High-Fatality Escalation Pathways in Hazardous Chemical Accidents: A Hierarchical Configurational Analysis for Process Safety
Jingwen Zhang, Yanan Li, Yuhao Wang, Bing FengAccidents in process industries continue to cause severe casualties, and a small number of events account for a large share of fatalities. This study proposes a Topic–Hierarchy Coincidence Analysis (T-H CNA) framework to identify condition combinations associated with high-fatality outcomes by integrating BERTopic, Human Factors Analysis and Classification System (HFACS), and Coincidence Analysis (CNA). The framework is applied to 121 Chinese investigation reports of serious-or-above chemical accidents from 2015 to 2025. BERTopic is used to extract 25 causal semantic themes from accident-cause texts, which are then mapped by expert classification onto eight second-level HFACS categories (Fleiss’κ = 0.7118). On this basis, CNA identifies minimally sufficient configurations (MSCs) and traces their cross-level transmission pathways. Six three-condition MSCs are obtained, with consistency values ranging from 0.750 to 0.923; the broadest pathway covers 28.3% of high-fatality cases. Deficient organizational climate and failure to correct known problems recur as the main upstream endpoints and remain stable under stricter fatality thresholds. Although operational errors appear in 88.43% of cases, they do not enter any sufficient configuration. The results indicate that high-fatality outcomes are more closely associated with coupled upstream organizational and supervisory failures than with terminal errors alone, supporting upstream-oriented process safety governance.