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Exploring an Infrastructure Investment Methodology to Risk Mitigation from Rail Hazardous Materials Shipments Cover

Exploring an Infrastructure Investment Methodology to Risk Mitigation from Rail Hazardous Materials Shipments

By: Ali Vaezi and  Manish Verma  
Open Access
|Jan 2022

Abstract

Railroad is one of the primary modes to transport hazardous materials (hazmat) in North America. For instance, Canadian railroads carried around 50 million tons of hazmat in 2018. Given the inherent danger of trains carrying hazmat, this study aimed at exploring a novel way towards mitigation of the associated risk. This study sought to investigate whether proper rail track infrastructure investment can mitigate the risk from hazmat shipments. To this end, a methodology was developed and then applied to the Canadian railroad network. The proposed three-step methodology captured the differing perspectives of rail carriers and regulatory agencies, and entailed (1) ascertaining the risk-level of various yards and links in the given railroad network, (2) specifying potential candidates for infrastructure investment, and (3) finding the optimum set of investment decisions. The proposed methodology was then applied to the Canadian railroad network to demonstrate that significant risk-reduction can be achieved by adding alternative rail-links around the riskiest locations (i.e. the network hot-spots), and also to show that risk-reduction function is non-linear with non-monotonous behavior. The study showed the possibility of significant hazmat risk reduction through alternative rail-links that could take traffic away from the network hot-spots. The methodology and the results from the Canadian case can be used by railroad companies and policy makers to estimate the value of potentially risk-reducing infrastructure investments.

Language: English
Page range: 1 - 16
Submitted on: Jul 27, 2021
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Published on: Jan 18, 2022
Published by: University of Maribor
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Ali Vaezi, Manish Verma, published by University of Maribor
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.