Case Study in a Working Environment Highlighting the Divergence between Sound Level and Workers’ Perception towards Noise

BackgroundMachines, processes, and tasks in the iron and steel factories may produce noise levels that are harmful to hearing if not properly controlled. Studies documenting noise exposure levels and related determinants in sub-Saharan Africa, including Tanzania are lacking. The aim of this study was to document noise exposure and to identify determinants of noise exposure with a view to establishing an effective hearing conservation programme.MethodsA walk-through survey was conducted to describe the working environment in terms of noise sources in four metal factories (A–D) in Tanzania. Noise measurements were conducted by both personal, full-shift noise measurements (8 h) using dosimeters and area measurements (10-s measurements) using a sound level meter. A total of 163 participants had repeated personal noise measurements (Factory A: 46 participants, B: 43, C: 34, and D: 40). Workers were randomly selected and categorized into 13 exposure groups according to their job. Linear mixed effects models were used to identify significant determinants of noise exposure in the furnace section and the rolling mill section.ResultsThe average personal noise exposure in the four factories was 92.0 dB(A) (range of job group means; 85.4–96.2 dB(A)) (n = 326). Personal exposure was significantly higher in the rolling mill section (93.0 dB(A)) than in the furnace section (89.6 dB(A)). Among the job groups, the cutters located in the rolling mill section had the highest noise exposure (96.2 dB(A)). In the furnace section, furnace installation (below the ground floor), manual handling of raw materials/billets/crowbars, and billet weighing/transfer were significant determinants explaining 40% of the total variance in personal noise exposure. In the rolling mill section, the size of the cutting machine, steel billet weight and feeding re-heating furnace explained 46% of the total variance in personal noise exposure. The mean noise level of the area measurements was 90.5 dB(A) (n = 376).ConclusionWorkers in the four iron and steel factories in Tanzania were exposed to average noise of 92.0 dB(A), without using hearing protection, implying a high risk of developing hearing loss. Task and factory level determinants were identified in the furnace and the rolling mill sections of the plant, which can inform noise control in factories with similar characteristics.

Mobile sound level applications have been proposed as potential adjuncts for conventional sound level meters (SLM) in noise measurement. However, their performance remains uncertain in the manufacturing industry setting. This study was aimed to determine the validity, reliability, and agreement of the NIOSH SLM app in measuring noise in the manufacturing industry with reference to conventional SLM. A total of 93 samples were collected from five machineries. An iPhone 12 Pro and an iPhone 12 mini, each installed with the latest version of NIOSH SLM app, were tested against the conventional SLM (as gold standard). Three noise parameters, namely the average noise level (i.e., LAeq), maximum sound level (i.e., LMax) and 8-hour time-weighted average (i.e., TWA-8 h) were measured by all devices. Concurrent validity was assessed using Pearson’s correlation coefficient while two-way mixed effects intraclass correlation coefficient (ICC 3,1) was used to assess the intra-rater reliability. The agreement in the noise parameters measured was assessed using the Bland-Altman plot. The NIOSH SLM app demonstrated high concurrent validity, as measured by Pearson’s correlation (p < 0.001) and moderate-to-good reliability, as measured by ICC 3,1 (p < 0.001) in all three noise parameters measured. The LAeq and TWA-8 h measured by the NIOSH SLM app were in agreement with the conventional SLM, with the exception of LMax. The NIOSH SLM app is valid and reliable in measuring noise when compared to conventional SLM. Two out of three noise parameters measured by NIOSH SLM app were agreeable to that measured by the conventional SLM.

A methodological development is proposed to compare the results of measurements of the equivalent level of noise exposure (ambient sound) and SEL in urban areas near traffic routes obtained in the conventional way by using a fixed-point sound level meter and mobile noise dosimeters with respect to the location of the sound level meter. Class I calibrated equipment is used for the sound level meter and Class II for the dosimeter. Comparisons are made by maintaining a fixed point location for the sound level meter and using 1 dosimeter for measurements in different media moving with reference to the fixed point. The investigation is ongoing. To simulate the measured scenarios a mathematical model, from the Department of Mechanical and Energy Engineering of the Miguel Hernandez University of Elche (Spain), is used to compare measured results against model results. The field values are used to calibrate the model validating it for use when it is necessary to have exposure values at different heights. The first results show an appreciable difference between noise exposure results in the conventional way, for different environments in urban areas close to traffic routes, with the highest incidence on pedestrians.

Maximum sound pressure levels are commonly used for environmental noise and building acoustics measurements. This paper investigates the signal processing errors due to Fast or Slow time-weighting detectors when combined with octave band filters, one-third octave band filters or an A-weighting filter. For 6th order Butterworth CPB filters the inherent time delay caused by the phase response of filters is quantified using three different approaches to establish the following rules-of-thumb: (1) time-to-gradient/amplitude matching occurs when Bt≈1, (2) time-to-peak matching occurs when Bt≈2 and (3) time-to-settle matching occurs when Bt≈4 for octave band filters, and when Bt≈3 for one-third octave band filters. Four different commercially-available sound level meters are used to quantify the variation in measured maximum levels using tone bursts, half-sine pulses, ramped noise and recorded transients. Tone bursts indicate that Slow time-weighting is inappropriate for maximum level measurements due to the large bias error. The results also show that there is more variation between sound level meters when considering Fast time-weighted maximum levels in octave bands or one-third octave bands than with A-weighted levels. To reduce the variation between measurements with different sound level meters, it is proposed that limits could be prescribed on the phase response for CPB filters and A-weighting filters.

Cyclist noise exposure has implications for health, comfort, and safety. Methods used for in situ measurement of on-road noise levels for cyclists vary, and the effects of key study design factors have not been investigated. To enable reliable research into cyclist noise exposure, this study aims to determine the accuracy of smartphone noise measurements in comparison with a sound level meter (SLM) reference instrument, and how noise levels are affected by travel speed, air speed, sensor placement, and use of a windscreen. Field data were collected with paired instruments in a typical urban cycling scenario, and comparisons made varying one design factor at a time (smartphone versus SLM, with versus without windscreen, handlebar versus shoulder placement, etc.). Results show that smartphones can generate reliable measurements (compared with SLM) of high-resolution (1-s) cyclist exposure for C-weighted noise, but not A-weighted noise. Sensor placement and windscreen have small effects on noise readings, but air speed and travel speed greatly affect measured noise levels. Future studies measuring on-road noise must consider the effects of wind- and bicycle-generated noise to ensure internal validity. Studies should also consider both study objectives and instrumentation when selecting a noise measure (frequency weighting). Research is needed into bicycle noise generation and perception of traffic noise by cyclists to enhance the reliability of future studies.

Noise exposures in different community settings measured by traditional dosimeter and smartphone app

Audiometers—A Closer Look

Background & Aims: Noise exposure can impact nurses' performance and may result in disruptions to their tasks.This study aimed to examine the correlation between the average equivalent sound level and the occurrence of medication errors. Materials & Methods:This cross-sectional study involved 150 nurses in Iran in 2020.First, two medical and two surgical wards were randomly selected using a coin toss method.Second, the nurses who worked in those wards were sampled using the convenience method.Nurses' medication errors were assessed using a questionnaire.A sound level meter was used to measure the sound level in decibel.Data were analyzed using analytical tests, including Kruskal-Wallis, Spearman correlation coefficient, and Poisson model. Results:The mean sound equivalent level in the cardio-respiratory internal ward (58.94 ± 1.88) was higher than the same level in the other internal and surgical wards (p < 0.001).An increase in the mean sound equivalent level in the wards was accompanied by an increase in the mean number of medication errors among unmarried individuals (e 0.22 = 1.25), which was 1.25 times more than the errors made by married individuals.Finally, an increase in age and the mean sound equivalent level resulted in the occurrence of medication errors (p < 0.002). Conclusion:The results showed that there was no relationship between the sound pressure level and nurses' medication errors in the research environment.Therefore, it is necessary to conduct more studies to investigate the factors that increase the incidence of medication errors.

Introduction:Exposure to high levels of noise is a problem among tea factory workers worldwide, but it is poorly studied in India.Aims:This study aimed to assess noise generation in various parts of a black tea factory and find out prevalence of occupational noise-induced hearing loss (ONIHL) and its determinants among employees.Materials and Methods:An observational cross-sectional study was performed in a black tea processing factory of Darjeeling District. Noise levels and exposure data at different parts of the factory were measured using a sound level meter. Participant characteristics were obtained using a questionnaire and noise-induced hearing loss data obtained by audiometry. A sound map was generated based on noise exposure data and a multivariable logistic regression performed to assess determinants of ONIHL.Results:Sound pressure levels ranged from 58.7 to 90.3 dBA, with the highest levels in the crushing–tearing–curling (CTC) room. Noise exposure of workers was the highest during curling process and the lowest during packaging in the packing room. The prevalence of ONIHL was found to be 28.3%, most of which were of moderate degree, and the highest prevalence was among CTC room workers. Multivariable analysis showed significant association only between daily noise exposure and the presence of ONIHL (AOR 1.68, P value = 0.018). None of the study participants used any hearing protection equipment during work.Conclusions:Generation of high levels of noise is a pertinent problem in the black tea factory, which, coupled with non-use of personal protective equipment, led to a high risk and prevalence of ONIHL.

Background: Industrial noise exposure is a significant occupational hazard, with prolonged exposure leading to irreversible noise-induced hearing loss (NIHL). This study examines the relationship between occupational factors (noise exposure, work tenure, hearing protective device usage, and worker age) and hearing impairment among production workers at PT Binder Indonesia, a manufacturing company with high-intensity noise levels (90–100 dBA). Methods: A cross-sectional analytic study was conducted with 176 male workers aged 20–65 years, exposed to ≥85 dBA noise for ≥5 years. Data were collected through noise level measurements (Sound Level Meter), hearing tests (Rinne, Weber, Schwabach), and questionnaires. Statistical analysis included chi-square tests and prevalence ratios (PR) with 95% confidence intervals (CI) using SPSS. Results: Hearing impairment was prevalent in 60.2% of workers. Significant relationships were found between work tenure &gt;5 years (PR=1.640; 95% CI: 1.174–2.291; *p*=0.001) and age ≥40 years (PR=0.725; 95% CI: 0.576–0.913; *p*=0.014). Noise exposure (&gt;85 dB) and hearing protective device usage showed no significant relationship (*p*&gt;0.05). Conclusion: Long work tenure increases NIHL risk, while older age may have a protective effect, possibly due to adaptive measures. Despite high noise exposure, consistent use of protective devices did not significantly reduce impairment, suggesting the need for improved compliance and workplace interventions.

Noise level measurement (using a sound level meter GM1352 device) was carried out in Federal University of Technology, Owerri (FUTO). Noise measurements were taken in 36 different locations covering the six schools of the university. These measurements were taken at the onset of working hours (9am), during peak working hours (12pm) and at the closure of work (3pm). The average noise levels measured was 67.78-dB for 9-am, 71.07-dB for 12-pm and 67.79-dB for 3-pm respectively. The higher noise levels were measured when lectures and school activities were at its peak (12 pm) and most of the power generating sets were turned on. The result indicated that the minimum noise level of the school environment is gotten at the morning hours (9am) when daily activities in the school were just kicking off. These noise level from studies were found to be within the range that may cause both cognitive and non-auditory effects on students and lecturers alike.

Excessive environmental noise and poor air quality can be adverse to human health, living comfort and the environment itself. Measurement of sound pressure levels and air quality in critical areas including libraries, campus areas, public parks and hospitals thus becomes necessary to monitor and mitigate existing noise levels. In a university environment, student activities will be less disrupted if the locations of the activities are sufficiently away from noise sources. The present study is intended to measure sound levels and air quality around the Engineering Complex, Universiti Teknologi Mara, Shah Alam. The measured data is compared with to acceptable sound pressure levels and air quality index specified by the Department of Environment (DOE), Malaysia. Sound pressure levels are measured using the Castle Sound Level Meter Type 6224 and air quality measurement was done by using the BW Gas Alert MicroClip XT device. Both measurements were conducted at five selected stations around the Engineering Complex for three times each weekday for five weeks. Results obtained indicated that sound levels at some locations and time zones are above the thresholds recommended by the DOE. The air quality is acceptable in most locations except the vicinity of a bus stop. With the growing number of students in the university and other factors like construction and redevelopment of existing roads, a continuously increasing noise situations and air pollution proportional to the traffic flow is inevitable.

Transport conveys substantial socioeconomic benefits. It is a vital sector that facilitates progressive developments in economy of a nation. Advantages derived from transportation sector are vital in the integration of various regions and sectors of the economy of nations. Despite this advantage, one of the negative externalities it exhibits is noise pollution ‘an unwanted and undesirable sound’. Excessive noise in an environment is identified to constitute the most disturbing among the city pollutants and this is a serious urban crisis in Akure. This study ascertains the level of awareness of the users of transport services on the impact of transportation on the environment in Akure South LGA. and determines the effects of Noise pollution on the residents in the study area. Noise level measurement was done using a PCE-322A sound level meter and direct interview was conducted with residents and other road users. Noise data were collected at different time intervals to find out the variation of sound levels. Based on the findings, respondents reported that the most disturbing period of the day was evening (peak period) between 3 pm and 5.00 pm. The findings revealed that the level of awareness of negative effects of noise pollution is significantly low. The study recommended that pubic needs to be sensitized on the negative externalities of vehicular noise pollution and the need to curtail it.

Transport conveys substantial socioeconomic benefits. It is a vital sector that facilitates progressive developments in economy of a nation. Advantages derived from transportation sector are vital in the integration of various regions and sectors of the economy of nations. Despite this advantage, one of the negative externalities it exhibits is noise pollution ‘an unwanted and undesirable sound’. Excessive noise in an environment is identified to constitute the most disturbing among the city pollutants and this is a serious urban crisis in Akure. This study ascertains the level of awareness of the users of transport services on the impact of transportation on the environment in Akure South LGA. and determines the effects of Noise pollution on the residents in the study area. Noise level measurement was done using a PCE-322A sound level meter and direct interview was conducted with residents and other road users. Noise data were collected at different time intervals to find out the variation of sound levels. Based on the findings, respondents reported that the most disturbing period of the day was evening (peak period) between 3 pm and 5.00 pm. The findings revealed that the level of awareness of negative effects of noise pollution is significantly low. The study recommended that pubic needs to be sensitized on the negative externalities of vehicular noise pollution and the need to curtail it.

This Recommendation deals with sound level meters, i.e. instruments for the measurement of frequency and time weighted sound pressure levels. It contains an appropriate test scheme for pattern evaluation and verification and a test report format for pattern evaluation.