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Defects in nanostructures play a pivotal role in determining their properties and performance in the desired applications. Herein, the defect states and structural properties of the bi-metal oxide composite of ZnO and α-Fe2O3 (ZF-W) are varied by annealing the composite at different temperatures. The changes in defects, structures, and phase are evaluated thoroughly using transmission electron microscopy, x-ray diffraction, photoluminescence, and Mössbauer spectroscopy techniques. The defect-rich ZF-W composite is found to be composed of defect-deficient ZnFe2O4 attaining the equilibrium state when as-synthesized ZF-W is annealed at 500 °C [ZF-W(500)]. Further annealing at 1000 °C, ZF-W(1000), a non-stoichiometric and highly defected ZnFe2O4 is evidenced in the composite. The changes in the composite with the annealing temperature are correlated with the cationic migration and evolution of defect states. Moreover, the transition associated with the vacancy defects, which trapped the excited electron and dispel the free electrons, thereby inhibiting fast electron–hole pair recombination, is corroborated from the photoluminescence spectra. When implemented for methyl blue adsorption/degradation without the assistance of any external sources, the degradation efficiency of ZF-W, ZF-W(300), ZF-W(500), and ZF-W(1000) is found to be 86%, 84%, 68%, and 82%, respectively. The prepared samples are highly stable and can be used repeatedly without losing effectiveness. The simultaneous evolution of defects and structural properties of the composite are attributed for the variation in methyl blue adsorption/degradation. The present study reveals the importance of defects present in the mixed metal oxide composite in obtaining high-performance dye degradation/adsorption properties for sustainable wastewater treatment. [ABSTRACT FROM AUTHOR]

To characterize the pollutant dispersal across major metropolitan cities in India, daily particulate matter (PM 10 and PM 2.5 ) data for the study areas were collected from the National Air Quality Monitoring stations database provided by the Central Pollution Control Board (CPCB) of India. The data were analysed for three temporal ranges, i.e. before the pandemic-induced lockdown, during the lockdown, and after the upliftment of lockdown restrictions. For the purpose, the time scale ranged from 1st April to 31st May for the years 2019 (pre), 2020, and 2021 (post). Statistical distributions (lognormal, Weibull, and Gamma), aerosol optical thickness, and back trajectories were assessed for all three time periods. Most cities followed the lognormal distribution for PM 2.5 during the lockdown period except Mumbai and Hyderabad. For PM 10 , all the regions followed the lognormal distribution. Delhi and Kolkata observed a maximum decline in particulate pollution of 41% and 52% for PM 2.5 and 49% and 53% for PM 10 , respectively. Air mass back trajectory suggests local transmission of air mass during the lockdown period, and an undeniable decline in aerosol optical thickness was observed from the MODIS sensor. It can be concluded that statistical distribution analysis coupled with pollution models can be a counterpart in studying the dispersal and developing pollution abatement policies for specific sites. Moreover, incorporating remote sensing in pollution study can enhance the knowledge about the origin and movement of air parcels and can be helpful in taking decisions beforehand., Competing Interests: Conflict of interestThe authors have no competing interests to declare that are relevant to the content of this article. I confirm that the work is original and has not been published elsewhere, or currently under consideration for elsewhere publication., (© The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

A novel green nanocomposite has been prepared by immobilizing CaO nanoparticles (CaO NPs) on the surface of graphene oxide. Biogenic CaO-NPs were synthesized from Lala clamshells. Morphological and structural characterizations of the nanocomposite were studied extensively. The adsorption capacity (q max ) of the nanocomposite for removing Cr(VI) was 38.04 mg g -1 . In addition to this, the adsorption data were adequately simulated with Langmuir, Freundlich, Temkin, and pseudo-second-order models, suggesting that the adsorption process was the combination of external mass transfer and chemisorption. Electrostatic interaction was the dominant mechanism for Cr(VI) removal. In addition, the synthesized nanocomposites also serve as an excellent sensor for Cr(VI) sensing, with a limit of detection (LOD) of 0.02 μM utilizing electrochemical methods. Therefore, this green nanocomposite can simultaneously serve as an adsorbent and sensor for Cr(VI)removal from aqueous solutions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Industrial effluents generally contain several metals, so during adsorptive treatment, they may influence the removal of each other. It is essential to explore the effect of co-cations on metal removal in multi-metal solutions. The present study examined the possibility of processed rice husk and saw dust to remove Cr 6+ , Ni 2+ , Cu 2+ , Cd 2+ and Zn 2+ , from the single, binary and multi-component aqueous solutions. A substantial lesser removal of metal ions was observed in the presence of co-ions. This study revealed antagonistic effect on the removal of a particular metal ion, from the industrial effluent, even at optimum process parameters if other metal ions are present in the effluent. Although, a higher concentration of one metal ion than others in effluents increased its removal due to a greater number of ions as compared to other for the biosorption, yet presence of other ions influences the uptake of individual ions. In case of industrial effluents, maximum adsorption was obtained at pH 2.0 for Cr 6+ , 5.0 for Ni 2+ and Cd 2+ and 6.0 for Zn 2+ and Cu 2+ . The study confirms the beneficial use of the studied biosorbents in water remediation., (Copyright © 2022 Elsevier Ltd. All rights reserved.)