Probabilistic Risk Assessment Research Articles

Probabilistic Approaches for Risk Assessment and Regulatory Criteria Development: Current Applications, Gaps, and Opportunities.

Traditional ecological and human health risk assessment often relies on deterministic frameworks that preclude the presence of variability or uncertainty among input parameters characterizing exposure, effects, and risk. To promote increased realism and generate more robust risk management decisions, probabilistic risk assessment (PRA) has been introduced as a foundational grouping of techniques that seeks to broadly characterize variability among its components. While multiple methods exist (e.g., Monte Carlo simulations, Bayesian networks) along with some federal and state regulatory guidance, gaps remain in prescriptive regulatory recommendations for the implementation of PRA methods. This article describes specific probabilistic approaches for risk characterization and assessment, regulatory support of PRA, challenges that may limit more widespread use, and opportunities for its expanded use in regulatory areas where it is not currently applied. Taken together, we hope to advance the understanding of probabilistic methodologies and their versatility for robust, transparent, data-based environmental risk assessment and standards derivation across a range of media that align with regulatory objectives to protect aquatic and terrestrial biota, human health, and vulnerable populations.

Risk analysis and protection in case of intrusion of nuclear facilities

Abstract Physical protection systems (PPSs) are designed to counter and neutralize any theft or sabotage attempts carried out against a given site. PPS designs are crucial, requiring rigorous analysis and evaluation to ensure their reliability, sustainability and optimal security. This paper assumes a Hypothetical Nuclear Research Center (HNRC) for PPS analysis and evaluation. This work will determine the PPS’s most vulnerable path elements, by demonstrating expected intrusion attack scenarios by taking advantage of the HNRC’s design weaknesses. Also, this work determines the threats resulting from adversary intrusion through the weakness path elements located at the nuclear site. Additionally, this paper develops an analytical methodology for this evaluation and risk assessment, by using the Systematic Analysis of Vulnerability to Intrusion (SAVI) computer program. Through constructing adversary sequence diagrams (ASDs), SAVI can easily identify the HNRC’s most vulnerable paths, pinpointing the areas which require the most attention. Alongside SAVI is the quantitative risk analysis method - the Dai et al. Model – which can calculate the effectiveness and risk of the PPS itself by measuring its degree of uncertainty using effectiveness entropy. To comply with effectiveness and risk standards, this work also introduces security system upgrade processes and determines the optimal security solution for the HNRC.

Development of Progressively Earth-Independent Medical Operations to Enable NASA Exploration Missions.

Introduction -The National Aeronautics and Space Administration's (NASA's) transition from operations in low-Earth orbit to long-duration missions to the Moon and Mars necessitates the development of progressively Earth-independent medical operations (EIMO) to support crews and reduce overall mission risk. Previous work has defined and laid the foundation for EIMO, but further development of the concept is required to prepare for future exploration missions. Methods -NASA's Exploration Medical Capability element organized a series of 5 technical interchange meetings from 2023 to 2024, which included internal (NASA) and external subject-matter experts in human spaceflight, health technology, and austere medicine to create a framework for developing the technologies and procedures necessary to maintain human health and performance in a progressively Earth-independent fashion. Results -The EIMO technical interchange meetings provided a forum for a field of experts and stakeholders to better understand gaps between current approaches to medical care in low-Earth orbit and the innovations needed to maintain the health and performance of astronauts on long-duration deep-space missions. These discussions were recorded, analyzed, and collated into reports that can inform the maturation of EIMO concepts. Conclusions -Multidisciplinary input from experts with experience in human spaceflight, health technology, and austere medicine is critical when planning for long-duration exploration missions. Innovations such as probabilistic risk assessment tools, extended reality devices, and advanced clinical artificial intelligence capabilities have been identified as high-value targets that can enhance inflight medical autonomy while maintaining appropriate workload balance and crew safety. By further developing the EIMO paradigm, NASA aims to identify areas of future work, research, and collaboration to reduce overall risk on future human spaceflight missions into deep space.

Gerenciamento de riscos de desastres naturais em Santa Catarina

Natural disasters cause deaths, damage, and significant losses to Brazilian cities. Santa Catarina, located in southern Brazil, a region geographically prone to climate variability, frequently suffers from meteorological, climatological, geological, and hydrological disasters. Between 1993 and 2023, extreme events displaced or left homeless over 1 million residents of Santa Catarina, with flash floods, heavy rains, and flooding being responsible for most cases. The aim of this study was to analyze the main risks of these three occurrences, which have been intensified by global warming, to which the state of Santa Catarina is exposed, and to identify their respective levels of probability and impact. The methodology was divided into risk identification, risk classification, quantitative risk analysis, risk response planning, and risk monitoring and mitigation. The study analyzes the three main phenomena (heavy rains, flash floods, and flooding) to propose a risk management method that can contribute to the implementation of public policies to mitigate impacts and increase the resilience of affected communities. The research shows that flash floods are the highest-impact risks and therefore must be prioritized in public management, as the trend is for these phenomena to occur more frequently and with greater intensity over time due to the effects of climate change.

Probabilistic Risk Analysis for Catenary System of Heavy‐Haul Railway Based on Casual Inference

Probabilistic Risk Analysis for Catenary System of Heavy‐Haul Railway Based on Casual Inference

Probabilistic assessment of the cumulative risk from dietary heavy metal exposure in Chongqing, China using a hazard-driven approach

Cumulative risk assessment is significant for evaluating the combined exposure to multiple substances, but its widespread acceptance and application have been limited due to the complexity of clarifying and assessing actual exposure. In this study, we conducted a cumulative risk assessment based on hazard-driven criteria to evaluate the co-exposure to elemental contaminants in the diet of the population in Chongqing Municipality. The cumulative risk was calculated and evaluated using Monte Carlo modeling and the modified Reference Point Index (mRPI) method. Neurotoxicity and nephrotoxicity were identified as the main toxic endpoints, and the final evaluation elements included were Pb, Cd, As, and Hg. The results showed that the combined mRPI values for neurotoxicity and nephrotoxicity, resulting from exposure to the four heavy metals, ranged from 0.922 to 4.835 and 1.306 to 7.031, respectively. Cd and Pb were the primary contributors to nephrotoxicity, while Pb was the main contributor to neurotoxicity. The results indicated that combined dietary exposure to Pb, Cd, As, and Hg may pose risks of neurotoxicity and nephrotoxicity, with the combined exposure likely amplifying this risk compared to exposure to individual heavy metal elements. mRPI proves to be a more suitable index for cumulative risk assessment using a hazard-driven approach compared to other indexes, as it is derived based on specific studies and endpoints.

Source-oriented health risk assessment of soil potentially toxic elements based on Monte Carlo simulation in the upper reaches of Wei River Basin, China.

The natural environment and public health are gravely threatened by the enrichment of soil potentially toxic elements (PTEs). To explore the contamination level, sources and human health risks posed by PTEs, high-density soil sampling was carried out in the upper Wei River region (UWRR). The results demonstrated that the pollution risk and ecological risk in UWRR as a whole were at a low level, but there were moderate or higher ecological risks of Hg and Cd in some areas. Source analysis of soil PTEs was conducted via absolute principal component score multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) receptor models. APCS-MLR identified three potential sources, while the source division of PMF model was more detailed, which identified four potential sources: mining, coal combustion, machinery manufacturing and agricultural sources, with contribution percentages of 31%, 3%, 37% and 29% respectively. According to the probabilistic human health risk assessment (HHRA), the non-carcinogenic risk for adults was negligible, while that for children cannot be negligible. There were total carcinogenic risks for all populations, but the risk level was acceptable. The total cancer risk for children surpassed 1E-04 by 31.29%, implying a significant carcinogenic risk. Machinery manufacturing was found to be the most significant anthropogenic source of health concerns. This study offers an illustration of probabilistic risk assessment based on sources. The results of the study are favorable to provide new perspectives and scientific reference for soil PTE risk assessment and pollution control.

A Probabilistic Liquefaction Hazard Analysis: Case Studies from the Marmara Region

Earthquake induced soil liquefaction poses a significant threat to buildings and infrastructure, as evidenced by numerous catastrophic seismic events. Existing approaches of regional liquefaction hazard assessment predominantly rely on deterministic analysis methods. This paper presents a novel Probabilistic Liquefaction Hazard Analysis (PLHA) framework based on Monte-Carlo (MC) simulations to mitigate future seismic risks associated with liquefaction. The proposed procedure requires only publicly available data, offering accessibility and applicability in resource-constrained settings. A key feature of the procedure is its ability to deal with uncertainties in earthquake and soil parameters using distribution functions. Liquefaction potential is assessed through parameters such as Liquefaction Potential Index (LPI) and Liquefaction Severity (LS). The procedure is implemented in MATLAB as part of a broader probabilistic risk assessment framework for developing countries. The developed procedure is applied to the high risk city of Adapazari, Türkiye; an area lacking prior PLHA studies. Results are validated against observed liquefaction data from a simulated scenario event of the 1999 Kocaeli earthquake. Probabilistic liquefaction hazard maps are generated for the study area and the entire Marmara region in terms of LPI and LS. A novel aspect of this work is the integration of a time-dependent Probabilistic Seismic Hazard Analysis (PSHA) model into the PLHA framework. Results are compared with those predicted using the Poisson model for the Marmara region. Findings demonstrate that the developed PLHA procedure offers a robust and flexible tool for predicting seismic liquefaction hazards, providing valuable insights for loss estimation and risk mitigation planning.

Three-dimensional identification of drought events and copula-based multivariate meteorological drought risk probability assessment in the Huai River Basin, China

Three-dimensional identification of drought events and copula-based multivariate meteorological drought risk probability assessment in the Huai River Basin, China

Quantifying the sources and health risks of groundwater nitrate via dual NO isotopes and Monte Carlo simulations in a developed planting-breeding area.

Nitrate (NO3-) pollution in groundwater is a worldwide environmental issue, particularly in developed planting-breeding areas where there is a substantial presence of nitrogen-related sources. Here, we explored the key sources and potential health risks of NO3- in a typical planting-breeding area in the North China Plain based on dual stable isotopes and Monte Carlo simulations. The analysis results revealed that the NO3- concentration ranged from 0.02 to 44.6 mg/L, with a mean value of 7.54 mg/L, along with a significant spatial variability. Analysis by combining stable isotopes (δ15N-NO3- and δ18O-NO3-) with the Bayesian isotope mixing model (MixSIAR) revealed that soil N (60.3 %) and manure and sewage (35.9 %) contributed the most NO3- in groundwater, followed by chemical N fertilizer (2.9 %) and atmospheric N deposition (0.8 %). However, the contribution of N fertilizer may be underestimated because it has undergone a long-term applied history and have progressively accumulated in the soil, and then promoted the entry of groundwater under frequent rainfall and irrigation practices. From the probabilistic health risk assessment, a relatively low probability of exceeding the threshold (HI=1) was observed (0.2 % for adults and 2.59 % for children); nevertheless, children still face some nonnegligible risk, particularly for the oral ingestion of drinking water at high-pollution sites. Therefore, we highlight the importance of effective management of manure and sewage from breeding plants and reduction of chemical N fertilizer usage are suggested in developed agricultural areas.

Advanced matter-element extension model and machine learning for source-specific probabilistic health risk assessment of heavy metals/metaloids in soil-rose systems in Kushui, Northwest China

Advanced matter-element extension model and machine learning for source-specific probabilistic health risk assessment of heavy metals/metaloids in soil-rose systems in Kushui, Northwest China

Quantitative Risk Analysis of China’s Financial Industry—Based on AHP + Fuzzy Comprehensive Evaluation Model

Quantitative Risk Analysis of China’s Financial Industry—Based on AHP + Fuzzy Comprehensive Evaluation Model

Bayesian source apportionment and eco-probabilistic risk assessment of aliphatic and polycyclic aromatic hydrocarbons in sediments from the offshore area between the Deep Water Tano and West Cape three points blocks, Ghana.

This study investigates aliphatic and polycyclic aromatic hydrocarbons in sediments from offshore Ghana, focusing on their distribution, sources, and ecological risk. Samples were collected from 15 sites near Deep Water Tano and West Cape Three Points blocks. GC-FID and GC-MS analyses revealed higher concentrations in West Cape Three Points compared to Deep Water Tano. Bayesian source apportionment indicated microorganisms as the primary contributor to AHs in both areas. For polycyclic aromatic hydrocarbons, pyrogenic sources dominated in Deep Water Tano (63.3%), while grass/coal/wood combustion was primary in West Cape Three Points (60%). Probabilistic risk assessment identified benzo[a]pyrene as posing the highest ecological risk. This study demonstrates the utility of Bayesian methods in identifying hydrocarbon sources and highlights the importance of species-specific sensitivities in ecological risk assessments, providing valuable insights for marine environment management.

Enrichment mechanism and probabilistic health risk assessment of high-fluoride groundwater in Gaomi City, China.

Fluoride (F) is the most important inorganic pollutant in groundwater that affects human health, and analyzing the causes of high-fluoride groundwater is a prerequisite for protecting the health of residents. To comprehensively understand the enrichment characteristics of groundwater in the high-fluoride areas, this study systematically investigated the concentrations of fluoride in Gaomi City, a typical study area in the Jiaolai Plain and explored the spatiotemporal distribution patterns, enrichment mechanisms, and the probabilistic health risk associated with F-. The results indicate that there is serious fluorine pollution in groundwater, which is mainly concentrated in the alluvial plain in the north and affected by topographical and aquifer characteristics. Favorable runoff conditions effectively improve the fluoride status of shallow groundwater on both sides of rivers and in hilly areas. Hydrogeochemical methods reveal the mechanism of fluoride enrichment. The relative contributions rates of different hydrogeochemical processes to the fluoride enrichment are as follows: dissolution and precipitation (39.02%) > cation exchange (25.25%) > competitive adsorption (19.48%) > seawater intrusion (3.14%) > evaporative and concentration (1.99%). Health risk assessment based on Monte Carlo simulation shows that health risk susceptibilities of different populations are infants (76.07%), children (66.59%), teenagers (44.54%), and adults (5.68%), respectively. In addition, targeted management suggestions are put forward regarding the enrichment mechanisms of fluoride in groundwater and its impact on health. These findings have significant implications for controlling regional diffuse F- contamination in groundwater, protecting public health, and promoting social development in regions with a high risk of groundwater fluoride contamination.

Probabilistic health risk assessment of BTEX contamination in groundwater using the set of triplets methodology: a case study near Shiraz Oil Refinery, Iran

Probabilistic health risk assessment of BTEX contamination in groundwater using the set of triplets methodology: a case study near Shiraz Oil Refinery, Iran

Predicting Exploration Crew Medical Officer Training Needs: Applying Evidence-Based Predictive Analytics to Space Medicine Training.

Predictive analytics may be a useful adjunct to identify training needs for exploration class medical officers onboard deep space vehicles. This study used a preliminary version of NASA's newest medical predictive analytics tool, the Medical Extensible Database Probabilistic Risk Assessment Tool (MEDPRAT), to test the application of predictive analytics to exploration crew medical officer curriculum design for 5 distinct design reference mission (DRM) profiles. Partial and fully treated paradigms were explored. Curriculum elements were identified using a leave-one-out analysis and a threshold of 5% risk increase over the fully treated baseline. For the partial treatment scenario, among the 5 DRM profiles 4-32 curriculum elements met the 5% RRI increase. For the absolute treatment scenario, among the 5 DRM profiles, 13-126 curriculum elements met the 5% RRI increase. For the partial treatment paradigm, 13 capabilities are present in at least 3 of the 5 DRM profiles, and these elements may constitute a common baseline curriculum. This covers 41% of the skillsets needed for an ISS-like profile, 100% of a late Artemis-like profile, 41% of a Mars mission-like profile, 100% of a Starship orbital-like profile, and 68% of a Starship lunar flyby-like profile. This proof-of-concept study demonstrated that predictive analytics can rapidly generate generic and mission profile-specific exploration CMO curricula using an evidence-based process driven by optimizing mission risk reduction. This technique may serve as part of a human-machine team approach to medical curriculum planning for future space missions. It has significant potential to improve astronaut health and save time and effort for planners, trainers, and trainees.

Model for integral codes for calculating containment thermohydraulics in severe accidents at nuclear power plants with a water coolant

The article describes a model for calculating the containment thermal in severe accidents at nuclear power plants with a water coolant. The model is implemented in the SOCRAT integral code in the form of a CONT_TH module, which allows performing self-consistent calculation of parameters in a VVER reactor plant and a containment during a severe accident. In conjunction with other modules of the SOCRAT code, a realistic calculation of the transfer of radioactive substances to the containment is provided, which is necessary to calculate source term into the environment when justifying the safety of nuclear power plants, including probability safety assessment level 2. With a slight adaptation, the model can be used to calculate the parameters of containment in a water-cooled NPP as part of other integral codes.

Unveiling the nutritional value and potentially toxic elements in fish species from Miliç Wetland, Türkiye: A probabilistic human health risk assessment using Monte Carlo simulation

This study evaluates the nutritional value and health risks of fish from Miliç Wetland, Türkiye, focusing on potentially toxic elements (PTEs) in Esox lucius, Squalius cephalus, and Carassius gibelio. Using ICP-MS, mean PTE concentrations were determined, including Zn (4979 μg/kg), Fe (4241 μg/kg), and As (125 μg/kg). Macro elements like K, P, and Ca were also assessed for nutritional profiling. A Monte Carlo-based risk assessment confirmed that PTE levels were below safety limits, indicating safe consumption. Chemometric techniques (PCA, PCC, HCA) helped trace contamination sources, identifying residential, agricultural, and lithogenic inputs. Esox lucius showed the highest essential nutrient levels. This research highlights the importance of combining chemometric analysis with regular monitoring for food safety and public health protection.

European Native Oyster Reef Ecosystems Are Universally Collapsed

ABSTRACTOyster reefs are often referred to as the temperate functional equivalent of coral reefs. Yet evidence for this analogy was lacking for the European native species Ostrea edulis. Historical data provide a unique opportunity to develop a robust definition for this ecosystem type, confirm that O. edulis are large‐scale biogenic reef builders, and assess its current conservation status. Today, O. edulis occur as scattered individuals or, rarely, as dense clumps over a few m2. Yet historically, O. edulis reef ecosystems persisted at large scales (several km2), with individual reefs within the ecosystems present at the scale of several hectares. Using the IUCN Red List of Ecosystems Framework, we conclude the European native oyster reef ecosystem type is collapsed under three of five criteria (A: reduction in geographic distribution, B: restricted geographic range, and D: disruption of biotic processes and interactions). Criterion C (environmental degradation) was data deficient, and Criterion E (quantitative risk analysis) was not completed as the ecosystem was already deemed collapsed. Our assessment has important implications for conservation policy and action, highlighting that the habitat definitions on which conservation policies are currently based reflect a highly shifted baseline, and that the scale of current restoration efforts falls far short of what is necessary for ecosystem recovery.

Initial Event Analysis for Turbine Missile Events at Floating Nuclear Power Plants Using the Master Logic Diagram Method

Floating Nuclear Power Plants (FNPP) have become a popular design choice in several countries, including South Korea, China, and Denmark. Safety analysis, including probabilistic safety assessment, must be conducted for every nuclear reactor design. Among the parameters that need to be determined are initiating events. Initiating events is crucial information as it impacts further analyses, such as event and fault tree analyses. Various methods exist for deciding and initiating events, including the Master Logic Diagram (MLD). The determination of initiating events can be based on the potential impact of internal or external hazards on the FNPP. This study aims to demonstrate the application of MLD in determining initiating events in the case of a turbine missile incident on Akademik Lomonosov floating NPP. Turbine missile events are critical due to their potential to damage important safety-related structures, systems, and components in the vicinity. From the analysis, it was found that ten basic events could be candidates for initiating events. After the screening process, four initiating events were identified as the final result: reactor vessel rupture (RVR), loss of feedwater (LOFW), feedwater line break (FWLB), and loss of condenser vacuum (LOCV). Keywords: Floating NPP, safety analysis, initiating event, master logic diagram (MLD)