dosage, reaction time and pH were investigated by evaluating the percentage removal efficiencies of total organic carbon (TOC), chemical oxygen demand (COD), biological oxygen demand (BOD) and biodegradability (BOD/COD). Design Expert-Response Surface Methodology Box Behnken Design (BBD) and MATLAB Artificial Neural Network - Adaptive Neuro Fuzzy Inference system (ANN-ANFIS) methods were employed to perform the statistical modelling. The experimental values of maximum percentage removal efficiencies were found to be TOC = 82.4, COD = 85.9, BOD = 30.9% and biodegradability was 0.070. According to RSM-BBD and ANFIS analysis, the maximum percentage removal efficiencies were found to be TOC = 90.3, 82.4; COD = 85.4, 85.9; BOD = 28.9, 30.9% and the biodegradability = 0.074, 0.080 respectively at the pH 7.5, reaction time 300 min and photocatalyst dosage of 4 g L-1. The study reveals both models found to be well predicted as compared with experimental values. The values of R2 for RSM-BBD (0.920) and for ANFIS (0.990) models were almost close to 1. The ANFIS model was found to be marginally better than that of RSM-BBD.
Water quality plays a significant role as a key factor in water resource management. The photocatalytic method is widely used for the removal of recalcitrant pollutants present in seawater. Photocatalysis is a cost-effective technology, sustainable, and environmentally friendly treatment process. In the current approach, a batch reactor was utilized experimentally to study the degradation of contaminants present in seawater by utilizing ZnO as a photocatalyst under natural sunlight. The performance of the process was studied by measuring the percentage removal efficiencies of total organic carbon (TOC), chemical oxygen demand (COD), biological oxygen demand (BOD), and biodegradability with respect to photocatalyst dosage, reaction time and pH of the solution. Biodegradability is defined as the ratio of BOD to COD and this parameter significantly removes pollutants from seawater. The higher the biodegradability, the better the performance of the treatment technology. It also significantly reduces the fouling characteristics of seawater during the desalination process. According to experimental values, the maximum percentage removal efficiencies were found to be TOC = 45.6, COD = 65.4, BOD = 20.01% and biodegradability = 0.038 with respect to the initial values of the seawater sample. The response surface methodology based on Box Behnken design (RSM-BBD) and a predictive model based on the MATLAB adaptive neuro-fuzzy inference system (ANFIS) tool were employed for modeling, optimizing, and evaluating the effects of parameters. According to the RSM-BBD and ANFIS models, the determination coefficients were R2 = 0.959 and R2 = 0.99, respectively, which was very close to 1. The maximum percentage removal efficiencies according to the RSM-BBD design were found to be TOC = 40.3; COD = 61.9; BOD = 18.8% and BOD/COD = 0.0390, whereas for the ANFIS model, the maximum reduction were found to be TOC = 46.5; COD = 65.4; BOD = 20.4% and BOD/COD = 0.040. In process optimization, the ANFIS model was shown better prediction than RSM-BBD in the process's optimization.
The aim of this study is to investigate the performance of combined solar photo-catalyst of titanium oxide/zinc oxide (TiO2/ZnO) with aeration processes to treat petroleum wastewater. Central composite design with response surface methodology was used to evaluate the relationships between operating variables for TiO2 dosage, ZnO dosage, air flow, pH, and reaction time to identify the optimum operating conditions. Quadratic models for chemical oxygen demand (COD) and total organic carbon (TOC) removals prove to be significant with low probabilities (<0.0001). The obtained optimum conditions included a reaction time of 170 min, TiO2 dosage (0.5 g/L), ZnO dosage (0.54 g/L), air flow (4.3 L/min), and pH 6.8 COD and TOC removal rates of 99% and 74%, respectively. The TOC and COD removal rates correspond well with the predicted models. The maximum removal rate for TOC and COD was 99.3% and 76%, respectively at optimum operational conditions of TiO2 dosage (0.5 g/L), ZnO dosage (0.54 g/L), air flow (4.3 L/min), reaction time (170 min) and pH (6.8). The new treatment process achieved higher degradation efficiencies for TOC and COD and reduced the treatment time comparing with other related processes.
Hospital wastewater has emerged as a major category of environmental pollutants over the past two decades, but its prevalence in freshwater is less well documented than other types of contaminants. Due to compound complexity and improper operations, conventional treatment is unable to remove pharmaceuticals from hospital wastewater. Advanced treatment technologies may eliminate pharmaceuticals, but there are still concerns about cost and energy use. There should be a legal and regulatory framework in place to control the flow of hospital wastewater. Here, we review the latest scientific knowledge regarding effective pharmaceutical cleanup strategies and treatment procedures to achieve that goal. Successful treatment techniques are also highlighted, such as pre-treatment or on-site facilities that control hospital wastewater where it is used in hospitals. Due to the prioritization, the regulatory agencies will be able to assess and monitor the concentration of pharmaceutical residues in groundwater, surface water, and drinking water. Based on the data obtained, the conventional WWTPs remove 10-60% of pharmaceutical residues. However, most PhACs are eliminated during the secondary or advanced therapy stages, and an overall elimination rate higher than 90% can be achieved. This review also highlights and compares the suitability of currently used treatment technologies and identifies the merits and demerits of each technology to upgrade the system to tackle future challenges. For this reason, pharmaceutical compound rankings in regulatory agencies should be the subject of prospective studies.
In this study, novel lamellar double hydroxide composites (LDH-MgAl and LDH-MgFe) were synthesized at different metal salt ratios (1:1 to 3:1) and fully characterized using various techniques such as XRD, FTIR, SEM, EDS, and TGA. The resulting LDHs demonstrated a high affinity for efficiently removing tetracycline (TC) antibiotic from water, particularly at a moderate molar ratio of 3:1. This ratio exhibited improved structural characteristics, resulting in better TC uptake from water. The improved performance was supported by the increased abundance of surface functional groups (OH, NO3, CO32-, C-O-C, Fe-O, and Al-O-Al). The TGA analysis established the high stability of the LDHs when subjected to high temperatures. The kinetics of TC adsorption onto LDH fitted with the PSO (R2 = 0.935-0.994) and Avrami (R2 = 0.9528-0.9824) models, while the equilibrium data fitted the Liu and Langmuir isotherm models, with maximum monolayer adsorption capacities of 101.1 mg g-1 and 70.83 mg g-1, respectively-significantly higher than many reported values in the literature. The positive values of ΔH0 and ΔS0 indicate an endothermic process, with TC removal mechanisms influenced by physical interactions, such as hydrogen bonding, electrostatic interaction, and π-cation with the surface functional groups of the LDH adsorbents. These results suggest that LDH-MgAl and LDH-MgFe are promising adsorbents for the removal of TC from water.