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Toxicological assessments of skin sensitizers have progressed towards a higher reliance on non-animal methods. Current technological trends aim to extend the utility of non-animal methods to accurately characterize skin-sensitizing potency. The GARDskin Dose–Response assay has previously been described; it was shown that its main readout, cDV0 concentration, is associated with skin-sensitizing potency. The ability to predict potency from cDV0 in the form of NESILs derived from LLNAs or human NOELs was evaluated. The assessment of a dataset of 30 chemicals showed that the cDV0 values still correlated strongly and significantly with both LLNA EC3 and human NOEL values (ρ = 0.645–0.787 [p < 1 × 10−3]). A composite potency value that combined LLNA and human potency data was defined, which aided the performance of the proposed model for the prediction of NESILs. The potency model accurately predicted sensitizing potency, with cross-validation errors of 2.75 and 3.22 fold changes compared with NESILs from LLNAs and humans, respectively. In conclusion, the results suggest that the GARDskin Dose–Response assay may be used to derive an accurate quantitative continuous potency estimate of skin sensitizers. [ABSTRACT FROM AUTHOR]

Aims: The importation of rabid animals poses a continual threat to rabies freedom in the European Union (EU). Following the Russian invasion of Ukraine in 2022, the European Commission eased the rules on companion animal importations for Ukrainian refugees through derogations to the EU Pet Travel Scheme (EU PETS). As Ukraine remains endemic for canine rabies, this paper aimed to quantitatively assess whether the change in regulations affected the risk of rabies introduction to the EU. Method and Results: Transmission pathways for both EU PETS and derogations to this scheme were considered, as well as the scenarios of 100% compliance and reduced compliance within both schemes. Stochastic modelling was performed via a Monte Carlo simulation to calculate the median and 95% confidence intervals of the annual risk of rabies entry and the years between rabies entries into the EU. Following 100% compliance, the derogation scheme posed a significantly lower risk at a value of 3.63 × 10−3 (CI 95% 1.18 × 10−3–9.34 × 10−3) rabies entries per year in comparison to EU PETS where the risk was 4.25 × 10−2 (CI 95% 1.44 × 10−2–9.81 × 10−2). Despite a significantly lower risk as compared to EU PETS under 100% compliance, the derogation scheme was more sensitive to a reduction in compliance which resulted in a 74‐fold increase in risk. Given this, even under reduced compliance, the annual risk remained lower under the derogation scheme, although this was not statistically significant. Conclusion: The findings of this study suggest that a 4‐month period of quarantine, as modelled for the derogation scenario, could reduce the annual risk of rabies entry. This scheme may present a viable solution for the management of companion animal influxes in future crises. [ABSTRACT FROM AUTHOR]

Benchmark analysis is a general risk estimation strategy for identifying the benchmark dose (BMD) past which the risk of exhibiting an adverse environmental response exceeds a fixed, target value of benchmark response. Estimation of BMD and of its lower confidence limit (BMDL) is well understood for the case of an adverse response to a single stimulus. In many environmental settings, however, one or more additional, secondary, qualitative factor(s) may collude to affect the adverse outcome, such that the risk changes with differential levels of the secondary factor. Bayesian methods for estimation of the BMD and BMDL have grown in popularity, and a large variety of candidate dose–response models is available for applying these methods. This article applies Bayesian strategies to a mixed‐factor setting with a secondary qualitative factor possessing two levels to derive two‐factor Bayesian BMDs and BMDLs. We present reparameterized dose–response models that allow for explicit use of prior information on the target parameter of interest, the BMD. We also enhance our Bayesian estimation technique for BMD analysis by applying Bayesian model averaging to produce the BMDs and BMDLs, overcoming associated questions of model adequacy when multimodel uncertainty is present. An example from environmental carcinogenicity testing illustrates the calculations. [ABSTRACT FROM AUTHOR]

A safe and sustainable transition to hydrogen requires that the risks associated with hydrogen systems be rigorously investigated and quantified. Quantitative risk assessment (QRA) is a rigorous process to achieve this purpose. This paper reviews existing studies on the safety aspects of hydrogen pipelines and analyzes the applicability of existing methods and models for QRA of hydrogen transmission pipelines. This work identifies QRA research gaps for hydrogen transmission pipelines and outlines initial approaches to address them. According to our analysis, consequence modeling has received considerable attention, while limited work has been conducted to quantitatively analyze the failure causes of hydrogen pipelines. Most existing models for pipelines in general cannot be directly applied to hydrogen pipelines, yet they might serve as the basis for future hydrogen pipeline QRA models. The results provide insights into the most critical research needed to enable QRA for hydrogen pipelines. • Timely reviewed the existing studies on the safety aspects of hydrogen pipelines. • Analyzed the existing transmission pipeline systems and hydrogen's effect on them. • Analyzed existing methods and models for QRA of hydrogen transmission pipelines. • Identified research gaps in the QRAs of hydrogen transmission pipelines. [ABSTRACT FROM AUTHOR]

Typhoons are recurring meteorological phenomena in the southeastern coastal area of China, frequently triggering debris flows and other forms of slope failures that result in significant economic damage and loss of life in densely populated and economically active regions. Accurate prediction of typhoon-triggered debris flows and identification of high-risk zones are imperative for effective risk management. Surprisingly, little attention has been devoted to the construction of physical vulnerability curves in typhoon-affected areas, as a basis for risk assessment. To address this deficiency, this paper presents a quantitative method for developing physical vulnerability curves for buildings by modeling debris flow intensity and building damage characteristics. In this study, we selected the Wangzhuangwu watershed, in Zhejiang Province of China, which was impacted by a debris flow induced by Typhoon Lekima on August 10, 2019. We conducted detailed field surveys after interpreting remote sensing imagery to analyze the geological features and the mechanism of the debris flow and constructed a comprehensive database of building damage characteristics. To model the 2019 debris flow initiation, entrainment, and deposition processes, we applied the Soil Conservation Service-Curve Number (SCS-CN) approach and a two-dimensional debris flow model (FLO-2D). The reconstructed debris flow depth and extent were validated using observed debris flow data. We generated physical vulnerability curves for different types of building structures, taking into account both the degree of building damage and the modeled debris flow intensity, including flow depth and impact pressure. Based on calibrated rheological parameters, we modeled the potential intensity of future debris flows while considering various recurrence frequencies of triggering rainfall events. Subsequently, we calculated the vulnerability index and economic risk associated with buildings for different frequencies of debris flow events, employing diverse vulnerability functions that factored in uncertainty in both intensity indicators and building structures. We observed that the vulnerability function utilizing impact pressure as the intensity indicator tends to be more conservative than the one employing flow depth as a parameter. This comprehensive approach efficiently generated physical vulnerability curves and a debris flow risk map, providing valuable insights for effective disaster prevention in areas prone to debris flows. [ABSTRACT FROM AUTHOR]

Background: Quantitative risk assessment (QRA) for skin sensitization is used to derive safe use levels of sensitising fragrance ingredients in products. Post‐marketing surveillance of the prevalence of contact allergy to these ingredients provides relevant data to help evaluate the performance of these measures. Objectives: To determine a suitable patch test concentration for five fragrance materials that had hitherto not been tested on a regular basis. These concentrations are then to be used in a surveillance study with patch testing consecutive patients over an extended monitoring period. Materials and Methods: Furaneol, CAS.3658‐77‐3; trans‐2‐hexenal, CAS.6728‐26‐3; 4,8‐dimethyl‐4,9‐decadienal, CAS.71077‐31‐1; longifolene, CAS.475‐20‐7; benzaldehyde, CAS.10052‐7, were patch tested with other fragrance allergens in four clinics. Patch testing was conducted in three rounds, starting with the lowest concentrations of the five ingredients. The doses were increased in the subsequent rounds if no late‐appearing positive reactions and virtually no irritant reactions were reported. Results: Overall, 373 patients were tested. No positive allergic reaction was reported to the five ingredients. Patch test results of other fragrance allergens are reported. Conclusions: The highest test concentrations are each considered safe for patch testing consecutive patients. Further surveillance based on these preparations will evaluate the hypothesis that QRA‐driven consumer product levels of these fragrances can prevent sensitization. [ABSTRACT FROM AUTHOR]

The demand for hydrogen, a carbon–neutral fuel, is expected to increase in the coming decades. However, the current storage efficiency of gaseous hydrogen is poor. Liquid organic hydrogen carriers (LOHCs), which store hydrogen in liquid form under ambient conditions, show promise for on-site hydrogen refueling stations. Toluene-methylcyclohexane is one of the LOHC, it has advantages cost-effect and environmentally to large-scale hydrogen transportation, but it should be evaluated risk assessment based on the chemicals, because there is inherent harm from the properties like toxicity or flammability. Herein, quantitative risk assessment (QRA) results for worst-case scenarios, individual risk (IR), and societal risk (SR) for a methylcyclohexane-based on-site hydrogen refueling station (MHRS) are compared with those a gaseous hydrogen refueling stations (GHRS). The latter is more likely to have explosion-related accidents, while the former is more likely to have had fire-related accidents. Both show similarly high societal risks. The rupture of the MCH storage tank poses the most significant risk, but installing a dike reduces by 86%, thereby placing it within acceptable limits. Thus, the key risk factors for future on-site hydrogen refueling stations are identified and insights into mitigating them are offered. [ABSTRACT FROM AUTHOR]

Over large regions exposed to natural disasters, cascading effects resulting from complex or concatenated natural processes may represent a large portion of total risk. Populated high‐mountain environments are a major concern, and methods for large‐scale quantitative risk analyses are urgently required to improve risk mitigation. This article presents a comprehensive quantitative rockfall risk assessment over a large archetypal valley of the Andean mountains, in Central Chile, which integrates a wide spectrum of elements at risk. Risk is expressed as an expected damage both in monetary terms and casualties, at different scales relevant for decision making. Notably, total rockfall risk is divided into its main drivers, which allows quantifying seismically induced rockfall risk. For this purpose, the local seismic hazard is quantified and the yield acceleration, that is, acceleration required to initiate rockfall, is determined at the regional scale. The probability of failure is thereafter derived in terms of annual frequency of rockfall initiation and integrated in the quantitative risk assessment (QRA) process. Our results show the significant role of seismic activity as the triggering mechanism of rockfalls, and highlight elements at risk that have a major contribution to the total risk. Eventually a sensitivity analysis is conducted to (i) assess the robustness of obtained risk estimates to the data and modeling choices and (ii) identify the most influential assumptions. Our approach evidences the feasibility of large‐scale QRAs in sensitive environments and opens perspectives for refining QRAs in similar territories significantly affected by cascading effects and multihazards. [ABSTRACT FROM AUTHOR]

Toxoplasma gondii is a globally distributed zoonotic protozoan parasite. Infection with T. gondii can cause congenital toxoplasmosis in developing fetuses and acute outbreaks in the general population, and the disease burden is especially high in South America. Prior studies found that the environmental stage of T. gondii, oocysts, is an important source of infection in Brazil; however, no studies have quantified this risk relative to other parasite stages. We developed a Bayesian quantitative risk assessment (QRA) to estimate the relative attribution of the two primary parasite stages (bradyzoite and oocyst) that can be transmitted in foods to people in Brazil. Oocyst contamination in fruits and greens contributed significantly more to overall estimated T. gondii infections than bradyzoite-contaminated foods (beef, pork, poultry). In sensitivity analysis, treatment, i.e., cooking temperature for meat and washing efficiency for produce, most strongly affected the estimated toxoplasmosis incidence rate. Due to the lack of regional food contamination prevalence data and the high level of uncertainty in many model parameters, this analysis provides an initial estimate of the relative importance of food products. Important knowledge gaps for oocyst-borne infections were identified and can drive future studies to improve risk assessments and effective policy actions to reduce human toxoplasmosis in Brazil.

This paper primarily investigates the influence of spatial layout on the safety risks associated with urban natural gas pipelines. Drawing from the actual spatial configuration around the pipeline and local climatic characteristics, the study delves into the distribution patterns of natural gas leakage diffusion and explosion accident consequences, considering various factors such as leakage apertures, soil porosity, and spatial layouts. By integrating the outcomes of the consequence analysis, the quantitative risk of urban natural gas pipelines, accounting for the impact of spatial layout, was computed and juxtaposed with the results of traditional two-dimensional risk analysis. The findings underscore that spatial layout exerts a substantial impact on risk distribution, with significantly elevated risk values in more congested spatial layouts. Additionally, the introduction of a barrier along the pipeline leakage path resulted in a 91.4% reduction in risk compared to scenarios without obstruction. It is evident that the spatial layout surrounding the pipeline plays a pivotal role in influencing the distribution of pipeline failure risks, establishing the spatial environment as a critical factor in risk analysis. This study offers valuable insights for urban land planning, safety control line establishment, and related considerations.

Water electrolysis is the primary production technology for clean hydrogen, and thus ensuring safe and reliable deployment and operation of electrolyzers is essential to global sustainability efforts. In this paper, electrolytic hydrogen production pathways and upcoming deployment capacities are briefly discussed. Then we examine the main risk and reliability challenges and analyze the state of the art in quantitative risk assessment (QRA) of electrolysis technologies. We identify gaps in electrolysis QRA studies and present recommendations to enable more robust risk and reliability analysis for these technologies. Recommendations and opportunities for research to fill these gaps include: developing and adopting a system reliability approach in electrolysis risk analysis, developing and disseminating detailed electrolysis system design documentation, developing reliability data collection and analysis methods and tools, conducting importance measures analysis, conducting uncertainty analysis and propagation, developing electrolysis QRA standards, and creating programs to develop and educate the hydrogen risk and reliability workforce. • Examined state-of-the-art in QRA studies for water electrolysis technologies. • Identified main electrolysis risk and reliability assessment modelling approaches. • Identified five key gaps in the electrolysis QRA studies examined. • Synthesized seven research opportunities to enhance electrolysis QRA validity. [ABSTRACT FROM AUTHOR]

With the increasing global reliance on maritime oil transportation, oil spills pose significant environmental hazards to coastal ecosystems. This study presents a comprehensive quantitative framework for assessing oil spill risks along the Jiaozhou Bay coastline in China. The research begins with an analysis of historical spill data to construct representative oil spill simulation scenarios. The advanced MEDSLIK-II oil spill prediction model is then employed to simulate oil spill trajectories under these scenarios, focusing on key parameters such as oil thickness and mass to evaluate the hazard levels associated with each scenario. Subsequently, the Environmental Sensitivity Index (ESI) is utilized to assess the vulnerability of coastal zones, while Geographic Information System (GIS) techniques are employed for a spatial analysis and visualization of the results. The case study, covering a 26.87 km stretch of the Jiaozhou Bay coastline, reveals 10 high-risk zones with a total length of 8561.2 m. These areas are predominantly characterized by saltwater marshes, brackish water marshes, and inundated low-lying areas, with ESI rankings of 9 and 10, accounting for 24% of the 339 analyzed segments. The modeling results indicate that in the simulated scenarios, oil spills originating from the Huangdao Oil Port and Qianwan Port pose the greatest risks, with potential impacts extending up to 12 km and 15 km along the coastline, respectively. The study highlights the importance of considering multiple factors, including oil spill trajectories, coastal geomorphology, and ecological sensitivity, in comprehensive risk assessments. The proposed framework demonstrates potential for adaptation and application to other coastal regions facing similar oil spill risks, contributing to the advancement of coastal management practices worldwide. [ABSTRACT FROM AUTHOR]

Hydrogen refueling stations (HRSs) are among the most important infrastructures for fuel cell vehicles. However, the safety issue of HRSs has become a key constraint to the wide application and development of hydrogen energy. This article presents a quantitative risk assessment of the first liquid HRS (LHRS) in China and conducts a comprehensive assessment in terms of both individual (IR) and societal risks (SRs). The results showed that both the IRs and SRs related to the LHRS exceeded the risk acceptance criteria. The rupture of the flexible hose of the dispenser and the leak from the compressor are the main contributors to these risks. On the other hand, implementing appropriate mitigation measures on the level of the LHRS dispenser and compressor, including the addition of breakaway couplings in the flexible hose of the dispenser, the installation of hydrogen detection sensors, the arrangement of automatic and manual emergency shutdown buttons, and the elevation of the compressor, is capable of reducing the risk of the LHRS to be within the risk acceptance criteria. [ABSTRACT FROM AUTHOR]

Accidental release of liquid CO 2 can pose a certain risk to people, animals and equipment near release points. In addition to asphyxiation, cryogenic burns and dry-ice inhalation are potential risks that must be considered. In this study, a source model was established considering the formation of dry ice, which can quickly provide the inlet boundary condition for the computational fluid dynamics (CFD) model to simulate the jet dispersion of liquid CO 2. The size distribution of the dry ice particles was described by the Rosin-Rammler expression. The effects of size distribution, initial pressure, liquid mass fraction and orifice size on the temperature, velocity, CO 2 concentration, mass flow rate (nonsublimated dry ice) and survival distance were analysed. A quantitively risk assessment (QRA) method was used to evaluated the joint impact of source strength, dose-effect and impingement distance. The hazard distances associated with asphyxiation, cryogenic burn and dry ice inhalation were assessed. The results showed that the prediction errors of the mass flow rate using the source model were lower than 20 %. The temperature, velocity and CO 2 concentration predicted by the CFD model agree well with the experimental results. The hazard distance was very dependent on and sensitive to the source strength and dose-effect. [Display omitted] [ABSTRACT FROM AUTHOR]

In the absence of epidemiological data, there is a need to develop computational models that convert in vitro findings to human disease risk predictions following toxicant exposure. In such efforts, in vitro data can be evaluated in the context of adverse outcome pathways (AOPs) that organize mechanistic knowledge based on empirical evidence into a sequence of molecular-, cellular-, tissue-, and organ-level key events that precede an adverse outcome (AO). Here we combined data from advanced in vitro organotypic airway models exposed to combustible cigarette (CC) smoke or Tobacco Heating System (THS) aerosol with an AOP for increased oxidative stress leads to decreased lung function. The mathematical modeling predicted reduced risk of decreased ciliary beating frequency (CBF) based on oxidative stress measurements and reduced risk of decreased mucociliary clearance (MCC) based on CBF measurements in THS aerosol- compared with CC smoke-exposed cultures. To extend the predictions to the AO of decreased lung function, we leveraged human MCC data from current smokers, nonsmokers, former smokers, and users of heated tobacco products. This approach provided a plausible prediction of diminished reduction in lung function in response to THS use compared with continued smoking. The current approach may also present a basis for an integrated approach to testing and assessment of tobacco products for future regulatory decision-making. • AOP 411 Oxidative Stress Leading to Decreased Lung Function is considered. • A quantitative model (qAOP) is proposed that uses in vitro /human data as input. • The qAOP enables assessing the risk of the adverse outcome Decreased Lung Function. • It is applied to subjects switching from smoking to using heated tobacco products. • The qAOP results predict the reduction of the adverse outcome risk after switching.. [ABSTRACT FROM AUTHOR]

Existing natural gas pipelines can facilitate low-cost, large-scale hydrogen transportation and storage, but hydrogen may entail safety challenges. These challenges stem from hydrogen's different properties compared to natural gas, such as higher ignition probability, different flame behavior, and potential for hydrogen embrittlement. Although risk assessments for hydrogen pipelines are increasing, the impact of hydrogen on the risk of third-party excavation damage (TPD), the major cause of pipeline incidents in the U.S., has received little attention. This work presents the SHyTERP model for Safe Hydrogen Transportation and Excavation Risk Prevention for Pipelines. The model incorporates causal models, excavation damage and pipeline failure statistics, and validated physical models of hydrogen and natural gas release and jet flame behavior. Through four case studies, the model compares the TPD risks of hydrogen and natural gas pipelines, offering insights and recommendations for the safe implementation of hydrogen in existing pipelines. • Presents a new model, SHyTERP, which assesses excavation risk in hydrogen pipelines via Bayesian networks. • SHyTERP integrates multi-source data relevant to modeling natural gas and hydrogen pipeline excavation risk. • SHyTERP identifies key risk drivers for excavation damage in hydrogen and natural gas pipelines. • SHyTERP offers timely safety insights and recommendations for managing risk for hydrogen and natural gas pipelines. • SHyTERP provides a baseline for future pipeline risk assessments. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: In August 2004 a series of debris flows caused significant disruption to the Scottish (strategic) Trunk Road Network. The subsequent Scottish Road Network Landslides Study identified a number of sites considered to be at highest risk. Some of these sites have been the subject of formal quantitative assessment of the risk from debris flow to mobile road users in vehicles. The A82 in Glen Coe has the added complication that two car parks have developed on debris fans exposing significant numbers of people to the risk while, they are essentially static and largely outside their vehicles. Methodology: The risk to road users is determined using a previously developed probabilistic methodology for mobile road users (mobile elements at risk) and a new and related methodology developed for static road users (static elements at risk) is described and applied. Within the latter, an entirely new metric of Annual Average Daily Visits is used to allow the temporal component of the probability of a landslide impacting a person to be determined given the occurrence of an event. Results: While Personal Individual Risk is at an acceptable level, including for frequent users, the risk presented to society as a whole presents a rather different picture; this is largely due to the number of visitors. The results assess the overall, societal risk for mobile elements at risk as As Low As reasonably Practicable, being at a similar level to other sites, albeit with a higher risk associated with higher numbers of fatalities. The results for the static elements at risk on the other hand suggest that the risks are classified as Unacceptable for higher numbers of fatalities. The assessment of the total societal risk, for mobile and static elements at risk, at the A82 Glen Coe suggests As Low As Reasonably Practicable for low numbers of fatalities but classify as Unacceptable for higher numbers of fatalities (around 20 to 250). [ABSTRACT FROM AUTHOR]

Hydrogen refueling stations are increasingly being built in densely populated urban areas and operating under high temperature and pressure conditions. Therefore, the safety of hydrogen refueling stations has received great attention. In present work, a new dynamic quantitative risk assessment method is established for hydrogen leakage at refueling stations based on Bayesian networks (BN). Firstly, risk factors are identified using a fault tree, considering multiple equipment operating states. A Dynamic Bayesian Network (DBN) is established, and event tree analysis is combined to determine accident consequence probabilities. Furthermore, a Bayesian Domino Model is constructed to assess the impact of accident consequence propagation on the probability and risk of hydrogen leakage accidents. Through a typical case study of an off-site hydrogen refueling station, the practicality of the proposed method is validated, the risk factors and safety barriers, the dynamic evolution of hydrogen leakage probabilities within a three-year period are obtained. The probability of hydrogen leakage in hydrogen station is 2.69 × 10−2 in the first month and 2.45 × 10−2 in the 36th month. Simultaneously, the maximum personal risk value for the first month is 5.07 × 10−4. When the Domino effect is considered, the maximum accident probability is 1.96 × 10−3 is obtained in the first month, and the equipment unit with the greatest impact of the accident is A2. Measures were also proposed to reduce hydrogen leakage risks during the operation of off-site hydrogen refueling stations, with an emphasis on prioritizing safety measures for hydrogen storage bundles and risk mitigation strategies. [Display omitted] • Risk assessment for supply at tube trailers hydrogen refueling stations was finished. • DBN for hydrogen leakage and BN for the accident domino effect were established. • The dynamic probability, key risk factors and safety barriers were obtained. • The probability of the accident domino effect at various levels were proposed. • Individual risk values and ranges of accident damage zones were confirmed. [ABSTRACT FROM AUTHOR]

The construction of hydrogen refueling stations (HRSs) is crucial in supporting the comprehensive popularization of hydrogen energy. However, many countries have difficulties expanding hydrogen infrastructure due to the high risk of hydrogen. In this work, a Computational Fluid Dynamics three-dimensional model is combined with individual lethality probability models to study the consequences of a leak explosion at the main components within a HRS. Two new canopies of hydrogen dispensers are designed to improve hydrogen evacuation efficiency. Results indicate that the safety distance based on the individual risk between the main equipment in the station can be reduced by 21.7%–67.0% compared with the actual layout distance. And the safety distance between dispensers, which is not specified in Chinese standards, is proposed to be 6.8 m. When the inclination angle of the dispenser canopy does not exceed 15° and the width does not exceed 12 m, the hydrogen leaking from the top of the dispenser has the smallest retention volume. Moreover, the tube trailers are advised to avoid parking in HRSs due to the increased consequences of explosive accidents. [Display omitted] • Various leakage and explosion accident scenarios of main components in HRS are analyzed. • The safety distance between the main components based on individual risk can be further reduced. • Two newly designed canopies significantly improve the hydrogen evacuation efficiency. • Effect law of long tube trailers on the explosion hazard range and overpressure peak is obtained. [ABSTRACT FROM AUTHOR]

The potential risks associated with debris flows have significantly increased due to changes in global climate, population growth, and economic development. Despite the high susceptibility of debris flows in the Wenchuan earthquake-affected area, few studies have focused on quantitative risk assessment methods for debris flows. To overcome this shortcoming, we proposed an integrated approach by using a probability-based model and numerical simulations to quantify the expected direct economic losses of buildings for debris flows under multiple rainfall intensity scenarios. First, we simulated the hazard processes of debris flows with recurrence periods of 20, 50, 100, and 200 years and obtained the distribution of debris flow intensities defined by the momentum flux. Then, we assessed the direct economic losses for each building related to different recurrence periods based on fragility curves and debris flow intensity maps. The results show that the risk loss of different hazard scenarios increases dramatically with an increase in debris flow magnitude. This methodology provides visual and quantitative risk assessment for specific buildings affected by debris flows, enabling authorities and decision-makers to reduce risk and optimize risk management strategies. It is a rapid and effective way to assess the capacity of the built environment to resist the risk of debris flows in the Wenchuan earthquake-affected areas. [ABSTRACT FROM AUTHOR]

Bacitracin is an antimicrobial used in the feed or water of poultry in the U.S. for the prevention, treatment, and control of clostridial diseases such as necrotic enteritis. Concern has been raised that bacitracin can select for antimicrobial-resistant bacteria that can be transmitted to humans and subsequently cause disease that is more difficult to treat because of the resistance. The objective of the present study was to perform a quantitative risk assessment (QRA) to estimate the potential risk in the U.S. of human infection with antimicrobial-resistant Enterococcus faecalis and E. faecium derived from chicken and turkey products as a result of bacitracin usage in U.S. poultry. The modeling approach estimated the annual number of healthcare-associated enterococcal infections in the U.S. that would be resistant to antimicrobial therapy and that would be derived from poultry sources because of bacitracin use in poultry. Parameter estimates were developed to be “maximum risk” to overestimate the risk to humans. While approximately 60% of E. faecalis and E. faecium derived from poultry were predicted to possess bacitracin resistance based on the presence of the bcrABDR gene locus, very few human-derived isolates possessed this trait. Furthermore, no vancomycin or linezolid-resistant strains of E. faecalis or E. faecium were detected in poultry sources between the years 2002 and 2019. The model estimated the number of antimicrobial-resistant E. faecalis and E. faecium cases per year that might resist therapy due to bacitracin use in poultry as 0.86 and 0.14, respectively, which translates to an annual risk estimate for E. faecalis of less than 1 in 350 million and for E. faecium of less than 1 in 2 billion for members of the U.S. population. Even with the use of risk-maximizing assumptions, the results indicate that there is a high probability that the use of bacitracin according to label instructions in U.S. poultry presents a negligible risk to human health.

Toxicological assessments of skin sensitizers have progressed towards a higher reliance on non-animal methods. Current technological trends aim to extend the utility of non-animal methods to accurately characterize skin-sensitizing potency. The GARDskin Dose–Response assay has previously been described; it was shown that its main readout, cDV0 concentration, is associated with skin-sensitizing potency. The ability to predict potency from cDV0 in the form of NESILs derived from LLNAs or human NOELs was evaluated. The assessment of a dataset of 30 chemicals showed that the cDV0 values still correlated strongly and significantly with both LLNA EC3 and human NOEL values (ρ = 0.645–0.787 [p < 1 × 10−3]). A composite potency value that combined LLNA and human potency data was defined, which aided the performance of the proposed model for the prediction of NESILs. The potency model accurately predicted sensitizing potency, with cross-validation errors of 2.75 and 3.22 fold changes compared with NESILs from LLNAs and humans, respectively. In conclusion, the results suggest that the GARDskin Dose–Response assay may be used to derive an accurate quantitative continuous potency estimate of skin sensitizers.

Storm surge is a common nature disaster in China southern coastal area, which usually causes heavy human life and economic losses. With the economic development and population concentration of coastal cities, the storm surges may result in more impacts and damage in the future. Therefore, it is of vital importance to conduct risk assessment to identify high-risk areas and evaluate economic losses. However, quantitative study of storm surge risk assessment in undeveloped areas of China is difficult, since there is a lack of building characters and damage assessment data. Aiming at the problem of data missing in undeveloped areas of China, this paper proposes a methodology for conducting storm surge risk assessment quantitatively based on deep learning and geographic information system (GIS) techniques. Five defined storm surge inundation scenarios with different typhoon return periods are simulated by coupled FVCOM-SWAN model, the reliability of which is validated using official measurements. Building footprints of the study area are extracted through TransUNet deep learning model and Remote Sensing Image (RSI), while building heights are obtained through Unmanned Aerial Vehicle (UAV) measurement. Subsequently, economic losses are quantitatively calculated by combing the adjusted depth-damage functions and overlay analysis of the buildings exposed to storm surge inundation. Zonation maps of the study area are illustrated to display the risk levels according to the economic losses. The quantitative risk assessment and zonation maps can help the government to make storm surge disaster prevention measures and optimize land use planning, and thus to reduce the potential economic losses of the coastal area. [ABSTRACT FROM AUTHOR]

As hydrogen refueling stations come into increasing use and being common, both benefit and safety are required. To promote its use, an optimized trade-off must be reached for hydrogen station configurations. We constructed a dynamic physical model of the station that enables quantitative evaluation of benefit and risk for a trade-off study, aiming to formulate a technical standard for hydrogen refueling stations that would realize high-level safety and rationalize the equipment configuration and operation. The proposed model enables a quantitative evaluation of both the hydrogen refueling time during normal operation and external leakage under several accident scenarios. This paper discusses the modeling concept and approach of the proposed model and reports quantitative verification results of the proposed model based on past experimental test results. In this study, capability of the proposed model for quantitative evaluation of dynamic behavior of hydrogen during refueling operation at the station reflecting its configuration and operation condition was demonstrated. This feature of the proposed model also provides a physical and realistic dynamic leakage rate for calculating individual risks compared to the conventional risk analysis method. • A dynamic physical model of Japanese hydrogen refueling station was constructed. • Verification results of the model based on past experimental test results were reported. • The model enables quantitative evaluation of dynamic behavior of hydrogen during refueling. • Transient leakage flow rate depending on the leak location was evaluated using the model. • The model provides physical and realistic leakage rate for risk analysis. [ABSTRACT FROM AUTHOR]

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. To address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents. • Developed requirements for hydrogen component reliability databases. • Developed HyCReD database structure for system, incident, and maintenance data. • Created definitions for data elements and failure modes. • Built generic component hierarchy for H2 fueling stations from public designs. • Demonstrated HyCReD database usability by extracting data from event narratives. [ABSTRACT FROM AUTHOR]

Natural hazards constantly threaten the sustainable construction and operation of railway engineering facilities, making railway disaster risk assessment an essential approach to disaster prevention. Despite numerous studies that have focused on railway risk assessment, few have quantified specific damages, such as economic losses and human casualties. Meanwhile, the mechanism of impact damage from various disasters on railway facilities and the propagation of functional failure in railway systems have not been thoroughly summarized and addressed. Thus, it is essential to conduct effective quantitative risk assessments (QRAs) to facilitate the sustainable design, construction, and operation of rail infrastructure. This paper aimed to review and discuss the systematic development of risk assessment in railway engineering facilities. Firstly, we highlighted the importance of disaster QRA for railway facilities. Next, numerous limitations of QRA methods were concluded after conducting a comprehensive review of the risk assessment research applied to railway facilities, such as bridges, tunnels, and roadbeds. Furthermore, true QRA (TQRA) application in railway engineering has faced several significant challenges. Therefore, we proposed a promising TQRA strategy for railway engineering facilities based on the integration of building information modeling (BIM) and geographic information systems (GIS). The proposed BIM+GIS technology is expected to provide sustainable future directions for railway engineering QRA procedures. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the risk of food poisoning caused by Listeria monocytogenes in Jinhua ham processed using modern processing techniques. The parameters affecting the growth of Listeria monocytogenes during the production and sale of Jinhua ham, such as pH, water activity, temperature, lactic acid bacteria quantity, were investigated. The initial contamination rate of Listeria monocytogenes in raw pork was also evaluated. Listeria monocytogenes growth model and deactivation model were used to evaluate the exposure levels to Listeria monocytogenes in Jinhua ham. The risk of listeriosis after consumption of ready-to-eat Jinhua ham slices in different populations was explored. The results showed that the contamination level of Jinhua ham in the market was −9.47~7.05 lg CFU/g (90% confidence interval). The probability of listeriosis from ready-to-eat Jinhua ham slices consumption per portion consumed in healthy adults and at-risk populations were estimated with average values of

Introduction: Pipelines are widely used to transport large volumes of oil and gas over long distances. Risk assessment can help identify risk factors and create an appropriate action plan and strategy to reduce or eliminate them. The main goal of this research is to provide a method for assessing the risk of pipelines based on the Fuzzy Inference System (FIS), creating a systematic format that is expected to be a more effective, accurate, and reliable model for controlling risks related to oil and gas pipelines. Material and Methods: In this article, fuzzy logic is used to model uncertainty and present a model for assessing pipeline risk. The Muhlbauer method, one of the most common risk assessment methods for oil and gas pipelines, has been employed to determine critical factors affecting the lines. This method has been implemented using the Mamdani algorithm and based on expert knowledge in the fuzzy logic toolbox of MATLAB software. To validate the results of the proposed model, data from the interphase pipelines of the fifth refinery of the South Pars Gas Field have been used as a study sample. Results: The findings from the implementation of the model created in South Pars Phases 9-10 pipelines (on shore) show that the studied pipelines are divided into three parts (A, B, and C) based on indicators such as population density and equipment deployment. Part C of the pipeline has the highest risk, with third-party damage and design being the most important factors affecting it. Part B has the lowest level of risk and results in the fewest consequences for human accidents. It was also observed that corrosion is essential in increasing leakage and risk in all three pipeline parts. Conclusion: To verify the developed model, the inter-phase shore pipe of phase 9-10 refinery in the South Pars Gas Field was considered as a case study. The findings indicate that the proposed method provides more accurate and reliable results than traditional methods. Factors such as improper operation, dispersion, receptors, leakage volume, and product risk, which are other factors affecting pipeline risk, were not considered in traditional methods. Therefore, the risk level of oil and gas pipelines can be calculated using this model as a comprehensive and intelligent tool.

Introduction: Gas pressure reduction stations are one of the most important parts of natural gas distribution networks. Risk assessment in operational units is a suitable method to assess risks, and their results can be used for management and decision-making regarding control and reduction of its consequences without critical concern. In other words, risk assessment is a process that identifies risks, assesses losses and determines risk characteristics. The present study aimed to model possible accidents, the subsequent evaluation of the consequences, and determination of safe boundaries in the suburban natural gas pressure reduction station located in the Bromi area of Ahvaz city using PHAST software. Materials and Methods: In this study, possible scenarios based on the investigated background and utilizing the process data of the studied gas pressure reduction station, such as temperature, gas pressure, gas analysis, and meteorological data, and also using Pasquil's classification of atmospheric conditions the safe boundaries in the suburban natural gas pressure reduction station was investigated using PHAST software version 22.8 and. For this purpose, 6 possible scenarios were investigated in the selected atmospheric classes as well as the worst possible conditions. The consequences were evaluated based on different states of gas discharge, gas release, flash fire, sudden fire, and explosion. Results: Based on the obtained results, the areas with high-risk potential were related to gas release and explosion, respectively. Also, the highest risk range belonging to scenario number five was reported for a gas explosion with atmospheric class F and wave intensity of 0.02068 bars and equivalent to 358.5 meters. In this range, according to the damage caused by the explosion, with a probability of 95%, without serious damage, 50% of the windows will be broken, and therefore it can cause human injuries. Based on this, the safe distance in this station was determined to be 358.5 meters. Conclusion: Based on concerns about the lack of risk assessment studies over the initial phases and during the operation of the station, the study shows that determining the safe boundaries and high-risk areas along with the priority of risk reduction is very necessary. It can be concluded that the modeling of accidents and the evaluation of the resulting consequences along with the determination of safe boundaries is one of the basic factors in the health of the working environment of personnel and the general public.

Background and Aim: Pig farming is a livelihood activity undertaken by many rural communities in Tanzania. However, pigs in rural communities become infected with Taenia solium, a zoonotic parasite leading to porcine cysticercosis (PCC). Thus, routine meat inspection is fundamental in ensuring that the meat consumed is PCC-free. However, routine meat inspection is constrained by low sensitivity as a diagnostic test. Regardless of its low sensitivity, at the local level, no substitute tool would potentially lead to meat being risk-free for human infection. This study aimed at quantifying the risk of humans getting exposed to T. solium taeniasis through the consumption of pork approved safe for human consumption by employing a quantitative risk assessment (QRA) model. Materials and Methods: A cross-sectional study employing a quantitative risk assessment technique was conducted to quantify the risk of human infection in Mpwapwa District through exposure to T. solium infection through consumption of officially inspected pork. The input parameters in this study were simulated in @risk software to obtain the risk of exposure and the risk factors for exposure to T. solium taeniasis. Results: The risk of one getting exposed to T. solium taeniasis/cysticercosis (TSTC) through consumption of pork approved for human consumption was found to be 0.018 (95% confidence interval [CI] = 0.00–0.0250). Likewise, the probability that a cyst is localized in a pork portion was found to be the most influencing input risk factor of getting exposed to TSTC. Furthermore, the probability of developing T. solium taeniasis was estimated to be 0.73605 (95% CI = 0–0.950) when infected undercooked pork portion is consumed and 0.99652 (95% CI = 0.98161–0.99908) from consuming raw pork portion. Likewise, about 47 (95% CI = 42–52) people who consumed undercooked pork and 26 (95% CI = 22–30) who consumed raw pork would get infected in Mpwapwa District per year. Conclusion: The results from this study are anticipated to create public awareness of the problem and promote the use of one-health approach in the control and prevention of the consumption of infected pork.

Inter-basin water diversion projects have led to accelerated colonization of aquatic organisms, including the freshwater golden mussel (Limnoperna fortunei), exacerbating global biofouling concerns. While the influence of environmental factors on the mussel's invasion and biofouling impact has been studied, quantitative correlations and underlying mechanisms remain unclear, particularly in large-scale inter-basin water diversion projects with diverse hydrodynamic and environmental conditions. Here, we examine the comprehensive impact of environmental variables on the establishment risk of the golden mussel in China's 1432-km-long Middle Route of the South-to-North Water Diversion Project. Logistic regression and multiclass classification models were used to investigate the environmental influence on the occurrence probability and reproductive density of the golden mussel. Total nitrogen, ammonia nitrogen, water temperature, pH, and velocity were identified as crucial environmental variables affecting the biofouling risk in the project. Logistic regression analysis revealed a negative correlation between the occurrence probability of all larval stages and levels of total nitrogen and ammonia nitrogen. The multiclass classification model showed that elevated levels of total nitrogen hindered mussel reproduction, while optimal water temperature enhanced their reproductive capacity. Appropriate velocity and pH levels were crucial in maintaining moderate larval density. This research presents a quantitative analytical framework for assessing establishment risks associated with invasive mussels, and the framework is expected to enhance invasion management and mitigate biofouling issues in water diversion projects worldwide.

The average temperature of the Earth has risen due to the accumulation of greenhouse gases emitted from the usage of fossil fuels. The consequential climate changes have caused various problems, fueling the growing demand for environmentally friendly energy sources that can replace fossil fuels. Batteries and hydrogen have thus been utilized as substitute energy sources for automobiles to reduce fossil fuel consumption. Consequently, the number of hydrogen refueling stations is increasing due to an increase in the number of hydrogen-powered vehicles. However, several incidents have been reported in the United States of America and Japan where hydrogen refueling stations have been operating for a long time. A risk assessment of hydrogen refueling stations operating in urban areas was performed in this study by calculating the risk effect range using a process hazard analysis tool (PHAST) v8.7 from DNV-GL and a hydrogen risk assessment model (HyRAM) from Sandia National Laboratories (SNL). The societal risk was assessed through a probit model based on the calculation results. The assessment results showed that the risk caused by jet fire and overpressure in an incident is lower than the 'as low as reasonably practicable' (ALARP) level. [ABSTRACT FROM AUTHOR]

Traditional information security risk assessment (RA) methodologies and standards, adopted by information security management systems and frameworks as a foundation stone towards robust environments, face many difficulties in modern environments where the threat landscape changes rapidly and new vulnerabilities are being discovered. In order to overcome this problem, dynamic risk assessment (DRA) models have been proposed to continuously and dynamically assess risks to organisational operations in (near) real time. The aim of this work is to analyse the current state of DRA models that have been proposed for cybersecurity, through a systematic literature review. The screening process led us to study 50 DRA models, categorised based on the respective primary analysis methods they used. The study provides insights into the key characteristics of these models, including the maturity level of the examined models, the domain or application area in which these models flourish, and the information they utilise in order to produce results. The aim of this work is to answer critical research questions regarding the development of dynamic risk assessment methodologies and provide insights on the already developed methods as well as future research directions. [ABSTRACT FROM AUTHOR]

Accidents involving the transportation of hazardous materials (hazmats) may cause fatalities, injuries, and property damage along the transport route. It is thus imperative to adopt and implement a risk assessment and management framework that can be easily employed by decision/policymakers. This paper presents a quantitative risk assessment (QRA) framework to select the safest route for the transport of hazardous materials utilizing an accident database and human vulnerability models. Statistical models from relevant accident studies are used to determine the accident enhancing/mitigating contributions of different road geometrical features, which are then applied to data derived from an available database to determine accident frequencies. Consequences of accidents with humans are assessed using ALOHA and vulnerability models, while the risk is determined by combining both accident frequencies and consequences. The proposed method has been applied in a case study to assess the relative risks involved in LPG transportation along two different routes in Bangladesh and to identify the safer route. The effectiveness of a number of risk reduction measures has been assessed to manage risks, and the results of the risk assessment have been spatially presented on a geographical map. This map will help decision makers to make routing decisions and identify route sections that are most at risk to take appropriate emergency response actions and allocate medical and support services during emergencies. [ABSTRACT FROM AUTHOR]

Hazardous production facilities contain numerous technical devices, the reliability assessment of which is a part of quantitative risk assessment. The paper considers the pressure valve as a safety system element of equipment operating under excessive pressure and evaluates its reliability (survival function value) during the operational period. Valve reliability during the wear-out period has been modeled to assess wear-out period influence on this element failure probability. Modeling was carried out by approximating the failure rate tabular values obtained based on statistical data. Approximation was carried out by: a second-degree polynomial, the Weibull distribution law and a power function. Comparison of the obtained quantitative estimates with the element failure probability, calculated without taking into account the wear-out period, showed necessity of wear-out period influence consideration in risk assessment procedure. [ABSTRACT FROM AUTHOR]

Landslide risk assessment (LRA) is of great significance to hazard prevention and mitigation. However, the historical landslide information is incomplete in most areas, which makes the landslide quantitative risk assessment (LQRA) extremely difficult. This research proposed a set of frameworks for LQRA, so as to achieve LQRA in areas with incomplete historical landslide information. Firstly, we constructed the convolutional neural network (CNN) model suitable for landslide susceptibility assessment (LSA) by studying the structure and hyperparameters optimization of CNN. Secondly, we proposed a method to calculate the temporal probability by using the Poisson model based on the time range of historical landslides occurrence, and then conducted landslide hazard assessment (LHA). Then, we established a mathematical model for landslide intensity of shallow landslide based on landslide area and slope, aiming at solving the problem that it is difficult to calculate landslide intensity due to the lack of landslide volume and velocity. Based on the landslide intensity and the hazard-resistant capacity of the element at risk, we assessed the landslide vulnerability. Finally, population risk map and economic risk map are obtained based on the landslide hazard, vulnerability, and estimated value of the elements at risk. The proposed LQRA framework was applied to Tumen City, China for testing and field validation. From the results, the CNN model built can help improve the accuracy of LSA. The proposed temporal probability calculation method is conducive to the completion of LHA in areas with incomplete historical landslide information. The established landslide intensity mathematical model has certain credibility. Since the landslide risk map is obtained through appropriate simplification and substitution estimation, its final value cannot be used as an accurate prediction of future losses, but it can be used as a reference for the extent of potential losses, so as to determine the areas where hazard prevention and mitigation measures need to be taken. [ABSTRACT FROM AUTHOR]

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This article updates earlier publications of an ongoing research project on worldwide fire incidents that occurred in tank farms, which store products ranging from low flashpoint materials to crude and heavier hydrocarbons. The incidents and information in the database came from almost 300 sources, including technical reports and news releases. This research supports tank farm hazard identification/risk assessment and the reliability analysis of fire water protection systems (FWS). The research provides valuable insights such as the frequency of tank farm fires, the frequency of boilovers, the frequency of injuries/fatalities, the probability of failure of the FWSs, and the time to extinguish (TtEx) the fires. When the database provides sufficient information, these numbers appear as a function of the stored product. The data also allows plotting TtEx as a function of time for over a century. Additionally, this article illustrates the results of a confidence level analysis of the risk assessment of a distribution terminal that handles low and high‐flashpoint products. [ABSTRACT FROM AUTHOR]

As the decision‐making basis for "safety" in risk management and risk assessment activities, acceptable risk has always been an important topic of risk‐related research. Based on the records in the Science Citation Index Expanded database and Social Sciences Citation Index database via the Web of Science Core Collection, 1124 articles or reviews related to acceptable risk in engineering and operations research and management science were retrieved. These documents, published between 1961 and 2021, covered 3056 authors, 75 countries/territories, 1296 institutions, and 323 journals. In this study, bibliometric data such as annual growth trends were analyzed by using descriptive statistics. Through the co‐occurrence maps created by CiteSpace and Gephi, the most productive and influential countries/territories, institutions, and authors as well as their cooperation networks were identified. Further analysis was conducted to determine the core publications and publication sources in this field through co‐citation analysis. Insights into focus areas and research topics over time were obtained through keyword co‐occurrence analysis. This study provides a macroscopic overview of acceptable risk research and may help researchers better understand this research field and predict its dynamic directions. [ABSTRACT FROM AUTHOR]

With the increasing global reliance on maritime oil transportation, oil spills pose significant environmental hazards to coastal ecosystems. This study presents a comprehensive quantitative framework for assessing oil spill risks along the Jiaozhou Bay coastline in China. The research begins with an analysis of historical spill data to construct representative oil spill simulation scenarios. The advanced MEDSLIK-II oil spill prediction model is then employed to simulate oil spill trajectories under these scenarios, focusing on key parameters such as oil thickness and mass to evaluate the hazard levels associated with each scenario. Subsequently, the Environmental Sensitivity Index (ESI) is utilized to assess the vulnerability of coastal zones, while Geographic Information System (GIS) techniques are employed for a spatial analysis and visualization of the results. The case study, covering a 26.87 km stretch of the Jiaozhou Bay coastline, reveals 10 high-risk zones with a total length of 8561.2 m. These areas are predominantly characterized by saltwater marshes, brackish water marshes, and inundated low-lying areas, with ESI rankings of 9 and 10, accounting for 24% of the 339 analyzed segments. The modeling results indicate that in the simulated scenarios, oil spills originating from the Huangdao Oil Port and Qianwan Port pose the greatest risks, with potential impacts extending up to 12 km and 15 km along the coastline, respectively. The study highlights the importance of considering multiple factors, including oil spill trajectories, coastal geomorphology, and ecological sensitivity, in comprehensive risk assessments. The proposed framework demonstrates potential for adaptation and application to other coastal regions facing similar oil spill risks, contributing to the advancement of coastal management practices worldwide.

With the increasing deployment of hydrogen fuel cell forklifts, it is essential to understand the risks of incidents involving these systems. A quantitative risk assessment (QRA) study was conducted to determine the potential hydrogen release scenarios, probabilities, and consequences in fuel cell forklift operations. QRA modeling tools, such as fault tree analysis (FTA) and event sequence diagrams (ESD), were used together with hydrogen systems data. This work provides insights into the fatality risk from a hydrogen fuel cell forklift and the reliability of its design and components. The analysis shows that the expected fatal accident rate of a hydrogen forklift is considerably higher than current fatal injury rates observed by the Bureau of Labor Statistics for industrial truck operators and material handling occupations. Nevertheless, the average individual risk posed to forklift drivers was found to be likely tolerable based on current risks accepted by industrial truck operators. Jet fires are found to dominate the system's risk, however, the risk of explosions is also considerable. An importance measures analysis shows that these risks could be mitigated by improving the design and reliability of pressure relief devices, as well as other components prone to leak such as filters and check valves. We also identify sources of uncertainty and conservatisms in the QRA process that can guide future research in hydrogen systems. These results provide powerful insight into improvements in the design of fuel cell forklifts to reduce risk and enable the safe deployment of this key technology for a decarbonized future. [Display omitted] • Employed FMEA and fault trees to model failure events in H2 forklifts. • Utilized Event Sequence Diagrams and physics simulations to assess loss of life. • Determined risk tolerability of H2 forklift compared to current industry statistics. • Determined most important risk-influencing factors for a H2 forklift design. • Provided H2 forklift design recommendations for risk reduction and safer deployment. [ABSTRACT FROM AUTHOR]

Critical comments can be made to the current risk assessment framework for critical infrastructure used in The Netherlands: the Dutch National Risk Assessment (DNRA). The DNRA uses a qualitative approach to risk assessment, based on, for example, ordinal risk scoring and the risk matrix. Even though qualitative risk assessment methods are internationally popular, there is no scientific evidence that a qualitative approach to risk assessment actually works. In the case of the DNRA, the main points of criticisms relate to the usage of a subjective concept of risk, dependency on subjective risk experts, the use of risk matrices and the absence of decision rules. To combat these criticisms, this article proposes a quantitative probabilistic risk assessment framework for critical infrastructure based upon four design principles, that a methodologically justified risk assessment method for critical infrastructure should meet. The proposal made for the quantitative risk assessment framework uses a Bayesian approach, a standardized measure for negligible risk in the form of a yearly mortality probability of 10−6, and Disability Adjusted Life Years to quantify human life years for social cost–benefit analysis. Finally, the proposed quantitative method is demonstrated in a case study. [ABSTRACT FROM AUTHOR]