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Application of a plume model for decision makers’ situation awareness during an outdoor airborne HAZMAT release

Ronald G. Meris, BS, MBA, Joseph A. Barbera, MD

Abstract


In a large-scale outdoor, airborne, hazardous materials (HAZMAT) incident, such as ruptured chlorine rail cars during a train derailment, the local Incident Commanders and HAZMAT emergency responders must obtain accurate information quickly to assess the situation and act promptly and appropriately. HAZMAT responders must have a clear understanding of key information and how to integrate it into timely and effective decisions for action planning. This study examined the use of HAZMAT plume modeling as a decision support tool during incident action planning in this type of extreme HAZMAT incident. The concept of situation awareness as presented by Endsley's dynamic situation awareness model contains three levels: perception, comprehension, and projection. It was used to examine the actions of incident managers related to adequate data acquisition, current situational understanding, and accurate situation projection. Scientists and engineers have created software to simulate and predict HAZMAT plume behavior, the projected hazard impact areas, and the associated health effects. Incorporating the use of HAZMAT plume projection modeling into an incident action plan may be a complex process. The present analysis used a mixed qualitative and quantitative methodological approach and examined the use and limitations of a “HAZMAT Plume Modeling Cycle” process that can be integrated into the incident action planning cycle. HAZMAT response experts were interviewed using a computer-based simulation. One of the research conclusions indicated the “HAZMAT Plume Modeling Cycle” is a critical function so that an individual/team can be tasked with continually updating the hazard plume model with evolving data, promoting more accurate situation awareness.


Keywords


HAZMAT, hazardous materials response, incident accident plan, situation awareness, emergency response risk, plume model, emergency management

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References


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DOI: http://dx.doi.org/10.5055/jem.2014.0205

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