Public safety and health cannot be secured without the comprehensive recognition of characteristics and reliable emergency response schemes under the disaster chain. Distinct from emergency resource allocation that focuses primarily on a single disaster, dynamic response, periodic supply, and assisted decision-making are necessary. Therefore, we propose a multiobjective emergency resource allocation model considering uncertainty under the natural disaster chain. Resource allocation was creatively combined with path planning through the proposed multiobjective cellular genetic algorithm (MOCGA) and the improved A* algorithm with avoidance of unexpected road elements. Furthermore, timeliness, efficiency, and fairness in actual rescue were optimized by MOCGA. The visualization of emergency trips and intelligent avoidance of risk areas were achieved by the improved A* algorithm. The effects of logistics performance, coupling of disaster factors, and government regulation on emergency resource allocation were discussed based on different disaster chain scenarios. The results show that disruption in infrastructure support, cascading effect of disasters, and time urgency are additional environmental challenges. The proposed model and algorithm work in obtaining the optimal solution for potential regional coordination and resilient supply, with a 22.2% increase in the total supply rate. Cooperative allocation complemented by political regulation can be a positive action for successfully responding to disaster chains.

Public health and effective risk response cannot be promoted without a coordinated emergency process during a natural disaster. One primary problem with the emergency relief chain is the homogeneous layout of rescue organizations and reserves. There is a need for government-enterprise coordination to enhance the systemic resilience and demand orientation. Therefore, a bi-level multi-phase emergency plan model involving procurement, prepositioning and allocation is proposed. The tradeoff of efficiency, economy and fairness is offered through the multi-objective cellular genetic algorithm (MOCGA). The flood emergency in Hunan Province, China is used as a case study. The impact of multi-objective and coordination mechanisms on the relief chain is discussed. The results show that there is a significant boundary condition for the coordinated location strategy of emergency facilities and that further government coordination over the transition phase can generate optimal relief benefits. Demand orientation is addressed by the proposed model and MOCGA, with the realization of the process coordination in multiple reserves, optimal layout, and transition allocation. The emergency relief chain based on government-enterprise coordination that adapts to the evolution of disasters can provide positive actions for integrated precaution and health security.

Frequent high-rise building fires have posed serious threats to urban public safety. In this study, real-time travel times extracted from online maps were applied to estimate fire service coverage rates for high-rise buildings. Firstly, the minimum fire apparatus requirement for high-rise building “at least 1 water fire truck and 1 aerial fire truck should arrive at the fire scene of high-rise building within 240 s” was proposed. Then, a dynamic estimation model of fire service coverage rate for high-rise buildings was established. To validate the model, 5146 high-rise buildings, 61 water fire trucks, and 56 aerial fire trucks in Changsha were selected as case studies. The results show that the total effective coverage rate and total average travel time in Changsha are 20.43% and 421.95 s, respectively. There are 10,840 water fire trucks and 6192 aerial fire trucks in China. Based on the average number of water fire trucks and aerial fire trucks per high-rise building, it can be estimated that the total effective coverage rate in China may not exceed 60.00%. Due to limited fire resources and frequent traffic congestion, only partial high-rise buildings can be effectively covered by fire services, whether in Changsha or China.

The ignition of combustible materials by electric welding spatters represents a significant cause of fires in welding operations, and the current intensity is a sensitive factor that affects the ignition capacity of welding spatters. In this work, the influence of different current intensities on the physical properties and ignition capacity of welding spatters on common combustible materials was investigated, and the ignition mechanism of electric welding spatter was also explained by means of the hot-spot theory. The results indicated that the splash range, the total generated quantity, the maximum diameter, and the temperature of electric welding spatters increased with the enhancement in current intensity. Furthermore, a higher current intensity was associated with a greater likelihood of producing irregular spatter particles. The probability of ignition of electrode welding spatters was found to be sensitive to their physical properties, exhibiting a non-linear increase with increasing current intensity. At a current intensity of 360 A, a surge in both the physical properties and ignition capacity of the spatters was observed, which is attributed to the coupling of a reduction in the critical hot-spot radius and an unstable pulsation in the arc.

To achieve a scientific and efficient emergency response, a dynamic route-planning strategy for emergency vehicles based on government–enterprise collaboration was studied. Firstly, a hybrid evaluation approach was developed, integrating the Analytic Hierarchy Process, Entropy Weight Method, and Gray Relation Analysis-TOPSIS to quantitatively assess the urgency of demands at disaster sites. Secondly, a government–enterprise coordinated route-planning strategy was designed, leveraging the government’s strong mobilizing capabilities and enterprises’ flexible operational mechanisms. Thirdly, to optimize scheduling efficiency, a dynamic route-planning model was proposed, incorporating multiple distribution conditions to minimize scheduling time, delay penalties, and unmet demand rates. A two-stage cellular genetic algorithm was employed to address realistic constraints such as demand splitting, soft time windows, open scheduling, and differentiated services. Numerical simulations of potential flooding in Hunan Province revealed that the collaborative strategy significantly improved performance: the demand satisfaction rate rose from 70.1% (government-led) to 92.3%, while the material transportation time per unit decreased by 23.6% (from 1.61 to 1.23 min/unit). Vehicle path characteristics varied under different operational behaviors, aligning with theoretical expectations. Even under sudden road disruptions, the model maintained a 98% demand satisfaction rate with only a negligible 0.076% increase in system loss. This research fills the gaps in previous studies by comprehensively addressing multiple factors in emergency vehicle route planning, offering a practical and efficient solution for post-disaster emergency response.

Although fire service accessibility has been extensively studied for urban public facilities such as hospitals and parks, it remains largely unexplored for high-risk industrial facilities such as fireworks manufacturers. In this study, fire risk and transportation network conditions are jointly considered, and a dynamic risk-weighted fire service accessibility evaluation framework is developed. An empirical study was conducted using 35 fire stations and 410 fireworks manufacturers in Liuyang City, China. Fire truck travel times were simulated via online map application programming interfaces (APIs) at 10–30 min intervals over a continuous three-day period, generating 193 evaluation scenarios and 158,260 data samples. The results indicate that the total average travel time of different types of fire trucks to demand points with varying risk levels was found to range from 570.33 to 1362.18 s, and risk-weighted fire service accessibility ranges from 16.84 to 57.26, reflecting a generally poor level of fire service accessibility within the current transport network. To resolve these constraints, it is recommended to optimize the spatial configuration of micro fire stations, promote the collaborative planning of shared enterprise-based fire units, and cross-integrate accessibility metrics into regional industrial land-use planning. These spatial measures are expected to significantly enhance the spatial resilience of transportation systems serving peripheral high-risk industrial clusters.