Biogenic nanosilver incorporated reverse osmosis membrane for antibacterial and antifungal activities against selected pathogenic strains: An enhanced eco-friendly water disinfection approach

Reverse osmosis (RO) membranes have been used extensively in water desalination plants, waste water treatment in industries, agricultural farms and drinking water production applications. The objective of this work is to impart antibacterial and antifungal activities to commercially available RO membrane used in water purification systems by incorporating biogenic silver nanoparticles (AgNPs) synthesized using Rosa indica wichuriana hybrid leaf extract. The morphology and surface topography of uncoated and AgNPs-coated RO membrane were studied using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Elemental composition of the AgNPs-coated RO membrane was analyzed by energy-dispersive X-ray spectroscopy (EDAX). The functional groups were identified by Fourier Transform Infrared spectroscopy (FT-IR). Hydrophilicity of the uncoated and AgNPs-coated RO membrane was analyzed using water contact angle measurements. The thermal properties were studied by thermogravimetric analysis (TGA). The AgNPs incorporated RO membrane exhibited good antibacterial and antifungal activities against pathogenic bacterial strains such as E. coli, S. aureus, M. luteus, K. pneumoniae, and P. aeruginosa and fungal strains such as Candida tropicalis, C. krusei, C. glabrata, and C. albicans.

Modeling of Bubble-Size Distribution in Water and Freon Co-Blown Free Rise Polyurethane Foams

A model has been developed to simulate the foam characteristics obtained, when chemical (water) and physical (Freon) blowing agents are used together for the formation of polyurethane foams. The model considers the rate of reaction, the consequent rise in temperature of the reaction mixture, nucleation of bubbles, and mass transfer of CO2 and Freon to them till the time of gelation. The model is able to explain the experimental results available in literature. It further predicts that the nucleation period gets reduced with increase in water (at constant Freon content), whereas with increase in Freon (at constant water) concentration nucleation period decreases marginally leading to narrower bubble-size distribution. By the use of uniform sized nuclei added initially, the model predicts that the bubble-size distribution can be made independent of the rate of homogeneous nucleation and can, thus, offer an extra parameter for its control. (C) 2014 Wiley Periodicals, Inc.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.

Toward a High-Resolution Monitoring of Continental Surface Water Extent and Dynamics, at Global Scale: from GIEMS (Global Inundation Extent from Multi-Satellites) to SWOT (Surface Water Ocean Topography)

Up to now, high-resolution mapping of surface water extent from satellites has only been available for a few regions, over limited time periods. The extension of the temporal and spatial coverage was difficult, due to the limitation of the remote sensing technique e.g., the interaction of the radiation with vegetation or cloud for visible observations or the temporal sampling with the synthetic aperture radar (SAR)]. The advantages and the limitations of the various satellite techniques are reviewed. The need to have a global and consistent estimate of the water surfaces over long time periods triggered the development of a multi-satellite methodology to obtain consistent surface water all over the globe, regardless of the environments. The Global Inundation Extent from Multi-satellites (GIEMS) combines the complementary strengths of satellite observations from the visible to the microwave, to produce a low-resolution monthly dataset () of surface water extent and dynamics. Downscaling algorithms are now developed and applied to GIEMS, using high-spatial-resolution information from visible, near-infrared, and synthetic aperture radar (SAR) satellite images, or from digital elevation models. Preliminary products are available down to 500-m spatial resolution. This work bridges the gaps and prepares for the future NASA/CNES Surface Water Ocean Topography (SWOT) mission to be launched in 2020. SWOT will delineate surface water extent estimates and their water storage with an unprecedented spatial resolution and accuracy, thanks to a SAR in an interferometry mode. When available, the SWOT data will be adopted to downscale GIEMS, to produce a long time series of water surfaces at global scale, consistent with the SWOT observations.