Optimizing removal of antiretroviral drugs from tertiary wastewater using chlorination and AI-based prediction with response surface methodology.

Chemical and pharmaceutical chemicals found in water sources create substantial risks to human health and the environment. The presence of pharmaceutical contaminants in water can cause antibiotic resistance development, toxicity to aquatic organisms, and endocrine disruption. Hence, the elimination of chemicals and other contaminants from wastewater prior to its release is a burgeoning concern in the domains of engineering and science. The use of treatment technologies in wastewater treatment plants can remove pharmaceutical contaminants through the oxidation process. However, many traditional wastewater treatment plants lack the advanced monitoring tools required to detect low concentrations of pharmaceuticals. Without the ability to detect these compounds, it's challenging to treat them effectively. The goal of this study was to use Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) algorithms to model and improve how Nevirapine and Efavirenz break down in different chlorination conditions. The RSM analysis revealed statistically significant models (F-values: Nevirapine, pH-t: 108.15, T-t: 76.55, ICC-t: 110.84), indicating a strong correlation between operational parameters (pH, temperature, and initial chlorine concentration) and degradation behavior. The ANN model accurately predicted the degradation of both Nevirapine and Efavirenz under various chlorination conditions, as confirmed by analyzing actual-predicted graphs, residual plots, and Mean Squared Error (MSE) values. The ANN model using ICC-t achieved the highest MOD value of 31.31 % for Nevirapine. The ANN model based on ICC-t yielded a maximum MOD value of 16.06 % for Efavirenz. These findings provide valuable insights into optimizing chlorination processes for better removal of these pharmaceutical contaminants from water.

WITHDRAWN: Effects of hydraulic retention time and cultivation on nutrients removal and biomass production in wastewater by membrane photobioreactor: Modeling and optimization by machine learning and response surface methodology.

This article has been withdrawn at the request of the Editor-in-Chief.

Removing polyfluoroalkyl substances (PFAS) from wastewater with mixed matrix membranes.

Polyfluoroalkyl and perfluoroalkyl (PFAS) chemicals are fluorinated and exhibit complicated behavior. They are determined and highly resistant to ecological modifications that render plants ecologically robust. Thermal stability and water and oil resistance are examples of material qualities. Their adverse consequences are causing increasing worry due to their bioaccumulative nature in humans and other creatures. Direct data indicates that PFAS exposure in humans causes endocrine system disruption, immune system suppression, obesity, increased cholesterol, and cancer. Several PFASs are present in drinking water at low doses and may harm people. These cancer-causing PFAS have caused concern for water bodies all around the globe. Analytical techniques are used to identify and measure PFAS in an aqueous medium (membrane). Furthermore, a deeper explanation is provided for PFAS removal methods, including mixed matrix membrane (MMM) technology. By removing over 99 % of the PFAS from wastewater, MMMs may effectively remove PFAS from sewage when the support matrix contains adsorbing components. Furthermore, we consider several factors affecting the removal of PFAS and practical sorption methods for PFAS onto various adsorbents.

Heavy metal (Cu2+) removal from wastewater by metal-organic framework composite adsorbent: Simulation-based- artificial neural network and response surface methodology.

Metal-organic framework (MOF)--based composites have received significant attention in a variety of applications, including pollutant adsorption processes. The current investigation was designed to model, forecast, and optimize heavy metal (Cu2+) removal from wastewater using a MOF nanocomposite. This work has been modeled by response surface methodology (RSM) and artificial neural network (ANN) algorithms. In addition, the optimization of the mentioned factors has been performed through the RSM method to find the optimal conditions. The findings show that RSM and ANN can accurately forecast the adsorption process's the Cu2+ removal efficiency (RE). The maximum values of RE are achieved at the highest value of time (150 min), the highest value of adsorbent dosage (0.008 g), and the highest value of pH (=6). The R2 values obtained were 0.9995, 0.9992, and 0.9996 for ANN modeling of adsorption capacity based on different adsorbent dosages, Cu2+ solution pHs, and different ion concentrations, respectively. The ANN demonstrated a high level of accuracy in predicting the local minima of the graph. In addition, the RSM optimization results showed that the optimum mode for RE occurred at an adsorbent dosage value of 0.007 g and a time value of 144.229 min.

Hydrogeochemical assessment of aquifer salinization in north-eastern Morocco's Gueroaou coastal plain using statistical methods.

The Guerouaou aquifer investigation spanning 280 km2 in Ain Zohra yields promising outcomes, instilling optimism for regional water quality. These analyses were applied to 45 sampling instances from 43 wells, enabling a comprehensive water quality assessment. Groundwater conductivity ranged from medium to high, peaking at 18360 ms/cm2. The conductivity reveals insights about the groundwater's mineralization. Key physiochemical parameters fell within desirable thresholds, bolstering the positive perspective. HCO3- levels spanned 82-420 mg/L, while chloride content ranged from 38 to 5316 mg/L, benefiting water quality. NO3- ions, vital for gauging pollution, ranged from 0 to 260 mg/L, indicating favorable results. Cation concentrations exhibited encouraging variations: Ca2+- 24 to 647 mg/L, Mg2+- 12 to 440 mg/L, Na+- 18 to 2722 mg/L, K+- 1.75 to 28.65 mg/L. These collectively favor water quality. Halite breakdown dominated mineralization, as evidenced by the prevalence of Na-Cl-Na-SO4 facies. Water resource management and local communities need effective management and mitigation strategies to prevent saltwater intrusion.

Hazardous waste management (Buxus papillosa) investment for the prosperity of environment and circular economy: Response surface methodology-based simulation.

Dealing with the current defaults of environmental toxicity, heating, waste management, and economic crises, exploration of novel non-edible, toxic, and waste feedstock for renewable biodiesel synthesis is the need of the hour. The present study is concerned with Buxus papillosa with seeds oil concentration (45% w/w), a promising biodiesel feedstock encountering environmental defaults and waste management; in addition, this research performed simulation based-response surface methodology (RSM) for Buxus papillosa bio-diesel. Synthesis and application of novel Phyto-nanocatalyst bimetallic oxide with Buxus papillosa fruit capsule aqueous extract was advantageous during transesterification. Characterization of sodium/potassium oxide Phyto-nanocatalyst confirmed 23.5 nm nano-size and enhanced catalytic activity. Other characterizing tools are FTIR, DRS, XRD, Zeta potential, SEM, and EDX. Methyl ester formation was authenticated by FTIR, GC-MS, and NMR. A maximum 97% yield was obtained at optimized conditions i.e., methanol ratio to oil (8:1), catalyst amount (0.37 wt%), reaction duration (180 min), and temperature of 80 °C. The reusability of novel sodium/potassium oxide was checked for six reactions. Buxus papillosa fuel properties were within the international restrictions of fuel. The sulphur content of 0.00090% signified the environmental remedial nature of Buxus papillosa methyl esters and it is a highly recommendable species for biodiesel production at large scale due to a t huge number of seeds production and vast distribution.

Effects of CO2 concentration and time on algal biomass film, NO3-N concentration, and pH in the membrane bioreactor: Simulation-based ANN, RSM and NSGA-II.

The practice of aquaculture is associated with the generation of a substantial quantity of effluent. Microalgae must effectively assimilate nitrogen and phosphorus from their surrounding environment for growth. This study modeled the algal biomass film, NO3-N concentration, and pH in the membrane bioreactor using the response surface methodology (RSM) and an artificial neural network (ANN). Furthermore, it was suggested that the optimal condition for each parameter be determined. The results of ANN modeling showed that ANN with a structure of 5-3 and employing the transfer functions tansig-logsig demonstrated the highest level of accuracy. This was evidenced by the obtained values of coefficient (R2) = 0.998, R = 0.999, mean squared error (MAE) = 0.0856, and mean square error (MSE) = 0.143. The ANN model, characterized by a 5-5 structure and employing the tansig-logsig transfer function, demonstrates superior accuracy when predicting the concentration of NO3-N and pH. This is evidenced by the high values of R2 (0.996), R (0.998), MAE (0.00162), and MSE (0.0262). The RSM was afterward employed to maximize the performance of algal film biomass, pH levels, and NO3-N concentrations. The optimal conditions for the algal biomass film were a concentration of 2.884 mg/L and a duration of 6.589 days. Similarly, the most favorable conditions for the NO3-N concentration and pH were 2.984 mg/L and 6.787 days, respectively. Therefore, this research uses non-dominated sorting genetic algorithm II (NSGA II) to find the optimal NO3-N concentration, algal biomass film, and pH for product or process quality. The region has the greatest alkaline pH and lowest NO3-N content.

Green and sustainable synthesis of CaO nanoparticles: Its solicitation as a sensor material and electrochemical detection of urea.

Urea is recognized as one of the most frequently used adulterants in milk to enhance artificial protein content, and whiteness. Drinking milk having high urea concentrations which causes innumerable health disputes like ulcers, indigestion, and kidney-related problems. Therefore, herein, a simple and rapid electroanalytical platform was developed to detect the presence of urea in milk using a modified electrode sensor. Calcium oxide nanoparticles (CaO NPs) were green synthesized and used as a catalyst material for developing the sensor. Synthesized materials formation was confirmed by different techniques like FTIR, UV-visible, XRD, SEM-EDX, and Raman spectroscopy. The carbon paste electrode (CPE) was modified using the CaO NPs and used as a working electrode during the analysis followed by cyclic voltammetry and differential pulse voltammetry (DPV) techniques. The fabricated calcium oxide modified carbon paste electrode (CaO/CPE) successfully detected the presence of urea in the lower concentration range (lower limit of detection (LLOD) = 0.032 µM) having a wide linear detection range of 10-150 µM. Adsorption-controlled electrode process was achieved at the scan rate variation parameter. The leading parameters like the selectivity, repeatability, and stability of the CaO/CPE were investigated. The relative standard deviation of sensor was ± 3.8% during the interference and stability study.

Experimental investigation of H3PO4 activated papaya peels for methylene blue dye removal from aqueous solution: Evaluation on optimization, kinetics, isotherm, thermodynamics, and reusability studies.

This investigation is centered on the effectiveness of methylene blue (MB), a cationic dye, adsorbed from an aqueous media by H3PO4 activated papaya skin/peels (PSPAC), with initial pH (2-10), contact time (30-180 min), MB dye concentration (varying from 10 to 50 mg/L), and MB dose (0.1-0.5 gm). The findings show that the best optimal conditions for MB dye removal occur at a 6 pH, 0.3 gm dose of PSPAC adsorbent for 10 mg/L MB dye concentration, with 90 min of contact time. To optimize and validate the extraction efficiency of MB dye, a response surface methodology (RSM) study was conducted using a central composite design (CCD) with a regression model showing R2 = 0.9940. FT-IR spectroscopy shows, CO, and O-H stretching functional groups while FE-SEM is assessed to supervise morphological features of the PSPAC adsorbent. The peak adsorption capacity with 46.95 mg/g for the Langmuir isotherm model conveniently satisfies the adsorption process with R2 = 0.9984 while with R2 = 0.999, a kinetic model, pseudo-second-order, confirms MB dye adsorption by PSPAC adsorbent. Moreover, thermodynamic parameters including ΔGᵒ, ΔH°, and ΔS° were computed and found to be spontaneous and exothermic. Furthermore, regeneration studies employed with NaOH (0.1 M) and HCl (0.1 M) solution media show an acceptable MB removal efficiency consecutive up to three cycles. The study highlights that H3PO4 papaya skin/peel (PSPAC) is an effectual, sustainable, reasonably available biosorbent to remove industrial cationic dyes disposal.

Pharmaceutical residues in the ecosystem: Antibiotic resistance, health impacts, and removal techniques.

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.

Wastewater treatment with algal based membrane bioreactor for the future: Removing emerging containments.

The difficulty of developing pollutants in aquatic ecosystems and their potential effects on animals and plants have been raised. Sewage effluent can seriously harm a river's plant and animal life by reducing the water's oxygen content. Due to their increasing use and poor elimination in traditional municipal wastewater treatment plants (WWTPs), pharmaceuticals are one of the developing pollutants that have the potential to penetrate aquatic ecosystems. Due to undigested pharmaceuticals and their metabolites, which constitute a significant class of potentially hazardous aquatic pollutants. Using an algae-based membrane bioreactor (AMBR), the primary objective of this research was to eliminate emerging contaminants (ECs) identified in municipal wastewater. The first part of this research covers the basics of growing algae, an explanation of how they work, and how they remove ECs. Second, it develops the membrane in the wastewater, explains its workings, and uses the membrane to remove ECs. Finally, an algae-based membrane bioreactor for removing ECs is examined. As a result, daily algal production using AMBR technology might range from 50 to 100 mg/Liter. These kinds of machines are capable of nitrogen and phosphorus removal efficiencies of 30-97% and 46-93%, respectively.

A novel investigations on medical and non-medical mask performance with influence of marine waste microplastics (polypropylene).

The entire human race is struggling with the spread of COVID-19. Worldwide, the wearing of face masks is indispensable to prevent such spread. Despite numerous studies reporting on the fabrication of face masks and surgical masks to reduce spread and thus human deaths, this novel work is considered the marine waste of microplastics, namely Polypropylene (PP) polymer, used to fabricate non-woven fabric masks through the melt-blown process. This experimental work aims to maximize the mask's quality and minimize its fabrication cost by optimizing the melt-blown process parameters and using microplastics. The melt-blown process was used to make masks. Parameters such as extruder temperature, hot air temperature, melt flow rate, and die-to-collector distance (DCD) were investigated as independent variables. The quality of the mask was investigated in terms of bacterial filtration efficiency (BFE), particle filtration efficiency (PFE), and differential pressure. The Taguchi L16 orthogonal array and Taguchi analysis were employed for experimental design and statistical optimization, respectively. The results reveal that the higher BFE and PFE are recorded at 96.7 % and 98.6 %, respectively. The surface morphological investigation on different layers ensured the fine and uniform porosity of the layers and exhibited minimum breath resistance (a low differential pressure of 0.00152 kPa/cm2). Hence the chemically treated marine waste microplastics improved the masks' performance.

Zinc oxide nanoparticles adsorb emerging pollutants (glyphosate pesticide) from aqueous solutions.

The present study captures the precipitation synthesis of zinc nanoparticles and modification with alumina and oleic acid. The crystalline size evaluated from the XRD profile of the zinc oxide nanoparticles was 18.05 nm but was reduced to 14.20 and 14.50 nm upon modification with oleic acid and alumina. The XRD spectra also showed evidence of the amorphous nature of zinc oxide nanoparticles and subsequent enhancement upon modification. A porous appearance was observed in the SEM instrumentation but seems to be enhanced by modification. The FTIR absorption spectra of the nanoparticles showed a peak associated with ZnO vibration around 449 cm, but the enhanced intensity was observed due to modification. The prepared ZnO-NPs and the modified samples were good materials for the adsorption removal of glyphosate from water, recording efficiencies above 94% at neutral pH and showing a possible incremental trend with an enhanced period of contact and adsorbent dosage. The adsorbents showed maximum capacity that ranged from 82.85 to 82. 97 mg/g. The adsorption models of Freundlich, Temkin, Dubinin-Radushkevich and BET showed excellent fitness. Results from computational results complemented experimental data and were used to identify the sites for adsorption and characteristics of molecular descriptors for the systems.

Evaluation of the impact of alkyl silane entity (APTES) on photocatalyst (TiO2) and their photocatalytic degradation of organic compounds for environmental remediation.

Environmental pollution by diverse organic pollutants is a serious issue facing humanity, and the scientific community is working hard to find a solution to climatic change due to pollution. Along the same lines, we have tried to find a material/method which is economical and less laborious for achieving the same desired objectives. In this work, the surface modification of titanium dioxide to be used as a photocatalyst was carried out with different concentrations of alkyl silane agent APTES (3-aminopropyltriethoxysilane) and studied their impact on the degradation of representative compound, i.e., methylene blue. The surface-modified TiO2-APTES nanoparticles were obtained via the solvothermal process. The APTES in different molar (0.21-0.41 M) concentrations was obtained by dissolving APTES in ethanol. The obtained samples were characterized through Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscopy, and UV-visible spectroscopy. The photocatalytic activity was inferred from the degradation ability of functionalized nanoparticles for methylene blue and evaluated by UV-visible spectroscopy. Our results demonstrated a significant 70% degradation rate of methylene blue.

Pyrolytic conversion of human hair to fuel: performance evaluation and kinetic modelling.

There are several environmental and human health impacts if human hair waste is not adequately disposed of. In this study, pyrolysis of discarded human hair was carried out. This research focused on the pyrolysis of discarded human hair under controlled environmental conditions. The effects of the mass of discarded human hair and temperature on bio-oil yield were studied. The proximate and ultimate analyses and calorific values of disposed of human hair, bio-oil, and biochar were determined. Further, chemical compounds of bio-oil were analyzed using a gas chromatograph and a mass spectrometer. Finally, the kinetic modeling and behavior of the pyrolysis process were characterized through FT-IR spectroscopy and thermal analysis. Based on the optimized mass of disposed of human hair, 250 g had a better bio-oil yield of 97% in the temperature range of 210-300 °C. The different parameters of bio-oil were: pH (2.87), specific gravity (1.17), moisture content (19%), heating value (19.34 MJ/kg), and viscosity (50 CP). C (56.4%), H (6.1%), N (0.16%), S (0.01%), O (38.4%), and Ash (0.1%) were discovered to be the elemental chemical composition of bio-oil (on a dry basis). During breakdown, the release of different compounds like hydrocarbons, aldehydes, ketones, acids, and alcohols takes place. According to the GC-MS results, several amino acids were discovered in the bio-oil, 12 abundant in the discarded human hair. The FTIR and thermal analysis found different concluding temperatures and wave numbers for functional groups. Two main stages are partially separated at about 305 °C, with maximum degradation rates at about 293 oC and 400-4140 °C, respectively. The mass loss was 30% at 293 0C and 82% at temperatures above 293 0C. When the temperature reached 4100C, the entire bio-oil from discarded human hair was distilled or thermally decomposed.

Nanotechnology future in food using carbohydrate macromolecules: A state-of-the-art review.

It is commonly known that agricultural pest and disease management is achieved through the use of agricultural chemicals and other synthetic compounds, which can contaminate water, soil, and food. Using agrochemicals indiscriminately has negative effects on the environment and poor food quality. In contrast, the world's population is increasing rapidly, and arable land is diminishing daily. Traditional agricultural methods must be replaced by nanotechnology-based treatments that efficiently address both the demands of the present and the needs of the future. As a promising contributor to sustainable agriculture and food production worldwide, nanotechnology has been applied through innovative and resourceful tools. Recent advances in nanomaterial engineering have increased agricultural and food sector production and protected crops using nanoparticles (1000 nm). Agrochemicals, nutrients, and genes can now be distributed to plants in a precise and tailored manner through nanoencapsulation (nanofertilizers, nanopesticides, and genes). Despite the advancement of technology in agriculture, some areas remain unexplored. The various agricultural domains must therefore be updated in priority order. The development of long-lasting and efficient nanoparticle materials will be key to the development of future eco-friendly and nanoparticle-based technologies. We thoroughly covered the many types of nanoscale agro-materials and gave an overview of biological techniques in nano-enabled tactics that can effectively reduce plant biotic and abiotic challenges while potentially boosting plant nutritional values.

Valorization of Waste Watermelon Rinds as a Bio-adsorbent for Efficient Removal of Methylene Blue Dye from Aqueous Solutions.

Nature-based solutions (NBSs) for remediation of various emerging contaminants have gained impetus during the last few decades. In the current study, watermelon (citrullus lanatus), a highly consumed seasonal fruit, was used as a feedstock waste biomass for biochar synthesis through valorization of watermelon rinds. The watermelon biochar (WM-BC) was synthesized through slow pyrolysis at 550°C under anoxic conditions. Langmuir model with R2>99, was found to best fit the adsorption isotherm, and the adsorption kinetics was best described by the pseudo-second-order model. Various characterization tools including FTIR, SEM, BET, XRD, and TEM were used to evaluate the surface morphology of the biochar. The removal efficiency increased from 35% (dosage = 0.4 g), to 81% at WM-BC dosage of 2 g. A maximum adsorption capacity of 115.61 mg/g was found. The results from kinetic and isotherm model model suggested that the adsorption was favorable and multilayer adsorption can be considered. The adsorption mechanism was found to be governed by the co-existing factors such as hydrogen bonding, electrostatic interactions, and aromatic interactions. Results suggest that WM-BC has high potential to be employed as an adsorbent for efficient remediation of methylene blue dyes from aqueous solutions.

Novel and sustainable green sulfur-doped carbon nanospheres via hydrothermal process for Cd (II) ion removal.

Herein, the synthesis, characterization, and adsorption performance of a novel green sulfur-doped carbon nanosphere (S-CNs) is studied to eliminate Cd (II) ions from water effectively. S-CNs were characterized using different techniques including Raman spectroscopy, powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) with energy dispersive X-ray analysis (EDX), , Brunauer-Emmett-Teller (BET) specific surface area analysis and Fourier transform infrared spectrophotometry (FT-IR), were performed. The efficient adsorption of the Cd (II) ions onto S-CNs strongly depended on pH, initial concentration of Cd (II) ions, S-CNs dosage, and temperature. Four isotherm models (Langmuir, Freundlich, Temkin & Redlich Peterson) were tested for modeling. Out of four, Langmuir showed more applicability than the other three models, with a Qmax value of 242.72 mg/g. Kinetic modeling studies suggest a superior fit of the obtained experimental data with the Elovich equation (linear) and pseudo-second-order (non-linear) rather than other linear and non-linear models. Data obtained from thermodynamic modeling indicates that using S-CNs for Cd (II) ions adsorption is a spontaneous and endothermic . The current work recommends using better and recyclable S-CNs to uptake excess Cd (II) ions.

Generation of bio-energy after optimization and controlling fluctuations using various sludge activated microbial fuel cell.

An aerobic microbial fuel cell (MFC) was designed to produce bio-electricity using cow manure-pretreated slurry (CM) and sewage sludge (SS). A comparative study of parametric effects on power generation for various parameters like feed ratio of wastes, pH of anode media, and electrode depth was conducted. This experiment aimed to identify the most important system parameters and optimize them to develop a suitable controller for a stable output. Power production reached its maximum at an electrode depth of 7 cm, a pH of 6, and a feed ratio of 2:1 in the CM + SS system before applying the controller. Response surface methodology (RSM) was practiced to explore the relationships between various parameters and the response using MINITAB software. The regression equation of the most productive system deduced from the RSM result has an R2 value of 85.3%. The results show that an ON/OFF controller works satisfactorily in this study. The highest energy-generating setup has a chemical oxygen demand (COD) removal efficiency of 45%. The morphology and content of the used wastes indicate that they can be recycled in other applications.

Curve fitting model of Polycarbonate Al2O3-nanoparticle membranes for removing emerging contaminants from wastewater: Effect of temperature and nanoparticles.

The purpose of this paper is to demonstrate the use of the phase separation procedure in order to synthesize ultrafiltration polycarbonate containing aluminum oxide (Al2O3) nanoparticles (NPs) to remove emerging contaminants from wastewater at varying temperatures and nanoparticle contents. In the membrane structure, Al2O3-NPs are loaded at rates of 0≤φ≤1% volume. Fourier transform infrared (FTIR), atomic force microscopy (AFM), and scanning electron microscopy (SEM) were used to characterize the fabricated membrane containing Al2O3-NPs. Nevertheless, volume fractions ranged from 0 to 1% during the experiment, which was conducted between 15 and 55 °C. An analysis of the ultrafiltration results was conducted by using a curve-fitting model to determine the interaction between these parameters and the effect of all independent factors on the emerging containment removal. Shear stress and shear rate for this nanofluid are nonlinear at different temperatures and volume fractions. Viscosity decreases with increasing temperature at a specific volume fraction. In order to remove emerging contaminants, a decrease in viscosity at a relative level fluctuates, resulting in more porosity in the membrane. NPs become more viscous with an increasing volume fraction at any given temperature on the membrane. For example, a maximum relative viscosity increases of 34.97% is observed for a 1% volume fraction at 55 °C. A novel model is then used to measure the viscosity of nanofluid. This indicates that the results and experimental data are in very close agreement, as the maximum deviation is 2.6%.