Response surface modeling and optimization of chromium(VI) removal from aqueous solution using Tamarind wood activated carbon in batch process

Application of artificial intelligence in (waste)water disinfection: Emphasizing the regulation of disinfection by-products formation and residues prediction

Water/wastewater ((waste)water) disinfection, as a critical process during drinking water or wastewater treatment, can simultaneously inactivate pathogens and remove emerging organic contaminants. Due to fluctuations of (waste)water quantity and quality during the disinfection process, conventional disinfection models cannot handle intricate nonlinear situations and provide immediate responses. Artificial intelligence (AI) techniques, which can capture complex variations and accurately predict/adjust outputs on time, exhibit excellent performance for (waste)water disinfection. In this review, AI application data within the disinfection domain were searched and analyzed using CiteSpace. Then, the application of AI in the (waste)water disinfection process was comprehensively reviewed, and in addition to conventional disinfection processes, novel disinfection processes were also examined. Then, the application of AI in disinfection by-products (DBPs) formation control and disinfection residues prediction was discussed, and unregulated DBPs were also examined. Current studies have suggested that among AI techniques, fuzzy logic-based neuro systems exhibit superior control performance in (waste)water disinfection, while single AI technology is insufficient to support their applications in full-scale (waste)water treatment plants. Thus, attention should be paid to the development of hybrid AI technologies, which can give full play to the characteristics of different AI technologies and achieve a more refined effectiveness. This review provides comprehensive information for an in-depth understanding of AI application in (waste)water disinfection and reducing undesirable risks caused by disinfection processes.

A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning

Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era of remarkable research and innovation. This review article thoroughly examines the recent advancements in the field, focusing on the interplay between PV systems and water desalination within the framework of AI and ML applications, along with it analyses current research to identify significant patterns, obstacles, and prospects in this interdisciplinary field. Furthermore, review examines the incorporation of AI and ML methods in improving the performance of PV systems. This includes raising their efficiency, implementing predictive maintenance strategies, and enabling real-time monitoring. It also explores the transformative influence of intelligent algorithms on desalination techniques, specifically addressing concerns pertaining to energy usage, scalability, and environmental sustainability. This article provides a thorough analysis of the current literature, identifying areas where research is lacking and suggesting potential future avenues for investigation. These advancements have resulted in increased efficiency, decreased expenses, and improved sustainability of PV system. By utilizing artificial intelligence technologies, freshwater productivity can increase by 10 % and efficiency. This review offers significant and informative perspectives for researchers, engineers, and policymakers involved in renewable energy and water technology. It sheds light on the latest advancements in photovoltaic systems and desalination, which are facilitated by AI and ML. The review aims to guide towards a more sustainable and technologically advanced future.

Critical layer in liquid-solid system influencing the remediation of chromium using zeolite-supported sulfide nano zero-valent iron

Sulfidated nano zero-valent iron particles were immobilized on ZSM-5 zeolite (Z/S-nZVI) and used for hexavalent chromium (Cr(VI)) remediation. The performance of Z/S-nZVI improved with the increase in Cr(VI) concentration (< 60 mg/L), while the performance significantly decreased for a Cr(VI) concentration of more than 60 mg/L. The adsorption behavior for Cr(VI) was different from that reported in previous studies. The improved performance can be tailored for increasing efficiency of nano zero-valent iron (nZVI) corrosion, while the degree of corrosion of nZVI was affected by the concentration of the pollutant as discussed by kinetics, X-ray diffraction (XRD) and X-ray photoelectron spectrometer (XPS) analyses. The experiments for the dissolution of ferrous ions and the dosage of adsorbent demonstrated that the critical layer in the liquid-solid system changed with the increase in the concentration of Cr(VI) (Cr(VI): Z/S-nZVI > 0.6). Moreover, the removal mechanisms of Cr(VI) were elucidated through XRD, transmission electron microscopy (TEM) and XPS techniques. This results demonstrate that the species of chromium in the critical layer changed from Cr(III) to Cr(VI) as the concentration of chromium increased from low to high. Furthermore, the critical layer was composed of Cr(VI), Fe(II), O and H elements. Additionally, the experiments of coexisting ions and aging time confirmed that Z/S-nZVI possessed high selectivity and stability to ensure efficiency and cost-effectiveness in practical applications.

Efficient Cr(VI) sequestration from aqueous solution by chemically modified Garcinia kola hull particles: characterization, isotherm, kinetic, and thermodynamic studies

There is a need for the removal of hexavalent chromium from contaminated water prior to its discharge into the environment, as part of industrial effluents, due to its toxic nature. In this present study, an adsorbent prepared via chemical modification of Garcinia kola hull particles (GK-HP) using NaOH was applied for Cr(VI) sequestration from aqueous solution. Both the raw (rGK-HP) and chemically modified Garcinia kola hull particles (cMGK-HP) were characterized using BET, SEM, XRD, FTIR, TGA, and EDS. The effects of pH, contact time, adsorbent dose, adsorbate initial concentration, and temperature on Cr(VI) sequestration were examined. The adsorbent, cMGK-HP, proved to be more effective for the adsorption process than rGK-HP with 96.25% removal efficiency at a pH of 2, a contact time of 60 min, an adsorbent dose of 5 g/L, Cr(VI) initial concentration of 20 mg/L and a temperature of 40°C. Isotherm and kinetic studies showed experimental data to be well-fitted with Langmuir isotherm and follow the pseudo-second-order kinetic model. The thermodynamic study revealed adsorption nature to be feasible, occur via physisorption, spontaneous, and exothermic. Changes in morphological structure, textural property, spectral peak, phase composition, and chemical composition of adsorbents before and after Cr(VI) sequestration from solution were proved by SEM, BET, FTIR, XRD, and EDS analyses, respectively. cMGK-HP possessed excellent reusability attribute and high thermal stability as shown by TGA. In conclusion, the adsorption capacity of cMGK-HP is better than many other adsorbents generated from agrowastes used in previous studies for Cr(VI) removal.

Investigation on Applying Biodegradable Material for Removal of Various Substances (Fluorides, Nitrates and Lead) from Water

Sapropel was used as a biodegradable material for water treatment. Sapropel is a sedimentary layer of a mix of organic and inorganic substances accumulated in the bottoms of lakes for thousands of years. It is a jelly-like homogeneous mass and has properties of sorption. Sapropel is used as a biosorbent and an environment-friendly fertiliser, and it is used in building materials and in the beauty industry as well. In water, there are abundant various solutes that may cause a risk to human health. Such substances include fluorides, nitrates and lead in different sources of water. The goal of this investigation is to explore and compare the efficiencies of removal of different pollutants (fluorides, nitrates and lead) from aqueous solutions upon using sapropel as a sorbent. In this research, various doses of sapropel (0.1, 0.5, 1, 5, 10, 20, 50, 100 and 200 g/L) and various mixing times (15, 30, 60, 90 and 120 min) were used for removal of fluorides, nitrates and lead from aqueous solutions. It was found that the maximum efficiency (up to 98.57%) of lead removal from aqueous solutions by sapropel was achieved when the minimum doses of it (0.1 and 0.5 g/L) were used. The most efficient removal of fluorides (64.67%) was achieved by using 200 g/L of sapropel and mixing for 120 min. However, sapropel does not adsorb nitrates from aqueous solutions.

Insights into the electron activation mechanisms at the micro level by nano zero-valent iron supported by molybdenum disulfide (nZVI@MD) from preparation to application

Both molybdenum disulfide (MoS2) and nano zero-valent iron (nZVI) exhibit excellent adsorption abilities. However, the constrained conductivity of MoS2 and the lack of selectivity of nZVI for electron transfer still pose challenges. In this study, we designed a series of novel nano zero-valent iron supported by molybdenum disulfide composites (nZVI@MD) with multiple electron-rich active sites, including iron dopant replacement, iron atom intercalation and exposed Mo4+, for effective removal of Cr(VI). Results showed that preparation temperature and the amount of MoS2 added were identified as the two most significant factors affecting the reduction properties of nZVI@MD. Systematic experiments revealed that the nZVI@MD exhibited good anti-interference performance, stability and reusability due to its excellent electron selectivity. Characterization results exhibited that iron atoms replaced the sulfur vacancies in MoS2 and inserted into an intercalation of MoS2 during the preparation process. The mechanisms underlying the uptake of Cr(VI) by nZVI@MD can be proposed as follows: (i) electrostatic interactions, (ii) reduction reaction, and (iii) co-precipitation involving Fe-O-Cr. Furthermore, nZVI@MD exhibited excellent electron activity, hydrophilicity and oxidation resistance, confirmed by density functional theory (DFT) calculations. This work provided new strategies and mechanistic insights for the rational design of adsorbents.

Computational fluid dynamic and response surface methodology coupling: A new method for optimization of the duct to be used in ducted wind turbines

Wind energy technology, particularly power generation by wind turbines, has received substantial attention due to resource depletion and global warming concerns. These concerns highlight the importance of conducting studies to enhance their efficiency by increasing their power output. The goal of this work was to combine the RSM (Response Surface Methodology (RSM) with CFD (Computational Fluid Dynamics) to discover the optimal design parameters and conditions for ducted wind turbines. To that purpose, twenty-seven runs were chosen using Central Composite Design (CCD) in the design phase. Duct simulation was performed by employing different dimensional parameters and feeding them into a third-order polynomial that fitted to an eight-order function. The analyzed runs discussed the maximum available wind velocity and power at the throat area of the various designed ducts. The wind-enhanced power and speed were studied under different design parameters, and their effects were discussed. The optimum design conditions to capture maximum power were 0.16 m, 2, and 1.5 for design parameters of the duct's throat diameter, contraction ratio, and length-to-throat diameter ratio, respectively. A good selection of design parameters can increase the outpour power up to six times as a general result. By modeling CFD simulations using the RSM method, it is possible to minimize the time and cost of calculation to find the optimized range for the design parameters of the ducts.

Heavy metals in influent and effluent from 146 drinking water treatment plants across China: Occurrence, explanatory factors, probabilistic health risk, and removal efficiency

Heavy metals (HMs) in drinking water have drawn worldwide attention due to their risks to public health; however, a systematic assessment of the occurrence of HMs in drinking water treatment plants (DWTPs) at a large geographical scale across China and the removal efficiency, human health risks, and the correlation with environmental factors have yet to be established. Therefore, this study characterised the occurrence patterns of nine conventional dissolved HMs in the influent and effluent water samples from 146 typical DWTPs in seven major river basins across China (which consist of the Yangtze River, the Yellow River, the Songhua River, the Pearl River, the Huaihe River, the Liaohe River and the Haihe River) for the first time and removal efficiency, probabilistic health risks, and the correlation with water quality. According to the findings, a total of eight HMs (beryllium (Be), antimony (Sb), barium (Ba), molybdenum (Mo), nickel (Ni), vanadium (V), cobalt (Co) and titanium (Ti)) were detected, with detection frequencies in influent and effluent water ranging from 2.90 (Mo) to 99.30% (Ba) and 1.40 (Ti) to 97.90% (Ba), respectively. The average concentration range was 0.41 (Be)- 77.36 (Sb) μg/L. Among them, Sb (exceeding standard rate 8%), Ba (2.89%), Ni (21.43%), and V (1.33%) were exceeded the national standard (GB5749-2022). By combining Spearman's results and redundancy analysis, our results revealed a close correlation among pH, turbidity (TURB), potassium permanganate index (COD_Mn), and total nitrogen (TN) along with the concentration and composition of HMs. In addition, the concentration of HMs in finished water was strongly affected by the concentration of HMs in raw water, as evidenced by the fact that HMs in surface water poses a risk to the quality of finished water. Metal concentration was the primary factor in assessing the health risk of a single metal, and the carcinogenic risk of Ba, Mo, Ni, and Sb should be paid attention to. In DWTPs, the removal efficiencies of various HMs also vary greatly, with an average removal rate ranging from 16.30% to 95.64%. In summary, our findings provide insights into the water quality and health risks caused by HMs in drinking water.

A review of novel green adsorbents as a sustainable alternative for the remediation of chromium (VI) from water environments

The presence of heavy metal, chromium (VI), in water environments leads to various diseases in humans, such as cancer, lung tumors, and allergies. This review comparatively examines the use of several adsorbents, such as biosorbents, activated carbon, nanocomposites, and polyaniline (PANI), in terms of the operational parameters (initial chromium (VI) concentration (C_o), temperature (T), pH, contact time (t), and adsorbent dosage) to achieve the Langmuir's maximum adsorption capacity (q_m) for chromium (VI) adsorption. The study finds that the use of biosorbents (fruit bio-composite, fungus, leave, and oak bark char), activated carbons (HCl-treated dry fruit waste, polyethyleneimine (PEI) and potassium hydroxide (KOH) PEI-KOH alkali-treated rice waste-derived biochar, and KOH/hydrochloric acid (HCl) acid/base-treated commercial), iron-based nanocomposites, magnetic manganese-multiwalled carbon nanotubes nanocomposites, copper-based nanocomposites, graphene oxide functionalized amino acid, and PANI functionalized transition metal are effective in achieving high Langmuir's maximum adsorption capacity (q_m) for chromium (VI) adsorption, and that operational parameters such as initial concentration, temperature, pH, contact time, and adsorbent dosage significantly affect the Langmuir's maximum adsorption capacity (q_m). Magnetic graphene oxide functionalized amino acid showed the highest experimental and pseudo-second-order kinetic model equilibrium adsorption capacities. The iron oxide functionalized calcium carbonate (IO@CaCO₃) nanocomposites showed the highest heterogeneous adsorption capacity. Additionally, Syzygium cumini bark biosorbent is highly effective in treating tannery industrial wastewater with high levels of chromium (VI).

Modified carbon paste ion selective electrode for determining Cr(iii) ions in aqueous solutions and some real samples using tetragonal zirconia nanoparticles

Tetragonal zirconia (t-ZrO₂) nanoparticles (ionophore) are used in newly designed and improved ion selective electrodes for chromium ion detection as an alternative, low-cost, high-precision, and selectivity method. Tetragonal zirconia nanoparticles were synthesized using a modified co-precipitation technique and calcined at 1000 °C for an hour. The phase composition, surface area, microstructure, pore size and particle size of synthesized t-ZrO₂ nanoparticles were examined using the X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), transmission electron microscope (TEM) and scanning electron microscopy (SEM) attached with an EDAX unit, respectively. Results from XRD showed that the t-zirconia was synthesized and have nanocrystallites size about 20.2 nm. The nano size of t-ZrO₂ was confirmed by the SEM and TEM (the particle size between 26.48 and 40.4 nm), the mesoporous character (average pore size about 4.868 nm) and large surface area (76.2802 m² g^-1) was confirmed by BET analysis. The paste composition with 67.3 : 30.5 : 2.7 (wt%) graphite, t-ZrO₂, and TCP, respectively, exhibited the best results. With a detection limit of 1.0 × 10^-8 mol L^-1, the electrode displayed a good Nernstian slope of 19.50 ± 0.10 mV decade^-1 over the concentration range from 1.0 × 10^-2 to 1.0 × 10^-8 mol L^-1 of Cr(iii) ions. The built-in sensor displayed a quick response time (7 s), was highly thermally stable in the range of 10 to 60 °C without departing from Nernstian behaviour and could be used for about 60 days in the pH range of 2.0 to 6.0. The electrode demonstrated excellent selectivity for the Cr(iii) ion towards a variety of metal ions. For chromium ion determination, numerous spiked real samples, including honey, water, tea, coffee, milk, cheese, and cosmetics, were used. Validation methods were used, and the results showed that there is no significant difference between the two methods (ICP and ISE) at a 95% confidence level. In several real water samples, the estimated limits of detection, limits of quantification, percent recovery, standard deviation, and relative standard deviation showed the effectiveness of the proposed electrode in the potentiometric detection of Cr(iii) ions.

Synthesis and Structure of a Copper-Based Functional Network for Efficient Organic Dye Adsorption

In the work, by incorporating polyoxometalates (POMs) into a copper(II)-based network, a novel three-dimensional (3D) porous framework, [Cu₁₇Cl₃(trz)₁₂]H₃[GaW₁₂O₄₀]·9H₂O (Cu-GaW-TRZ), was successfully prepared and explored for the adsorption of dyes. The adsorption capacity of Cu-GaW-TRZ was calculated as 13.11 mg/g, and the dye adsorption rate equaled 96.2% for the adsorption of methylene blue (MB). Furthermore, this recyclable adsorbent is stable enough without obvious loss of adsorption capacity for at least five runs. Meanwhile, the structure of the macropores is suitable for the entry of large molecular dyes, and [GaW₁₂O₄₀]^5- also can achieve efficient adsorption for cationic dyes. The results displayed a pseudo-second-order kinetic model and were well matched for MB adsorption onto Cu-GaW-TRZ. The free energy, entropy, and enthalpy of the thermodynamic parameters for the adsorption of MB were calculated, which revealed that the adsorption process was befitting for the adsorption of MB.

A facile modification of cation exchange resin by nano-sized goethite for enhanced Cr(VI) removal from water

A novel macroporous strong acidic cation exchange resin (D001) modified by nano-sized goethite (nFeOOH@D001) was fabricated by using a facile ethanol dispersion and impregnation method, and its efficiency for Cr(VI) removal was tested thereafter. Due to the dispersing effect of ethanol, FeOOH particles of 20-150 nm were coated on the D001 surfaces. The nFeOOH@D001 obtained a Cr(VI) removal efficiency and capacity of 80.2% and 7.4 mg/g respectively, 5 times and 8 times higher than that of the pristine D001. The Cr(VI) removal by nFeOOH@D001 followed the pseudo second-order kinetics and the Langmuir adsorption model. Column experiments also demonstrated that the nFeOOH@D001 exhibited a much better ability to remove Cr(VI) as compared to the D001. Additionally, the nFeOOH@D001 showed a potential for reusability and renewability. The adsorbed nFeOOH@D001 could be easily desorbed by 0.1 M acetic acid and a reuse efficiency of 92.7% could be maintained after 4 desorption-adsorption cycles. The used nFeOOH@D001 could be eluted by 0.1 M HCl to remove nFeOOH, and the renewed D001 could be recoated by nFeOOH and achieved a regeneration rate of 97.8% for Cr(VI) removal. The above results indicated that nano-sized goethite modification is a promising method to endow D001 with the ability to remove Cr(VI) from water.

Review on COD and ammoniacal nitrogen removal from landfill leachate using low-cost adsorbent

The rapid generation rate of solid waste is due to the increasing population and industrialization. Nowadays, solid waste has been a major concerning problem in handling and disposal thus adsorption treatment process has been introduced which is an effective and low-cost method in removing organic and inorganic compounds from leachates such as chemical oxygen demand (COD) and ammoniacal nitrogen (NH₃-N). A most commonly adsorbent used for the removal of organic and inorganic compounds is activated carbon (AC), yet the main disadvantage is being too expensive in cost. Many researchers tried to use low-cost adsorbent waste materials, such as peat soil, limestone etc. This review article reveals a list of low-cost adsorbent and their capacity of adsorption for the removal of COD and NH₃-N. Furthermore, the preparation of these low-cost adsorbents as well as their removal efficiencies, relative cost, and limitation are discussed. The most efficient, cost-effective, and environment-friendly adsorbent can be used for the removal of COD and NH₃-N thus can be provided for commercial usage or water treatment plant.Implications: The concentration of organic constituents (COD) and ammonia nitrogen in stabilized landfill leachate has significant strong influences of human health and environmental. This review article shows the list of low-cost adsorbent (i.e., Activated carbon, Peat soil, Zeolite, Limestone, and cockle shell and their capacity of adsorption for the removal of COD and ammonia nitrogen. This would be greatly applicable in future research era as well as conventionally minimizing high-cost materials use and thereby lowering the operating cost of leachate wastewater treatment.

Optimization of Fluoride Adsorption on Acid Modified Bentonite Clay Using Fixed-Bed Column by Response Surface Method

Using small-scale batch tests, various researchers investigated the adsorptive removal of fluoride using low-cost clay minerals, such as Bentonite. In this study, Column adsorption studies were used to investigate the removal of fluoride from aqueous solution using acid-treated Bentonite (ATB). The effects of initial fluoride concentration, flow rates, and bed depth on fluoride removal efficiency (R) and adsorption capability (qe) in continuous settings were investigated, and the optimal operating condition was determined using central composite design (CCD). The model's suitability was determined by examining the relationship between experimental and expected response values. The analysis of variance was used to determine the importance of independent variables and their interactions. The optimal values were determined as the initial concentration of 5.51 mg/L, volumetric flow rate of 17.2 mL/min and adsorbent packed-bed depth of 8.88 cm, with % removal of 100, adsorptive capacity of 2.46 mg/g and desirability of 1.0. This output reveals that an acid activation of Bentonite has made the adsorbent successful for field application.

Mixed metal ferrite (Mn0.6Zn0.4Fe2O4) intercalated g-C3N4nanocomposite: efficient sunlight driven photocatalyst for methylene blue degradation

Visible active mixed metal ferrite intercalated semiconductor photocatalyst Mn_0.6Zn_0.4Fe₂O₄/g-C₃N₄was prepared via facile hydrothermal and liquid assembly method for methylene blue (MB) dye degradation. The prepared samples were well characterized in term of their functional groups, crystallinity, elemental analysis, surface morphology using Fourier transform infrared spectroscopy, x-ray diffraction spectroscopy, energy dispersive x-ray, and scanning electron microscopy, respectively. The optical response of catalysts was checked by estimating the energy band gap (E_g) of semiconductor photocatalysts using UV-vis spectroscopy. The photoluminescence spectroscopy was also performed to estimate the reduction in emission intensity after insertion of g-C₃N₄into Mn_0.6Zn_0.4Fe₂O_4.The novel composition of Mn_0.6Zn_0.4Fe₂O₄with g-C₃N_4,improved the optical response of pristine photocatalysts due to the reduction in the energy band gap and insertion of heterojunction. The surface area analysis of Mn_0.6Zn_0.4Fe₂O₄and Mn_0.6Zn_0.4Fe₂O₄/g-C₃N₄were acquired by Brunauer-Emmett-Teller. Point zero charge was also determined to observe the surface behavior of composite under different solution pH. Various parameters such as pH, catalyst dose, oxidant dose, irradiation time and initial dye concentration were optimized, and their effects were studied in photo-Fenton process. It was observed that 98% MB dye was degraded under optimized conditions (pH = 8, composite dose = 50 mg/100 ml, oxidant dose = 7 mM, initial dye conc. = 10 ppm, and irradiation time = 120 min). The results showed that when the ferrites of mixed metals (Mn, Zn) were used with g-C₃N₄their photocatalytic activity enhanced due to mutual effect of both mixed metals ferrite and g-C₃N₄, which is considerably higher than their individual effect already reported. Furthermore, the combined effect of independent variables was evaluated by response surface methodology.

Optimization of Progressive Freezing for Residual Oil Recovery from a Palm Oil-Water Mixture (POME Model)

Oil and grease remain the dominant contaminants in the palm oil mill effluent (POME) despite the conventional treatment of POME. The removal of residual oil from palm oil-water mixture (POME model) using the progressive freezing process was investigated. An optimization technique called response surface methodology (RSM) with the design of rotatable central composite design was applied to figure out the optimum experimental variables generated by Design-Expert software (version 6.0.4. Stat-Ease, trial version). Besides, RSM also helps to investigate the interactive effects among the independent variables compared to one factor at a time. The variables involved are coolant temperature, X _A (4-12 °C), freezing time, X _B (20-60 min), and circulation flow, X _C (200-600 rpm). The statistical analysis showed that a two-factor interaction model was developed using the obtained experimental data with a coefficient of determination (R ²) value of 0.9582. From the RSM-generated model, the optimum conditions for extraction of oil from the POME model were a coolant temperature of 6 °C in 50 min freezing time with a circulation flowrate of 500 rpm. The validation of the model showed that the predicted oil yield and experimental oil yield were 92.56 and 93.20%, respectively.

Response Surface Design for Removal of Lead by Different Lactic Acid Bacteria

Background: Toxic heavy metals, such as lead, are widely used in industry and may cause serious health problems and ecological hazards for living organisms. Objectives: The current study aimed to investigate the removal efficiency of lead by Lactobacillus strains using a methodological approach. Methods: After selecting the bacteria with the maximum metals removal ability, experiments were conducted according to (i) the Plackett-Burman design (Minitab18 program) to screen several significant process factors and (ii) Central Composite Design (Design-Expert 11.1.2.0 program) to find out the optimum process conditions for the maximum capacity of metal removal efficiency. Results: The optimum pH, metal, and bacterial concentration were 6.76, 391 mg.L-1, and 4.60 g.L-1 for lead removal ability of L. acidophilus ATCC4356. A quadratic model was developed to correlate the variables with removal efficiency. According to the results, this model was not statistically significant (P > 0.05). Conclusions: The experimental removal efficiencies at the optimum condition for lead by L. acidophilus ATCC4356 (73.9%) were consistent with the predicted values. Consequently, due to their appreciate efficiency and the lower cost of the lead removal ability, these two bacteria may be a candidate as good biosorbents. The results also confirmed that the Response Surface Methodology is an appropriate methodology for modeling of removal efficiency.

Parametric Optimization in Rougher Flotation Performance of a Sulfidized Mixed Copper Ore

The dominant challenge of current copper beneficiation plants is the low recoverability of oxide copper-bearing minerals associated with sulfide type ones. Furthermore, applying commonly used conventional methodologies does not allow the interactional effects of critical parameters in the flotation processes to be investigated, which is mostly overlooked in the literature. To tackle this issue, the present paper aimed at characterizing the behavior of five key effective factors and their interactions in a sulfidized copper ore. In this context, dosage of collector (sodium di-ethydithiophosphate, 60–100 g/t), depressant (sodium silicate, 80–120 g/t) and frother (methyl isobutyl carbinol (MIBC), 6–10 g/t), pulp pH (7–11) and agitation rate (900–1300 rpm) were examined and statistically analyzed using response surface methodology. Flotation experiments were conducted in a Denver type agitated flotation cell at the rougher stage. The experimental results showed that increasing the pH (from 8 to 10) at low agitation rate (1000 rpm) enhanced the recovery from 80.36% to 85.22%, while at high agitation rate (1200 rpm), a slight declination occurred in the recovery. Meanwhile, increasing the collector dosage at a lower frother value (7 g/t), caused a reduction of about 4.44% in copper recovery owing to the interactions between factors, whereas at a higher frother level (9 g/t), the recovery was almost unchanged. The optimization process was also performed using the goal function approach, and maximum copper recovery of 92.75% was obtained using ~70 g/t collector, 110 g/t depressant, 7 g/t frother, pulp pH of 10 and 1000 rpm agitation rate.

Application of ANN and RSM on fluoride removal using chemically activated D. sissoo sawdust

Response surface methodology (RSM) and artificial neural network (ANN) were used to generate a model for the optimization of fluoride removal using chemically activated Dalbergia sissoo sawdust (CADS). The single and collective effects of process parameters, i.e., solution pH, CADS dose, initial fluoride concentration, and contact time, were studied. The point of zero charge was found to be 4.2 with zeta potential analysis. In the first phase, a single-parameter study was performed to reveal dependency of fluoride removal on a particular process parameter. Positive effects of increment in CADS dose and contact time and negative effects of solution pH and initial fluoride concentration were observed. The second phase included RSM in which analysis of variance (ANOVA) was applied to test the feasibility of the mathematical model. The F value 1.91, R² value 0.87, and P value 0.11 show significance of the proposed model. Results obtained from the experiment set for central composite design (CCD) were used to predict the ANN response. Reasonable acceptable values of regression for training, test, and validation (0.76, 0.93, and 0.37) represent the suitability of the model. The ANN predicted 22.1% fluoride removal, which was close to the actual value (20.1%) and was comparable with CCD prediction (25.0%). BET surface area of CADS was found to be 76.33 m²/g. FTIR was performed to recognize the functional groups available for fluoride binding while SEM and EDX were conducted to ensure the changes in adsorbent surface morphology. Regeneration of CADS was feasible using an alkali medium. This study shows that CADS can be used for fluoride removal from aqueous stream in an efficient way.

A review on the applicability of activated carbon derived from plant biomass in adsorption of chromium, copper, and zinc from industrial wastewater

Metal ion contamination in wastewater is an issue of global concern. The conventional methods of heavy metal removal from wastewater have some drawbacks, ranging from generation of sludge to high cost of removal. Adsorption technique for copper(II), zinc(II), and chromium(VI) using activated carbon has been found efficient. However, it is not economical on a large scale. This, therefore, necessitates the search for economical and readily available plant biomass-based activated carbons for the sequestration of the metal ions. This review presents the state of the art on the adsorption of copper(II), zinc(II), and chromium(VI) from industrial wastewater. Based on the literature review presented, the groundnut husk and corncob based activated carbons were found to possess the maximum adsorption capacities for copper(II), zinc(II), and chromium(VI) removal, when compared with the other plant biomass-based activated carbons. The high values of the adsorption capacities obtained were as a result of the isotherms and pH of the adsorbent as well as the initial concentration of the metal solutions. From the review, the equilibrium data fitted better with Langmuir and Freundlich isotherms than with other isotherms. Research gaps were identified which include a need to investigate the kinetic and the thermodynamic behaviors of the metal ions onto the studied adsorbents. Furthermore, a comparative analysis of the three types of activation of the adsorbents should be investigated using single and multi-metals. The optimization of particle size, contact time, temperature, initial concentration, and adsorbent dosage for adsorption of copper(II), zinc(II), and chromium(VI) onto the studied adsorbents using response surface methodology is equally required.

Insights into the competitive adsorption of pollutants on a mesoporous alumina–silica nano-sorbent synthesized from coal fly ash and a waste aluminium foil

A highly efficient and low-cost alumina–silica nano-sorbent was fabricated and characterized to understand the key factors responsible for its superiority over the existing adsorbents in treating the industry-discharged wastewater for the removal of dyes and heavy metals. As compared to the properties of raw fly ash, the following fundamental improvements were observed for the alumina–silica nano-sorbent: (a) transformation of throttled mesopores into slit-type pores, (b) increment in the surface area by 65-fold, (c) change in the morphology from spherical particles to a flake-type structure with sharp edges, (d) reduction in the average crystal size from 61.143 to 27.176 nm, and (e) increase in the pore volume from 0.005 to 0.50 cm³ g⁻¹. These desired properties of the nano-sorbent were obtained by blending a waste aluminium foil with fly ash. This process increased the ratio of alumina to silica from 0.59 : 1 to an optimum ratio of 1.9 : 1, beyond which the particles agglomerated and the pore volume reduced. Eventually, the precipitated hydroxides were calcined at 700 °C that favoured the formation of γ-alumina. Moreover, this heat treatment changed its crystallinity and morphology of γ-alumina, which abruptly enhanced its activity towards the pollutants. The obtained product (nano-sorbent) was tested for the removal of lead and malachite green from a model wastewater solution over a wide range of initial pollutant concentrations and adsorbent dosages. After observing almost complete removal capacity and reusability for the pollutants, we propose this synthesized adsorbent as a universal material for treating industrial wastewater.

A highly efficient and low-cost alumina–silica nano-sorbent was fabricated and characterized to realize the key factors responsible for its superiority over the existing adsorbents in treating the wastewater for the removal of dyes and heavy metals.

Enhanced removal of hexavalent chromium by engineered biochar composite fabricated from phosphogypsum and distillers grains

Two kinds of industrial wastes (distillers grains and phosphogypsum) were used as raw materials to produce a new biochar composite for Cr(VI) removal in water. The influencing factors including pyrolysis temperature, dosage, initial solution pH as well as contacting time were explored. The adsorption kinetics, isotherms, and thermodynamics of two biochars were conducted. The results show that the adsorption of Cr(VI) by biochar is related to pH. The ideal pH was 3.0 and the adsorbed Cr(VI) decreases as the pH increases. The Cr(VI) adsorption process conformed to the pseudo-second-order equation. Phosphogypsum modified (PM)-biochar is well described by the Freundlich model. The maximum adsorption capacities of distillers grains (DG)-biochar and PM-biochar on Cr(VI) were 63.1 and 157.9 mg g^-1, respectively. The thermodynamic analysis indicates that the Cr(VI) adsorption occurs spontaneously which is an endothermic process. This study provided an alternative way for Cr(VI) removal from water.

Investigation of the effective factors on the mutagen X formation in drinking water by response surface methodology

Mutagen 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX) is known as a potent factor in inducing DNA damage and increasing cancer risk. MX is a chlorination disinfection byproduct that comes from the reaction of humic acids and chlorine in drinking water. The purpose of this study was to evaluate the effects of significant factors (including pH, reaction time, chlorine and the concentration of organic materials (TOC)) and their interactions on the MX formation rate in chlorinated drinking water using Box-Behnken Design (BBD) and response surface method (RSM). For this purpose, the simulation of water chlorination disinfection process was carried out in a laboratory scale. A quadratic model was chosen to determine the mathematical relations between the response and the effective factors. All linear parameters, as well as second-degree components except chlorine, were statistically significant. Also, the interactions of contact time with TOC, free chlorine residual with TOC, and chlorine with pH were also statistically significant. Statistical results showed that the pH had a great effect on the potential of MX formation, and then the factors of TOC, chlorine and contact time were effective, respectively. The percentage of contribution (PC) of each component in the formation of MX. The highest significant percentage of contribution (48.36%) was allocated to the pH. Under the optimum conditions (contact time of 48.38 min, chlorine concentration of 0.79 mg/L, TOC concentration of 0.53 mg/L, and pH of 7.98), minimum value of MX was equal to 28.6.

Recycling of Date Pits Into a Green Adsorbent for Removal of Heavy Metals: A Fractional Factorial Design-Based Approach

Date pits (DPs) have been recycled into a low-cost adsorbent for removing of selected heavy metals (HMs) from artificially contaminated aqueous solutions. Adsorption of targeted HMs, both by raw date pits (RDP) and burnt date pits (BDP) was tested. Results showed that BDP is more efficient as an adsorbent and mostly adsorbing Cu(II). A novel approach; fractional factorial design (2^k−p – FrFD) was used to build the experimental pattern of this study. The effects of four factors on the maximum percentage (%) of removal (Y) were considered; pH, adsorbent dose (AD), heavy metal concentration (HMC), and contact time (CT). Statistically significant variables were detected using Pareto chart of standardized effects, normal and half-normal plots together with analysis of variance (ANOVA) at 95.0 confidence intervals (CI). Optimizing (maximizing) the percentage (%) removal of Cu(II) by BDP, was performed using optimization plots. Results showed that the factors: pH and adsorbent dose (AD) affect the response positively. Scanning electron microscopy (SEM) was used to study the surface morphology of both adsorbents while fourier-transform infrared spectroscopy (FTIR) was employed to get an idea on the functional groups on the surface and hence the adsorption mechanism. Raman spectroscopy was used to characterize the prepared adsorbents before and after adsorption of Cu(II). Equilibrium studies show that the adsorption behavior differs according to the equilibrium concentration. In general, it follows Langmuir isotherm up to 155 ppm, then Freundlich isotherm. Free energy of adsorption (ΔG_ad) is −28.07 kJ/mole, when equilibrium concentration is below 155 ppm, so the adsorption process is spontaneous, while (ΔG_ad) equals +17.89 kJ/mole above 155 ppm, implying that the process is non-spontaneous. Furthermore, the adsorption process is a mixture of physisorption and chemisorption processes, which could be endothermic or exothermic reactions. The adsorption kinetics were described using a second order model.

Nano-magnetic walnut shell-rice husk for Cd(II) sorption: design and optimization using artificial intelligence and design expert

This study attempted to investigate the use of nanomagnetic activated carbon prepared from walnut shell and rice husk wastes for removal of Cd(II) from aqueous solution via application of ANN and design expert as adsorbent preparation design and optimization tools. The novel adsorbent was characterized using SEM, FTIR, EDS and BET. The result from 2-level factorial design expert revealed 78.58% Cd(II) sorption efficiency could be achieved for adsorbent prepared at optimum calcination temperature, calcination time, SS-RH mixing ratio and magnetite loading of 859.20 °C, 2.32 h, 2.54 and 5.56 wt% respectively. Sensitivity analysis by both proposed methodologies revealed calcination temperature as most influential factor in adsorbent preparation. Average relative errors and R2 values of 1.2931% and 4.806%; and 0.9967 and 0.9055 obtained respectively for developed ANN model with 4-9-1 architecture and 2-level factorial design expert revealed ANN model as better prediction and optimization tool for Cd(II) sorption using NM-WS-RH-AC. Laboratory analysis revealed presence of -OH, -NH and COO- groups on adsorbent surface; presence of Cd(II) after adsorption; change in adsorbent textural and morphological structure after Cd(II) adsorption; and increase in its surface area and average pore diameter due to magnetization. Average relatively stable desorption strength of 62.74% towards Cd(II) was exhibited by adsorbent for four consecutive cycles using 0.1M HNO3. Prepared adsorbent is effective in removing Cd(II) from solution than commercial activated carbon with economically viable regeneration attribute.

Optimized adsorption onto biosolids-based activated carbon for tartrazine removal from wastewater

This study investigates optimized tartrazine uptake by activated carbon prepared from biosolids (BBAC). Different tartrazine concentrations (10-20 mg/L), adsorbent dosages (1.0-2.0 g), pH (2.0-4.0), and contact times (60-120 min) were tested. These independent variables formed a 2⁴ full factorial experiment arranged as central composite rotative design (CCRD). Response surface methodology (RSM) analyzed the responses of 50 experimental runs. Tartrazine removal efficiency fluctuated between 76.2% and 99.9%. The experimental data were best fitted by a quadratic model (R²  > 0.95, p > 0.0001). All variables exerted statistically significant (p < 0.05) effects on the tartrazine uptake (initial concentration, p = 0.0011; BBAC dosage, p = 0.0004; pH, p < 0.0001; contact time, p < 0.0001). Optimized tartrazine uptake efficiency of 97.4% can happen when variables mutually correlate at 10.1 mg/L of tartrazine concentration, 1.07 g of adsorbent dosage, 2.13 of pH, and 116.9 min of contact time. PRACTITIONER POINTS: Production of biosolids-based activated carbon (BBAC) is presented. Adsorptive affinity to tartrazine in aqueous solution was experimented. Experimental conditions optimized by Response Surface Methodology.

Optimization of Photocatalytic Degradation of Acid Blue 113 and Acid Red 88 Textile Dyes in a UV-C/TiO2 Suspension System: Application of Response Surface Methodology (RSM)

Textile industries produce copious amounts of colored wastewater some of which are toxic to humans and aquatic biota. This study investigates optimization of a bench-scale UV-C photocatalytic process using a TiO2 catalyst suspension for degradation of two textile dyes, Acid Blue 113 (AB 113) and Acid Red 88 (AR 88). From preliminary experiments, appropriate ranges for experimental factors including reaction time, solution pH, initial dye concentration and catalyst dose, were determined for each dye. Response surface methodology (RSM) using a cubic IV optimal design was then used to design the experiments and optimize the process. Analysis of variance (ANOVA) was employed to determine significance of experimental factors and their interactions. Results revealed that among the studied factors, solution pH and initial dye concentration had the strongest effects on degradation rates of AB 113 and AR 88, respectively. Least-squares cubic regression models were generated by step-wise elimination of non-significant (p-value > 0.05) terms from the proposed model. Under optimum treatment conditions, removal efficiencies reached 98.7% for AB 113 and 99.6% for AR 88. Kinetic studies showed that a first-order kinetic model could best describe degradation data for both dyes, with degradation rate constants of k1, AB 113 = 0.048 min−1 and k1, AR 88 = 0.059 min−1.

Thermodynamic spectral and kinetic analysis of the removal of Cu(II) from aqueous solution by sodium carbonate treated rice husk

A new adsorbent for removing copper ions from aqueous solutions has been developed and characterized. The present study deals with the sorption of Cu(II) from aqueous solution on chemically pretreated sodium carbonate-treated rice husk (SCRH). The physico-chemical characteristics of rice husks were investigated to analyze their suitability to adsorb Cu(II) ions from water and wastewater. The raw rice husk (RRH), SCRH and Cu(II) adsorbed rice husk were analyzed by SEM-EDAX analysis. FTIR spectroscopy was also applied to identify functional groups, capable of adsorbing metal ions. Batch kinetic studies were conducted for the adsorption of Cu(II) on SCRH. It has been observed that 92.9-96.0% removal of Cu(II) is achieved at 4.8 mg of Cu(II)/g of adsorbent, adsorbent dose of 10 g L^-1 and initial Cu(II) concentration of 10 mg L^-1 in a temperature range of 15-50 °C. It was observed that the adsorption of Cu(II) on SCRH followed pseudo second-order kinetic and time to achieve equilibrium was found to be 60 min. The maximum uptake (97%) of Cu (II) was observed at pH 6. In this paper, an attempt has also been made to develop simple and readily understandable thermodynamic parameters related to sorption process at the equilibrium for understanding the adsorption mechanism. The Gibbs free energy ΔG° values for the adsorption processes of Cu(II) at 15, 30, 40 and 50 °C were calculated as -6.16, -6.84, -8.01 and -8.53 kJ mol^-1, respectively. The negative value of ΔG° indicates spontaneity of adsorption. The values of ΔH° and ΔS° for Cu(II) adsorption were calculated as 14.37 kJ mol^-1 and 70.92 J K^-1 mol^-1, respectively. The activation energy for the adsorption of Cu(II) was found to be 9 kJ mol^-1 which is a characteristic for diffusion limited processes.

Modeling and optimization of process variables for HCl gas removal by response surface methodology

In the present article, optimization of process variables has been done to maximize the removal efficiency of toxic HCl gas in a submerged self-priming venturi scrubber. Response surface methodology with central composite design has been chosen to predict the effect of process variables on the removal efficiency. A quadratic equation was found from this study to predict the removal efficiency and from the ANOVA test, the significance of process variables was evaluated. Regression analysis confirmed the suitability of the developed model by the higher R² square value (0.9717). Optimum conditions were obtained as 55.18 m s^-1 of throat gas velocity, 405.10 ppm of inlet HCl concentration and 0.0038 N of NaOH concentration in scrubbing liquid to achieve 90.80% of the HCl removal efficiency.

Chitosan grafted onto Fe3O4@poly(N-vinylcaprolactam) as a new sorbent for detecting Imatinib mesylate in biosamples using UPLC-MS/MS

Fe₃O₄ nanoparticles with chitosan grafted onto poly(N-vinylcaprolactam) copolymers are synthesized and showed dual sensitivity to temperature and pH.

Adsorptive Removal of Methylene Blue and Crystal Violet onto Micro-Mesoporous Zr3O/Activated Carbon Composite: A Joint Experimental and Statistical Modeling Considerations

Zirconium oxide/activated carbon (Zr3O/AC) composite was synthesized to remove methylene blue (MB) and crystal violet (CV) from the aqueous medium. The Zr3O/AC sample was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray analyses (EDS), Raman spectroscopy (RS), BET surface area, and Fourier transform infrared spectroscopy (FTIR). XRD profiles confirmed the successful synthesis of the zirconium oxide/activated carbon composite. SEM images showed multideveloped walls with irregular particle size with channel arrays. The nitrogen physisorption combines I and IV types with a calculated BET surface area of 1095 m2/g. Raman spectrum illustrated a disorder of both crystalline structure and the graphitic structure. The adsorption was better fitted to the pseudo-second-order (PSO) kinetic model. Langmuir model fitted better the experimental results of MB adsorption, whereas the CV was better consistent with the Freundlich model. The obtained results suggested that the MB and CV adsorption might be influenced by the mass transfer that involves multiple diffusion steps. The maximum adsorption capacities are 208.33 and 204.12 mg/g for MB and CV, respectively. The MB and CV removal mechanisms were proposed, and statistical optimization was performed using central composite design combined with the response surface methodology.

Hydrodynamic performance of a hybrid anaerobic baffled reactor (HABR): effects of number of chambers, hydraulic retention time, and influent temperature

Hydrodynamic performance of a biological reactor is an important design concern since it directly affects the treatment efficiency. In this research, a hybrid anaerobic baffled reactor (HABR) was proposed with improved design concepts and principles. The HABR consisted of a front sedimentation chamber, four regular baffled chambers followed by two floated filter media chambers. The effects of operating variables 5-20 hr hydraulic retention time (HRT) and 10-40 °C of influent temperature, as well as their interactive effects, on the hydrodynamic behaviour were investigated by residence time distributions study and response surface methodology. The study suggests that the hydrodynamic performance is greatly influenced by the number of chambers in the reactor rather than HRT and influent temperature. The influence of HRT and feed temperature were mainly observed on the front chambers (1-4) rather than rear chambers (5-7). The optimum reactor performance - low dead space (<10%), excellent hydraulic efficiency (>0.75), and intermediate mixing pattern (Peclet number > 10) - were achieved using the proposed HABR with more than five chambers.

Hexavalent chromium removal from aqueous solution using functionalized chitosan as a novel nano-adsorbent: modeling and optimization, kinetic, isotherm, and thermodynamic studies, and toxicity testing

Hexavalent chromium is a highly toxic metal that can enter drinking water sources. Chitosan, which contains amino and hydroxyl functional groups, is considered an appropriate candidate to remove heavy metals through absorption. In this study, a novel adsorbent, magnetic nanoparticles of chitosan modified with polyhexamethylene biguanide (Ch-PHMB NPs) was synthesized and was used to successfully remove chromium from aqueous solution. Quadratic models with independent variables including pH, adsorbent dosage, time, and the initial concentration of chromium were proposed through RSM to describe the behavior of both magnetic chitosan (M-Ch) and Ch-PHMB NPs in Cr(VI) removal. Optimized models with adjusted R² values of 0.8326 and 0.74 for M-Ch and Ch-PHMB NPs were developed. Cr(VI) removal from aqueous solution by both absorbents followed pseudo-second-order kinetics. The experimental data were best fitted to the Temkin and Freundlich models for M-Ch and Ch-PHMB NPs, respectively. M-Ch and Ch-PHMB NPs can effectively remove the hexavalent chromium from aqueous solution with pH above 7. Ch-PHMB NPs have higher removal efficiency than M-Ch, removing up to 70% of Cr(VI) from aqueous solution. However, toxicity evaluation on Daphnia magna revealed that Ch-PHMB NPs was more toxic than M-Ch nanoparticles.

A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence

Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima. This article summarizes the modeling and optimization of pollutants removal processes in water treatment by using multilayer perception, fuzzy neural, radial basis function and self-organizing map networks. Furthermore, the results conclude that the hybrid models of ANNs with GA and PSO can be successfully applied in water treatment with satisfactory accuracies. Finally, the limitations of current AI tools and their new developments are also highlighted for prospective applications in the environmental protection.

Horizontally rotating disc recirculated photoreactor with TiO2-P25 nanoparticles immobilized onto a HDPE plate for photocatalytic removal of p-nitrophenol

In this study, a horizontally rotating disc recirculated (HRDR) photoreactor equipped with two UV lamps (6 W) was designed and fabricated for photocatalytic removal of p-nitrophenol (PNP). Photocatalyst (TiO₂) nanoparticles were immobilized onto a high-density polyethylene (HDPE) disc, and PNP containing solution was allowed to flow (flow rate of 310 mL min^-1) in radial direction along the surface of the rotating disc illuminated with UV light. The efficiency of direct photolysis and photocatalysis and the effect of rotating speed on the removal of PNP were studied in the HRDR photoreactor. It was found that TiO₂-P25 nanoparticles are needed for the effective removal of PNP and there was an optimum rotating speed (450 rpm) for the efficient performance of the HRDR photoreactor. Then effects of operational variables on the removal efficiency were optimized using response surface methodology. The results showed that the predicted values of removal efficiency are consistent with experimental results with an R₂ of 0.9656. Optimization results showed that maximum removal percent (82.6%) was achieved in the HRDR photoreactor at the optimum operational conditions. Finally, the reusability of the HRDR photoreactor was evaluated and the results showed high reusability and stability without any significant decrease in the photocatalytic removal efficiency.