X-ray absorption spectroscopy identifies calcium-uranyl-carbonate complexes at environmental concentrations

Current research on bioremediation of uranium-contaminated groundwater focuses on supplying indigenous metal-reducing bacteria with the appropriate metabolic requirements to induce microbiological reduction of soluble uranium(VI) to poorly soluble uranium(IV). Recent studies of uranium(VI) bioreduction in the presence of environmentally relevant levels of calcium revealed limited and slowed uranium(VI) reduction and the formation of a Ca-UO₂-CO₃ complex. However, the stoichiometry of the complex is poorly defined and may be complicated by the presence of a Na-UO₂-CO₃ complex. Such a complex might exist even at high calcium concentrations, as some UO₂-CO₃ complexes will still be present. The number of calcium and/or sodium atoms coordinated to a uranyl carbonate complex will determine the net charge of the complex. Such a change in aqueous speciation of uranium(VI) in calcareous groundwater may affect the fate and transport properties of uranium. In this paper, we present the results from X-ray absorption fine structure (XAFS) measurements of a series of solutions containing 50 μM uranium(VI) and 30 mM sodium bicarbonate, with various calcium concentrations of 0-5 mM. Use of the data series reduces the uncertainty in the number of calcium atoms bound to the UO₂-CO₃ complex to approximately 0.6 and enables spectroscopic identification of the Na-UO₂-CO₃ complex. At nearly neutral pH values, the numbers of sodium and calcium atoms bound to the uranyl triscarbonate species are found to depend on the calcium concentration, as predicted by speciation calculations.     

Utilization of a multicriteria least cost path model in an aquatic environment

A critical component of maintaining biodiversity in fragmented habitats is maintaining connectivity among the usable fragments. Least cost path (LCP) analysis is a tool that can be used for predicting the ability of an organism to move from one habitat patch to another, based on geographical features of the landscape and life history traits of the organism. While this analysis has been utilized for terrestrial habitats, it is rarely applied to aquatic environments. Aquatic hypoxic conditions occur when dissolved oxygen falls below 2 mg/L. These conditions can create barriers in the water column that can either force fish to leave a habitat, or avoid that habitat altogether. Using the lower St. Johns River (LSJR) estuary in Florida, USA, as a study system, the ability of an adult silver perch, Bairdiella chrysoura, to escape a large-scale hypoxic event was modeled using a multicriteria LCP approach. Criteria-specific cost grids were constructed based upon current speed, risk of predation, and whether oxygen levels in the habitat area were normoxic (>5.5 mg/L), or hypoxic (<2.0–1.5 mg/L) as a function of water depth for the LSJR. The criteria cost grids were combined using relative weighting to produce the multicriteria cost grid used to implement the LCP analysis. Three origin and destination point locations within the LSJR study area were selected for modeling whether or not a silver perch would be able to escape a hypoxic zone. Since the LCP model will always determine a LCP from the specified origin point location, ecologically relevant swimming capacities for silver perch under normoxic and hypoxic conditions were then applied to assess the model, and to determine whether the fish would be able to reach areas unimpacted by hypoxia. The LCP model and the swimming capacity results for this study predict that under normoxic conditions, fish movement was unimpeded. During the rapidly developing hypoxic event that was modeled, the results from the LCP model indicate that the fish could move outside the hypoxic zone, but when swimming capacities were applied to the model, the silver perch could not escape. Ecologically, the results of this study suggest that silver perch would experience high mortality under a rapidly developing hypoxic event. Additionally, the results of this study indicate that a LCP model can be applied to an aquatic habitat, as long as the cost grids incorporate relevant abiotic and biotic factors.     

The role of social capital,personal networks,and emergency responders in post-disaster recovery and resilience: a study of rural communities in Indiana

The factors that explain the speed of recovery after disaster remain contested. While many have argued that physical infrastructure, social capital, and disaster damage influence the arc of recovery, empirical studies that test these various factors within a unified modeling framework are few. We conducted a mail survey to collect data on household recovery in four small towns in southern Indiana that were hit by deadly tornadoes in March 2012. The recovery effort is ongoing; while many of the homes, businesses, and community facilities were rebuilt in 2013, some are still under construction. We investigate how households in these communities are recovering from damage that they experienced and the role of social capital, personal networks, and assistance from emergency responders on the overall recovery experience. We used an ordered probit modeling framework to test the combined as well as relative effects of (a) damage to physical infrastructures (houses, vehicles, etc.); (b) recovery assistance from emergency responders (FEMA) as well as friends and neighbors; (c) personal network characteristics (size, network density, proximity, length of relationship); (d) social capital (civic engagement, contact with neighbors, trust); and (e) household characteristics. Results show that while households with higher levels of damage experienced slower recovery, those with recovery assistance from neighbors, stronger personal networks, and higher levels of social capital experienced faster recovery. The insights gained in this study will enable emergency managers and disaster response personnel to implement targeted strategies in facilitating post-disaster recovery and community resilience.     

A friction damped base isolation system with fail-safe characteristics

An experimental study of a Coulomb friction damped aseismic base isolation system with fail-safe characteristics is described in this paper. The base isolation system utilized commercially made natural rubber bearings and a skid system which comes into operation at preset-levels of relative horizontal displacement between the structure and the foundation. The fail-safe skid provides hysteretic damping and prevents failure of the isolation system in the event of displacements larger than those assumed in the original design. The isolation system can be designed for an earthquake which can be reasonably expected within the lifetime of the structure; in the event of an earthquake of unanticipated intensity the failsafe system will prevent collapse of the structure. The testing of the system involved an 80,000lb model, approximately 1/3 scale to a real structure mounted on the 20′ × 20′ shaking table at EERC and subject to a variety of earthquake inputs. The results show that the hysteretic effect of the fail-safe system does not greatly increase the accelerations experienced by the structure but considerably reduces the relative displacements at the isolation bearings. The action of the fail-safe system was tested by using an earthquake input that produced a resonant response in the isolated mode of the model. The stability limit of the isolation system was exceeded and the bearings failed but complete failure of the isolation system and thus collapse of the model was prevented by the fail-safe system. The implementation of the system in full scale structures poses no technical or construction problems. An equivalent linearization technique was developed for this system for design purposes using response spectra. The accuracy of this approach was verified by comparison with the experimental results.     

Kriging with imprecise (fuzzy) variograms. I: Theory

Imprecise variogram parameters are modeled with fuzzy set theory. The fit of a variogram model to experimental variograms is often subjective. The accuracy of the fit is modeled with imprecise variogram parameters. Measurement data often are insufficient to create good experimental variograms. In this case, prior knowledge and experience can contribute to determination of the variogram model parameters. A methodology for kriging with imprecise variogram parameters is developed. Both kriged values and estimation variances are calculated as fuzzy numbers and characterized by their membership functions. Besides estimation variance, the membership functions are used to create another uncertainty measure. This measure depends on both homogeneity and configuration of the data.     

Training Images from Process-Imitating Methods

The lack of a suitable training image is one of the main limitations of the application of multiple-point statistics (MPS) for the characterization of heterogeneity in real case studies. Process-imitating facies modeling techniques can potentially provide training images. However, the parameterization of these process-imitating techniques is not straightforward. Moreover, reproducing the resulting heterogeneous patterns with standard MPS can be challenging. Here the statistical properties of the paleoclimatic data set are used to select the best parameter sets for the process-imitating methods. The data set is composed of 278 lithological logs drilled in the lower Namoi catchment, New South Wales, Australia. A good understanding of the hydrogeological connectivity of this aquifer is needed to tackle groundwater management issues. The spatial variability of the facies within the lithological logs and calculated models is measured using fractal dimension, transition probability, and vertical facies proportion. To accommodate the vertical proportions trend of the data set, four different training images are simulated. The grain size is simulated alongside the lithological codes and used as an auxiliary variable in the direct sampling implementation of MPS. In this way, one can obtain conditional MPS simulations that preserve the quality and the realism of the training images simulated with the process-imitating method. The main outcome of this study is the possibility of obtaining MPS simulations that respect the statistical properties observed in the real data set and honor the observed conditioning data, while preserving the complex heterogeneity generated by the process-imitating method. In addition, it is demonstrated that an equilibrium of good fit among all the statistical properties of the data set should be considered when selecting a suitable set of parameters for the process-imitating simulations.     

Simplification and Validation of a Spectral-Tensor Model for Turbulence Including Atmospheric Stability

A spectral-tensor model of non-neutral, atmospheric-boundary-layer turbulence is evaluated using Eulerian statistics from single-point measurements of the wind speed and temperature at heights up to 100 m, assuming constant vertical gradients of mean wind speed and temperature. The model has been previously described in terms of the dissipation rate \(\epsilon \), the length scale of energy-containing eddies \(\mathcal {L}\), a turbulence anisotropy parameter \(\varGamma \), the Richardson number Ri, and the normalized rate of destruction of temperature variance \(\eta _\theta \equiv \epsilon _\theta /\epsilon \). Here, the latter two parameters are collapsed into a single atmospheric stability parameter z / L using Monin–Obukhov similarity theory, where z is the height above the Earth’s surface, and L is the Obukhov length corresponding to \(\{Ri,\eta _\theta \}\). Model outputs of the one-dimensional velocity spectra, as well as cospectra of the streamwise and/or vertical velocity components, and/or temperature, and cross-spectra for the spatial separation of all three velocity components and temperature, are compared with measurements. As a function of the four model parameters, spectra and cospectra are reproduced quite well, but horizontal temperature fluxes are slightly underestimated in stable conditions. In moderately unstable stratification, our model reproduces spectra only up to a scale \(\sim \) 1 km. The model also overestimates coherences for vertical separations, but is less severe in unstable than in stable cases.     

Variable Grid Method: An Intuitive Approach for Simultaneously Quantifying and Visualizing Spatial Data and Uncertainty

Efforts to develop applications and methods that effectively quantify and communicate uncertainty associated with spatial data remains a focus within many scientific communities. However, the inherent complexity of uncertainty makes it difficult to define, characterize, and represent. Frequently, the products of spatial and spatio‐temporal data are presented without a clear explanation of the inherent uncertainty underlying the data. As uses and applications for spatial data and their products continues to increase, so does the importance for utilizing reliable approaches to effectively communicate spatial data along with their inherent uncertainties. To address this need, the Variable Grid Method (VGM) was developed as an intuitive approach that simultaneously communicates both spatial patterns and trends and the uncertainty associated with data or their analyses. This article details the VGM approach and demonstrates the utility of the VGM to provide critical information about the relationship between uncertainty and spatial data, necessary to support the increasing utilization of spatial information for a wide range of research and other needs.     

High- and low-affinity binding sites for Cd on the bacterial cell walls of Bacillus subtilis and Shewanella oneidensis

Bulk Cd adsorption isotherm experiments, thermodynamic equilibrium modeling, and Cd K edge EXAFS were used to constrain the mechanisms of proton and Cd adsorption to bacterial cells of the commonly occurring Gram-positive and Gram-negative bacteria, Bacillus subtilis and Shewanella oneidensis, respectively. Potentiometric titrations were used to characterize the functional group reactivity of the S. oneidensis cells, and we model the titration data using the same type of non-electrostatic surface complexation approach as was applied to titrations of B. subtilis suspensions by Fein et al. (2005). Similar to the results for B. subtilis, the S. oneidensis cells exhibit buffering behavior from approximately pH 3-9 that requires the presence of four distinct sites, with pK_a values of 3.3 ± 0.2, 4.8 ± 0.2, 6.7 ± 0.4, and 9.4 ± 0.5, and site concentrations of 8.9(±2.6) × 10⁻⁵, 1.3(±0.2) × 10⁻⁴, 5.9(±3.3) × 10⁻⁵, and 1.1(±0.6) × 10⁻⁴ moles/g bacteria (wet mass), respectively. The bulk Cd isotherm adsorption data for both species, conducted at pH 5.9 as a function of Cd concentration at a fixed biomass concentration, were best modeled by reactions with a Cd:site stoichiometry of 1:1. EXAFS data were collected for both bacterial species as a function of Cd concentration at pH 5.9 and 10 g/L bacteria. The EXAFS results show that the same types of binding sites are responsible for Cd sorption to both bacterial species at all Cd loadings tested (1-200 ppm). Carboxyl sites are responsible for the binding at intermediate Cd loadings. Phosphoryl ligands are more important than carboxyl ligands for Cd binding at high Cd loadings. For the lowest Cd loadings studied here, a sulfhydryl site was found to dominate the bound Cd budgets for both species, in addition to the carboxyl and phosphoryl sites that dominate the higher loadings. The EXAFS results suggest that both Gram-positive and Gram-negative bacterial cell walls have a low concentration of very high-affinity sulfhydryl sites which become masked by the more abundant carboxyl and phosphoryl sites at higher metal:bacteria ratios. This study demonstrates that metal loading plays a vital role in determining the important metal-binding reactions that occur on bacterial cell walls, and that high affinity, low-density sites can be revealed by spectroscopy of biomass samples. Such sites may control the fate and transport of metals in realistic geologic settings, where metal concentrations are low.