Journal of Health and Safety at Work

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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.