Search Results (144)

Hurricanes create compound hazards such as storm surge, flooding, and wind-driven debris that can degrade roadway capacity, fragment network connectivity, and hinder evacuation and shelter operations. From a sustainability perspective, improving evacuation planning is essential for reducing disaster-related losses, protecting vulnerable populations, and strengthening the resilience of coastal communities facing intensifying climate-driven hazards. This paper develops a micro-scale, agent-based evacuation modeling framework to assess evacuation performance under baseline and compound-hazard conditions, with emphasis on municipal decision support. The framework is demonstrated for Westbrook, Connecticut, at the census block-group scale in AnyLogic by integrating household locations, vehicle availability, road-network connectivity, and shelter capacities from publicly available datasets. Evacuation propensity and destination choice are parameterized using survey data, enabling empirically grounded decisions for in-town versus out-of-town evacuation among household-vehicle agents. Compound disruptions are represented through flood-related road closures derived from SLOSH storm-surge outputs and stochastic wind-related disruptions that dynamically constrain accessibility during the simulation. Scenarios are evaluated for Saffir–Simpson Category 1–2 and Category 3–4 hurricanes under baseline and compound conditions. Model outputs quantify normalized evacuation time, congestion and critical intersections, shelter demand and unmet capacity, evacuation failure, and spatial heterogeneity across block groups. Results indicate that compound flooding substantially increases evacuation times and failure rates, with the largest performance degradation concentrated in higher-vulnerability areas. Optimization experiments further compare the effectiveness of behavioral shifts, shelter-capacity expansion, and earlier departure timing in reducing delays and unmet shelter demand. Overall, the proposed framework provides transparent, reproducible, and scalable analytics that town engineers and emergency planners can use to evaluate evacuation readiness under compound hurricane impacts. Full article

Existing standards for distribution network safety under combined typhoon–rain hazards often overlook the nonlinear coupling effects induced by rain impact. To address this issue, this paper proposes a refined modeling and threshold-based failure assessment framework for distribution pole–line systems under coupled wind–rain loading. A full dynamic model is established by integrating a multi-point spatiotemporally coherent wind field with raindrop impact effects, and the coupled time-domain response of the system is then simulated. The results indicate that wind–rain coupling significantly amplifies the dynamic response, with nonlinear energy accumulation occurring at the pole base. Under the analyzed extreme case, this amplification causes the pole-base stress to first exceed the collapse threshold within the simulated duration, indicating that neglecting rain loads may lead to a non-conservative assessment of system safety. In addition, the results reveal differentiated failure characteristics among components: conductors are primarily associated with functional flashover risk, whereas poles are more directly exposed to structural failure demand. These findings provide a preliminary analytical basis for the differential reinforcement and resilience enhancement of coastal distribution networks. Full article

The increasing frequency and intensity of extreme climate events have posed more geohazards worldwide. It is therefore crucial to quantify and map risk to reduce disaster-related losses. The main objective of this study is to propose a quantitative framework to conduct risk assessment of buildings and infrastructures impacted by geohazards. A debris flow hazard in Tianjin, North China was taken as a case study. A physically based model and the Gumbel extreme value distribution were utilized to construct a range of extreme rainfall and runoff scenarios. The FLO-2D and ABAQUS software were subsequently employed to simulate the surging behavior of the debris flow and assess the structural vulnerability of buildings, respectively. Furthermore, the number of elements at risk and economic values were estimated to generate risk maps. The results revealed that variations in peak discharge in the channel evidently affected flow velocity and depth, thus elevating the debris flow intensity and the likelihood of the materials threatening buildings. The stiffness degradation of concrete was strategically used as the indicator to quantify structure vulnerability and effectively present the dynamic responses under the impacts of the debris flow. Under a 100-year return period rainfall scenario, the proportion of very high- and high-risk areas reached 31%, with the estimated economic loss approximately ¥167.7 million. This highlighted the critical role that extreme rainfall played in shaping both the spatial distribution and severity of debris flow risks. The proposed method provides a scientific basis for enhancing the resilience of mountainous regions to compound natural disasters exacerbated by climate change. Full article

Compound geological disaster chains pose major challenges for disaster prevention in mountainous regions due to their complex mechanisms and cascading impacts. This study investigates a landslide–debris flow–flash flood hazard chain that occurred on 21 July 2024 in the Xujia River catchment, Mianning County, Sichuan Province, China. This event is used as a representative case to improve the understanding of the formation and amplification mechanisms of breach-type debris flows through dynamic inversion constrained by sedimentary records. The objective is to reconstruct the evolution of the event and assess its downstream hazard extent. Post-disaster sedimentary and geomorphological records, including deposit distribution, channel aggradation, and flow traces, were systematically analyzed based on remote sensing interpretation, unmanned aerial vehicle surveys, and detailed field investigations. These sedimentary data were used as key constraints to estimate debris flow magnitude and mobility under different rainfall scenarios. A rainfall flood scenario-based estimation method was applied to quantify debris flow magnitude, and numerical simulations were conducted using the Rapid Mass Movement Simulation model to reproduce debris flow propagation and deposition processes. The results indicate that prolonged antecedent rainfall triggered slope failure in a tributary, leading to the accumulation of landslide-derived material and the formation of a temporary channel blockage. The subsequent breach of this blockage significantly amplified debris flow discharge, velocity, and sediment outflow, resulting in downstream hazard expansion. Simulation results constrained by sedimentary evidence show that peak discharge and solid material output under breach conditions were approximately three times higher than those of rainfall-driven scenarios under comparable rainfall frequencies. These findings demonstrate that sedimentary records provide critical constraints for the inversion of landslide debris flow disaster chain dynamics and highlight the effectiveness of post-disaster evidence based numerical assessment for hazard analysis and risk mitigation in debris flow-prone mountainous catchments. Full article

Snowmelt-season sediment hazards in cold regions are becoming increasingly complex under climate change, as rising air temperatures and rainfall-on-snow events enhance interactions between snow, meltwater, and sediment. Compound processes may generate hazard magnitudes that are inadequately captured when avalanches and debris flows are assessed independently. This study develops a first-order framework for assessing snowmelt-season sediment hazards, using the 2018 Nozuka Tunnel disaster in Hokkaido, Japan, as a case study. Numerical simulations for the three scenarios (avalanche flow, debris flow, and snow–sediment mixed flow) were conducted under identical topographic and numerical conditions to evaluate the influence of snow–sediment interactions on the flow behavior, affected area, and deposition characteristics. Key initiation and material parameters were constrained via inverse analysis (parameter-search calibration) using the observed deposition extent, and Sentinel-1 SAR-derived surface change areas were used as independent spatial information to assess the plausibility and spatial consistency of the simulated deposition footprint. Future hazard amplification was examined using projected climate conditions. The snow–sediment mixed-flow scenario produces larger affected areas and deposition volumes than simulations that treat avalanche- or debris flow processes independently, and its simulated deposition extent is spatially consistent with SAR imagery. Future hazards may be amplified under warmer and wetter conditions. The proposed framework integrates disaster records, topographic analysis, validated snow–sediment mixed-flow simulations, and impact-area estimations to support hazard assessment and disaster mitigation in snow-dominated cold regions. These insights support climate-adaptive, sustainable infrastructure risk management in snow-dominated cold regions. Full article

Coal mining in plain regions and its related surface subsidence and geological hazards have been extensively studied, whereas research on mining-induced hazards in mountainous areas remains limited. This knowledge gap has contributed to the frequent occurrence of mining disasters, particularly under steep ridge-type mountain geometry, where deformation characteristics, large-scale slope failure risks, and mining-induced hazard mechanisms remain poorly understood. In this study, a mining area in Zhenxiong, Zhaotong, Yunnan Province, China, is investigated using SBAS-InSAR, GNSS observations, UAV surveys, optical satellite imagery, and detailed field investigations. Surface hazards triggered by coal extraction are identified, and the response relationship between surface subsidence and mining activities is analyzed to reveal the development mechanisms of surface deformation beneath steep ridge-type mountain geometry. The results show that: (1) deep coal mining can still induce significant surface deformation due to the combined amplification effects of steep slopes and lithological conditions; (2) mining-induced deformation does not necessarily evolve into large-scale slope collapse and may gradually stabilize through natural adjustment processes; (3) SBAS-InSAR, validated by GNSS and field observations, provides an effective approach for detecting mining-related subsidence; (4) surface deformation in the study area is jointly influenced by multiple working faces; and (5) strong coupling between the unique steep ridge-type mountain geometry and underlying coal extraction leads to a compound disaster chain under multi-source interactions. These findings offer a critical scientific understanding of mining-induced deformation beneath steep ridge-type mountain geometry and provide important guidance for geological hazard prevention and control in similar mountainous mining areas. Full article

Sea-level rise (SLR), a climate hazard driven by global warming, poses a severe threat to low-lying coastal regions when combined with strong typhoons and storm surges, endangering human lives and socio-economic development. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a core strategic zone for China’s economic development and is increasingly affected by such compound hazards, exacerbating its storm-related disasters amid climate change. Here, we analyze long-term observational data from the GBA using mathematical statistics and simulation methods to address these climate-related challenges. This study predicts future scenarios of extreme water levels in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), aiming to assess the hazard posed by storm surge disasters under varied sea-level rise (SLR) scenarios. The findings indicate that, under future climate projections, both the extreme water levels in the GBA and the hazard of storm surge disasters in its floodplain areas will exhibit a significant upward trend—with the degree of hazard amplification positively correlated with the magnitude of SLR. This study provides a scientific basis to improve the accuracy of extreme water-level prediction, supporting more reliable short-term early flood warnings. It also offers guidance for optimizing SLR-adapted coastal zone spatial planning, guiding the layout of storm surge control projects and land use in high-hazard areas. Additionally, our results fill a gap in the literature on the SLR’s impact in the GBA and support decision-makers in the GBA in building climate resilience and mitigating disaster hazards. Full article

Tetanus, a disease caused by the neurotoxin-producing bacteria Clostridium tetani (C. tetani), remains a serious threat, particularly among individuals who are unvaccinated or under-vaccinated. Although public health guidelines in the United States continue to recommend a well-established, multi-dose vaccination schedule to prevent tetanus, recent revisions to the Centers for Disease Control and Prevention webpage language on vaccine safety prompted renewed public discussion. Despite this, extensive evidence continues to demonstrate the effectiveness and safety of tetanus immunization, and certain demographic groups remain disproportionately at risk. Globally and within the United States, natural disaster zones remain especially high-risk environments for tetanus infection. This review examines the pathophysiology of tetanus, current vaccination recommendations, and the social and geographic inequities that influence vaccine uptake. It also evaluates strategies of protection and prevention. Particular emphasis is placed on tetanus risk in disaster settings, where disrupted infrastructure, greater likelihood of contaminated wounds, and preexisting disparities in vaccination coverage compound vulnerability. A clearer understanding of these factors is essential for strengthening public health preparedness and ensuring equitable protection against tetanus, especially for populations disproportionately affected by disasters. Full article

Global climate change has emerged as a critical challenge for human society in the 21st century. As hubs of population and economic activity, urban and rural areas are increasingly exposed to complex and compounded disaster risks. To systematically evaluate the role of educational intervention in climate adaptability capacity building, this study employs a case study approach, focusing on the “Climate Change Adaptation Education and Teaching Alliance Program” launched in Taiwan in 2014. Through a comprehensive analysis of its institutional structure, curriculum, alliance network, and practical activities, the study explores the effectiveness of educational innovation in cultivating climate resilience talent. The study found that the program, through interdisciplinary collaboration and a practice-oriented teaching model, successfully integrated climate adaptability content into 57 courses, training a total of 2487 students. Project-based learning (PBL) and workshops significantly improved students’ systems thinking and practical abilities, and many of its findings were adopted by local governments. Based on these empirical results, the study proposes that urban and rural planning education should be promoted in the following ways: first, updating teaching materials to reflect regional climate characteristics and local needs; second, enhancing curriculum design by introducing core courses such as climate-resilient planning and promoting interdisciplinary collaboration; third, enriching hands-on learning through real project cases and participatory workshops; and fourth, deepening integration between education and practice by establishing multi-stakeholder partnerships supported by dedicated funding and digital platforms. Through such an innovative educational framework, we can prepare a new generation of professionals capable of supporting global sustainable development in the face of climate change. This study provides a replicable model of practice for education policymakers worldwide, particularly in promoting the integration of climate resilience education in developing countries, which can help accelerate the achievement of UN Sustainable Development Goals (SDG11) and foster interdisciplinary collaboration to address the global climate crisis. Full article

Heracleum sosnowskyi Manden., or H. sosnowskyi, of the Apiaceae was first cultivated in the USSR in 1947 as a potential fodder plant. Due to the development of cold-resistant cultivars and the characteristics of H. sosnowskyi, it quickly became feral. As a result, H. sosnowskyi began to spread as an aggressive invasive species in the 1970s and 1980s. By the 90s it had become an ecological disaster. As well as forming monocultures and displacing native species, H. sosnowskyi contains furanocoumarins, photosensitizing compounds that increase skin sensitivity to ultraviolet rays and cause severe burns. In addition, furanocoumarins have cytotoxic, genotoxic, mutagenic and estrogenic effects. H. sosnowskyi also contains essential oils, which are particularly active during flowering and can irritate the mucous membranes of the eyes and respiratory tract, as well as cause allergic reactions in the form of bronchospasm in people with asthma and hypersensitivity. When released in high concentrations, these biologically active compounds have an allelopathic effect on native plant species, displacing them and reducing biodiversity. As H. sosnowskyi is not native; the biologically active compounds it secretes have a xenobiotic effect, causing serious damage to the ecosystems it occupies. However, in parallel with these negative properties, furanocoumarins have been found to be effective in the treatment of cancer and skin diseases. Furanocoumarins possess antimicrobial antioxidant osteo- and neuroprotective properties. Essential oils containing octyl acetate, carboxylic acid esters, and terpenes can be used in the pharmaceutical industry as antiseptic and anti-inflammatory agents. Additionally, essential oils can be used as biofumigants and natural herbicides. A comprehensive approach allows H. sosnowskyi to be viewed in two ways. On the one hand, it is an aggressive alien species that causes significant damage to ecosystems and poses a threat to human health. On the other hand, it is a potentially valuable natural resource whose biomass can be used within the principles of the circular economy. It is hoped that the use of H. sosnowskyi for economic interests can be a partial compensation for the problem of its aggressive invasion, which is of anthropogenic origin. Full article

In the context of global warming, the continued increase in the frequency of compound events—where drought and high-temperature extremes coincide—has led to severe natural disasters and substantial socio-economic losses. To systematically reveal the evolution of summer dry-heat compound events in Liaoning Province, this study constructs a whole-chain analysis framework of “identification–feature extraction–multivariate probability assessment”. Based on the Standardised Precipitation Index (SPI) and the Standardised Temperature Index (STI), we develop the Standardised Dry-Heat Index (SDHI) to identify dry-heat compound events. Run theory is applied simultaneously to extract key attributes for three types of events—drought, high temperature, and dry-heat compound events—and the Mann–Kendall test is used to detect their temporal mutation characteristics. By combining Copula functions with spatial analysis techniques, we further establish a whole-chain analysis method from “identification–feature extraction–hazard quantification”. The results show that during 1961–2020, summer drought, high-temperature, and dry-heat compound events occurred 4, 14, and 10 times, respectively, in Liaoning Province, with all three types showing a significant increase in frequency after the late 1990s. Spatially, zones of high drought intensity are mainly located in western Liaoning; the duration and severity of high temperatures are most pronounced in inland basin areas; and regions with high compound hazard intensity of dry-heat events largely coincide with urbanised areas. Climate propensity analyses further reveal that the province is experiencing an increasingly dry-heat-prone climate, with high temperatures being the dominant factor driving the enhanced hazard associated with dry-heat compound events. This study overcomes the limitations of traditional single-event analyses and provides a more accurate scientific basis for hazard assessment and zonal prevention and control of dry-heat disasters in Liaoning Province. Full article

Brazil suffered the largest oil spill disaster in its history, beginning on August 2019, affecting the Northeast coast. This study proposes a chemical investigation of oils from the 2019 spill in Brazil, which had naturally undergone different weathering processes in terrestrial and aquatic environments after an extended period of exposure. Three samples were collected at different times and under distinct environmental conditions, coded as spilled oil (SO), oil recovered from the aquatic environment (SA), and oil collected from the terrestrial environment (ST), the latter two having spent more time naturally exposed to aquatic and terrestrial environments. The analyses were performed by gas chromatography–mass spectrometry (GC-MS) and electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS). The results of the GC-MS analysis indicated that, although the samples share a common geochemical origin, the SA and ST samples showed a decrease in the intensity of n-alkane distribution compared to the SO sample, mainly attributed to evaporation and biodegradation processes. FT-ICR MS analysis identified dozens of classes of ESI(+) and ESI(–) compounds, most of them rich in sulfur and oxygen, with the highest intensities and quantities of molecular formulas in the SA and ST samples. Diagnostic ratios for heteroatom classes concluded that the SA and ST samples had undergone a higher level of weathering, mainly associated with photooxidation and biodegradation processes. Thus, the combined use of GC-MS and FT-ICR MS proved to be a robust approach for the detailed characterization of spilled oils, contributing to a clearer understanding of the extent and type of weathering in samples from the 2019 Brazilian spill. Full article

With the increasing volatility and extremity of global climate change, the frequency, intensity, and associated impacts of compound extreme climate events have escalated substantially. To investigate the temporal trends and characteristics of such events, we identified compound extreme climate events in the Huangshui River Basin, located in the northeastern Qinghai–Tibet Plateau, using daily mean temperature and precipitation records from eight meteorological stations. Compound warm–wet, warm–dry, cold–wet, and cold–dry events from 1960 to 2022 were detected based on cumulative distribution functions, and their long-term trends and intensity structures were examined. The results show that: (1) Warm–dry events dominate the basin, with an average annual frequency of 32.84 days per year, occurring frequently across all seasons; cold–dry events rank second (22.38 days per year) and are particularly frequent in winter. (2) Warm–dry events are highly concentrated in the river valley region (e.g., Minhe station), whereas cold–dry and warm–wet events mainly occur in the low-mountain areas (e.g., Huangyuan and Datong). (3) From 1960 to 2022, warm–dry and warm–wet events exhibit a highly significant increasing trend (p < 0.001), cold–dry events show a significant decreasing trend, and cold–wet events display no statistically significant trend. (4) In terms of intensity, all four types of compound events—warm–wet, warm–dry, cold–wet, and cold–dry—are dominated by weak to moderate grades. Overall, the basin is undergoing a compound-risk transition from historically “cold–dry dominated” conditions toward a regime characterized by “warm–dry predominance with emerging warm–wet events.” By identifying compound extreme climate events and analyzing their spatiotemporal variability and intensity characteristics, this study provides scientific support for disaster prevention, daily management, and risk mitigation in climate-sensitive regions. It also offers a useful reference for developing strategies to address compound extreme events induced by climate change and for implementing regional risk-prevention measures. Full article

Climate change has intensified the frequency, scale, and interconnection of disasters, challenging the resilience of urban social–ecological systems. Progress remains fragmented because studies on climate adaptation, disaster risk, and resilience often evolve in isolation. Using an integrated methodological approach that combines bibliometric and knowledge mapping analyses of 2396 climate change, 1228 disaster risk, and 989 climate-related disaster risk publications (1994–2024) from the Web of Science Core Collection, this study explores global trends, collaboration networks, and thematic evolution. Results show that (1) disaster risk research remains centered on emergency management; (2) climate change resilience emphasizes adaptive governance and nature-based transformation; and (3) climate-related disaster studies increasingly address compound hazards and cross-sectoral feedback. Synthesizing these strands, this study develops a Dynamic Resilience Framework integrating multi-level feedbacks, governance coordination, and spatiotemporal coupling across robustness, redundancy, transformability, and learnability. The framework identifies future research priorities in multi-risk governance, urban transformability, and justice-oriented adaptation. Full article

Wildfires in the Wildland–Urban Interface (WUI) pose escalating threats to socio-ecological systems, challenging regional resilience and sustainable recovery. Understanding the compound impacts of such fires requires an integrated, data-driven assessment of both ecological disturbance and social response. This study develops a multi-dimensional framework combining multisource remote sensing data (Landsat/Sentinel-2 NDVI and VIIRS nighttime light) with socio-structural indicators. A Composite Disturbance Index (ImpactIndex) was constructed to quantify ecological, population, and socioeconomic disruption across six fire clusters in the January 2025 Southern California wildfires. Mechanism analysis was conducted using Fixed-Effects OLS (M2) and Geographically Weighted Regression (GWR, M3) models. The ImpactIndex revealed that Eaton and Palisades experienced the most severe compound disturbances, while Border 2 showed purely ecological impacts. During-disaster CNLI signals were statistically decoupled from ecological disturbance (ΔNDVI) and dominated by site-specific effects (p < 0.001). GWR results (Adj. R² = 0.354) confirmed asymmetric spatial heterogeneity: high-density clusters (Palisades, Kenneth) exhibited a significant “Structural Burden” effect, whereas low-density areas showed weak, nonsignificant recovery trends. This “Index-to-Mechanism” framework redefines the interpretation of nighttime light in disaster contexts and provides a robust, spatially explicit tool for targeted WUI resilience planning and post-fire recovery management. Full article