Results Of Probabilistic Risk Assessment Research Articles

Human health risks associated with the consumption of groundwater in the Gaza Strip

Groundwater of the Gaza Strip, the main source of drinking water for the Gazans, is highly contaminated by several chemicals of natural and anthropogenic origins. The results of this study confirm the findings of several studies conducted over the past two decades. Over those two decades, the population of Gaza has doubled, resulting in heavy demand for the limited reserves of groundwater. After 20 years since the first comprehensive study, it was found that groundwater salinity increased by 30 %, due to seawater intrusion. On the other hand, nitrate (NO3) decreased by 30 %, due to expansion of the sewer network and decrease in the number and distribution of septic tanks. Salinity, chloride (Cl), NO3 and fluoride (F) distribution maps for the year 2022 are very similar to those of the year 2002. This indicates that sources and loads of such contaminants are still the same. Metals and metalloids are still within the permissible limits set by the World Health Organization (WHO). Strontium (Sr) only showed concentrations of 12 mg/L across the Gaza Strip, which calls for further investigations. Maximum concentrations of the NO3 and F were 365 and 2.6 mg/L, respectively. The results of probabilistic risk assessment using Monte Carlo simulation showed that NO3 and F consumption through drinking water were above the reference dose for 35 % and 5 % of the trials performed, respectively. Consequently, the hazard quotient (HQ) is larger than 1 for 35 % and 5 % of the exposure scenarios simulated for these ions. For all metals and metalloids analyzed, HQ were below one (HQ1) indicating no risk; however, Sr presented an HQ 95th percentile equal to 0.19. Exposure routes such as dietary intake and soil ingestion, among others, should be further investigated to ensure that cumulative exposure does not surpass the safety limit. Recent advances in desalination technology should put an end to this truly regrettable situation.

Accident Sequence Precursor Analysis of an Incident in a Japanese Nuclear Power Plant Based on Dynamic Probabilistic Risk Assessment

Probabilistic risk assessment (PRA) is an effective methodology that could be used to improve the safety of nuclear power plants in a reasonable manner. Dynamic PRA, as an advanced PRA, allows for more realistic and detailed analyses by handling time-dependent information. However, the applications of this method to practical problems are limited because it remains in the research and development stage. This study aimed to investigate the possibility of utilizing dynamic PRA in risk-informeddecision-making. Specifically, the author performed an accident sequence precursor (ASP) analysis on the failure of emergency diesel generators that occurred at Unit 1 of the Tomari Nuclear Power Plant in Japan using dynamic PRA. The results were evaluated by comparison with the results of simplified classical PRA. The findings indicated that dynamic PRA may estimate lower risks compared with those obtained from classical PRA by reasonable modeling of alternating current power recovery. The author also showed that dynamic PRA can provide detailed information that cannot be obtained with classical PRA, such as uncertainty distribution of core damage timing and importance measure considering the system failure timing.

Probabilistic Assessment of Pluvial Flood Risk Across 20 European Cities: A Demonstrator of the Copernicus Disaster Risk Reduction Service for Pluvial Flood Risk in Urban Areas

Pluvial flooding is a major concern in urban environments with limited or temporarily reduced efficiency of surface drainage. Climate change, land use change, and increased exposure in hazard prone areas play a role in increasing pluvial flood risks. We describe a methodology for rapid probabilistic pluvial flood hazard mapping and risk assessments in urban environments developed for the Copernicus Climate Change Service “Pluvial Flood Risk Assessment in Urban Areas” demonstrator project for large computational domains. The methodology is designed to be flexible and robust enough to be adapted to other cities in Europe and elsewhere, and is composed of three main steps: (i) computation of the intensity–frequency relationship to express the depth of extreme hourly rainfall events at the urban scale; (ii) characterization of the pluvial flood hazard by means of raster-based flood modeling, and; (iii) estimation of the direct tangible damages at the building level for residential, commercial, and industrial buildings. Methods are tested for 20 cities across Europe and considering two infiltration rate scenarios. Spatial-explicit results at the urban-scale highlight the neighborhoods and sub-urban areas more adversely affected in terms of direct tangible damage to buildings and assets. Probabilistic risk assessment results indicate that Brussels, Antwerp, and London are the cities with higher expected annual damages per built-up area among the 20 cities considered in this study. These results can be useful for supporting the implementation of the Sendai Framework for DRR 2015–2030, for developing multi-hazard risk assessments, and for supporting the development of national climate change adaptation plans.

Neonicotinoid Insecticides Threaten Surface Waters at the National Scale in China

This study was conducted in response to the current situation in our country in which neonicotinoid pesticides (NNIs) are used in large quantities and their concentration in surface water is gradually increasing. Based on the species sensitivity distribution (SSD), the hazard quotient (HQ) and probabilistic risk assessment (PRA) were used to compare single and mixture risks of NNIs in the surface water in China. The target and recommended values of NNIs in China's surface water quality supervision were also presented. The results showed that:① in the single acute hazard assessment, imidacloprid (IMI) was the most harmful insecticide, and in the single chronic hazard assessment, imidacloprid (IMI) and acetamiprid (ACE) were more harmful. Furthermore, insects were the most sensitive creatures. ② Hainan province was the region with the highest single acute and chronic hazard in the study area. ③ Based on the joint probability curves of five neonicotinoids, the probability in which 5% of species would be affected by long-term exposure was approximately 91.12%. Thus, the combined ecological risk of these five neonicotinoids cannot be ignored. ④ Based on the toxicity reference value from SSD and the combined results of HQ and PRA, the regulatory values of surface water quality in China were as follows:acetamiprid (ACE) 0.04 μg·L-1, clothianidin (CLO) 0.22 μg·L-1, imidacloprid (IMI) 0.01 μg·L-1, thiacloprid (THI) 0.03 μg·L-1, and thiamethoxam (THIA) 0.24 μg·L-1. In short, the concentration of NNIs in the surface water in China has threatened the safety of aquatic organisms, and its supervision must be improved.

Spatial distribution and benthic risk assessment of cyclic, linear, and modified methylsiloxanes in sediments from Tokyo Bay catchment basin, Japan: Si-based mass profiles in extractable organosilicon

We investigated the spatial distribution, mass profiles, and benthic risk assessment of a wide range of methylsiloxanes (MSs), including 7 cyclic MSs (CMSs; D3–D9; the number refers to the number of SiO bonds), 13 linear MSs (LMSs; L3–L15), and 15 modified and other MSs (MMSs) in sediments from the Tokyo Bay catchment basin, Japan. We observed widespread distribution of MSs (ΣCMS, ΣLMS, and ΣMMS) in the sediment samples, with concentrations of 1.0–6180 ng/g dry weight (dw), 1.8–10,100 ng/g dw, and < 0.31–210 ng/g dw, respectively. Our study is the first to measure various MMSs modified with hydrogen, vinyl, or phenyl groups; however, only methyltris(trimethylsiloxy)silane and phenyltris(trimethylsiloxy)silane were detected with high occurrence frequency. Notably, no elevated concentrations of MSs were observed downstream of silicone manufacturers, whereas the sediment was characterized by a specific D4/D5 ratio. With the Si-based mass profiles in extractable organosilicon (EOSi), the measured CMSs, LMSs, and MMSs accounted for 5.4%, 7.8%, and 0.2%, respectively. Unidentified EOSi (unknown fraction) constituted a major proportion of the EOSi in the sediment, with a mean of 87%, suggesting that the organosilicon environmental emissions were more than the measured MSs. In risk assessment of the adverse effects of D4, D5, and D6 in sediment on benthic organisms, the respective distributions indicated no overlap between the 95th percentile field sediment concentration and the 5th percentile chronic sediment no-effect concentration in organic carbon-normalized concentration. Although the hazard quotient compared with the predicted no-effect concentration for D5 and D6 exceeded the threshold level (hazard quotient ≥1), the results of probabilistic risk assessment for the three CMSs were not high enough to indicate a threat to benthic organisms in the study area.

Liver-Based Probabilistic Risk Assessment of Exposure to Organophosphate Esters via Dust Ingestion Using a Physiologically Based Toxicokinetic (PBTK) Model.

Organophosphate esters (OPEs) are widely used and harmful to organisms and human health. Dust ingestion is an important exposure route for OPEs to humans. In this study, by integrating ToxCast high-throughput in vitro assays with in vitro to in vivo extrapolation (IVIVE) via physiologically based Toxicokinetic (PBTK) modeling, we assessed the hepatocyte-based health risk for humans around the world due to exposure to two typical OPEs (TPHP and TDCPP) through the dust ingestion exposure route. Results showed that the health guidance value of TPHP and TCDPP obtained in this study was lower than the value obtained through animal experiments. In addition, probabilistic risk assessment results indicate that populations worldwide are at low risk of exposure to TPHP and TDCPP through dust ingestion due to low estimated daily intakes (EDIs) which are much lower than the reference dose (RfDs) published by the US EPA, except in some regional cases. Most margin of exposure (MOE) ranges of TDCPP for children are less than 100, which indicates a moderately high risk. Researchers should be concerned about exposure to TDCPP in this area. The method proposed in this study is expected to be applied to the health risk assessment of other chemicals.

Heavy metal pollution and human health risk assessment at mercury smelting sites in Wanshan district of Guizhou Province, China.

The Wanshan district of Guizhou Province has a long history of mercury mining and smelting. Previous studies have been carried out on heavy metal (HM) pollution in the soil around Wanshan (such as in urban and farmland areas), but these studies have not been conducted at mercury smelting sites. In this study, the distribution characteristics of As, Be, Cd, Cr, Cu, Hg, Ni, Sb, Pb and Zn and their sources in the shallow stratum (<10 m) of the mercury smelting site in the Wanshan district were analyzed. Human health risks were evaluated using deterministic risk assessment (DRA) and probabilistic risk assessment (PRA) models. The contribution rates of different HM sources to human health risks were also calculated. The maximum HM concentration in mercury smelting site soil occured in the shallow soil (0–1 m), and the concentration sequences were as follows: 358.51 mg kg−1 (Hg) > 248.6 mg kg−1 (Zn) > 67.42 mg kg−1 (As) > 59.04 mg kg−1 (Ni) > 57.56 mg kg−1 (Pb) > 49.59 mg kg−1 (Cr) > 46.65 mg kg−1 (Sb) > 15.65 mg kg−1 (Cu) > 2.02 mg kg−1 (Be) > 0.78 mg kg−1 (Cd). The variable coefficients (CVs) were 1.64 (As), 0.67 (Be), 3.15 (Cd), 1.89 (Cr), 0.95 (Cu), 3.08 (Hg), 0.79 (Ni), 1.41 (Sb), 0.68 (Pb) and 1.13 (Zn), respectively. The HM concentrations in deep soils (9 m) still exceed the local background values, suggesting that heavy metals in shallow soil have migrated downward in the site. Three pollution sources identified with the shallow soil (0–1 m) HMs using the positive matrix factorization (PMF) model, were mercury smelting and coal combustion mixed sources (As, Hg and Zn), parent material sources (Ni, Cu, Cr, Cd and Sb) and wastewater discharge sources (Cu and Pb), respectively. DRA indicated that oral ingestion was the main pathway affecting the carcinogenic risk (CR) and hazard quotient (HQ) of heavy metals. The total-CR of twenty-five sampling points is between 1.219 × 10−6 and 3.446 × 10−4, and the total-HQ is between 0.37 and 43.56. PRA results indicated that DRA will underestimate the health risk of all populations in Guizhou Province, especially female, and BWa is the most influential variable for the PRA results. Smelting and coal combustion mixed sources contributed the most CR (99.29%) and with an HQ of 89.38% were the major sources of pollution affecting human health.

Developing and applying a site-specific multimedia fate model to address ecological risk of oxytetracycline discharged with aquaculture effluent in coastal waters off Jangheung, Korea

The overuse of oxytetracycline (OTC) in aquaculture has become a problem because of its chronic toxic effects on marine ecosystems. The present study assessed the ecological risk of OTC in the coastal waters near the Jangheung Flatfish Farm using a site-specific multimedia fate model to analyze exposure. Before the model was applied, its performance was validated by comparing it with field data. The coastal waters in the testbed were sampled and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by solid-phase extraction (SPE). The concentrations of OTC measured varied from 7.05 to 95.39ng/L. The results of validating the models showed that the site-specific multimedia fate model performed better (root mean square error (RMSE): 24.217, index of agreement (IOA): 0.739) than conventional fugacity approaches. This result demonstrated the utility of this model in supporting effective future management of aquaculture effluent. The results of probabilistic risk assessment indicated that OTC from aquaculture effluent did not cause adverse effects, even in a maximum-use scenario.

S0820203 原子力施設の免震技術の開発 : 免震プラントの地震PRAについて

This study is part of a series titled "Development of an evaluation method for seismic isolation systems of nuclear power facilities". In this study, seismic Level 1 probabilistic risk assessment (PRA) was performed for a nuclear power plant equipped with a seismic isolation system in order to evaluate its effects under the design basis and also design extension conditions. The study also clarifies the risk feature of the seismically isolated plant and suggests ways to improve the plant reliability by comparing the results of PRA with those of a conventional nuclear power plant.

An alternative comprehensive framework using belief functions for parameter and model uncertainty analysis in nuclear probabilistic risk assessment applications

In nuclear power plants, probabilistic risk assessment insights contribute to achieve a safe design and operation. In this context, the decision-making process must be robust and uncertainties must be taken into account and controlled. In general, the uncertainties in a nuclear probabilistic risk assessment context can be categorized as either aleatory or epistemic. The epistemic uncertainty, which can be subdivided into parameter and model uncertainties, is recognized to have an important impact on actual results of probabilistic risk assessment. Traditionally, the approach of an epistemic uncertainty analysis in nuclear probabilistic risk assessment often relies on the probabilistic approach in which parameter uncertainty is treated by using an assigned probability distribution, e.g. the log-normal one, and model uncertainty can be taken into account through sensitivity studies. Such an approach has been recognized in several recent researchs to present limitations regarding the impacts of assigning probability distribution in case of rare operating feedback data. In order to overcome such a limitation, in this article we propose a comprehensive approach for uncertainty analysis from the parameter and model uncertainties modeling to the final step of the decision-making process using the Dempster-Shafer theory, which is recognized to be more general than the probabilistic approach. We also show that the traditional probabilistic approach, currently used in probabilistic risk assessment practice, can be totally integrated in this framework. Finally, the proposed framework is illustrated and compared with the traditional approach through a practical example from EDF Nuclear Power Plants probabilistic risk assessment application. Some discussions and conclusions for industrial probabilistic risk assessment contexts will be given.

Arsenic exposure and tobacco consumption: Biomarkers and risk assessment

Arsenic is measurable in tobacco and cigarette mainstream smoke (MSS). Whether arsenic has an independent role in diseases associated with tobacco consumption is not known. Epidemiology and biomonitoring data and probabilistic risk assessment (PRA) methods were used to investigate this potential association. Analysis of data from the National Health and Nutrition Examination Survey (NHANES) showed that urine arsenic concentrations in tobacco consumers were not different or were lower than levels in non-consumers of tobacco. Additionally, urine arsenic levels from NHANES tobacco consumers were five-times or more lower than levels reported in epidemiology studies to be associated with adverse health effects. Results of PRA indicated that mean non-cancer hazard estimates and mean incremental lifetime cancer risk estimates were within accepted ranges. Taken together, these results suggest that arsenic may not be independently associated with tobacco consumption or diseases related to tobacco consumption.

On comparing PRA results with operating experience

A procedure is presented for quantifying the consistency between probabilistic risk assessment (PRA) results and corresponding plant-specific operating data not considered in the PRA. The method, which is easily implemented in practice, is based on the use of Bayes p-values for the predictive probability that the observed data would have been produced from the PRA results in conjunction with an assumed binomial or Poisson sampling distribution. Uncertainties in both the PRA results and the operating data are considered. The method is used to quantify the consistency between PRA results and operating data for high-pressure coolant injection system unreliabilities at 11 US commercial boiling water reactors.

A decision-oriented measure of uncertainty importance for use in PSA

For the interpretation of the results of probabilistic risk assessments it is important to have measures which identify the basic events that contribute most to the frequency of the top event but also to identify basic events that are the main contributors to the uncertainty in this frequency. Both types of measures, often called Importance Measure and Measure of Uncertainty Importance, respectively, have been the subject of interest for many researchers in the reliability field. The most frequent mode of uncertainty analysis in connection with probabilistic risk assessment has been to propagate the uncertainty of all model parameters up to an uncertainty distribution for the top event frequency. Various uncertainty importance measures have been proposed in order to point out the parameters that in some sense are the main contributors to the top event distribution. The new measure of uncertainty importance suggested here goes a step further in that it has been developed within a decision theory framework, thereby providing an indication of on what basic event it would be most valuable, from the decision-making point of view, to procure more information.

Experiences in using PRA as an operational tool

The Probabilistic Risk Assessment (PRA) of Koeberg Nuclear Power Station has been used for a number of years to support operation decision making. The principle aim of this risk assessment of Koeberg is to determine the probability of a severe accident under varying operating conditions. This plant model is used by ourselves and our licensing authority to assess nuclear safety issues. Through this process, considerable practical experience has been gained in using a “living” PRA to improve plant safety and performance. This paper presents some of the insights obtained in using reliability engineering in such a dynamic way and demonstrates that by developing and using the “living” PRA considerable safety and financial gains can be obtained. These insights mainly concern the prerequisites required before optimal use of a “living” PRA can be made. Other insights concern how PRA results are best presented and interpreted. Finally, examples are presented of occurrences when PRA was used to aid operating decisions.

Development of In-Service Inspection Priorities for Pressurized Water Reactor High-Pressure Injection System Components

The multiyear program entitled Nondestructive Evaluation Reliability for In-Service Inspection of Light Water Reactors, sponsored by the US Nuclear Regulatory Commission, is being conducted at the Pacific Northwest Laboratory. The goals of the program are to determine the reliability of current in-service inspection of pressure boundary systems and components and to develop recommendations that can ensure a suitably high inspection reliability. The long-term objective is to develop recommendations for improved in-service inspections. In meeting program objectives, a risk-based method has been developed to guide the development of inspection plans. The method uses results of probabilistic risk assessment and failure modes and effects analysis techniques to identify and prioritize the most risk-important systems and components for inspection at nuclear power plants. The Surry Nuclear Power Station Unit 1 was selected for demonstrating the methodology. The specific system addressed in this study was the high-pressure injection/recirculation (HPI/R) system. The results provide a risk-based ranking of components within the HPI/R system, which can be used to guide the development of improved inspection plans for nuclear power plants. This work will subsequently be used in supporting the revisions of the American Society of Mechanical Engineer's codes and standards.

Development of the advanced procedure for emergency operation using task allocation and synthesis of PRA results

Abstract An advanced emergency operating procedure (AEOP) for emergency operation is developed and discussed by focusing attention on the importance of the operator's role in emergency conditions for nuclear power plants (NPPs). Progress and improvement in the procedures now seem to be at a standstill insofar as the remaining problems cannot apparently be solved using the conventional approach. To overcome the complexity of emergency operating procedures (EOPs) and maintain the consistency of action steps according to plant emergency conditions, operator tasks are allocated according to their duties in the AEOP and a computerized operator aided system (COAS) is developed as an alternative to reduce the operator's burden and provide the detail action procedures. The PRA (Probabilistic Risk Assessment) results are synthesized in the AEOP using the event tree (ET) to give awareness and prediction of accident progression in advance dynamically and COAS is implemented on a SUN-4/75 workstation using C and Quintus TM prolog language. Finally, the time response for completing the required action is observed to evaluate the impact of the AEOP with COAS on operator performance during the loss of offsite power (LOOP) scenario with the full scope simulator of NPP at Kori. The results indicated that operator actions using AEOP are not only more consistent but are also able to provide earlier termination and mitigation of accidents.

Development of In-Service Inspection Plans for Nuclear Components at the Surry Unit 1 Nuclear Power Station

As part of the nondestructive evaluation reliability program sponsored by the US Nuclear Regulatory Commission at Pacific Northwest Laboratory, a methodology has been developed for establishing in-service inspection priorities of nuclear power plant components. The method uses results of probabilistic risk assessment in conjunction with the techniques of failure modes and effects analysis to identify and prioritize the most risk-important systems and components for inspection at nuclear power plants. Surry nuclear power station unit 1 was selected for demonstrating the methodology. The specific systems selected for analysis were the reactor pressure vessel, the reactor coolant, the low pressure injection including the accumulators, and the auxiliary feedwater. The results provide a risk-based ranking of components that can be used to establish a prioritization of the components and a basis for developing improved in-service inspection plans at nuclear power plants.

Estimates of Rupture Probabilities for Nuclear Power Plant Components: Expert Judgment Elicitation

This paper reports that as part of the nondestructive evaluation reliability program sponsored by the U.S. Nuclear Regulatory Commission (NRC), Pacific Northwest Laboratory (PNL) developed a risk-based method for establishing inspection priorities for systems and components at nuclear power plants. In this method, the results of probabilistic risk assessment (PRA) are used to estimate the safety consequences of component failures. The method also requires estimates of the probabilities of structural failures. Since sufficient operating experience data and detailed fracture mechanics analyses are not available, an expert judgment elicitation is conducted to estimate component rupture probabilities. (An expert judgment process is generally adapted from the NRC severe accident risk program).

Development of Generic In-Service Inspection Priorities for Pressure Boundary Systems

This paper reports on, to provide a technical basis for improved in-service inspection (ISI) plans, Pacific Northwest Laboratory (PNL) developed and applied a method that uses results of probabilistic risk assessment to establish piping system ISI priorities. In the PNL program, the feasibility of generic ISI guidances is being conducted in two phases. Phase I identifies and prioritizes the systems most relevant to plant safety. These evaluations lead to the development of comprehensive ISI guidances for pressure boundary systems and components that take place in Phase II.

Use of fuzzy set theory for level-I studies in probabilistic risk assessment

At a post-Chernobyl conference on Probabilistic Safety Assessment and Risk management (PSA '87) held in September 1987, the inadequacies of the current Probabilistic Risk Assessment (PSA) came into sharp focus. Highlighting the importance of improvements in the current PSA, Professor Rasmussen - a pioneer in the PSA methodology - made a strong plea for reduction of rather large uncertainties in the results of current PSA. Obviously, amongst the ways to achieve this, one of the approaches would be to encourage collection and use of accurate failure data. However as the state of affairs is, a better alternative would be to develop a methodology which could handle imprecision of data and uncertainties of models which are existence in the current PSA. Fuzzy Set Theory (FST) provides a natural framework to achieve the above goal and therefore the present paper is intended to emphasize and explore the possibility of the use of such a theory to develop a methodology which is computationally simple and easy to use in the quantitative assessment of failure probability of catastrophic events in PSA, particularly, in level-I studies. Some illustrative examples are provided to demonstrate the feasibility and effectiveness of such an approach. It is demonstrated that a general purpose computer code can be developed without much difficulty to recast the PRA studies to incorporate fuzzy probabilities.