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Jana, A., Unni, A., Ravuru, S. S., Das, A., Das, D., Biswas, S., et al. (2022). In-situ polymerization into the basal spacing of LDH for selective and enhanced uranium adsorption: A case study with real life uranium alkaline leach liquor. Chemical Engineering Journal, 428, 131180.
Abstract: Uranium is used as a fuel for nuclear power plant and can be extracted from different ores, mainly acidic (silicious ore) and alkaline (carbonate ore). Recovery of uranium through acid leaching from silicious ore is well established, whereas, alkaline leaching from carbonate ore is challenging due to the excessive salinity of leach liquor and high concentration of carbonate, bicarbonate and sulphate. Herein, two monomers, acrylic acid (AA) and N, N-methylene bisacrylamide (BAM), selective towards uranyl were intercalated in-situ into the interlayer, followed by their polymerization and cross-linking to form novel polymer intercalated hybrid layered double hydroxide (LDH). The LDH acts as a backbone to overcome coiling and swelling of polymer and anchors them as free-standing. Various parameters, like, the type of metal ions, monomer ratio (AA: BAM) and metal ion ratio (M2+:M3+), were studied to determine the optimum conditions for effective intercalation and polymerization of monomers. Magnesium aluminum (MgAl) LDH with a cross-linked polymer having a monomer ratio of 3:2 (AA: BAM) as intercalating species showed maximum efficiency of uranyl adsorption (1456 mg/g at 30 °C) with highest capacity so far. The distribution coefficient (Kd, l/mg) in the order of 105 suggested that the adsorbent was highly selective for uranyl in the presence of different cations, anions and humic acid. The adsorbent extracts uranium effectively and selectively from a real-life alkaline leach liquor with an efficiency of 96% at 5 g/l dose. Uranium can be recovered from the adsorbent in the form of sodium di-uranate using 2(M) NaOH and was reused for eight cycles.
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Jin, Z., & Külls, C. (2020). FDM based OA-ICOS for high accuracy 13C quantification in gaseous CO2. EES, 446(3), 032061.
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Jing, M., Kumar, R., Attinger, S., Li, Q., Lu, C., & Heße, F. (2021). Assessing the contribution of groundwater to catchment travel time distributions through integrating conceptual flux tracking with explicit Lagrangian particle tracking. Advances in Water Resources, 149, 103849.
Abstract: Travel time distributions (TTDs) provide an effective way to describe the transport and mixing processes of water parcels in a subsurface hydrological system. A major challenge in characterizing catchment TTD is quantifying the travel times in deep groundwater and its contribution to the streamflow TTD. Here, we develop and test a novel modeling framework for an integrated assessment of catchment scale TTDs through explicit representation of 3D-groundwater dynamics. The proposed framework is based on the linkage between a flux tracking scheme with the surface hydrologic model (mHM) for the soil-water compartment and a particle tracking scheme with the 3D-groundwater model OpenGeoSys (OGS) for the groundwater compartment. This linkage provides us with the ability to simulate the spatial and temporal dynamics of TTDs in these different hydrological compartments from grid scale to regional scale. We apply this framework in the Nägelstedt catchment in central Germany. Simulation results reveal that both shape and scale of grid-scale groundwater TTDs are spatially heterogeneous, which are strongly dependent on the topography and aquifer structure. The component-wise analysis of catchment TTD shows a time-dependent sensitivity of transport processes in soil zone and groundwater to driving meteorological forcing. Catchment TTD exhibits a power-law shape and fractal behavior. The predictive uncertainty in catchment mean travel time is dominated by the uncertainty in the deep groundwater rather than that in the soil zone. Catchment mean travel time is severely biased by a marginal error in groundwater characterization. Accordingly, we recommend to use multiple summary statistics to minimize the predictive uncertainty introduced by the tailing behavior of catchment TTD.
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Johnson, R. S. H., & Alila, Y. (2023). Nonstationary stochastic paired watershed approach: Investigating forest harvesting effects on floods in two large, nested, and snow-dominated watersheds in British Columbia, Canada. Journal of Hydrology, 625, 129970.
Abstract: Drawing on advances in nonstationary frequency analysis and the science of causation and attribution, this study employs a newly developed nonstationary stochastic paired watershed approach to determine the effect of forest harvesting on snowmelt-generated floods. Moreover, this study furthers the application of stochastic physics to evaluate the environmental controls and drivers of flood response. Physically-based climate and time-varying harvesting data are used as covariates to drive the nonstationary flood frequency distribution parameters to detect, attribute, and quantify the effect of harvesting on floods in the snow-dominated Deadman River (878 km2) and nested Joe Ross Creek (99 km2) watersheds. Harvesting only 21% of the watershed caused a 38% and 84% increase in the mean but no increase in variability around the mean of the frequency distribution in the Deadman River and Joe Ross Creek, respectively. Consequently, the 7-year, 20-year, 50-year, and 100-year flood events became approximately two, four, six, and ten times more frequent in both watersheds. An increase in the mean is posited to occur from an increase in moisture availability following harvest from suppressed snow interception and increased net radiation reaching the snowpack. Variability was not increased because snowmelt synchronization was inhibited by the buffering capacity of abundant lakes, evenly distributed aspects, and widespread spatial distribution of cutblocks in the watersheds, preventing any potential for harvesting to increase the efficiency of runoff delivery to the outlet. Consistent with similar recent studies, the effect of logging on floods is controlled not only by the harvest rate but most importantly the physiographic characteristics of the watershed and the spatial distribution of the cutblocks. Imposed by the probabilistic framework to understanding and predicting the relation between extremes and their environmental controls, commonly used in the general sciences but not forest hydrology, it is the inherent nature of snowmelt-driven flood regimes which cause even modest increases in magnitude, especially in the upper tail of the distribution, to translate into surprisingly large changes in frequency. Contrary to conventional wisdom, harvesting influenced small, medium, and very large flood events, and the sensitivity to harvest increased with increasing flood event size and watershed area.
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Joseph, J., & Külls, C. (2014). Calibration of 13C and 18O measurements in CO2 using Off-axis Integrated Cavity Output Spectrometer (ICOS). In EGU Geophysical Abstracts (659).
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