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A methodology combining Bayesian inference with Markov chain Monte Carlo (MCMC) sampling is applied to a real accidental radioactive release that occurred on a continental scale at the end of May 1998 near Algeciras, Spain. The source parameters (i.e., source location and strength) are reconstructed from a limited set of measurements of the release. Annealing and adaptive procedures are implemented to ensure a robust and effective parameter-space exploration. The simulation setup is similar to an emergency response scenario, with the simplifying assumptions that the source geometry and release time are known. The Bayesian stochastic algorithm provides likely source locations within 100 km from the true source, after exploring a domain covering an area of approximately 1800 km × 3600 km. The source strength is reconstructed with a distribution of values of the same order of magnitude as the upper end of the range reported by the Spanish Nuclear Security Agency. By running the Bayesian MCMC algorithm on a large parallel cluster the inversion results could be obtained in few hours as required for emergency response to continental-scale releases. With additional testing and refinement of the methodology (e.g., tests that also include the source geometry and release time among the unknown source parameters), as well as with the continuous and rapid growth of computational power, the approach can potentially be used for real-world emergency response in the near future.

The dielectric function of a charged Bose gas is determined from the response to an imposed static sinusoidal electric field. Variational and diffusion quantum Monte Carlo simulations are used to calculate the ground-state properties of the system with trial wave functions containing a parameter dependent on the amplitude and wavelength of the perturbation. The induced charge is most efficiently extracted from the difference in ground-state energies at different magnitudes of the external field, rather than directly from the expectation value of the density fluctuation operator. Results are compared to the random-phase approximation for the weakly coupled fluid and to classical lattice values at low densities where the system forms a Wigner crystal. The dielectric function is also calculated at intermediate fluid densities and the transition from positive to negative response is found to occur in the metallic regime.

A modified urban canopy parameterization (UCP) is developed and evaluated in a three-dimensional mesoscale model to assess the urban impact on surface and lower-atmospheric properties. This parameterization accounts for the effects of building drag, turbulent production, radiation balance, anthropogenic heating, and building rooftop heating/cooling. U.S. Geological Survey (USGS) land-use data are also utilized to derive urban infrastructure and urban surface properties needed for driving the UCP. An intensive observational period with clear sky, strong ambient wind, and drainage flow, and the absence of a land–lake breeze over the Salt Lake Valley, occurring on 25–26 October 2000, is selected for this study. A series of sensitivity experiments are performed to gain understanding of the urban impact in the mesoscale model. Results indicate that within the selected urban environment, urban surface characteristics and anthropogenic heating play little role in the formation of the modeled nocturnal urban boundary layer. The rooftop effect appears to be the main contributor to this urban boundary layer. Sensitivity experiments also show that for this weak urban heat island case, the model horizontal grid resolution is important in simulating the elevated inversion layer. The root-mean-square errors of the predicted wind and temperature with respect to surface station measurements exhibit substantially larger discrepancies at the urban locations than their rural counterparts. However, the close agreement of modeled tracer concentration with observations fairly justifies the modeled urban impact on the wind-direction shift and wind-drag effects.