Distribution, Mobility, and Health Risks Assessment of Trace Metals in River Sediments from Intense Agricultural Activity Areas in West Africa

The economy of West African countries is mainly based on agriculture. However, the trace metal(loid)s contamination status in rivers is relatively unknown in the region. In this work, 45 surface sediments collected from the Bandama, Comoé, and Bia Rivers in south and south eastern Côte d’Ivoire (West Africa), were analyzed for total metal concentrations and chemical speciation. The results showed that the river sediments were considerably contaminated by Cd and moderately contaminated by As, Cu, Pb, and Zn. Significant spatial variations were observed among the stations but not between the rivers. Metals Cd and Cu were likely to cause more ecological risks. The speciation analysis unravelled that the metal(loid)s partitioned mainly in the residual fraction, with the potential mobile fraction varying from 14% to 28%. The study calls for establishment of strict policies relative to the application of fertilizers and agrochemicals and mining activities to protect the environment and human health risks.

Risks Matrixes Risks Assessment Tools of Small and Medium-Sized Enterprises： The Case of Latvia

The enterprises need to assess the risk dynamic of financial instability and its impact on small and medium-sized enterprises＇ development, because it is important for enterprises to extend commercial activity and to open a new structural subdivision. We have researched types of risks, their identification, classification, and assessment possibilities in activities of small and medium-sized enterprises. We have used our own algorithm of identification, classification, and assessment of enterprises＇ risks. The goal of this research is to study the economic and financial risks＇ impact on small and medium-sized enterprises＇ development in Latvia. For study purpose, we have carried out the questionnaire of representative small and medium-sized enterprises about the economic and financial risks＇ impact on enterprises＇ development in Latvia. We have created classification of Latvian services sectors＇ economic and financial risks in the period from 2011 to 2012. Those risks have been included in the questionnaire. The risks matrix is a quantitative assessment tool of risks. We have created Latvian service sector economic and financial risks matrix. We have arranged risks by their sizes of possible losses for enterprises. For each risk has been assessed its probability of realization. We have created Latvian accommodations （hotel） and food services technological process risks map. Several parts of the risk map （segments） make it possible to assess each type of the risk separately in its segment. Risks matrix can be used to choose enterprises＇ strategy of risk management. Enterprise＇s strategy of risk management is developed by analysing zones of risk level.

Heavy metals leaching in bottom ash and fly ash fractions from industrial-scale BFB-boiler for environmental risks assessment

The bottom ash and fly ash from the co-combustion of wood residues and peat at a bubbling fluidised bed boiler（296 MW） contained only quartz（SiO_2）, microcline（KAl Si_3O_8） and albite（NaAlSi_3O_8）. Thus, X-ray powder diffraction（XRD） was not useful for clarifying the difference in the release of associated heavy metals from ash matrices. In order to assess the release of heavy metals from ashes under changing environmental conditions, they were sequentially extracted and fractionated by the BCR-procedure into acid soluble/exchangeable（CH_3COOH）, reducible（NH_2OH-HCl） and oxidizable（H_2O_2/CH_3COONH_4） phases. The CH_3 COOH extractable fraction in conjunction with the total heavy metals concentrations were used to calculate the risk assessment code values for heavy metals leaching from the ash matrix. The leaching studies indicate that the heavy metals in the bottom ash and fly ash are bound to different fractions with different strengths. From the environmental and utilization perspectives, heavy metals in ashes posed different levels of environmental contamination risk. Only As in the bottom ash posed a very high risk. High risk metals were Cd in the bottom ash as well as As, Cd and Se in the fly ash.

Health Risks Assessment of Heavy Metal Pollution in the Soil-Crop System from an E-Waste Dismantling Area

Soil is an essential resource for agricultural production.In order to investigate the pollution situation of heavy metals in the soil-crop system in the e-waste dismantling area,the crop and soil samples(226 pairs,including leaf vegetables,solanaceous vegetables,root vegetables,and fruits)around the e-waste dismantling area in southeastern Zhejiang Province were collected.The concentrations of Cd,Cu,Pb,and Cr were determined.The average concentrations of Cd,Cu,Pb,and Cr in soils were 0.94,107.79,80.28,and 78.14 mg kg-1,respectively,and their corresponding concentrations in crops were 0.024,0.7,0.041,and 0.06 mg kg-1,respectively.The transfer capacity of leaf vegetables was significantly higher than that of non-leaf vegetables,and the accumulation of four heavy metals in crops tended to be Cd>Cu>Cr/Pb.The pollution index’s results revealed that the soil pollution degree under different land uses ranked as root vegetables soil>leaf vegetables soil>solanaceous vegetables soil>fruit soil.The carcinogenic and non-carcinogenic risks of heavy metal exposure were ranked as food intake>accidental ingestion>dermal contact>inhalation.The comprehensive non-carcinogenic risk was ranked as Cr>Cd>Pb/Cu.Our results could be used to provide useful information for further crop cultivation layout in the study area,which can guarantee the local residents’health and food safety.

Health Risks Assessment Due to Exposure to Vinyl Chloride in Groundwater from a Closed Landfill： A Case Study as a Contaminant of Concern and Effect of Subsurface Characteristics

The purpose of this study was to analyze the migration pathways of contaminants from closed landfills and to estimate health risks based on soil characteristics. The health risks were estimated using Framework for Risk Analysis Multimedia Environmental Systems （FRAMES） software. The sensitivity of human health risks and hazard indices due to vinyl chloride contamination in groundwater were performed in relation to soil characteristics such as Darcy velocity, thickness of soil layer, mass of contaminant present in the aquifer. Based on the analysis, Darcy velocity showed no effect on estimated risks. Since soil layer thickness had a significant effect on the estimated health risks, effects of different soil types on estimated risks were analyzed. The results showed that soils from the least appropriate to the most appropriate for risk management due to groundwater contamination were sand, sandy clay, sandy loam, loam and clay loam. FRAMES model was suitable for assessing the health risks due to vinyl chloride contamination in groundwater originating from a municipal solid waste landfill. The model showed the changes in both carcinogenic and non carcinogenic risks over time. The estimated health risks were directly correlated with the levels of vinyl chloride detected in groundwater.

Development of Localized Assessment of Municipal Wastewater Disposal Risks

A means to develop a comparative assessment of the risks of available wastewater effluent disposal options on a local scale needs to be developed to help local decision-makers make decisions on options such as direct or indirect potable reuse options. These options have garnered more interest as a result of water supply limitations in many urban areas. This risk assessment was developed from a risk assessment developed at the University of Miami in 2001 and Florida Atlantic University (FAU) in 2023. Direct potable reuse and injection wells were deemed to have the lowest risk in the most recent study by FAU. However, the injection well option may not be available everywhere. As a result, a more local means to assess exposure risk is needed. This paper outlines the process to evaluate the public health risks associated with available disposal alternatives which may be very limited in some areas. The development of exposure pathways can help local decision-makers define the challenges, and support later expert level analysis upon which public health decisions are based.

Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

A risk assessment method considering risk attributes and work safety informational needs and its application

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.Risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

Comprehensive Risk Assessment of Sea Level Rise and Tropical Cyclones in Dongzhaigang Mangroves,China

Mangroves play a pivotal role in tropical and subtropical coastal ecosystem,yet they are highly vulnerable to the effects of climate change,particularly the accelerated global sea level rise(SLR)and stronger tropical cyclones(TCs).However,there is a lack of research addressing future simultaneous combined impacts of the slow-onset of SLR and rapid-onset of TCs on China's mangroves.In order to develop a comprehensive risk assessment method considering the superimposed effects of these two factors and analyze risk for mangroves in Dongzhaigang,Hainan Island,China,we used observational and climate model data to assess the risks to mangroves under low,intermediate,and very high greenhouse gas(GHG)emission scenarios(such as SSP1-2.6,SSP2-4.5,and SSP5-8.5)in 2030,2050,and 2100,and compiled a risk assessment scheme for mangroves in Dongzhaigang,China.The results showed that the combined risks from SLR and TCs will continue to rise;however,SLRs will increase in intensity,and TCs will decrease.The comprehensive risk of the Dongzhaigang mangroves posed by climate change will remain low under SSP1-2.6 and SSP2-4.5 scenarios by 2030,but it will increase substantially by 2100.While under SSP5-8.5 scenario,the risks to mangroves in Dongzhaigang are projected to increase considerably by 2050,and approximately 68.8%of mangroves will be at very high risk by 2100.The risk to the Dongzhaigang mangroves is not only influenced by the hazards but also closely linked to their exposure and vulnerability.We therefore propose climate resilience developmental responses for mangroves to address the effects of climate change.This study for the combined impact of TCs and SLR on mangroves in Dongzhaigang,China can enrich the method system of mangrove risk assessment and provide references for scientific management.

Arsenic and fluoride co-enrichment of groundwater in the loess areas and associated human health risks:A case study of Dali County in the Guanzhong Basin

This study aims to reveal the occurrence and origin of typical groundwater with high arsenic and fluoride concentrations in the loess area of the Guanzhong Basin—a Neogene faulted basin.Key findings are as follows:(1)Groundwater samples with high arsenic and fluoride concentrations collected from the loess area and the terraces of the Weihe River accounted for 26%and 30%,respectively,of the total samples,with primary hydrochemical type identified as HCO_(3)-Na.The karst and sand areas exhibit relatively high groundwater quality,serving as preferred sources for water supply.It is recommended that local governments fully harness groundwater in these areas;(2)groundwater with high arsenic and fluoride concentrations in the loess area and the alluvial plain of rivers in Dali County is primarily distributed within the Guanzhong Basin,which represents the drainage zone of groundwater;(3)arsenic and fluoride in groundwater originate principally from natural and anthropogenic sources;(4)the human health risk assessments reveal that long-term intake of groundwater with high arsenic and fluoride concentrations pose cancer or non-cancer risks,which are more serious to kids compared to adults.This study provides a theoretical basis for the prevention and treatment of groundwater with high arsenic and fluoride concentrations in loess areas.

Distribution, health and ecological risk assessments of trace elements in Nigerian oil sands

The Nigerian oil sands represent the largest oil sand deposit in Africa, yet there is little published information on the distribution and potential health and ecological risks of trace elements in the oil resource. In the present study, we investigated the distribution pattern of 18trace elements(including biophile and chalcophile elements) as well as the estimated risks associated with exposure to these elements. The results of the study indicated that Fe was the most abundant element, with a mean concentration of 22,131 mg/kg while Br had the lowest mean concentration of 48 mg/kg. The high occurrence of Fe and Ti suggested a possible occurrence of ilmenite(Fe TiO_(3)) in the oil sands. Source apportionment using positive matrix factorization showed that the possible sources of detected elements in the oil sands were geogenic, metal production, and crustal. The contamination factor, geo-accumulation index, modified degree of contamination, pollution load index, and Nemerow pollution index indicated that the oil sands are heavily polluted by the elements. Health risk assessment showed that children were relatively more susceptible to the potentially toxic elements in the oil sands principally via ingestion exposure route(HQ > 1E-04). Cancer risks from inhalation are unlikely due to CR < 1E-06 but ingestion and dermal contact pose severe risks(CR > 1E-04). The high concentrations of the elements pose serious threats due to the potential for atmospheric transport, bioaccessibility, and bioavailability.

Identifying the Hydrochemical Characteristics,Genetic Mechanisms and Potential Human Health Risks of Fluoride and Nitrate Enriched Groundwater in the Tongzhou District,Beijing,North China

Fluoride and nitrate enriched groundwater are potential threats to the safety of the groundwater supply that may cause significant effects on human health and public safety,especially in aggregated population areas and economic hubs.This study focuses on the high F^(−)and NO_(3)^(−)concentration groundwater in Tongzhou District,Beijing,North China.A total of 36 groundwater samples were collected to analyze the hydrochemical characteristics,elucidate genetic mechanisms and evaluate the potential human health risks.The results of the analysis indicate:Firstly,most of the groundwater samples are characterized by Mg-HCO_(3) and Na-HCO_(3) with the pH ranging from 7.19 to 8.28 and TDS with a large variation across the range 471-2337 mg/L.The NO_(3)^(−)concentration in 38.89%groundwater samples and the F^(−)concentration in 66.67%groundwater samples exceed the permissible limited value.Secondly,F^(−)in groundwater originates predominantly from water-rock interactions and the fluorite dissolution,which is also regulated by cation exchange,competitive adsorption of HCO_(3)−and an alkaline environment.Thirdly,the effect of sewage disposal and agricultural activities have a significant effect on high NO3-concentration,while the high F^(−)concentration is less influenced by anthropogenic activity.The alkaline environment favors nitrification,thus being conducive to the production of NO_(3)^(−).Finally,the health risk assessment is evaluated for different population groups.The results indicate that high NO_(3)^(−)and F^(−)concentration in groundwater would have the largest threat to children’s health.The findings of this study could contribute to the provision of a scientific basis for groundwater supply policy formulation relating to public health in Tongzhou District.

Health Risk Assessment of Employees Exposed to Chlorination By-products of Recreational Water in Large Amusement Parks in Shanghai

Objective Chlorination is often used to disinfect recreational water in large amusement parks;however,the health hazards of chlorination disinfection by-products(DBPs)to occupational populations are unknown.This study aimed to assess the exposure status of chlorinated DBPs in recreational water and the health risks to employees of large amusement parks.Methods Exposure parameters of employees of three large amusement parks in Shanghai were investigated using a questionnaire.Seven typical chlorinated DBPs in recreational water and spray samples were quantified by gas chromatography,and the health risks to amusement park employees exposed to chlorinated DBPs were evaluated according to the WHO's risk assessment framework.Results Trichloroacetic acid,dibromochloromethane,bromodichloromethane,and dichloroacetic acid were detected predominantly in recreational water.The carcinogenic and non-carcinogenic risks of the five DBPs did not exceed the risk thresholds.In addition,the carcinogenic and non-carcinogenic risks of mixed exposure to DBPs were within the acceptable risk limits.Conclusion Typical DBPs were widely detected in recreational water collected from three large amusement parks in Shanghai;however,the health risks of DBPs and their mixtures were within acceptable limits.

An Innovative Deep Architecture for Flight Safety Risk Assessment Based on Time Series Data

With the development of the integration of aviation safety and artificial intelligence,research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management,but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry.Therefore,an improved risk assessment algorithm(PS-AE-LSTM)based on long short-term memory network(LSTM)with autoencoder(AE)is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels.Firstly,based on the normal distribution characteristics of flight data,a probability severity(PS)model is established to enhance the quality of risk assessment labels.Secondly,autoencoder is introduced to reconstruct the flight parameter data to improve the data quality.Finally,utilizing the time-series nature of flight data,a long and short-termmemory network is used to classify the risk level and improve the accuracy of risk assessment.Thus,a risk assessment experimentwas conducted to analyze a fleet landing phase dataset using the PS-AE-LSTMalgorithm to assess the risk level associated with aircraft hard landing events.The results show that the proposed algorithm achieves an accuracy of 86.45%compared with seven baseline models and has excellent risk assessment capability.

Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

IoT Smart Devices Risk Assessment Model Using Fuzzy Logic and PSO

Increasing Internet of Things(IoT)device connectivity makes botnet attacks more dangerous,carrying catastrophic hazards.As IoT botnets evolve,their dynamic and multifaceted nature hampers conventional detection methods.This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization(PSO)to address the risks associated with IoT botnets.Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically.Fuzzy component settings are optimized using PSO to improve accuracy.The methodology allows for more complex thinking by transitioning from binary to continuous assessment.Instead of expert inputs,PSO data-driven tunes rules and membership functions.This study presents a complete IoT botnet risk assessment system.The methodology helps security teams allocate resources by categorizing threats as high,medium,or low severity.This study shows how CICIoT2023 can assess cyber risks.Our research has implications beyond detection,as it provides a proactive approach to risk management and promotes the development of more secure IoT environments.

Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

With the exponential increase in information security risks,ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment.However,experts possess a limited understanding of fundamental security elements,such as assets,threats,and vulnerabilities,due to the confidentiality of airborne networks,resulting in cognitive uncertainty.Therefore,the Pythagorean fuzzy Analytic Hierarchy Process(AHP)Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks.First,Pythagorean fuzzy AHP is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights,which is used to solve the expert cognitive uncertainty in the process of evaluating the index system weight of airborne networks.Second,Pythagorean fuzzy the TOPSIS to an Ideal Solution is utilized to assess the risk prioritization of airborne networks using the Pythagorean fuzzy weighted distance measure,which is used to address the cognitive uncertainty in the evaluation process of various indicators in airborne network threat scenarios.Finally,a comparative analysis was conducted.The proposed method demonstrated the highest Kendall coordination coefficient of 0.952.This finding indicates superior consistency and confirms the efficacy of the method in addressing expert cognition during information security risk assessment for airborne networks.