Chemical, biological, radiological, and nuclear (CBRN) events can take a catastrophic toll on human life, the environment, and the economy. This article first presents the beginnings of a framework for the analysis of behavioral aspects of population mobility in the aftermath of a CBRN event in terms of four phases: quarantine, evacuation, resettlement, and return. Population movements are often omitted from economic consequence analyses because of the difficulty of conceptualizing and estimating them. Through a synthesis of the literature in the context of our analytical framework, we provide estimates of the drivers of important dimensions of population mobility relating to compliance, geography, and timing for each major threat type. We also provide an assessment of error bounds on these estimates. Our findings indicate that omission of various dimensions of population mobility can lead to the underestimation of economic consequences of CBRN events by one or two orders of magnitude. The analysis is intended to point out the relative sensitivities of bottom-line economic impacts to the various population mobility dimensions, so as to guide researchers undertaking this estimation and to help prioritize future research on reducing uncertainties in the direction of drivers that are the most impactful.

Given the contemporary increase in the frequency, intensity, and duration of extreme anomalous hydromet hazards (droughts, floods, tropical storms, heatwaves), heightened attention of governments, scientists, media, and humanitarian organizations is being given to hydromet early warning systems. The focus of this article is multidisciplinary and multifaceted: it involves connecting an earliest warning indicator associated with the Oceanic Niño Index, one that complements the existing National Oceanic and Atmospheric Administration indicator, with early warning early action and anticipatory action approaches for disaster risk reduction (DRR). This new indicator in theory at least could increase the lead time between the release of an official forecast of an El Niño and the first appearance of its adverse impacts, thereby serving as the earliest warning of an event. As such, this DRR research links new usable earliest warning information, providing additional time to initiate tactical actions to cope with El Niño-spawned hydromet hazards. Integrating an earliest indicator of the likely onset of an El Niño into early action frameworks would hasten humanitarian assistance by providing at-risk communities and humanitarian organizations with more time to consider a range of options for responding to El Niño’s impacts.

Australia is a significant hotspot for heatwaves due to its geographical location and pronounced climatic variability, and heatwave exposure is expected to further increase in the future with anthropogenic climate change. With the intent to support United Nations Sustainable Development Goals 3 (Good health and well-being) and 13 (Climate action), in this study we identified key challenges and opportunities for adapting to heatwaves, focusing on the most vulnerable members of our community—older adults. A naturalistic, qualitative approach was selected for this study. Data were collected via semistructured interviews. Key insights were captured through a series of semistructured interviews with key informants from local government agencies and community groups that provide care for older adults in New South Wales, Australia. Questions centered around current preventative measures adopted by the organization regarding heatwaves, level of heatwave knowledge of local residents, and common effects of heatwaves in the local community. The findings highlight four primary challenges: (1) increasing duration and intensity of heatwaves; (2) lack of knowledge among older adults regarding symptoms and the effect on the body; (3) the financial and social impacts of heatwaves; and (4) inadequate urban planning practices and building codes including the need for the creation of cool and green spaces. This study provides important insights for protecting our most vulnerable populations from the growing threat of heatwaves.

Formal disaster prevention, preparation, risk management, and response remain highly anthropocentric, with non-human animals afforded minimal attention, resourcing, and support. This article reports on informal community efforts to care for non-human animals during and after the 2019/2020 “Black Summer” bushfires in Australia, when over three billion animals were killed, injured, or displaced. We conducted 56 in-depth interviews with community members, government officials, and experts, and ran four full day workshops with community members to investigate: how communities sought to protect and care for domesticated, farmed, and wild animals; the factors that facilitated and impeded their efforts; and the changes they believed would lead to better outcomes for animals in disasters in the future. Key findings are that: human communities understood and treated non-human animals as part of their communities; humans went to extraordinary lengths to care for and rescue animals; these efforts were largely invisible to, and unsupported—even condemned—by formal emergency management agencies. We conclude that human-centric emergency and disaster management policies are at odds with community values and behaviors. We argue that disaster management must evolve to accommodate and support the realities of community-based rather than individual-based approaches, and must simultaneously expand to consider communities as multispecies.

Organizations play significant roles in society by providing goods and services and contributing to the economies of communities, globally. Amid the predicted increase in the frequency and impact of disasters, which will invariably lead to higher disaster costs, there is an urgent need to ameliorate disaster impact on society and organizations. Disaster mitigation and preparedness are strategies for stemming disaster impact and losses within organizations. Cognizant of the importance of disaster mitigation and preparedness, researchers have conducted a myriad of studies on both concepts at the organizational level. To advance knowledge on this topic, this study conducted a comprehensive systematic literature review by examining the global trends in disaster mitigation and preparedness research at the organizational level, identifying research gaps in methodological dimensions, and recommending future research topics based on gaps in the literature. The authors searched three databases—Web of Science, EBSCO-ProQuest, and ABIinform—for keywords related to the topic and conducted a reverse citation search of the identified studies from the initial search, resulting in a final list of 123 studies. The findings indicate that research on this topic is relatively young and tends to mostly occur in collaborative environments. Additionally, most studies are quantitative and empirical in nature, and much of the research is on North America and Asia. Furthermore, while three-quarters of the studies do not specify a particular hazard type, among those that do, most focus on earthquakes and terrorist attacks in Asia and North America respectively, among other hazard types. This study concluded by recommending areas for future research.

The COVID-19 pandemic has influenced the way the sustainable built environment—encompassing buildings, infrastructure, and other physical structures—is designed, managed, and utilized, as societal responses to the pandemic may have contributed to shifts in priorities and practices in these areas. Research has predominantly focused on the pandemic’s impacts on enhancing the resilience of the built environment and its role in supporting health protocols, such as reducing transmission risks. However, a critical gap persists in understanding the evolving relationship between the various stages of the COVID-19 pandemic and the sustainable built environment. Accordingly, this systematic literature review (SLR) aims to explore the major themes and trends in sustainable built environment responses to the COVID-19 pandemic and identify gaps in existing studies. The authors employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to systematically search four databases for English-language journal articles published between 2020 and 2023. A total of 331 articles were analyzed using descriptive and thematic methods. The findings reveal that research priorities shifted during different stages of the pandemic, with particular attention given to key areas of the sustainable built environment: healthy outdoor spaces, such as urban green spaces (UGS); energy efficiency and urban planning; and urban mobility and transportation. This SLR contributes to advancing risk reduction strategies that address the intricate interdependencies between major health emergencies and long-term sustainability imperatives for the built environment.

The fifth-generation seismic hazard map for China’s mainland (CSHM5) was developed based on the delineated seismic source models and the ground motion models (GMMs) for the peak ground acceleration (PGA) for four different seismic regions. In the present study, we developed a new set of GMMs as functions of the rupture distance or the closest distance to the projection of the rupture plane. The development of the GMMs is based on the projection method and GMMs from the NGA-West2 project. We then estimated, mapped, and compared the seismic hazard in terms of PGA and pseudo-spectral acceleration by using the new set of GMMs and other relevant GMMs, and two seismic source models—one used in developing CSHM5, which includes the fault orientation characterization and the other based on a spatially smoothed source model. The comparison of the estimated seismic hazard indicates that CSHM5 may significantly underestimate the seismic hazard. Part of this is likely due to the inclusion of an additional 15 km focal depth in the original GMM that is adopted for CSHM5. The comparison of the obtained standardized uniform hazard spectra (UHS) to the standardized response spectrum implemented in the current structural design code shows that the value of the latter is greater than that of the former for the natural vibration period less than about 0.1 s or greater than 0.4 s and this is reversed for the natural vibration period around 0.2 s. It is recommended that the use of UHS for design code making should be seriously considered, or at least, the shape of the current implemented standardized design spectrum could be improved.

The probabilistic seismic hazard analysis (PSHA) method used in existing seismic ground motion parameters zonation map of China (the traditional PSHA-CN method) is based on a two-dimensional area seismic source framework and does not account for the rupture dimension of large earthquakes, which may lead to underestimation of seismic hazard at near-fault sites. By employing stochastic sampling to integrate three-dimensional fault sources and two-dimensional area seismic sources, a new PSHA-CN method was developed in recent years, but it faces limitations in accuracy and computational efficiency due to sampling constraints, particularly for low probability of exceedance scenarios or large earthquakes with long return periods. To enhance the computational efficiency of the new PSHA-CN method, this study developed a novel spatial integration algorithm for PSHA. The algorithm considers rupture dimension, enables efficient fault geometry modeling using the Frankel Fault Surface (FFS) and Stirling Fault Surface (SFS) models, and maintains compatibility with the traditional PSHA-CN framework. Validation against test cases from the Pacific Earthquake Engineering Research Center (PEER) demonstrated the algorithm’s reliability. Furthermore, the algorithm was applied to assess seismic hazard in the Changsha-Zhuzhou-Xiangtan metropolitan region in Hunan Province to validate its performance in regions with moderate seismic activity in China. A comparative analysis of the new algorithm results with those of the traditional PSHA-CN method revealed that the PSHA-CN method underestimates near-fault seismic hazards. The proposed algorithm will be implemented in next-generation seismic ground motion parameters zonation map in China.

Post-earthquake building reconstruction usually faces challenges such as inadequate preparation and lack of resources, while compensation measures can help alleviate these difficulties. Although various compensation measures have been proposed for accelerating post-earthquake recovery, their effects on building reconstruction are still unclear. This study aimed to analyze and evaluate the effects of compensation measures on post-earthquake building reconstruction. To achieve this objective, this study first identified the post-earthquake building reconstruction goals, 21 reconstruction factors across five categories, and four compensation measures, and employed the methods of structural equation modeling, paired-samples t-test, and repeated measures analysis of variance to analyze the effects of reconstruction factors on the reconstruction goals and the effects of compensation measures on the reconstruction factors, respectively. A questionnaire was designed to investigate the post-earthquake building reconstruction projects in China, with 251 respondents participated. The results show that apart from project-specific condition, the other four categories of reconstruction factors, including owner condition, technology condition, resource availability, and contractor management capability, have significant effects on the reconstruction goals. The study also evaluated the extent of the above effects. On the other hand, the results indicate that the affecting extents of various compensation measures on reconstruction factors are significantly different. These findings can provide support and guidance for government management of post-earthquake building reconstruction and the development of compensation measures. They also provide a basis for future research on optimizing compensation measures for post-earthquake building reconstruction.

Urban flooding is caused by multiple factors, which seriously restricts the sustainable development of society. Understanding the driving factors of urban flooding is pivotal to alleviating flood disasters. Although the effects of various factors on urban flooding have been extensively evaluated, few studies consider both interregional flood connection and interactions between driving factors. In this study, driving factors of urban flooding were analyzed based on the water tracer method and the optimal parameters-based geographical detector (OPGD). An urban flood simulation model coupled with the water tracer method was constructed to simulate flooding. Furthermore, interregional flood volume connection was analyzed based on simulation results. Subsequently, driving force of urban flooding factors and interactions between them were quantified using the OPGD model. Taking Haidian Island in Hainan Province, China as an example, the coupled model simulation results show that sub-catchment H6 is the region experiencing the most severe flooding and sub-catchment H9 contributes the most to overall flooding in the study area. The results of subsequent driving effect analysis show that elevation is the factor with the maximum single-factor driving force (0.772) and elevation ∩ percentage of building area is the pair of factors with the maximum two-factor driving force (0.968). In addition, the interactions between driving factors have bivariable or nonlinear enhancement effects. The interactions between two factors strengthen the influence of each factor on urban flooding. This study contributes to understanding the cause of urban flooding and provides a reference for urban flood risk mitigation.

Drought is one of the most complicated natural hazards and is among those that pose the greatest socioeconomic risks. How long-term climate change on a large scale affects different types of drought has not been well understood. This study aimed to enhance comprehension of this critical issue by integrating the run theory for drought identification, Mann-Kendall trend analysis, and partial correlation attribution methods to analyze global drought dynamics in 1901–2018. Methodological innovations include: (1) a standardized drought severity metric enabling cross-typology comparisons; and (2) quantitative separation of precipitation and temperature impacts. Key findings reveal that socioeconomic drought severity exceeded meteorological, agricultural, and hydrological droughts by 350.48%, 47.80%, and 14.40%, respectively. Temporal analysis of Standardized Precipitation Evapotranspiration Index (SPEI) trends demonstrated intensification gradients: SPEI24 (− 0.09 slope/100 yr) > SPEI01 (− 0.088/100 yr) > SPEI06 (− 0.087/100 yr) > SPEI12 (− 0.086/100 yr). Climate drivers exhibited distinct patterns, with precipitation showing stronger partial correlations across all drought types (meteorological: 0.78; agricultural: 0.76; hydrological: 0.60; socioeconomic: 0.39) compared to temperature (meteorological: − 0.45; agricultural: − 0.38; hydrological: − 0.27; socioeconomic: − 0.18). These results quantitatively establish a hierarchical climate response gradient among drought types. The framework advances drought typology theory through three original contributions: (1) systematic quantification of cross-typology drought severity disparities; (2) precipitation-temperature influence partitioning across drought types; and (3) identification of socioeconomic drought as the most climate-decoupled yet fastest-intensifying type. This study refined drought typological theories and provides a methodological foundation for climate-resilient drought management planning.

Marine aquaculture plays a significant role in China’s economic development, accounting for nearly one-third of the aquaculture industry. Tropical Cyclone (TC)-induced extreme waves are one of the primary factors that destabilize the structures of aquaculture net cages, resulting in substantial economic losses. However, current research on quantitative risk assessment in marine aquaculture is limited. To fill this gap, we took Northern East China Sea (NECS) as the study area to examine the potential impact of tropical cyclone-induced extreme waves on marine aquaculture. First, we simulated TC-induced extreme waves between 1979 and 2018 by a tightly coupled ADvanced CIRCulation (ADCIRC) model and Simulating Waves Nearshore numerical model, and calculated the probability of occurrence and return period of the hazard. Subsequently, by constructing the failure probability of net cage structures under different significant wave heights, we established a physical vulnerability function relating wave height to failure probability. Using the developed physical vulnerability curves, we assessed the risk faced by offshore marine surface aquaculture under extreme typhoon waves with different return periods, and calculated the expected loss for marine aquaculture. The research results reveal that the hazard of extreme typhoon waves exhibited a spatial pattern of higher occurrences in the vicinity of Qinhuangdao, the Shandong Peninsula, and the northern Jiangsu region compared to other coastal regions, and the risk of marine aquaculture is high in the southern part of Liaoning Province, the eastern part of Shandong Province, and the northeastern part of Jiangsu Province. It is crucial to enhance the capacity for disaster response, reduce potential losses, and improve the ability of marine aquaculture to withstand TC-induced extreme waves in these areas.