A medium developed by coating BaSO 4 and Fe on quartz sand known as sulfate-modified iron oxide-coated sand (SMIOCS) was evaluated for the removal of arsenic(III) from simulated water with an ionic strength of 0.01 M NaNO 3 during batch studies. The medium was characterised for BET surface area, alkali-resistance, acid-resistance and the presence of iron and barium on the coated surface. Two simplified kinetic models, ie active available site (AAS) and chemical reaction rate models, were tested to investigate the adsorption mechanisms. The values of rate constants for both the models were found to decrease with increasing As(III) concentrations in the solute. The inverse relationship of rate constants of the reaction rate model with BET surface area showed that As(III) adsorption on SMIOCS was not due to physisorption but to chemisorption. A study of the effect of solute temperature showed that the adsorption of As(III) on SMIOCS media was due to chemisorption. The results of isothermal studies conducted at different pH values showed that adsorption data satisfied both the Langmuir and the Freundlich isotherm models. The adsorption of As(III) on the medium was pH dependent and maximum removal was observed in the pH range of 7-9.
A novel granular media developed by the coating of iron, barium and sulfur on quartz sand surface has been demonstrated to be an effective sorbent for removal of arsenic(V) from a 0.01 M NaNO3-spiked distilled water system in laboratory-scale tests. The results of fixed bed studies indicate that arsenic(V) removal is dependent on pH, the size of sorbent and influent arsenic concentrations. The particle size of media has shown significant differences in reactor breakthrough times in similar experimental conditions. The removal of As(V) may be explained using the surface complexation theory. The presence of alkalinity (250–260 mg/L as CaCO3) and hardness (200 mg/L as CaCO3) slightly increases reactor breakthrough time for similar experimental conditions without alkalinity and hardness. Desorption studies using 0.2 M NaOH as elutant resulted in nearly 92% recovery of arsenic(V). A theoretical model based on two parameters has shown good correlation with observed experimental data generated during depth variation studies.
For the effective management of watershed accurate understanding of hydrological behavior is needed and is required. Estimation of runoff from storm rainfall is frequently needed for water resource planning and environmental impact analysis. Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. Remote sensing (RS) and Geographic information system (GIS) can be effectively used to manage spatial and non-spatial database that represent the hydrologic characteristics of the watershed. The Land use and Land Cover map, Soil map, Rainfall data are collected from different sources and processed. The weighted Curve numbers were determined based on antecedent moisture condition with an integration of hydrologic soil groups and land use/ land cover classes. The study area shows that 40% of area falls under high CN value which interprets in more runoff to the study area. The annual runoff depth for catchment was computed for this un-gauge catchment area. The study reveals that the SCS-CN model can be used to estimate surface runoff depth when adequate hydrological information is not available.
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