Analyzing the Risk Factors of Hazardous Chemical Road Transportation Accidents Based on Grounded Theory and a Bayesian Network

Abstract

With the increase in the production and use of hazardous chemicals in China, road transportation safety issues are becoming increasingly prominent. To study the causes of road transportation accidents involving hazardous chemicals, prevent accident occurrence, and realize the safety and sustainable development of the transportation of hazardous chemicals, we combined grounded theory (GT) and a Bayesian network (BN) model to quantify the causal relationship of the interactions among the influencing factors leading to hazardous chemical road transportation accidents that occurred in China in the period of 2017–2020. The influencing factors of these accidents were classified into 5 core categories, 12 main categories, and 28 categories through the GT method, and then a BN-based model was established for these collected accidents. The conditional probability and posterior probability of each influencing factor leading to an accident were determined through BN learning, and then the causal relationship of the interactions between the influencing factors was quantified. The results indicated that the probability of road transportation accidents involving hazardous chemicals considered in this study reaches 72.5% under the combined influence of various factors, and the most likely causal chain of an accident is that equipment failure during the hazardous chemical transportation process contributes to an Unsafe Tanker State, which in turn leads to an accident. The sensitivity analysis confirmed that the key impact factor of hazardous chemical road transportation accidents is equipment failure, followed by improper operation. Overall, this study presents a reference and a foundation for avoiding or reducing risks as much as possible during daily hazardous chemical road transportation operations and risk supervision, realizing safe, sustainable development.