The optimization of nickel ion (Ni2+) removal in aqueous solutions with various factors (initial Ni concentration, solution pH, adsorbent dosage, contact time), as affected by raw cow bone (RBO) and its biochar (bone char: BC; produced by pyrolysis processes at 500 °C and a residence time of 4 hours) as adsorbents was investigated by a three-level Box–Behnken model (BBM) under response surface methodology (RSM). A total of 29 experimental runs were set for each adsorbent, and the experimental data were fitted to the empirical model. To understand the Ni2+ adsorption processes better, the properties of RBO and BC were characterized using Fe-SEM, FT-IR, BET, XRD, and CHNS elemental analysis techniques. The BC characteristics showed that pyrolysis increased the specific surface area (by 100 times) and phosphate functional groups, but decreased the carbonate functional groups, and yielded a more irregular and rougher morphological surface compared to RBO. Based on BC's superior ion exchange mechanisms and physical electrostatic adsorption compared to RBO, the removal efficiency of Ni2+ by BC was higher in aqueous solutions. The numerical optimization of BBM revealed that the optimum removal by BC (82.56%) was obtained at an initial Ni2+ concentration of 30.79 mg L−1, pH of 6.99, adsorbent dose of 4.87 g L−1, and contact time of 57.82 min, with the desirability of "1". BC can be effectively used for Ni removal from Ni-contaminated aqueous solutions; still, the application of modification methods (e.g., physical and chemical activation) may be necessary to help remove more Ni2+ by BC.

The soil of many places of eastern India contains high amount of arsenic, due to several geogenic activities in this area. In the specific regions of the country where there is no such type of Geogenic activities, the soil is found to be almost free of arsenic. In such places where there are industries, the soil is being contaminated with the arsenic due to anthropogenic activities. One of such site which was selected for the study was in close vicinity to the textile industries in Jaipur, Rajasthan, India discharging their effluents having 423 µg/g arsenic. While the soil sample collected from the far eastern part of Tezpur Assam, India, contaminated by Geogenic sources contained 443µg/g arsenic. Four arsenite resistant bacterial strains were isolated from each of the samples. Strains SE-3 and TB-1 isolated from Jaipur and Tezpur, respectively showed highest minimum inhibitory concentration of 46.5mM and 38.7mM sodium arsenite. Based on 16S rDNA sequencing and nucleotide homology and Phylogenetics analysis strain, SE-3 was identified as Pseudomonas sp. SE-3 (accession no. KP730605) and TB-1 as Bacterium TB-1 (accession no KP866680). Complete oxidation of arsenite to less toxic form arsenate was observed in Pseudomonas sp. SE-3, while 64.6% by Bacterium TB-1. The arsenite oxidation was supported on the molecular level by confirming the presence of aox gene by PCR amplification. The enzyme activity of arsenite oxidase was also established. Arsenic hyper tolerant bacteria isolated from these soils having arsenite oxidizing ability show a promising way for the bioremediation of arsenic in contaminated soil.

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.

There is great competition to improve the performance of membranes for water treatment within the scope of the research, especially the problem of biofouling on the membrane as it is related to the performance and life of the membrane. This study introduces a new mixture of hybrid bioreactor membranes that combine oxidized multi-walled carbon nanotubes (OMWCNTs) with polyethersulfone (PES) using a phase inversion method, along with equal proportions of zinc oxide nanoparticles (ZnO NPs) and Arabic gum (AG) from an acacia tree, for application in a submerged membrane bioreactor to treat wastewater for a dairy product at the College of Agriculture / Baghdad University. The results when comparing the nascent composite membranes (PES / OMWCNTs / ZnO / AG) with that of (PES / OMWCNTs) indicated that the membrane mixed with ZnO / AG has more hydrophilic (16%) As well as reducing the negative charge on the surface of the membrane almost three times, As evidenced by the water contact angle test and the zeta potential data respectively, furthermore, the atomic force microscopy analysis showed that this improved membrane showed lower values of surface roughness (by 46.8%), and more flexible normal flux values (by almost doubling), Moreover, the rate of rejection increased when the bovine serum albumin (BSA) solution was passed a percentage (13%) when compared with PES / MWCNTs membrane. Importantly, the prepared membrane also presented removal efficiency of chemical oxygen demand (COD) was significantly 37.5% higher when compared with the commercial MBR system.

Severodvinsk city is the largest industrial center for the construction and repair of naval vessels in the NW Russia. The purpose of the presented study was to identify the main sources of pollution of the Severodvinsk industrial region and assess the ecological situation based on analysis of toxic metals in water and snow. Heavy metals content in water, melt snow filtrate and solid residue was measured using ICP-MS. On the urban area, there were high concentrations of Fe (up to 2843 MPC) in soluble form of snow, Al (up to 4680 MPC), Fe (up to 2807 MPC), Ni (up to 66.5 MPC), Pb (up to 44.7 MPC), Cd (up to 43.3 MPC), Cr (up to 43.2 MPC), Mn (up to 13.3 MPC), Co (up to 7.3 MPC), and As (up to 3.4 MPC) in insoluble form of snow, Fe (up to 56213 MPC) in water from wells. There were high values of mineralization (598 mg/L) and low pH values (to 5.21) in sites most susceptible to anthropogenic pollution. Statistical analysis showed that most of the metals in snow cover were linked with each other by strong correlation (r>0.9). Calculation of toxicological indices HMEI, HMPI, HMTL, HI and CR showed extremely high and dangerous for public health level of heavy metal pollution in the Severodvinsk industrial district. Studied radiation parameters of water from wells were within acceptable limits. Results obtained indicate the need to change the type of fuel in thermal power plant and reduce toxic emissions from the shipbuilding enterprises.

A green approach was employed to fabricate ZSM-5 zeolite from expanded perlite and reduced graphene oxide (rGO) in the presence of the synthesized ZSM-5 zeolite to produce ZSM-5@rGO composite by one-step synthesis process via hydrothermal treatment. ZSM-5@rGO composites were characterized by various techniques such as scanning electron microscopy (SEM),  X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, Raman spectroscopy, and N2 desorption–adsorption. The results showed that ZSM-5@rGO composite have a large surface area, uniform distribution and orderly crystal form. Moreover, the synthesized composites were evaluated as an adsorbent for removing cationic dye, methylene blue (MB), from an aqueous solution. The influence of factors on the adsorption, such as adsorption time, adsorbent dosage, initial dye concentration, and pH of solution, were investigated. The results of isothermal adsorption showed that the adsorption process was fit for both Langmuir and Freundlich models, and the highest adsorption capacity of ZSM-5@rGO composite for MB dye was 95.87 mg/g at environment temperature (30 oC). In addition, the study of adsorption kinetics indicated that the adsorption was consistent with the pseudo-second-order kinetic model with correlation coefficients of 0.9962. From these results, it can be confirmed that ZSM-5@rGO composite uses silicoaluminate as economical starting material with relatively high adsorption capacity and removal efficiency, which is a promising application for treating wastewater on a large scale.

Microplastics are widely used to manufacture diverse products such as textiles, skin care products, and household products such as detergents and soaps. However, microplastic pollution and its potential health risks are raising concerns worldwide. This study characterized and determined the safety of microplastics in water and sediments obtained from three locations, namely Ibeshe, Amuwo Odofin, and Ojo along Badagry lagoon, Lagos, Nigeria. The samples of the lagoon's surface water and sediments were treated and analyzed for the abundance of microplastics, as well as their shapes, sizes, and types of polymers. The risk index of the polymers in the microplastics was also estimated. Microplastics were found to be more abundant (p ≤ 0.05) in the sediments (283–315 particles/kg) than in the surface water (108–199 particles/L). In both the water and sediments at all the locations, the dominant shapes were fibers (52%–90%), followed by fragments (3%–32%) and films (1%–25%). In order of significance, the microplastic size range of 0-100µm and 100-500µm dominated the surface water, while the size range of 1000-5000µm and 500-1000µm dominated the sediments at all the locations. The dominant polymers in both the water and sediments at all the locations were polyethylene, polypropylene, and polyamide, while the least was polystyrene. In both the water and sediments at all the locations, the dominant risk score among the polymers is III (moderate risk). The results obtained suggest that microplastic pollution poses environmental and health risks to the lagoon, aquatic organisms, and humans. As such, the lagoon required microplastic remediation and control.

The salt obtained from salt sources has a low purity level and contains contaminants. The primary contaminants in the brines were eliminated in this investigation by using analytical separation (titration) techniques. Following the purification method, sodium hydroxide (NaOH) was added to magnesium chloride (MgCl2) to make magnesium hydroxide (Mg(OH)2) coagulate in pH control. This was done by PID and Self-Tuning PID (STPID) Control. Using STPID Control, hydrochloric acid (HCl) at a rate of 20% was employed as an effective acid current, MgCl2 as a coagulant, and NaOH at a rate of 10% as a neutralization base throughout the process. The coagulation technique was carried out with pH values of 7, 9, and 11, respectively. The pH of the medium was adjusted using the PID and STPID algorithms, as well as an on-line computer control system. As the system model, ARMAX was employed. As a forcing function, a pseudo-random binary sequence (PRBS) was used to identify the dynamics of the process to be controlled, and the system output was measured. The Bierman algorithm was used to evaluate the model parameters. The STPID controller's tuning parameters were calculated. Following the coagulation method, an analytical titration procedure was used to find out if there are any trace amounts of Mg(OH)2 in the current environment, and a settlement percentage of 90% to 95% was found. To get the best coagulation, a pH value of 11 was chosen as the optimal value based on the performed calculations.

In this research, the capability of vermiculite in arsenic extraction, associated with characterizing its main properties was evaluated. To address this purpose, vermiculite was artificially contaminated with arsenic at 7 and 28-day intervals. Then, arsenic was extracted from contaminated soils by different extractants. Various physical and mechanical tests were performed to investigate the effect of arsenic as an anionic contaminant on the properties of the vermiculite, as well as to evaluate how the properties of the contaminated soil were altered by the extraction process. The carbonate bonding phase was probably mainly responsible for the adsorption and fixation of arsenic with more than 50% portion among measured fractions at different curing times. Based on the vermiculite condition, hydrochloric acid was the best extractant for removing arsenic in all studied samples (around 3 -18 % more than other extractants). The clay soil demonstrated few changes due to arsenic contamination and modification. In general, the most promising characteristics of vermiculite as clay liner are its stability after contamination due to high CEC and SSA; however, its workability and strength (UCS between 110 to 220 kPa at different soil conditions) is a challenge and must be improved by adding coarser fractions like silt particles. In general, the results of this study regarding the effects of arsenic contamination and extraction onto vermiculite’s physical properties can provide appropriate information for researchers and geo-environmental engineers.

The optimal performances of starches produced from two cassava varieties–Manihot aipi (SMA) and Manihot palmate (SMP) as bioflocculants for the treatment of textile wastewater were investigated in this study. The central composite rotatable design was used to investigate the effects of varying dosages of each cassava starch, wastewater-pH, and settling time on the turbidity removal from the wastewater with alum as the primary coagulant. Highly significant second-order multilinear quadratic regression models were developed from the experimental data, resulting in a very high coefficient of determination (r2) values of 0.999 for the SMA and 1.000 for the SMP models. The optimum cassava doses of 50 and 150 mg/L, pH-values of 6.5 and 8.0, and settling times of 95 and 77 minutes led to predictive maximum turbidity removals of 98.35 and 88.87%% with desirability functions of 0.95 and 0.63 for the SMA and SMP, respectively. The corresponding observed turbidity removal recorded at these optimum conditions were 88.72% and 88.52% for the SMA and SMP, respectively. At these optimum conditions, there was no significant difference between the predicted and observed turbidity removed from the wastewater at a p≤0.05 significance level. Verification of the Jar tests showed a good agreement between the experimental data and the models and confirmed that the SMA was superior to the SMP in supporting the alum to remove turbidity from the textile wastewater. As a result, the study revealed that Manihot aipi starch has more flocculating capability than Manihot palmate for the treatment of textile wastewater.