From the green color of eskolaite to the red color of ruby: an X-ray absorption spectroscopy study

The best known cause for colors in insulating minerals is due to transition metal ions as impurities. As an example, Cr³⁺ is responsible for the red color of ruby (α-Al₂O₃:Cr³⁺) and the green color of eskolaite (α-Cr₂O₃). Using X-ray absorption measurements, we connect the colors of the Cr _x Al_2−x O₃ series with the structural and electronic local environment around Cr. UV–VIS electronic parameters, such as the crystal field and the Racah parameter B, are related to those deduced from the analysis of the isotropic and XMCD spectra at the Cr L_2,3-edges in Cr_0.07Al_1.93O₃ and eskolaite. The Cr–O bond lengths are extracted by EXAFS at the Cr K-edge in the whole Cr _x Al_2−x O₃ (0.07≤x< 2) solid solution series. The variation of the mean Cr–O distance between Cr_0.07Al_1.93O₃ and α-Cr₂O₃ is evaluated to be 0.01₅ Å (≈1%). The variation of the crystal field in the Cr _x Al_2−x O₃ series is discussed in relation with the variation of the averaged Cr–O distances.     

Real surface conductivity component as indicator for the hydraulic conductivity

Estimation of hydraulic conductivity from surface resistivity measurements is one of the most difficult and challenging hydrogeophysical targets. The promising side of this relation is the analogy between electric current flow and water flow, whereas the grand ambiguity is the non-dimensionality between both two quantities. Imaginary surface conductivity component is used recently to deduce the hydraulic conductivity via complex resistivity measurements. Since there are similar properties between imaginary (out-of-phase) and real (in-phase) surface conductivity components, the latter is used in this paper to predict the hydraulic conductivity. Two mathematical parameters were determined to express the electrical equivalent of hydraulic conductivity in sand and clay systems based on the mode of electrical double-layer formation in both systems. The reliability of the proposed method is tested through applying on two datasets representing sand and clay systems. The first dataset is a clean sand and gravel aquifer in the Keritis basin in Chania, Crete, Greece. The second is mostly clayey sand aquifer in Wadi El-Assuity, Egypt. Application of the present approach in these two cases resulted in promising nearly identical values with the measured hydraulic conductivity via pumping test or geometric hydraulic conductivity via grain size analysis.     

Investigating the robustness of the intraseasonal see-saw in the Indo-Pacific barotropic sea level across models

Ocean Dynamics - An intraseasonal see-saw has been observed in the Indo-Pacific barotropic sea level anomaly during boreal winters. This see-saw carries a significant amount of energy and is...     

Hydro-chemical analysis and ionic flux of meltwater runoff from Khangri Glacier,West Kameng,Arunachal Himalaya,India

The detailed hydro-chemical study of meltwater draining from Khangri glacier Arunachal Pradesh has been carried out to evaluate the major ion chemistry and weathering processes in the drainage basin. The investigative results shows that the meltwater is almost neutral to slightly acidic in nature with Mg–HCO₃-dominated hydro-chemical facies. In glacial meltwater, Ca^+?2 is the most dominated cation followed by Mg⁺², Na⁺, and K⁺, while HCO₃^? is the most dominant anion followed by SO₄^2?, NO₃^?, and Cl^?. The dominant cations such as Ca⁺² and Mg⁺² show a good relation with the minerals abundance of the rocks. Calcite (CaCO₃) and biotite [K(Mg,Fe)₃AlSi₃O₁₀(F,OH)₂] are the most abundant minerals in the deformed carbonate-rich metasedimentary rocks near to the snout with some K feldspar (KAlSi₃O₈) and quartz (SiO₂). This suggests Ca⁺² have definitely entered into the water due to the dissolution of calcite and Ca feldspar (CaAl₂Si₂O₈), while one of the source of Mg⁺² is biotite. Na feldspar (NaAlSi₃O₈) has contributed towards the availability of sodium ion, while potassium ion is derived from the chemical weathering of K feldspar and biotite. The chemical weathering is the foremost mechanism controlling the hydro-chemistry of the Khangri glacier because of the least anthropogenic interferences. The mineralogy of surrounding rocks is studied to understand better, the rock–water interaction processes, and their contribution towards ionic concentration of meltwater. The meltwater discharge and individual ion flux of the catchment area have also been calculated, to determine the ionic denudation rate for the ablation season. The high elemental ratio of (Ca?+?Mg)/(Na?+?K) (7.91?±?0.39 mg/l) and low elemental ratio of (Na?+?K)/total cations (0.11?±?0.004) indicate that the chemical composition of meltwater is mainly controlled by carbonate weathering and moderately by silicate weathering. The scatter plot result between (Ca?+?Mg) and total cations confirms that carbonate weathering is a major source of dissolved ions in Khangri glacier meltwater. In addition, the statistical analysis was also used to determine the correlation between physical parameters of glacier meltwater which controlled the solute dynamics.     

Digital soil mapping in a Himalayan watershed using remote sensing and terrain parameters employing artificial neural network model

Digital soil mapping relies on field observations, laboratory measurements and remote sensing data, integrated with quantitative methods to map spatial patterns of soil properties. The study was undertaken in a hilly watershed in the Indian Himalayan region of Mandi district, Himachal Pradesh for mapping soil nutrients by employing artificial neural network (ANN), a potent data mining technique. Soil samples collected from the surface layer (0–15 cm) of 75 locations in the watershed, through grid sampling approach during the fallow period of November 2015, were preprocessed and analysed for various soil nutrients like soil organic carbon (SOC), nitrogen (N) and phosphorus (P). Spectral indices like Colouration Index, Brightness Index, Hue Index and Redness Index derived from Landsat 8 satellite data and terrain parameters such as Terrain Wetness Index, Stream Power Index and slope using CartoDEM (30 m) were used. Spectral and terrain indices sensitive to different nutrients were identified using correlation analysis and thereafter used for predictive modelling of nutrients using ANN technique by employing feed-forward neural network with backpropagation network architecture and Levenberg–Marquardt training algorithm. The prediction of SOC was obtained with an R² of 0.83 and mean squared error (MSE) of 0.05, whereas for available nitrogen, it was achieved with an R² value of 0.62 and MSE of 0.0006. The prediction accuracy for phosphorus was low, since the phosphorus content in the area was far below the normal P values of typical Indian soils and thus the R² value observed was only 0.511. The attempts to develop prediction models for available potassium (K) and clay (%) failed to give satisfactory results. The developed models were validated using independent data sets and used for mapping the spatial distribution of SOC and N in the watershed.     

Leachability of radium-226 from industrial phosphogypsum waste using some simulated natural environmental solutions

This study investigated the leaching of radium-226 from phosphogypsum (PG) waste produced from the fertilizer industry by synthetic solutions that replicate water that may contact the waste in natural conditions. The results indicated that the activity concentration of Ra-226 in the PG was 461 ± 12 Bq kg^?1 and compared with other studies carried out worldwide. The leached percentage of Ra-226 represents the exchangeable fraction loosely bounded in the matrix of the PG waste. The leached fraction of Ra-226 was 6.5 ± 0.6 and 9.0 ± 0.5% when the waste was exposed to rainwater and saline solution, respectively. It is also found that the leaching fraction increased 10–12 ± 0.4% when the waste was exposed to the admixture of saline solution containing Sr²⁺ or Ba²⁺ cations, whereas it was lowered to 4–5 ± 0.5% in the presence of carbonate or sulfate anions. When the PG is used as an economic fertilizer, the irrigation water can leach 7.8 ± 0.6% of Ra-226 that could contribute to plant uptake, thereby to animal and/or human consumption. The primary tests of the drinking water (well and tap resources) consumed by the populations surround the PG facility showed that the activity concentration of Ra-226 was below the minimum detectable activity.     

A quantitative assessment of groundwater resources in the Middle East and North Africa region

The Middle East and North Africa (MENA) region is the world’s most water-stressed region, with its countries constituting 12 of the 15 most water-stressed countries globally. Because of data paucity, comprehensive regional-scale assessments of groundwater resources in the MENA region have been lacking. The presented study addresses this issue by using a distributed ArcGIS model, parametrized with gridded data sets, to estimate groundwater storage reserves in the region based on generated aquifer saturated thickness and effective porosity estimates. Furthermore, monthly gravimetric datasets (GRACE) and land surface parameters (GLDAS) were used to quantify changes in groundwater storage between 2003 and 2014. Total groundwater reserves in the region were estimated at 1.28 × 10⁶ cubic kilometers (km³) with an uncertainty range between 816,000 and 1.93 × 10⁶ km³. Most of the reserves are located within large sedimentary basins in North Africa and the Arabian Peninsula, with Algeria, Libya, Egypt, and Saudi Arabia accounting for approximately 75% of the region’s total freshwater reserves. Alternatively, small groundwater reserves were found in fractured Precambrian basement exposures. As for groundwater changes between 2003 and 2014, all MENA countries except for Morocco exhibited declines in groundwater storage. However, given the region’s large groundwater reserves, groundwater changes between 2003 and 2014 are minimal and represent no immediate short-term threat to the MENA region, with some exceptions. Notwithstanding this, the study recommends the development of sustainable and efficient groundwater management policies to optimally utilize the region’s groundwater resources, especially in the face of climate change, demographic expansion, and socio-economic development.     

Interplay between urban communities and human‐crowd mobility: A study using contributed geospatial data sources

An intense process of urbanization, witnessed particularly in the last decade, has stressed the need to comprehend human mobility behavior in urban settings. Although the emergence of contributed geospatial data (i.e., pervasive activity‐based data) has contributed to substantial progress toward understanding human activity, the relationship between human‐crowd mobility and the functional structure of a city is not yet well understood. In this context, the present research focuses on the intra‐urban origin–destination matrix modeling founded on a combination of two major crowdsourced datasets as well as the inclusion of urban communities’ structure. Specifically, the well‐known “radiation” and “PWO” models were modified through first, identifying the communities embedded in the cyberspace network then employing the identified hierarchical structure of the spatial‐interaction network for the formulation of the users’ movement network and second, imposing proper input variables including the telecommunication activity volume and check‐in frequency. The results obtained by various empirical analyses suggest that the modified community‐constrained origin–destination flow estimation models exhibit better performance levels than those of alternative conventional mobility models.     

An overview of the diagenesis of the Upper Jurassic carbonates of Jubaila and Hanifa formations, central Saudi Arabia

The Jubaila Formation (Upper Jurassic) in central Saudi Arabia has been divided into lower, middle, and upper parts purely on lithologic grounds. Each part consists of a major lower unit of lime mudstone and a minor upper unit of grainstone. This persistent change in the limestone facies is interpreted as a reflection of repeated shoaling up in the depositional shelf environment. It is a normal marine carbonate sequence that varies in thickness from 85 to 126 m. In the Hanifa Formation, the lowermost brown ledges in the section comprise a series of coarsening upward sequences which generally terminate in a fossiliferous/peloidal packstone and grainstone and subordinately lime mudstone facies. The middle slope member is yellow, blocky weathered shale and marl. Above this slope member are several thick beds of brown-coated fossiliferous wackestone, packstone, and grainstone with the association of lime mudstone in certain levels. These are fairly resistant ledges due to the occurrence of stromatoporoids. Dedolomitization occurs in the Jubaila Formation in various textural forms which include composite calcite rhombohedra, zonal dedolomitization, regeneration of predolomitization fabric of the limestone, and coarsely crystalline calcite mosaics with or without ferric oxide rhombic zones. Rhombohedral pores commonly occur in intimate association with dolomite, possibly resulting from the leaching of calcitized dolomite rhombohedra. The regional dedolomitization was most likely brought about by calcium sulfate solutions reacting with dolomites. The source of sulfate solutions is the dissolved anhydrite deposits of the Arab–Hith Formations, sometime before their erosion, and it takes place at or near an exposed surface. The Hanifa Formation shows various diagenetic features. These include dolomitization, dedolomitization, micritization, cementation, and recrystallization. Most of the examined samples of the Hanifa carbonates are dolomitized and subsequently dedolomitized as evidenced by the presence of iron-coated dolomite rhombs partially or completely calcitized. Dolomite also occurs in the lime mudstone, wackestone, packstone, and grainstone facies, while leaching of wackestone and packstone and dedolomitization of dolomite and dolomitic limestone followed by recrystallization are common processes.