Urban Resources Selection and Allocation for Emergency Shelters: In a Multi-Hazard Environment

Emergency Relief Chain for Natural Disaster Response Based on Government-Enterprise Coordination

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.

Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning

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.

Influence of network structure on contaminant spreading efficiency

Contaminants, such as pathogens or non-living substances, can spread through the interaction of their carriers (e.g., air and surfaces), which constitute a network. The structure of such networks plays an important role in the contaminant spread. We measured the contaminant spreading efficiency in different networks using a newly defined parameter. We analyzed basic networks to identify the effect of the network structure on the contaminant spread. The spreading efficiency was highly related to some network parameters, such as the source node's average path length and degree, and considerably varied with the transfer rate per inter-node interaction. We compared the contaminant spreading efficiencies in some complex networks, namely scale-free, random, regular-lattice, and bipartite networks, with centralized, linear, and fractal networks. The contaminant spreading was particularly efficient in the fractal network when the transfer rate was ~0.5. Two categories of experiments were performed to validate the effect of the network structure on contaminant spreading in practical cases: (I) gas diffusion in multi-compartment cabins (II) bacteria transfer in multi-finger networks. The gas diffusion could be well estimated based on the diffusion between two compartments, and it was considerably affected by the network structure. Meanwhile, the bacteria spread was generally less efficient than expected.

Wind disasters adaptation in cities in a changing climate: A systematic review

Wind-related disasters will bring more devastating consequences to cities in the future with a changing climate, but relevant studies have so far provided insufficient information to guide adaptation actions. This study aims to provide an in-depth elaboration of the contents discussed in open access literature regarding wind disaster adaptation in cities. We used the Latent Dirichlet Allocation (LDA) to refine topics and main contents based on 232 publications (1900 to 2019) extracted from Web of Science and Scopus. We conducted a full-text analysis to filter out focal cities along with their adaptation measures. The results show that wind disaster adaptation research in cities has formed a systematic framework in four aspects: 1) vulnerability and resilience of cities, 2) damage evaluation, 3) response and recovery, and 4) health impacts of wind disaster. Climate change is the background for many articles discussing vulnerability and adaptation in coastal areas. It is also embedded in damage evaluation since it has the potential to exacerbate disaster consequences. The literature is strongly inclined towards more developed cities such as New York City and New Orleans, among which New York City associated with Hurricane Sandy ranks first (38/232). Studies on New York City cover all the aspects, including the health impacts of wind disasters which are significantly less studied now. Distinct differences do exist in the number of measures regarding the adaptation categories and their subcategories. We also find that hard adaptation measures (i.e., structural and physical measures) are far more popular than soft adaptation measures (i.e., social and institutional measures). Our findings suggest that policymakers should pay more attention to cities that have experienced major wind disasters other than New York. They should embrace the up-to-date climate change study to defend short-term disasters and take precautions against long-term changes. They should also develop hard-soft hybrid adaptation measures, with special attention on the soft side, and enhance the health impact study of wind-related disasters.

Assessing Emergency Shelter Demand Using POI Data and Evacuation Simulation

Mapping the fine-scale spatial distribution of emergency shelter demand is crucial for shelter planning during disasters. To provide shelter for people within a reasonable evacuation distance under day and night disaster scenarios, we formed an approach for examining the distribution of day and night shelter demand at the plot-scale using point of interest (POI) data, and then analyzed the supply and demand status of shelters after an evacuation simulation built in Python programming language. Taking the downtown areas of Guangzhou, China as a case study, the results show that significant differences exist in the size and spatial distribution of shelter demand in daytime and nighttime, and the total demand is 7.929 million people, which is far larger than the resident population. The average evacuation time of all 16,883 routes is 12.6 min, and after the evacuation, 558 of 888 shelters exceed their capacity to varying degrees, accounting for 62.84% of the total, indicating that the shelters cannot completely receive the potential evacuees. The method proposed in this paper provides a direct quantitative basis for the number and size of new shelter resources being planned during urban renewal activities, and form a reference for land reuse and disaster prevention space organization in future urban planning.

Planning Emergency Shelters for Urban Disasters: A Multi-Level Location–Allocation Modeling Approach

In recent years, cities are threatened by various natural hazards. Planning emergency shelters in advance is an effective approach to reducing the damage caused by disasters and ensuring the safety of residents. Thus, providing the optimal layout of urban emergency shelters is an important stage of disaster management and an act of humanitarian logistics. In order to study the optimal layout of emergency shelters in small mountain cities, this paper constructs multi-level location models for different grades of emergency shelters so as to minimize the travel and construction costs and maximize the coverage rate. Specifically, the actual service of emergency shelters is determined using Geographic Information System (GIS) software and Weighted Voronoi Diagram (WVD) models under the limitation of site capacity, and the space layout is adjusted through combining the actual urban land with the construction position. In this paper, the Jianchuan county seat at Yunnan Province, China, was considered as a case study to illustrate the models of emergency shelters in which the feasibility of the presented models is verified. The proposed research methods and models have provided theoretical basis and a benchmark for the optimal layout of emergency shelters in other small mountain cities.

How Can Cities Respond to Flood Disaster Risks under Multi-Scenario Simulation? A Case Study of Xiamen, China

Flood disasters often have serious impacts on cities. Disaster prevention and mitigation schemes for flood disasters must be based on risk assessment. We constructed an indicator system for flood disaster risk assessment from the aspects of hazard factors, sensitivity to the environment, disaster vulnerability, flood disaster prevention, and resilience. Then we add the precipitation factor as a scenario parameter to the assessment of flood disasters, in order to assess the flood disaster risk under annual average precipitation scenarios, multi-year flood season average precipitation scenarios, and large typhoon precipitation scenarios. Xiamen is one of the cities with more serious flood disasters. We select Xiamen as an example and refer to existing indicators of flood disaster assessment. The results show that: (1) the coefficient of variation of flood disasters in Xiamen under the impact of large-scale typhoon precipitation is large; (2) the drainage and flood control capacity of Xiamen is generally insufficient, and the risk in the old city is high; (3) there are many flood-prone locations in Xiamen. Underpass interchanges, underground spaces, and urban villages have become the new key areas for flood control; and (4) the flood risk in the northern mountainous areas of Xiamen is the highest. Based on the assessment results, we further delineate the urban flood control zones and propose corresponding countermeasures. The study expands the research on flood disaster risk assessment, and also provides reference for relevant cities to deal with flood disasters.

How Can Cities Adapt to a Multi-Disaster Environment? Empirical Research in Guangzhou (China)

Urban disaster risk assessment is the most basic and important part of urban safety development. Conducting disaster prevention and mitigation on the basis of urban disaster risk assessment requires an understanding of the relationship between the city and the natural environment. This enhances the city's ability to withstand various types of disasters and achieves the development of a safe city. Based on a review of the existing literature, we propose a fuzzy comprehensive evaluation method for urban multi-disaster risk assessment. The multi-disaster risk assessment method includes the identification and screening of urban disasters, the assessment of individual disaster risk, and integrated urban disaster risks, the division of urban comprehensive disaster risks into several risk levels, and the determination of coping strategies. Taking Guangzhou (China) as an example, we determined the major disaster risks faced by Guangzhou, assessed the risks of individual disasters, and finally obtained the results of the comprehensive disaster risk of Guangzhou. Second, we analyzed the relationship between the disaster risk assessment and urban safety development, and proposed countermeasures and recommendations for the development of different disaster risk levels.