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Although most of the world's uranium exists as pitchblende or uraninite, this mineral can be weathered to a great variety of secondary uranium minerals, most containing the uranyl cation. Anthropogenic uranium compounds can also react in the environment, leading to spatial–chemical alterations that could be useful for nuclear forensics analyses. Soft X‐ray absorption spectroscopy (XAS) has the advantages of being non‐destructive, element‐specific and sensitive to electronic and physical structure. The soft X‐ray probe can also be focused to a spot size on the order of tens of nanometres, providing chemical information with high spatial resolution. However, before XAS can be applied at high spatial resolution, it is necessary to find spectroscopic signatures for a variety of uranium compounds in the soft X‐ray spectral region. To that end, we collected the near edge X‐ray absorption fine structure (NEXAFS) spectra of a variety of common uranyl‐bearing minerals, including uranyl carbonates, oxyhydroxides, phosphates and silicates. We find that uranyl compounds can be distinguished by class (carbonate, oxyhydroxide, phosphate or silicate) based on their oxygen K‐edge absorption spectra. This work establishes a database of reference spectra for future spatially resolved analyses. We proceed to show scanning X‐ray transmission microscopy (STXM) data from a schoepite particle in the presence of an unknown contaminant.  相似文献   
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A transient finite difference groundwater flow model has been calibrated for the Nasia sub-catchment of the White Volta Basin. This model has been validated through a stochastic parameter randomization process and used to evaluate the impacts of groundwater abstraction scenarios on resource sustainability in the basin. A total of 1500 equally likely model realizations of the same terrain based on 1500 equally likely combinations of the data of the key aquifer input parameters were calibrated and used for the scenario analysis. This was done to evaluate model non-uniqueness arising from uncertainties in the key aquifer parameters especially hydraulic conductivity and recharge by comparing the realizations and statistically determining the degree to which they differ from each other. Parameter standard deviations, computed from the calibrated data of the key parameters of hydraulic conductivity and recharge, were used as a yardstick for evaluating model non-uniqueness. All model realizations suggest horizontal hydraulic conductivity estimates in the range of 0.03–78.4 m/day, although over 70 % of the area has values in the range of 0.03–14 m/day. Low standard deviations of the horizontal hydraulic conductivity estimates from the 1500 solutions suggest that this range adequately reflects the properties of the material in the terrain. Lateral groundwater inflows and outflows appear to constitute significant components of the groundwater budgets in the terrain, although estimated direct vertical recharge from precipitation amounts to about 7 % of annual precipitation. High potential for groundwater development has been suggested in the simulations, corroborating earlier estimates of groundwater recharge. Simulation of groundwater abstraction scenarios suggests that the domain can sustain abstraction rates of up to 200 % of the current estimated abstraction rates of 12,960 m3/day under the current recharge rates. Decreasing groundwater recharge by 10 % over a 20-year period will not significantly alter the results of this abstraction scenario. However, increasing abstraction rates by 300 % over the period with decreasing recharge by 10 % will lead to drastic drawdowns in the hydraulic head over the entire terrain by up to 6 m and could cause reversals of flow in most parts of the terrain.  相似文献   
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Atom probe microscopy (APM) is a relatively new in situ tool for measuring isotope fractions from nanoscale volumes (< 0.01 μm3). We calculate the theoretical detectable difference of an isotope ratio measurement result from APM using counting statistics of a hypothetical data set to be ± 4δ or 0.4% (2s). However, challenges associated with APM measurements (e.g., peak ranging, hydride formation and isobaric interferences), result in larger uncertainties if not properly accounted for. We evaluate these factors for Re‐Os isotope ratio measurements by comparing APM and negative thermal ionisation mass spectrometry (N‐TIMS) measurement results of pure Os, pure Re, and two synthetic Re‐Os‐bearing alloys from Schwander et al. (2015, Meteoritics and Planetary Science, 50, 893) [the original metal alloy (HSE) and alloys produced by heating HSE within silicate liquid (SYN)]. From this, we propose a current best practice for APM Re‐Os isotope ratio measurements. Using this refined approach, mean APM and N‐TIMS 187Os/189Os measurement results agree within 0.05% and 2s (pure Os), 0.6–2% and 2s (SYN) and 5–10% (HSE). The good agreement of N‐TIMS and APM 187Os/189Os measurements confirms that APM can extract robust isotope ratios. Therefore, this approach permits nanoscale isotope measurements of Os‐bearing alloys using the Re‐Os geochronometer that could not be measured by conventional measurement principles.  相似文献   
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For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.  相似文献   
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Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.  相似文献   
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Natural Hazards - Tornadoes pose a significant threat to residential communities, causing enormous physical damage and losses to their social fabric. The dominant type of single-family residential...  相似文献   
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This paper presents the development of a probabilistic multi‐model ensemble of statistically downscaled future projections of precipitation of a watershed in New Zealand. Climate change research based on the point estimates of a single model is considered less reliable for decision making, and multiple realizations of a single model or outputs from multiple models are often preferred for such purposes. Similarly, a probabilistic approach is preferable over deterministic point estimates. In the area of statistical downscaling, no single technique is considered a universal solution. This is due to the fact that each of these techniques has some weaknesses, owing to its basic working principles. Moreover, watershed scale precipitation downscaling is quite challenging and is more prone to uncertainty issues than downscaling of other climatological variables. So, multi‐model statistical downscaling studies based on a probabilistic approach are required. In the current paper, results from the three well‐reputed statistical downscaling methods are used to develop a Bayesian weighted multi‐model ensemble. The three members of the downscaling ensemble of this study belong to the following three broad categories of statistical downscaling methods: (1) multiple linear regression, (2) multiple non‐linear regression, and (3) stochastic weather generator. The results obtained in this study show that the new strategy adopted here is promising because of many advantages it offers, e.g. it combines the outputs of multiple statistical downscaling methods, provides probabilistic downscaled climate change projections and enables the quantification of uncertainty in these projections. This will encourage any future attempts for combining the results of multiple statistical downscaling methods. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
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