Value At Risk Research Articles

Hip fracture in elderly: malnutrition and health outcomes. A systematic review and meta-analysis

Abstract Background Hip fracture is a common condition among elderly and one of the leading causes of disability. Malnutrition is widely present in older patients and has been identified in several studies as an important and modifiable prognostic factor for several medical conditions, including hip fracture. The aim of the present study is to evaluate the association between malnutrition, assessed by validated tools, and selected health outcomes for different follow-up intervals from hip fracture, in particular: mortality, changes in mobility/living arrangements and postoperative delirium. Methods A literature search on PubMed, Web of Science and Scopus databases up to September 2023, was conducted to identify all studies involving older subjects that reported an association between MNA/GNRI/PNI/CONUT score and health outcome after hip fracture. Meta-analysis was performed by a random-effects model using risk values (RR/OR/HR) extracted from 14 eligible selected studies. Results Malnutrition significantly increased the risk of any adverse outcome by 70% at 1 month, and up to 250% at 1 year, showing an increasing trend with longer follow-up periods. One month after hip fracture, malnutrition significantly increased the risk of postoperative delirium by 275% (OR = 2.75; 95% CI 1.80-4.18; p ≤ 0.05), mortality by 342% (OR = 3.42; 95% CI 2.14-5.48; p ≤ 0.05) and mortality hazard risk by 351% (HR = 3.51; 95% CI 1.63-7.55; p ≤ 0.05). One year after hip fracture, malnutrition significantly increased the risk of transfer to more supported living arrangements by 218% (OR = 2.18; 95% CI 1.58-3.01; p ≤ 0.05), declined mobility by 41% (OR = 1.41; 95% CI 1.14-1.75; p ≤ 0.05), mortality by 368% (OR = 3.68; 95% CI 3.00-4.52; p ≤ 0.05) and mortality hazard risk by 234% (HR = 2.34; 95% CI 1.91-2.87; p ≤ 0.05). Conclusions These findings underscore that malnutrition worsens outcomes after hip fracture in elderly, emphasizing the importance of nutritional assessment to mitigate potential adverse consequences. Key messages • The results of the present study underscore that malnutrition increases the risk of death and worsens mobility and independence after hip fracture in older adults. • Routine nutritional status evaluation could prove beneficial in the management of hip fracture older patients in order to prevent potential adverse outcomes.

Prognostic role of gene variants in sudden cardiac death risk associated to paediatric hypertrophic cardiomyopathy

Abstract Introduction Genetic testing plays an important role in diagnosis of hypertrophic cardiomyopathy (HCM), being sarcomeric genes commonly involved, particularly MYBPC3. However, arrhythmic risk related to genotype remains unclear in adults and almost unexplored in children. Hence, current sudden cardiac death (SCD) risk calculators do not include genetic information. Purpose To analyse risk of arrhythmic events associated with causal variants in MYBPC3 respecting to other genes in a paediatric cohort with non-syndromic HCM from a cardiomyopathy referral centre. Methods This retrospective study included patients with non-syndromic HCM 0-18 years old between 2009-2022. Demographic, clinical, and genetic data were collected. Genetic variants pathogenicity followed American College of Medical Genetics criteria. A positive genetic test was considered if a likely pathogenic or pathogenic variant in HCM related genes was found. Considered outcomes were SCD or a major arrhythmic cardiac event (MACE) within 5 years follow-up: recovered SCD, appropriate ICD therapy, or sustained ventricular tachycardia. Some SCD-risk estimation models (in 5 years) as HCM Risk-SCD model for patients >=15 y.o and/or 55 kg, ESC Guidelines paediatric algorithm, and HCM Risk-Kids model were applied. Results 77 patients were diagnosed with non-syndromic HCM. A causal variant was found in 45/73 (62%). No significant differences in cardiac phenotype were found related to genes. 10/77 patients (13%) presented a MACE in 5 years follow-up. A positive genetic study was significantly associated with having an event (p=0.011). Most patients with a positive genetic test harboured MYBPC3 variants (21/45, 47%), however only 2 patients who suffered a MACE had a causal variant in MYBPC3. Those with causal variants in genes other than MYBPC3 presented more and earlier events (p=0.022). Risk of having a MACE during follow-up was higher when presenting causal variants in genes other than MYBPC3: Hazard Ratio 18.5 (95% CI 2.31, 148), p=0.006. Applying HCM Risk-SCD calculator, model had better predictive discrimination when variable "causal variant in gene other than MYBPC3" was added in multivariate analysis, with high-risk category >=6% (C-statistic =0.931 vs 0.844) and intermediate-risk category 4-6% (C-statistic =0.845 vs 0.514). Same occurred with ESC Guidelines algorithm, adding that variable to 2 risk factors category (C-statistic =0.881 vs 0.742) or 1 risk factor (C-statistic =0.844 vs 0.635). HCM Risk-Kids also improved its predictive discrimination adding the genetic value to high-risk category >=6% (C-statistic =0.896 vs 0.796) and intermediate-risk (C-statistic =0.821 vs 0.506). Conclusions Genotype may have prognostic value in SCD risk in HCM in children. Our results suggests that causal genetic variants in genes other than MYBPC3 can lead to higher risk of SCD. Genetic information might be considered for future models of arrhythmic risk in children with HCM.

Accelerated hazard prediction based on age time-scale for women diagnosed with breast cancer using a deep learning method

Breast cancer is the most common cancer in women. Previous studies have investigated estimating and predicting the proportional hazard rates and survival in breast cancer. This study deals with predicting accelerated hazards (AH) rate based on age categories in breast cancer patients using deep learning methods. The AH has a time-dependent structure whose rate changes according to time and variable effects. We have collected data related to 1225 female patients with breast cancer at the Mandarin University of Medical Sciences. The patients' demographic and clinical characteristics including family history, age, history of tobacco use, hysterectomy, first menstruation age, gravida, number of breastfeeding, disease grade, marital status, and survival status have been recorded. Initially, we dealt with predicting three age groups of patients: ≤ 40, 41–60, and ≥ 61 years. Then, the prediction of accelerated risk value based on age categories for each breast cancer patient through deep learning and the importance of variables using LightGBM is discussed. Improving clinical management and treatment of breast cancer requires advanced methods such as time-dependent AH calculation. When the behavioral effect is assumed as a time scale change between hazard functions, the AH model is more appropriate for randomized clinical trials. The study results demonstrate the proper performance of the proposed model for predicting AH by age categories based on breast cancer patients' demographic and clinical characteristics.

Association of TRI-SCORE with clinical outcomes after percutaneous tricuspid annuloplasty

Abstract Background Significant tricuspid regurgitation (TR) has been associated with excess mortality and heart failure. Functional TR is associated to progressive right ventricular remodeling and dysfunction, leading to comorbidities which elevate the perioperative mortality of isolated tricuspid regurgitation surgery, with an in-hospital mortality between 6-10% according to series. Transcatheter tricuspid annuloplasty is a promising therapeutic alternative in patients with high surgical risk. Appropriate risk stratification and patient selection is essential to ensure benefits of this intervention. European System for Cardiac Operative Risk Evaluation (EUROSCORE) II and the Society of Thoracic Surgeons (STS) score are widely spread in-hospital mortality risk scores in valvular surgery. TRI-SCORE is focused on isolated TR surgery; nevertheless, application of these scores to transcatheter annuloplasty has not been specifically studied yet. Purpose To analyze the utility of surgical scores (EUROSCORE-II, STS and TRISCORE) to predict all-cause mortality in patients undergoing transcatheter tricuspid annuloplasty. Methods A cohort of 49 patients with significant TR was followed up prospectively after the transcatheter tricuspid annuloplasty with Cardioband between 2019 and January 2024 (mean follow-up 18,43 ± 10,95 months). Every score was evaluated in all patients. According to the TRI-SCORE –– 6 points was the 75-percentile and taken as cutoff value –– we divided the cohort in two groups: a low score group (≤6 points) and a high score group (>6 points). Survival was analyzed in the whole cohort and in both subgroups. The curves are depicted using Kaplan-Meier method and were compared using log rank test. Results The study included 49 patients, with mean age of 77,6 ± 7,67 years, 77,6% being women. All the patients had a secondary etiology of TR and 46,9% massive or torrential TR before the intervention. 49% had previous left heart surgery. The median surgical risk values are represented in Table 1. All-cause mortality during follow-up occurred in 9 patients (18,3%). Survival analysis based on EUROSCORE II and STS did not find statically significant association (Table 1). TRI-SCORE had a hazard ratio (HR) of 1,59, also without statically significant association (CI 0.93 – 2.71; p 0.089). Survival analysis in high score group found an increased risk of all-cause mortality (HR 8.5; p 0.025). According to our findings TRI-SCORE > 6 before the procedure confers significant risk of all-cause death (log rank p = 0.009). Figure 1. Conclusions Transcatheter tricuspid annuloplasty is a promising therapy for patients with significant TR regurgitation who are at high surgical risk. According to our findings, TRI-SCORE is an appropriate scoring model to predict all-cause mortality after percutaneous annuloplasty with band. It is not so for other surgical risk scores. Extended follow-up and broader experienced are needed to corroborate these results.Surgical scores: median and mortalitySurvival curves TRI-SCORE

Elemental composition and health risk assessment of PM10, PM2.5, at different microenvironments: Addis Ababa, Ethiopia.

This study was designed to evaluate the health risks faced by inhabitants living in the slum areas of Addis Ababa, Ethiopia. The levels of PM2.5 and PM10 and elemental composition of the PM10 were measured in indoors (in the kitchen and living room) and outdoors (at the roadside). A total of 75 sampling locations (45 indoor and 30 outdoor) were selected for the study. The levels of PM2.5 and PM10 were determined using an AROCET531S instrument, while an universal air pump was used for the sampling of PM10 for the determination of trace elements by inductively coupled plasma-optical emission spectroscopy (ICP‒OES). The health impacts of PMs on the inhabitants of twelve microenvironments (MEs), where they spend much of their daily time, were estimated. The total amounts of PM2.5 and PM10, and trace metals in PM10 found in the nine or twelve MEs ranged from 10.6-119, 128-185, and 0.007-0.197 μg m-3, respectively. According to the United States Environment Protection Agency (USEPA) guidelines, ten of the twelve MEs can cause significant health problems for inhabitants (HI > 1) due to PM2.5 and PM10. Thus, special attention should be given by stakeholders/inhabitants to minimize the health impacts on long-term exposure. This study assessed the risk of levels of trace elements on the inhabitants who spend most of their daily lives. The study revealed that the lifetime cancer risk values for the individual and cumulative trace elements were within the tolerable range set by the USEPA guidelines.

Long-term analysis of BTEX concentrations and health risks in semi-arid urban regions

Rajasthan, experiencing rapid industrialization and urbanization, faces critical air quality challenges, particularly concerning toxic volatile organic compounds (VOCs) such as BTEX (Benzene, Toluene, Ethylbenzene, Xylene). This study presents a long-term analysis of BTEX concentrations across various cities in Rajasthan, India, using data from the Central Pollution Control Board (CPCB) from 2017 to 2022. The findings revealed that the average ∑BTEX concentrations increased from 4.15 µg/m3 in 2017 to 12.29 µg/m3 in 2022, with a temporary decline in 2020. The Hazard Quotient (HQ) values for BTEX exposure ranged from 0.052 to 0.15 for males, 0.056 to 0.17 for females, and 0.09 to 0.29 for children over the study period, indicating higher health risks for children. Similarly, the Lifetime Cancer Risk (LCR) values varied from 6.04 × 10⁻⁶ to 1.92 × 10⁻5 for males, 1.09 × 10⁻⁶ to 2.24 × 10⁻5 for females, and 1.17 × 10⁻5 to 3.73 × 10⁻5 for children. The results demonstrate that children are at a greater cancer risk from BTEX exposure compared to adults. This study emphasizes the urgent need for effective air pollution control measures and continuous monitoring to protect public health, particularly vulnerable populations like children.

Validation of the 2019 American Society of Colposcopy and Cervical Pathology Online Cervical Cancer Screening Program via 9 Large-Cohort Data of Chinese Women.

The aim of the study is to validate the applicability and performance of the 2019 US risk-based guideline for Chinese women. We analyzed 10,055 cases with data on human papillomavirus testing, cytology, and pathologically confirmed diagnosis (analysis-set). According to the 2019 US risk-based guideline, we recorded the risk value and triage recommendations for each case. Then, we assessed the concordance of the guideline triage recommendations with pathology diagnosis for the relevant case from the real-world projects. Among the analysis-set, 9,495 cases with an estimated risk value were identified as analysis cohort while the remaining 560 cases were cataloged as "special cases." Among the analysis cohort, 960 and 526 cases were pathologically confirmed as cervical intraepithelial neoplasia (CIN) 2+ and CIN3+, respectively. The US risk-based guideline recommended colposcopy or more aggressive interventions (Colp+) for 86.8% (833/960) of the CIN2+ and 95.8% (504/526) of the CIN3+ cases, with 87.1% sensitivity and 82.5% specificity for CIN3+ cases (AUC = 0.926, p < .0001). The US risk-based recommended no-Colp for 98.0% (6,142/6,269) of the pathologically confirmed CIN1 or benign cases. In addition, 97.3% (545/560) of the "special cases" cases were recommended as Colp+. The 2019 US risk-based guideline works well with satisfied clinical sensitivity for CIN2+ and CIN3+ and seems applicable for cervical cancer screening in China.

Moss biomonitoring in areas affected by ashfalls of Shiveluch volcano (Kamchatka).

The moss bag technique was applied on Kamchatka to assess the effect of Shiveluch volcano on the air quality. Moss bags were exposed in settlements located at different distances from the volcano and affected by ashfall to varying degrees. The inductively coupled plasma optical emission spectrometry was used for the determination of the content of Al, Ba, Co, Cd, Cr, Cu, Fe, Mn, P, Pb, Sr, S, V, and Zn in both exposed and unexposed moss samples. Relative accumulation factor revealed enrichment of mosses exposed in the area affected by ashfall with Al, Cr, V, and Zn. Correlation and principal component analysis allowed to identify elements of volcanogenic, geogenic, and anthropogenic origin. Ecological risk values less than 150 indicate low potential ecological risk in the region. Active moss biomonitoring can be considered a cheap and efficient tool for in-depth study of the influence of volcanic activity on air quality on the peninsula.

A Passenger Ship Emergency Evacuation Line Efficiency Evaluation Operator Considering Safety Capacity and its Application

Introduction: Aiming at evaluating the efficiency of passenger ship emergency evacuation routes, this study proposes an evaluation operator for passenger ship emergency evacuation routes, and then conducts simulation research on the passenger ship evacuation process. Method: The main innovations of this study are as follows. Firstly, this study proposes an evaluation operator for passenger ship emergency evacuation lines based on consideration of the passage capacity, ship heeling effect, traffic flow obstruction, personnel evacuation mood, accident location, and other factors. Secondly, this study discretizes the emergency evacuation path of passenger ships into a three-dimensional topological network structure and uses simulation data to calculate the traffic capacity between nodes. By comparing the calculated value with the simulated value, a risk assessment method for emergency evacuation is given. Thirdly, this study takes the three-story ro-ro passenger ship in the European "SAFEGUARD" project as an example and gives three passenger ship evacuation simulation processes under different passenger flow densities. Result: The results of the calculation example show that the risk-prone areas are mainly concentrated in the passenger ship stairs, and the risk value increases with the passenger flow. Conclusion: The calculation results verify the effectiveness of the emergency evacuation line efficiency evaluation operator proposed in this study.

Enhancing Portfolio Decarbonization Through SensitivityVaR and Distorted Stochastic Dominance

Recent trends in portfolio management emphasize the importance of reducing carbon footprints and aligning investments with sustainable practices. This paper introduces SensitivityVaR (SensitivityVaR), an advanced distortion risk measure that combines Value-at-Risk (VaR) and Expected Shortfall (ES) with the Cornish–Fisher expansion. SensitivityVaR provides a more robust framework for managing risk, particularly under extreme market conditions. By incorporating first- and second-order distorted stochastic dominance criteria, we enhance portfolio decarbonization strategies, aligning financial objectives with environmental targets such as the Paris Agreement’s goal of a 7% annual reduction in carbon intensity from 2019 to 2050. Our empirical analysis evaluates the impact of integrating carbon intensity data—including Scope 1, Scope 2, and Scope 3 emissions—on portfolio optimization, focusing on key sectors like technology, energy, and consumer goods. The results demonstrate the effectiveness of SensitivityVaR in managing both risk and environmental impact. The methodology led to significant reductions in carbon intensity across different portfolio configurations, while preserving competitive risk-adjusted returns. By optimizing tail risks and limiting exposure to carbon-intensive assets, this approach produced more balanced and efficient portfolios that aligned with both financial and sustainability goals. These findings offer valuable insights for institutional investors and asset managers aiming to integrate climate considerations into their investment strategies without compromising financial performance.

A Novel NLP-based Stock Market Price Prediction and Risk Analysis Framework

Stock market prediction is an interesting and complex problem that has recently been in the limelight, thanks to the significant accuracy achieved by deep learning models. However, a complete platform with prediction and risk analysis ability is unavailable. In the current work, we present a novel framework for investment analysis designed to create ease for investors and provide a confidence measure along with the stock price to depict the risk involved in investing in stocks of a particular company. The model integrates two different approaches successfully to improve accuracy significantly. The model inputs two sources – a stock price dataset depicting the original scores as numerals and textual data extracted from Reddit news articles. The traditional problem of stock price prediction is dealt with using LSTMs on individual stock prices. At the same time, the confidence is represented by a risk value calculated intelligently using XGBoost and LSTM output. We have deployed natural language processing techniques for performing sentiment and subjectivity analyses, which are then used to extract features for further investigation in the study. The results show that an accuracy of 94% for stock trend prediction can be achieved using PCA as the feature extractor with tuned parameters for XGBoost and around 76% accuracy for stock price prediction with a tuned LSTM. It removes the hassle for investors to research the project or company they want to invest in and provides all relevant analysis and data.

A new Bayesian method for estimation of value at risk and conditional value at risk

AbstractValue at Risk (VaR) and Conditional Value at Risk (CVaR) have become the most popular measures of market risk in Financial and Insurance fields. However, the estimation of both risk measures is challenging, because it requires the knowledge of the tail of the distribution. Therefore, Extreme Value Theory initially seemed to be one of the best tools for this kind of problems, because using peaks-over-threshold method, we can assume the tail data approximately follow a Generalized Pareto distribution (GPD). The main objection to its use is that it only employs observations over the threshold, which are usually scarce. With the aim of improving the inference process, we propose a new Bayesian method that computes estimates built with all the information available. Informative prior Bayesian (IPB) method employs the existing relations between the parameters of the loss distribution and the parameters of the GPD that models the tail data to define informative priors in order to perform Metropolis–Hastings algorithm. We show how to apply IPB when the distribution of the observations is Exponential, stable or Gamma, to make inference and predictions. .Afterwards, we perform a thorough simulation study to compare the accuracy and precision of the estimates computed by IPB and the most employed methods to estimate VaR and CVaR. Results show that IPB provides the most accurate, precise and least biased estimates, especially when there are very few tail data. Finally, data from two real examples are analysed to show the practical application of the method.

Risk assessment for the surface water quality evaluation of a hydrological basin

AbstractThis paper proposes a risk assessment methodology for evaluating the surface water quality of hydrological basins based on physico-chemical parameter concentrations. Considering the Douro River basin in Portugal and monthly recorded dissolved oxygen and conductivity parameter measurements in 18 water sampling stations from January 2002 to December 2013, the work intends to answer the research question of identifying the riskiest periods for water pollution in the year and classifying the water sampling stations in terms of risk for water pollution. The methodology consists first in determining the pollution risk implied by the physico-chemical parameters, based on the monthly water station measurements, using six different risk measures, namely mean, variance, loss probability, entropy, mean excess loss and value at risk. The risk values are ordered according to each risk measure and a final ranking is established through a ranking aggregation method. The final ranking permitted identifying the high risk period as ranging from May to October and the low risk period from November to April. Furthermore, July was classified as riskiest month concerning the dissolved oxygen concentration, and August as riskiest month regarding the conductivity levels. On the other hand, the ranking allowed classifying the water sampling stations, previously grouped in clusters, in terms of similar risk for water pollution: six sampling stations in the west of the basin formed the riskiest cluster in the dry period considering the dissolved oxygen concentrations, and four of those stations formed also the riskiest cluster concerning the conductivity levels.

Environmental and human health risk of potentially toxic metals in freshwater and brackish water Nile tilapia (Oreochromis niloticus) aquaculture.

Tilapia aquaculture is rapidly expanding worldwide, particularly in Bangladesh. However, metal pollution in aquaculture presents significant environmental and human health risks. This study aimed to evaluate the concentrations of 13 potentially toxic metals (As, Be, Cd, Co, Cr, Cu, Hg, Ni, Pb, V, Mn, Se, and Zn) in Nile tilapia (Oreochromis niloticus), surface water, and sediment from freshwater and brackish water aquaculture ponds. The study also assessed the associated environmental and human health risks. Samples of tilapia, water, and sediment were collected between October and November 2021 and analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The estimated daily intake (EDI) of As, Cr, Pb, Se, and Zn in tilapia muscle of both freshwater and brackish water, as well as Cd and Ni in brackish water, exceeded recommended EDI values. The Target Hazard Quotient (THQ) was less than 1 for most metals, except for As in brackish water tilapia and Cr in both freshwater and brackish water tilapia, indicating potential health risks. The Target Cancer Risk (TR) values for As in both freshwater and brackish water tilapia, and for Cr and Ni in freshwater tilapia, exceeded acceptable ranges. While the concentrations of metals in surface water of both freshwater and brackish water tilapia farms varied, all mean concentrations were below WHO recommended limits. The contamination factor (Cf) values were less than 1 for all metals in both types of aquaculture ponds, except for Zn in freshwater sediment and Se in brackish water sediment. Additionally, the calculated risk indices including the Pollution Load Index (PLI), Geoaccumulation Index (Igeo), Ecological Risk Factor (Er), and Potential Ecological Risk Factor (PER) for sediment were below the risk thresholds values (PLI < 1, Igeo < 0, Er < 40, and PER < 150). The significant positive correlations were found between tilapia muscle and the sediment of the respective ponds for arsenic (As) (ρ= 0.8, p<0.002) and Cr (ρ= 0.7, p<0.02). Although the levels of studied metals in water and sediment from freshwater and brackish water aquaculture ponds were generally within recommended guidelines, this study underscores the need for continuous monitoring and preventative measures, particularly to address elevated levels of As and Cr in tilapia muscle, which may pose potential risks to human health.

Contamination Features and Quantitative Source Apportionment of Potentially Toxic Elements in the Urban Surface Soil, the Case of Hamedan, West of Iran.

In this study, a total of 180 surface soil samples were collected from a control area and residential, commercial, and industrial regions of Hamedan, Iran during the fall season in 2023. Contents of analyzed elements were then determined using ICP-OES. The results illustrated that the average contents of As, Cd, Cu, Mn, Ni, and Pb were 1.17-2.26 times greater than those reported as local background values, while the mean contents of As, Cd, and Cu were respectively 3.41, 1.25, and 1.00 times greater than the background contents for Iran by implying the possible human sources of these PTEs. The cumulative average ecological risk value with 81.9, demonstrated moderate ecological risk across the study area. The results of source apportionment showed that the PTEs contamination in the soil of the study area mainly originates from the anthropogenic activities (65.6%) and traffic emissions as the primary pollution source (47.3%) had the highest contribution to the PTE pollution in the study area. In conclusion, by providing a useful approach to identifying the sources and contributions of toxic elements across different functional areas, this study has the potential to guide future efforts aimed at managing and mitigating the pollution caused by metal elements.

A Two-Stage Bayesian Network Approach to Inland Waterway Navigation Risk Assessment Considering the Characteristics of Different River Segments: A Case of the Yangtze River

Identifying the main sources of risk for different types of waterways helps to develop targeted risk control strategies for different river segments. To improve the level of risk management in inland waterways for sustainable development, a two-stage risk evaluation model is proposed in this study by integrating a fuzzy rule base and Bayesian networks. The model evaluates risk sources from the following four dimensions: probability of occurrence, visibility, probability of causing accidents, and consequences. Typical river sections in the upper, middle, and lower reaches of the Yangtze River were selected as cases, and 19 risk sources were identified and comparatively analyzed from the perspectives of humans, ships, the environment, and management. The fuzzy rule base is employed to compare expert opinions, yielding three key risk sources for each section based on their risk values. The findings reveal certain commonalities in the principal risk sources across sections. For example, natural disasters (landslides, earthquakes, and extreme hydrological conditions) are present in both the middle and lower reaches, and an insufficient channel width is common in the upper and middle reaches. However, the key risk sources differ among the sections. The upper reaches are primarily threatened by the improper management of affiliated vessels and adverse weather, while the middle reaches suffer from insufficient channel width surplus, and the lower reaches are mainly threatened by high vessel traffic density and low-quality crews. The results of the study show that the key risk sources in each section of the Yangtze River have obvious differences and need to be assessed according to the characteristics of different sections. This study can provide a reference for decision-making in inland waterway risk management by maritime safety authorities.

Evaluation of human and ecological health risks associated with the potentially toxic heavy metals in groundwater of Vellore city, Tamil Nadu, India

Groundwater pollution by heavy metals is a significant and alarming threat globally, through its chronic effect on human health and ecosystem. The current study evaluated the identification and risk assessment of heavy metals in groundwater of the Vellore city, Tamilnadu, India. Groundwater samples were collected from 32 locations over a continuous period of 2022–2023 for every three months on seasonal basis. The samples were analysed for pH, Total Dissolved Solids (TDS), Hardness and heavy metals (Al, As, Ba, Cd, Cu, Pb, Al and Zn). The analysed mean concentrations of these heavy metals were found in the order: As > Cd > Pb > Ba >Zn >Al> Cu. Elevated concentrations of heavy metals were observed in 2022, likely influenced by rainfall and land use patterns. Heavy metals such as Al, As, Pb, and Cd exceeded the BIS limits and whereas Ba, Cu, and Zn concentrations remain within desirable limits. Groundwater Quality Index (GWQI) classified 41% as 'unfit for drinking'. Ecological risk indices (ERI) indicate significant contamination in 34% of samples, with Al and Pb being primary contributors. Non-carcinogenic health risk assessments reveal, chronic hazards, where children facing higher risks followed by men and women groups. Carcinogenic risk assessments indices such as Heavy metal pollution Index (HPI) shown 25% of samples in critical quality, Heavy metal Evaluation Index (HEI) evaluated all samples were in low contamination and Contamination Index (CI) shown 72% samples under high contamination posing high risk to humans. Probable Cancer Risk (PCR) values for As, Pb, and Cd exceed acceptable ranges across all demographic groups posing cancer risk to humans particularly children. The present study highlights the need for groundwater treatment and regulatory interventions to mitigate health and ecological risks due to the contamination of heavy metals in Vellore city.

Assessment of the activity concentration of radon and its health hazard in surface water around the Rooppur Nuclear Power Plant (RNPP) site, Bangladesh

ABSTRACT Radon is a colourless, unscented, radioactive inert gas. As a gaseous element, Rn-222 can be effectively breathed in, leading to a health hazard. The main objective of this study is to measure the amount of Rn-222 concentration in surface water and its associated health hazards around the Rooppur Nuclear Power Plant (RNPP) construction site area in Bangladesh. Twenty water samples were collected each year (2022 and 2023) from different specific locations of the Padma River and investigated for radon concentration through a Durridge RAD7 detector with RAD H2O accessories. The range of radon activity in surface water measured from 0.070 ± 0.035 to 0.385 ± 0.211 BqL−1 with a mean activity of 0.194 ± 0.114 BqL−1 in the year 2022 and in the year 2023, the range of radon activity in surface water measured from 0.035 ± 0.070 to 0.455 ± 0.239 BqL−1 with an average activity of 0.228 ± 0.140 BqL−1. All the radon concentration results were below the recommended limits of WHO (100 BqL−1) and USEPA (11.1 BqL−1). The ranges of annual effective dose (AED) were from 0.1911 to 1.051 µSvy−1 and from 0.095 to 1.242 µSvy−1 in the years 2022 and 2023, respectively, which were lower than the AED recommended by WHO (0.1 mSvy−1). The mean values of excess lifetime cancer risk are 0.0021 × 10−3 and 0.0025 × 10−3 in the years 2022 and 2023, respectively, which were lower than the average standard value recommended by UNSCEAR (0.29 × 10−3). The result of this investigation can be applied as baseline data for radon concentration measurement in the under-construction nuclear power plant site area vicinity of Bangladesh.

Assessing the potential ecological and human health risks of trace metal pollution in surface water, sediment, and commercially valuable fish species in the Pashur River, Bangladesh.

This research examines the contamination levels in the Pashur River in Bangladesh stemming from trace metal discharge originating from the Mongla seaport and various industrial outlets. It delves into both ecological risks and potential health hazards for humans consuming fish carrying accumulated trace metals. The research employed atomic absorption spectrometry to measure the concentrations of chromium (Cr), arsenic (As), manganese (Mn), copper (Cu), zinc (Zn), nickel (Ni), lead (Pb), and cadmium (Cd) in surface water, sediment, and fish samples. Target hazard quotient (THQ) and carcinogenic risks were calculated to determine the human health risk caused by the consumption of these targeted fish species. An RI value of 42.89 indicates that the collective presence of trace metals in sediment poses significant ecological risks to the study area. Although the majority of trace metals present in sediment are categorized under class 1 (ranging from unpolluted to moderately polluted) based on the Igeo values, Cd is classified under class 2, signifying a moderate level of pollution. Significantly, THQ values surpass the threshold of 1 for Cr and As, indicating potential health risks associated with the consumption of specific fish species. Among the trace metals analyzed, Ni demonstrates the highest cancer risk (CR) value, at 5.78 × 103, indicating a notable cancer risk associated with the consumption of targeted fish. Recommendations include the strict enforcement of waste disposal policies to mitigate anthropogenic discharge and safeguard the river from further pollution.

A fuzzy evidential reasoning-based approach for assessing the navigation obstruction risk of shipwrecks in the Yangtze river

ABSTRACT This paper aims to evaluate the navigation obstruction risk represented by shipwrecks in shallow waters based on a fuzzy evidential reasoning approach. The purpose of this approach is to establish a hierarchical decision-making framework that considers ship conditions, traffic environment, distance from sensitive areas, and natural environment; to derive the belief rule base using the IF-THEN rule with a belief structure; and to obtain the crisp values of navigation obstruction risk of shipwrecks via evidential reasoning. This approach is applied to the navigation obstruction risk assessment of 10 historical shipwrecks in the Yangtze River, and the evaluation results are consistent with historical data. Consequently, this approach can be used for assisting in shipwreck salvage decision-making in navigable waters.