Comprehensive Risk Evaluation Research Articles

Can large language models be sensitive to culture suicide risk assessment?

AbstractSuicide remains a pressing global public health issue. Previous studies have shown the promise of Generative Intelligent (GenAI) Large Language Models (LLMs) in assessing suicide risk in relation to professionals. But the considerations and risk factors that the models use to assess the risk remain as a black box. This study investigates if ChatGPT-3.5 and ChatGPT-4 integrate cultural factors in assessing suicide risks (probability of suicidal ideation, potential for suicide attempt, likelihood of severe suicide attempt, and risk of mortality from a suicidal act) by vignette methodology. The vignettes examined were of individuals from Greece and South Korea, representing countries with low and high suicide rates, respectively. The contribution of this research is to examine risk assessment from an international perspective, as large language models are expected to provide culturally-tailored responses. However, there is a concern regarding cultural biases and racism, making this study crucial. In the evaluation conducted via ChatGPT-4, only the risks associated with a severe suicide attempt and potential mortality from a suicidal act were rated higher for the South Korean characters than for their Greek counterparts. Furthermore, only within the ChatGPT-4 framework was male gender identified as a significant risk factor, leading to a heightened risk evaluation across all variables. ChatGPT models exhibit significant sensitivity to cultural nuances. ChatGPT-4, in particular, offers increased sensitivity and reduced bias, highlighting the importance of gender differences in suicide risk assessment. The findings suggest that, while ChatGPT-4 demonstrates an improved ability to account for cultural and gender-related factors in suicide risk assessment, there remain areas for enhancement, particularly in ensuring comprehensive and unbiased risk evaluations across diverse populations. These results underscore the potential of GenAI models to aid culturally sensitive mental health assessments, yet they also emphasize the need for ongoing refinement to mitigate inherent biases and enhance their clinical utility.

Challenges and Future Directions in Evaporative Cooling: Balancing Sustainable Cooling with Microbial Safety

Evaporative cooling systems are gaining popularity due to their environmental benefits, particularly in reducing energy consumption and utilizing air (R-729) and water (R-718) as refrigerants. However, these systems are susceptible to microbial contamination, posing significant health risks, especially in environments where air is in direct contact with water. The article provides an in-depth analysis of the microbial risks associated with evaporative cooling systems, focusing on bacteria such as Legionella pneumophila, fungi, and other pathogens that can proliferate in the moist environments these systems create. While Legionella contamination is well-documented and frequently addressed, this study highlights the need for more comprehensive evaluation of other microbial risks. The research compares the microbial safety of evaporative cooling systems with that of traditional vapor compression cooling and examines the role of cooling pad materials and water quality in promoting microbial growth. It also underscores the limitations of current maintenance practices, which often overlook non-Legionella risks. To improve microbial safety, the paper proposes several mitigation strategies, including UV water treatment and heat exchanger surface modifications, to reduce microbial contamination. Additionally, the study calls for more detailed and consistent maintenance guidelines that cover a broader spectrum of microbial threats beyond Legionella, as well as regular monitoring of indoor air quality to ensure the safe operation of these systems in human-occupied spaces.Ultimately, the findings emphasize that, with improved microbial safety protocols and regular maintenance, evaporative cooling systems can become a sustainable and safe alternative to conventional cooling technologies in various environments.

Microplastic pollution in Taihu Lake: Spatial distribution from the lake inlet to the lake centre and vertical stratification in the water column

The aim of this study was to analyse the distribution characteristics of microplastics in lakes, assess their potential impacts on ecosystems, and explore effective management and control strategies. Despite a wealth of research focused on lake water, the variations in microplastics with offshore distance and their vertical distribution within the water column are not well understood. Here, we investigated the freshwater continuum from the inlet of Taihu Lake to the centre, and vertically from the surface to the bottom water. The results revealed that the distribution of microplastics (<5 mm in size) exhibited a clear spatial gradient. The microplastic abundance at the lake entrance was 2.12 times greater than that at the centre, and on the lake surface, the microplastic abundance was 1.36–1.69 times higher than that estimated from the water column. Notably, the proportion of small-sized microplastics (<0.1 mm) in the bottom water was 1.72 times higher than that in the surface water. The main types of polymers identified were polyamide (PA) and polyvinyl chloride (PVC), and their main sources may be from clothes washing and industrial activities. The Monte Carlo simulation results indicated that the overall risk of microplastics in surface water was higher than that in the water column, and the contributions of PVC and polyurethane (PU) to the ecological risk were 90.10% and 9.57%, respectively. Therefore, PVC and PU should be the priority of microplastic pollution control. This study provides the first comprehensive evaluation of the spatial ecological risk of microplastics in Taihu Lake, which improves our understanding of the distribution and environmental risks of microplastics in lake systems.

Comprehensive evaluation of rockburst risk by multiparameter characteristics based on microseismic signals: A case study

AbstractNowadays, the seismological monitoring system in China is a valuable tool in the rockburst risk evaluation for deep coal mines. In the past, only parameters, like source location and energy, are widely used to estimate the risk level of rockburst. Sometimes, it is effective; however, some other important physical parameters, such as apparent stress drop, static stress drop, P‐wave velocity, and moment tensor, should also be included in order to improve the accuracy of risk assessment. In this study, these parameters are calculated using mine tremor signals recorded in the LW35001 workface of Liangbaosi Coal Mine. These calculations provide an overall identification of periodical stress distribution and rock mass energy‐releasing type under high concentrated stress. Via linear moment tensor inversion procedure, the source mechanism of mine tremors and stress state of the rock mass is determined whether it is risk or not to underground roadway. This comprehensive analysis provides a specific guidance for rockburst prevention for coal mine management, that is, knowing when and where measures must be taken to decrease the risk level or induce the occurrence of rockburst under control.

Ontology-Based Landslide Knowledge Representation and Hazard Assessment Research

The occurrence of landslides is characterized by suddenness and unpredictability, with many complex relationships among various influencing factors. This study, by introducing the ontology of knowledge engineering, summarizes the characteristics of landslide knowledge and constructs a multidisciplinary, multi-level, and multi-perspective ontology of the landslide domain. Through in-depth analysis of existing landslide research systems and methods, the study defines the basic concepts, attributes, and their complex relationships and rules related to landslides. This research expresses landslide knowledge using the Web Ontology Language (OWL), enabling effective storage and retrieval of landslide knowledge, thus promoting the systematization and standardization of knowledge in the landslide domain. Furthermore, leveraging the high knowledge density feature of the constructed landslide domain ontology, this study extends traditional landslide evaluation and prediction methods by introducing more evaluation indicators based on the constructed landslide ontology. The comprehensive evaluation of landslide risk is conducted using the contribution-weighting method, providing new insights and tools for landslide risk management and decision-making.

Managing Induced Seismicity Risks From Enhanced Geothermal Systems: A Good Practice Guideline

AbstractGeothermal energy is a green source of power that could play an important role in climate‐conscious energy portfolios; enhanced geothermal systems (EGS) have the potential to scale up exploitation of thermal resources. During hydraulic fracturing, fluids injected under high‐pressure cause the rock mass to fail, stimulating fractures that improve fluid connectivity. However, this increase of pore fluid pressure can also reactivate pre‐existing fault systems, potentially inducing earthquakes of significant size. Induced earthquakes are a significant concern for EGS operations. In some cases, ground shaking nuisance, building damages, or injuries have spurred the early termination of projects (e.g., Basel, Pohang). On the other hand, EGS operations at Soultz‐sous‐Forêts (France), Helsinki (Finland), Blue Mountain (Nevada, USA), and Utah FORGE (USA) have adequately managed induced earthquake risks. The success of an EGS operation depends on economical reservoir enhancements, while maintaining acceptable seismic risk levels. This requires state‐of‐the‐art seismic risk management. This article reviews domains of seismology, earthquake engineering, risk management, and communication. We then synthesize “good practice” recommendations for evaluating, mitigating, and communicating the risk of induced seismicity. We advocate for a modular approach. Recommendations are provided for key technical aspects including (a) a seismic risk management framework, (b) seismic risk pre‐screening, (c) comprehensive seismic hazard and risk evaluation, (d) traffic light protocol designs, (e) seismic monitoring implementation, and (f) step‐by‐step communication plans. Our recommendations adhere to regulatory best practices, to ensure their general applicability. Our guidelines provide a template for effective earthquake risk management and future research directions.

Molecular docking analysis and in vivo assessment of zinc oxide nanoparticle toxicity in zebrafish larvae

The zinc oxide nanoparticles (ZnO-NPs) being widely employed in several industries and consumer products, are raising concerns about their safety on aquatic biota and human health. This study aims to investigate the possible toxicological effects of ZnO-NPs through a combined in vivo and in silico approach. Zebrafish embryos were exposed to several ZnO-NPs concentrations and morphological alterations and lipid peroxidation (MDA) were investigated. Furthermore, molecular docking simulations were applied to study the intermolecular interactions of ZnO-NPs against critical embryonic proteins namely zebrafish hatching enzyme1 (ZHE1) as well as the superoxide dismutase (SOD1). Treatment with ZnO-NPs resulted in an increase in MDA concentration and a decrease in antioxidant enzyme levels. Besides a significant decrease in mRNA expression of key enzymes of ROS detoxification genes, a modulation of inflammatory genes with a low downregulation of tnf-α, and an upregulation of il-1β were observed. Docking study suggests that the delayed hatching and increased cellular oxidative stress in zebrafish embryos may occur through a synergistic mechanism based on the ZnO-NP—dependent inhibition of ZHE1 and SOD1 enzymes. The integration of in vivo assessments with in silico computational modeling provided a more comprehensive evaluation of potential physiological risks in zebrafish embryos associated with nanomaterial exposure.

Research on the group effect of new energy vehicles from different policy perspectives

Abstract Policies play a pivotal role in fostering the growth of new energy vehicles. This paper delves into the benefits and risks associated with the development of new energy vehicles under varying policy landscapes. Firstly, the intricate relationship between the competition and growth of new energy vehicles and internal combustion engine vehicles is captured through the application of the extended Lotka-Volterra model. Secondly, a simulation flow diagram is constructed, taking into account the actual mediums of policy impact and drawing insights from diverse research methodologies. This flow diagram enables a comprehensive evaluation of environmental benefits, health risks, and traffic pressure. Finally, a critical evaluation of the actual impact of policies on new energy vehicles is conducted, along with an exploration of the root causes of potential policy paradoxes. The findings reveal that a standalone infrastructure support policy, research and development support policy, or carbon tax policy can, in certain periods, lead to an increase in carbon emissions and traffic pressure. Although the driving restriction policy does not exert negative impacts on the environment, health, and traffic at the national level, it can result in a surge in the total vehicle population. Therefore, it is imperative to adopt a combination of policies to mitigate the potential risks associated with any single policy.

A comprehensive analysis and risk evaluation of microplastics contamination in Australian commercial plant growth substrates: Unveiling the invisible threat

In Australia, quality standards for composts and potting mixes are defined by AS4454-2012 and AS3743-2012. These standards outline key parameters, including physicochemical properties, nutrient content, and plant toxicity. However, they do not address emerging pollutants like microplastics (< 1mm). This study investigates the prevalence and characteristics of MPs in commercial plant growth substrates (PGS), including nineteen potting mixes and five composts, revealing a significant occurrence of MPs, with concentrations ranging from 233 to 7367 particles Kg-1 and an average of 1869 ± 109 particles Kg-1. MPs categorized by shape, size, and color, with fragments (491 ± 34 particles Kg-1), white colour (3700 ± 917 particles Kg-1), and size 500µm being predominant. The polymer composition was diverse, with polyethylene being the most prevalent, followed by polypropylene and others. Polyterpene, Polyalkene, Pentaerythritol, and Propylene glycol were identified in PGS for the first time. The structural equation model showed that physicochemical properties like pH, EC, TOC, and heavy metals influence MPs abundance and characteristics. The Polymer Risk Index and Pollution Load Index indicated varying risk levels among the samples. These findings highlight the need to address MPs contamination in PGS to ensure ecosystem safety and human health. Environmental ImplicationsThe study reveals significant microplastic contamination in Australian commercial PGS, with compost exhibiting higher levels than potting mixes. Application of these contaminated substrates can lead to microplastic release, which can further alter soil properties, disrupt microbial communities, and leach environmental toxins. Current regulations primarily target larger plastic items, neglecting the issue of microplastics (<1mm). The findings underscore the necessity for updated standards and quality controls for commercial PGS. Enhancing public awareness and improving waste sorting are crucial steps to mitigate contamination. Effective source separation is essential for producing high-quality compost and potting mixes. Collaborative efforts among policymakers, industries, and communities are vital for advancing waste management practices and environmental protection.

Development of intestinal colonic drug delivery systems for diverticular disease: A QbD approach

This study aimed to advance the development of intestinal colon-coated sustained-release matrix tablets of metronidazole for diverticulitis treatment, employing the Quality by Design (QbD) methodology. Comprehensive Risk analysis and Risk evaluation were conducted to assess the potential risks associated with Critical Material Attributes (CMA) and Critical Process Parameters (CPP). Ishikawa diagram, color-coded risk classification and the Risk Priority Number (RPN) were used as tools for risk evaluation. A Design of Experiments (DoE) was executed using a fractional factorial design, incorporating five key factors derived from the Risk analysis and Risk evaluation. Two levels and a central point were established for each factor, resulting in 28 batches of coated tablets. The manufacturing process involved direct compression, followed by a coating process using pH-dependent or time-dependent polymers. Characterization and dissolution studies were conducted on all batches, and the obtained results underwent analysis of variance (ANOVA).The findings demonstrated the robustness and reproducibility of both the direct compression and coating processes. Statistical analysis identified HPMC/chitosan ratio, blending time, coating polymer, and coating weight gain as factors significantly impacting drug release. A Design Space was established to delineate the interplay of these factors, offering insights into various combinations influencing drug release behavior. Thus, the design space for 10 % weight gain formulations includes a range of HPMC/CH ratios between 2.7–3 and mixing times between 10 and 12 min; for 20 % weight gain formulations it includes a range of HPMC/CH ratios up to 2 and mixing times between 10 and 16 min. Multiple Linear Regression between technological and biopharmaceutical variables were optimized facilitating scale-up operations. Batches with a 10 % weight increase and varied HPMC viscosity grades and coating polymers achieve ∼50 % drug release at 24 h; however, batches with a 20 % weight increase along, with either high proportions of HPMC and short blending times or low proportions of HPMC and longer blending times, achieve slow release of metronidazole. This study contributes to optimizing metronidazole colonic delivery systems, enhancing their potential efficacy in diverticulitis treatment.

Effect of per- and polyfluoroalkyl substances on neurodevelopment: Evidence-based risk assessment in the TRAEC strategy context

Although emerging evidence on the association between per- and polyfluoroalkyl substances (PFASs) and neurodevelopment have been investigated, there is no consensus on the effect of maternal PFASs on neurodevelopment in offspring. Here, we assessed the risk of maternal PFASs exposure on the neurodevelopment of offspring using a novel Targeted Risk Assessment of Environmental Chemicals (TRAEC) strategy based on multiple evidence. The evidence from five online databases were analyzed the effect of PFASs on neurodevelopment. The potential neurodevelopment risk of PFASs was evaluated by the TRAEC strategy, which was conducted on a comprehensive scoring system with reliability, correlation, outcome fitness and integrity. The studies from five databases and additional researchers’ experiments were included the present study to proceed following risk assessment. Based on the framework with TRAEC strategy, the comprehensive evaluation of health risks was classified as low (absolute value 0–4), medium (absolute value 4–8), high (absolute value 8–10). In the present study, the effect of PFASs exposure on neurodevelopment was a medium-risk level with 5.61 overall risk-score. The population-attributable risk (PAR) was 8.26 % for maternal PFASs exposure. The study identified a low-risk effect of prenatal PFASs exposure on ASD and behavioral disabilities. The chain length, type of PFASs and neurodevelopmental trajectories contributed to the risk of maternal PFASs on the neurodevelopment of offspring. Consistent with results of four criteria-based tools (ToxRTool, SciRAP, OHAT and IRIS), health risk assessment based on the TRAEC strategy demonstrated robustness and reliability in the present study. These results illustrated a medium-risk effect of maternal PFASs exposure on neurodevelopmental disorders of offspring. In addition, the TRAEC strategy provided a scientific and structured method for effect evaluation between prenatal PFASs and neurodevelopmental disorders, promoting the consistency and validation in risk assessment.

Introducing a climate, demographics, and infrastructure multi-module workflow for projected flood risk mapping in the greater Pamba River Basin, Kerala, India

Enhanced understanding of extreme events is essential for comprehensive risk assessment promoting informed decision-making and early warning to ensure the resilience against challenges imposed by changing climate. This study proposes a novel multi-module integration framework for the comprehensive evaluation of future flood risk in the Greater Pamba River basin, Kerala, India. The integrative modelling framework is developed by assembling a Cellular Automata-Markov Chain (CAMC) based and Use/Land Cover (LULC) projections, Reliability Ensemble Averaging (REA) of Global Climate Model (GCM) rainfall projections, Bayesian approach-based population projection, and spatial analysis of projected infrastructure and Digital Elevation Models (DEMs). By seamlessly interweaving the associated datasets, we illustrate the intricacies of flood vulnerability, exposure, and frequency across multiple return periods (2, 5, 10, and 100, 200 and 500 year) leading to the creation of diagnostic and prognostic high-resolution flood risk maps. The resultant flood analytics and analyses shown that around 36 % of the villages/municipalities and between 70 and 80 % of the critical facilities like schools, hospitals, and flood relief camps are falling under high-risk zones, for the 100-year return period flood. This finding is in line with Kerala's devastating flood episode in 2018, which exhibited characteristics of a nearly 100-year return period flood. In light of a changing climate, population growth, and shifting landscapes, these approaches provide a roadmap for more informed decision-making and adaptive flood risk management measures.

Dynamic Risk Forecasting Based on Deep Learning and Collapse Risk Comprehensive Evaluation of Mountain Tunnel Portal Construction

Dynamic Risk Forecasting Based on Deep Learning and Collapse Risk Comprehensive Evaluation of Mountain Tunnel Portal Construction

Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir.

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC.

Optimizing child protection systems: A systematic review of the literature on risk assessment practices

Child maltreatment is a global phenomenon that has affected millions of children, with far-reaching consequences for their development. The assessment of risk has emerged as a fundamental and indispensable component within child protection services. Professionals should use safe and effective risk assessment practices, always prioritizing the best interests of the child. This systematic review aims to elucidate the prevailing risk assessment practices employed by professionals within the child protection systems. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Thirteen empirical studies were selected, featuring participants from diverse fields such as social services, health, psychology, and law enforcement. The professionals relied on a multifaceted approach, incorporating clinical judgment, professional expertise, actuarial risk assessment tools, individual interviews with children, adolescents, and family members, as well as the observation of familial dynamics. Moreover, intra- and interinstitutional collaboration played a pivotal role in the comprehensive evaluation of risk. Consequently, the discerned efficient practice appears to be a synergistic effort undertaken by a transdisciplinary team. This collaborative action encompasses the utilization of clinical judgment, augmented by the judicious administration of actuarial risk assessment instruments.

Comprehensive Evaluation of Health, Safety, and Environmental Risks in Railway Construction Project Management

Comprehensive Evaluation of Health, Safety, and Environmental Risks in Railway Construction Project Management

Comprehensive evaluation and optimal management of extreme disaster risk in Chinese urban agglomerations by integrating resilience risk elements and set pair analysis

This study comprehensively assesses the extreme disaster risk faced by Chinese urban agglomerations and optimizes disaster risk management strategies to enhance their disaster resilience and sustainable development. The focus is specifically on droughts, floods, and earthquakes. The integration of resilience risk elements and set pair analysis (SPA) is employed to obtain risk assessment results for different urban agglomerations, including hazard, exposure, vulnerability, and disaster prevention and mitigation capabilities. The study explores the contributions of important indicators, such as exposure, vulnerability, and disaster prevention and mitigation capabilities, in disaster risk assessment, as well as their performance in various risk-prone urban areas. Comparative analysis of the assessment results for different urban agglomerations under various disaster types reveals varying levels of risk in droughts, floods, and earthquakes across different regions. Some areas exhibit higher hazard, exposure, or vulnerability levels, necessitating strengthened disaster prevention and mitigation measures. Regions with high exposure, low vulnerability, and strong disaster prevention and mitigation capabilities may face lower earthquake disaster risk, while regions with low exposure, high vulnerability, and weak disaster prevention and mitigation capabilities may face higher earthquake disaster risk. Moreover, the Comprehensive SPA model and Interval-valued SPA model outperform traditional SPA methods in assessing the existing flood risk level in Chinese urban agglomerations. The integrated model plays a significant role in predicting earthquake disasters, demonstrating the best predictive performance. This study provides essential reference data for urban disaster prevention and mitigation efforts, aiming to enhance urban resilience and disaster resilience capabilities.

Using tele-paramedicine to conduct in-home fall risk reduction after emergency department discharge: Preliminary data.

Older adults discharged from our emergency department (ED) do not receive comprehensive fall risk evaluations. We conducted a quality improvement project using an existing Community Tele-Paramedicine (CTP) program to perform in-home fall risk assessment and mitigation after ED discharge. High falls-risk patients, as defined by STEADI score >4, were referred for a CTP home visit by community paramedics supervised virtually by emergency physicians. Home hazards assessment, Timed Up and Go test (TUG), medication reconciliation, and psychosocial evaluation were used to develop fall risk mitigation plans. Outcomes assessed at 30 days post ED-discharge included: completed CTP visits, falls, ED revisits, hospital admissions, and referrals. Between November 2022 and June 2023, 104 (65%) patients were discharged and referred to CTP. The mean age of enrolled patients was 80 years, 66% were female, 63% White, 79% on Medicare or Medicaid, most lived with a family member (50%) or alone (38%). Sixty-one (59%) patients received an initial CTP visit, 48 (79%) a follow-up visit, and 12 (11%) declined a visit. Abnormal TUG tests (74%), home hazards (67%), high-risk medications (36%), or need for outpatient follow-up (49%) or additional home services (41%) were frequently identified. At 30 days, only one of the CTP patients reported a fall, one patient had a fall-related ED visit, and one patient was admitted secondary to a fall. A quality improvement initiative using CTP to perform fall risk reduction after ED discharge identified areas of risk mitigation in the home where most falls take place. Further controlled studies are needed to assess the impact of CTP on clinical outcomes important to patients and health systems.

Distribution and Comprehensive Risk Evaluation of Cr, Cd, Fe, Zn, and Pb from Al Lith Coastal Seawater, Saudi Arabia

Seawater contamination is a global challenge due to its hazardous effects on marine organisms and human health. Twenty-three surface seawater samples were collected from the Al Lith intertidal area along the Saudi Red Sea coast to evaluate the ecological risks and document the potential sources of Cr, Cd, Fe, Zn, and Pb. Contamination factor (CF), contamination degree (Cd), water quality index (WQI), and heavy metal pollution index (HPI), as well as multivariate tools were applied. The average concentrations of HMs (μg/L) had the following order: Zn (6.616) &gt; Pb (0.284) &gt; Cd and Cr (0.268) &gt; Fe (0.197). CF results showed moderate contamination of seawater with Cd and low contamination of Cr, Fe, Zn, and Pb. However, 26.09% of the samples showed considerable contamination with Cd. Average Cd values revealed low contamination with HMs, while 17.39% of the samples showed moderate contamination. HPI average values indicated medium pollution of Al Lith seawater, while 13 samples reported high pollution. The higher HPI values were reported in samples characterized by higher concentrations of HMs, particularly Cd and Zn. Correlation matrix and principal component analysis suggested anthropogenic sources for Pb and Zn, mostly from industrial and agricultural effluents, landfilling, and domestic wastewater, apart from their natural sources.

Comprehensive risk evaluation in Rapti Valley, Nepal: A multi-hazard approach

While research on natural hazards in Nepal has primarily focused on the consequences of individual hazards within an area, it is also essential to analyze the probable occurrence of several types of natural hazards and their interaction, i.e., Multi-hazard assessment. In light of this, the study conducted a Multi-Hazard Risk Assessment of the proposed capital city of Lumbini province, which covers 14 wards from three municipalities. The four prevalent hazards in the area, i.e., flood, landslide, debris flow, and forest fire, have been considered in the study, which includes generating individual susceptibility maps using different geospatial and modeling techniques. The vulnerability and risk assessment was done on a ward level and considered physical, social, economic, and environmental vulnerability indicators. The results on the multi-hazard susceptibility map show that 29.36% of the area was at low susceptibility, while the medium and high zones comprised 46.16% and 24.46% of the total area, respectively. Wards 2, 3, and 7 of Rapti are highly vulnerable, while Ward 8 of Sitganga and Ward 9 of Rapti are the least vulnerable. Moreover, wards 1, 2, and 3 are at high risk to the vulnerability parameters, while ward 8 of Sitganga is at the least risk. The high-risk areas are on the foothills of the Siwalik range, which are prone to landslide, debris flow, and forest fire hazards, as well as are on the bank of West Rapti River, which marks them as potential flood hazard zones. The capital city of Lumbini province is fast developing. Therefore, the results derived from this study assist in identifying potential risk zones to consider while creating a master plan for the area.