Arsenic is a highly toxic element for human beings, which is generally found in groundwater. Dissolved Arsenic in water can be seen as As+3 and As+5 states. The adsorption process is one of the available methods to remove Arsenic from aqueous solutions. Thus, this papers aims at removing Arsenic (III) from aqueous solutions through adsorption on iron oxide granules. The relation among four independent variables, namely the initial concentration of Arsenic (III), pH, adsorbent dose, and contact time have been investigated through Response Surface Methodology. Design-Expert software and Central Composite Design method have been used to design and analyze the experiments and results. Also, SEM and FTIR analysis have been conducted to characterize the absorbent morphology. The optimum initial concentration of Arsenic (III), pH, contact time, and adsorbent dosage are 30ppm, 5, 49.99min, and 8g/l, respectively. Under these optimum conditions, the Arsenic (III) removal efficiency is 67%. The predicted 2FI model shows the highest Arsenic removal coefficient (R2=0.887).

Cedrus deodara is a coniferous tree native to Himalayan region. Its wood is a valuable resource for the timber industry; however, its bark is typically discarded as a waste material. The present study examines the performance of Cedrus deodara bark powder (CD) as an inexpensive adsorbent for elimination of Pb (II) ions. In addition to this multiple linear regression (MLR) and artificial neural network (ANN) models were developed for modelling the adsorption process and prediction of Pb (II) removal efficiency. The structural and chemical properties of CD were explored using Field Emission Scanning Electron Microscope (FE-SEM), Energy Dispersive Spectrometer (EDS), X-Ray Diffractometer (XRD) and Fourier Transform Infrared Spectroscopy (FTIR). Batch experiments were conducted to investigate the influence of factors including pH, contact time, initial Pb (II) concentration and temperature on Pb (II) adsorption. The adsorption followed pseudo-second-order kinetic and Langmuir isotherm models with maximum monolayer uptake capacity 77.52 mg/g. Based on the thermodynamic criteria, the process was endothermic and spontaneous with enthalpy change (ΔH = 8.08 kJ/mol), free energy change (ΔG = -2.44 kJ/mol) and entropy change (ΔS = 0.03 kJ/K/mol). Statistical comparison of MLR model (R2 = 0.817, RMSE = 8.954, MAPE = 17.379 %) and ANN model (R2 = 0.993, RMSE = 1.777, MAPE = 2.054 %) confirmed that ANN model was far more accurate in predicting removal efficiency.

This paper aims to study the possibility of providing a low-cost alternative for the adsorbents used in the fluoride adsorption from water by using eggshells. Indeed, eggshells were used as an adsorbent for fluoride adsorption from a drinking groundwater sample containing (2.14 mg/l) of fluoride. The eggshells were crushed and sieved into three particle sizes (0.2, 0.5, and 1mm) and then heated at different temperatures ranging from 100 to 250°C. XRD, FT-IR, pHpzc, and TG/DTA analysis were used for the characterization of the adsorbents.  Adsorption batch experiments were carried out to determine the adsorption capacity of eggshell powder such as, particle size, preparation temperature, contact time, and adsorbent dose. A spectrophotometer UV-VIS was used to assess fluoride removal efficiency. The eggshell powder heated at 250°C with 0.2mm of particle size was found to be the most efficient adsorbent, with a maximum fluoride removal efficiency of 51.4%, a maximum adsorption capacity of 0.052mg/g, and a residual fluoride concentration of 1.1mg/l within 150 minutes. The data of the adsorption kinetic on ES250°0.2 were successfully fitted with the pseudo-second-order model with a satisfying coefficient of determination (R2=0.993). The results of the intra-particle diffusion model showed a multi-linearity, revealing that the diffusion of fluoride into the adsorbent was by two stages with diffusion rate constants of Ki = 0.007 (mg /g/min1/2) and Ki = 0.001(mg /g/min1/2) for the first and second stage respectively. An adsorbent dose of 1.5g and 1 hour of contact time were sufficient to decrease fluoride concentration from 2.14 to 1.1mg/l.

Domestic and industrial wastewater contributed to some urban wastewater, which requires specific processing before being disposed into surface waters or reused for irrigation. This paper aimed to employ kaolin as an adsorbent to remove heavy metals from wastewater, as well as aeration and alum to remove nutrients. Experiment were conducted in three parts: first, involved using the aeration method to determine the ideal amount of time to remove or minimize the nutrients. Second, involves treating the solution with potassium alum using various alum doses at the obvious times to eliminate or minimize the nutrients, while third step involves treating the solution with kaolin ore with a size of < 63 µm at various doses, pH, and contact times to remove heavy metals. The findings showed that the aeration method completely removed CO3, OH, PO4, NO3, Ca, and Mn ions after contact time equal 120, 24, 192, 24, 120, and 48 hrs, respectively. Applaying alum treatment method can remove completely CO3, OH, PO4, NO3, and Mn, after contact time 120, 24, 120, 24, and 24 hrs, respectively. When Kaolin ore used as adsorbent, the removal efficiency of  Fe, Cd, Cr, Cu, Sr, Mn, and Zn were; 92, 100, 100, 100, 94, 100, and 88 % ,respectively in 24 hours contact time. The experiment succeeds in treatment of industrial wastewater that was within the range of specified limitations for disposing into surface water or reuse in irrigation field as stated by Egyptian standard code using the three successive treatment techniques.

Increasing the pollution rate of water sources is one of the most severe issues that the world faces. This issue has stimulated researchers to investigate different treatment methods such as adsorption, chemical precipitation, membrane filtration, flocculation, ion exchange, flotation, and electrochemical methods. Among them, adsorption has gained broad interest due to its ease of operation, low cost, and high efficiency. The critical factor of the successful adsorption treatment process is finding attractive adsorbents with attractive criteria such as low cost and high adsorption capacity. In the last few decades, nanotechnology has attracted much attention, and numerous nanomaterials have been synthesized for water and wastewater treatment. This work provides a quick overview of nanomaterials, which have been investigated for water remediation as adsorbent and photocatalyst. This work reviewed more than 100 articles to provide a critical review that would determine the limitation of using nanomaterials in water treatment at the commercial scale.

Activated carbon is known an as appropriate adsorbent due to its high adsorption capacity for most pollutants, especially heavy metals. In the present study, activated carbon was synthesized from orange wood by employing the chemical activation method. Additionally, cysteine amino acid was used to modify the activated carbon surface, leading to an enhancement in adsorption ability because of having a nitrogen group. Based on the results, the adsorption capacity of the modified activated carbon was obtained at 120 mg g-1 adsorbent. The parameters affecting adsorption such as the amount of used adsorbent, as well as solution pH, primary concentration, and contact time were optimized, followed by performing the adsorption process under optimal conditions. The optimal adsorption conditions included the pH of 6, contact time of 60 min, adsorbent amount of 50 mg, and primary cadmium concentration of 80 ppm. Further, kinetic and thermodynamic parameters were assessed and optimized. The results of which represented the best fit between adsorption with Langmuir isotherm and the pseudo-second-order kinetic model. The results represented that the quasi-second-order model with a higher regression coefficient (R2 = 0.97) described the experimental data better than the quasi-first-order one (R2 = 0.83). The adherence of adsorption kinetics to the pseudo-second-order model suggested a chemical interaction as the rate-determining step. Regarding adsorption thermodynamics, the effect of temperature was examined on adsorption by using Van't Hoff's equations, which reflect the endothermicity of the process.

In this study natural bentonite (NB) and acid-thermal co-modified bentonite (MB) were utilized as adsorbents for the removal of Thymol Blue (TB) from aqueous solution. The batch adsorption experiments were conducted under different experimental conditions. The artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS) were applied to estimate removal percentage (%) of TB. Mean squared error (MSE), root mean square error (RMSE) and coefficient of determination (R2) values were used to evaluate the results. In addition, the experimental data were fitted isotherm models (Langmuir, Freundlich and Temkin) and kinetic models (pseudo first order (PFO), pseudo second order (PSO) and intra-particle diffusion (IPD)). The adsorption of TB on both the NB and MB followed well the PSO kinetic model, and was best suited Langmuir isotherm model. When the temperature was increased from 298 K to 323 K for 20 mg/L of TB initial concentration, the removal percentage of TB onto the NB and MB increased from 74.91% to 84.07% and 81.19% to 93.12%, respectively. This results were confirmed by the positive ΔH° values indicated that the removal process was endothermic for both the NB and MB. The maximum adsorption capacity was found as 48.7805 mg/g and 117.6471 mg/g for the NB and MB, respectively (at 323 K). As a result, with high surface area and adsorption capacity, the MB is a great candidate for TB dye removal from wastewater, and the ANFIS model is better than the ANN model at estimating the removal percentage of the dye.

In this research, a response surface methodology (RSM) was used to investigate the effects of independent parameters (pH, contact time, temperature, adsorbent dosage, and initial concentration of pollutant), their simultaneous interactions, and quadratic effects on crystal violet adsorption onto two starch based materials in the form of batch experiments. The characterizing results indicated that there is no significant difference between the potato starch and synthesized starch phosphate, as phosphorylation has not changed the crystalline structure of starch inside the granules. The maximum removal efficiency of crystal violet ions was obtained 99 % at the optimum adsorption conditions of initial concentration 213.54 mg/L, adsorbent dosage 0.25 g, contact time 14.99 min, temperature 15 °C, and initial pH of solution 9. RSM outputs showed that the maximum adsorption of crystal violet ions by could be achieved by raising pH and adsorbent dosage, and decreasing the initial crystal violet concentration. While temperature and contact time are not effective parameters in crystal violet removal from aqueous solutions using synthesized starch phosphate. Generally, the RSM model is suitable to optimize the experiments for dye elimination by adsorption, where the modified starch phosphate would be an effective adsorbent for treating crystal violet solution.

The present study was carried out to investigate the adsorption and leaching behavior of Cu2+, Zn2+ and Pb2+ by sediments collected from the western banks of three different sectors along River Nile at Aswan governorate, Egypt. The feasibility of sediments for the removal of Cu2+, Zn2+ and Pb2+ from aqueous solutions was tested under the effect of three conditions (pH, initial metal concentration and contact time). By increasing pH, the adsorption of Cu2+ and Pb2+ by sediments decreased while that of Zn2+ increased. The optimum pH values for Cu2+, Zn2+ and Pb2+ removal were determined as 5, 8.5 and 5, respectively. The adsorption capacities of sediments for metal ions were in the order of Pb2+ > Cu2+ > Zn2+. The maximum uptake for Cu2+, Zn2+ and Pb2+ by sediments occurred at contact times of 48 h, 24 h and 72 h, respectively. Adsorption data were fitted well by Freundlich, Dubinin–Radushkevich and Temkin isotherms. The experimental results obtained were analyzed using two adsorption kinetic models, pseudo-first-order and pseudo-second-order, in which pseudo-second-order equation described the data more than pseudo-first-order one. The average leaching percentages of Cu2+, Zn2+ and Pb2+ from sediments were 0.77%, 2.72% and 0.38%, respectively, with respect to pH, 0.83%, 2.49% and 0.38%, respectively , with respect to temperature, and also 0.79%, 2.34% and 0.38%, respectively with respect to contact time. The leaching percentages of metal ions from sediments were in the order of Zn2+ > Cu2+ > Pb2+.

The present research investigates the ability of graphene oxide nanosheets for treatment of dairy wastewater, using In Situ Sludge Magnetic Impregnation” (ISSMI) to separate sludge after adsorption process. To increase the interaction between magnetic nanoparticles and graphene oxide, the former has been functionalized, using 3-Aminopropyl triethoxysilane, with the synthesized graphene oxide and magnetic nanoparticles being characterized by FT-IR, SEM, and NCHS analysis. The experiments have been conducted on the effluent of Pegah factory. The batch adsorption experiments have been carried out to investigate the effect of adsorbent dose, contact time, and pH on the removal of total nitrogen, total phosphorus, COD, and turbidity. At adsorbent dose of 320 mg L-1, the removal efficiencies of 90, 80, 84, and 94% have been observed for TN, TP, COD, and turbidity, respectively. The adsorbent data has been modeled by Langmuir and Freundlich isotherms, giving results that are compatible with Freundlich isotherm. TN, TP, and COD are mostly particulate materials in dairy wastewaters; therefore, when nanosheets aggregate, particulate materials are trapped between GO nanosheets; as a result, pollutants are distributed heterogeneously on the adsorbent's surface. Consequently, adsorption does not occur as monolayer on the surface of GO; for this reason, adsorption follows Freundlich model. Maximum absorption capacity of the adsorbent turns out to be 730 mg g-1 for total nitrogen, 600 mg g-1 for total phosphorus, 26000 mg g-1 for COD, and 5500 mg g-1 for turbidity. Adsorption kinetic has been studied with the first and second order equation, giving results that are compatible with second order equation.