A Risk Assessment Approach for Evaluating the Impact of Toxic Contaminants Released Indoors by Considering Various Emergency Ventilation and Evacuation Strategies

A Simulation Analyzing Approach to Estimating the Probability of Airborne Infection Risks in Railway Station Platform Coupling with the Wells-Riley Model and Pathfinder Model

Railway station platforms present a particular challenge, especially during a train departure or arrival where some passengers may have potential conditions that make them vulnerable to airborne infections due to the high density and close proximity of passengers. This study presented a simulation analyzing approach to estimating the probability of airborne infection risks in station platform spaces coupling with the Wells-Riley model and Pathfinder model. We examine the impact of overcrowded area of the station platform on infection rates under various traces of evacuation. The result of the potential risk for three modes is discussed, and the results of the standard model under the same parameter setting are optimised. Next, the impact of the ventilated volume based on uneven distribution of individuals and the exposure time based on evacuation on the infection risk in platform spaces are studied. The relationship between platform spaces overcrowding and the infection risk provided further insights to observe the supporting information.

Influence of Evacuation Policy on Clearance Time under Large-Scale Chemical Accident: An Agent-Based Modeling

Large-scale chemical accidents that occur near areas with large populations can cause significant damage not only to employees in a workplace but also to residents near the accident site. Despite the increasing frequency and severity of chemical accidents, few researchers have argued for the necessity of developing scenarios and simulation models for these accidents. Combining the TRANSIMS (Transportation Analysis and Simulation System) agent-based model with the ALOHA (Areal Location of Hazardous Atmospheres) dispersion model, this study aims to develop a modeling framework for simulating emergency evacuations in response to large-scale chemical accidents. The baseline accident scenario assumed the simultaneous leakage of toxic chemicals from industrial complexes near residential areas. The ALOHA model results showed that approximately 60% of residents in the scenario's city were required to evacuate their homes. The majority of evacuees completed their evacuations within 5 h in the baseline scenario (evacuating maximum number of private vehicles without any intervention), while the distribution of the population and street network density caused geographical variability in clearance time. Clearance time can be significantly reduced by changing both the evacuees' behaviors and the evacuation policy, which suggests the necessity for proper public intervention when the mass evacuation of residents is required due to chemical accidents.

Concept and demonstration of a fully coupled and dynamic exposure-response methodology for crowd evacuation numerical modelling in airborne-toxic environments

Evacuation simulation plays an indispensable role when planning for emergencies and evaluating the consequences of disasters related to airborne toxics. Various attempts have been made to improve simulation of evacuation in toxic environments and to account for the varying concentration levels and the dynamic exposure. However, most studies neglect the reverse effect, how the exposure and dosage levels affect the physical and psychological state of an evacuee and consequently the evacuation path and process. In this work, a fully coupled exposure-response-evacuation and agent based algorithm is proposed, focusing on the H₂S airborne toxic. Accordingly, the dynamically estimated exposure of the evacuee affects, non-linearly, the evacuation speed and thus the overall evacuation. This coupling is challenging and thus it depends on the available epidemiological and toxicological data. Nevertheless, the diversity and advantages of the algorithm is successfully demonstrated over three case studies including single- and multi-agent in straight-path and building evacuation scenarios. For example, the building evacuation time increased by more than 50% by inclusion of the aforementioned coupling. In conclusion, herein, a gap on the evacuation modelling is addressed by a fully coupled methodology that could be easily adapted by safety engineers and further improved by researchers as more data become available.