Journal of Health and Safety at Work

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Introduction: Volatile organic compounds such as xylene are one of the main air pollutants. Adsorption method are of the most common methods used in the control of volatile organic compounds. The aim of this study was to investigate the xylene removal from air through nano activated carbon adsorbent in comparison with NIOSH approved carbon adsorbent.
 

Material and Method: Xylene adsorption tests on nano activated carbon and activated carbon in static mode (batch) were done in glass vials with volume of 10 ml. Gas chromatography with FID detector was used for analysis. Various variables including contact time, amount of adsorbent, concentration of xylene, and temperature were studied.
 

Results: Absorption capacity of xylene at ambient temperature (25° C) in static mode and duration of 10 minutes for activated carbon and nano activated carbon was obtained 349.8 and 435 mg/g, respectively. Results of Scanning Electron Microscope (SEM) images of nano activated carbon showed particle size pf less than 100 nm. Furthermore, Transmission Electron Microscope (TEM) pictures showed particle size of 30 nm. XRD images also showed cube structure of nano activated carbon adsorbent.
 

Conclusion: The results showed that adsorption capacity at constant humidity increased by raising in temperature and contact time. What is more, nano activated carbon absorbent showed greater absorption capacity for xylene removal compared to activated carbon absorbent

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Introduction: Volatile organic compounds from industrial activities are one of the most important pollutants released into the air and have adverse effects on human and environment. Therefore, they should be removed before releasing into atmosphere. The aim of the study was to evaluate xylene removal from air by nano-grapheme and nano-graphene oxide in comparison with activated carbon adsorbent.

Material and Method:  After preparing adsorbents of activated carbon, nano-graphene, and nano-graphene oxide, experiments adsorption capacity in static mode (Batch) were carried out in a glass vial. Some variables including contact time, the amount of adsorbent, the concentration of xylene, and the temperature were studied. Langmuir absorption isotherms were used in order to study the adsorption capacity of xylene on adsorbents. Moreover, sample analysis was done by gas chromatography with Flame Ionization Detector (GC-FID).

Results: The adsorption capacities of activated carbon, nano-graphene oxide and nano-graphene for removal of xylene were obtained 349.8, 14.5, and 490 mg/g, respectively. The results of Scanning Electron Microscope (SEM) for nano-graphene and nano-graphene oxide showed particle size of less than 100 nm. While, the results of Transmission Electron Microscope (TEM) showed particle size of 45nm for nano-graphene and 65 nm for nano-graphene oxide. Also, X-Ray Diffraction (XRD) showed cube structure of nano-adsorbents.

Conclusion: In constant humidity, increase in exposure time and temperature caused an increase in the adsorption capacity. The results revealed greater adsorption capacity of xylene removal for nano-graphene compared to the activated carbon, and nano-graphene oxide.

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Introduction: Nurses of the emergency department experience stressful events that affect their mental health and reduce the quality of their work life. Career adaptability is considered a personal capability that enables employees to adapt to changes and avoid the negative consequences of job mismatch. This study was conducted to study career adaptability and its correlation with the quality of work life in the emergency department.
Material and Methods: This descriptive-correlational study was conducted on 104 nurses in the emergency department of teaching–therapeutic hospitals in Tabriz who were selected using random stratified sampling. Data was collected using a demographic checklist, the Career Adapt-Abilities Scale (CAAS) by Savickas, and the Quality of Nursing Work Life (QNWL) scale by Brooks & Anderson. Data were analyzed in SPSS using descriptive statistics (frequency, mean and standard deviation) and inferential statistics (independent t-test, one-way analysis of variance, Pearson’s correlation coefficient, and linear regression analysis).
Results: The total scores of career adaptability and the quality of nursing work life were 88.55±25.01 from the achievable range of 24-120 and 141.15±22.56 from the achievable range of 42-252, respectively, which were moderate. In this study, 85.6% of nurses enjoyed a moderate quality of work life. Furthermore, the results of Pearson’s correlation indicated a significant positive correlation between career adaptability and scopes with the quality of work life score (p=0.05). Regression analysis results indicated that career adaptability significantly predicts the quality of nursing work life (p=0.000).
Conclusion: In this study, nurses experienced moderate career adaptability and quality of work life. Given the above factors, and considering adaptability as a variable predicting quality of work life, it is suggested to take measures to increase career adaptability in nurses through training or consulting interventions to improve the quality of nursing work life.

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Introduction: Volatile organic compounds (VOCs) are hazardous toxic pollutants in the air, which are released from various industrial sources. Due to the adverse effects of xylene on health, the effective removal of VOCs from the air by nano sorbents is crucial. In this study, nanographene (NG) and nanographene oxide (NGO) were used as adsorbents to investigate the efficiency of xylene removal.
Material and Methods: In this study, in order to investigate the absorption efficiency of nanographene and nanographene oxide after the synthesis of nano absorbents in a dynamic system, xylene vapor was produced in a chamber in pure air and stored in a Tedlar sampling bag and then transferred to the adsorbent. Subsequently, the effect of various parameters such as xylene concentration, inlet air flow rate, and absorbent mass values at 32% humidity and 25°C temperature on the absorption rate and performance of the desired absorbents was investigated. Finally, the gas chromatographic flame ion detector (GC-FID) determined the concentration of xylene in air after the adsorption-desorption process.
Results: The average adsorption efficiencies for NG and NGO were found to be 96.8% and 17.5%, respectively. The characteristics of the NG and NGO adsorbents indicated that the particle size range was less than 100 nanometers.
Conclusion: The results demonstrated that the adsorption efficiency of NG for the removal of xylene from the air is higher than that of NGO. The GC-MS method validated the proposed approach in real air samples.

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Introduction: With the rapid development of new chemicals across various industries and the growing need for efficient and accurate toxicity assessments, in silico methods have emerged as a screening tool due to their cost-effectiveness, time efficiency, and reduction in animal testing. The aim of this review is to examine the existing studies on the application of in silico methods in predicting the toxicity of chemical compounds in occupational and industrial settings.
Material and Methods: This systematic review follows established protocols and is based on data extracted from reputable scientific databases such as PubMed, Scopus, and Web of Science. The review analyzes articles published between 2000 and 2024 that utilized in silico methods for toxicity prediction in occupational toxicology. Inclusion criteria focused on studies that applied modeling, simulation, and prediction methods primarily to chemical toxicity in workplace environments. Also, the quality assessment of the articles was done using the STROBE form.
Results: This study surveyed 13 articles on computer simulation of chemical compounds from 2000 to 2024. The majority of research was conducted between 2020 and 2024. The reviewed articles, based on the STROBE form, had a moderate to high quality. Various methods, including Quantitative Structure-Activity Relationship (QSAR), machine learning, and molecular dynamics, were widely used to predict the toxicity of chemical compounds, with the predictive accuracy of these models generally being high. The results also indicated that QSAR methods had the most application in studies predicting the toxicity of chemical compounds used in industries.
Conclusion: In silico methods, using molecular descriptors and structural data, have shown high accuracy in predicting toxicity. However, challenges such as limitations in reliable data, the need for model improvement, lack of experimental data, and the complexity of chemical interactions exist. The results indicated that the use of computational methods can significantly reduce the need for animal testing and improve risk assessment. These studies also emphasize the importance of improving and developing predictive models to enhance their accuracy and applicability. Overall, it can be said that modeling can serve as an effective tool in reducing costs and improving safety in workplace environments. 
 

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Introduction: Students play a key role in shaping the future of any society and spend a significant amount of time in educational environments. Creating an optimal learning environment requires close attention to factors affecting student well-being, particularly thermal comfort and indoor air quality. This study aims to systematically review the existing literature on thermal comfort and ventilation systems in schools.
Material and Methods: This systematic review was conducted based on the Cochrane methodology, involving a comprehensive search of three major databases — Scopus, Web of Science, and PubMed — for articles published between 2020 and 2024. The inclusion criteria encompassed peer-reviewed, conference, and review articles published in English that included the keywords “thermal comfort,” “ventilation,” and “school” in their title, abstract, or keywords. Studies focusing on preschools, universities, or other non-primary/secondary educational settings, as well as those conducted during the COVID-19 pandemic, were excluded.
Results: A total of 42 articles were selected after a rigorous screening process. The highest number of publications was reported in 2023. Key findings included: Most studies focused on elementary and secondary schools. The majority of research was conducted during the summer season, which may limit generalizability across seasons. There was considerable variation in CO₂ levels, with some exceeding recommended standards. In simulation studies, DesignBuilder and EnergyPlus were the most frequently used software tools. Additionally, results showed that: Indoor air quality and thermal comfort are significantly influenced by the type of ventilation system. Schools using natural ventilation often experienced higher CO₂ concentrations and lower thermal comfort than recommended. Implementation of Demand-Controlled Ventilation (DCV) has shown promise in improving indoor air quality and reducing pollutant levels.
Conclusion: This paper can contribute to the improvement of educational space design, enhancement of student learning, and promotion of indoor environmental health. It also provides insights into the latest methods for measuring and simulating thermal comfort and indoor air quality. For more practical outcomes, long-term studies with larger sample sizes across different seasons and times of day are needed. Combining computer simulations with real-world measurements can support cost-effective and optimized design of educational spaces. Future research should focus on standardizing temperature, humidity, CO₂ levels, and selecting the most appropriate ventilation strategies for classrooms.