Treatment of Arsenic Contaminated Groundwater Using Calcium Impregnated Granular Activated Carbon in a Batch Reactor: Optimization of Process Parameters

This paper is an experimental investigation into the removal of arsenic species from simulated groundwater by adsorption onto Ca²⁺ impregnated granular activated carbon (GAC‐Ca) in the presence of impurities like Fe and Mn. The effects of adsorbent concentration, pH and temperature on the percentage removal of total arsenic (As(T)), As(III) and As(V) have been discussed. Under the experimental conditions, the optimum adsorbent concentration of GAC‐Ca was found to be 8 g/L with an agitation time of 24 h, which reduced As(T) concentration from 188 to 10 μg/L. Maximum removal of As(V) and As(III) was observed in a pH range of 7–11 and 9–11, respectively. Removal of all the above arsenic species decreased slightly with increasing temperature. The presence of Fe and Mn increased the adsorption of arsenic species. Under the experimental conditions at 30°C, the maximum percentage removals of As(T), As(III), As(V), Fe, and Mn were found to be ca. 94.3, 90.6, 98.0, 100 and 63%, respectively. It was also observed that amongst the various regenerating liquids used, a 5 N H₂SO₄ solution exhibited maximum regeneration (ca. 91%) of the spent GAC‐Ca.     

Improvement of Monsoon Depressions Forecast with Assimilation of Indian DWR Data Using WRF-3DVAR Analysis System

An attempt is made to evaluate the impact of Doppler Weather Radar (DWR) radial velocity and reflectivity in Weather Research and Forecasting (WRF)-3D variational data assimilation (3DVAR) system for prediction of Bay of Bengal (BoB) monsoon depressions (MDs). Few numerical experiments are carried out to examine the individual impact of the DWR radial velocity and the reflectivity as well as collectively along with Global Telecommunication System (GTS) observations over the Indian monsoon region. The averaged 12 and 24 h forecast errors for wind, temperature and moisture at different pressure levels are analyzed. This evidently explains that the assimilation of radial velocity and reflectivity collectively enhanced the performance of the WRF-3DVAR system over the Indian region. After identifying the optimal combination of DWR data, this study has also investigated the impact of assimilation of Indian DWR radial velocity and reflectivity data on simulation of the four different summer MDs that occurred over BoB. For this study, three numerical experiments (control no assimilation, with GTS and GTS along with DWR) are carried out to evaluate the impact of DWR data on simulation of MDs. The results of the study indicate that the assimilation of DWR data has a positive impact on the prediction of the location, propagation and development of rain bands associated with the MDs. The simulated meteorological parameters and tracks of the MDs are reasonably improved after assimilation of DWR observations as compared to the other experiments. The root mean square errors (RMSE) of wind fields at different pressure levels, equitable skill score and frequency bias are significantly improved in the assimilation experiments mainly in DWR assimilation experiment for all MD cases. The mean Vector Displacement Errors (VDEs) are significantly decreased due to the assimilation of DWR observations as compared to the CNTL and 3DV_GTS experiments. The study clearly suggests that the performance of the model simulation for the intense convective system which influences the large scale monsoonal flow is significantly improved after assimilation of the Indian DWR data from even one coastal locale within the MDs track.     

Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean

The convection and planetary boundary layer (PBL) processes play significant role in the genesis and intensification of tropical cyclones (TCs). Several convection and PBL parameterization schemes incorporate these processes in the numerical weather prediction models. Therefore, a systematic intercomparison of performance of parameterization schemes is essential to customize a model. In this context, six combinations of physical parameterization schemes (2 PBL Schemes, YSU and MYJ, and 3 convection schemes, KF, BM, and GD) of WRF-ARW model are employed to obtain the optimum combination for the prediction of TCs over North Indian Ocean. Five cyclones are studied for sensitivity experiments and the out-coming combination is tested on real-time prediction of TCs during 2008. The tracks are also compared with those provided by the operational centers like NCEP, ECMWF, UKMO, NCMRWF, and IMD. It is found that the combination of YSU PBL scheme with KF convection scheme (YKF) provides a better prediction of intensity, track, and rainfall consistently. The average RMSE of intensity (13?hPa in CSLP and 11?m?s^?1 in 10-m wind), mean track, and landfall errors is found to be least with YKF combination. The equitable threat score (ETS) of YKF combination is more than 0.2 for the prediction of 24-h accumulated rainfall up to 125?mm. The vertical structural characteristics of cyclone inner core also recommend the YKF combination for Indian seas cyclones. In the real-time prediction of 2008 TCs, the 72-, 48-, and 24-h mean track errors are 172, 129, and 155?km and the mean landfall errors are 125, 73, and 66?km, respectively. Compared with the track of leading operational agencies, the WRF model is competing in 24?h (116?km error) and 72?h (166?km) but superior in 48-h (119?km) track forecast.     

Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model

Comprehensive sensitivity analyses on physical parameterization schemes of Weather Research Forecast (WRF-ARW core) model have been carried out for the prediction of track and intensity of tropical cyclones by taking the example of cyclone Nargis, which formed over the Bay of Bengal and hit Myanmar on 02 May 2008, causing widespread damages in terms of human and economic losses. The model performances are also evaluated with different initial conditions of 12?h intervals starting from the cyclogenesis to the near landfall time. The initial and boundary conditions for all the model simulations are drawn from the global operational analysis and forecast products of National Center for Environmental Prediction (NCEP-GFS) available for the public at 1° lon/lat resolution. The results of the sensitivity analyses indicate that a combination of non-local parabolic type exchange coefficient PBL scheme of Yonsei University (YSU), deep and shallow convection scheme with mass flux approach for cumulus parameterization (Kain-Fritsch), and NCEP operational cloud microphysics scheme with diagnostic mixed phase processes (Ferrier), predicts better track and intensity as compared against the Joint Typhoon Warning Center (JTWC) estimates. Further, the final choice of the physical parameterization schemes selected from the above sensitivity experiments is used for model integration with different initial conditions. The results reveal that the cyclone track, intensity and time of landfall are well simulated by the model with an average intensity error of about 8?hPa, maximum wind error of 12?m?s^?1and track error of 77?km. The simulations also show that the landfall time error and intensity error are decreasing with delayed initial condition, suggesting that the model forecast is more dependable when the cyclone approaches the coast. The distribution and intensity of rainfall are also well simulated by the model and comparable with the TRMM estimates.     

Geophysical anomalies associated with uranium mineralization from Beldih mine, South Purulia Shear Zone, India

Beldih mine at the central part of the South Purulia Shear Zone (SPSZ) has been reported with low grade uranium-bearing formation within quartz-magnetite-apatite host in kaolinized formation. Therefore, the present integrated geophysical study with gravity, magnetic, radiometric, very low frequency electromagnetic (VLF) and gradient resistivity profiling methods around the known mineralized zones aimed at identifying the exact geophysical signatures and lateral extent of these uranium mineralization bands. The closely spaced gravity-magnetic contours over the low to high anomaly transition zones of Bouguer, reduced-to-pole magnetic, and trend surface separated residual gravity-magnetic anomaly maps indicate the possibility of high altered zone(s) along NW-SE direction at the central part of the study area. High current density plots of VLF method and the low resistive zones in gradient resistivity study depict the coincidence with low gravity, moderately high magnetic and low resistivity anomalies at the same locations. Moderate high radioactive zones have also been observed over these locations. This also suggests the existence of radioactive mineralization over this region. Along profile P2, drilled borehole data revealed the presence of uranium mineralization at a depth of ～100 m. The vertical projection of this mineralization band also identified as low gravity, low resistivity and high magnetic anomaly zone. Thus, the application of integrated geophysical techniques supported by geological information successfully recognized the nature of geophysical signatures associated with the uranium mineralization of this region. This enhances the scope of further integrated geophysical investigations in the unexplored regions of SPSZ.     

http://www.sciencedirect.com/science/article/pii/S1674987113000066

<正>The evolution of the earth is marked by development of more than 70%of the present day continents during Archean.The Archean-Proterozoic boundary is characterized by continental amalgamation, and subsequent breaking and development of worldwide glaciations. The Paleoproterozoic time is characterized by change in atmospheric oxygen and intense biogenic activity during the early part,and amalgamation of the continents to form the supercontinent "Columbia",     

Efficient uncertainty quantification techniques in inverse problems for Richards’ equation using coarse-scale simulation models

This paper concerns efficient uncertainty quantification techniques in inverse problems for Richards’ equation which use coarse-scale simulation models. We consider the problem of determining saturated hydraulic conductivity fields conditioned to some integrated response. We use a stochastic parameterization of the saturated hydraulic conductivity and sample using Markov chain Monte Carlo methods (MCMC). The main advantage of the method presented in this paper is the use of multiscale methods within an MCMC method based on Langevin diffusion. Additionally, we discuss techniques to combine multiscale methods with stochastic solution techniques, specifically sparse grid collocation methods. We show that the proposed algorithms dramatically reduce the computational cost associated with traditional Langevin MCMC methods while providing similar sampling performance.     

Numerical simulation of the marine boundary layer characteristics over the Bay of Bengal as revealed by BOBMEX-98 Pilot experiment

An attempt has been made to study the marine boundary layer characteristics over Bay of Bengal using BOBMEX (Bay of Bengal and Monsoon Experiment) pilot experiment data sets, which was conducted between 23rd October and 12th November 1998 on board ORV Sagar Kanya. A one-dimensional multilevel atmospheric boundary layer with TKE-ε closure scheme is employed to study the marine boundary layer characteristics. In this study two synoptic situations are chosen: one represents an active convection case and the other a suppressed convection. In the present article the marine boundary layer characteristics such as temporal evolution of turbulent kinetic energy, height of the boundary layer and the airsea exchange processes such as sensible and latent heat fluxes, drag coefficient for momentum are simulated during both active and suppressed convection. Marine boundary layer height is estimated from the vertical profiles of potential temperature using the stability criterion. The model simulations are compared with the available observations.     

Detection of major geological structures in the Eastern offshore of India using Geosat altimeter data

Satellite altimetry can be used to infer subsurface geological structures analogous to gravity anomaly maps generated through ship-borne survey. The Eastern offshore was taken up for analysis using Geosat Exact Repeat Mission (ERM) altimeter data. A methodology is developed to use altimeter data as an aid to offshore hydrocarbon exploration. Processing of altimeter data involves corrections for various atmospheric and oceanographic effects, stacking and averaging of repeat passes, cross-over correction, removal of deeper earth and bathymetric effects, spectral analysis and conversion into free-air gravity anomaly. The final processed results were derived for Eastern offshore in the form of prospecting geoid and gravity anomaly maps and their spectral components. The highs and lows observed in those maps were derived in terms of a number of prominent megastructures e.g., gravity linears, 85°E and 90°E ridges, the Andaman trench complex etc. Satellite-derived gravity profiles along 12°N latitude match well with the existing structures.