## 4 Discussion
### Critical Causal Path Analysis  
The research proceeded with Bayesian network diagnostic analysis through GeNIe 4.0 subsequent to sensitivity testing. The diagnostic approach reconstructs the most credible accident causation chain through upward reasoning in the Bayesian network framework. Then, the last possible path that caused the accident can be found. First, clear all object nodes, and start from \"Accident\" to \"set evidence\", and then use the computer to calculate the inferred probability of parent nodes of node; for node A (accident node), the a posteriori probability of node A (accident node) is calculated by the computer, assuming that the probability of occurrence of the general accident is 100%, i.e., \(P(A=1)=1\), and its parent node is set as \(X_{i}\). The a posteriori probability of the parent node of A is calculated as detailed in Equation (16):  
\[P(X_{i}=1|A=1)=\frac{P(A=1,X_{i}=1)}{P(A=1)} \tag{16}\]  
According to Equation (16), a parent node with the largest a posteriori probability is identified, and then \"set evidence\" is performed, and so on, until the root node is reached. Consequently, the critical causal pathways for general accidents, larger-scale accidents, and major/severe accidents were successfully identified, as illustrated in Figure 11a-c.  
As can be seen in Figure 11, despite the various accident categories and probability of propagation of the key causal factors, the second half of the path that leads to all kinds of accidents is the same, which is the failure of the safety monitoring and surveillance equipment, which may include the failure of sensors, instruments, or monitoring systems, which results in the impact on the real-time monitoring and detection function of the production process or equipment status. In contrast, the failure of the safety monitoring and surveillance equipment makes the related equipment and facilities unreliable. Because the role of monitoring equipment is to detect and correct potential problems promptly, when monitoring fails, it may result in the equipment failing to be informed of the problem or to take the necessary action promptly. This may leave the entire production system in an unreliable state, and further unreliable equipment and facilities may cause problems in the production process, one of which is the possibility of leakage. With adequate monitoring and control, it may be possible to detect, isolate, or repair potential sources of leakage in time. This can increase the risk of leaks of hazardous substances, which may involve chemicals, gases, or other dangerous substances. Ultimately, these leaks can lead to accidents, which demonstrate dependence on the specific category and size of spilled substance, including fires, explosions, and chemical spills, posing a potential threat to the safety of people and the environment. In the previous accident type statistics, it was also found that the number of accident types such as explosions, fires, poisoning, and asphyxiation, etc., which are closely related to the leakage problems, accounted for 94% of the total number of accidents, which inversely confirms the validity of the accident causation chain. Inadequate regulation is the root cause of both general and significant accidents. Negligence on the part of the regulator may lead to irregular contracting and the involvement of unqualified firms in production, resulting in safety management deficiencies and non-compliance issues. This may lead to lax or false site inspections and affect the maintenance of safety management equipment, such as safety monitoring equipment, that may fail. Failure to wear protective equipment is particularly prominent in significant accidents. This may be due to lax inspections or misrepresentation leading to the inability to implement emergency rescue and drills effectively, and rescue workers may have expanded the accident in the early stages because they needed to wear protective equipment or blindly performed the rescue.