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GIS‐Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness, Planning, and Response for Severe Nuclear Power Plant Accidents
Author(s) -
Pence Justin,
Miller Ian,
Sakurahara Tatsuya,
Whitacre James,
Reihani Seyed,
Kee Ernie,
Mohaghegh Zahra
Publication year - 2019
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.13241
Subject(s) - nuclear power plant , emergency response , preparedness , vulnerability (computing) , emergency management , probabilistic risk assessment , emergency planning , probabilistic logic , disaster planning , risk assessment , risk analysis (engineering) , poison control , social vulnerability , environmental planning , vulnerability assessment , disaster response , medical emergency , suicide prevention , computer science , computer security , business , geography , medicine , political science , artificial intelligence , physics , psychiatry , nuclear physics , law , psychological intervention
In the nuclear power industry, Level 3 probabilistic risk assessment (PRA) is used to estimate damage to public health and the environment if a severe accident leads to large radiological release. Current Level 3 PRA does not have an explicit inclusion of social factors and, therefore, it is not possible to perform importance ranking of social factors for risk‐informing emergency preparedness, planning, and response (EPPR). This article offers a methodology for adapting the concept of social vulnerability, commonly used in natural hazard research, in the context of a severe nuclear power plant accident. The methodology has four steps: (1) calculating a hazard‐independent social vulnerability index for the local population; (2) developing a location‐specific representation of the maximum radiological hazard estimated from current Level 3 PRA, in a geographic information system (GIS) environment; (3) developing a GIS‐based socio‐technical risk map by combining the social vulnerability index and the location‐specific radiological hazard; and (4) conducting a risk importance measure analysis to rank the criticality of social factors based on their contribution to the socio‐technical risk. The methodology is applied using results from the 2012 Surry Power Station state‐of‐the‐art reactor consequence analysis. A radiological hazard model is generated from MELCOR accident consequence code system, translated into a GIS environment, and combined with the Center for Disease Control social vulnerability index (SVI). This research creates an opportunity to explicitly consider and rank the criticality of location‐specific SVI themes based on their influence on risk, providing input for EPPR.