Silver nanoparticles from Tabernaemontana divaricate leaf extract: mechanism of action and bio-application for photo degradation of 4-aminopyridine

Silver nanoparticles (Ag NPs) were synthesised by the reduction of Ag⁺ to Ag⁰ in the presence of enol form of flavonoids present in plant extract of Tabernaemontana divaricate (T. divaricate). Prepared Ag NPs were characterised using UV–Vis, XRD, HR-TEM with EDX and XPS techniques. XPS spectra exhibited peaks at 366 eV and 373 eV, which specified spin orbits for Ag 3d_3/2, and Ag 3d_5/2 that confirmed the formation of Ag NPs. Ag NPs were spherical in shape with an average size of 30 nm as revealed by HR-TEM and FE-SEM techniques. EDX studies verified the high purity of Ag NPs with silver 46.96%, carbon 16.35%, oxygen 16.22%, nitrogen 20.25% and sulphur 0.21%. LC–MS analysis of plant extract confirmed the qualitative presence of alkaloids, tannins, flavonoids, phenols, and carbohydrates. Prepared Ag NPs showed good photocatalytic activity towards degradation of 4-Amniopyridine with 61% degradation efficiency at optimum conditions in 2 h of reaction time under visible light. The ten intermediates were found within the mass number of 0–450. Ag NPs synthesised using bio-extract have also shown good inactivation against Escherichia coli (E. coli) and Bacillus subtilis (B. subtilis) bacteria due to the availability of free radicals.

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Spatial distribution and seasonal variation of atmospheric bulk deposition of polycyclic aromatic hydrocarbons in Beijing-Tianjin region, North China

Bulk deposition samples were collected in remote, rural village and urban areas of Beijing-Tianjin region, North China in spring, summer, fall and winter from 2007 to 2008. The annually averaged PAHs concentration and deposition flux were 11.81 ± 4.61 μg/g and 5.2 ± 3.89 μg/m²/day respectively. PHE and FLA had the highest deposition flux, accounting for 35.3% and 20.7% of total deposition flux, respectively. More exposure risk from deposition existed in the fall for the local inhabitants. In addition, the PAHs deposition flux in rural villages (3.91 μg/m²/day) and urban areas (8.28 μg/m²/day) was 3.8 and 9.1 times higher than in background area (0.82 μg/m²/day), respectively. This spatial variation of deposition fluxes of PAHs was related to the PAHs emission sources, local population density and air concentration of PAHs, and the PAHs emission sources alone can explain 36%, 49%, 21% and 30% of the spatial variation in spring, summer, fall and winter, respectively.     

Differential effects of hydroxylamine and ethyl methane sulphonate on potato virus X

The Science of Nature -     

On the emergence of a health-pollutant-climate nexus in the wake of a global pandemic

Environmental Science and Pollution Research - COVID-19 has wreaked havoc throughout the planet within a short time frame, inducing substantial morbidity and mortality in the global population. The...     

Modeling and multi-objective optimization of commercial ethylene oxide reactor to strike a delicate balance between profit and negative environmental impact

Environmental Science and Pollution Research - The present work emphasizes the development of a generic methodology that addresses the core issue of any running chemical plant, i.e., how to...     

Enhancement of nutritional value of fried fish using an artificial intelligence approach

Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and mustard oil, experiments were carried out in varying temperatures (140–240 °C), times (5–20 min), and oil amounts (25–100 ml/kg of fish) which established drastic reduction of 44.97% and 99.40% for polyunsaturated fatty acid (PUFA)/saturated fatty acids (SFA) and index of atherogenicity (IA) profile, respectively. Artificial neural network (ANN) was implemented successfully to provide an association between the independent inputs with dependent outputs (values of R² were 0.99 and 0.98; RMSE were 0.038 and 0.046; and performance were 0.038 and 0.067 for PUFA/SFA and IA, respectively) by exhaustive search of various algorithms and activation functions available in literature. ANN model–based meta-heuristic, stochastic optimization formalisms, genetic algorithm (GA) and particle swarm optimization (PSO), were applied to optimize the combination of cooking parameters for improving the nutritional quality of food which improved the nutritional value by maximizing the PUFA/SFA profile up to 63.05% and minimizing the IA profile to 99.64%. Multi-objective genetic algorithm (MOGA) was also employed to tune the inputs by maintaining a balance between the contrasting outputs and enhance the overall food value simultaneously with multi-objective (beneficial for health, economic, and environment-friendly) proposal. MOGA was able to improve the PUFA/SFA profile up to 44.76% and reduce the IA profile to 92.94% concurrently with the reduction of wastage of culinary media and energy consumption, following the optimized cooking condition (118.92 °C, 6.06 min, 40 ml oil/kg of fish).

     

Occupational health hazards and wide spectrum of genetic damage by the organic solvent fumes at the workplace: A critical appraisal

Environmental Science and Pollution Research - Long-term exposure to organic solvents is known to affect human health posing serious occupational hazards. Organic solvents are genotoxic, and they...