Conversion of waste cooking oil into value-added emulsion liquid membrane for enhanced extraction of lead: Performance evaluation and optimization

Construction and formulation optimization of prothioconazole nanoemulsions for the control of Fusarium graminearum: Enhancing activity and reducing toxicity

In this study, the optimal emulsifier for prothioconazole nanoemulsions was initially screened based on appearance, microscopic observation, mean droplet size and polydispersity index (PDI). In addition, the BoxBehnken design method is adopted, and the optimal formula is screened with an emulsification time, emulsifier content, and solvent content as a single factor. On this basis, the nanoemulsion meets FAO standards for various indicators. The contact angle of droplets on wheat leaves was significantly reduced. This nanoemulsion also showed good inhibitory activity against Fusarium graminearum (EC₅₀ =1.94 mg L^-1), low acute toxicity to zebrafish (LC₅₀ =26.35 mg L^-1) and good biosafety to BEAS-2B cells. The nanoemulsion reduced the adverse effects of pesticide on wheat seed germination and growth. This study can help promote the design and manufacture of stable, efficient and safe agricultural nanoemulsions, and is expected to benefit the sustainable development of green plant protection.

Optimization and characterization of biodiesel from waste cooking oil using modified CaO catalyst derived from snail shell

Currently, research has diverted toward generating renewable fuels due to the unreliable supply and rising cost of conventional fuels. Biodiesel is renewable fuel commonly obtainable via a simple process. Biodiesel was produced via the transterification of waste cooking oil (WCO) using heterogeneous catalysts. The aim of this study was to synthesis a ZnO and TiO₂-supported CaO catalyst from a snail shell for the transterification of waste cooking palm oil to produce biodiesel. Sol-gel and wet-impregnated methods were adopted to synthesize ZnO and catalyst, respectively. The physicochemical properties of waste cooking oil and biodiesel were characterized in accordance to AOAC and ASTMD standard methods. The FTIR and XRD analyses were carried out to characterize the biodiesel and the prepared catalysts. The result of this study revealed that CaO catalyst derived from snail shall, resulted to a WCO-derived biodiesel yield of 80%. The CaO catalyst modified with ZnO and TiO₂, further led to an increased biodiesel of 90% and 95%, respectively. The result of this study showed that the optimum conditions associated with highest biodiesel yield over the synthesized catalysts were at 3% catalyst weight, 65 °C, a 6:1 methanol-to-oil ratio and 3-h reaction time. The FTIR spectra also proved successful formation of biodiesel. Biodiesel was successfully synthesized from WCO, and the CaO catalyst synthesized from snail shells and modified with ZnO and TiO₂, showed potential to substitute for costly catalysts derived from chemical reagents for biodiesel production.

Evaluation of different machine learning approaches and aerosol optical depth in PM2.5 prediction

Atmospheric Aerosol Optical Depth (AOD), derived from polar-orbiting satellites, has shown potential in PM_2.5 predictions. However, this important source of data suffers from low temporal resolution. Recently, geostationary satellites provide AOD data in high temporal and spatial resolution. However, the feasibility of these data in PM_2.5 prediction needs further study. In this paper, we analyzed the impact of AOD derived from Himawari-8 in PM_2.5 predictions. Moreover, by combining wavelet, machine learning techniques, and minimum redundancy maximum relevance (mRMR), a novel hybrid model was proposed. The results showed that AOD missing rate over Yangtze River Delta region is the highest in Nanjing, Hefei, and Maanshan. In addition, missing rates are the lowest in winter and summer (∼80%). Moreover, we found that considering AOD, as an auxiliary variable in the model, could not improve the accuracy of PM_2.5 predictions, and in some cases decreased it slightly. In comparison with other models, our proposed hybrid model showed higher prediction accuracy, R² is improved by 11.64% on average, and root mean square error, mean absolute error, and mean absolute percentage error is reduced by 26.82%, 27.24%, and 29.88% respectively. This research provides a general overview of the availability of Himawari-8 AOD data and its feasibility in PM_2.5 predictions. In addition, it evaluates different machine learning approaches in PM_2.5 predictions. Our proposed framework can be used in other regions to predict different air pollutants concentrations and can be used as an aid for air pollution controlling programs.

Conversion of Waste Oil from Oil Refinery into Emulsion Liquid Membrane for Removal of Phenol: Stability Evaluation, Modeling and Optimization

The waste oil emulsion liquid membrane produced by waste oil from oil refineries (WELM) is used to separate the phenol in purified water from the sour water stripper in oil refinery facilities, and the stability of WELM was studied. It is verified that waste refinery oil can be produced into emulsion liquid membrane with good stability and high removal rate for the first time. The WELM stability models were established by response surface methodology (RSM) and artificial neural network (ANN), respectively. The principle and mechanism of various parameters, as well as the interaction effects on the stability of WELM, are proposed. The effects of parameters, including the ratio of Span-80, liquid paraffin, the ratio of internal and oil, and the rotational speed of the homogenizer, were investigated. Under the optimal operating parameters, the WELM had a demulsification percentage of just 0.481%, and the prediction results of RSM and ANN were 0.536% and 0.545%, respectively. Both models demonstrate good predictability. The WELM stability model has a high application value in the treatment of phenol-containing wastewater in the oil refining industry, and provides a green method of resource recovery.

Alginate-modified biochar derived from rice husk waste for improvement uptake performance of lead in wastewater

In this work, alginate-modified biochar derived from rice husk waste was synthesized using a simple process. The modified biochar (MBC) and rice husk biochar (RhBC) were investigated for removing Pb (II) ions in wastewater. The BET result displayed significantly improved specific surface area of MBC up to 120 m²/g along with a total pore volume of 0.653 cm³/g. FTIR spectrums presented the higher oxygen-contained functional groups of MBC as compared to RhBC, resulting in increasing adsorption capacity of Pb (II). MBC had higher adsorption capacity (112.3 mg/g) and faster removal rate (0.0081 g mg^-1 min^-1) than those of RhBC (41.2 mg/g and 0.00025 g mg^-1 min^-1). Modified RhBC can remove more than 99% of Pb (II) from wastewater and it could be utilized for three cycles with a removal performance of over 90%. In addition, the Pb adsorption mechanism by using MBC was proposed and the practical application of MBC for the treatment of wastewater in Vietnam was discussed.

Enhanced remediation of lead (II) and cadmium (II) ions from aqueous media using porous magnetic nanocomposites - A comprehensive review on applications and mechanism

Lead and Cadmium, identified as toxic heavy metals, cause significant imbalance in the eco-system due to their tendency to bioaccumulate. Remediation of heavy metals by conventional adsorptive materials suffer demerits related to low efficiency or removal. Among the variety of adsorbent materials used in the adsorption process, metal oxides- and graphene oxide magnetic nanocomposites have gained a considerable attention. The use of nanomaterials may help to reduce this contamination, but after use, they are difficult to remove from water. An added magnetic property to nanomaterials facilitates their retrieval after use. The magnetic properties of these hybrid magnetic nanocomposites, coupled with unique characteristics of organic and inorganic elements, have found extensive application in water treatment technology. Detailed discussion on functionalisation of magnetic nanocomposites and the enhanced performance are presented. Magnetic graphene oxide-covalently functionalized-tryptophan was reported to have the highest adsorption capacity of 766.1 mg/g for remediation of lead (II) ions and graphene oxide exhibited the highest adsorption capacity of 530 mg/g for Cd (II) ions. The adsorption mechanisms for heavy metal ions on the surface of novel adsorbents, particularly lead and cadmium, using magnetic nanocomposites have been explained with reference to the isotherm models studied. The future scope of research in this area of research is proposed.

Conductive polymer layered semiconductor for degradation of triclopyr acid and 2,4-dichlorophenoxyacetic acid from aqueous stream using coalesce adsorption-photocatalysis technique

Polyaniline supported titanium dioxide nanoparticles (PTs) were fabricated using chemical oxidative aniline polymerization in the presence of titanium dioxide with ammonium peroxydisulfate as an oxidant. The synthesized PTs were thoroughly characterized for their morphological and functional features. PTs were employed for the photodegradation of acidic herbicides; 2,4-dichlorophenoxyacetic acid (2,4-D) and triclopyr acid (TCP). PT's surface modifications were imparted and their herbicide removal efficiencies were compared. The best operating conditions for adsorption/photocatalysis were 0.5 g/L photocatalyst, 10 mg/L concentration of individual herbicides resulted in 90.72% removal of TCP at pH 4 and 99.91% removal of 2,4-D at pH 5. Adsorption kinetics of herbicides, onto PT-1 showed the equilibrium attainment within 30 min and experimental data obeyed pseudo-second order model for TCP and 2,4-D removal which was governed by chemisorption. Analysis of TCP and 2,4-D adsorption indicated that the removal followed Sips model for TCP removal while Redlich-Peterson model explained the removal of 2,4-D by PT-1. Rate constants indicated that the amount of TiO₂ in the PTs played an important role in removing the herbicides and PT-1 material excellent remarkable activity for three cycles of photodegradation. Thus, this work reports the polymerization of aniline onto TiO₂ and their utility as photocatalyst for the expulsion of 2,4-D and TCP from water.

Emerging pharma residue contaminants: Occurrence, monitoring, risk and fate assessment - A challenge to water resource management

Water is one of the important gifts to mankind. In recent days the accessibility of pharmaceuticals in the environment is progressively a worldwide concern. The significant wellspring of these contaminations in water assets is drugs for human use or veterinary medications. Intermediates, active metabolites and raw materials present in water from pharmaceutical industry waste because of incomplete sewage treatment systems. Various pharmaceutical components such as analgesic/antipyretics such as Ibuprofen (57.9-104 ng/L), Diclofenac (17-129 ng/L), antibiotics such as Sulfamethoxazole (28.7-124.5 ng/L), Sulfamethazine (29.2-83.9 ng/L), Azithromycin (10-68 ng/L), psychiatric drug such as Carbamazepine (9.3-92.4 ng/L), stimulants such as caffeine greater than 55 ng/L, antidepressants, antihypertensive, contraceptives etc., are present in water resources and have been detected in mg/L to μg/L range. The synergic effects and ecotoxicological hazard assessment must be developed. Studies demonstrate that these drugs might cause morphological, metabolic and sex alterations on sea-going species, and interruption of biodegradation activities. Hazard analysis and assessments are in progress. However, the conventional effluent treatment methods are not sufficient to remove API (active pharmaceutical ingredients) from this water effectively. There is necessitate for continuous monitoring of the pharmaceutical compounds in aquatic ecosystem to save the environment and living form of lives from health hazards. This work highlights the hazards, environmental assessment and the mitigation measures of pharmaceutical pollutants.

A review on magnetic sensors for monitoring of hazardous pollutants in water resources

Water resources have long been of interest to humans and have become a serious issue in all aspects of human life. The disposal of hazardous pollutants in water resources is one of the biggest global concerns and poses many risks to human health and aquatic life. Therefore, the control of hazardous pollutants in water resources plays an important role, when it comes to evaluating water quality. Due to low toxicity, good electrical conductivity, facile functionalization, and easy preparation, magnetic materials have become a good alternative in recent years to control hazardous pollutants in water resources. In the present study, the idea of using magnetic sensors in controlling and monitoring of pharmaceuticals, pesticides, heavy metals, and organic pollutants have been reviewed. The water pollutants in drinking water, groundwater, surface water, and seawater have been discussed. The toxicology of water hazardous pollutants has also been reviewed. Then, the magnetic materials were discussed as sensors for controlling and monitoring pollutants. Finally, future remarks and perspectives on magnetic nanosensors for controlling hazardous pollutants in water resources and environmental applications were explained.

MXene-based electrochemical sensors for detection of environmental pollutants: A comprehensive review

Since the discovery of MXenes at Drexel University in the United States in 2011, there has been extensive research regarding various applications of MXenes including environmental remediation. MXenes with a general formula of M_n+1X_nT_x are a class of two-dimensional (2D) transition metal carbides, carbonitrides, and nitrides with unique chemical and physical characteristics as nanomaterials. MXenes feature characteristics such as high conductivity, hydrophobicity, and large specific surface areas that are attracting attention from researchers in many fields including environmental water engineering such as desalination and wastewater treatment as well as designing and building efficient sensors to detect hazardous pollutants in water. In this study, we review recent developments in MXene-based nanocomposites for electrochemical (bio) sensing with a particular focus on the detection of hazardous pollutants, such as organic components, pesticides, nitrite, and heavy metals. Integration of these 2D materials in electrochemical enzyme-based and affinity-based biosensors for environmental pollutants is also discussed. In addition, a summary of the key challenges and future remarks are presented. Although this field is relatively new, future research on biosensors of MXene-based nanocomposites need to exploit the remarkable properties of these 2D materials.

Boron removal from aqueous solutions by chitosan/functionalized-SWCNT-COOH: Development of optimization study using response surface methodology and simulated annealing

Boron contamination in water resources (especially drinking waters and agricultural land) is a major problem for the ecosystem. In this study, a novel synthesized chitosan/functionalized-SWCNT-COOH was prepared to separate boron (as boric acid) from aqueous solutions. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis revealed that SWCNT was dispersed in chitosan homogenously. Moreover, this study has related to the constrained optimization problem with an engineering approach. Response surface method (RSM) with face-centered central composite design (FCCCD) was chosen for maximizing the adsorption capacity as well as determining optimal independent factors such as pH, adsorbent dose, and concentration of boric acid. The optimized response (adsorption capacity) was reached 62.16 mg g^-1 under the optimal conditions (98.77 mg L^-1 of boric acid concentration, pH of 5.46 and 76 min). The present study has indicated that the synthesized material can be used as an adsorbent for eliminating boric acid from aqueous solutions depending on its high adsorbent capacity to remove boron and has better performance than existing adsorbents. Furthermore, simulated annealing (SA) optimization technique was used to compare the findings of RSM. Moreover, the selected optimization techniques were compared with error functions. The optimal conditions derived from SA were 91.17 mg L^-1 of boric acid concentration, pH of 5.86, and 76.17 min. The optimal adsorption capacity of SA was found to be 62.06 mg g^-1. These results revealed that the predictions of the two models are very close to each other.

Synthesis and characterization of nano zerovalent iron-kaolin clay (nZVI-Kaol) composite polyethersulfone (PES) membrane for the efficacious As2O3 removal from potable water samples

In this study, Kaolin clay, a mining material, was used as an abundant and available mineral as zero-valent iron-kaolinite composites for As₂O₃ removal from the water samples. The composites were made by the sodium borohydrate reduction method. The existence of Fe⁰ in the produced composites was confirmed by X-ray diffraction (XRD) and Fourier-Transform Infrared Spectroscopy (FTIR) analysis. The membranes are prepared with zerovalent nano Iron-Kaolin and PES. The synthesized composites were then mixed with polyethersulfone to prepare the membranes S1, S2, and S3 with varying compositions. Field Emission Scanning Electron Microscopy (FESEM) analysis of the produced membranes showed the porous structure and the contact angle of membranes increased the hydrophilicity. The membranes were explored for the removal of As₂O₃ (AsIII) in potable water samples. The filtration studies were carried out using the syringe filtration setup. Analysis of the arsenic (III) solution was carried out, before and after the filtration process using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), which showed a maximum of 50% reduction in its original concentration. The filtered membrane is analyzed for arsenic by Energy Dispersive X-ray (EDX) technique. Thus, the synthesized membrane effectively sieves the arsenic in water samples.