Noise Level Distribution Functions for Outdoor Applications

Tang, Shiu Keung; Chu, Sing

doi:10.1006/jsvi.2001.3827

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…This coefficient indicates that a high percentage of the equivalent continuous noise level L eq can be explained by the variation in the background noise level data L 90 (Montgomery and Runger, 1999), indicating that the background noise level is dominated by the noise of road traffic. Tang and Chu (2001) pointed out that the scattering of noise data reflect the randomness of noise level fluctuations in the outdoor environment. In addition, high scatter of noise data can be attributed to the sensitivity of L eq noise levels to other sources of noise and short-duration noisy events.…”

Section: Resultsmentioning

confidence: 99%

“…For non-constant noise source, the equivalent continuous sound level L eq is generally reported to represent the constant noise level containing the same quantity of sound energy over a time period as the actual varying noise level (Georgiadou et al, 2003). The equivalent continuous noise level L eq is related to the statistical noise level L 10 by the following empirical relationship (Nelson, 1987;Tang and Chu, 2001;Piccolo et al, 2004): Background noise level data L 90 reported in Tables II and III and equivalent continuous noise level L eq calculated from the above equation were correlated to investigate the presence of a relationship between the two types of noise data. Figure 10 presents the relationship between measured day-time and night-time statistical background noise level (L 90 ) and the calculated equivalent continuous noise level L eq without barrier in 28 locations in the City of Amman.…”

Section: Resultsmentioning

confidence: 99%

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Evaluation of Traffic Noise Pollution in Amman, Jordan

Jamrah

Al‐Omari

Sharabi

2006

Environ Monit Assess

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The City of Amman, Jordan, has been subjected to persistent increase in road traffic due to overall increase in prosperity, fast development and expansion of economy, travel and tourism. This study investigates traffic noise pollution in Amman. Road traffic noise index L10(1 h) was measured at 28 locations that cover most of the City of Amman. Noise measurements were carried out at these 28 locations two times a day for a period of one hour during the early morning and early evening rush hours, in the presence and absence of a barrier. The Calculation of Road Traffic Noise (CRTN) prediction model was employed to predict noise levels at the locations chosen for the study. Data required for the model include traffic volume, speed, percentage of heavy vehicles, road surface, gradient, obstructions, distance, noise path, intervening ground, effect of shielding, and angle of view. The results of the investigation showed that the minimum and the maximum noise levels are 46 dB(A) and 81 dB(A) during day-time and 58 dB(A) and 71 dB(A) during night-time. The measured noise level exceeded the 62 dB(A) acceptable limit at most of the locations. The CTRN prediction model was successful in predicting noise levels at most of the locations chosen for this investigation, with more accurate predictions for night-time measurements.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Evaluation of Traffic Noise Pollution in Amman, Jordan

Jamrah

Al‐Omari

Sharabi

2006

Environ Monit Assess

View full text Add to dashboard Cite

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“…While the noise level difference between L50 and Leq was 0.2 dBA in the garden of the institution, this difference was 5.3 dBA due to traffic noise in the street. Also, L10 and L5 define the noise peaks, and the difference L10-L90 defines the noise fluctuations or noise climate [38,39]. The difference L10 -L90 and Leq represents as the sum of the noise pollution level, and defines the degree of annoyance that is caused by fluctuating noise [40].…”

Section: Resultsmentioning

confidence: 99%

Reduction through Brick Wall Barrier and Acoustic Sponge of Environmental Noise Levels from Chiller Cooling System

Tufaner

2020

Sakarya University Journal of Science

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The aim of this study was to investigate the noise level reduction of the air cooled liquid chiller to the desired levels of environmental noise requisite. Noise control procedures are implemented with various systems to prevent environmental noise disturbances. This paper examines the application of a passive noise control approach to the control of air-cooled liquid chiller noise located in the garden of an official institution. The approach of passive noise control utilizing brick walls with acoustic sponge in the immediate vicinity of the chiller is discussed. When the chiller was covered with a brick wall, the noise level was reduced by 5.5 Leq dBA 1 m away from the nearest residence. However, this reduction could not meet the requirements of legal regulations. Therefore, the inside of brick wall was covered with acoustic sponge. As a result, the ambient noise level where 1m away from the nearest residence to the chiller has been reduced to the background noise levels with a total reduction of about 8.5 Leq dBA. It is shown that, due to the noise produced by the chiller fans and compressors, so as to achieve significantly cognizable levels of noise reduction it is necessary to isolation brick walls with acoustic sponge.

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“…(These ad hoc arguments could preclude statistical normality but cannot statistically affirm normality.) #7 Non-Gaussian -In the early 2000s, [18] presented noise level datasets that are close to log-tanh distributed (thus implicitly not Gaussian), according to only subjective inspection of data graphs but without any rigorous statistical testing. #8 Gaussian occasionally -Also in the early 2000s, [33] presented noise-level empirical datasets measured near the facade of buildings of unspecified heights, with a conclusion that some of these datasets are possibly Gaussian, based simply on visual inspection of (i) scatter plots of those datasets' sample noise-climate and sample variance -by checking if the scattered points (on the "noise-climate / variance" plane) lie in the subregions allowed by Gaussian distributions; (ii) scatter plots of the empirical datasets' sample kurtosis and sample skewness -by checking if the scattered points (on the "kurtosis-skewness" plane) lie in the subregions allowed by Gaussian distributions.…”

Section: B Roadway Sound-level Distribution's Empirical Normality -A ...mentioning

confidence: 99%

Roadway Traffic Sound Measured up on a High-Rise Building–The Sound-Level’s Statistical Normality

Muaz¹,

Tang

Lin

et al. 2022

IEEE Access

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Percentile-value ceilings/thresholds have been mandated by governments around the world on roadway traffic sound-level. Such percentile values, by definition, change with the sound-level's underlying probability distribution, i.e., the same percentile can imply different percentile values for different probability distributions. Whether the underlying probability distribution is Gaussian or not for the roadway traffic sound-level: contrary reports populate the open literature but such reports are typically weak in statistical rigor. This decades-long but ongoing debate will be surveyed comprehensively in this paper for the first time in the open literature. Then, this paper will present two new datasets measured in two separate evenings at exactly the same location up in a high-rise building, and will employ the Jarque-Bera hypothesis test to rigorously show that neither dataset is Gaussian.

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Noise Level Distribution Functions for Outdoor Applications

Cited by 8 publications

References 16 publications

Evaluation of Traffic Noise Pollution in Amman, Jordan

Evaluation of Traffic Noise Pollution in Amman, Jordan

Reduction through Brick Wall Barrier and Acoustic Sponge of Environmental Noise Levels from Chiller Cooling System

Roadway Traffic Sound Measured up on a High-Rise Building–The Sound-Level’s Statistical Normality

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