Opportunities and Constraints to Rural HAZMAT Risk Reduction

Author:

Thompson Courtney M.,Frazier Tim G.,Vachon Michele D.

Abstract

AbstractThe successful implementation of a hazardous materials (HAZMAT) emergency response plan aimed at risk reduction varies by jurisdiction. Rural communities often face challenges in HAZMAT planning and training due to lower economic vitality that is often a result of fewer economic resources, a lack of knowledge of HAZMAT risk/response training, and data collection limitations. In order to identify opportunities and constraints in HAZMAT planning in rural communities, this paper presents a case study of HAZMAT transportation in North Central in Idaho. Researchers collected and analyzed HAZMAT transportation data to provide a basis for planning and implementation of mitigation measures that help reduce the risks of HAZMAT in rural areas. An interview with the Director of the board of Regional Emergency Managers was conducted to determine the utility of the study for local HAZMAT planning. This study also informs responders about the types of HAZMAT that are transported throughout the region. This information can be used to develop hazard-specific preparedness activities particular to the region, such as training, equipment selection and future grant opportunities. This study also contributes to the limited body of literature that examines challenges rural communities face in HAZMAT risk assessments and risk reduction response planning.

Publisher

Walter de Gruyter GmbH

Subject

Safety Research,Safety, Risk, Reliability and Quality,Business, Management and Accounting (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Risk Assessment of Hazardous Materials Transportation for Small and Tribal Communities in Nebraska;Transportation Research Record: Journal of the Transportation Research Board;2023-07-24

2. Exploration of Hazardous Material Truck Crashes on Wyoming’s Interstate Roads using a Novel Hamiltonian Monte Carlo Markov Chain Bayesian Inference;Transportation Research Record: Journal of the Transportation Research Board;2020-06-30

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