Rapid and efficient ultrasonic assisted adsorption of diethyl phthalate onto FeIIFe2IIIO4@GO: ANN-GA and RSM-DF modeling, isotherm, kinetic and mechanism study

Fabrication of novel glutathione-Fe3O4-loaded/activated carbon encapsulated sand bionanocomposites for enhanced removal of diethyl phthalate from aqueous environment in a vertical flow reactor

The extensive use of plasticizers in various industries has made Diethyl phthalate (DEP), a serious threat to the environment and ecological water security, owing to its complex-structure and low-biodegradability. Thus, the present study aimed to design a sustainable sand-coated nano glutathione (GSH) -Fe3O4-loaded/activated carbon (AC) bionanocomposite (AC-GSH-Fe3O4@sand bionanocomposite) for effective removal of DEP from water. Characterization results suggested bionanocomposites' rough and irregular texture due to the uneven distribution of AC and Fe3O4 nanoparticles over the sand. The XRD spectra indicated high crystallinity of bionanocomposites, while the FTIR spectra confirmed the presence of all individual components, i.e., GSH, AC, Fe3O4, and sand. EDX-mapping, AFM, and TGA further verified its elemental composition, topographical changes and thermal stability. The influence of pH (3, 7, 9), bed height (2, 4, 6) cm, and flow rate (2.5, 3.5, 4.5) mL min-1 were studied in a dynamic system with an initial DEP concentration of 50 mg L-1 to investigate the removal behavior of the bionanocomposites. The best DEP removal efficiency (90.18 %) was achieved over 28-h at pH 9, bed-height-4 cm, and flow-rate-3.5 mL min-1, with an optimum qmax-200.25 mg g-1 as determined through Thomas-model. Breakthrough curves were predicted using various column models, and the corresponding parameters essential for column-reactor process design were calculated. The high reusability up to the 10th cycle (≥83.32%) and the effective treatment in complex matrices (tap-water: 90.11 %, river-water: 89.72 %, wastewater: 83.83%) demonstrated bionanocomposites' prominent sustainability. Additionally, the production cost at 6.64 USD per Kg, underscores its potentiality for industrial application. Phytotoxicity assessment on mung-bean revealed better root (5.02 ± 0.27 cm) and shoot (17.64 ± 0.35 cm) growth in the bionanocomposite-treated DEP samples over the untreated samples. Thus, AC-GSH-Fe3O4@sand bionanocomposites could be considered a highly-sustainable, low-cost technique for the effective removal of DEP and other phthalate-esters from contaminated matrices.

Study of factors affecting the magnetic sensing capability of shape memory alloys for non-destructive evaluation of cracks in concrete: Using response surface methodology (RSM) and artificial neural network (ANN) approaches

Currently, the field of structural health monitoring (SHM) is focused on investigating non-destructive evaluation techniques for the identification of damages in concrete structures. Magnetic sensing has particularly gained attention among the innovative non-destructive evaluation techniques. Recently, the embedded magnetic shape memory alloy (MSMA) wire has been introduced for the evaluation of cracks in concrete components through magnetic sensing techniques while providing reinforcement as well. However, the available research in this regard is very scarce. This study has focused on the analyses of parameters affecting the magnetic sensing capability of embedded MSMA wire for crack detection in concrete beams. The response surface methodology (RSM) and artificial neural network (ANN) models have been used to analyse the magnetic sensing parameters for the first time. The models were trained using the experimental data obtained through literature. The models aimed to predict the alteration in magnetic flux created by a concrete beam that has a 1 mm wide embedded MSMA wire after experiencing a fracture or crack. The results showed that the change in magnetic flux was affected by the position of the wire and the position of the crack with respect to the position of the magnet in the concrete beam. RSM optimisation results showed that maximum change in magnetic flux was obtained when the wire was placed at a depth of 17.5 mm from the top surface of the concrete beam, and a crack was present at an axial distance of 8.50 mm from the permanent magnet. The change in magnetic flux was 9.50 % considering the aforementioned parameters. However, the ANN prediction results showed that the optimal wire and crack position were 10 mm and 1.1 mm, respectively. The results suggested that a larger beam requires a larger diameter of MSMA wire or multiple sensors and magnets for crack detection in concrete beams.

Coagulative removal of polystyrene microplastics from aqueous matrices using FeCl3-chitosan system: Experimental and artificial neural network modeling

Effluent from sewage treatment plants (STPs) is a significant source of microplastics (MPs) re-entry into the environment. Coagulation-flocculation-sedimentation (CFS) process as an initial tertiary treatment step requires investigation for coagulative MPs removal from secondary-treated sewage effluents. In this study, experiments were conducted on synthetic water containing 25 mg/L polystyrene (PS) MPs using varying dosages of FeCl3 (1-10 mg/L) and chitosan (0.25-9 mg/L) to assess the effect of process parameters, such as pH (4-8), stirring speed (0-200 rpm), and settling time (10-40 min). Results revealed that ∼89.3% and 21.4% of PS removal were achieved by FeCl3 and chitosan, respectively. Further, their combination resulted in a maximum of 99.8% removal at favorable conditions: FeCl3: 2 mg/L, chitosan: 7 mg/L, pH: 6.3, stirring speed: 100 rpm, and settling time: 30 min, with a statistically significant (p < 0.05) effect. Artificial neural network (ANN) validated the experimental results with RMSE = 1.0643 and R2 = 0.9997. Charge neutralization, confirmed by zeta potential, and adsorption, ascertained by field-emission scanning electron microscope (FESEM) and Fourier-transform infrared spectroscopy (FTIR), were primary mechanisms for efficient PS removal. For practical considerations, the application of the FeCl3-chitosan system on the effluents from moving bed biofilm reactor (MBBR) and sequencing batch reactor (SBR)-based STPs, spiked with PS microbeads, showed > 98% removal at favorable conditions.

Statistical modeling and optimization of dexamethasone adsorption from aqueous solution by Fe3O4@NH2-MIL88B nanorods: Isotherm, Kinetics, and Thermodynamic

The presence of pharmaceutical compounds in the environment poses a significant threat to human and aquatic animal health. Dexamethasone (DEX), a synthetic steroid hormone with endocrine-disrupting effects, is one such compound that needs to be effectively removed before discharging into the environment. This research presents a novel approach utilizing magnetically recyclable Fe3O4@NH2-MIL88B NRs as an efficient adsorbent for the treatment of DEX from aqueous solutions. The synthesized adsorbent was characterized by X-ray diffraction (XRD), scanning microscopy (SEM), transmission electron microscopy (TEM), vibrating sample magnetometer (VSM), diffuse reflectance spectra (DRS), and Fourier transform infrared spectroscopy (FTIR). Response surface methodology based on central composite design (RSM-CCD) was employed to optimize DEX removal efficiency by determining the optimal conditions, including pH, adsorbent dose, time, and DEX concentration. Under the optimized conditions (pH: 5.53, adsorbent dose: 0.185 g/L, time: 16.068 min, and DEX concentration: 33.491 mg/L), Fe3O4@NH2-MIL88B NRs revealed remarkable DEX adsorption efficiency of 91 ± 1.34% and adsorption capacity of 180.01 mg/g. The Langmuir isotherm and pseudo-second-order kinetic model were found to fit well with the experimental data, indicating a monolayer and chemical adsorption process. Thermodynamic analysis revealed that the adsorption process was spontaneous and endothermic. The study also investigated the inhibitory effect of background ions on DEX removal by Fe3O4@NH2-MIL88B NRs. Magnesium exhibited superior competitive ability with dexamethasone to occupy the active sites of the adsorbent compared to other background ions. The reuse of the adsorbent over ten consecutive cycles resulted in a 39.46% decrease in removal efficiency. The Fe3O4@NH2-MIL88B NRs are surrounded by abundant amounts of functional groups and π-electrons bands that can play a key role in the adsorption and separation of DEX from aqueous environments. The promising results obtained under real conditions highlight the potential of Fe3O4@NH2-MIL88B NRs as a practical and efficient adsorbent for the removal of DEX and other similar corticosteroids from aqueous solutions.

Novel Graphene oxide-Polyethylene Glycol mono-4-nonylphenyl Ether adsorbent for solid phase extraction of Pb2+ in blood and water samples

A novel and efficient Graphene Oxide-Polyethylene Glycol mono-4-nonylphenyl Ether (GO-PEGPE) nanocomposite was synthesized and used for solid phase extraction of trace levels of Pb²⁺ in different water and blood samples. The synthesized adsorbent was then characterized by the Fourier Transform-Infrared spectrophotometry (FT-IR), Field Emission-Scanning Electron Microscopy (FE-SEM), Energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction analysis (XRD). To optimize the critical parameters including pH of samples solution, amounts of adsorbent and extraction time, the response surface methodology based on the central composite design (RSM-CCD) was used and based on the results, pH = 6.0, extraction time = 22 min and amounts of adsorbent = 15 mg were selected as the optimum conditions. The relative standard deviation based on seven replicate analysis of 2 µg L^-1 Pb²⁺ was 5.2% and the limit of detection was 0.023 µg L^-1 (n = 8). The results of adsorption isotherm investigation show that the adsorption of Pb²⁺ onto the GO-PEGPE nanocomposite obeyed by the Langmuir isotherm with the maximum adsorption capacity of 69.44 mg g^-1. Also, based on the Temkin and Dubinin-Radushkevich (DR) isotherms, the adsorption of Pb²⁺ onto the GO-PEGPE nanocomposite is a physisorption phenomenon and the consequences of the kinetic models illustrated that the adsorption of Pb²⁺ followed by the pseudo second order adsorption kinetic model. Finally, the proposed method was successfully applied for preconcentration of Pb²⁺ in different water and blood samples of turning industry workers.

Artificial Intelligence-Based Tools for Process Optimization: Case Study—Bromocresol Green Decolorization with Active Carbon

This study highlights the benefits of optimizing the decolorization of bromocresol green (a colorant/pH indicator widely used in the industry, whose degradation produces toxic byproducts) by adsorption on active carbon. A set of experiments were planned and performed based on the design of experiments methodology for the following parameters: the colorant concentration (0.009-0.045 g/L), the amount of adsorbent (0.5-3 g/L), and the contact time (60-240 min). Modeling and optimization strategies were employed to determine the working conditions leading to efficiency maximization. Using the response surface methodology, the optimum values of the primary process parameters were established. In addition, a modified bacterial foraging optimization algorithm was applied as an alternative optimizer in combination with artificial neural networks in order to determine multiple combinations of parameters that can lead to maximum process efficiency. Different solutions were obtained with the considered strategies, and the maximum efficiency obtained was >99%. The study emphasizes that adsorption on active carbon is an effective method for bromocresol green decolorization in wastewater that can be further improved using advanced optimization methods.

ANN-GA based biosorption of As(III) from water through chemo-tailored and iron impregnated fungal biofilter system

The iron impregnated fungal bio-filter (IIFB) discs of luffa sponge containing Phanerochaete chrysosporium mycelia have been used for the removal of As(III) from water. Two different forms of same biomass viz. free fungal biomass (FFB) and modified free fungal biomass (chemically modified and iron impregnated; CFB and IIFB) have been simultaneously investigated to compare the performance of immobilization, chemo-tailoring and iron impregnation for remediation of As(III). IIFB showed highest uptake capacity and percentage removal of As(III), 1.32 mg/g and 92.4% respectively among FFB, CFB and IIFB. Further, the application of RSM and ANN-GA based mathematical model showed a substantial increase in removal i.e. 99.2% of As(III) was filtered out from water at optimised conditions i.e. biomass dose 0.72 g/L, pH 7.31, temperature 42 °C, and initial As(III) concentration 1.1 mg/L. Isotherm, kinetic and thermodynamic studies proved that the process followed monolayer sorption pattern in spontaneous and endothermic way through pseudo-second order kinetic pathway. Continuous mode of As(III) removal in IIFB packed bed bioreactor, revealed increased removal of As(III) from 76.40 to 88.23% with increased column height from 5 to 25 cm whereas the removal decreased from 88.23 to 69.45% while increasing flow rate from 1.66 to 8.30 mL/min. Moreover, the IIFB discs was regenerated by using 10% NaOH as eluting agent and evaluated for As(III) removal for four sorption–desorption cycles, showing slight decrease of their efficiency by 1–2%. SEM–EDX, pHzpc, and FTIR analysis, revealed the involvement of hydroxyl and amino surface groups following a non-electrostatic legend exchange sorption mechanism during removal of As(III).

Elucidating the effect of different desorbents on naphthalene desorption and degradation: Performance and kinetics investigation

In this work, the effect of different desorbents (low molecular weight organic acids (LMWOAs), surfactants, and inorganic salts) on naphthalene (NAP) desorption in soil was investigated, and the results showed that NAP desorption pattern fitted the pseudo-second-order kinetics. The addition of LMWOAs, especially citric acid (CA), could stimulate the reactive oxygen species (ROS) generation and NAP degradation in Fe(II) activated persulfate (PS) system, while the presence of surfactants and CaCl₂ could inhibit the NAP removal due to the competitive consumption of ROS. The maximum removal of NAP was 97.5% within 120 min at the PS/Fe(II)/CA/NAP molar ratio of 15/5/1/1, and the pseudo-first-order kinetic constant of NAP removal increased from 0.0110 min^-1 to 0.0783 min^-1 with the addition of CA. Compared with surfactants and inorganic salts, LMWOAs, especially CA, were more suitable as desorbent in soil washing coupled with in situ chemical oxidation technique. Moreover, 1.86 mg L^-1 desorbed amount and 36.1% removal of NAP from soil could be obtained with the presence of 1 mM CA. Finally, the significant removal of NAP and other contaminants (phenanthrene, fluoranthene, and benzene series) in actual groundwater could provide theoretical basis and technical support for the remediation of organic contaminated sites with desorbents.

Simple Preparation of the CuO•Fe3O4/Silica Composite from Rice Husk for Enhancing Fenton-Like Catalytic Degradation of Tartrazine in a Wide pH Range

SiO2 was prepared from rice husk (RH) with the assistance of cetrimonium bromide (CTAB), and the CuO•Fe3O4/SiO2 composite was prepared by a simple coprecipitation method to enhance the Fenton-like degradation of dyes in a wide pH range. SiO2 was a mesoporous material with a relatively large surface area of 496.4 m2/g and a highly relative pore volume of 1.154 cm3/g. The Fe3O4 and CuO particles with the size of 20–50 nm were well dispersed in the composite, making the composite tighter and causing the disappearance of large pores in the range of 20–55 nm. The surface area and pore volume of the composite were reduced to 248.6 m2/g and 0.420 cm3/g, respectively. Fe3O4/SiO2 and Fe3O4 samples only exhibited high catalytic activity in an acidic medium, while the CuO•Fe3O4/SiO2 composite could effectively work in a wide pH range of 3–7. Besides, the effects of reaction conditions such as catalyst dosage, H2O2 concentration, and initial dye concentration on the catalytic performance of the composite were studied. The optimal conditions for the degradation of dye were tartrazine (TA) concentration of 50 mg/L, dosage catalyst of 0.5 g/L, H2O2 concentration of 120 mM, and pH 5. The CuO•Fe3O4/SiO2 composite reached the highest activity at pH 5, showing a degradation efficiency (DE) of 93.3% and a reaction rate of 0.061 min−1. The reusability of the catalyst was investigated by cyclic experiments. The DE of the 3rd reuse remained at 55.1%, equivalent to 93.5% of the first use. The catalytic mechanism for the Fenton system has also been proposed.

A comprehensive study on the adsorption-photocatalytic processes using CoFe2O4/SiO2/MnO2 magnetic nanocomposite as a novel photo-catalyst for removal of Cr (VI) under simulated sunlight: Isotherm, kinetic and thermodynamic studies

PURPOSE

The present study aimed to investigate the efficiency of CoFe₂O₄/SiO₂/flower-like MnO₂ nanoparticles as a catalyst for Cr (VI) adsorption-photocatalytic processes.

METHODS

The magnetic nanocomposite used was first synthesized and then characterized using TEM, SEM, EDX, XRD, FTIR, XRF and BET advanced techniques. The removal of the Cr (VI) was performed through a batch adsorption approach and the effects of sample pH (A; 2-6), initial chromate concentration (B; 50-100 ppm) and adsorbent weight to sample volume ratio (C; 1-3 mg ml^-1), hole scavenger (0.1 -0.3%w/v) and time (E; 30-60 min), to evaluate the individual and interactive effects under ultraviolet light conditions, were also studied by the central composite design in the photocatalytic process of adsorption.

RESULTS

The adsorption-photocatalytic performance of the CoFe₂O₄/SiO₂/MnO₂ composite was high in which 98.1% of Cr(VI) after 30 min of photocatalytic treatment in optimum conditions (i.e. pH = 3, catalyst concentration = 2 mg L^-1, Cr(VI) concentration = 200 mg L^-1, and hole scavenger concentration = 0.4% (w/ v), At laboratory temperature, speed = 400 rpm, under UV radiation).Under optimum conditions, Cr(VI) reductive followed pseudo-second-order kinetics and followed the Langmuir and Temkin isotherms, also, positive value of ΔH° indicates endothermic nature.

CONCLUSIONS

The results showed that the synthesized CoFe₂O₄/SiO₂/MnO₂ magnetic nanocomposite holds a great potential for use as a photocatalyst to remove Cr (VI) in adsorption reactions. It can be used as an effective catalyst in the eradication of Cr (VI) wastewater.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-021-00763-1.

Phthalates removal from wastewater by different methods - a review

Phthalate esters are commonly used as plasticizers to improve the durability and workability of polymeric materials, locating and identifying them in various contexts has become a major challenge. Because of their ubiquitous use in plastic packaging and personal care items, as well as their tendency to leach out of these materials, phthalates have been detected in a variety of aquatic situations, including surface water, groundwater, drinking water, and wastewater. Phthalate esters have been shown to affect reproductive health and physical growth by disrupting the endocrine system. As a result, developing energy-efficient and effective technologies to eliminate these harmful substances from the atmosphere has become more important and urgent. This paper examines the existing techniques for treating phthalates and degradation mechanisms, as well as knowledge gaps and future research directions. These technologies include adsorption, electrochemical, photocatalysis, membrane filtration and microbial degradation. Adsorption and photo catalysis are the most widely used techniques for phthalate removal, according to the literature survey papers.

Optimization by Box–Behnken Design and Synthesis of Magnetite Nanoparticles for Removal of the Antibiotic from an Aqueous Phase

Some environmental problems caused by the intrusion of active drug ingredients, especially antibiotics, into water resources pose a serious threat. Ciprofloxacin (CIP) is an antibiotic from the group of fluoroquinolones that is used extensively in the treatment of bacterial infections. The presence of drug residues in the environment, especially in water resources, is an essential issue due to their stability and nondegradability. This study is aimed at investigating the efficiency of magnetite (Fe3O4) nanoparticles and the effect of independent variables, including initial concentrations of CIP (35-80 mg/L), adsorbent doses (20–60 mg), and pH values (4–10) at reaction time (80 min) for the removal efficiency of CIP antibiotics based on the Box-Behnken design (BBD) method. The analysis of variance (ANOVA) results indicated that a quadratic model was convenient for modeling CIP removal. The first step, the coprecipitation method, was appropriate for the preparation of Fe3O4 nanoparticles and developed as highly efficient adsorbents. Synthesized nanoparticles were later characterized by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Fourier transform infrared spectra (FT-IR). The results of XRD have shown that angles for the peaks at $2\theta =30,35.22,43.35,53.68,57,62.79,\text{and}71.38\mathrm{deg}$ , which corresponded to the crystal planes 220, 311, 400, 422, 511, 440, and 535, respectively, were consistent with standard peaks of magnetite and a cubic face structure. The obtained results indicated that the CIP removal efficiency was 74.44% under optimum operation parameters: initial concentration of CIP 44.15 (mg/L), adsorbent dosage of 59.6 (mg), $\text{pH}\cong 5$ , and contact time of 80 min. In fact, a cooperative agreement between model prediction and experimental data using BBD with significant $R^2$ values of 0.95 was observed. Based on the results, magnetite nanoparticles have an excellent ability to remove antibiotics from an aqueous phase.

Soil microbiomes divergently respond to heavy metals and polycyclic aromatic hydrocarbons in contaminated industrial sites

Contaminated sites from electronic waste (e-waste) dismantling and coking plants feature high concentrations of heavy metals (HMs) and/or polycyclic aromatic hydrocarbons (PAHs) in soil. Mixed contamination (HMs + PAHs) hinders land reclamation and affects the microbial diversity and function of soil microbiomes. In this study, we analyzed HM and PAH contamination from an e-waste dismantling plant and a coking plant and evaluated the influences of HM and PAH contamination on soil microbiomes. It was noticed that HMs and PAHs were found in all sites, although the major contaminants of the e-waste dismantling plant site were HMs (such as Cu at 5,947.58 ± 433.44 mg kg-1, Zn at 4,961.38 ± 436.51 mg kg-1, and Mn at 2,379.07 ± 227.46 mg kg-1), and the major contaminants of the coking plant site were PAHs (such as fluorene at 11,740.06 ± 620.1 mg kg-1, acenaphthylene at 211.69 ± 7.04 mg kg-1, and pyrene at 183.14 ± 18.89 mg kg-1). The microbiomes (diversity and abundance) of all sites were determined via high-throughput sequencing of 16S rRNA genes, and redundancy analysis was conducted to investigate the relations between soil microbiomes and contaminants. The results showed that the microbiomes of the contaminated sites divergently responded to HMs and PAHs. The abundances of the bacterial genera Sulfuritalea, Pseudomonas, and Sphingobium were positively related to PAHs, while the abundances of the bacterial genera Bryobacter, Nitrospira, and Steroidobacter were positively related to HMs. This study promotes an understanding of how soil microbiomes respond to single and mixed contamination with HMs and PAHs.

Neural-based modeling adsorption capacity of metal organic framework materials with application in wastewater treatment

We developed a computational-based model for simulating adsorption capacity of a novel layered double hydroxide (LDH) and metal organic framework (MOF) nanocomposite in separation of ions including Pb(II) and Cd(II) from aqueous solutions. The simulated adsorbent was a composite of UiO-66-(Zr)-(COOH)2 MOF grown onto the surface of functionalized Ni50-Co50-LDH sheets. This novel adsorbent showed high surface area for adsorption capacity, and was chosen to develop the model for study of ions removal using this adsorbent. A number of measured data was collected and used in the simulations via the artificial intelligence technique. Artificial neural network (ANN) technique was used for simulation of the data in which ion type and initial concentration of the ions in the feed was selected as the input variables to the neural network. The neural network was trained using the input data for simulation of the adsorption capacity. Two hidden layers with activation functions in form of linear and non-linear were designed for the construction of artificial neural network. The model's training and validation revealed high accuracy with statistical parameters of R2 equal to 0.99 for the fitting data. The trained ANN modeling showed that increasing the initial content of Pb(II) and Cd(II) ions led to a significant increment in the adsorption capacity (Qe) and Cd(II) had higher adsorption due to its strong interaction with the adsorbent surface. The neural model indicated superior predictive capability in simulation of the obtained data for removal of Pb(II) and Cd(II) from an aqueous solution.

Modeling defluoridation of real-life groundwater by a green adsorbent aluminum/olivine composite: Isotherm, kinetics, thermodynamics and novel framework based on artificial neural network and support vector machine

The kinetic, isotherm, and thermodynamics of adsorptive removal of fluoride from the real-life groundwater was evaluated to assess the applicability of a green adsorbent, aluminum/olivine composite (AOC). The isotherm and kinetics were demonstrated by the Freundlich and Elovich model indicating significant surface heterogeneity of AOC in favouring the fluoride sorption. The fluoride removal efficiency of AOC was achieved as 87.5% after 240 min of contact time. The diffusion kinetic model exhibited that both the intra-particle and film diffusion together control the rate-limiting step of fluoride adsorption. A negative value of ΔG⁰ (-19.919 kJ/mol) at 303 K confirmed the spontaneous adsorption reaction of fluoride, and its endothermic nature was supported by the negative value of ΔH⁰ (39.504 kJ/mol). A novel framework for a predictive model by artificial neural network (ANN), and support vector machine (SVM) considering the real and synthetic fluoride-containing water was developed to assess the efficiency of adsorbent under different scenarios. ANN model was observed to be statistically significant (RMSE: 1.0955 and R²: 0.9982) and the proposed method may be instrumental in a similar area for benchmarking the synthetic and real-life samples. The low desorption potential of the spent adsorbent exhibited safe disposal of sludge and the secondary-pollutant-free treated water by the efficient and green adsorbent AOC enhanced the field-scale applicability of the green technology.

Enhancement of plasticizer adsorption by utilizing a rice bran-derived adsorbent

Bis(2-ethylhexyl) phthalate (DEHP) and di-n-butyl phthalate (DBP) are commonly used plasticizers in many countries and are detected at significant levels in the environment. Wastewater treatment plants are currently unable to completely treat wastewater discharges containing plasticizers. Rice bran was used to prepare magnetic-activated biochar (MAB) as a reusable adsorbent for enhanced adsorption of DEHP and DBP. The influence of the adsorbent dose, temperature, and adsorption time on the removal efficiency of MAB was studied using response surface methodology (RSM). An analysis of the results indicated that the optimum conditions were a MAB dose of 3.6 g/L, a temperature of 49 °C, and an adsorption time of 454 min for DEHP removal; and a MAB dose of 3.7 g/L, a temperature of 36 °C and an adsorption time of 312 min for DBP removal. The adsorption isotherm data were well fitted by the Langmuir isotherm model, and the adsorption kinetic data were reasonably described by the pseudosecond-order model. MAB is a potential adsorbent for DEHP and DBP removal because of good removal efficiency and reusability.

The superior adsorption capacity of 2,4-Dinitrophenol under ultrasound-assisted magnetic adsorption system: Modeling and process optimization by central composite design

2,4-Dinitrophenol (DNP) was listed as a priority pollutant; accordingly, DNP-contaminated effluent must be treated before discharging to the receiving resources. In the present study, the hybrid ultrasound-assisted GO-Fe₃O₄ system was employed to decontaminate DNP solution. Ultrasound irradiation makes the mass transfer of adsorbate improved and Fe₃O₄ enables GO separation from liquid phase under external magnetic field. The as-synthesized GO-Fe₃O₄ composite was characterized by SEM, TEM, XRD, FTIR, BET and VSM. A response surface methodology based central composite design (RSM-CCD) was used to estimate and optimize of various variables on DNP removal percentage. Under optimal conditions (pH: 4.45, adsorbent dose: 0.178 g/L, ultrasound frequency: 40.02 kHz and DNP concentration: 50.10 mg/L, maximum adsorption capacity was calculated to be 425.58 mg/g for the ultrasound system, higher than the simple system 309.40 mg/g, indicating the importance of synergistic effect between the ultrasound waves and the adsorption process. The ultrasound-assisted adsorption system showed the better agreement with the Langmuir isotherm (R² > 0.997), while the results of the stirring system were more consistent with the Freundlich model (R² > 0.991). The experimental results indicated that the pseudo-second-order kinetic model well fitted by experiment data and rate constant was calculated to be 0.000148 min^-1 and 0.000002 min^-1 under ultrasound and silent systems, respectively. The rate of desorption under ultrasound was more favorable and reuse of the adsorbent in both systems after 10th consecutive cycles reduced by about 22%. Thermodynamic calculations also confirmed the endothermicity and spontaneity of both systems. Electrostatic attraction, hydrogen bonding, and π -π interactions played key roles during the adsorption of DNP onto the MGO. In conclusion, the outcomes of this study provide valuable information of the ultrasound-assisted GO-Fe₃O₄ system for practical applications.

Prediction of methyl orange removal by iron decorated activated carbon using an artificial neural network

Date Stones were used as a bio-degradable waste source for preparing iron impregnated activated carbon. The prepared activated carbon-containing oxides of iron were characterized using SEM, XRD, FTIR, and BET. The specific surface area of the iron decorated activated carbon was 738.65 m²/g. The XRD confirmed the presence of magnetite and hematite while the SEM images assured the presence of pores. The prepared activated carbon was used to remove methyl orange from wastewater. Genetic Algorithm was used to develop a model which could predict the removal efficiency of the dye. The ANN model was validated and the effect of different parameters like adsorbent dosage (0.1-1 g/L), initial dye concentration (2-20 mg/L), pH (2-11), time (10-55 min) and temperature (30-75°C) was estimated both experimentally and predicted using the model. The adsorption process follows the Freundlich isotherm and pseudo-second-order kinetic model. The values of 1/n and K_F obtained from the Freundlich isotherm designate good adsorption capacity. Both experimental and model-predicted data agrees with the kinetic model. The adsorption rate is proportionate to the square of the number of vacant adsorption sites. From the thermodynamic study, the positive worth of ΔH° indicates the energy-absorbing nature of the surface assimilation method and the process is endothermic in nature. The low values of each ΔG° (-200 to 0 kJ/mol) and ΔH° correspond to physical surface assimilation. A positive worth of ΔS° reflects the inflated randomness at the solid-aqueous interface with some structural changes in adsorbate and adsorbent.

Assessing the Applicability of Photocatalytic-Concrete Blocks in Reducing the Concentration of Ambient NO2 of Chandigarh, India, Using Box–Behnken Response Surface Design Technique: A Holistic Sustainable Development Approach

Anthropogenic emissions, such as industrial, vehicular, biomass burning, and coal combustion, play a significant role in degrading the atmospheric conditions of India. Therefore, in the present study, applicability of the photocatalytic-concrete blocks was estimated in improving the ambient environment of Chandigarh, India. The photocatalytic-concrete blocks were prepared by mixing the TiO2 particles with cement. All the experiments, designed in accordance with the Box–Behnken approach, in combination with response surface methodology, were performed in a batch reactor. Further, the process parameters, namely, concentration of TiO2 (1 to 5 g), UV-A irradiance (1 to 5 mW/cm2), and relative humidity (RH) (10 to 70%), were optimized to achieve maximum degradation of NO2. Outcomes of batch experiments depicted that the maximum degradation of NO2, that is, 68.32%, was attained at 3.35 g of TiO2, 5 mW/cm2 of UV-A irradiance, and 64.60% RH. The findings of batch experiment were further theoretically applied to degrade the ambient NO2 concentration of Chandigarh, India. It was estimated that using the photocatalytic concrete for construction of Chandigarh’s pavements may reduce the ambient NO2 concentration of Chandigarh, India, to an average of 5.80 μg/m3. Afterwards, reusability of photocatalytic-concrete blocks was also assessed, and it was made evident that after five cycles, their efficiency was reduced by only 7.15%. Subsequently, it was revealed that hydrogen peroxide-based treatment of photocatalytic-concrete blocks could completely regenerate its treatment efficiency. Therefore, it is expected that the findings of this study may prove beneficial in urban planning, as it may assist scientific auditory in identifying the applicability of TiO2-based photocatalysis in mitigating the impacts of vehicular emissions.

Oxidative stress responses caused by dimethyl phthalate (DMP) and diethyl phthalate (DEP) in a marine diatom Phaeodactylum tricornutum

A marine diatom (Phaeodactylum tricornutum) was exposed to different concentrations of dimethyl phthalate (DMP) and diethyl phthalate (DEP) for 96 h within a batch-culture system to investigate their toxicities. Results showed that P. tricornutum could remove DMP and DEP effectively with removal rates of 0.20-0.30 and 0.14-0.21 mg L^-1 h^-1, respectively. In addition, DMP and DEP significantly inhibited the photosynthesis and chlorophyll a biosynthesis of P. tricornutum with 96-h EC₅₀ values of 390.5 mg L^-1 and 74.0 mg L^-1, respectively. Results of reactive oxygen species (ROS) level suggested that the two PAEs could induce excessive ROS production in the diatom. Moreover, activities of antioxidant enzymes (i.e., SOD and POD) in the diatom increased with the increase of DMP and DEP concentrations. The results will help to understand the toxic mechanisms of PAEs, and provide strong evidences for evaluating their ecological risks in the marine environment.

Experimental investigation, binary modelling and artificial neural network prediction of surfactant adsorption for enhanced oil recovery application

Throughout the application of enhanced oil recovery (EOR), surfactant adsorption is considered the leading constraint on both the successful implementation and economic viability of the process. In this study, a comprehensive investigation on the adsorption behaviour of nonionic and anionic individual surfactants; namely, alkyl polyglucoside (APG) and alkyl ether carboxylate (AEC) was performed using static adsorption experiments, isotherm modelling using (Langmuir, Freundlich, Sips, and Temkin models), adsorption simulation using a state-of-the-art method, binary mixture prediction using the modified extended Langmuir (MEL) model, and artificial neural network (ANN) prediction. Static adsorption experiments revealed higher adsorption capacity of APG as compared to AEC, with sips being the most fitted model with R² (0.9915 and 0.9926, for APG and AEC respectively). It was indicated that both monolayer and multilayer adsorption took place in a heterogeneous adsorption system with non-uniform surfactant molecules distribution, which was in remarkable agreement with the simulation results. The (APG/AEC) binary mixture prediction depicted contradictory results to the experimental individual behaviour, showing that AEC had more affinity to adsorb in competition with APG for the adsorption sites on the rock surface. The adopted ANN model showed good agreement with the experimental data and the simulated adsorption values for APG and AEC showed a decreasing trend as temperature increases. Simulating the impact of binary surfactant adsorption can provide a tremendous advantage of demonstrating the binary system behaviour with less experimental data. The utilization of ANN for such prediction procedure can minimize the experimental time, operating cost and give feasible predictions compared to other computational methods. The integrated workflow followed in this study is quite innovative as it has not been employed before for surfactant adsorption studies.

The mixotrophic denitrification characteristics of Zoogloea sp. L2 accelerated by the redox mediator of 2-hydroxy-1,4-naphthoquinone

Denitrification in mixed culture system has been extensively researched to date, but few studies have focused on accelerating the process using redox mediators to promote electron transfer. Strain L2, an iron-reducing bacteria, can remove 75.44% of nitrate under temperature of 30.60 °C, pH of 6.75 and Fe²⁺ concentration of 27.86 mg·L^-1. Additionally, the removal rate of nitrate reached 1.516 mg·L^-1·h^-1 in 8 h with the addition of 0.030 mmol·L^-1 2-hydroxy-1,4-naphthoquinone (HNQ), which increased by 1.38 times than control group. Furthermore, analysis by fluorescence spectroscopy, flow cytometer and gas chromatography demonstrated that HNQ positively stimulated denitrification. This study provides a reference for enhancing denitrification in mixed culture and lays the foundation for the practical application of redox mediators in groundwater treatment.