Probabilistic Risk Assessment Research Articles

Applicability of 'Toolkit for Safety Assessment' tool to interventional radiology using probabilistic risk assessment techniques.

Interventional radiology brings extensive benefits to patients. Nevertheless, certain procedures may result in high doses of radiation, leading to health risks to occupationally exposed individuals (OEIs). Therefore, a more comprehensive risk analysis is essential to ensuring safety and minimising radiation exposures for all OEIs. The Toolkit for Safety Assessment (TOKSA) tool performs risk assessments based on the concepts described in 'General Safety Requirements' Part 3 (Radiation Protection and Safety of Radiation Sources: International Basic Safety Standards) and Part 4 (Safety Assessment for Facilities and Activities). This tool was developed based on the 'Ibero-American Forum of Radiological and Nuclear Regulatory Agencies' risk models and can promote the use of the risk assessment processes by OEIs. The aim of this study was to experimentally analyse the applicability of the TOKSA tool in interventional radiology with the use/support of probabilistic risk assessment techniques. The results were used to reduce the risks associated with a hemodynamics room in a hospital in Belo Horizonte, Brazil.

Risk probability assessment of winter wheat net primary productivity loss and its driving factors in North China Plain

Risk probability assessment of winter wheat net primary productivity loss and its driving factors in North China Plain

Mitigation of pesticide residue levels in the exposed dermal regions of occupationally exposed farmworkers by use of personal protective equipment.

Unsafe pesticide handling practices with the limited use of personal protective equipment (PPE) by the Indian farming groups lead to an increased risk of exposure to pesticides. Therefore, a community-based follow-up study based on dosimeters, wipes, and hand-wash technique was carried out to evaluate the dermal exposure to pesticides and to analyze the impact of the usage of PPE on minimizing the exposure among the farmworkers of Rangareddy district, Telangana, India. Risk in terms of hazard quotient (HQ), hazard index (HI), and safety analysis as margins of safety was assessed. Farmworkers averaged 18 years of farming experience and showed resistance to adopting good agricultural practices. Ten pesticide residues were detected in concentrations ranging from 0.000 to 246 mg ml-1 in hand-wash, 0.000 to 198.33 ng cm-2 in patch dosimeter, and 0.000 to 1,740 ng cm-2 in wipe samples collected from farmworkers not using PPE. The second phase includes the intervention study results that revealed a significant reduction both in the concentrations and the number of pesticide residues detected in the hand-wash, patch, and wipe samples of the farmworkers who have used the PPE provided to them (p < 0.01). Furthermore, the probabilistic health risk assessment in terms of the HQ values ranged from 0.02 to 1029.82, and HI was >1, suggesting the non-carcinogenic risks associated with dermal exposure to pesticides among them. Additionally, the safety risk assessment in terms of the margin of safety suggests that they follow risky handling practices. The study confirms that farmworkers are exposed to pesticides and emphasizes the significance of using PPE in reducing the risk.

Modeling, quality assessment, and Sobol sensitivity of water resources and distribution system in Shiraz: A probabilistic human health risk assessment

Given water's vital role in supporting life and ecosystems, global climate change and human activities have significantly diminished its availability and quality. This study explores the health risks of drinking water consumption in the shiraz county water resources and distribution system. The result showed that the water was slightly alkaline. However, the average pH values during the study were within the permissible range. The area's abundance of total hardness and calcium was due to the high concentration of minerals in rocks and soils. The nitrate and fluoride concentrations in drinking groundwater varied from 0.02 to 116.70 mg/L and 0.10–1.85 mg/L, respectively. Although the water quality index indicated that 52.63, 45.03, and 20.3 percent of samples were of excellent, good, and poor quality in 2020, those percentages obtained 46.05, 52.09, and 14.0 percent in 2021. The regression values of training, testing, validation, and the proposed artificial neural network model were 0.93, 0.92, 0.85, and 0.92. The maximum levels of hazard quotient of nitrate and fluoride (except for adults) were higher than 1 in all age groups, indicating a high non-carcinogenic risk by exposure to nitrate. Furthermore, according to the Monte Carlo simulation, the 95th percentile hazard index in all groups was more than 1. Children and infants were more inclined towards risk than teens and adults based on the intake of nitrate and fluoride from drinking water. The Sobol sensitivity reflected that the nitrate concentration and ingestion rate are vital parameters that influence the outcome of the oral exposure model for all age groups. The interaction of ingestion rate with a concentration of nitrate and fluoride is an important parameter affecting the health risk assessment. In conclusion, these findings suggest that precise measures can reduce health risks and guarantee safe drinking water for residents of Shiraz County.

Probabilistic Safety Assessment of Gas Plant Using Fault Tree-based Bayesian Network

Probabilistic Safety Assessment of Gas Plant Using Fault Tree-based Bayesian Network

Comprehensive Investigation of Fluoroquinolone Residues in Apis mellifera and Apis cerana Honey and Potential Risks to Consumers: A Five-Year Study (2014-2018) in Zhejiang Province, China.

As a group of antibiotics largely used in China's animal husbandry, fluoroquinolone (FQ) residues in honey may pose potential threats to human health. This study performed a five-year investigation on the occurrence of FQ residues in honey in 521 Apis mellifera and 160 Apis cerana honey samples collected from Zhejiang Province, China and compared FQ residue profiles in honey with a subgroup of various factors. Deterministic and probabilistic risk assessments of exposure to FQ residues in honey were further conducted. Overall, four FQs were detected in 6.9% (47/681) of analyzed samples; banned norfloxacin with the highest level (7890 μg·kg-1) and detection frequency (4.9%) was the primary safety risk factor associated with honeybees raised in China. FQ detection frequency and concentration of rape honey was highest among four of the largest and most stable honeys (rape, acacia, chaste, and linden) in China. Processed honey from commercial sale channels had a significantly higher detection frequency of FQ residues than raw honey from apiaries. Deterministic assessment showed that the noncarcinogenic hazard quotient (HQ) value of the dietary intake of FQs by the local population was between 4.75 × 10-6 and 1.18 × 10-3, less than 1.0, indicating that FQ residues in honey posed a low risk for consumers. The order of the HQ value was ciprofloxacin > norfloxacin > enrofloxacin > ofloxacin. Probabilistic assessment showed that at P95, the HQ of FQs for the age groups of children, adolescents, adults, and older adults over 65 years ranged from 2.39 × 10-5 to 0.217, less than 1, and the exposure risk for adults was higher than for children and adolescents. Sensitivity analysis showed that FQ concentrations were the major contributors to health risks. Although a low risk was found, a strict hive management is needed for beekeepers regarding troubles of food safety, international trade, and human bacterial resistance.

Mitigating casualty risks from primary fragmentation hazards

Primary fragmentation from detonation of high-explosive metal-cased munitions imposes significant risks to the safety of related personnel and the public. Barricades or other protective structures are commonly used to stop fragments and reduce casualty risks caused by detonated munitions when a sufficient safety distance cannot be guaranteed. This study aims to provide decision support for the positioning of barricades that can reasonably mitigate primary fragmentation hazards from the detonation of large calibre munitions using a probabilistic risk assessment approach. This approach enables a stochastic characterization of fragment ejections, stacking effects, fragment trajectories, human vulnerability and fragment hazard reduction by barricade. In a case study, the assessments of casualty risks and effectiveness of barricades were conducted for a single and a pallet of 155 mm projectiles. It was found that barricades with heights exceeding the height of munitions can significantly reduce the hazardous fragment densities and casualty risks beyond the barricade. The benefit of increasing the barricade height becomes marginal when it exceeds the height of munitions.

A Quantitative Rockfall Risk Analysis System for Highway Rock Slopes

A Quantitative Rockfall Risk Analysis System for Highway Rock Slopes

A Hybrid Probabilistic Risk Analytical Approach to Ship Pilotage Risk Resonance with FRAM

Collision risk in ship pilotage process has complex characteristics that are dynamic, uncertain, and emergent. To reveal collision risk resonance during ship pilotage process, a hybrid probabilistic risk analysis approach is proposed, which integrates the Functional Resonance Analysis Method (FRAM), Dempster–Shafer (D–S) evidence theory, and Monte Carlo (MC) simulation. First, FRAM is used to qualitatively describe the coupling relationship and operation mechanism among the functions of the pilotage operation system. Then, the D–S evidence theory is used to determine the probability distribution of the function output in the specified pilotage scenario after quantitatively expressing the function variability, coupling effect, and the influence of operation conditions through rating scales. Finally, MC simulation is used to calculate the aggregated coupling variability between functions, and the critical couplings and risk resonance paths under different scenarios are identified by setting the threshold and confidence level. The results show that ship collision risk transmission is caused by function resonance in the pilotage system, and the function resonance paths vary with pilotage scenarios. The critical coupling ‘F2-F7(I)’ emerges as a consistent factor in both scenarios, emphasizing the significance of maintaining a proper lookout. The hybrid probabilistic risk analytical approach to ship pilotage risk resonance with FRAM can be a useful method for analysing the causative mechanism of ship operational risk.

Probabilistic double hierarchy linguistic risk analysis based on failure mode and effects analysis and S-ARAS method

Failure mode and effects analysis (FMEA) is regarded as useful and efficient tool in identifying and eliminating system failures and important means in safety and reliability analysis. It is widely utilized in diverse areas for improving and enhancing the performance of systems. However, in the procedure of risk assessment, traditional FMEA method usually ignores the influence of weights. Simultaneously, when represent risk assessment information, fuzzy and complex information cannot be represented accurately. Besides, psychological behaviors of decision-makers cannot be considered. Thus, this paper aims to present a new method based on FMEA and S-additive ratio assessment (S-ARAS) method to address the marine risk assessment problems under probabilistic double hierarchy linguistic (PDHL) environment. Firstly, the probabilistic double hierarchy linguistic term sets (PDHLTSs) are utilized to express the evaluation information of failure modes. The expert evaluation information of failure modes and subjective weight is also assessed by using PDHLTSs. The PDHLTSs can describe the information more reasonably and precisely. Secondly, FMEA method is used to evaluate these alternatives from three aspects of Severity (S), Occurrence (O) and Detection (D). Then, the bounded rationality of decision-makers (DMs) is considered. So, the prospect theory and ARAS method is combined to evaluate the risk problems. Meanwhile, comprehensive weight determination method is established based on the social network analysis (SNA) and The Integrated Determination of Objective CRIteria Weights (IDOCRIW) method under PDHL environment. The integrated method is more flexible in determining the importance of failure modes and avoids the randomness of subjective evaluation. Finally, the newly proposed method is applied to address the marine risk assessment problem. Sensitivity analysis of parameter and weight methods is carried out. Furthermore, comparison analysis is given to illustrate the superiority of the presented method.

Organotins in fish, shrimp, and cephalopods from the Pearl River Estuary, China: Dietary exposure risk to Indo-Pacific humpback dolphin and human

Food has regularly been proven to be a key source of exposure to environmental pollutants, drawing attention to the dietary exposure risks of contaminants to mammals with significant daily food intake. Here, the levels of six organotin compounds (OTs) in 18 fish (n = 310), three cephalopods (n = 50), and one shrimp (n = 34) from the Lingdingyang (LDY) and west four region (WFR) of the Pearl River Estuary (PRE) and their dietary exposure risks to Indo-Pacific humpback dolphins and humans were first investigated. Total OT levels ranged from 3.84 to 901. 48 ng/g wet weight (ww) in 22 prey species from the LDY, and from 14.37 to 1364.64 ng/g ww in 19 species from the WFR. The LDY marine species generally accumulated higher butyltin levels but lower phentyltin levels than those in the WFR. All species have a phenyltin degradation index <1 and over 60 % of the sampled species have a butyltin degradation index <1, suggesting the PRE marine species might be exposed to the fresh discharge of OTs. A total of nine marine species exceeded the threshold levels of OT intake for adverse health effects on human juveniles by consumption, all 22 marine species posed high dietary risks to the PRE humpback dolphins. Moreover, probabilistic risk assessment using Monte Carlo simulation revealed that the probabilities of RQ values associated with WFR OT exposure higher than 1 were 18.87 % for human adults, 40.55 % for human juveniles, 100 % for both humpback dolphin adults and humpback dolphin juveniles. Our results highlighted the potentially high dietary exposure risks of OTs to marine mammals and residents in the PRE.

Pollution characteristics and probabilistic human health risks of thallium and other heavy metals in soils from a typical copper mining city in the Yangtze river Delta, eastern China

ABSTRACT Heavy metals contamination in soil from copper mine areas is a serious and widespread problem in China. In this study, the content of Tl, Hg, Cu, Cd, Ni, Pb and As and probabilistic human health risks were investigated in a typical copper mining city. Copper showed the highest average content of 184.29 mg/kg, followed by Pb, As, Ni, Tl, Cd and Hg. Approximately 54.2% of study sites were moderately contaminated by Cu, Cd, As and Tl. Among the heavy metals, Hg, Cu and Cd showed relatively high mobility and medium risk in the environment based on the chemical speciation. In particular, Tl was mainly present as Tl(I) in soil with more biovailability and solubility. Moreover, the probabilistic human health risk assessment using Monte-Carlo approach revealed that heavy metals in soil can cause non-carcinogenic risks (adults: 0.03%, children: 48.45%) and carcinogenic risks (adults: 41.79%; children 61.98%). The soil oral ingestion is the main exposure pathway for human exposed to heavy metals. Our findings indicate that the copper mining activities can cause high level of heavy metals in soils, and corresponding health risks. Meanwhile, these results could provide important information and theoretical support the development of precise soil pollution management strategies in copper mining areas.

Theoretical investigation of nonergodic solute dispersion in natural porous formations characterized by persistent and antipersistent power-law log-conductivity correlations

Tracer dispersion within log-conductivity fields represented by power-law semivariograms is investigated by an analytical first-order Lagrangian approach that, in treating subsurface flow and transport, resorts to the superposition principle of an infinite double hierarchy of mutually independent scales of heterogeneity. The results of the investigation, which are corroborated by a preliminary field validation, and also interpreted in terms of probabilistic risk analysis, say that transport anomaly is intrinsically associated with evolving-scale heterogeneous porous formations, regardless of their semivariogram scaling exponent b. In contrast with what was found by previous studies that dealt with this subject in a Lagrangian framework, it is demonstrated that: (1) the magnitude of nonergodic dispersion is nonmonotonically related to b; (2) consistently assuming a characteristic advective-heterogeneity length-scale leads to a universal (and quadratic) dependence of the dimensionless macrodispersion coefficients on the dimensionless time. Additionally, it is demonstrated that, in the presence of fractal heterogeneity, and unlike what happens for short-range correlations, diffusion acts as an antagonist mechanism in terms of Fickian dispersion achievement. Finally, the reinterpretation of antipersistent and persistent correlations as a double hierarchy of oscillatory nonperiodic and periodic fields, respectively, besides allowing for a technical explanation of all the detected trends, envisions a possible alternative methodology for their numerical generation.

Quantifying the risk of mass shootings at specific locations.

Mass shootings are horrific events that annually take scores of innocent lives in the United States. Federal, state, and local governments as well as educational, religious, and private-sector organizations propose and enact polices and strategies to protect people from and during active shooter situations. A probabilistic risk assessment of a mass shooting for a specific organization, jurisdiction, or location can be the first step toward evaluating the effectiveness of risk mitigation strategies and determining which strategies might be most appropriate for a location. This article proposes a novel hierarchical method to assess the probability of a mass shooting at specific locations based on available historical data. First, the method generates a probability distribution over the annual number of mass shootings in the United States. Second, the article uses this national number of mass shootings to determine the risk for each state. Third, the state risk assessment is decomposed to calculate the probability of a mass shooting in a specific location such as a school. Multiple ways to assess the risk are presented, leading to slightly different probability assessments for a location. Results indicate that annual probability of a mass shooting in the largest high school in California is on the order of , and the annual probability of a mass shooting in the largest high school in Iowa is about half as likely as in the Californiaschool.

Modelling potential human exposure to the urease inhibitor NBPT through the environment-food pathway

The urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) has recently attracted a lot of attention attributing to its efficiency in reducing ammonia loss from urea fertiliser applied to temperate grassland soils. Ammonia gas lost to the environment causes soil acidification, eutrophication and contributes to global warming through increased greenhouse gas emissions and ozone layer depletion. The active chemical NBPT blocks the soil microbial enzyme (urease) and reduces ammonia emission. Furthermore, NBPT’s use in agriculture might benefit farmers by reducing reliance on expensive nitrate fertiliser and aiding in a shift to more urea-based fertiliser (using NBPT co-applied with urea is more cost-effective). The present study was carried out to characterise the potential transfer of NBPT from grass to liquid milk and compute the associated human health risks. Using probabilistic risk assessment techniques, an exposure assessment model was developed to calculate the Estimated Daily Intake (EDI) of NBPT from milk, following co-application of NBPT with a urea N-fertiliser. Results show that the predicted mean concentration of NBPT in milk is 2.5 × 10−8 mg NBPT/kg milk, while the mean daily intake (EDI) of NBPT is 5 × 10−11 mg NBPT /kg BW/day). Back-calculations revealed that, under the studied conditions, for the EDI to exceed ADI of 3 × 10−2 mg NBPT/kg BW/ day, the NBPT application rate would need to exceed the NBPT fertiliser limit (0.09–0.2% by mass of urea nitrogen) set in the Commission Regulation (EC) No 1107/2008, and the bio-transfer factor would need to be over 100% (implausible). Sensitivity analysis revealed soil pH (SPH), phytoaccumulation factor (PF), NBPT permissible levels in fertiliser (NBPT%), pasture cover (P), and grazing rotation length (t) as critical factors influencing the EDI of NBPT. The present study concludes that NBPT presents negligible risk to human health under the conditions and assumptions studied.

Quantitative risk assessment of the presence of fumonisin in corn produced in different regions of Brazil: Influence of climatic conditions

In this study, the probability of occurrence of fumonisins in corn in the states of greatest production in Brazil was determined. The data were analyzed through quantitative risk analysis using the Monte Carlo simulation. The results indicated that there is a strong correlation between fumonisins contamination levels and the geographical region due to the influence of climatic characteristics, with temperature having the main influence. The Southern states presented higher risks of occurrence and concentration levels of fumonisins in corn due to the temperate climate with lower average temperature and higher relative humidity and precipitation indices. Cultivation in the best season indicates a significant reduction in the production of fumonisins when this period was evaluated, with average concentration levels up to 42% lower. The generated data are important for regulatory agencies and the agricultural sector, which needs to be aware that the chance of success in grain production depends on efficient planning of the growing season, mainly concerning the climatic conditions to which it is subject to minimize the risks.

Application of internal fire probabilistic risk assessment in design optimization for marine SMR

Abstract Small Modular Reactors (SMR) have attracted more and more attention. It can provide economic, stable and clean power for remote areas. It is also a reliable solution in satisfying the power supply of small and medium grids, as well as comprehensive energy supply including heat, electricity, water and steam, and distributed energy supply. Internal Fire Probabilistic Risk Assessment (PRA) is a system analysis method of assessing fire risk for a nuclear power plant, which plays a more and more important role. It can provide an overall understanding of the internal fire risk for SMR. Corresponding design optimization suggestions can be obtained through further analysis of the fire areas with major fire risk, which can help reduce the risk of internal fire and improve the safety of reactor. The paper introduces the basic information of marine SMR and development of internal fire PRA. Then the internal fire risk for marine SMR have been analyzed by this method. The results show that marine SMR have high safety with a Core Damage Frequency (CDF) for internal fire risk of less than 1.0 × 10−7 per year.

A hybrid HFACS model using DEMATEL-ORESTE method with linguistic Z-number for risk analysis of human error factors in the healthcare system

The human error factor is one of the leading causes of medical errors. Among risk analysis techniques for human error factors, HFACS (Human Factor Analysis and Classification System) method has been regarded as one of the most valuable approaches due to its advantage in potential failure classification. However, the conventional HFACS method is insufficient to handle the risk analysis problem for human error factors considering the interactive relationship among these factors. Moreover, the current fuzzy HFACS frameworks cannot address quantitative risk analysis issues, including imprecision and reliability of information. Thus, this paper constructs an integrated linguistic Z-number-based HFACS framework for analyzing the risk of human error factors. This framework can capture the uncertainty and reliability of the risk evaluation information and the interactive relationships among factors. First, the linguistic Z-number-DEMATEL (Decision Making Trial and Evaluation Laboratory) method is used to generate the comprehensive risk matrix of human error factors identified by the HFACS method. Then, an extended linguistic Z-number-ORESTE method based on the score function is presented to prioritize the risk of human error factors, which can show the preference, indifference, and incomparability relationship among human error factors. Finally, a case study of a healthcare system is conducted to illustrate the reliability of the proposed method. The result of this case indicates that inadequate resources are the most severe risk. Sensitivity analysis and comparative analysis indicate the necessity of considering the effect of the semantics of language terms and the interrelationships between human error factors on risk analysis results. These results show that the proposed hybrid framework is a reliable means to analyze the risk of human error factors within the HFACS method.

Quantitative microbial risk assessment of haemolytic uremic syndrome associated with Argentinean kosher beef consumption in Israel.

The aim of this study was to perform a quantitative microbial risk assessment (QMRA) of Shiga toxin-producing Escherichia coli hemolytic uremic syndrome (STEC-HUS) linked to the consumption of Kosher beef produced in Argentina and consumed in Israel in children under 14 years. A probabilistic risk assessment model was developed to characterize STEC prevalence and contamination levels in the beef supply chain (cattle primary production, cattle transport, processing and storage in the abattoir, for export and at retail, and home preparation and consumption). The model was implemented in Microsoft Excel 2016 with the @Risk add-on package. Results of 302 surveys with data collected in Israel were as follows: 92.3% of people consumed beef, mostly at home, and 98.2% preferred levels of cooking that ensured STEC removal from the surface of beef cuts. The preferred degree of ground beef doneness was "well-done" (48.2%). Cooking preference ranged from red to "medium-well done" (51.8%). Median HUS probability from Argentinean beef cut and ground beef consumption in children under 14 years old was <10-15 and 8.57x10-10, respectively. The expected average annual number of HUS cases and deaths due to beef cut and ground beef consumption was zero. Risk of infection and HUS probability correlated with salting effect on E. coli count, processing raw beef before vegetables, ways of storage and refrigeration temperature at home, joint consumption of salad and beef cuts, degree of beef doneness and cutting board washing with detergent after each use with beef and vegetables. The STEC-HUS risk in Israel from consumption of bovine beef produced in Argentina was negligible. The current QMRA results were similar to those of previous beef cut consumption QMRA in Argentina and lower than any of the QMRA performed worldwide in other STEC-HUS linked to ground beef consumption. This study confirms the importance of QMRA to estimate and manage the risk of STEC-HUS from beef consumption. The impact variables identified in the sensitivity analysis allowed us to optimize resources and time management, to focus on accurate actions and to avoid taking measures that would not have an impact on the risk of STEC-HUS.

Integrating Commercial-Off-The-Shelf Components into Radiation-Hardened Drone Designs for Nuclear-Contaminated Search and Rescue Missions

This paper conducts a focused probabilistic risk assessment (PRA) on the reliability of commercial off-the-shelf (COTS) drones deployed for surveillance in areas with diverse radiation levels following a nuclear accident. The study employs the event tree/fault tree digraph approach, integrated with the dual-graph error propagation method (DEPM), to model sequences that could lead to loss of mission (LOM) scenarios due to combined hardware–software failures in the drone’s navigation system. The impact of radiation is simulated by a comparison of the total ionizing dose (TID) with the acceptable limit for each component. Errors are then propagated within the electronic hardware and software blocks to determine the navigation system’s reliability in different radiation zones. If the system is deemed unreliable, a strategy is suggested to identify the minimum radiation-hardening requirement for its subcomponents by reverse-engineering from the desired mission success criteria. The findings of this study can aid in the integration of COTS components into radiation-hardened (RAD-HARD) designs, optimizing the balance between cost, performance, and reliability in drone systems for nuclear-contaminated search and rescue missions.