Potential urban threat after a radiological fire event.

An accident involving both fire and radioactive material might eventually deteriorate into a dual-threat situation. Such scenario connects two important consequences: (a) fire damage and (b) radiation health threat. Computational simulations considering hypothetic fire scenarios in hospitals using radioactive material can provide valuable information about such an event. The initial decision in regards to an emergency response should consider the fire consequences and radiation doses distribution in the environment with consequences appearing at different times. While the fire presents an immediate threat, radiation exposure also creates immediate and future concerns. The purpose of this study is to evaluate leukemia risk from a hypothetical radiological fire event in a hospital operating Cs-137 gamma blood irradiator. The simulation in this study used the Hotspot Health Physics software to generate output data such as total effective dose (TED). The data from HotSpot was then used as an input to the leukemia risk equations from Biological Effects of Ionizing Radiation Committee V and VII (BEIR V and VII) models accordingly. Results suggest that the risks are dependent of wind speed and height of release; however, when age and sex are taken into account different outputs are shown. Also, the risk model can be changed from BEIR VII (low doses) to BEIR V (high doses) as radiation doses rise due to its time-dependent behavior. Such change would bring potential impacts on logistics and risk communication.

Impact of the affected population size assessment on the decision-making after a nuclear event.

In this study an improvised nuclear device (IND) is simulated using a software called HotSpot. The explosion took place in a theoretical central business district (CBD), for the major issue addressed in this paper is the comparison of two methods used for estimating the size of the potentially affected population. The first method estimates the size by multiplying the local average demographic density by the area of the zone of interest. The second method uses the population density gradient model developed by Colin Clark in 1951. The comparison of the two methods enables authorities to better estimate the allocation of resources. The conservative approach allocates the maximum resources possible. However, the Clark model enables a more realistic approach which allocates minimum resources to the emergency response. This study shows how accurate information can be quintessential for authorities to maximize the efficiency of their decisions.

Urban critical infrastructure disruption after a radiological dispersive device event.

This study aims to evaluate the impacts of the activation of a hypothetical radiological dispersal device (RDD) on the urban critical infrastructure (health facilities and public transport). A densely populated urban region was chosen as a scenery. Additionally, the influence of local environmental factors in the post-detonation process was verified. The source term was Cs-137 due to its mobility in the environment and relative ease of access. The approach used for the evaluation of the consequences was a computer simulation by Gaussian modeling. The HotSpot Health Physics Codes software was applied in conjunction with the RESRAD-RDD software. The results suggest that there is a strong influence of the local atmospheric stability classes (Pasquill-Gifford classes) on both the total equivalent effective dose (TEDE) and soil contamination. Consequently, the impacts on critical urban infrastructure follow the same trend. The method used for comparing the simulated and reference limits was the proportional ratio. All calculated values for radioactive contamination were divided by the reference value adopted by the RESRAD-RDD model for urban critical infrastructure. The results indicate that the information compiled is useful to support the decision-making process, although it is not sufficient to provide care and support for longer periods than those considered in the initial response phase.