A comprehensive investigation was engaged to determine the spatial distribution of Uranium (U) and the consequential chemical and radiological health risk associated due to the consumption of groundwater containing U, in Panchkula district. A well-accepted technique of fluorescence of U estimation in an aqueous medium was employed having a detection limit of 0.50 µgL-1. The chemo-radiological health risk and water quality index was computed using a standard equation of concerned agencies to determine the suitability for human health. The concentration of U was observed to vary from 1.70 – 12.28 µgL-1 with the mean value of 5.89 µgL-1 The concentration of U was far below the standard prescribed limits as per World Health Organisation, Atomic Energy Regulatory Board, and United Nation Environmental Protection Agency. Except  nitrate and total alkalinity in few samples, all water quality paramters were within the recommended limit of BIS. The annual effective dose (AED), excess cancer risk (ECR), and lifetime average daily dose (LADD) indicated no potential health issue due to the consumption of groundwater of studied locations. The correlation was computed between U and various macro-anions and cations present in water samples. U was observed to have a significant weak positive correlation with total dissolved solids (TDS), electrical conductivity (EC), and salinity.

The stable stabilization of uranium (U) in iron (Fe) containing environments is restricted by the reoxidation of UO₂. In the current study, based on air reoxidation tests, we propose a novel two steps accumulation method to enrich microbial consortia from paddy soil. The constructed microbial consortia, denoted as the Fe–U bacteria, can co-precipitate U and Fe to form stable Fe–U solids. Column experiments running for 4 months demonstrated the production of U(IV)–O–Fe(II) precipitates containing maximum of 39.51% uranium in the presence of Fe–U bacteria. The reoxidation experiments revealed the U(IV)–O–Fe(II) precipitates were more stable than UO₂. 16S rDNA high throughput sequencing analysis demonstrated that Acinetobacter and Stenotrophomonas were responsible for Fe and U precipitation, while, Caulobacteraceae and Aminobacter were crucial for the formation of U(VI)-PO₄ chemicals. The proposed two steps accumulation method has an extraordinary application potential in stable immobilization of uranium in iron containing environments.

Uranium, a radionuclide, is a predominant element utilized for speciality requirements in industrial applications, as fuels and catalyst. The radioactive properties and chemical toxicity of uranium causes a major threat to the ecosystem. The hazards associated with Uranium pollution includes the cancer in bones, liver, and lungs. The toxicological properties of Uranium are discussed in detail. Although there are many methods to eliminate those hazards, this research work is aimed to describe the application of bioremediation methods. Bioremediation methods involve elimination of the hazards of uranium, by transforming into low oxidation form using natural microbes and plants. This study deeply elucidates the methods as bioleaching, biosorption, bioreduction and phytoremediation. Bioleaching process involves bio-oxidation of tetravalent uranium when it gets in contact with acidophilic metal bacterial complex to obtain leach liquor. In biosorption, chitin/chitosan derived sorbents act as chelators and binds with uranium by electrostatic attraction. Bio reduction employs a bacterial transformation into enzymes which immobilize and reduce uranium. Phytoremediation includes phytoextraction and phytotranslocation of uranium through xylems from soil to roots and shoots of plants. The highest uranium removal and uptake reported using the different methods are listed as follows: bioleaching (100% uranium recovery), biosorption (167 g kg⁻¹ uranium uptake), bioreduction (98.9% uranium recovery), and phytoremediation (49,639 mg kg⁻¹ uranium uptake). Among all the techniques mentioned above, bioleaching has been proved to be the most efficient for uranium remediation.

The derivation of sediment quality guideline values (SQGVs) presents significant challenges. Arguably the most important challenge is to conduct toxicity tests using contaminated sediments with physico-chemistry that represents real-world scenarios. We used a novel metal spiking method for an experiment that ultimately aims to derive a uranium SQGV. Two pilot studies were conducted to inform the final spiking design, i.e. percolating a uranyl sulfate solution through natural wetland sediments. An initial pilot study that used extended mixing equilibration phases produced hardened sediments not representative of natural sediments. A subsequent percolation method produced sediment with similar texture to natural sediment and was used as the method for spiking the sediments. The range of total recoverable uranium (TR-U) concentrations achieved was 8–3200 mg/kg. This reflected the concentrations found in natural wetlands and water management ponds found on a uranium mine site and was above natural levels. Dilute-acid extractable uranium (AE-U) concentrations were >80% of total concentrations, indicating that much of the uranium in the spiked sediment was labile and potentially bioavailable. The portion of TR-U extractable as AE-U was similar at the start and end of the 4.5-month field-deployment. Porewater uranium (PW–U) analyses indicated that partition coefficients (Kd) were 2000–20,000 L/kg, and PW-U was greater in post- than pre-field-deployed samples when TR-U was ≤1500 mg/kg, indicating the binding became weaker during the field-deployment period. At higher spiked-U concentrations, the PW-U was lower post-field-deployment. Comparing the physico-chemical data of the spiked sediments with environmental monitoring data from sediments in the vicinity of a uranium mining operation indicated that they were representative of sediments contaminated by mining and that the U-spiked sediments had a clear U concentration gradient. This confirmed the suitability of the spiking procedure for preparing sediments that were suitable for deriving a SQGV for uranium.

Understanding the radon dispersion released from this mine are important targets as radon dispersion is used to assess radiological hazard to human. In this paper, the main objective is to develop and optimize a machine learning model namely Artificial Neural Network (ANN) for quick and accurate prediction of radon dispersion released from Sinquyen mine, Vietnam. For this purpose, a total of million data collected from the study area, which includes input variables (the gamma data of uranium concentration with 3 × 3m grid net survey inside mine, 21 of CR-39 detectors inside dwellings surrounding mine, and gamma dose at 1 m from ground surface data) and an output variable (radon dispersion) were used for training and validating the predictive model. Various validation methods namely coefficient of determination (R²), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) were used. In addition, Partial dependence plots (PDP) was used to evaluate the effect of each input variable on the predictive results of output variable. The results show that ANN performed well for prediction of radon dispersion, with low values of error (i.e., R² = 0.9415, RMSE = 0.0589, and MAE = 0.0203 for the testing dataset). The increase of number of hidden layers in ANN structure leads the increase of accuracy of the predictive results. The sensitivity results show that all input variables govern the dispersion radon activity with different amplitudes and fitted with different equations but the gamma dose is the most influenced and important variable in comparison with strike, distance and uranium concentration variables for prediction of radon dispersion.

The microbial characteristics and bacterial communities of sediment sludge upon different concentrations of exposure to uranium were investigated by high solution transmission electron microscopy (HRTEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and high-throughput sequencing. After exposure to initial uranium concentrations of 10–50 μM for 24 h in synthetic wastewater, the removal efficiencies of uranium reached 80.7%–96.5%. The spherical and short rod bacteria were dominant in the sludge exposed to uranium. HRTEM-EDS and XPS analyses indicated that reduction and adsorption were the main mechanisms for uranium removal. Short-term exposure to low concentrations of uranium resulted in a decrease in bacterial richness but an increase in diversity. A dramatic change in the composition and abundances of the bacterial community were present in the sediment sludge exposed to uranium. The highest removal efficiency was identified in the sediment sludge exposed to 30 μM uranium, and the dominant bacteria included Acinetobacter (44.9%), Klebsiella (20.0%), Proteiniclasticum (6.7%), Enterobacteriaceae (6.6%), Desulfovibrio (4.4%), Porphyromonadaceae (4.1%), Comamonas (2.4%) and Sedimentibacter (2.3%). By comparison to the inoculum sediment sludge, exposure to uranium caused a substantial difference in the majority of bacterial abundance.

In Iraq, war contamination is the result of dispensed bombs, bullets, detonation of chemical and conventional weapons, and burn-pit emissions by US bases. Increases in congenital anomalies were reported from Iraqi cities post-2003. These cities were heavily bombed and encircled by US bases with burn-pits. Thorium is a radioactive compound and a direct depleted-uranium decay-product. Radioactive materials, including depleted uranium, are routinely stored in US bases and they have been shown to leak into the environment. We conducted a case-control study to investigate associations of residential proximity to Tallil Air Base, a US military base near Nasiriyah, as well as levels of uranium and thorium in hair and deciduous teeth with congenital anomalies. The study was based on a sample of 19 cases and 10 controls who were recruited during late Summer and early Fall of 2016. We developed mixed effects logistic regression models with village as the random effect, congenital anomaly as the outcome and distance to the US base and hair metal levels (one at a time) as the predictor variable, controlling for child's age, sex and paternal education. We also explored the mediation of the association between proximity to the base and congenital anomalies by hair metal levels. We found an inverse association between distance to Tallil Air Base and risk of congenital anomalies and hair levels of thorium and uranium. The results of our mediation analyses were less conclusive. Larger studies are necessary to understand the scope of war contamination and its impact on congenital anomalies in Iraq.

Natural subsurface environment is a complex heterogeneous system. To investigate the effect of ionic strength (IS) and heterogeneity on the transport and remobilization of graphene oxide (GO)-facilitated uranium (U(VI)) in saturated porous media, column experiments were performed by the injection of U(VI) alone and U(VI)+GO mixtures into homogeneous and heterogeneous porous media under low and high ionic strength (1 and 50 mM) conditions, and then the columns were successively flushed with background solution and DI water. Results showed that when U(VI) only was introduced into the columns, IS had little effect on the migration of U(VI) alone in both media and the presence of preferential flow in heterogeneous media slightly enhanced the mobility of U(VI). As U(VI)+GO mixtures were injected into the columns, GO showed strong mobility at low IS and high released peak at high IS. The appearance of GO significantly enhanced U(VI) transport in both media. Under low IS condition, the mobility of U(VI) was significantly enhanced at the injection phase, and the medium heterogeneity further promoted the amount of GO-sorbed U(VI) transport. At high IS, less GO-sorbed U(VI) was observed during injection phase, and a large amount of retained GO-sorbed U(VI) were released with GO remobilization during water flushing phase, and the release showed the longer-tailing phenomenon and the release amount was more pronounced in heterogeneous media. The findings in this study showed that the coupled effect of solution chemistry and media heterogeneity played important roles on GO-facilitated U(VI) transport and release in soil and groundwater system.

Huelva is a highly industrialized city in SW Spain hosting, among others, a Cu smelter, a phosphate fertilizer plant, a power plant, and oil refineries. This study aims to evaluate metal concentrations in lichens as bioindicators of atmospheric pollution in the impacted urban areas. Xanthoria parietina species from Huelva and nearby villages, as well as reference samples from remote, non-contaminated urban areas, were analyzed for trace elements (V, Cr, Mn, Co, Ni, Cu, Zn, Sr, As, Cd, Sb, Cs, Ba, La, Ce, Pr, Nd, Sm, Er, Tm, Yb, Lu, Pb, Th, U) using Inductively Coupled Plasma-Mass Spectrometry; and for major elements (Ca, K, Mg, P, and S) by Inductively Coupled Plasma-Optical Emission Spectrometry after acid digestion.The metal composition of X. parietina exhibits spatial distribution patterns with extremely elevated concentrations (Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Pb, U, and S) in the surroundings of the industrial estates to <1 km distance. Mean concentrations were significantly lower in the urban areas >1 km from the pollution sources. However, air pollution persists in the urban areas up to 4 km away, as the mean concentrations of Cu, Zn, As, Cd, Sb and S remained considerably elevated in comparison to the reference samples. Though rigorous source apportionment analysis was not the aim of this study, a good positive correlation of our results with metal abundances in ambient particulate matter and in pollution sources points to the Cu smelter as the main source of pollution. Hence, the severe air pollution affecting Huelva and nearby urban areas may be considered a serious health risk to local residents.

Abiotic reduction represents an attractive technology to control U(VI) contamination. In this work, an abiotic route of U(VI) reduction with humic acid at mineral surfaces is proposed and reaction mechanisms are addressed by periodic density functional theory calculations. Different influencing factors such as ligand effect, content of CO₃²⁻ ligands and substituent effect are inspected. The coordination chemistry of uranyl(VI) surface complexes relies strongly on substrates and ligands, and the calculated results are in good agreements with experimental observations available. For the OH⁻ ligand, two competitive mechanisms co-exist that respectively produce the U(IV) and U(V) species, and the former is significantly preferred because of lower energy barriers. Instead, the NO₃⁻ ligand leads to the formation of U(V) while for the Cl⁻ ligand, the U(VI) surface complex remains very stable and is not likely to be reduced because of very high energy barriers. The U(V) and U(IV) complexes are the predominant products for low and high CO₃²⁻ contents, respectively. Accordingly, the abiotic reduction processes with humic acid are efficient to manage U(VI) contamination and become preferred under basic conditions or at higher CO₃²⁻ contents. The U(VI) reduction is further promoted by introduction of electron-donating rather than electron-withdrawing substituents to humic acid. Electronic structure analyses and vibrational frequency assignments are calculated for the various uranium surface complexes of the reduction processes, serving as a guide for future experimental and engineered studies. The molecular-level understanding given in this work offers an abiotic route for efficient reduction of U(VI) and remediation of U(VI)-contaminated sites at ambient conditions.