The frequent occurrence of earthquakes worldwide has rendered highway slope protection projects highly vulnerable to damage from seismic events and their secondary disasters. This severely hampers the smooth implementation of post-disaster rescue and recovery efforts. To address this challenge, this study proposes a comprehensive method for assessing seismic losses in slope protection projects, incorporating factors such as topography and elevation to enhance its universality. The method categorizes seismic losses into two main components: damage to protection structures and costs associated with landslide and rockfall clearance and transportation. This study estimates the cost range for common protection structures and clearance methods under general conditions based on widely recognized quota data in China. It establishes criteria for classifying the damage states of protection structures and provides loss ratio values based on real-world seismic examples and expert experience, constructing a model for assessing damage losses. Additionally, by summarizing the geometric characteristics of soil and rock accumulations on road surfaces, a method for estimating landslide volumes is proposed, considering the dynamic impact of slope gradients on clearance and transportation volumes, and a corresponding cost assessment model for clearance and transportation is developed. The feasibility and reliability of the proposed method are verified through two case studies. The results demonstrate that the method is easy to implement and provides a scientific basis for improving relevant standards and practices. It also offers an efficient and scientific tool for loss assessment to industry practitioners.

Seismic risk assessment of code-noncompliant reinforced concrete (RC) frames faces significant challenges due to structural heterogeneity and the complex interplay of site-specific hazard conditions. This study aims to introduce a novel framework that integrates three key concepts specifically targeting these challenges. Central to the methodology are fragility fuses, which employ a triplet of curves-lower bound, median, and upper bound-to rigorously quantify within-class variability in seismic performance, offering a more nuanced representation of code-noncompliant building behavior compared to conventional single-curve approaches. Complementing this, spectrum-consistent transformations dynamically adjust fragility curves to account for regional spectral shapes and soil categories, ensuring site-specific accuracy by reconciling hazard intensity with local geotechnical conditions. Further enhancing precision, the framework adopts a nonlinear hazard model that captures the curvature of hazard curves in log-log space, overcoming the oversimplifications of linear approximations and significantly improving risk estimates for rare, high-intensity events. Applied to four RC frame typologies (2-5 stories) with diverse geometries and material properties, the framework demonstrates a 15-40 % reduction in risk estimation errors through nonlinear hazard modeling, while spectrum-consistent adjustments show up to 30 % variability in exceedance probabilities across soil classes. Fragility fuses further highlight the impact of structural heterogeneity, with older, non-ductile frames exhibiting 25 % wider confidence intervals in performance. Finally, risk maps are presented for the four frame typologies, making use of non-linear hazard curves and spectrumconsistent fragility fuses accounting for both local effects and within-typology variability.

Chromium is a heavy metal used in tanneries, leather industries, electroplating, and metallurgical operations, but improper disposal of waste from these industries leads to environmental contamination. Chromium exists primarily in trivalent and hexavalent forms, with hexavalent chromium (Cr (VI)) being highly toxic. Cr (VI) is carcinogenic, damages fish gills, and negatively impacts crops. Considering these negative impacts of Cr (VI), several physical, chemical, and biological remediation methods have been implemented at contaminated sites, but in most instances, these methods could be uneconomical, highly labor-intensive, and not sustainable. Therefore, a crucial goal is to implement an effective and sustainable remediation technique with consideration of actual site conditions. The aim is to develop a sustainable remediation strategy for a hexavalent chromiumcontaminated site in Ranipet, Tamil Nadu. The comprehensive risk assessment for the site has depicted hazard quotients greater than 1 for both onsite and offsite conditions, indicating the necessity of remediation. To address this, it is suggested to build permeable reactive filters (PRFs) packed with scrap iron filings to reduce Cr (VI) to Cr (III), and succeeding filters with locally produced waste coconut shell biochar to aid in adsorption. The use of waste here aims to eliminate the need to procure any commercially available materials for remediation, completely cutting down the environmental impact of raw material extraction or processing. A continuous chambered set-up packed with contaminated soil and PRFs with biochar and iron filings aided in the decrease of the peak concentration of Cr (VI) by 61 % as compared to a set-up without intervention. Moreover, the outlet concentration after 7 days reduced to 0.08 mg/L, which was 97.6 % less than that in the set-up without intervention.

The frequent occurrence of extreme rainfall events often triggers levee slope failure (LSF), which, due to the levee effect, significantly damages the roads behind the levee. This paper presents a novel framework for the quantitative risk assessment of roads posed by LSF. Within the framework, the innovative integration of Monte Carlo simulation (MCS) and Material point method (MPM) provides a unique solution for simulating the complicated dynamic relationship between LSF and road destruction. MCS generates precise failure scenarios for MPM simulations, overcoming the limitations of traditional approaches in addressing uncertainty in complex scenario systems. With its technical superiority in capturing post-failure deformations, MPM offers critical insights for assessing road exposure and vulnerability. The framework also accounts for indirect losses from road disruptions, which have long been overlooked. The application of the framework to the risk assessment of the road behind the Shijiao Levee in the Pearl River Basin fully demonstrates its practicality and robustness. Compared to traditional risk assessment methods, the proposed framework provides a more refined dynamic evaluation, facilitating the formulation of more effective disaster mitigation strategies.

Intensifying human activities have triggered significant ecological degradation, necessitating innovative approaches to ecosystem restoration. This study introduces a novel integrated methodology combining Ecological Security Patterns (ESP) and Ecological Risk Assessment (ERA) to identify priority ecological restoration areas in the Hefei Metropolitan Area. By synthesizing these complementary approaches, we overcome the limitations of individual methods and establish a comprehensive framework for prioritizing ecological restoration. We construct a complex ecological network comprising 36 source areas spanning 8313.96 km2 and 92 interconnected ecological corridors extending 24,489.17 km. We have identified 73 ecological restoration nodes and 19 key restoration areas covering 544.45 km2, predominantly located at critical ecological junctions. The study categorizes restoration zones into five distinct types: river and lake wetland restoration, mine environment remediation, urban ecological landscape reconstruction, ecological corridor connectivity restoration, and soil and water conservation improvement. Combining ESP with ERA allows for the identification of regions most vulnerable to ecological damage while preserving key ecological functions and networks. Through the identification of urban ecological conflict zones, this study provides a strategic framework for enhancing ecosystem resilience and promoting sustainable urban development. This research is significant because of its potential to address the urgent need for effective ecological restoration strategies in rapidly urbanizing regions, offering a systematic approach to balance ecological preservation with urban development.

Polychlorinated biphenyls (PCBs) are classified as persistent organic pollutants (POPs) due to their potential threat to both ecosystems and human health. The Tibetan Plateau (TP), characterized by its low temperatures, pristine ecological conditions, and remoteness from anthropogenic influences, serves as the investigation region. This study analyzed water samples from the temperature glacial watershed and employed the risk assessment method established by the United States Environmental Protection Agency (US EPA) to assess both carcinogenic and non-carcinogenic risks of PCBs in five age groups. The total concentrations of PCBs (& sum;3PCBs) varied from 738 to 1914 ng/L, with a mean value of 1058 ng/L, which was comparable to or exceeded levels reported in the surface water around the TP. Notably, the riverine sites located near the villages and towns exhibited the highest pollution levels. Our analyses indicated that glacier melting, long-range atmospheric transport (LRAT), reductive dechlorination processes, and various anthropogenic activities might be potential sources of PCB emission in the Meili Snow Mountains. According to the established national and international water quality standards, as well as toxic equivalency concentrations (TEQs) for dioxin-like PCBs (DL PCBs), the PCB concentrations detected in this study could result in serious biological damage and adverse ecological toxicological effects. However, the PCBs in all samples posed a negligible cancer risk to five age groups, and a non-carcinogenic risk to adults. These findings contribute valuable insights into the risks and sources of PCBs and may serve as a foundational reference for subsequent study of these compounds in the Meili Snow Mountains area of the southeastern TP.

Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure. Assessment of hurricane risk furnishes a spatial depiction of the interplay among hazard, vulnerability, exposure, and mitigation capacity, crucial for understanding and managing the risks hurricanes pose to communities. These assessments aid in gauging the efficacy of existing hurricane mitigation strategies and gauging their resilience across diverse climate change scenarios. A systematic review was conducted, encompassing 94 articles, to scrutinize the structure, data inputs, assumptions, methodologies, perils modelled, and key predictors of hurricane risk. This review identified key research gaps essential for enhancing future risk assessments. The complex interaction between hurricane perils may be disastrous and underestimated in the majority of risk assessments which focus on a single peril, commonly storm surge and flood, resulting in inadequacies in disaster resilience planning. Most risk assessments were based on hurricane frequency rather than hurricane damage, which is more insightful for policymakers. Furthermore, considering secondary indirect impacts stemming from hurricanes, including real estate market and business interruption, could enrich economic impact assessments. Hurricane mitigation measures were the most under-utilised category of predictors leveraged in only 5% of studies. The top six predictive factors for hurricane risk were land use, slope, precipitation, elevation, population density, and soil texture/drainage. Another notable research gap identified was the potential of machine learning techniques in risk assessments, offering advantages over traditional MCDM and numerical models due to their ability to capture complex nonlinear relationships and adaptability to different study regions. Existing machine learning based risk assessments leverage random forest models (42% of studies) followed by neural network models (19% of studies), with further research required to investigate diverse machine learning algorithms such as ensemble models. A further research gap is model validation, in particular assessing transferability to a new study region. Additionally, harnessing simulated data and refining projections related to demographic and built environment dynamics can bolster the sophistication of climate change scenario assessments. By addressing these research gaps, hurricane risk assessments can furnish invaluable insights for national policymakers, facilitating the development of robust hurricane mitigation strategies and the construction of hurricaneresilient communities. To the authors' knowledge, this represents the first literature review specifically dedicated to quantitative hurricane risk assessments, encompassing a comparison of Multi-criteria Decision Making (MCDM), numerical models, and machine learning models. Ultimately, advancements in hurricane risk assessments and modelling stand poised to mitigate potential losses to communities and infrastructure both in the immediate and long-term future. (c) 2025 China University of Geosciences (Beijing) and Peking University. Published by Elsevier B.V. on behalf of China University of Geosciences (Beijing). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

As urbanization and industrialization advance, China faces increasingly severe ecological challenges. The Ecological Protection Redline (EPR) policy is a crucial tool for land use management and ecological protection but requires a comprehensive risk assessment method to address ongoing challenges. This study integrated multiple factors with ecological resilience theory to establish a Hazard-Exposure-Vulnerability-Damage-Final Risk framework, assessing the spatiotemporal dynamics and risks of different EPR types in Qinghai Province over 20 years. Path analysis was further used to reveal relationships between risk stages. Results show increasing hazards and exposure in Water Conservation (WC), Biodiversity Maintenance (BM) and Land Desertification (LD) EPR types, with improved water conservation, stable biodiversity, and controlled desertification vulnerability across regions. Integrated risk results show a downward risk trend in WC type, BM type fluctuated but improved, and an initial increase followed by risk decrease in LD type. Path analysis revealed that damage in WC-type EPR was driven by direct hazard impacts, BM-type EPR by vulnerability, and damage in LD-type EPR by indirect effects of hazard through exposure. This study emphasizes the optimization of EPR policies by reducing external disturbances and enhancing ecosystem resilience, providing policy recommendations and practical experience for ecological protection and sustainable land use management.

Rare earth elements (REEs) are increasingly recognized as significant environmental pollutants due to their environmental persistence, bioaccumulation, and chronic toxicity. This study assessed REEs pollution in soil, water, and vegetables in an ion-adsorption rare earth mining area in Ganzhou, and evaluated the associated health risks to the local population. Results indicated that the REEs content in soil ranged from 168.58 to 1915.68 mg/kg, with an average of 546.71 mg/kg, substantially surpassing the background level for Jiangxi Province (243.4 mg/kg) and the national average (197.3 mg/kg). Vegetables displayed an average REEs content of 23.17 mg/kg in fresh weight, far exceeding the hygiene standard of 0.7 mg/kg. Water samples contained REEs at a concentration of 4.09 mu g/L. The estimated daily intake (EDI) of REEs from vegetables exceeded the threshold for subclinical damage, posing potential health risks, particularly for children and adolescents. Further analysis of the adjusted average daily intake (ADI) and non-carcinogenic risk suggested that while most vegetable consumption remains within safe threshold, the intake of REEs from high-risk vegetables such as pakchoi should be limited. Overall, carcinogenic risks associated with lifetime cancer risk (LCR) model for REEs exposure through vegetables and water were found to be low in this area.

The black cutworm Agrotis ipsilon (Hufnagel) (Lepidoptera: Noctuidae) can damage the cotton seedlings and induce destructive yield loss. Seed coating with systemic insecticides is a cost-effective alternative to control A. ipsilon during the early stage of cotton, but the control efficacy and exposure risk to honeybees remain unclear. This study evaluated the control effects of the anthranilic diamide insecticide chlorantraniliprole on A. ipsilon in cotton crops and the corresponding exposure risks to honeybees. Field studies revealed the control efficacy of chlorantraniliprole at 2 or 4 g/kg seed was greater than 75%, which was comparable to its spray control during the seedling development stage. A residual toxicity trial revealed that chlorantraniliprole treatment had a dose-response control effect on A. ipsilon during the 19 days after sowing. The residue levels of chlorantraniliprole in the stem bases and soil were found consistent with the residual toxicity against A. ipsilon. In the cotton flowering period, the highest detection frequency and residue of chlorantraniliprole were found in pollen from the plots treated with 4 g/kg seed. By using 2 independent risk assessment approaches, the exposure risk of chlorantraniliprole seed treatments were evaluated to be acceptable to honeybees. Overall, chlorantraniliprole coated with 2 g/kg seed was an effective alternative for controlling A. ipsilon at the cotton seedling stages.