Equivalent Continuous Sound Pressure Level Research Articles

A study on the control indices and emission limits of substation noise

Equivalent continuous A-weighted sound pressure level (LAeq) underestimates the influence of low-frequency components of substation noise, so it is necessary to optimise control indices and emission limits of substation noise. To this end, 148 noise samples from 110 kV–1000 kV substations were selected. 280 subjects were randomly recruited for listening tests in which the 11-point numerical scale specified by ISO 15666-2021 was used. The mean noise annoyance (Am) of each noise sample was obtained to establish the LAeq-Am model of substation noise. Meanwhile, the LAeq-LFNR model was established based on the low-frequency noise rating number (LFNR) proposed by Broner. Based on these models, the LFNR corresponding to the limit of LAeq could be determined. The limit of sound pressure level of substation noise was proposed at each 1/1 octave band from 31.5 Hz to 500 Hz and the limit-exceeding ratio for the existing substations noise of China was analyzed. Results showed that Am of 500 kV–1000 kV substation noise was 1.0 higher than that of 110 kV–220 kV substation noise on average when LAeq was 25 dBA–80 dBA. LAeq of the latter were 6.1 dBA higher than that of the former on average when Am was 1–10. It was estimated that utmost 20 % of substations need further to take noise control measures in order to meet the limit suggested by this study in China. Binding with the limit of LAeq, the limit of sound pressure level at each octave band proposed according to equal noise annoyance can better evaluate the influence of substation noise.

Physiological evaluations of low-level impulsive sounds generated by an air conditioner.

Air conditioners are typically installed in buildings and vehicles to control thermal conditions for long periods of time. Air conditioners generate certain types of sounds while functioning, which are among the main noise sources in buildings and vehicles. Most sounds produced by the air conditioner do not change with time, and the sound quality of steady sounds has been investigated. However, air conditioners can generate low-level impulsive sounds. Customers complain of the discomfort caused when these sounds disturb the silence in their living rooms and bedrooms. This study aimed to determine the physical factors that have a significant effect on physiological responses to low-level impulsive sounds produced by air conditioners. We used physiological responses because it is difficult for people to evaluate sounds psychologically when they are sleeping or are not focused on the sounds. The A-weighted equivalent continuous sound pressure level (LAeq) and the factors extracted from the autocorrelation function (ACF) were evaluated as physical factors. Participant responses on electroencephalography (EEG) were evaluated. The correlation between the EEG responses and ACF factors was determined. The LAeq, peak, and delay time to the first maximum peak of the ACF were identified as significant factors for physiological responses to low-level impulsive sounds.

Multiple effects of visual-acoustic-thermal perceptions on the overall comfort of elderly adults in residential outdoor environments

We selected typical residential outdoor spaces and five common sounds (birdsong, dance music, traditional opera, conversation and traffic sound) with three A-weighted equivalent continuous sound pressure level (LAeq) (60, 70 and 80 dBA) as visual-acoustic-thermal conditions. 458 elderly adults completed a subjective questionnaire while environmental parameters (meteorological parameters, illumination intensity (LUX), visible green index (VGI) and LAeq) were simultaneously measured to determine effects of visual-acoustic-thermal perceptions on overall comfort. We found that: 1) When physiological equivalent temperature (PET) was above 43.80 °C, the elderly felt thermally uncomfortable. Older adults perceived traffic sound as acoustic uncomfortable when LAeq was higher than 66.1 dBA. A higher VGI decreased the sensitivity of respondents to LUX. 2) Thermal sensation vote (TSV) and thermal comfort vote (TCV) were susceptible to the acoustic and visual environments. The influence of the visual environment and PET on acoustic sensation vote (ASV) and acoustic comfort vote (ACV) were not significant. We found a significant correlation between PET and sunlight sensation vote (SSV). 3) Acoustic and thermal comfort had a one-vote veto tendency relative to overall comfort, but no absolute veto power. Thermal comfort was the most important factor affecting overall comfort in summer while acoustic comfort was the most important in spring. 4) A binary logistic regression to predict overall comfort of elderly adults had 84.7 % accuracy, indicating a good performance.

Evaluation of Soundscape Variations through the Open Public Spaces in Saharan Cities: A Case of Biskra, Algeria

This study aims initially to evaluate the quality of different soundscapes in the public space of the city of Biskra, in Algeria. A total of 35 participants took part in a laboratory experiment, where 28 sound clips of one-minute duration taken from public spaces in the city were used as stimuli. The A-weighted equivalent continuous sound pressure level (LAeq,1min) was calculated. The participants rated the quality of the soundscape using attribute scales provided in their own native language. The results of the questionnaire on the recorded soundtracks confirm that the immediate environment affects the ambient sound level and the quality of the sound environment, where the sound environments of the areas located near the roads, with a high mechanical flow, are considered the most unpleasant and noisy, with a high A-weighted equivalent continuous sound pressure level (LAeq,1min). The findings of this study indicate that there are statistically significant correlations between pleasantness and loudness, presence of mechanical sounds, presence of non-mechanical sounds, and a sound exposure level. In addition, this study shows that there is a significant positive correlation between pleasantness and the presence of non-mechanical sounds. The results also showed an inverse relationship between the presence of mechanical and non-mechanical sounds, and that the absence of mechanical sounds allows natural and human sounds to be more audible, making the soundscape more pleasant and calm according to the results of the questionnaire. From this study, the duality LAeq,1min and the components of the soundscape are very representative indicators of the quality of the soundscape.

Psychological responses to low-level transient sounds in background sounds generated by an air conditioner

Although air conditioners are installed extensively in buildings to achieve thermal amenities over extended periods, they are considered as one of the primary noise sources in buildings. Air conditioners mostly generate sounds that remain constant over time, and the sound quality of these steady sounds has been evaluated in several studies. However, these appliances occasionally generate low-level transient sounds that disturb the users during sleep or at other times when they require silence. This study aimed to determine how users respond to low-level transient background noises generated by air conditioners and correlate their responses with existing physical factors. Subjective loudness, pitch, and annoyance were appraised using a paired comparison method. The A-weighted equivalent continuous sound pressure level (LAeq) and the factors evaluated using the autocorrelation function (ACF) were utilised to characterise low-level transient noises among several background sounds. Multiple linear regression analyses were performed using the statistical values of LAeq and ACF factors. The results revealed the following significant predictive variables used to assess subjective responses to low-level transient background sounds: the 10th percentile values of the delay time of the first maximum peak, width of the initial decay of the ACF, and the difference between the 10th percentile and 90th percentile values of LAeq and the amplitude of the first maximum peak. This suggests that pitch salience, spectral centroid, and the amount of level change can have significant effects on the user’s psychological response to low-level transient sounds among background sounds.

The Importance of Noise Attenuation Levels in Neonatal Incubators

Background: It is known that high noise levels can be harmful to preterm infants, causing physiological and psychological disorders. It is also known that premature babies spend a lot of time in an incubator. In this sense, many studies show that incubator noise levels can range from 45 to 70 dB. However, these differences in noise levels depend, fundamentally, on the wide range of methodology that can be used. This study aims to know the levels of noise from a fan in the incubator itself and how much it can isolate the noises coming from the outside. Methods: For this purpose, the noise levels of three incubators were measured within a sound-dampened booth for free-field audiometry. For the emission of acoustic energy, a pink noise generator was used; likewise, two microphones were placed, one inside the incubator cabin and the other outside, to determine the acoustic insulation levels of the tested incubators. Results: The incubators produced equivalent continuous sound pressure levels between 53.5 and 58 dB. Acoustic insulation analysis showed that levels varied from one incubator to another, between 5.2 and 10.4 dB. Conclusions: It is necessary to improve the acoustic insulation inside the incubator cabin and to reduce the noise levels of the motor fan. On the other hand, although the incubators are meeting the noise criteria set out in the IEC60601-2-19: 2009 standard of 60 dBA, under normal use conditions, they are still far from the limit recommended by the American Academy of Pediatrics (45 dBA).

Sound prediction based on footstep-induced vibrations in concrete building using a convolutional neural network

Heavy-weight impact sounds caused by footsteps are a major factor that affects acoustic comfort in concrete residential buildings. An impact monitoring system that predicts sound based on vibration could be beneficial to alter the behavior of the occupant causing excessive sound, or the stored data can be used by mediators in case of disputes to identify the sound source household and assess the disturbance. This study presents a method for predicting the actual impact sound especially footstep in the rooms of buildings. A convolutional neural network (CNN) was used as the prediction model and the signal from vibration sensors placed in the floors and walls of the room as input data. We experimentally collected a dataset and compared its performance according to the location of the vibration sensors and the resolution of the short-time Fourier transform (STFT) feature, which represents footstep-induced vibrations. The highest accuracy was achieved when the vibration signals of both the wall and floor slab were used simultaneously in the CNN model, with the frequency resolution of the STFT of 10 Hz and the window frame offset of 50 ms. The equivalent continuous A-weighted sound pressure level for 2 s was predicted with 0.99 dB as the mean absolute error, and the value of the coefficient of determination was 0.95. The performance of sound pressure level in the 63 and 500 Hz frequency bands achieved mean absolute error of 1.63–2.22 dB.

Study on Subjective Evaluation of Acoustic Environment in Urban Open Space Based on "Effective Characteristics".

With the continuous expansion of urban scale with dense population and traffic and the gradual improvement of residents’ requirements for environmental quality, the traditional evaluation method relying on acoustic energy is not enough to reflect the feelings of urban crowds about acoustic environment quality. The acoustic environment quality evaluation method based on human subjective perception has gradually become one of the research focuses in the field of environmental noise control. In recent years, various subjective and objective acoustic characteristic parameters have been introduced into the study of acoustic environment assessment in the global literature. However, the extraction of “effective characteristics” from a large number of physical and psychoacoustic characteristics contained in acoustic signals and the creation of a scientific and efficient subjective evaluation model have always been key technical problems in the field of acoustic environment evaluation. Based on subjective human perceptions, the overall acoustic environment quality evaluation of urban open spaces is studied in this paper. Based on the “effective characteristic” parameters and the subjective characteristic proposed in the previous research, including equivalent continuous A-weighted sound pressure level (LA), the difference between median noise and ambient background noise (L50 − L90), Sharpness (Sh), as well as satisfaction (Sat), the multivariable linear regression algorithm is used to further study the intrinsic correlation between the proposed “effective characteristics” and subjective perception. Then, a satisfaction evaluation model of the acoustic environment based on “effective characteristics” is built in this paper. Furthermore, the soundwalk evaluation experiment and the MATLAB numerical simulation experiment are carried out, which verify that the prediction accuracy of the proposed model is more than 92%, the consistency of satisfaction level is more than 88%, as well as the changes in the values of Sh and L50 − L90 have a significant impact on the satisfaction prediction of the proposed model. It shows that the proposed “effective characteristics” more comprehensively describe the quality level of the regional acoustic environment in urban open space compared with a single LA index, and the proposed acoustic environment satisfaction evaluation model based on “effective characteristics” has significant accuracy superiority and regional applicability.

No effect of occupational noise exposure on auditory brainstem response and speech perception in noise.

The primary aim of this study was to investigate whether auditory brainstem response (ABR) and speech perception in noise (SPiN) were associated with occupational noise exposure in normal hearing young factory workers. Forty young adults occupationally exposed to noise and 40 non-exposed young adults (control group) from Zhejiang province in China were selected. All participants presented with normal hearing thresholds and distortion product otoacoustic emissions. Participants were evaluated with the Mandarin Bamford-Kowal-Bench (BKB) test and ABR. The latter was obtained for click stimulus at 50, 60, 70, 80, and 90 dBnHL. Peak-to-trough amplitudes and latencies for waves I and V were obtained. The ABR wave I amplitude, the wave I/V amplitude ratio, the slope of the wave I amplitude growth as a function of stimulus intensity (AMP-ISlope), and the wave V latency shift with ipsilateral noise (LAT-VSlope) were used as ABR outcomes. Finally, equivalent continuous average sound pressure level normalized to 8 h (LAeq.8h) and cumulative noise exposure (CNE) were obtained for noise-exposed participants. No significant differences between groups were found for any ABR outcomes. Noise-exposed participants exhibited worse BKB scores than control group participants. A multivariate regression model showed that 23.3% of the variance in BKB scores was explained by group category (exposed vs. non-exposed) and hearing thresholds. However, since none of the ABR outcomes exploring cochlear synaptopathy were associated with noise exposure, we cannot conclude that cochlear synaptopathy was the contributing factor for the differences between groups for BKB scores. Factors that go beyond sensory processing may explain such results, especially given socio-economic differences between the noise-exposed and control groups. We conclude that in this sample of participants, occupational noise exposure was not associated with signs of cochlear synaptopathy as measured by ABR and BKB.

Influencing Factors Identification and Prediction of Noise Annoyance-A Case Study on Substation Noise.

Noise-induced annoyance is one person’s individual adverse reaction to noise. Noise annoyance is an important basis for determining the acceptability of environmental noise exposure and for formulating environmental noise standards. It is influenced by both acoustic and non-acoustic factors. To identify non-acoustic factors significantly influencing noise annoyance, 40 noise samples with a loudness level of 60–90 phon from 500–1000 kV substations were selected in this study. A total of 246 subjects were recruited randomly. Using the assessment scale of noise annoyance specified by ISO 15666-2021, listening tests were conducted. Meanwhile, basic information and noise sensitivity of each subject were obtained through a questionnaire and the Weinstein’s noise sensitivity scale. Based on the five non-acoustic indices which were identified in this study and had a significant influence on noise annoyance, a prediction model of annoyance from substation noise was proposed by a stepwise regression. Results showed that the influence weight of acoustic indices in the model accounted for 80% in which the equivalent continuous A-weighted sound pressure level and the sound pressure level above 1/1 octave band of 125 Hz were 65% and 15%, respectively. The influence weight of non-acoustic indices entering the model was 20% in which age, education level, noise sensitivity, income, and noisy degree in the workplace were 8%, 2%, 4%, 4%, and 2%, respectively. The result of this study can provide a basis for factors identification and prediction of noise annoyance.

Analysis of the Effects and Causes of Driver Horn Use on the Acoustic Environment at Urban Intersections in Taiwan

Car horns were originally installed in vehicles for safety. However, many urban areas in several countries face noise problems related to the use of car and motorbike horns. To propose measures to suppress the use of horns, relationships between horn use and factors including driver awareness and behavior, traffic environment, and the transportation system should be investigated. The present study therefore conducted surveys to grasp the current circumstances of horn use and traffic at urban intersections in Taiwan. The relationship between horn use and the traffic volume of standard-sized vehicles was found. According to an analysis of horn use during traffic signal cycles, in many cases, horns were honked after entering intersections to turn left. In particular, horns were honked when the driver waited more than 4 s for the car in front to start moving after the green light allowing left turns was turned on. An analysis of noise levels at intersections showed that the maximum noise level value (LAmax) could be reduced if vehicle horns were not used. Multiple regression analysis also indicated that LAmax values increased with the frequency of horn use. The equivalent continuous A-weighted sound pressure level (LAeq,10min) did not change with driver horn use, and increased with the traffic volume of motorcycles.

Applying kurtosis-adjusted equivalent continuous A-weighted sound pressure level to evaluate risk of occupational hearing loss associated with non-steady state noise

Applying kurtosis-adjusted equivalent continuous A-weighted sound pressure level to evaluate risk of occupational hearing loss associated with non-steady state noise

Are Smartwatches a Suitable Tool to Monitor Noise Exposure for Public Health Awareness and Otoprotection?

Introduction and ObjectivesNoise-induced hearing loss (NIHL) and tinnitus are common problems that can be prevented with hearing protection measures. Sound level meters and noise dosimeters enable to monitor and identify health-threatening occupational or recreational noise, but are limited in their daily application because they are usually difficult to operate, bulky, and expensive. Smartwatches, which are becoming increasingly available and popular, could be a valuable alternative to professional systems. Therefore, the aim of this study was to evaluate the applicability of smartwatches for accurate environmental noise monitoring.MethodsThe A-weighted equivalent continuous sound pressure level (LAeq) was recorded and compared between a professional sound level meter and a popular smartwatch. Noise exposure was assessed in 13 occupational and recreational settings, covering a large range of sound pressure levels between 35 and 110 dBA. To assess measurement agreement, a Bland-Altman plot, linear regression, the intra-class correlation coefficient, and descriptive statistics were used.ResultsOverall, the smartwatch underestimated the sound level meter measurements by 0.5 dBA (95% confidence interval [0.2, 0.8]). The intra-class correlation coefficient showed excellent agreement between the two devices (ICC = 0.99), ranging from 0.65 (music club) to 0.99 (concert) across settings. The smartwatch's sampling rate decreased significantly with lower sound pressure levels, which could have introduced measurement inaccuracies in dynamic acoustic environments.ConclusionsThe assessment of ambient noise with the tested smartwatch is sufficiently accurate and reliable to improve awareness of hazardous noise levels in the personal environment and to conduct exploratory clinical research. For professional and legally binding measurements, we recommend specialized sound level meters or noise dosimeters. In the future, smartwatches will play an important role in monitoring personal noise exposure and will provide a widely available and cost-effective measure for otoprotection.

Noise as a Criterion for Designating Sanitary Protection Zones of Traffic Arteries

The article is devoted to the study of a possibility of designating the boundaries of sanitary zones (distancing) for traffic arteries outside settlements within the right-of-way.The study was conducted regarding the current Russian laws, projects of possible changes in legislation and draft amendments. It offers definitions of the right-of-way and of sanitary zone and highlights topics that have not yet been regulated.At the same time, the research methods are of universal character and after introducing other regulatory parameters may be applied for similar research in other countries as well.Calculations and field studies allowed to find that within the railway right-of-way and with the existing train traffic intensity, equivalent continuous sound pressure level in aggregate does not exceed the established maximum permissible level of 80dBA for personnel performing their labour functions within the railway rightof-way.A growth in the Leq/LAeq on the right-of-way from 80,0 to 95,0 dBA may lead to an increase in the hazard class (subclass).An analysis of the actual results of a special assessment of working conditions at JSC Russian Railways showed in the vast majority of cases the acceptability of working conditions evaluated according to noise factor measured at the workplaces of employees working during full or part-time shift on the right-of-way. Hazardous working conditions at the level of some subclasses for certain professions (operator of track measurement, railway track worker) arise rather due to indicators of severity of the labour process.

Traffic noise prediction using machine learning and monte carlo data augmentation: a case study on the Patiala city in India

Traffic noise pollution is a serious problem in the modern urban areas especially to design new architecture of smart cities, highways, hospitals, schools for an efficient and healthy environment. To analyse this aspect, we have proposed a machine learning based prediction of sound pressure level on an original dataset collected in Patiala city in India. Vehicular traffic and sound pressure level data was collected on different sites in the city. A total of 502 data samples on the identified sites were obtained for the study. Further this data is augmented using Monte Carlo simulation to 10 times of its initial size and the Artificial Neural Networks (ANN) have been trained and compared with other Machine learning methods for the vehicular traffic noise prediction. The input parameters in the model are traffic volume Q, percentage of heavy vehicles P and the average speed of vehicles V and the output parameter is the equivalent continuous sound pressure level, Leq dB(A). The experimental results show ANN which is trained on the augmented data using Monte Carlo simulations outperforms other advanced methods making it an effective measure for vehicular traffic noise prediction to develop a healthy environment which is free of noise pollution.

Personal Audio Systems Unsafe At Any Sound

Personal Audio Systems Unsafe At Any Sound

Traffic Noise Modelling Using Land Use Regression Model Based on Machine Learning, Statistical Regression and GIS

This study estimates the equivalent continuous sound pressure level (Leq) during peak daily periods (‘rush hour’) along the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning, statistical regression, and geographical information systems (GIS). The research utilises two types of soft computing methods including machine learning (i.e., decision tree, random frost algorithms) and statistical regression (i.e., linear regression, support vector regression algorithms) to determine the best approach to create a prediction Leq map at the NKVE in Shah Alam, Malaysia. The selection of the best algorithm is accomplished by considering correlation, correlation coefficient, mean-absolute-error, mean-square-error, root-mean-square-error, and mean absolute percentage error. Traffic noise level was monitored using three sound level meters (TES 52A), and a traffic tally was done to analyse the traffic flow. Wind speed was gauged using a wind speed meter. The study relied on a variety of noise predictors including wind speed, digital elevation model, land use type (specifically, if it was residential, industrial, or natural reserve), residential density, road type (expressway, primary, and secondary) and traffic noise average (Leq). The above parameters were fed as inputs into the LUR model. Additional noise influencing factors such as traffic lights, intersections, road toll gates, gas stations, and public transportation infrastructures (bus stop and bus line) are also considered in this study. The models utilised parameters derived from LiDAR (Light Detection and Ranging) data, and various GIS (Geographical Information Systems) layers were extracted to produce the prediction maps. The results highlighted the superior performances by the machine learning (random forest) models compared to the statistical regression-based models.

Psycho-physiological evaluations of low-level impulsive sounds produced by air conditioners

Air conditioners are widely used in buildings to maintain thermal comfort for long time. Air conditioners produce sounds during operation, and air conditioners are regarded as one of the main noise sources in buildings. Most sounds produced by the air conditioner do not fluctuate over time and sound quality of the steady sounds produced by the air conditioner have been evaluated. However, air conditioners sometimes produce low-level and impulsive sounds. Customers criticizes such sounds are annoying when they sleep and they spend time quietly in the living room. The aim of this study was to determine the factors that significantly influence the psycho-physiological response to the low-level impulsive sounds produced by air conditioners. We assessed the A-weighted equivalent continuous sound pressure level (LAeq) and factors extracted from the autocorrelation function (ACF). Subjective loudness, sharpness, annoyance, and electroencephalography (EEG) were evaluated. Multiple regression analyses were performed using a linear combination of LAeq, the ACF factors, and their standard deviations. The results indicated that LAeq, the delay time of the first maximum peak, the width of the first decay of the ACF, and the magnitude and width of the IACF could predict psycho-physiological responses to air conditioner sounds.

Acoustic Barriers to Reduce Sound Pressure and Environmental Noise in the Ica Fencing

The objective was to determine the reduction of sound pressure through acoustic barriers, knowing the factors that affect the propagation of its acoustic emission, the methodology was the quantitative design, explanatory level, pre-experimental type, pre and post-test, based on studies of behaviors of other barriers such as noise mitigating measures; Two sound level meters were used to measure noise, one of which served as a reference since the sound spectrum due to traffic has a varied behavior. The results obtained in the tests carried out in the field and office work, allowed us to corroborate the Equivalent Continuous Sound Pressure Level (LAeqT). We conclude that Calle Lima 1ra. block and 1st. block Av. Grau, exceeds the standard limits established in the S.D.N ° 085-2003-PCM Words.

Application of loudness level to temporally varying sounds

Most of the environmental noises are temporally varying and include various frequency components. Various methods for evaluating the environmental noises have been proposed. Among them, the method for calculating loudness level was first standardized in 1975 as ISO 532, including Stevens' and Zwicker's methods. Unfortunately, these methods can only be applied to steady state sounds. On the other hand, Aeq (Equivalent Continuous A-weight Sound Pressure Level) is standardized for the evaluation of level fluctuating environmental sounds as ISO 1996. In , the energy mean and A-weighting are used for averaging temporal fluctuation and frequency weighting, respectively. The present authors with their colleagues have conducted many psychological experiments using artificial sounds and actual sounds since 1970's and have being introduced that p (Loudness-based Method), which is a combination of ISO 532 for frequency weighting and ISO 1996 for temporal level fluctuation, is a good method for evaluating various kinds of environmental sounds. ISO 532-1 (Zwicker's method) has been revised including the temporal fluctuation into consideration in 2017, in which p has been adopted as a note. The merit of p will be introduced in this paper presenting many examples.