Phytase-Fe3O4 nanoparticles-loaded microcosms of silica for catalytic remediation of phytate-phosphorous from eutrophic water bodies

Agriculture P management practices elevate the level of inorganic phosphates in soil that results in phosphorous (P) seepage into water-bodies. This is one of the key factors that have accelerated the menace of eutrophication. Phytic acid (phytate)-P-rich plant metabolite is infamous for its anti-nutrient activity and regularly oozing in to environment though discharge of mono-gastric animals. That has amplified the magnitudes of eutrophication. In this work, for catalysis of phytate-P, the metal-organic framework fabricated towards metal oxides (Fe₃O₄) and phytase in highly ordered microcosms of silica was employed. The synthesized framework was characterized through transmission electron microscopy (TEM) and nitrogen isotherm analysis. Average pore diameter of synthesized bisect oval shaped structures was measured around ≈200 nm. Herein, phytase and Fe₃O₄ nanoparticles were loaded to the cavities of microcosms through glutaraldehyde-mediated crosslinking. Whereas Fe₃O₄ nanoparticles act as nano-absorbents that adsorb P liberated from phytase-mediated catalysis of phytate. Kinetic analysis of free and loaded phytase has shown relatively small reduction in catalytic efficiency. These loaded microcosms have removed 60–80% of phytate-phosphate. The optimized process has reduced the growth of photoautotrophs by 50%. Additionally the magnet-assisted separation of loaded microcosms eased the reapplication of loaded microcosms tested for six independent instances. The primary studies conducted to evaluate the geno-toxicity of loaded microcosms have not shown any harmful effect on the process like cell division and seed germination. The efficacy of this method has evaluated towards on-field testing in Changa (Gujarat, India) lake.

     

Statistical inferences from measured data on concentrations of naturally occurring radon,thoron, and decay products in Kumaun Himalayan belt

Environmental Science and Pollution Research - Regional averages of radon, thoron, and associated decay product concentration are reported to be higher than their respective global averages in...     

Inactivation of bacteria in sewage sludge by gamma radiation

The survival of certain bacterial cultures suspended in sewage sludge and exposed to gamma-radiation was studied. The inactivation patterns of most of the organisms were significantly different when irradiation was performed using sewage samples collected in the summer and monsoon seasons. The summer sample collected from the anaerobic digestor afforded significant protection to both Gram negative and Gram positive organisms. This was evident by the increase in dose required to bring about a 6 log cycle reduction in viable count of the bacterial cultures, when suspended in sewage samples instead of phosphate buffer. The observations made using monsoon digestor samples were quite different. This sewage sludge greatly enhanced inactivation by gamma-radiation in most cases. The effects of certain chemicals on the inactivation patterns of two organisms-Salmonella typhi and Shigella flexneri-were examined. Arsenate, mercury and lead salts sensitised S. typhi, while barium acetate and sodium sulphide protected this culture against gamma-radiation. In the case of Sh. flexneri, barium acetate and iodacetamide proved to be radioprotectors. The effects of some chemicals on the inactivation pattern of Sh. flexneri cells irradiated in sludge are also discussed.     

Complete dechlorination of endosulfan and lindane using Mg0/Pd(+4) bimetallic system

A Mg0/Pd(+4) bimetallic system was evaluated to dechlorinate endosulfan and lindane in the aqueous phase. Studies were conducted with endosulfan and lindane separately, with or without acid in a 1:1 (v/v) water:acetone phase. In the absence of any acid, higher degradation of endosulfan and lindane was observed using Mg0/Pd(+4) doses of 10/0.5 and 4/0.1 mg/mL, respectively. Acetone plays an important role in facilitating the dechlorination reaction by increasing the solubilities of pesticides. Dechlorination kinetics for endosulfan and lindane (30 and 50 mg/L [30 and 50 ppm] concentration of each pesticide) were conducted with varying Mg0/Pd(+4) doses, and the time-course profiles were well-fitted into exponential curves. The optimum observed rate constants (k(obs)) for endosulfan and lindane were obtained with Mg0/Pd(+4) doses of 5/0.5 and 4/0.1 mg/mL, respectively. Gas chromatography-mass spectrometry analyses revealed that endosulfan and lindane were dechlorinated completely into their hydrocarbon skeletons-Bicyclo [2,2,1] hepta 2-5 diene and benzene, respectively.     

Application of best subset method for river water quality modeling: A study on Godavari River,India

The utilization of water quality analysis to inform optimal decision-making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post-monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R², F value, adjusted R²_a, AIC_c, and RSS. The final best subset model across all parameters exhibits R² values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision-making and in the management of river water quality for its sustainable use in the study area.