Evaluation of individual and environmental sound pressure level and drawing noise-isosonic maps using Surfer V.14 and Noise at Work V.5.0

Noise pollution is one of the common physical harmful factors in many work environments. The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0. This cross-sectional, descriptive study is analytical that was conducted in 2018 in the Paste factory that contains Canister, production and Brewing unit. Following ISO 9612:2009, Casella Cel-320 was used to measure personal sound pressure level, while CEL-450 sound level meter (manufactured by Casella-Cel, the UK) was employed to assess environmental sound pressure level. Statistical analyzes was done using SPSS V.18 and Linear Regression test. The sound-isosonic maps were projected using Surfer V. 14 and Noise at work V.5.0. The results of assessing personal sound pressure level indicated that the highest received dose (172.21%) and personal equivalent sound level (87.36 dBA) were recorded for workers in the Canister unit. According to results of measuring of the environmental sound pressure level, out of 16 measurement stations in this unit, overall 87.5% were regarded as danger and caution areas. The lowest and highest sound pressure levels in this units were 61 dBA and 92 dBA that belong to Brewing and Canister units respectively. Results indicate Over 75% of the Canister and production units had a sound pressure level greater than 85 dBA and these two units were regarded as the most dangerous area in terms of noise pollution. It is therefore necessary to implement noise control measures, apply hearing protection program and auditory tests among workers in these units

The effects of live-fire drills on visual and auditory cognitive performance among firefighters

Introduction: The nature of firefighters� work is characterized by its unexpected emergencies, sleep deprivation, night shift schedules, and smoke exposure during firefighting. Methods: Eighteen firefighters were involved in simulated live-fire activities. Firefighters� health status in terms of cardiovascular and mental conditions was checked by a physician and through reviewing their medical records. Firefighters� cognitive functions were evaluated by visual and auditory continuous performance tests (VCPT and ACPT) and paced visual and auditory serial addition tests (PVSAT and PASAT). Results: VCPT and ACPT scores were lower after the activity relative to baseline. The results revealed that ACPT appears to be more difficult than VCPT. Also, PVSAT and PASAT scores decreased significantly after the experiment. PASAT scores following firefighting tasks experienced a more significant decline compared to those of the PVSAT. Conclusions: These findings suggest that firefighters have visual and auditory cognitive function problems following firefighting activities. In conclusion, auditory cognitive function was more influenced than the visual ability as a result of the experiment. © 2020 The Author(s)

Weighing and modelling factors influencing serum cortisol and melatonin concentration among workers that are exposed to various sound pressure levels using neural network algorithm: An empirical study

Background: Noise is one of the most common harmful agents in the workplace. Exposure to excessive noise can lead to complications such as cardiovascular disorders, disturbance of body hormones� rhythm and hearing loss. This study aimed at weighing and modelling factors influencing serum cortisol and melatonin concentrations of workers that are exposed to various sound pressure levels using neural network algorithm. Methodology: A case-control design was adopted in the current research. The required data were collected from 75 industrial and mining firm staff members. They were assigned to three groups with equal sample sizes (25 workers). In developing the conceptual model in regard to variables that may affect workers� serum cortisol and melatonin concentration, SPL, age, weight, and height were included. The influence of SPL on serum cortisol concentration as assessed in the three shifts. Moreover, radioimmunoassay (RIA) was utilized to assess serum cortisol and melatonin concentrations. Neural network algorithm was subsequently exploited to weigh and model predictor factors. IBM SPSS Modeler 18.0 was the software program used for data analysis. Results: The average cortisol concentration values for administrative, condensing, and pelletizing units respectively were 10.24 ± 2.35, 12.15 ± 3.46, and 14.91 ± 4.16Formula presented. On the other hand, the average melatonin concentration values for administrative, condensing, and pelletizing units respectively were 37 ± 12.52, 34 ± 13.15, and 27 ± 9.54Formula presented. According to the results of the developed model for cortisol, SPL3 (32%) and age (5%) respectively had the highest and lowest impact. On the other hand, considering the model developed for melatonin, height (27%) and SPL1 (10%) were the most and least influential factors in that order. The accuracy rates of the model were also found to be 95% for cortisol and 97% for melatonin. Conclusion: Comparing cortisol concentrations during various shifts revealed a significant reduction (from the beginning to the end of the shift) in all the three groups. Further, the rise of SPL would result in higher secretion of cortisol. Moreover, in all the three groups, the average serum melatonin concentration went up from the beginning to the middle of the shift and then declined to the end of the shift. Considering the accuracy rates of the models developed to predict hormones, neural network algorithm is a suitable and powerful tool for weighing and modelling factors influencing serum cortisol and melatonin concentrations. © 2020 The Author(s

Comparing Universal Thermal Climate Index (UTCI) with selected thermal indices/environmental parameters during 12 months of the year

Heat stress negatively influences human health and performance, and leading to lower efficiency in daily activities. The present study sought to examine the relationship between UTCI, other heat indices (SET, PET, PMV, PPD, and WBGT), and environmental parameters. Daily data, encompassing a 12 month period in 2016 (from 6 a.m. to 9 p.m. for each day), were retrieved from the Meteorological Organization of Kerman. The data were fed into SPSS 20, followed by conducting Pearson product moment correlation and linear regression to find the association between UTCI and other heat indices/environmental parameters. Excel 2016 was also utilized to draw the relevant diagrams. Significant correlations were detected between UTCI and other heat indices (SET, PET, PMV, and WBGT). UTCI also was measurably correlated with environmental parameters like dry temperature (P < 0.0001). The highest correlation coefficient was observed between UTCI and PET (r = 0.96). UTCI also had strong correlations with WBGT (r = 0.88), SET (r = 0.87), and dry temperature (r = 0.90). Thus, indices that are calculated based on body thermal equation (i.e. SET and PET) are more strongly connected with UTCI, registering a better slope. On the other hand, WBGT is more similar to UTCI (than other indices) in terms of thermal perception. Keywords: Heat indices, Heat, Thermal climate, Temperatur

The association between wet-bulb globe temperature and other thermal indices (DI, MDI, PMV, PPD, PHS, PSI and PSIhr): a field study

The current study aimed at comparing the correlation coefficients between wet-bulb globe temperature (WBGT) and a number of parameters, including the discomfort index (DI), modified discomfort index (MDI), predicted mean vote (PMV), predicted percentage of dissatisfaction (PPD), predicted heat strain (PHS), physiological strain index (PSI) and physiological strain index heart rate (PSIhr). In total, 30 workers of a pelletizing factory participated in this study. Environmental parameters and workers� physiological parameters were measured in 10 working stations. The results showed that effective WBGT (WBGTeff) strongly correlates with DI, MDI, PMV, PPD, PHS, PSI and PSIhr. WBGTeff had the highest correlation coefficients with PMV, MDI, PHS and PSIhr. Based on the obtained results, it was concluded that heat stress exceeded the standard limit for a number of indices in some of the working stations. Thus, some controlling measures should be taken to reduce heat stress in these stations. © 2018, © 2018 Central Institute for Labour Protection�National Research Institute (CIOP-PIB)