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Zeng, S., Shen, Y., Sun, B., Zhang, N., Zhang, S., & Feng, S. (2021). Pore structure evolution characteristics of sandstone uranium ore during acid leaching. Nuclear Engineering and Technology, 53(12), 4033–4041.
Abstract: To better understand the permeability of uranium sandstone, improve the leaching rate of uranium, and explore the change law of pore structure characteristics and blocking mechanism during leaching, we systematically analyzed the microstructure of acid-leaching uranium sandstone. We investigated the variable rules of pore structure characteristics based on nuclear magnetic resonance (NMR). The results showed the following: (1) The uranium concentration change followed the exponential law during uranium deposits acid leaching. After 24 h, the uranium leaching rate reached 50%. The uranium leaching slowed gradually over the next 4 days. (2) Combined with the regularity of porosity variation, Stages I and II included chemical plugging controlled by surface reaction. Stage I was the major completion phase of uranium displacement with saturation precipitation of calcium sulfate. Stage II mainly precipitated iron (III) oxide-hydroxide and aluminum hydroxide. Stage III involved physical clogging controlled by diffusion. (3) In the three stages of leaching, the permeability of the leaching solution changed with the pore structure, which first decreased, then increased, and then decreased.
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Moreau, M., & Daughney, C. (2021). Defining natural baselines for rates of change in New Zealand’s groundwater quality: Dealing with incomplete or disparate datasets, accounting for impacted sites, and merging into state of the-environment reporting. Science of The Total Environment, 755, 143292.
Abstract: To effectively manage sustainably groundwater bodies, it is essential to establish what the naturally occurring ranges of chemical concentrations in groundwaters are and how they change over time. We defined baseline trends for New Zealand groundwaters using: 1) pattern recognition techniques to deal with inconsistent monitoring suites between the national (110 sites) and the denser regional network (\textgreater1000 sites), and 2) multivariate statistics to identify and remove impacted sites from the enhanced dataset. Rates of changes were calculated for 13 parameters between January 2005 and December 2014 at more than 1000 groundwater quality monitoring sites. The resulting dataset included 262 complete cases (CC), which was enhanced using Machine-Learning (ML) techniques to a total of 607 sites. Hierarchical cluster analysis was used to identify trend clusters that were consistent between the CC, ML-enhanced datasets and a 2006 study based on solely on the national network. The largest cluster (WR) consisted of low magnitude changes across all parameters and was attributed to water-rock interaction processes. The second largest cluster (I) exhibited fast changes particularly for parameters linked to human-induced impact. The third largest cluster (D) comprised decreases of all parameters and was associated with dilution processes. Trend clusters were further refined using groundwater quality state information, enabling the identification of impacted sites outside of Cluster I in the ML-enhanced and CC datasets. Corresponding trend baselines were subsequently derived at unimpacted sites using univariate quantile distribution (5th and 95th percentile thresholds). Finally, we developed classifications combining baselines (state and trend) and natural variability to enhance state of the environment reporting. This allowed the new identification of deteriorating trends at sites where groundwater quality state is not yet affected in addition to trend reversals. These classifications can be adapted to incorporate new knowledge or align with surface water quality reporting.
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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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Mathuthu, M., Uushona, V., & Indongo, V. (2021). Radiological safety of groundwater around a uranium mine in Namibia. Physics and Chemistry of the Earth, Parts A/B/C, 122, 102915.
Abstract: Uranium mining activities produce the main element used in nuclear energy production. However, it can also negatively affect the environment including groundwater by release of residues or effluent containing radioactive elements. The study investigated the concentration and radiological hazard of uranium in groundwater and seepage water from the tailings of a uranium mine in Namibia. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was used to assess the concentration of uranium in the groundwater and seepage water and the radiological hazards were determined. The radiological hazard indices Radium equivalent activity (Raeq), Absorbed dose (D), Annual Effective Dose equivalent (AEDE), External hazard index (Hex) and Internal hazard index (Hin) were determined and compared to limits recommended by United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). The calculated average value of D and Hin of groundwater is 108.11nGyh−1 and 1.26, respectively and are above the UNSCEAR values (55 nGyh−1 and 1). Further, the average values of Raeq, AEDE and Hex were below the recommended values. The isotopic ratio of uranium radionuclides in groundwater indicates that the uranium in the sampled groundwater is below 1 suggesting it is not natural uranium present but a possible contamination from the mine seepage. The radiological hazard parameters of the seepage water were above the recommended values and thus pose a radiation risk to human and environment.
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