Quantitative Risk Assessment Methodology Research Articles

Estimation and evaluation of the risks of protozoa infections associated to the water from a treatment plant in southern Brazil using the Quantitative Microbiological Risk Assessment Methodology (QMRA).

In this study, the Quantitative Microbial Risk Assessment (QMRA) methodology was applied to estimate the annual risk of Giardia and Cryptosporidium infection associated with a water treatment plant in southern Brazil. The efficiency of the treatment plant in removing protozoa and the effectiveness of the Brazilian legislation on microbiological protection were evaluated, emphasizing the relevance of implementing the QMRA in this context. Two distinct approaches were employed to estimate the mechanical removal of protozoa:The definitions provided by the United States Environmental Protection Agency (USEPA), and the model proposed by Neminski and Ongerth.Although the raw water collected had a higher concentration of Giardia cysts than Cryptosporidium oocysts, the estimated values for the annual risk of infection were significantly higher for Cryptosporidium than for Giardia. From a general perspective, the risk values of protozoa infection were either below or very near the limit set by the World Health Organization (WHO). In contrast, all the risk values of Cryptosporidium infection exceeded the threshold established by theUSEPA. Ultimately, it was concluded that the implementation of the QMRA methodology should be considered by the Brazilian authorities, as the requirements and guidelines provided by the Brazilian legislation proved to be insufficient to guarantee the microbiological safety of drinking water. In this context, the QMRA application can effectively contribute to the prevention and investigation of outbreaks of waterborne disease.

BEYOND PASS/FAIL: DEVELOPING A QUANTITATIVE FRAMEWORK FOR CYBERSECURITY AUDITS

Cybersecurity audits are vital in today’s digital landscape, yet they come with numerous challenges, such as resource constraints and evolving audit requirements. This article explores the importance of risk quantification in cybersecurity audits, emphasizing its role in aiding decision-making processes and enhancing organizational resilience. Drawing from real-world examples like the 2019 First American Financial Corporation data breach, the article highlights the consequences of unresolved vulnerabilities and the necessity of effective risk communication. By introducing a simplified framework for risk quantification, the article proposes a practical approach that enables auditors to approximate probabilities without complex software tools. Furthermore, it discusses the synergy between risk quantification and compliance efforts, underscoring their collective impact on resource allocation, risk management strategy, and business continuity. Ultimately, the article advocates for a paradigm shift in cybersecurity audits, urging auditors to move beyond traditional pass/fail approaches and embrace quantitative risk assessment methodologies to better safeguard organizations against cyber threats.

Capturing cascading consequences is required to reflect risk from climate change and natural hazards

Climate change and natural hazards present a major risk to individuals and communities; however, the current quantitative risk assessment methodologies struggle to capture the wider consequences that arise from society’s complex interconnections. These complex interconnections exist due to the number of mutually dependent systems and mean that impacts on one system can be felt in another. These cascading impacts present a major challenge to climate risk assessments. Climate risk assessments often consider a range of “wellbeing” or “value” domains; for example, in New Zealand the five wellbeing domains are Natural Environment, Human, Economic, Built Environment, and Governance. Existing assessments have sought to characterize the risk to each domain, but do not quantitatively or rigorously consider the interplay between the domains. For example, how does the risk to the human domain change as a result of the impacts to the built environment? This interplay and the ensuing cascading impacts could substantially modify the assessed risk. The change could potentially alter the prioritization and subsequent adaptation plans. In this paper, we show that considering cascading impacts not only increases the magnitude of risk but can shift the prioritization. This highlights the importance of capturing cascading impacts for effective adaptation to climate change.

Treated domestic effluents for non-potable reuse: microbial risk assessment and economic viability

ABSTRACT In this study, we applied quantitative microbial risk assessment and net present value methodologies to evaluate the economic viability and safety of wastewater treatment to produce water for reuse. We found payback periods of three to over 15 years for investment in the universalisation of sanitation services in the selected municipalities, wherein the most feasible scenarios were those in which water reuse was carried out at its maximum potential. Microbial risk was assessed in terms of reduced concentrations of Escherichia coli. Results show that reuse of wastewater treated by different plant configurations for crop irrigation, involving only secondary treatment processes, presented high risk of infection for both farmers and consumers (3.50E–02 ± 3.10E–03 and 5.80E 02 ± 3.30E–03, respectively). In the urban and industrial context, it did not pose any risk beyond the tolerable risk recommended by WHO, except for the worker’s droplet ingestion route of exposure (2.40E–03 ± 3.80E–03).

Improvement of quantitative microbiological risk assessment (QMRA) methodology through integration with gaenetic data.

Quantitative microbiological risk assessment (QMRA) methodology aims to estimate and describe the transmission of pathogenic microorganisms from animals and food to humans. In microbiological literature, the availability of whole genome sequencing (WGS) data is rapidly increasing, and incorporating this data into QMRA has the potential to enhance the reliability of risk estimates. This study provides insight into which are the key pathogen properties for incorporating WGS data to enhance risk estimation, through examination of example risk assessments for important foodborne pathogens: Listeria monocytogenes (Lm), Salmonella, Campylobacter and Shiga toxin-producing Escherichia coli. By investigating the relationship between phenotypic pathogen properties and genetic traits, a better understanding was gained regarding their impact on risk assessment. Virulence of Lm was identified as a promising property for associating different symptoms observed in humans with specific genotypes. Data from a genome-wide association study were used to correlate lineages, serotypes, sequence types, clonal complexes and the presence or absence of virulence genes of each strain with patient's symptoms. We also investigated the effect of incorporating WGS data into a QMRA model including relevant genomic traits of Lm, focusing on the dose-response phase of the risk assessment model, as described with the case/exposure ratio. The results highlighted that WGS studies which include phenotypic information must be encouraged, so as to enhance the accuracy of QMRA models. This study also underscores the importance of executing more risk assessments that consider the ongoing advancements in OMICS technologies, thus allowing for a closer investigation of different bacterial subtypes relevant to human health.

Data-driven systematic analysis of waterborne viruses and health risks during the wastewater reclamation process

Waterborne viral epidemics are a major threat to public health. Increasing interest in wastewater reclamation highlights the importance of understanding the health risks associated with potential microbial hazards, particularly for reused water in direct contact with humans. This study focused on identifying viral epidemic patterns in municipal wastewater reused for recreational applications based on long-term, spatially explicit global literature data during 2000–2021, and modelled human health risks from multiple exposure pathways using a well-established quantitative microbial risk assessment methodology. Global median viral loads in municipal wastewater ranged from 7.92 × 104 to 1.4 × 106 GC L−1 in the following ascending order: human adenovirus (HAdV), norovirus (NoV) GII, enterovirus (EV), NoV GI, rotavirus (RV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Following secondary or tertiary wastewater treatment, NoV GI, NoV GII, EV, and RV showed a relatively higher and more stable log reduction value with medians all above 0.8 (84%), whereas SARS-CoV-2 and HAdV showed a relatively lower reduction, with medians ranging from 0.33 (53%) to 0.55 (72%). A subsequent disinfection process effectively enhanced viral removal to over 0.89-log (87%). The predicted event probability of virus-related gastrointestinal illness and acute febrile respiratory illnesses in reclaimed recreational water exceeded the World Health Organization recommended recreational risk benchmark (5% and 1.9%, respectively). Overall, our results provided insights on health risks associated with reusing wastewater for recreational purposes and highlighted the need for establishing a regulatory framework ensuring the safety management of reclaimed waters.

Enabling Safe and Sustainable Hydrogen Mobility: Circular Economy-Driven Management of Hydrogen Vehicle Safety

Hydrogen vehicles, encompassing fuel cell electric vehicles (FCEVs), are pivotal within the UK’s energy landscape as it pursues the goal of net-zero emissions by 2050. By markedly diminishing dependence on fossil fuels, FCEVs, including hydrogen vehicles, wield substantial influence in shaping the circular economy (CE). Their impact extends to optimizing resource utilization, enabling zero-emission mobility, facilitating the integration of renewable energy sources, supplying adaptable energy storage solutions, and interconnecting diverse sectors. The widespread adoption of hydrogen vehicles accelerates the UK’s transformative journey towards a sustainable CE. However, to fully harness the benefits of this transition, a robust investigation and implementation of safety measures concerning hydrogen vehicle (HV) use are indispensable. Therefore, this study takes a holistic approach, integrating quantitative risk assessment (QRA) and an adaptive decision-making trial and evaluation laboratory (DEMATEL) framework as pragmatic instruments. These methodologies ensure both the secure deployment and operational excellence of HVs. The findings underscore that the root causes of HV failures encompass extreme environments, material defects, fuel cell damage, delivery system impairment, and storage system deterioration. Furthermore, critical driving factors for effective safety intervention revolve around cultivating a safety culture, robust education/training, and sound maintenance scheduling. Addressing these factors is pivotal for creating an environment conducive to mitigating safety and risk concerns. Given the intricacies of conducting comprehensive hydrogen QRAs due to the absence of specific reliability data, this study dedicates attention to rectifying this gap. A sensitivity analysis encompassing a range of values is meticulously conducted to affirm the strength and reliability of our approach. This robust analysis yields precise, dependable outcomes. Consequently, decision-makers are equipped to discern pivotal underlying factors precipitating potential HV failures. With this discernment, they can tailor safety interventions that lay the groundwork for sustainable, resilient, and secure HV operations. Our study navigates the intersection of HVs, safety, and sustainability, amplifying their importance within the CE paradigm. Using the careful amalgamation of QRA and DEMATEL methodologies, we chart a course towards empowering decision-makers with the insights to steer the hydrogen vehicle domain to safer horizons while ushering in an era of transformative, eco-conscious mobility.

Quantitative Risk Assessment Methodology for Hydrogen Tank Rupture in a Tunnel Fire

This study presents a methodology of a quantitative risk assessment for the scenario of an onboard hydrogen storage tank rupture and tunnel fire incident. The application of the methodology is demonstrated on a road tunnel. The consequence analysis is carried out for the rupture of a 70 MPa, 62.4-litre hydrogen storage tank in a fire, that has a thermally activated pressure relief device (TPRD) failed or blocked during an incident. Scenarios with two states of charge (SoC) of the tank, i.e., SoC = 99% and SoC = 59%, are investigated. The risks in terms of fatalities per vehicle per year and the cost per incident are assessed. It is found that for the reduction in the risk with the hydrogen-powered vehicle in a road tunnel fire incident to the acceptable level of 10−5 fatality/vehicle/year, the fire-resistance rating (FRR) of the hydrogen storage tank should exceed 84 min. The FRR increase to this level reduces the societal risk to an acceptable level. The increase in the FRR to 91 min reduces the risk in terms of the cost of the incident to GBP 300, following the threshold cost of minor injury published by the UK Health and Safety Executive. The Frequency–Number (F–N) of the fatalities curve is developed to demonstrate the effect of mitigation measures on the risk reduction to socially acceptable levels. The performed sensitivity study confirms that with the broad range of input parameters, including the fire brigade response time, the risk of rupture of standard hydrogen tank-TPRD systems inside the road tunnel is unacceptable. One of the solutions enabling an inherently safer use of hydrogen-powered vehicles in tunnels is the implementation of breakthrough safety technology—the explosion free in a fire self-venting (TPRD-less) tanks.

A Chinese-Specific Reference Amounts Study With TNO Food Allergen Risk Assessment Models - China, 2022.

What is already known about this topic?There are no consistent regulations on possible unintended allergen presence in food. The Netherlands Organization for Applied Scientific Research (TNO) has been committed to developing a quantitative risk assessment methodology for the unintentional intake of allergens.What is added by this report?This study aims to derive the optimal food consumption point for a deterministic food allergy risk assessment under the TNO framework based on Chinese national consumption data. A case study has been presented as an illustration.What are the implications for public health practice?A robust evidence-based food consumption input in quantitative risk assessment of unintended allergens is necessary for future public policy on Precautionary Allergen Labeling for specific products to meet the safety objectives and to be adequately conservative.

The risk of Campylobacter jejuni and Campylobacter coli associated with the consumption of fresh camel milk in Qatar

Campylobacter spp. are among the ten top leading causes of foodborne diseases around the world and are capable of triggering severe gastroenteritis with potential for severe sequelae. Fresh camel milk is one of the most common hospitality gestures among certain cultures. We investigated the potential risk of illness from the consumption of camel milk contaminated with Campylobacter spp. in Qatar and identified critical intervention points that would contribute to mitigating its consequences. Quantitative risk assessment (QRA) methodology with a combination of deterministic and stochastic approaches was employed to address this objective. Data on the likelihood of either C. jejuni or C. coli in camel milk or in humans was obtained through repeat cross-sectional studies in these populations in Qatar. Estimates of the adverse health effects were computed using risk characterization which integrated data on the hazard, the probability of exposure, and dose-response models. Our analyses showed that the probability of illness for a healthy female from the consumption of camel milk contaminated with C. jejuni ranged from 5 x 10-3 to 24 x 10-2 depending on the amount of milk consumed. The risk of illness for males was higher (13 x 10-3 to 30 x 10-2). The estimates of illness were three times higher for immunocompromised females in comparison to healthy females. Immunocompromised males had five-times higher risk of illness in comparison to healthy men. The computed risk of illness from consumption of camel milk contaminated with either C. jejuni or C. coli could be significantly mitigated by increasing the efficacy of sterilizing or pasteurization before serving.

Counter-historical study of alternative dispersant use in the Deepwater Horizon oil spill response

Recent completion of oil fate modeling and a mass budget of the Deepwater Horizon (DWH) oil spill allows for a counter-historical study using quantitative Comparative Risk Assessment (CRA) methodology. Novel application of subsea dispersant injection (SSDI) during the response reduced surfacing oil, volatile organic carbon emissions, and oil on shorelines. The effectiveness of that application, and potential alternatives had dispersant not been used or been used more aggressively, were evaluated by modifying and comparing the validated oil fate model under different SSDI strategies. A comparison of mass balance results, exposure metrics, and CRA scoring for Valued Ecological Components (VECs) shows the value of SSDI in achieving risk reduction and tradeoffs that were made. Actual SSDI applied during the DWH oil spill reduced exposures to varying degrees for different VECs. Exposures and relative risks across the ecosystem would have been substantially reduced with more effective SSDI.

LNG Bunkering QRA: A Case Study on the Port of Piraeus

The use of LNG as maritime fuel is a viable option when it comes to reducing the harmful emissions produced by vessels throughout the world, to comply with IMO's Annex VI requirements. However, since the concept is gaining constant focus, special attention must be paid, so that stakeholders fully comprehend LNG's unique properties and hazards, as well as be aware of the standard procedures and best practices that must be followed when handling and storing LNG. In this paper, a Quantitative Risk Assessment (QRA) methodology is presented along with its application on an LNG bunkering case study at the Port of Piraeus. As a result, LNG's properties are considered, potential hazards are identified, failure frequencies are determined, and accidental consequences are modelled. Having evaluated these parameters, Individual Risk (IR) is assessed, safety distances are outlined, risk drivers are identified.

Quantitative microbial risk assessment for Escherichia coli O157:H7 in Mutton in Qatar: an example of application of One Health approach

The objectives of the study were to evaluate the risk of illness from the consumption of Mutton contaminated with Escherichia coli O157:H7 in Qatar and to highlight intervention points that would contribute to mitigating its associated risk. The quantitative risk assessment (QRA) methodology was employed to address this objective. Our approach consisted of a combination of deterministic and stochastic approaches. Data on the probability of E. coli O157:H7 in animals, animal products, retail, and humans were obtained through repeat cross-sectional studies. Estimates of the adverse health effects were computed using risk characterization which integrated data on hazard characterization and exposure assessment, including dose-response models. The probability of illness for a healthy female from the consumption of mutton contaminated with E. coli O157:H7 eating at a restaurant ranged from 7×10-3 to 28×10-2 depending on the amount of food consumed. However, the risk for the same female eating at home is less (5×10-3 to 24×10-2). The estimates of illness are three times higher for immunocompromised females exposed either at a restaurant or at home. The risk of illness due to this pathogen could be significantly reduced for either gender under different scenarios by increasing the efficacy of roasting the mutton before consumption.

Dynamic quantitative risk assessment of LNG bunkering SIMOPs based on Bayesian network

Liquified natural gas (LNG) bunkering simultaneous operations (SIMOPs) refers to the operations (such as cargo operations, port activities and ship maintenance) occurring around LNG bunkering. SIMOPs pose new risks to LNG bunkering, because the operations are dynamically interlocked in which the occurrence probabilities of potential consequences change at different times due to commencement or completion of specific SIMOP events. However, traditional static risk assessment approaches are not able to take the dynamic nature of these new risks into account. This article proposes a dynamic quantitative risk assessment (DQRA) methodology based on the Bayesian network (BN) to develop better understanding of dynamic risks of LNG bunkering SIMOPs. The methodology is demonstrated and evaluated through a truck-to-ship LNG bunkering case study. The results and discussion of the case study validate the utility of the proposed methodology and demonstrate that BNs are efficient in performing the probability calculations and are flexible in conducting causal diagnosis. The main innovation of this work is realizing the quantification of risks at different times, which reflects the most essential time-changing characteristics of risks associated with LNG bunkering SIMOPs.

Quantitative risk assessment methodology of installation process for deepwater oil and gas equipment

Proper installation of deepwater oil and gas equipment is a prerequisite to ensure its service life. Deepwater equipment faces many challenges during installation, such as the complexity of the installation process and uncertainty of the environment. Thus, risk assessment is necessary to guide personnel in avoiding and addressing potential problems during the installation of deepwater equipment. This study proposes a quantitative risk assessment method of installation process for deepwater oil and gas equipment based on fuzzy Bayesian networks (FBNs). First, the flow chart of deepwater oil and gas equipment in installation process is translated into a main Bayesian networks (BNs). Second, risk factors in different stages of installation are determined from human, management, equipment, environment and third-party interference, and entire risk assessment model is established. Finally, the FBN model is quantitatively analyzed by introducing fuzzy set theory. An empirical study on the installation process of subsea blowout preventer (BOP) is conducted. The results show that the failure of the subsea BOP installation is a small probability event, and equipment factors have the most prominent effect on the installation process. The sensitivity analysis results are consistent with the quantitative analysis. The corresponding improvement measures are proposed according to the analysis results.

In Silico Models for Skin Sensitization and Irritation.

The assessment of skin irritation, and in particular of skin sensitization, has undergone an evolution process over the last years, pushing forward to new heights of quality and innovation. Public and commercial in silico tools have been developed for skin sensitization and irritation, introducing the possibility to simplify the evaluation process and the development of topical products within the dogma of the computational methods, representing the new doctrine in the field of risk assessment.The possibility of using in silico methods is particularly appealing and advantageous due to their high speed and low-cost results.The most widespread and popular topical products are represented by cosmetics. The European Regulation 1223/2009 on cosmetic products represents a paradigm shift for the safety assessment of cosmetics transitioning from a classical toxicological approach based on animal testing, towards a completely novel strategy, where the use of animals for toxicity testing is completely banned. In this context sustainable alternatives to animal testing need to be developed, especially for skin sensitization and irritation, two critical and fundamental endpoints for the assessment of cosmetics.The Quantitative Risk Assessment (QRA) methodology and the risk assessment using New Approach Methodologies (NAM) represent new frontiers to further improve the risk assessment process for these endpoints, in particular for skin sensitization.In this chapter we present an overview of the already existing models for skin sensitization and irritation. Some examples are presented here to illustratetools and platforms used for the evaluation of chemicals.

Biomechanical risk in fatiguing frequency-dependent lifting activities: muscle coactivation in people with and without low back pain

Musculoskeletal diseases and disorders from biomechanical overload are very common among workers. In Italy in2019, occupational diseases of the osteomuscular system and connective tissue accounted for 66% of the total number ofdiseases reported to INAIL. Many factors can contribute to the establishment of a condition of biomechanical overloadand therefore to the onset of work-related musculoskeletal disorders (WMSDs). Among these, work-related low-backdisorders (WLBDs), caused mainly by handling heavy loads, are very common.In recent years, several methods have been developed to assess the risk of biomechanical overload, included in severalinternational standards (ISO-11228, ISO-11226, ISO/TR 12295 and 12296) aimed at identifying high-risk work activities and assessing the effectiveness of ergonomic interventions. Among the best known, with regard to the manual liftingof heavy loads, there is the Revised NIOSH Lifting Equation that, while presenting many advantages (cost-effectiveness,non-invasiveness, speed of application ...) at the same time also has limitations concerning mainly the high subjectivity(subject of scientific debate) and the impossibility of these methods to assess all work tasks.From these premises, it is clear the usefulness of being able to use new quantitative risk assessment methodologies,objectifiable and repeatable, which provide for the possibility of assessing the risk from biomechanical overload evenin modern working scenarios where the use of exoskeletons by workers and the sharing of working space with cobots isbecoming increasingly widespread. In fact, the methods currently used are incomplete and ineffective in assessing thereal impact that these technologies have on the health and safety of workers in Industry 4.0.Recent studies (some of which we were involved in) have introduced the possibilities offered by optoelectronic systems, inertial sensors (IMUs) and surface electromyography (sEMG), to integrate the most widely used observationalmethodologies. These modern technologies, evaluating how a subject moves his joints and uses his muscles during theexecution of a work task, can integrate the observational methods, quantify the elements that characterize the risk minimizing the evaluation errors caused by individual subjectivity and allow to carry out the assessment of biomechanicalrisk even in those areas where the currently most widespread methodologies are not able to give exhaustive answers. Inparticular, the innovative methodologies based on IMUs and sEMG, allow the instrumental quantitative assessment ofbiomechanical risk directly in the field thanks to the fact that the sensors are miniaturized, wearable, easily transportableand based on “wireless” transmission of data acquired on the worker who performs the task. These aspects facilitatedata recording, allowing accurate signal acquisition even in unfavorable environments and in work situations where theworker interacts with a cobot or uses an exoskeleton. Previous studies have involved studies of non-fatiguing lifts, wherethe movement and relative risk of single repetitions of lifting were studied. Currently, we wonder what happens when thework activity becomes fatiguing and whether it is still possible to use these methods to classify risk. In addition, anotherunexplored question concerns the presence of workers who continue to perform work activity during the first phase ofonset of musculoskeletal disorders: can the risk to which these workers are exposed be considered the same as thatinvolving workers without pain? To answer these questions, we conducted an experimental campaign at the Universityof Birmingham in collaboration with Roma Tre University and INAIL in which subjects with and without back disordersperformed fatiguing lifts of 15 minutes in three risk levels determined by three different lifting frequencies. We studiedtrunk muscle activity in terms of muscle coactivation of the trunk flexor and extensor muscles. The results show howcoactivation can classify risk during manual load lifting activities by distinguishing not only the level of risk but alsothe presence or absence of back disorders. These results suggest that the use of electromyographic features to assess thebiomechanical risk associated with work activities can also be used in the presence of fatiguing lifting also to distinguishthe risk in case of subjects with back pain. This methodology could be used to monitor fatigue and extend the possibilitiesoffered by currently available instrumental-based approaches.

Biomechanical risk in fatiguing frequency-dependent lifting activities: muscle coactivation in people with and without low back pain

Musculoskeletal diseases and disorders from biomechanical overload are very common among workers. In Italy in 2019, occupational diseases of the osteomuscular system and connective tissue accounted for 66% of the total number of diseases reported to INAIL. Many factors can contribute to the establishment of a condition of biomechanical overload and therefore to the onset of work-related musculoskeletal disorders (WMSDs). Among these, work-related low-back disorders (WLBDs), caused mainly by handling heavy loads, are very common. In recent years, several methods have been developed to assess the risk of biomechanical overload, included in several international standards (ISO-11228, ISO-11226, ISO/TR 12295 and 12296) aimed at identifying high-risk work activities and assessing the effectiveness of ergonomic interventions. Among the best known, with regard to the manual lifting of heavy loads, there is the Revised NIOSH Lifting Equation that, while presenting many advantages (cost-effectiveness, non-invasiveness, speed of application ...) at the same time also has limitations concerning mainly the high subjectivity (subject of scientific debate) and the impossibility of these methods to assess all work tasks. From these premises, it is clear the usefulness of being able to use new quantitative risk assessment methodologies, objectifiable and repeatable, which provide for the possibility of assessing the risk from biomechanical overload even in modern working scenarios where the use of exoskeletons by workers and the sharing of working space with cobots is becoming increasingly widespread. In fact, the methods currently used are incomplete and ineffective in assessing the real impact that these technologies have on the health and safety of workers in Industry 4.0. Recent studies (some of which we were involved in) have introduced the possibilities offered by optoelectronic systems, inertial sensors (IMUs) and surface electromyography (sEMG), to integrate the most widely used observational methodologies. These modern technologies, evaluating how a subject moves his joints and uses his muscles during the execution of a work task, can integrate the observational methods, quantify the elements that characterize the risk minimizing the evaluation errors caused by individual subjectivity and allow to carry out the assessment of biomechanical risk even in those areas where the currently most widespread methodologies are not able to give exhaustive answers. In particular, the innovative methodologies based on IMUs and sEMG, allow the instrumental quantitative assessment of biomechanical risk directly in the field thanks to the fact that the sensors are miniaturized, wearable, easily transportable and based on "wireless" transmission of data acquired on the worker who performs the task. These aspects facilitate data recording, allowing accurate signal acquisition even in unfavorable environments and in work situations where the worker interacts with a cobot or uses an exoskeleton. Previous studies have involved studies of non-fatiguing lifts, where the movement and relative risk of single repetitions of lifting were studied. Currently, we wonder what happens when the work activity becomes fatiguing and whether it is still possible to use these methods to classify risk. In addition, another unexplored question concerns the presence of workers who continue to perform work activity during the first phase of onset of musculoskeletal disorders: can the risk to which these workers are exposed be considered the same as that involving workers without pain? To answer these questions, we conducted an experimental campaign at the University of Birmingham in collaboration with Roma Tre University and INAIL in which subjects with and without back disorders performed fatiguing lifts of 15 minutes in three risk levels determined by three different lifting frequencies. We studied trunk muscle activity in terms of muscle coactivation of the trunk flexor and extensor muscles. The results show how coactivation can classify risk during manual load lifting activities by distinguishing not only the level of risk but also the presence or absence of back disorders. These results suggest that the use of electromyographic features to assess the biomechanical risk associated with work activities can also be used in the presence of fatiguing lifting also to distinguish the risk in case of subjects with back pain. This methodology could be used to monitor fatigue and extend the possibilities offered by currently available instrumental-based approaches.

Quantitative assessment of domino effect and escalation scenarios caused by fragment projection

Fragment projection from equipment failure has been extensively recognized as a cause of cascading events and of severe domino scenarios. In recent years several mathematical models suitable for the quantitative assessment of risk due to domino effects and cascading events were developed and validated, but a systematic methodology for quantitative risk assessment caused by fragment projection and impact is still missing. In the present study, a step-by-step approach is proposed for the assessment of domino risk indices due to fragment projection. The approach builds on available sub-models for the quantitative assessment of fragment generation, impact and damage probabilities. Altogether, the proposed model supports a quantification of the risk due to escalation triggered by fragment impact that can be easily automated and integrated in risk assessment studies.

Quantitative risk assessment of gas leakage and explosion accidents and its security measures in open kitchens

In this study, a quantitative risk assessment methodology is developed for gas leakage and explosion accidents in open kitchens. Meanwhile, the corresponding security measures are investigated. The physical and computational model of a typical open kitchen and the corresponding traditional kitchen is firstly developed, using CFD code FLACS, respectively. Based on the similarity principle, a small scale low-pressure natural gas leakage and explosion experiment platform like a kitchen was constructed to validate the accuracy of CFD model. Subsequently, gas leakage and dispersion behavior is performed to analyze the gas concentration distribution. Meanwhile, a time-of-exposure model is introduced to calculate the overall ignition probability during the whole gas leakage and dispersion process. And then, the explosion simulation with a real inhomogeneous flammable gas cloud is carried out to analyze the overpressure distribution. In addition, the maximum weighted average overpressure is estimated accurately. According to the overall ignition probability and the maximum weighted average overpressure, the integrated risk caused by gas leakage and explosion accidents is assessed. Furthermore, the active and passive security measures are investigated to reduce the integrated risk in open kitchens. This methodology and its security measures are applied to a typical open kitchen, located in Harbin, China. The results show that the simulation results reproduced by the CFD model are in good agreement with the experimental results. The explosion accident probability in open kitchens is much higher than that in traditional kitchens, whereas the explosion accident consequences in open kitchens are less than that in traditional kitchens. The integrated risk in open kitchens is greater than that in traditional kitchens. These achievements provide an effective theoretical guidance and technical support for safety gas supply design of open kitchens.