Requirements for estimation of doses from contaminants dispersed by a 'dirty bomb' explosion in an urban area

The mixed layer modified radionuclide atmospheric diffusion based on Gaussian model

Background

Atmospheric diffusion is often accompanied by complex meteorological conditions of inversion temperature.

Methods

In response to the emergency needs for rapid consequence assessment of nuclear accidents under these complex meteorological conditions, a Gaussian diffusion-based model of radionuclide is developed with mixed layer modification. The inhibition effect of the inversion temperature on the diffusion of radionuclides is modified in the vertical direction. The intensity of the radionuclide source is modified by the decay constant.

Results

The results indicate that the enhancement effect of the mixed layer on the concentration of radionuclides is reflected. The shorter the half-life of the radionuclide, the greater the effect of reducing the diffusion concentration. The Kincaid dataset validation in the Model Validation Kit (MVK) shows that, compared to the non-modified model, predictions of the modified model have an enhancement effect beyond 5 km, modulating the prediction values to be closer to the observation values.

Conclusions

This development is consistent with the modification effects of the mixed layer. The statistical indicators show that the criteria of the modified model meet the criteria of the recommended model.

Radiological risk evaluation applied to aerial evacuation procedures in a nuclear scenario

This study evaluates the risk assessment of a hypothetical scenario where an off-site radioactive release occurs at a nuclear power plant. By using the code Accident Reporting and Guiding Operational System (Prolog Development Center - PDC/ARGOS) a numerical simulation was performed to simulate exposure conditions in an atmospheric plume of contamination. Crews on a rescue mission traverse the plume through a pre-defined path to evaluate the risk from a hypothetical radiological exposure. Applying a sophisticated epidemiological assessment methodology, radiation doses and risks on the teams were evaluated. Core variables such as gender, age and radiation dose were considered in relation to specific morbidities. It was possible to propose a methodology capable of contributing to the reduction of risks to the personnel involved by connecting the results from the computer simulation and the epidemiological risk assessment.

Estimation of radiation-induced health hazards from a "dirty bomb" attack with radiocesium under different assault and rescue conditions

In the case of a terrorist attack by a "dirty bomb", blast injuries, external irradiation and the incorporation of radioactivity are to be expected. Departing from information about the radiological attack scenario with cesium-137 in the U.S. National Scenario Planning Guide, we estimated the radiological doses absorbed. Similar calculations were performed for a smaller plume size and a detonation in a subway. For conditions as described in the U.S. scenario, the committed effective dose amounted to a maximum of 848 mSv, even for very unfavorable conditions. Red bone marrow equivalent doses are insufficient to induce acute radiation sickness (ARS). In the case of a smaller plume size, the ARS threshold may be exceeded in some cases. In a subway bombing, doses are much higher and the occurrence of ARS should be expected. The health hazards from a dirty bomb attack will depend on the location and the explosive device. The derived Haddon matrix indicates that preparing for such an event includes education of all the medical staff about radiation effects, the time lines of radiation damages and the treatment priorities. Further determinants of the outcome include rapid evacuation even from difficult locations, the availability of a specific triage tool to rapidly identify victims at risk for ARS, the availability of an antidote stockpile and dedicated hospital beds to treat seriously irradiated victims.

Multi-scenario validation of CALMET-RIMPUFF for local-scale atmospheric dispersion modeling around a nuclear powerplant site with complex topography

The CALMET-RIMPUFF is composed of the California Meteorological Model and the Risø Mesoscale PUFF model, which provides refined atmospheric dispersion modeling for nuclear emergency response. Because the performance of an atmospheric dispersion model can be case-sensitive, a multi-scenario validation is important to understand a model's behavior and limits. In this study, a multi-scenario validation of CALMET-RIMPUFF was performed based on six wind tunnel experiments simulating a real China's nuclear powerplant site with complex topographies and dense buildings. The CALMET-RIMPUFF simulations were compared with the measurements of the vertical wind profiles, 2D ground wind and concentration fields, both qualitatively and quantitatively. The results demonstrate that the CALMET-RIMPUFF can simulate the ground-level wind with acceptable accuracies. For vertical wind profiles, the accuracies show high dependencies on the local topography and building layout. The simulated ground concentrations generally agree well with the measurements, though the plume axis showed slight discrepancies from the measurements in three cases. Because the CALMET-RIMPUFF lacks a building effect module, it shows noticeable discrepancies in the building area. However, such discrepancies do not propagate to the downwind mountainous and sea areas, which the accuracies are quite satisfactory. Thus, the CALMET-RIMPUFF is capable for local-scale modeling at this site.

Preparing for a "dirty bomb" attack: the optimum mix of medical countermeasure resources

BACKGROUND

In radiological emergencies with radionuclide incorporation, decorporation treatment is particularly effective if started early. Treating all people potentially contaminated ("urgent treatment") may require large antidote stockpiles. An efficacious way to reduce antidote requirements is by using radioactivity screening equipment. We analyzed the suitability of such equipment for triage purposes and determined the most efficient mix of screening units and antidote daily doses.

METHODS

The committed effective doses corresponding to activities within the detection limits of monitoring portals and mobile whole-body counters were used to assess their usefulness as triage tools. To determine the optimal resource mix, we departed from a large-scale scenario (60,000 victims) and based on purchase prices of antidotes and screening equipment in Germany, we calculated efficiencies of different combinations of medical countermeasure resources by data envelopment analysis. Cost-effectiveness was expressed as the costs per life year saved and compared to risk reduction opportunities in other sectors of society as well as the values of a statistical life.

RESULTS

Monitoring portals are adequate instruments for a sensitive triage after cesium-137 exposure with a high screening throughput. For the detection of americium-241 whole-body counters with a lower daily screening capacity per unit are needed. Assuming that 1% of the potentially contaminated patients actually need decorporation treatment, an efficient resource mix includes 6 monitoring portals and 25 mobile whole-body counters. The optimum mix depends on price discounts and in particular the fraction of victims actually needing treatment. The cost-effectiveness of preparedness for a "dirty bomb" attack is less than for common health care, but costs for a life year saved are less than for many risk-reduction interventions in the environmental sector.

CONCLUSION

To achieve economic efficiency a high daily screening capacity is of major importance to substantially decrease the required amount of antidote doses. Among the determinants of the number of equipment units needed, the fraction of the potentially contaminated victims that actually needs treatment is the most difficult to assess. Judging cost-effectiveness of the preparedness for "dirty bomb" attacks is an issue of principle that must be dealt with by political leaders.

Risk Analysis of Urban Dirty Bomb Attacking Based on Bayesian Network

Urban dirty bomb attacking is a type of unconventional terrorism threatening the urban security all through the world. In this paper, a Bayesian network of urban dirty bomb attacking is established to analyze the risk of urban dirty bomb attacking. The impacts of factors such as occurrence time, location, wind fields, the size of dirty bomb, emergency response and defense approaches on casualty from both direct blast and radiation-caused cancers are examined. Results show that sensitivity of casualty from cancers to wind fields are less significant; the impact of emergency response on the direct casualty from blast is not large; the size of the dirty bomb results in more casualties from cancers than that from bomb explosions; Whether an attack is detected by the police is not that related to normal or special time, but significantly depends on the attack location; Furthermore, casualty from cancers significantly depends on the location, while casualty from blast is not considerably influenced by the attacking location; patrol and surveillance are less important than security check in terms of controlling the risk of urban dirt bomb, and security check is the most effective approach to decreasing the risk of urban dirty bomb.

A MCREXS modelling approach for the simulation of a radiological dispersal device

Assessing the risks of radioactive dose in a radiological dispersal device (RDD) attack requires knowledge of how the radiological materials will be spread through the air surrounding the site of the detonation. Two essential parts of the accurate prediction of the behaviour of this dispersion are a characterization of the initial cloud size, directly after the blast, and detailed modelling of the behaviour of different size particulates. Capturing the transport of contaminants from the initial blast wave is integral to achieving accurate predictions, especially for regions where the blast dynamics dominates, but performing such calculations over a wide range of particle sizes and spatial scales is computationally challenging. Formulation of efficient computational techniques for such advanced models is required to provide predictive tools useful to first responders and emergency planners. In this work, a Multi-Cloud Radiological EXplosive Source (MCREXS) modelling approach for RDD is investigated. This approach combines a stochastic, particle-based, mechanistic model with a standard atmospheric dispersion model. The former is used to characterize the distribution of radioactive material near the source of the explosion, where the blast wind effects are important, while the latter is used to model the transport of the contaminant in the environment over large areas. The particle transport in the near-field of the explosion site is computed based on a Lagrangian description of the particle phase and a reconstructed-Eulerian field for the carrier phase. The information inferred from this physics-based model is then used as a starting point for a subsequent standard Gaussian puff model to calculate the dispersion of the radioactive contaminant. The predictive capabilities of the MCREXS model are assessed against the 2012 DRDC Suffield full-scale RDD experiments. The results demonstrate improved predictions relative to those performed using only a Gaussian puff calculation from an empirical initial cloud distribution.

Enhanced air dispersion modelling at a typical Chinese nuclear power plant site: Coupling RIMPUFF with two advanced diagnostic wind models

An enhanced air dispersion modelling scheme is proposed to cope with the building layout and complex terrain of a typical Chinese nuclear power plant (NPP) site. In this modelling, the California Meteorological Model (CALMET) and the Stationary Wind Fit and Turbulence (SWIFT) are coupled with the Risø Mesoscale PUFF model (RIMPUFF) for refined wind field calculation. The near-field diffusion coefficient correction scheme of the Atmospheric Relative Concentrations in the Building Wakes Computer Code (ARCON96) is adopted to characterize dispersion in building arrays. The proposed method is evaluated by a wind tunnel experiment that replicates the typical Chinese NPP site. For both wind speed/direction and air concentration, the enhanced modelling predictions agree well with the observations. The fraction of the predictions within a factor of 2 and 5 of observations exceeds 55% and 82% respectively in the building area and the complex terrain area. This demonstrates the feasibility of the new enhanced modelling for typical Chinese NPP sites.

Plasma Retention and Systemic Kinetics of 90Sr Intramuscularly Injected in Female Nonhuman Primates

Thirteen female Rhesus macaques were intramuscularly injected with Sr(NO3)2 diluted in sodium citrate solution. The biokinetic data from these animals were compared against the predictions of the NCRP 156 wound models combined with the ICRP systemic models. It was observed that the activities measured in plasma of these nonhuman primates (NHPs) were consistently lower than those predicted by the default human biokinetic models. The urinary excretion from the NHPs at times immediately after injection was much greater than that in humans. The fecal excretion rates were found to be in relatively better agreement with humans. Similarly, the activities retained in the skeleton of the NHPs were lower than those in humans. These differences were attributed to the higher calcium diet of the NHPs (0.03 to 0.12 g d kg body weight) compared to that of humans. These observations were consistent with the early animal and human studies that showed the effect of calcium on strontium metabolism, specifically urinary excretion. Strontium is preferentially filtered at a much higher rate in kidneys than calcium because it is less completely bound to protein than is calcium. These differences, along with large inter-animal variability, should be considered when estimating the behavior of strontium in humans from the metabolic data in animals or vice versa.

Near-field investigation of the explosive dispersal of radioactive material based on a reconstructed spherical blast-wave flow

A "dirty bomb" is a type of radiological dispersal device (RDD) that has been the subject of significant safety and security concerns given the disruption that would result from a postulated terrorist attack. Assessing the risks of radioactive dose in a hypothetical scenario requires models that can accurately predict dispersion in a realistic environment. Modelling a RDD is complicated by the fact that the most important phenomena occur over vastly disparate spatial and temporal length scales. Particulate dispersion in the air is generally considered on scales of hundreds to thousands of meters, and over periods of minutes and hours. Dispersion models are extremely sensitive, however, to the particle size and source characterization, which are determined in distances measured in micrometers to meters, over milliseconds or less. This study examines the extent to which the explosive blast determines the transport of contaminant particles relative to the atmospheric wind over distances relevant to "near-field" dispersion problems (i.e., hundreds of meters), which are relevant to urban environments. Our results indicate that whether or not the effect of the blast should be included in a near-field dispersion model is largely dependent on the size of the contaminant particle. Relatively large particles (i.e., >40 μm in diameter), which are most likely to be produced by a RDD, penetrate the leading shock front, thereby avoiding the reverse blast wind. Consequently, they travel much farther than suspended aerosols (<10 μm) before approaching the ambient wind velocity. This suggests that, for these "near-field" dispersion problems in urban environments, the transport of contaminants from the blast wave may be integral to accurately predicting their dispersion.

Revision of deposition and weathering parameters for the ingestion dose module (ECOSYS) of the ARGOS and RODOS decision support systems

The ECOSYS model is the ingestion dose model integrated in the ARGOS and RODOS decision support systems for nuclear emergency management. The parameters used in this model have however not been updated in recent years, where the level of knowledge on various environmental processes has increased considerably. A Nordic work group has carried out a series of evaluations of the general validity of current ECOSYS default parameters. This paper specifically discusses the parameter revisions required with respect to the modelling of deposition and natural weathering of contaminants on agricultural crops, to enable the trustworthy prognostic modelling that is essential to ensure justification and optimisation of countermeasure strategies. New modelling approaches are outlined, since it was found that current ECOSYS approaches for deposition and natural weathering could lead to large prognostic errors.