It remains unlikely that a terrorist organization could produce or procure an actual nuclear weapon. However, the construction of a radiological dispersal device (RDD) from commercially produced radioactive sources and conventional explosives could inflict moderate human casualties and significant economic damage. The vast availability of radioactive sources and the nearly limitless methods of dispersing them demand an inclusive study of the acquisition pathways for an RDD. A complete network depicting the possible acquisition pathways for an RDD could be subjected to predictive modeling in order to determine the most likely pathway an adversary might take. In this work, a comprehensive network of RDD acquisition pathways was developed and analyzed utilizing the Bayesian network analysis software, Netica. The network includes variable inputs and motivations that can be adjusted to model different adversaries. Also, the inclusion of evidence nodes facilitates the integration of real-time intelligence with RDD plot predictions. A sensitivity analysis was first performed to determine which nodes had the greatest impact on successful completion of RDD acquisition. These results detail which portions of the acquisition pathways are most vulnerable to law enforcement intervention. Next, a series of case studies was analyzed that modeled specific adversarial organizations. The analysis demonstrates various features of the constructed Bayesian RDD acquisition network and provides examples of how this tool can be utilized by intelligence analysts and law enforcement agencies. Finally, extreme cases were studied in which the adversary was given the maximum and minimum amount of resources in order to determine the limitations of this model. The aggregated results show that successful RDD acquisition is mostly dependent on the adversary’s resources. Furthermore, the network suggests that securing radiological materials has the greatest effect on interdicting possible RDD plots. Limitations of this work include a heavy dependence on conditional probabilities that were derived from intuition, as opposed to actual historical data which does not exist. However, the model can be updated as attempted or successful RDD plots emerge in the future. This work presents the first probabilistic model of RDD acquisition pathways that integrates adversary motivations and resources with evidence of specific RDD threats.

Large-scale radiological accidents have resulted in intakes of radioactive materials by members of the public and occupational radiation workers. However, current methods to evaluate intakes are designed for small numbers of individuals and cannot be easily scaled for large populations as has occurred. A proposed method for high throughput volumes of people to identify and quantify intakes of radioactive material through urine radiobioassay is described. MATERIALS AND METHODS: The MCNP V6.0 software code was used to model the General Electric Hawkeye V3 Gamma Camera for gamma ray efficiency. Technitium-99m was used to validate the model. The model was used to calculate detection efficiencies and minimum detectable doses for Cobalt-60, Iodine-131, Cesium-137/Barium-137m and Iridium-192. RESULTS: Differences of 8% were observed between measurements of the detection efficiency for Technitium-99m and the MCNP modeled detection efficiency (11.1% vs. 12.0%, respectively). Calculations showed that a dose of 20 mSv could be detected using urine radiobioassay in 6, 3, 2, and 20 days post incident for Type F intakes of Cobalt-60, Iodine-131, Cesium-137/Barium-137m and Iridium-192 respectively. Approximately 1,152 urine samples could be analyzed in an eight-hour shift using a single gamma camera. CONCLUSIONS: The use of the gamma camera for urine radiobioassay allows for high throughput volumes of samples and has sufficient detection sensitivity to meet dose-based decision guidelines.

One of the relatively cheap and easily available instruments suitable for a terrorist attack is the dirty bomb. Using conventional charges (TNT, Semtex etc.) it disperses radioactive materials. Its use is based on contamination of the area where the explosion took place and on creating a radioactive cloud, which may travel rather fast depending on the wind, and which pollutes other areas with its fall-out particles. Such areas become dangerous to live or stay in for a longer period due to the danger of irradiation sickness and cancer. The polluted areas must be decontaminated, which is a very difficult task. Another problem that may occur after the explosion of such a bomb is also panic as well as burns and injuries caused by shells. This work deals with possibilities of radiological weapon construction, the results of using a dirty bomb and with the work of integrated emergency services on such an occasion.

The detonation of a radiological dispersion device (RDD) may result in a situation where many individuals are exposed to contamination due to the inhalation of radioactive materials. Assessments of contamination may need to be performed by emergency response personnel in order to triage the potentially exposed public. The feasibility of using readily available standard 2x2-inch sodium-iodide detectors to determine the committed effective dose to a patient following the inhalation of a radionuclide has been investigated. The 2x2-NaI(Tl) detector was modeled using the Monte Carlo simulation code, MCNP-5, and was validated via a series of experimental benchmark measurements using a polymethyl methacrylate (PMMA) slab phantom. Such validation was essential in reproducing an accurate detector response. Upon verification of the detector model, six anthropomorphic phantoms, based on the MIRD-V phantoms, were modeled with nuclides distributed to simulate inhaled contamination. The nuclides assessed included Am-241, Co-60, Cs-137, I-131, and Ir-192. Detectors were placed at four positions on the phantoms: anterior right torso, posterior right torso, anterior neck, and lateral left thigh. The detected count-rate varied with respect to detector position, and the optimal detector location was determined on the body. The triage threshold for contamination was set at an action level of 250-mSv of intake. Time dependent biokinetic modeling was employed to determine the source distribution and activity in the body as a function of post-inhalation time. The detector response was determined as a function of count-rate per becquerel of activity at initial intake. This was converted to count-rate per 250-mSv intake for triage use by first responders operating the detector to facilitate triage decisions of contamination level. A set of procedure sheets for use by first responders was compiled for each of the phantoms and nuclides investigated.