Journal of Health and Safety at Work

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Introduction: In process industries, some of the primary events may result in secondary events in an industrial unit called the domino effect. Since refinery storage tanks are always at risk of fire and explosion, quantitative risk assessment is important in determining the severity and outcome of an accident, taking into account the effects of dominoes on the main industry, neighbors, and society and can play an important role in risk management. Therefore, the purpose of this study was to quantitatively evaluate the risk of condensate storage tanks taking into account the domino effect.
Material and Methods: The technique used in this study was Quantitative Risk Assessment (QRA), the analysis of the consequences of which was performed using PHAST (7.22) after setting goals, studying the process, identifying hazards and scenarios. Then, to determine the extent of the domino effects of the escalation vectors were matched against the threshold, and after screening, the overall vulnerability of the repositories for mapping individual risk levels was calculated.
Results: In the leakage scenario, after considering the domino effects, the risk contour 10-4 to about 250 meters and the risk contour 10-5 to about 400 meters increased. Also in the catastrophic rupture scenario, the radius of risk contour of the 10-5 increased to100 m after considering the domino effects up to around damage tank.
Conclusion: As can be deduced from the results, using this method can give a clear picture of the consequences of chain events and the probability of damage to nearby employees, equipment and neighbors, which is very important in risk, emergency and crisis management.

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Introduction: Failure modes and effects analysis (FMEA) method is used in industries to identify, assess and prioritize risks. Multi-criteria decision-making methods (MCDM) select the best option from different criteria. Therefore, this study aims to identify, assess and prioritize risks using FMEA based on SWARA-VIKOR multi-criteria decision-making methods in a gas pressure reduction station.
Material and Methods: In this descriptive and analytical study, stepwise weight assessment ratio analysis (SWARA) and decision-making optimization and compromise solution (VIKOR) methods were used to rank the risks of failure modes identified in FMEA. SWARA method was employed to determine the severity, probability and discovery weights, and VIKOR technique was applied to rank the failure modes of the system equipment. Finally, an operational example of the pressure reduction station was presented to show the application and feasibility of the proposed model. A comparative study was conducted to confirm the practicality and effectiveness of the proposed model.
Results: In total, 35 main failure modes were identified in the pressure reduction station. Failure of regulator sleeve and safety valve and regulator diaphragm rupture were assigned the first, second and third ranks of risk priority, respectively. The sensitivity analysis results showed the proposed approach had desirable stability and only the failure mode of increasing the heater flame temperature was very sensitive to changes in the weight of the criteria. Results of ranking the failure modes of the station indicated there were many changes in the ranking of failure modes based on the proposed approach.
Conclusion: The proposed approach could provide more reasonable and accurate results for ranking risks because the criteria were weighed step by step based on the experts’ opinion.

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Introduction: Failure Mode and Effects Analysis (FMEA) is a structured way to find and understand the states of a system’s failure and to calculate the resulting effects. In this method, which has been criticized by many researchers, the risk priority number is obtained for each failure mode based on the multiplication of the three parameters of occurrence (O), severity (S) and detection (D). In order to overcome the disadvantages of the traditional method of FMEA, such as ranking the failure and weighting the parameters, this research proposes a model in the fuzzy set.
Material and Methods: The model proposed in this paper is a nonlinear model for weighting the parameters of the FMEA and the revised TOPSIS method for ranking the failures, which is used for the first time to improve the FMEA method.
Results: The proposed model was presented in the Copper Complex of Shahr-e-Babak to assess safety risks. Based on the results of the study, it was found that in this proposed model, the weights of severity and detection were 0.479 and 0.186, respectively, and the results of the ranking showed that the risks of falling from height and getting stuck between objects had the highest and lowest priorities, respectively.
Conclusion: In the proposed model, based on Logarithmic Fuzzy Preference Programming and the revised TOPSIS method, the definite weights of the parameters were presented without any fuzzy number ranking and risk ranking with more criteria, respectively. Therefore, the proposed model has a higher ability compared to the traditional FMEA, and its application can be recommended to determine the ranking of risks.

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Introduction: This study quantitatively analyzed the fire risk using the Fire Risk Index Method: Multistorey Apartment Buildings (FRIM-MAB) method, considering the importance of fire safety in student dormitories as human gathering centers and previous limited studies.
Material and Methods: This descriptive-analytical study was conducted on 17 sections of the Qazvin University of Medical Sciences student dormitory in 2021. This study used the FRIM-MAB version 2.1. In this method, 17 parameters and their sub-parameters affecting the fire risk index were determined and weighted. Consequently, the studied dormitory was also inspected, the weighted degree of each parameter was computed, and the fire risk index for each section, which ranged between 1 and 5, was determined.
Results: The average fire risk index of the dormitory building at the time of the study was 2.37. The laundry room received the lowest risk index (1.69), while the computer site received the highest risk index (2.7). The results indicated that the most effective parameters causing fire risk were related to “compartmentation” (12 frequency items), “linings in the apartment” (4 frequency items), and “escape routes” (1 frequency item). These parameters contributed more than 42% to create the risk index for the dormitory’s most dangerous areas.
Conclusion: The FRIM-MAB method is a suitable quantitative and indexing fire risk assessment method for student dormitory buildings, and it is a quick, inexpensive, and effective screening and ranking tool. Periodically evaluating the dormitory’s fire risk and, if necessary, improving the environment is essential. In the present study, compartmentation, linings in the apartment, and escape routes were the most effective parameters in fire risk of the studied dormitory.

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Introduction: Nowadays, air pollution is now considered to be the largest environmental health threat. This study was conducted with the aim of determining occupational exposure to chemical pollutants, including sulfur dioxide (SO2) and hydrogen sulfide (H2S) and assessing the health risk of exposure to these compounds using a combination of AERMOD and SQRA methods.
Material and Methods: The present study is considered as a descriptive-analytical and cross-sectional research, which was conducted in 2002 in one of the gas air refineries of South Pars in the Persian Gulf region, in such a way that the amount of emissions coming out of refinery chimneys was measured by the Testo 350- XL. AERMOD model was used to simulate the dispersion of H2S and SO2 chemical pollutants. Respiratory exposure and health risk assessment of refinery personnel and nearby residents were performed using the recommended method by the Singapore Occupational Health Services Pte Ltd.
Results: Hydrogen sulfide and sulfur dioxide were introduced as the most dangerous chemicals. According to the results, the highest risk value for sulfur dioxide among the exposure groups was related to the sulfur recovery unit (SRU), the west side of the Train Gas unit and the gate pass building of the refinery, and the highest risk values for sulfur dioxide among the exposure groups were related to the HSE building, security door, fire stations building, tanks, steam generating unit, west side of Train Gas unit, dining hall and gate pass building of the refinery. Hydrogen sulfide obtained a low to medium risk level, and sulfur dioxide a low to high risk level in terms of frequency.
Conclusion: This model can be considered as a suitable and quick solution in the superior management of the concentration of pollutants and also a promising solution in order to increase the ability of decision makers to assess the health risk of industries’ personnel. Also, ensuring quality   monitoring results and reducing sampling costs are discussed.

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Introduction: Fire in hospitals and medical centers can lead to unfortunate and dire accidents due to the immobility of most patients, the presence of expensive medical equipment, and the essential role of hospitals in providing health services to people. This study aims to increase fire safety in a healthcare training center in Qazvin.
Material and Methods: The latest NFPA 101A was used for fire risk assessment in seven departments of an educational hospital in Qazvin City in 2021-2022. The study calculated the residential risk factor for residents of each area, examined fire safety parameters and determined their risk factor, calculated the obtained points of the area under evaluation, determined the minimum required points in different areas of fire safety, and estimated the fire risk level.
Results:  ICU 1 and 2 departments, CCU 1 and 2, central warehouse, pharmacy warehouse, and hospital facilities were selected for fire risk assessment. The ICU building had the best condition with a total fire safety point of 21.1. The facility building, with a total fire safety point of -14.5, was in the worst condition.
Conclusion: The results showed the need for more attention from researchers to conduct studies in outdoor environments, in various parts of the country, on development and validation of novel heat stress indices, and on implementation and evaluation of control measures in environments with high heat stress.

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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 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: 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: 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: 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.