Comprehensive Risk Evaluation Research Articles

Research on the Fire Behaviors of Polymeric Separator Materials PI, PPESK, and PVDF

Certain polymers, such as polyvinylidene fluoride (PVDF), polyimide (PI), and poly (phthalazinone ether sulfone ketone) (PPESK), are commonly used separator materials in batteries. However, during the thermal runaway (TR) processing of batteries, significant heat is released by the combustion of the polymer separator. Therefore, analysis of the fire behaviors of polymer separator materials will facilitate a more comprehensive quantitative evaluation of battery thermal risk. This paper investigated the combustion properties of three types of polymers, namely, PVDF, PI, and PPESK, as potential separator materials by cone calorimetry and thermogravimetry (TG). A series of characteristic parameters, including ignition time (TTI), heat release rate (HRR), smoke production rate (SPR), and total heat release (THR), were evaluated for three polymers and blends (PI/PVDF, PPESK/PVDF) under an external heat flux of 45 or 60 kW/m2, respectively. The combustion characteristics and fire hazards of the three polymers and corresponding mixtures were analyzed through the comparative analysis of experimental data and phenomena. Under 60 kW/m2, the HRR curves of all polymers presented two peaks, while PI/PVDF and PPESK/PVDF mixtures exhibited one obvious peak. Moreover, the peak HRR (pHRR) for the mixed polymers was higher, indicating a relatively higher fire risk. However, in the application scenario, the mixed state represents the main polymer form as the active separator materials in batteries. The results showed that the specific coupling behaviors were related primarily to the component type. This work will help evaluate the fire risk of polymeric separator materials based on the combustion characteristics to predict the safety of mixtures in batteries and develop new methods for fire suppression.

A Multi-Hazard Risk Assessment Framework for Urban Disaster Prevention Planning: A Case Study of Xiamen, China

Understanding and measuring the relative risk level of a city facing multi-hazards is fundamental to improving its disaster prevention planning and schemes. A comprehensive risk evaluation approach stands at the intersection of risk management and disaster system theory. It is also an important interdisciplinary field of catastrophology, economics, and urban infrastructure planning. We believe that current attempts to define and measure comprehensive urban natural disaster risks have certain limitations. Therefore, we propose an Urban Multi-hazards Risk Assessment Framework (UMRAF) which draws on definitions, methods, and experience from risk management, evaluation of property, the value of statistical life, and disaster system theory. It contains local disaster identification, place-based risk assessment (taking into account more than one hazard at a time), urban anti-disaster capability assessment, and relative composite risk index measurement. In our case study of Xiamen, China, to check the feasibility of our UMRAF, we examined local multi-hazards risk distribution and urban anti-disaster capacity layout. We then expanded and visualised the spatial distribution of the relative composite risk index of each evaluation unit across the city via our analyst tool, thereby helping to tailor measures that can reduce risk at a local level.

Construction Risk Assessment of Yellow River Bridges Based on Combined Empowerment Method and Two-Dimensional Cloud Model

(1) In recent years, the economy of the Yellow River basin in China has developed rapidly, and a series of large bridges across the Yellow River have been built on both sides of the Yellow River, which has brought great convenience to regional socio-economic activities. However, risk events are prone to occur during the construction of bridges across the Yellow River, which affect the safety of the bridges’ structure. Therefore, it is necessary to establish a new scientific risk assessment system for the construction safety of bridges across the Yellow River. (2) Methods: Firstly, based on the construction safety risk assessment index system of bridges across the Yellow River, the cloud AHP method and the cloud entropy weight method are used to determine the subjective weight and objective weight of risk indexes, and then the game theory combination weighting method is used to determine the comprehensive weight of each risk index, and then the digital characteristic values of the risk probability cloud and the consequence cloud are calculated and input into the forward cloud generator algorithm. MATLAB was used to generate a two-dimensional comprehensive cloud map, which was visually compared with the standard cloud map, and the probability level and consequence level of each risk index were preliminarily obtained. Finally, the risk assessment matrix was used for comprehensive risk evaluation. (3) Results: Applying the method to the construction safety risk assessment of the Jiaoping Expressway, the overall construction safety risk level of the Yellow River bridge was determined as level 4, and the risk levels of the four primary indicators were: personnel risk (level 3), material and equipment risk (level 4), construction technology risk (level 5), and construction environment risk (level 4). (4) Conclusions: The results of the risk evaluation are consistent with the actual construction state of the bridge, which shows that game theory’s combination of empowerment with a two-dimensional cloud model is scientific and effective when applied to the construction safety risk evaluation of Yellow River bridges.

Asphaltene Flow Assurance Risk Evaluation Case Study to Establish Guidelines for CCUS in Arabian Gulf Carbonate Oil Field

Summary In this paper, we present a case study for a comprehensive series of asphaltene flow assurance risk evaluations in the Arabian Gulf Carbonate Oil Field, where CO2 enhanced oil recovery (EOR) is recognized as one of the highest potential technologies for full-field implementation. At first, the sampling location was carefully selected considering the target reservoir’s features because the reliability of asphaltene studies highly depends on sample representativeness. After the quality assurance and quality control of collected samples, asphaltene onset pressures (AOPs) were measured at multiple temperatures under CO2 mixing conditions. The experimental design was optimized in terms of not only improving evaluation accuracy but also minimizing the experimental/sampling cost. The AOP measurements showed clear potential risks associated with CO2 injection. Subsequently, the numerical model analysis was conducted with the cubic-plus-association equation of state model to identify the risk area during CO2 injection. The analysis suggested that risk area is applicable to not only near-wellbore region at the sampling location but also tubing section/surface facility. Furthermore, risk level can be higher at the deeper location of the target reservoir. Finally, CO2-induced asphaltene formation damage risk was investigated from the viewpoints of precipitated asphaltene particle size and pore throat size in the porous media. As a result, the clogging risks from CO2-induced asphaltene were estimated to be high in the target reservoir. By virtue of the comprehensive risk evaluation, the asphaltene flow assurance risk associated with CO2 injection was identified field-wide. The findings from the evaluation encouraged us to move on to future actions, such as more detailed formation damage risk evaluation and mitigation plan development. The extended asphaltene risk evaluation covering the precipitation to deposition phenomena and the reverse engineering for sampling operations based on the experimental design made a worthy demonstration to reduce unnecessary cost and time while obtaining the key information to drive the project. The procedure in this work can contribute to establishing a subsurface part of a guideline for carbon capture, utilization, and storage (CCUS) from the viewpoint of asphaltene flow assurance risk evaluation.

Ambulatory blood pressure monitoring in pediatric patients with sickle cell anemia.

Sickle cell anemia (SCA) is a hemoglobinopathy presenting severe endothelial damage associated with increased prevalence of hypertension (HTN). Few studies have used ambulatory blood pressure monitoring (ABPM) in pediatric patients with SCA. The aim of this study was to characterize the ABPM profile in children with SCA. A retrospective cross-sectional study was conducted on all subjects <18 years of age with SCA who presented at a medical reference center in the city of Cartagena, Colombia. Anthropometric, clinical laboratory, treatment, and ABPM parameters, including ambulatory arterial stiffness index (AASI) were registered. The study included 79 patients, of these, 23 (29%) children had normal BP, 49 (62%) had abnormal BP and 7 (9%) had HTN. Mean age was 10.5 ± 3.6 years and 44 (56%) cases were male. Forty-eight (60%) patients had pre-HTN. Masked HTN was present in 6 (8%) patients. One (1%) had ambulatory HTN, and another one (1%) had white coat HTN. The HTA group exhibited significantly higher systolic BP and diastolic BP compared to the other groups in 24-hour BP readings, daytime BP, and night-time BP ABPM parameters ( P < 0.05), except for daytime DBP ( P = 0.08). Mean AASI was 0.4 ± 0.2. The HTN group had the highest AASI value compared to the other groups ( P = 0.006). Significant alterations in ABPM parameters are frequently observed in pediatric patients with SCA. The incorporation of ABPM, along with the assessment of AASI, is recommended for a comprehensive evaluation of cardiovascular and renal risk in SCA patients.

Moving Toward Partial Discharge-Free Design of Electrical Machines for More Electric Aircraft Applications

For aerospace electrical machines (EMs), the partial discharge (PD) risk is becoming much more severe due to higher DC link voltage levels and faster switching devices. Traditionally, EMs for safety-critical applications mainly rely on over-engineering methods to guarantee reliability. However, a recent shift towards reliability-oriented design, which is based on understanding the physics of failure, allows for meeting the reliability requirements while ensuring performance. From the perspective of the reliability-oriented methodology, the PD-free design of a starter/generator (S/G) with a 540V DC bus is presented and the main steps for a comprehensive PD risk evaluation are discussed. First, the PD inception mechanism is experimentally investigated under pulse voltage excitation for several rise times, temperatures, and pressure values. Then the measured partial discharge inception voltage (PDIV) values are used to perform an accurate PD risk assessment, which includes the winding hotspot temperature resulting from the S/G mission profile, the environment operating conditions, and the connection cable length. Finally, the PD risk of a S/G with a higher DC bus (i.e., 800V) is examined to comply with the future aircraft voltage level.

Impacts of autochthonous dissolved organic matter on the accumulation of methylmercury by phytoplankton and zooplankton in a eutrophic coastal ecosystem

The bioaccumulation of methylmercury (MeHg) within the pelagic food webs is a crucial determinant of the MeHg concentration in the organisms at higher trophic levels. Dissolved organic matter (DOM) is recognized for its influence on mercury (Hg) cycling in the aquatic environment because of its role in providing metabolic substrate for heterotrophic organism and serving as a strong ligand for MeHg. However, the impact of DOM on MeHg bioaccumulation in pelagic food chains remain controversial. Here, we explored MeHg bioaccumulation within a pelagic food web in China, in the eutrophic Bohai Sea and adjacent seas, covering a range of DOM concentrations and compositions. Our findings show that elevated concentrations of dissolved organic carbon (DOC) and phytoplankton biomass may contribute to a reduction in MeHg uptake by phytoplankton. Moreover, we observe that a higher level of autochthonous DOM in the water may result in more significant MeHg biomagnification in zooplankton. This can be explained by alterations in the structure of pelagic food webs and/or an increase in the direct consumption of DOM and particulate organic matter (POM) containing MeHg. Our study offers direct field monitoring evidence of dual roles played by DOM in regulating MeHg transfers from water to phytoplankton and zooplankton in coastal pelagic food webs. A thorough understanding of the intricate interactions is essential for a more comprehensive evaluation of ecological risks associated with MeHg exposure in coastal ecosystems.

Grey Fuzzy Comprehensive Evaluation of Bridge Risk during Periods of Operation Based on a Combination Weighting Method

Bridge safety during operating periods is a primary concern worldwide, and the evaluation of bridge risks is a critical aspect of ensuring bridge safety. The most common methods used for bridge risk evaluations include fuzzy comprehensive evaluations, grey system theory, fault tree analysis, the Kent index method, and data envelopment analysis. However, these approaches are highly subjective and have uneven distributions when determining the weights of risk indicators. To improve the accuracy and feasibility of bridge risk evaluations for a given period of operation, we first establish bridge risk indicators and assign subjective weights to each indicator based on an analytic hierarchy process. Additionally, objective weights are assigned to each indicator according to an entropy weighting method. Then, the combined weights of each risk indicator are obtained by applying game theory principles. This enables the construction of a degree of membership matrix comprising these risk indicators, which is established according to an expert grading method and grey fuzzy theory. Finally, the evaluation results vector is calculated, allowing the risk level of a bridge to be assessed according to the principle of the maximum degree of membership. Overall, this study provides a more accurate and objective method for evaluating bridge risk during a given period of operation.

Fiscal Risk Management of Public–Private Partnership Projects: A Multidimensional Identification and Assessment Framework

In public–private partnership (PPP) projects, governments often need to provide guarantees to investors because of the risks created by the large scale of the investments and the long tenures of the projects. Yet, research on the assessment of fiscal risk in PPP projects remains scarce. Based on the theory of project life-cycle management, this study constructed a multidimensional identification and assessment framework for PPP fiscal risk. A fiscal risk matrix model was developed, and feasibility, standardization, and sustainability were identified. These were categorized into three dimensions of PPP fiscal risk, and their indicators’ hierarchical levels were evaluated and ranked. A risk model, called the fuzzy evaluation model of PPP fiscal risk, which shows the value of the comprehensive evaluation of PPP fiscal risk based on a fuzzy analytic hierarchy process (FAHP) approach, is proposed. The results demonstrate the significance of this valuation for both governments and investors, providing a clear reference when they face pressure from the fiscal risks of PPP projects.

Fuzzy Comprehensive Evaluation Model of Project Investment Risk Based on Computer Vision Technology

With the development of the economy and real-time embedded systems and the progress of science and technology, people’s economic income forms have undergone tremendous changes, and the concept of financial management has become clearer in people’s property income arrangements. Project investment is one of the most popular financial management methods in the era of big data. Both large enterprise groups and individual petty bourgeoisie groups have begun to pay attention to the risks and benefits brought by the new financial management method of project investment. This paper’s goal is to develop a fuzzy comprehensive evaluation (FCE) model for project investment risk based on computer vision technology and explore the application of computer vision technology in project investment risk evaluation. This article first uses a real-time embedded system to understand the basic process of project investment and select 10 investment experts for risk assessment, risks, and causes of the risks through literature research and case analysis. Then, this paper establishes a model of fuzzy comprehensive evaluation of project investment risk through computer vision technology, real-time embedded systems, and neural network models in big data and artificial intelligence technology to realize the analysis and prediction of project investment risk. The fuzzy comprehensive evaluation method and analytic hierarchy process (AHP) are used in this evaluation model to evaluate and forecast project investment risks. In addition, this paper also trains and tests the risk evaluation model of this research through the support vector machine classification algorithm, the real-time embedded system, and the average random consistency index. The research shows that the fuzzy comprehensive evaluation model of this study has higher accuracy for project investment risk evaluation than other risk evaluation methods. For example, for the investment risk of chemical fiber projects, this research model evaluated the factors such as organization, management, technology, and economy and found that the risks were all higher than 21.36%, which concluded that the overall investment risk of chemical fiber projects was relatively high.

Comprehensive evaluation of perchlorate dietary exposure and health risks for Chinese adult males and breastfed infants

Perchlorate is an environmental contaminant that has both natural and anthropogenic sources. Widespread contamination of various foods with perchlorate can be caused by water, soil, and fertilizer. Because of concerns about the health effects of perchlorate, attention has focused on its occurrence in food and potential human exposure. In this study, the dietary exposures of Chinese adult males and breastfed infants to perchlorate were evaluated using data from the sixth China Total Diet Study and the third National Breast Milk Monitoring Program conducted between 2016 and 2019. In the sixth China Total Diet Study, perchlorate was detected in 94.8 % of composite dietary samples (n = 288) from 24 provinces in China, while for the third National Breast Milk Monitoring, perchlorate was found in 100 % of pooled breast milk samples (n = 100) collected from 100 cities/counties in China. Vegetables were found to be the main source of dietary exposure for Chinese adult males. Furthermore, the concentrations in breast milk between urban (n = 34, mean: 38.6 μg/L) and rural (n = 66, mean: 59.0 μg/L) regions from 100 cities/counties in China were not significantly different. On average, the estimated daily intake of Chinese adult males (18–45 years) to perchlorate was 0.449 μg/kg bw/day, while that for breastfed infants (0–24 months) was 3.21–5.43 μg/kg bw/day. The exposure to perchlorate in breastfed infants was almost 10-fold greater than that of Chinese adult males.

Optimize and analysis of drilling PMSM using hybrid technique based on BN, FFT, FCE, and FMA for risk assessment

A failure risk assessment must be carried out and potential drilling equipment failure risks must be promptly addressed in order to prevent drilling fluid pollution during offshore oil drilling. The qualitative, comprehensive, and quantitative failure risks for Drilling Permanent Magnetic Synchronous Motors (DPMSM) are examined in this article using a hybrid methodology. First, the Drilling PMSM using Failure Mode Analysis (FMA) method is combined with the Risk Matrix (RM) approach to analyse the risk levels of risk factors individually. Next, the Borda number is introduced to compare the risk levels exactly. To execute a Fuzzy Comprehensive Evaluation (FCE) of the system failure risk, a fuzzy relation matrix of risk factors is generated, and the weight of each risk component is calculated using importance analysis. The failure rate is then determined using fuzzy inference, and the Fault Tree (FT) is then built based on the risk variables. Fault tree analysis is used to compute the system failure rate, and the significance of the bottom event is evaluated. The Bayesian network (BN) is used to depict the Fuzzy Fault Tree (FFT) analysis. By utilizing Bayesian forward causal inference and reverse diagnostic inference to calculate the leaf node failure rate and root node posterior probability, the system’s weak points and potential failure causes are determined.

Comprehensive Evaluation of Occupational Accidents in a Hospital Setting: Insights from L-Type Matrix and Fine-Kinney Risk Assessment Methods

Objective: The objective of this study was to comprehensively evaluate occupational accidents in a hospital setting using the L-Type matrix and Fine-Kinney risk assessment methods. The aim was to assess the frequency, severity, and associated risks of different types of accidents. Methods: This single-center observational study analyzed occupational injuries that occurred to hospital employees between January 2018 and December 2022 in Arnavutköy State Hospital. Data were obtained from hospital records using a hospital information management system. Demographic characteristics, accident types, previous accident history, incapacity reports, L-Type matrix scores, and Fine-Kinney method scores were recorded. Risk scores were categorized based on predefined criteria. Results: The study included 249 occupational accidents, with a mean age of 30.94±9.69 years. Needle stick injuries in the hand were the most common type of accident (72.7%), followed by falls and bumps (16.1%). The L-Type matrix assessment showed that 90% of accidents were mild, and none were severe. According to the Fine-Kinney method, 0.8% of accidents were in the very high-risk group. Multiple accidents were observed among 23.7% of employees, and 11.6% resulted in work disability reports. Conclusion: Occupational accidents pose a significant risk to the safety and well-being of healthcare workers in hospitals. Needle stick injuries and falls or collisions were the most prevalent accidents. The use of risk assessment methods such as the L-Type matrix and Fine-Kinney approach allows for a comprehensive evaluation of occupational risks.

Comprehensive Battery Safety Risk Evaluation: Aged Cells versus Fresh Cells Upon Mechanical Abusive Loadings

AbstractDespite their wide applications, lithium‐ion batteries (LIBs) have been struggling with their safety risks arising from different lifetime stages. Here, the NCMA pouch cell is taken as an example, and the safety of both fresh and aged cells from three milestone stages, that is, internal short circuit (ISC) triggering risk, ISC mode, and the subsequent thermal runaway (TR) consequence is investigated. By combining mechanical abusive testing and physics‐based models on commercialized cells with various states‐of‐health (SOH) and states‐of‐charge, it is discovered that the ISC triggering delays with the decay of SOH and soft ISC mode will be triggered more frequently, which is mainly due to the mechanical behaviors of the current collectors. The temperature rises and peak temperature during the subsequent TR also become milder for aged cells due to the reduced capacity and deterministic soft ISC process. Results here provide a mechanistic explanation of the safety risk comparison between the fresh and aged cells, offering cornerstone guidance to the evaluation and design of next‐generation safer LIBs.

Risk of second primary cancer among women in the Kaiser Permanente Breast Cancer Survivors Cohort

BackgroundBreast cancer survivors are living longer due to early detection and advances in treatment and are at increased risk for second primary cancers. Comprehensive evaluation of second cancer risk among patients treated in recent decades is lacking.MethodsWe identified 16,004 females diagnosed with a first primary stage I-III breast cancer between 1990 and 2016 (followed through 2017) and survived ≥ 1 year at Kaiser Permanente (KP) Colorado, Northwest, and Washington. Second cancer was defined as an invasive primary cancer diagnosed ≥ 12 months after the first primary breast cancer. Second cancer risk was evaluated for all cancers (excluding ipsilateral breast cancer) using standardized incidence ratios (SIRs), and a competing risk approach for cumulative incidence and hazard ratios (HRs) adjusted for KP center, treatment, age, and year of first cancer diagnosis.ResultsOver a median follow-up of 6.2 years, 1,562 women developed second cancer. Breast cancer survivors had a 70% higher risk of any cancer (95%CI = 1.62–1.79) and 45% higher risk of non-breast cancer (95%CI = 1.37–1.54) compared with the general population. SIRs were highest for malignancies of the peritoneum (SIR = 3.44, 95%CI = 1.65–6.33), soft tissue (SIR = 3.32, 95%CI = 2.51–4.30), contralateral breast (SIR = 3.10, 95%CI = 2.82–3.40), and acute myeloid leukemia (SIR = 2.11, 95%CI = 1.18–3.48)/myelodysplastic syndrome (SIR = 3.25, 95%CI = 1.89–5.20). Women also had elevated risks for oral, colon, pancreas, lung, and uterine corpus cancer, melanoma, and non-Hodgkin lymphoma (SIR range = 1.31–1.97). Radiotherapy was associated with increased risk for all second cancers (HR = 1.13, 95%CI = 1.01–1.25) and soft tissue sarcoma (HR = 2.36, 95%CI = 1.17–4.78), chemotherapy with decreased risk for all second cancers (HR = 0.87, 95%CI = 0.78–0.98) and increased myelodysplastic syndrome risk (HR = 3.01, 95%CI = 1.01–8.94), and endocrine therapy with lower contralateral breast cancer risk (HR = 0.48, 95%CI = 0.38–0.60). Approximately 1 in 9 women who survived ≥ 1 year developed second cancer, 1 in 13 developed second non-breast cancer, and 1 in 30 developed contralateral breast cancer by 10 years. Trends in cumulative incidence declined for contralateral breast cancer but not for second non-breast cancers.ConclusionsElevated risks of second cancer among breast cancer survivors treated in recent decades suggests that heightened surveillance is warranted and continued efforts to reduce second cancers are needed.

Multidecadal heavy metals and microplastic deposition records in an urban lake: the ecological risk assessments and influencing factors.

With the development of urbanization and economic growth, the urban lake ecosystem faces many challenges derived from external factors. As pollutants in the aquatic environment, heavy metals and microplastics negatively influence the urban lake ecosystem due to their intrinsic properties. To understand the distribution patterns and multidecadal deposition characteristics of heavy metals and microplastics, six sediment cores were collected in March 2021 from a Chinese urban lake, Xinghu Lake, and the isotopic composition of cesium-137 and lead-210 was analyzed for the chronology of the sediment core. Here, the classifications of comprehensive ecological risk evaluation methods for heavy metals and microplastics were adjusted further. Meanwhile, the correlations among heavy metals, microplastics, sediment grains, and natural and social factors were further analyzed. The results showed that the sediments of Xinghu Lake were mainly fine silt (39%), and the average surface area of sediment was 1.82 ± 0.60 m2/g. The average concentrations of cadmium, chromium, copper, nickel, lead, vanadium, and zinc were 0.268 ± 0.077, 59.91 ± 16.98, 23.29 ± 6.48, 52.16 ± 13.11, 36.83 ± 11.78, 119.57 ± 26.91, and 88.44 ± 29.68mg/kg, respectively. The average comprehensive potential ecological risk indexes of heavy metals and microplastics in sediment cores were 46.59 ± 9.98 and 105.78 ± 23.32 in Xinghu Lake, and their risks were projected to reach high and very high levels by 2030 and 2050. The annual average temperature was the key natural factor for the abundances of heavy metals and microplastics, and the small sediment grain had a significant correlation with these. Agricultural activities were major pollution sources of heavy metals and microplastics, while the chemical fibers and plastic products were closely related to the abundance of microplastics.

A Potential Risk Comprehensive Evaluation Model of Probiotic Species Based on Complete Genome Sequences

A Potential Risk Comprehensive Evaluation Model of Probiotic Species Based on Complete Genome Sequences

Construction and empirical testing of comprehensive risk evaluation methods from a multi-dimensional risk matrix perspective: taking specific types of natural disasters risk in China as an example

Global climate change, continuous economic development and accelerated urbanisation have increased the frequency and complexity of various incidents. Risk assessment is an important means to deal with different crises and incidents. Based on the systematic analysis of the basic connotation, attribute relationship and main contents of risk assessment, this study extends the traditional two-dimensional risk matrix to multi-dimensional risk matrix. On this basis, this study further proposes four comprehensive risk assessment methods, including total ordinal, weighted average, Euclidean distance and two-norm methods. Empirical research was conducted by selecting three types of natural disasters, regional agro-meteorological disasters, geological disasters and forest fires, in 30 related regions in China between 2010 and 2019. The results indicated that compared to the two-dimensional risk matrix, the multi-dimensional risk matrix can intuitively characterise and compare the all-round risk situation of different regions, periods, types and dimensions, which is more helpful for a systematic analysis and risk comparison. All four evaluation methods proposed in this paper proved able to effectively conduct comprehensive regional risk evaluations with consistent results. However, when considering the fitting coefficient between the results obtained by various evaluation methods and the comprehensive evaluation results, it can be found that the accuracy (i.e. fitting coefficient) of Euclidean distance method is significantly higher than that of the other three methods. In the last 10 years, the temporal order of natural disaster risk in China has been more volatile, with Beijing, Shanxi, Tianjin, Hebei, Liaoning, Ningxia, Zhejiang, Shaanxi, Fujian and Gansu experiencing higher volatility in the ranking of natural disaster risk.

GIS-based fuzzy comprehensive evaluation of urban flooding risk with socioeconomic index system development.

Due to the climate change-induced extreme rainfall, urban flooding risk is one of the major concerning risks in the near future with accelerating occurrence frequency and intensity. To systematically evaluate the socioeconomic impacts induced by urban flooding, this paper proposed a GIS-based spatial fuzzy comprehensive evaluation (FCE) framework for local government to efficiently take contingency measures especially under urgent rescue conditions. The risk-assessing procedure could be investigated in 4 aspects: 1) application of the hydrodynamic model to simulate the depth and extent of inundation; 2) quantification of the impact of flooding with 6 methodically picked evaluation indexes concerning the transportation attenuation, residential security, and tangible and intangible monetary losses according to depth-damage functions; 3) implementing FCE method: comprehensive evaluation of urban flooding risk with the diverse socioeconomic indexes by fuzzy theory; and 4) presenting the risk maps of single and multiple impact factors intuitively in ArcGIS platform. The detailed case study in SA city validates the effectiveness of the adopted multiple index evaluation framework, which could help detect higher risk areas with low transport efficiency, high economic loss, high social impact, and high intangible damage. The results of single-factor analysis can also provide feasible suggestions for decision-makers and other stakeholders. Theoretically, the proposed method tends to improve the evaluation accuracy as the inundation distribution can be simulated by hydrodynamic model rather than subjective prediction with hazard factors, while the impact quantification with flood-loss models can also directly reflect the vulnerability of involved factors instead of empirical weight analysis of traditional methods. Besides, the results illustrate that the areas with higher risk levels reasonably coincide with severe inundation situations and dense hazard-bearing bodies. This systematic evaluation framework can support applicable references for further extension to other similar cities.

Groundwater non-carcinogenic health risk comprehensive assessment based on DLAFVRT model in an island city

The long-term leakage of surface contaminants can severely affect the quality of shallow groundwater, thereby significantly affecting human health. This paper analyzed the spatial variations in groundwater non-carcinogenic health risk on the west coast of the Wailingding Island. A novel method for groundwater health risk assessment combining Modflow, remote sensing, and geographic information system (GIS) data was proposed. The DLAFVRT model, which included seven indicators: Groundwater depth (D), Land-use type (L), Aquifer medium (A), Fracture (F), Vegetation coverage (V), Net recharge (R) and Terrain slope (T), and potential non-carcinogenic health risk were based on the groundwater flow field and pollutant transport model constructed by Modflow and MT3DMS. The analytic hierarchy process was used to determine the weight of each index and optimize the model. Finally, the two evaluation results were superimposed to obtain a comprehensive evaluation of the groundwater health risk. The health risk zoning map showed that in the study area, the heavy-risk area accounted for 16.83%, high-risk area accounted for 26.45%, medium-risk area accounted for 42.25%, and low-risk area accounted for 14.47%. Moreover, approximately half of the areas were rated as high-risk or above, indicating that groundwater is susceptible to surface pollutants. Based on the groundwater numerical simulations, the multi-index groundwater health risk comprehensive evaluation system developed by combining groundwater vulnerability and human health risk provides a theoretical reference basis for the scientific management and rational allocation of groundwater resources.