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The present research work explores different types of machine learning algorithms to estimate the water quality index and the water quality class. The samples were collected from Korattur Lake in Chennai city and tested for its necessary hydro-chemical parameters. The machine learning models such as support vector machine, decision tree, logistic regression, random forest, and naive Bayesian for assessing the water quality with respect to the accuracy and precision of the model. The water quality parameters such as pH, total dissolved salts, turbidity, phosphate, nitrate, iron, chemical oxygen demand, chloride, and sodium are used as a raw dataset. The models are then tested and evaluated to find the best suitable model by comparing and analyzing the accuracy of prediction, the precision rate, and the time taken for execution of all the models. Among all the algorithms employed, the random forest algorithm produces 95% accuracy which is the highest and also consumes the least execution time. From the random forest model, it was found that water quality has 84% of contamination which was attributed to unfit for drinking purpose. Hence, it could be suggested that water quality left disturbed due to anthropogenic activities and improper maintenance. [ABSTRACT FROM AUTHOR]

The past decades showed much research interest in lowering the fluoride ion content in water due to its hazardous nature. Fluoride present in water is likely to have favorable and unfavorable consequences to human life. It depends upon the permissible limits prescribed by the agencies, which paves the way to opt for fluoridation or defluoridation techniques. The excess intake of fluoride by human beings provides many issues that include deformities in skeletal structure, dental fluorosis, weakening of the nervous system, and severe damage to the kidney and liver. This review paper addresses the issues caused due to the over-dosage of fluoride and by compiling the recognized treatment techniques adopted to eliminate it from aqueous solution. The current study also figures out the versatility of every technique by revealing its pros and cons and bridges the gap between the emerging advancements to the practical mode of application. Several pieces of literature have been taken into consideration to withdraw the limitations of the key issues. This review paper suggests that adsorption technology can be adopted due to its simplicity and flexibility to overcome the technological issues. It is one such technique which enhances the defluoridation in trace amount and can be easily implemented in the rural areas. [ABSTRACT FROM AUTHOR]

Magnetic carbon were synthesized from sugarcane bagasse using hydrothermal carbonization followed by thermal activation was converted to solid state as beads (hydrogels SACFe) using sodium alginate and applied as adsorbent in removal sulfamethoxazole in batch and column mode. From adsorption parameter analysis it was confirmed that 0.6 g L−1 SACFe was effective in removing 50 mg L−1 of SMX at pH 6.2. Sorption of SMX on SACFe beads followed Elovich kinetics and Freundlich isotherm. It was further confirmed that sorption occurred on heterogeneous surface of SACFe beads with chemisorption as rate limiting step. Maximum adsorption capacity was obtained as 58.439 mg g−1 pH studies revealed that charged assisted hydrogen bonding, EDA interactions are some of the mechanism that favoured removal of SMX. From column studies it was found that bead height of 2 cm and flow rate of 1.5 mL min−1 found to be best in removing pollutant. Thomas model fitted better the experimental data stating that improved interaction between adsorbent and adsorbate act as major driving force tool in obtaining maximum sorption capacity. Breakthrough curve was completely affected by varied flow rate and bed height. Column adsorption was effective in reducing COD and BOD levels of sewage which are affected by toxic pollutants and miscellaneous compounds. Feasibility analysis showed that SACFe beads could be employed for real-time applications as it is cost, energy effective and easy recovery. [Display omitted] • Conversion of fine magnetic carbon composite particle to granular was achieved. • Magnetic hydrogels showed maximum sorption capacity of 58.439 mg g-1. • Elovich and Freundlich model fitted best in the batch adsorption models. • Breakthrough curve was analysed by varying column design parameters. • Sewage water spiked with SMX showed 65–75% reduction in BOD and COD. [ABSTRACT FROM AUTHOR]

In this present study, tin (Sn) doped MnFe 2 O 4 (Sn 0.15 Mn 0.85 Fe 2 O 4) nanocomposites were synthesized using a microwave combustion method by employing Alocasia odutra plant extract as a natural fuel. Sn is well incorporated with spinel ferrite (MnFe 2 O 4) which is confirmed by XRD analysis. FE-SEM analysis indicates that the synthesized sample having a rod-like structure in nature. The emerging pharmaceutical contaminant, namely, diclofenac (2-(2-(2,6-dichlorophenylamino)phenyl) acetic acid) (DCF), the non-steroidal anti-inflammatory drug was utilized as a model pollutant to evaluate the catalytic efficiency of the Sn 0.15 Mn 0.85 Fe 2 O 4 (SMF) under solar irradiation. SMF shows higher catalytic activity than pristine MnFe 2 O 4 due to a reduction in the bandgap energy from 1.78 eV to 1.54 eV as a result of Sn doping into MnFe 2 O 4. The degradation efficiency of DCF using the SMF catalyst was found to be 99% in a shorter interval (50 min) with 71% mineralization. Radical trapping experiments indicate that the photo-generated holes and hydroxyl radicals actively participate in the degradation process of DCF using the SMF catalyst. The optimum pH for the removal of DCF using the SMF catalyst was found to be 4 with the catalyst dosage of 0.8 g/L. The recycling experiment shows that the SMF catalyst has high stability up to five cycles and low iron leaching ability under optimum conditions. Sn 0.15 Mn 0.85 Fe 2 O 4 catalyst can be recovered using an external magnet from the reaction mixture and it is recycled. It was concluded that the synthesized catalyst can be used as a tertiary treatment option for the removal of emerging pharmaceutical pollutants. ga1 • SMF nanoparticles was synthesized via microwave assisted combustion method using Alocasia odutra plant extract. • 71% mineralization of DCF was achieved within 50 min in the presence of sunlight. • SMF has more stability and low iron leaching capacity. • Efficiency of SMF were tested against different water matrices. • The carbonate ions and humic acid in water competes with the active radicals declined the catalytic activity of SMF. [ABSTRACT FROM AUTHOR]

Sulfamethoxazole is a persistent organic pollutant having N-amine and carboxyl groups rising from pharmaceutical industry. Upon consumption, it undergoes transformation reactions thereby leading to formation of oxidised, acetylated and hydrolysed metabolites in the environment. Though many countries banned use of sulfamethoxazole as growth promoters for veterinary, its occurrence in environment is witnessed even today in rivers, lakes, groundwater, sediments and ocean. This review provides thorough note on occurrence, destiny, toxicity effects and important materials involved in removal technologies like adsorption, Fenton/photo-Fenton process, electrochemical oxidation and photocatalytic degradation. SMX is removed via adsorption by formation of strong chemical interaction with functional moieties present in active sites of sorbents like hydrogen bonding, electrostatic interaction, π-π and hydrophobic interaction whereas AOP's use external energy, chemical agents for cleaving SMX structure through catalytic degradation by generation of hydroxyl radicals. Removal efficiency of material depends on experimental designs which rely on standard protocol. The article highlights the importance of sustainable development of technology by focussing on its feasibility and cost factor for building economic industrialization and statistics. It urge the significance of synergistic effects involved in nanocomposites/polymer in removing toxic contaminant via adsorption or photocatalytic degradation because of its high stability, functionality, ability to adapt at varying pH, sustainability and decreased cost in life cycle assessment. Image 1036797 • Identification of sulfamethoxazole as toxic waste in water. • Removal mechanism of sulfamethoxazole is reviewed. • Strategies involved in adsorption and oxidation process with respect to materials, feasibility are discussed. • Importance of nanocomposites as an alternative is focussed in detail. [ABSTRACT FROM AUTHOR]

Pesticide has revolutionised the agricultural industry by reducing yield losses and by enhancing productivity. But indiscriminate usage of such chemicals can negatively impact human health and ecosystem balance as certain pesticides can be recalcitrant in nature. Out of some of the suggested sustainable techniques to remove the pesticide load from the environment, adsorption is found to be highly efficient and can also be implemented on a large scale. It has been observed that natural adsorption that takes place after the application of the pesticide is not enough to reduce the pesticide load, hence, adsorbents like activated carbon, plant-based adsorbents, agricultural by-products, silica materials, polymeric adsorbents, metal organic framework etc are being experimented upon. It is becoming increasingly important to choose adsorbents which will not leave any secondary pollutant after treatment and the cost of production of such adsorbent should be feasible. In this review paper, it has been established that certain adsorbent like biochar, hydrochar, resin, metal organic framework etc can efficiently remove pesticides namely chlorpyrifos, diazinon, 2,4-Dichlorophenoxyacetic Acid, atrazine, fipronil, imidacloprid etc. The mechanism of adsorption, thermodynamics and kinetic part have been discussed in detail with respect to the pesticide and adsorbent under discussion. The reason behind choosing an adsorbent for the removal of a particular pesticide have also been explained. It is further highly recommended to carry out a cost analysis before implementing an absorbent because inspite of its efficacy, it might not be cost effective to use it for a particular type of pesticide or contaminant. [Display omitted] • Adsorption is widely used owing to its efficacy and applicability on a larger scale. • Focused on the driving mechanism of removal of recalcitrant pesticide. • Process parameters affecting experimental design are highlighted. • Structural modification of adsorbent might improve the surface area and morphology. • The success of this process lies in cost analysis and its feasibility. [ABSTRACT FROM AUTHOR]

Generation of unprocessed effluents, municipal refuse, factory wastes, junking of compostable and non-compostable effluents has hugely contaminated nature-provided water bodies like rivers, lakes and ponds. Therefore, there is a necessity to look into the water standards before the usage. This is a problem that can greatly benefit from Artificial Intelligence (AI). Traditional methods require human inspection and is time consuming. Automatic Machine Learning (AutoML) facilities supply machine learning with push of a button, or, on a minimum level, ensure to retain algorithm execution, data pipelines, and code, generally, are kept from sight and are anticipated to be the stepping stone for normalising AI. However, it is still a field under research. This work aims to recognize the areas where an AutoML system falls short or outperforms a traditional expert system built by data scientists. Keeping this as the motive, this work dives into the Machine Learning (ML) algorithms for comparing AutoML and an expert architecture built by the authors for Water Quality Assessment to evaluate the Water Quality Index, which gives the general water quality, and the Water Quality Class, a term classified on the basis of the Water Quality Index. The results prove that the accuracy of AutoML and TPOT was 1.4 % higher than conventional ML techniques for binary class water data. For Multi class water data, AutoML was 0.5 % higher and TPOT was 0.6% higher than conventional ML techniques. • AutoML concept was adopted to analyze the water quality. • The dataset under study is taken from the Korattur Lake, Chennai, India. • The TDS, Turbidity, PH, COD, Iron, Phosphate, Sodium, Chloride and Nitrate are considered in this study. • The accuracy in analysis of water quality was obtained using AutoML concept. [ABSTRACT FROM AUTHOR]

The objective of the current study was focused on the potential adsorption capability of a biogenic hydroxyapatite/iron nanoparticles-based composite tailored for the elimination of toxic pollutant, Cd(II) ions. Morphological along with physicochemical properties of composites were analyzed by different techniques including Scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDAX), X-ray diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR). It has been noticed an increase in cell parameters of prepared composites with an increase in the amount of nanoparticles. The best adsorbent was found to be the one with a 5% amount of nanoparticles (P 400 F e (5%)). The kinetics studies have shown that the pseudo-first-order-models were in good agreement for the removal of Cd(II) ions onto P 400 Fe(5%) at any concentration, suggesting a physisorption mechanism. Besides, isotherms analysis has consistently revealed Freundlich as the model better explained the isotherm data, with a maximum removal capacity of 392.3 mg g−1, higher compared to many adsorbents. Thermodynamically, the removal adsorption process of Cd(II) ions onto the composite favorable, exothermic, and spontaneous. The regeneration study has been also investigated with reusability used until four cycles. The overall results pointed out the suitability and efficiency of the prepared biogenic composite for the elimination of metal pollutants in wastewater. [Display omitted] • Biogenic composites were successfully prepared from slaughterhouses by-product and iron nanoparticles. • The maximum adsorption capacity of P 400 Fe(5%) was up to 392.3 mg g−1. • The isotherm and kinetic data best fits Freundlich and pseudo-first-order models. • The mechanism could be due to cationic exchange between Ca2+ and Cd2+. • The biogenic composite was effective for four consecutive regeneration cycles. [ABSTRACT FROM AUTHOR]