[1] The ratios of noble gas radioisotopes can provide critical information with which to verify that a belowground nuclear test has taken place. The relative abundance of anthropogenic isotopes is typically assumed to rely solely on their fission yield and decay rate. The xenon signature of a nuclear test is then bounded by the signal from directly produced fission xenon, and by the signal that would come from the addition of xenon from iodine precursors. Here we show that this signal range is too narrowly defined. Transport simulations were done to span the range of geological conditions within the Nevada Test Site. The simulations assume a 1 kt test and the barometric history following the nuclear test at Pahute Mesa in March 1992. Predicted xenon ratios fall outside of the typically assumed range 20% of the time and situations can arise where the ground level signal comes entirely from the decay of iodine precursors. Citation: Lowrey, J. D., S. R. Biegalski, A. G. Osborne, and M. R. Deinert (2013), Subsurface mass transport affects the radioxenon signatures that are used to identify clandestine nuclear tests, Geophys.

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The influence of barometric cycling on gas transport through complex media can be described using a double porosity model. Here vertical channels simulate the effect of cracks that pass through homogeneous regions of media. The cracks are coupled to the atmosphere and act as boundaries for the sections of homogeneous media. Convection-diffusion models are then used to simulate gas transport through the coupled system. This approach has been used to model soil aeration, subsurface movement of volatile compounds, and the migration of gases to the surface after below ground nuclear detonations. In the present work, we describe four stable numerical methods that can be used to implement the double porosity model when first-order reactions produce and consume the gaseous species of interest. We find that all four methods satisfy analytical crosschecks and agree to at least seven digits of precision. An iterative solver based on Newton's method is found to be optimal as it is easily scalable to 3-D models and to multithreaded execution.

Radiation detectors installed at major ports of entry are a key component of the overall strategy to protect countries from nuclear terrorism. While the goal of deploying these systems is to intercept special nuclear material as it enters the country, no detector system is foolproof. Mobile, distributed sensors have been proposed to detect nuclear materials in transit should portal monitors fail to prevent their entry in the first place. In large metropolitan areas, a mobile distributed sensor network could be deployed using vehicle platforms such as taxis, Ubers, and Lyfts, which are already connected to communications infrastructure. However, performance and coverage that could be achieved using a network of sensors mounted on commercial passenger vehicles has not been established. Here, we evaluate how a mobile sensor network could perform in New York City using a combination of radiation transport and geographic information systems. The geographic information system is used in conjunction with OpenStreetMap data to isolate roads and construct a grid over the streets. Vehicle paths are built using pickup and drop off data from Uber, and from the New York State Department of Transportation. The results show that the time to first detection increases with source velocity, decreases with the number of mobile detectors, and reaches a plateau that depends on the strength of the source.

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