Journal of Health and Safety at Work

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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.

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Introduction: The COVID-19 pandemic caused many businesses to face problems and created job insecurity, leaving many workers and employees stressed about losing their jobs. Therefore, the current research aimed to analyze the impact of workplace safety management measures on the behavior of organizational citizens concerning the role of job insecurity and the perceived risk of COVID-19 among the employees of Mashhad Social Security Organization.
Material and Methods: The current applied research is a descriptive survey. The research population is all 560 employees of the social security organization of Mashhad city. The sample size was estimated based on Morgan’s table using a convenience sampling method, with a total number of 225. The data collection instrument was Wu et al.’s (2022) standard questionnaire, used to check construct validity and confirmatory factor analysis. Cronbach’s alpha coefficient and composite reliability were used to measure reliability, and the results showed that the questionnaire was adequately valid and reliable. The data analysis also involved structural equation modeling conducted in Smart PLS.
Results: The results showed that workplace safety management measures have an impact on organizational citizenship behavior and the perceived risk of COVID-19. Also, the perceived risk of COVID-19 has a positive effect on perceived job insecurity. Yet, the perceived risk of COVID-19 does not influence organizational citizenship behavior and does not mediate the relationship between workplace safety management measures and organizational citizenship behavior. Workplace safety management measures have an impact on perceived job insecurity, and job insecurity has an impact on organizational citizenship behavior.
Conclusion: In light of the present findings, it can be concluded that workplace safety management measures are among the most important programs and strategies of organizations to increase citizenship behaviors, support employees, and provide safe conditions in an organization.

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Introduction: Work-related musculoskeletal disorders (WMSDs) are a prevalent occupational health concern, influenced by both physical and psychosocial factors. Valid questionnaires offer a cost-effective and efficient means of evaluating WMSDs. This study aimed to validate the Persian version of the MDRF questionnaire, assess its applicability in Iran, and investigate the prevalence of WMSDs among employees in an automotive industry.
Material and Methods: This descriptive cross-sectional study was conducted among 100 employees (50 production line workers and 50 office workers) in Kerman province. The linguistic validity of the questionnaire and its translation were ensured using the Backward-Forward method. Content validity was assessed through CVI and CVR indexes. To evaluate the questionnaire’s reliability and agreement, Cronbach’s alpha and ICC were employed. User responses from the first and second series of the questionnaires were validated using Kappa and Spearman’s tests.
Results: Results indicated high reliability which was achieved by Cronbach’s alpha and ICC values of 0.960 and 0.925, respectively. The questionnaire’s validity was acceptable based on CVR and CVI tests. The prevalence of WMSDs was the highest in the lower back for both production line and office workers over the past year. The job satisfaction factor exhibited the highest risk level among the questionnaire’s four subgroups. Approximately 85% of participants were classified as having a high or very high-risk level, reflecting concerning conditions among the employees. The prevalence of WMSDs in different body parts significantly correlated with all physical and psychosocial stress factors.
Conclusion: This research highlights the influence of diverse physical and psychosocial risk factors on the occurrence of WMSDs among both occupational workers and office employees. Also, the MDRF questionnaire, whose high applicability in assessing the WMSDs risk factors was proven in this study, is an effective tool for prioritizing, planning, and executing educational and preventive measures within the workforce community to mitigate and prevent WMSDs. 

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Introduction: The COVID-19 pandemic has been a significant global health challenge. Primary care services, such as screening health centers, were crucial in identifying infected individuals. However, these centers were often crowded and posed a high risk to staff and non-COVID-19 patients. This study aims to assess the risk of airborne transmission of SARS-CoV-2 in such settings through simulation.
Material and Methods: In this study, waiting and sampling rooms of a COVID-19 healthcare center were simulated using different scenarios. Then, the Quanta emission rate was estimated using the viral load in the sputum of infected individuals. Finally, the airborne transmission risk of SARS-CoV-2 was determined using the Wells-Riley method for scenarios of wearing and without masks.
Results: The study showed that the Quanta emission rate in an unmodulated speaking activity was higher than other expiratory activities in both units (p <0.001). Also, the total amount of Quanta was slightly higher in the sampling room than in the waiting room, which was not statistically significant. On the other hand, the calculation of transmission risk showed that the probability of airborne virus transmission in the sampling room was higher (about 2 to 8%). In addition, wearing masks reduced the possibility of airborne transmission of the virus significantly (77 to 81%).
Conclusion: This study shows that the level of risk in the sampling and waiting rooms is moderate. Masks also significantly reduce the possibility of airborne transmission of SARS-CoV-2. Taking appropriate health and safety measures such as avoiding crowds, wearing masks, whispering, and monitoring social distancing can reduce the plausibility of airborne transmission of the SARS-CoV-2 virus.
 

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Introduction: People’s risk perception in an emergency situation affects how they behave. During the pandemic of a disease like COVID-19, the fear of the disease and its consequences causes people to deal with anxiety. The present study was conducted with the aim of determining the relationship between the perception of the risk of COVID-19 and the experience of anxiety caused by it among workers in manufacturing industries. 
Material and Methods: The present descriptive-analytical study was conducted cross-sectionally in 2022 among 545 workers of manufacturing industries located in Tehran, Mazandaran and North-Khorasan provinces. In the study, data collection was conducted using three questionnaires: a demographic information questionnaire, the COVID-19 Disease Anxiety Scale (CDAS), and the COVID-19 Risk Perception and Psychological Predictors against COVID-19 questionnaire. Data analysis was done using descriptive (mean and standard deviation) and analytical statistics (Canonical Correlation Coefficients or CCC) in SPSS V25 software.
Results: The mean ± SD of the workers’ age was 35.98 ± 7.58 years, while the scores for risk perception and anxiety were 12.89 ± 3.31 and 4.51 ± 1.51, respectively. The Concordance Correlation Coefficient (CCC) between risk perception and anxiety caused by the COVID-19 disease in the first Canonical point was 0.734, and in the second Canonical point, it was 0.229. The corresponding p-value was found to be less than 0.01. Psychological symptoms (Canonical loading = -0.725) and physical symptoms (Canonical loading = -0.421) played a significant role in predicting the variability of the risk perception of COVID-19.
Conclusion: The perception of risk related to the COVID-19 disease resulted in a decrease in anxiety, having a more pronounced effect on psychological symptoms compared to physical symptoms. Therefore, in times of pandemic outbreaks similar to COVID-19, implementing measures that enhance workers’ awareness and understanding of the disease risks can prove effective in managing anxiety. 

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Introduction: Steel erection is known as one of the most hazardous construction activities. From an occupational health and safety perspective, this process carries high risk. Therefore, this study aims to conduct a qualitative risk analysis of steel structure assembly and model it using the Functional Resonance Analysis Method (FRAM).
Material and Methods: In this cross-sectional study, the construction site of a high-rise building steel structure was first visited to identify the main processes involved. Then, semi-structured and open-ended interviews were conducted with 33 workers partaking in this process. Data from the interviews and process identification were entered into FRAM Model Visualiser (FMV) software to investigate and model complex relationships and interactions between daily tasks.
Results: Of the 19 major system component functions identified, four functions had potential instability and defects due to complex human, organizational, and technological function interactions. By intensifying the FRAM graphic model, risks may be imposed on the system if the interactions of these four functions are neglected. These include coordination with the experienced rigger, preparation of the tower crane, attachment of parts at the installation site, and execution of the rescue rope.
Conclusion: The findings demonstrate that conducting qualitative risk assessment and modeling the steel frame construction process using FRAM allows for an in-depth understanding of nonlinear conditions and dynamics resulting from escalating technical-social interactions. This approach enables a comprehensive analysis of system safety status.
 

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Introduction: The accurate evaluation of error probability and risk is important. Accordingly, this Comparative study was conducted to evaluate the risk of human error in emergency situations using SLIM and Fuzzy SLIM techniques in fierfighting tasks.
Material and Methods: This cross-sectional and descriptive-analytical study was conducted among 12, using Fuzzy SLIM and SLIM techniques. 39 sub-tasks were studied in 4 phases (Awareness, Evaluation, Egress and Recovery). Considering the advantages of the Fuzzy SLIM method, fuzzy logic was used in weighting of performance shaping factors (PSF). Excel software was used to calculate the probability of error. Also, correlation and kappa statistical tests were used for data analysis in SPSS software.
Results: The mean and standard deviation of human error probability in different sub-tasks of firefighting in SLIM and Fuzzy SLIM methods were 0.095357 ± 0.026193 and 0.06490 ± 0.051748, respectivly. In 48.7 percent of the sub-tasks, the probability category of human error and the assessed risk were the same; however, in 89.7 percent of the sub-tasks, the estimated level of risk was the same in both methods. Correlation test showed that the correlation coefficient of error probability values between the two methods was 0.32, which indicated a moderate correlation in this regard. Additionally, the results of kappa statistical test for the estimated level of risk showed that there is a high agreement between Fuzzy SLIM and SLIM (P value <0.05).
Conclusion: The results of the study indicated meaningful agreement and a moderate correlation between Fuzzy SLIM and SLIM. Therefore, due to the relatively high accuracy of Fuzzy logic methods, and also the long steps of implementing the SLIM method, the Fuzzy SLIM method can be a good alternative to this method.

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Introduction: Due to uncertainties regarding the risks of engineered nanomaterials for human health and the environment, different organizations and researchers have developed various management frameworks and assessment tools to mitigate hazards during the procedures and applications of engineered nanomaterials. However, most of these techniques do not meet all the individual requirements. This study provides a review and introduction to the techniques developed for the management of safety, health, and environmental risks associated with engineered nanomaterials.
Material and Methods: In order to find pertinent documents on the safe handling of engineered nanomaterials, a search was conducted using the following keywords: “Engineered nanomaterials”, “Framework”, “Tool”, “Risk management”, “Occupational exposure”, “Environment”, “Risk assessment”, and “Nanotechnology”. The search was conducted on various databases, including Scopus, Web of Science, NIOSH, ECHA, and ISO. Among the search results, tools and frameworks that specifically focus on the safety, health, and environmental risk management or assessment of engineered nanomaterials were selected.
Results: Among the search results, 17 frameworks and 11 developments in the field of managing occupational, environmental, and toxicological risks associated with engineered nanomaterials were discussed. Various frameworks and tools for identifying, evaluating, and managing the potential risks of engineered nanomaterials vary in terms of their scope, goals, risk assessment approaches, and output, offering diverse applications.
Conclusion: Various tools and frameworks, each with unique properties, applications, and limitations, can assist organizations in achieving their goals related to safety, health, and environmental issues in the field of nanotechnology. Currently, there is no consensus on the optimal approach for assessing the risks of nanomaterials, underscoring the necessity for additional research, development, and collaboration in this field.
 

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Introduction: One of the ways to produce electricity in power plants is to use gas turbines and generators. Due to the use of methane gas as the fuel of the burners and the high rotation speed, this equipment has a high DOW index level, therefore, if the hazardous conditions in the gas turbine are not controlled by the safety instrumented system and the process is not directed to a safe state, Catastrophic events will occur such as fire and explosion and damage to property and people as well as interruption of the power generation process will happen in the long term, so gas turbine safety instrumentation systems can be considered as “critical safety systems”. Therefore, the reliability and availability of their function should be evaluated. The purpose of this research is to determine and verify the safety integrity level (SIL) related to the safety instrumented function (SIF) of the gas turbine and generator in a combined cycle power plant.
Material and Methods: In this study, the safety integrity level was determined by using two methods, Calibrated Risk Graph (CRG) and Independent Protection Layer Analysis (LOPA), and to verify the safety integrity level, the requirements related to random hardware failure, hardware failure tolerance, and systematic capability are considered according to IEC 61511 and IEC 61508 standards.
Results: The results of a case study in gas turbine and generator showed that the LOPA method is more quantitative than CRG and provides more details of independent protective layers, so it is a more suitable method for determining SIL. The SIL verification results show the SIL2 level, closer to the LOPA results.
Conclusion: The obtained results show that the function of the studied gas turbine safety instrumentation system has a suitable level of reliability and availability and is well responsive to risky conditions and possible deviations. The present approach helps safety engineers and instrumentation engineers to calculate the reliability and availability of the Function of the safety instrumentation systems of their process equipment and ensure its acceptability or not.

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Introduction: Risk assessment matrix is a tool used in a project’s risk assessment process to identify the probability of risks and evaluate the potential damages caused by those risks. Generally, a risk assessment matrix is drawn in a two-dimensional form, with two factors: the severity of the accident and the probability of its occurrence. So, the purpose of this study is to develop a specific risk assessment matrix in a three-dimensional form by using the accident severity grade (ASG) rating system, the accident probability, and taking into account the preventive approach that helps occupational injury risk assessment in the automobile industry.
Material and Methods: This cross-sectional study was conducted in 1402 (2023) in one of the automobile assembly industries. One hundred cases were randomly selected by examining the reports of this industry’s past accidents. The ASG scoring checklist was designed and completed by the experts to assess the severity of accidents. Then, considering the ASG score, the frequency of the accident, and its preventability, a three-dimensional risk assessment matrix specific to this industry was presented.
Results: According to the findings of the accident analysis, a total of 658 accidents and 15,019 lost working days were recorded in this period. The most influential factor in the occurrence of accidents is related to “surface condition” (influence factor = 0.6), and the least of them belongs to the “weather conditions” (influence factor = 0.028). The results of the three-dimensional matrix show that when the ability to prevent accidents increases, the risk of accidents decreases.
Conclusion: Using the accident severity grade (ASG) and preventability in the proposed three-dimensional risk assessment matrix, the accident severity can be quantified immediately after the accident. This approach allows monitoring workplaces during the accident, leading to timely control and risk management implementation.
 

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Introduction: Fire safety in healthcare centers is crucial due to the limited evacuation capacity of the occupants and the necessity of not disrupting the operation in these centers. In this study, the fire risk of a public hospital was evaluated using the Fire Risk Assessment Method for Engineering (FRAME). Additionally, the factors affecting fire safety in the hospital were analyzed quantitavely, and fire control strategies were presented. 
Material and Methods: First, the fire risk assessment checklist was filled in all the hospital departments. Then, the values of the factors affecting fire safety were obtained. In the next step, the fire risk for the building, occupants and activities were estimated using Excel software-FRAME. Finally, control strategies and intervention measures were presented based on the value of these factors. 
Results: In the hospital under study, 22% of the departments posed an undesirable fire risk to the building and its property. On the other hand, 90% of the departments had risk levels that were undesirable for the occupants. The results of the initial risk (R0) showed that a balance between potential fire risk and risk acceptance can be established by implementing manual fire extinguishing systems and automatic detectors in all departments. 
Conclusion: ased on the condition of the hospital studied, a balance between potential fire risk level and risk acceptance level was not established. Therefore, there is a need for fire control measures, especially fire safety measures for the occupants. The results of this study can be useful for readers and experts in interpreting fire risk assessments and presenting detailed control measures based on the risk assessment and the value of the parameters.

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Introduction: Workplaces often contain potential risks, such as exposure to toxic chemicals. Conducting a thorough health risk assessment helps employers recognize these dangers and implement necessary controls. In the 20th century, modern risk assessment frameworks began to be established with the rise of public health agencies.
Material and Methods: The present study is a narrative review. In order to obtain necessary information, Persian and English texts were searched in Web of Science, PubMed, Scopus, SID and Magiran databases. Keywords such as “health risk assessment”, “chemicals” and “nanomaterials” were used in this study.
Results: Both quantitative and qualitative health risk assessments play critical roles in occupational health, with each method providing different levels of depth and accuracy depending on the situation. EPA Model, Monte-Carlo Simulation, Physiologically Based Pharmacokinetic (PBPK) Modeling, Quantitative Structure-Activity Relationship (QSAR) Models, Probabilistic Risk Assessment (PRA), Life Cycle Impact Assessment (LCIA), and Biologically Based Dose-Response (BBDR) Models, are among the most important quantitative methods for assessing the health risk of chemicals. COSHH Model, ICCT Model, ICMM Model, Australian Model, and Romanian Model, are the most important qualitative methods for health risk assessment of chemicals. In addition to the quantitative and qualitative methods, semi-quantitative methods like Singapore Model, LEC Method, and SEP Model, have also been proposed for assessing the health risk of chemicals. The preference for qualitative over quantitative methods in the risk assessment of activities involving nanomaterials stems from substantial uncertainties, limited data availability, and the unique and complex behaviors of nanomaterials in the workplaces.
Conclusion: Overall, the evolution of health risk assessment methods reflects a continuous drive towards greater accuracy, reliability, and relevance. As we continue to innovate and expand our knowledge, the field is well-positioned to address the complex and evolving landscape of chemical and material risks, ensuring the protection of human health and the environment. 

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Introduction: One of the most critical factors supporting industry managers and decision-makers in adapting to changes is the Business Intelligence (BI) dashboard. Dashboards, enriched with indicators, reports, and charts, enable managers to monitor industry performance at any given time.
Material and Methods: To evaluate safety status and prevent future accidents, risk factors within the industry were assessed using the RI risk index. In this study, the index was calculated through a geometric averaging relationship. Additionally, the ARIMA (2,0,0) time series model was applied, converting the average daily Risk Index into the Predicted Risk Index.
Results: Based on the occurrence of accidents, when the trend of the Risk Predictor Index is below 3, it is considered a safe zone in that industry. When the index trend is between 3 and 4, it represents a warning zone. If the index exceeds 4, there is a high probability of accidents, categorizing it as an action zone. According to the presented dashboard and zoning, the industry manager can conclude that 33% of risks are in the action area, 24% of the risks are in the warning area and 43% of the identified risks are in the safe area.
Conclusion: The results of this study demonstrated that leveraging business intelligence for prioritization can enhance decision-making and analytical processes for senior organizational managers.

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Introduction: Nanomaterials are widely applied across diverse scientific and industrial sectors; however, their emergence has introduced a new generation of occupational hazards for workers. Concurrent with discussions on the adverse effects of nanomaterials on human health, researchers have sought to develop methods for assessing occupational risks associated with these materials. Accordingly, this study aims to propose a general framework for the development of such methods.
Material and Methods: This is a critical analysis study designed to evaluate existing methods for assessing occupational risks related to nanomaterials and ultimately propose a modified framework for refining these methods. By examining current approaches and identifying their strengths and weaknesses, the authors have proposed an improved framework for occupational risk assessment of nanomaterials.
Results: The proposed framework is based on two key dimensions: “Severity/Hazard” and “Probability/Exposure.” The first dimension determines the potential risk level arising from exposure to nanomaterials, with the most critical factors being the intrinsic properties and toxicology of the nanomaterial itself, parent materials, and similar substances. The second dimension describes the likelihood and nature of exposure to nanomaterials during work activities, with the most influential factors being worker, job tasks, and workplace environment characteristics.
Conclusion: The lack of sufficient data and numerous uncertainties regarding bio-nano interactions make quantitative risk assessment (the traditional occupational health approach) difficult, less reliable, and in some cases unfeasible for nanomaterials—given current knowledge. Qualitative and semi-quantitative approaches, such as Control Banding, despite demonstrating positive aspects, have faced significant criticism. The framework-based method proposed herein appears capable of partially overcoming these challenges.

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Introduction: Transporting hazardous materials is inherently associated with multiple risks that can threaten human health, the environment, property and infrastructure. The deployment and operation of ammonia tanks in various industrial projects and organizations with diverse objectives present serious safety, health and environmental challenges. Therefore, conducting risk assessment in the chemical sector is essential. This study aimed to evaluate the effectiveness of a pressure sensor in reducing the risk of ammonia cargo release during road transportation, based on Quantitative Risk Assessment (QRA) in a petrochemical transport company.
Material and Methods: This study assessed the risk of ammonia release from a pressurized tanker and investigated the risk-reducing effects of employing a pressure sensor for leak prediction. Consequence modeling and QRA were conducted using SAFETI version 9.
Results: The results showed that the installation of a pressure sensor on the ammonia tanker reduced the gas release duration from 40 to 25 minutes, which consequently decreased the volume of the leaked gas and ultimately reduced the overall risk level of accidents. This risk reduction varied between 55% and 99% under different atmospheric conditions. By decreasing the release time from 40 to 25 minutes, the lethal radius of ammonia was consistently reduced in all weather conditions. The analysis of individual risk contours in the sudden rupture scenario revealed that atmospheric conditions, particularly during winter nights, had the greatest impact on the expansion of lethal zones.
Conclusion: The use of pressure sensors and alert systems can effectively reduce individual risk level. Continuous monitoring of tank conditions and prompt alerts in the event of leaks or pressure drops enable faster response and help prevent escalation of accident consequences.

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Introduction: Fire risk assessment in oil storage tanks faces challenges due to incomplete, conflicting, and uncertain data, particularly when empirical evidence is limited. Traditional point-based likelihood estimates often fail to capture expert doubt and epistemic uncertainty. This study aims to develop and evaluate a novel hybrid framework combining Dempster-Shafer Theory (DST) and Bayesian Networks (BN) to improve the trustworthiness of fire risk prediction in such industrial settings.
Material and Methods: The proposed approach integrates DST to model expert uncertainty through interval probabilities (Bel–Pl) and BN to dynamically update causal relationships as new information appears. The study implements computational coding to enable DST calculations for five expert opinions across 243 scenarios, overcoming prior limitations in multi-expert modeling due to computational complexity.
Results: The hybrid DST-BN framework demonstrated superior ability to incorporate incomplete and conflicting expert data, reducing overconfidence linked to point estimates. Interval probabilities offered more trustworthy representations of epistemic uncertainty, while BN integration allowed traceable and adaptable causal modeling. The computational solution facilitated practical application of DST with multiple experts, enhancing the strength of the risk assessment.
Conclusion: This research provides an effective DST-BN hybrid methodology for assessing fire risk in fixed-roof oil tanks, improving accuracy and trustworthiness in complex industrial environments. By addressing the shortcomings of point-based methods and enabling multi-expert participation, the framework supports clearer and more defensible probabilistic inferences. Future work may focus on integrating real-time sensor data and AI-based decision systems to further strengthen dynamic risk assessment capabilities.
 

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Introduction: Occupational exposure to volatile organic compounds (BTEX) and heavy metals in industrial settings poses significant health concerns. These substances may lead to toxic, carcinogenic, and hematobiochemical effects. This study aimed to assess the health risks associated with exposure to these pollutants in a power equipment manufacturing industry over a 10-year period and to compare the accuracy of quantitative (USEPA) and semi-quantitative (Singapore) risk assessment methods.
Material and Methods: This cross-sectional study was conducted across six occupational groups. Personal air sampling of BTEX and heavy metals was performed according to NIOSH protocols. Carcinogenic and non-carcinogenic risks were estimated using the USEPA method and the Singapore semi-quantitative approach. Additionally, hematological and biochemical indicators of exposed workers were analyzed.
Results: Nickel had the highest cancer risk, and the highest hazard quotient (HQ) values were related to xylene, benzene, and nickel. While the semi-quantitative method classified most risks as negligible to low, the USEPA method identified several cases with definite health risks. Significant effects were observed on SGOT, SGPT, fasting blood sugar, creatinine, and blood pressure among exposed groups.
Conclusion: The USEPA method demonstrated higher sensitivity and reliability in identifying occupational chemical hazards and should be prioritized in future assessments. Furthermore, the findings underscore the importance of preventive measures to reduce chronic exposure to BTEX and heavy metals in similar industrial settings.

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Introduction: Occupational diseases and workplace accidents have significant financial impacts on industries, communities, and nations each year. Risk assessment is considered an effective tool for managing these issues; however, many organizations fail to implement it successfully. This study explores this challenge from the perspective of Health, Safety, and Environment (HSE) officers.
Material and Methods: In this study, 30 Semi-structured individual interviews were conducted with HSE officers. Inductive content analysis was used for analyzing interviews. After analyzing the interviews, the codes in the interviews were categorized. To ensure credibility and transferability, participant checking and consultations with experts in the field of risk assessment were conducted.
Results: After analyzing the interviews, seven main categories were identified, each comprising several sub-categories. The main categories included: Resources, Technical Knowledge, Legal and Regulatory Barriers, Cultural Issues, Absence of Risk-Based Thinking in the Organization, Individual Issues, and Lack of Interaction and Communication.
Conclusion: This study revealed that seven major barriers hinder the implementation of risk management systems and the execution of risk assessments in the industries of East Azerbaijan Province. These obstacles can directly affect the identification, analysis, and control of risks, ultimately reducing the effectiveness of occupational health and safety processes. Therefore, to conduct effective risk assessments and enhance safety levels in industrial environments, it is essential for policymakers, industry managers, and regulatory bodies to accurately identify and analyze these barriers and develop appropriate solutions to address them. Moreover, designing and implementing educational programs, restructuring management systems, and strengthening interactions between regulatory organizations and industries can contribute to improving risk assessment processes and safety management in this sector.

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Introduction: Hospitals represent a critical fire safety challenge. The presence of patients with limited mobility, specialized staff, and invaluable infrastructure makes them seriously vulnerable. Further, toxic smoke inhalation, as a primary product of fire, is a leading cause of mortality. To address this concern, our study intended to conduct a comprehensive fire safety assessment of a teaching hospital in Tehran (2023-2024) by integrating risk assessment with numerical modeling.
Material and Methods: This study was conducted in a teaching hospital following three consecutive steps: risk assessment, fire scenario design, and fire and smoke modeling. First, vulnerable zones were identified using the FRAME method. Next, fire scenarios and control strategies were designed based on the identified risk factors and a review of the relevant literature. Ultimately, fire and smoke transport was modeled using the CFAST software to ascertain the performance of the proposed strategies.
Results: The risk assessment pinpointed two wards with unacceptably high occupant risk levels: the inpatient ward on the 10th floor, owing to a cluster of unsafe behaviors, and the basement warehouse, owing to improper storage and inadequate emergency exit access. Fire and smoke modeling was performed for these two zones, comparing the “current situation” against a proposed “risk control strategy.” The modeling results revealed that the control strategy positively affected key life safety indicators, significantly ameliorating the Fractional Effective Dose (FED) and Heat Release Rate (HRR).
Conclusion: According to this study, a fire risk assessment provides a clear and detailed perspective on a hospital building’s fire safety. Integrating the results of the FRAME assessment with CFAST simulations results in a comprehensive understanding of the facility’s safety status. These data can be utilized to design effective emergency plans and calculate the Required Safe Egress Time (RSET), thereby preventing life-threatening harm to occupants against toxic gases. 

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Introduction: Industrial units, such as oil refineries, face significant hazards due to the release of toxic and flammable gases. Hydrogen sulfide (H₂S), due to its high toxicity and environmental impact, is among the most dangerous pollutants. This study aimed to model and assess the consequences of H₂S release in the Sulfur Recovery Unit (SRU) of Abadan Refinery using PHAST software to support safety planning and risk reduction strategies.
Material and Methods: Consequence modeling was conducted using PHAST version 8.4. Process data, including temperature, pressure, flow rate, and feed composition, along with meteorological conditions (average temperature, relative humidity, and wind speed based on Pasquill stability classification), were used to define probable scenarios. Scenarios included partial pipeline rupture, variable leak flow, short pipe release, and catastrophic reactor tank rupture. Key damage criteria, including thermal radiation threshold, explosion overpressure, and toxic dose, were used to determine hazard zones.
Results: Thermal radiation up to 71.027 kW/m² can cause instant death within a 70-meter radius, while overpressure exceeding 0.206 bar can destroy equipment and structures up to 35 meters in summer conditions. The H₂S cloud can spread up to 120 meters downwind, causing immediate fatalities among exposed personnel. These findings identify high-risk zones in and around the SRU, emphasizing the need to relocate shelters, install gas monitoring systems, and provide protective equipment. Results are limited to the defined scenarios and PHAST assumptions.
Conclusion: Due to the lack of risk assessment studies in early phases and during operation, identifying safe points and high-risk zones, along with prioritizing risk reduction, is essential to ensure workplace and public safety. Comprehensive risk assessment, including probability analysis (using software such as SAFETI) and application of advanced models (CFD and AI-based methods), is recommended for future research.