Quantitative Assessment of Safety and Health Risks in HAZMAT Road Transport Using a Hybrid Approach: A Case Study in Tehran

Given the catastrophic consequences of hazardous materials' leakage from trucks, it has become necessary to adopt a coherent approach for quantitative risk assessment in this process. Therefore, this study aimed at assessing the quantitative risk in the road transport of hazardous materials using a Bayesian network and the fuzzy inference system. Using a bowtie analysis in a Bayesian network, this study conducted a cause-consequence analysis of material leakage from trucks. Accordingly, hybrid equations and a fuzzy inference system were used to evaluate the severity of health and safety consequences and determine the severity correction factor of the studied nodes. Finally, the quantitative risk was calculated. Based on the results, it was found that the probability of chemical leakage from trucks carrying hazardous materials was 3.7512 x 10(-1). In addition, the probabilities (in years) of health damage, BLEVE explosion, and fire were 2.47 x 10(-1), 5.775 X 10(-2), and 8.25 x 10(-2), respectively. The safe distance at the time of BLEVE of gasoline and dispersion of chlorine gas was 49.3 and 187 m, respectively. The results of this study showed that the combination of the Bayesian network (BN) and the fuzzy inference system (FIS) could be used as a precise tool for assessing the quantitative risk of hazardous chemicals' transport.