Radiation-induced cancer risk and decision-making in a simulated Cs-137 urban event

• Autorzy: Andrade Edson R. , Gomes Renato G. , Stenders Ricardo , Brum Tercio , Lima Sergio X. , Castro Mariana S. C. , Silva Ademir X.

Identyfikatory

DOI

10.2478/nuka-2020-0005

• Języki publikacji: EN

Abstrakty

EN

The triggering of a “dirty bomb” generates a complex scenario, with enormous challenges for the responders due to initial misinformation and the urgency to act quickly yet effectively. Normally, the first 100 h are decisive for perceiving the risk in a more realistic dimension, but the support of methodologies that rely on computational simulations can be valuable when making key decisions. This work seeks to provide support for the early decision-making process by using a Gaussian model for the distribution of a quantity of Cs-137 spread by a radiological dispersive device (RDD). By sequentially joining two independent programs, HotSpot Health Physics codes and RESidual RADiation (RESRAD)-RDD family of codes, we came up with results that suggest a segmented approach to the potentially affected population. These results advocate that (a) the atmospheric stability conditions represented by the Pasquill–Gifford classes and (b) the population subgroups defi ned by radiation exposure conditions strongly influence the postdetonation radiological effects. These variables should be taken into account in the elaboration of flexible strategies that include many climatic conditions and to prioritize attention to different groups of public at risk. During the initial phases of such an event, it is believed that simulations using Gaussian models may be of value in anticipating the possible changes in key variables during the decision-making process. These variables may severely affect the effectiveness of the actions of responders and the general public’s safety.

Słowa kluczowe

EN

environmental contamination; dispersive device; decision-making

• Wydawca: Institute of Nuclear Chemistry and Technology
• Czasopismo: Nukleonika
• Rocznik: 2020
• Tom: Vol. 65, No. 1
• Strony: 37--43
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Andrade Edson R.

• IBMEC, Faculty of Engineering, Graduate Program Rio de Janeiro, Brazil
• Nuclear Engineering Graduate Program Federal University of Rio de Janeiro (COPPE/UFRJ) Rio de Janeiro, Brazil
• Defense Engineering Graduate Program Military Institute of Engineering Praça General Tibúrcio 80, Rio de Janeiro, Brazil

autor

Gomes Renato G.

• Nuclear Engineering Graduate Program Federal University of Rio de Janeiro (COPPE/UFRJ) Rio de Janeiro, Brazil

autor

Stenders Ricardo

• IBMEC, Faculty of Engineering, Graduate Program Rio de Janeiro, Brazil

autor

Brum Tercio

• Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro, Brazil

autor

Lima Sergio X.

• Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro, Brazil

autor

Castro Mariana S. C.

• Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro, Brazil

autor

Silva Ademir X.

• Nuclear Engineering Graduate Program Federal University of Rio de Janeiro (COPPE/UFRJ) Rio de Janeiro, Brazil

Bibliografia

• 1. Rother, F. C., Rebello, W. F., Healy, M. J. F., Silva, M. M., Cabral, P. A. M., Vital, H. C., & Andrade, E. R. (2016). Radiological risk assessment by convergence methodology model in RDD scenarios. Risk Anal., 36(11), 2039–2046.
• 2. Andrade, C. P., Souza, C. J., Camerini, E. S. N., Alves, I. S., Vital, H. C., Healy, M. J. F., & De Andrade, E. R. (2018). Support to triage and public risk perception considering long-term response to a Cs-137 radiological dispersive device scenario. Toxicol. Ind. Health, 34(6), 433–438.
• 3. Jeong, H., Park, M., Jeong, H., Hwang, W., Kim, E., & Han, M. (2013). Radiological risk assessment caused by RDD terrorism in an urban area. Appl. Radiat. Isot., 79, 1–4.
• 4. Porter, K., & Lee, L. (2007). Radiological terrorism scenarios. Prehosp. Disaster Med., 22(6), 547.
• 5. Harper, F. T., Musolino, S. V., & Wente, W. B. (2007).Realistic radiological dispersal device hazard boundaries and ramifications for early consequence management decisions. Health Phys., 93(1), 1–16.
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• 13. Maillie, H. D., Simon, W., Watts, R. J., & Quinn, B. R. (1993). Determining person-years of life lost using the BEIR V method. Health Phys., 64(5), 461–466.
• 14. Maillie, H. D., & Jacobson, A. P. (1992). A graphical method of estimating fatal radiation-induced cancers using the BEIR V method. Health Phys., 63(3), 273–280.
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• 16. Institute of Medicine. (1999). Follow-up of persons with known or suspected exposure to ionizing radiation. In Potential radiation exposure in military operations: Protecting the soldier before, during, and after (pp. 88–107). Washington, DC: The National Academies Press. Available from https://doi.org/10.17226/9454.
• 17. IAEA. (1996). Methods for estimating the probability of cancer from occupational radiation exposure. Vienna: International Atomic Energy Agency. (IAEATECDOC-870).
• 18. INCa. (2018). Estimate/2018 – Cancer incidence in Brazil. Rio de Janeiro: Instituto Nacional de Câncer José Alencar Gomes da Silva.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).