Noise annoyance indicators for various industrial noise sources: Results and comparisons

2008 ◽  
Vol 123 (5) ◽  
pp. 3811-3811
Author(s):  
Marion Alayrac ◽  
Stéphanie Viollon ◽  
Catherine Marquis‐Favre
Keyword(s):  
Noise Sources ◽  
Industrial Noise ◽  
Noise Annoyance

scholarly journals Innovative techniques for the improvement of industrial noise sources identification by beamforming

Noise Mapping ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 129-137
Author(s):  
Giorgio Baldinelli ◽  
Francesco Bianchi ◽  
Danilo Costarelli ◽  
Francesco D’Alessandro ◽  
Flavio Scrucca ◽  
...  
Keyword(s):  
Image Processing ◽  
Noise Source ◽  
Focal Length ◽  
Noise Sources ◽  
Geometric Information ◽  
Industrial Noise ◽  
Sources Identification ◽  
Innovative Technique ◽  
Innovative Techniques

Abstract An innovative technique based on beamforming is implemented, at the aim of detecting the distances from the observer and the relative positions among the noise sources themselves in multisource noise scenarios. By means of preliminary activities to assess the optical camera focal length and stereoscopic measurements followed by image processing, the geometric information in the source-microphone direction is retrieved, a parameter generally missed in classic beamforming applications. A corollary of the method consists of the possibility of obtaining also the distance among different noise sources which could be present in a multisource environment. A loss of precision is found when the effect of the high acoustic reflectivity ground interferes with the noise source.

scholarly journals Lower Noise Annoyance Associated with GIS-Derived Greenspace: Pathways through Perceived Greenspace and Residential Noise

2018 ◽  
Vol 15 (7) ◽  
pp. 1533 ◽  
Author(s):  
Angel M. Dzhambov ◽  
Iana Markevych ◽  
Boris Tilov ◽  
Zlatoslav Arabadzhiev ◽  
Drozdstoj Stoyanov ◽  
...  
Keyword(s):  
Noise Level ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Buffer Zone ◽  
Tree Cover ◽  
Noise Sources ◽  
Noise Abatement ◽  
Noise Annoyance ◽  
Lower Noise

Growing amounts of evidence support an association between self-reported greenspace near the home and lower noise annoyance; however, objectively defined greenspace has rarely been considered. In the present study, we tested the association between objective measures of greenspace and noise annoyance, with a focus on underpinning pathways through noise level and perceived greenspace. We sampled 720 students aged 18 to 35 years from the city of Plovdiv, Bulgaria. Objective greenspace was defined by several Geographic Information System (GIS)-derived metrics: Normalized Difference Vegetation Index (NDVI), tree cover density, percentage of green space in circular buffers of 100, 300 and 500 m, and the Euclidean distance to the nearest structured green space. Perceived greenspace was defined by the mean of responses to five items asking about its quantity, accessibility, visibility, usage, and quality. We assessed noise annoyance due to transportation and other neighborhood noise sources and daytime noise level (Lday) at the residence. Tests of the parallel mediation models showed that higher NDVI and percentage of green space in all buffers were associated with lower noise annoyance, whereas for higher tree cover this association was observed only in the 100 m buffer zone. In addition, the effects of NDVI and percentage of green space were mediated by higher perceived greenspace and lower Lday. In the case of tree cover, only perceived greenspace was a mediator. Our findings suggest that the potential for greenspace to reduce noise annoyance extends beyond noise abatement. Applying a combination of GIS-derived and perceptual measures should enable researchers to better tap individuals’ experience of residential greenspace and noise.

Online Database of Industrial Noise Sources

2020 ◽  
pp. 165-171
Author(s):  
Tanja Miodragović ◽  
Mladen Rasinac ◽  
Jelena Tomić ◽  
Branko Radičević
Keyword(s):  
Online Database ◽  
Noise Sources ◽  
Industrial Noise

scholarly journals Modeling and Mapping of Combined Noise Annoyance for Aircraft and Road Traffic Based on a Partial Loudness Model

2021 ◽  
Vol 18 (16) ◽  
pp. 8724
Author(s):  
Wonhee Lee ◽  
Chanil Chun ◽  
Dongwook Kim ◽  
Soogab Lee
Keyword(s):  
Background Noise ◽  
Road Traffic ◽  
Noise Source ◽  
Transportation Systems ◽  
Masking Effect ◽  
Noise Sources ◽  
Noise Annoyance ◽  
Short And Long Term ◽  
Loudness Model

Complex transportation systems often produce combined exposure to aircraft and road noise. Depending on the noise source, the annoyance response is different, and a masking effect occurs between the noise sources within the combined noise. Considering these characteristics, partial loudness was adopted to evaluate noise annoyance. First, a partial loudness model incorporating binaural inhibition was proposed and validated. Second, short- and long-term annoyance models were developed using partial loudness. Finally, the annoyance of combined noise was visualized as a map. These models can evaluate the annoyance by considering both the intensity and frequency characteristics of the noise. In addition, it is possible to quantify the masking effect that occurs between noise sources. Combined noise annoyance maps depict the degree of annoyance of residents and show the background noise effect, which is not seen on general noise maps.

Exposure to industrial noise: impacts on cognitive performance

2021 ◽  
Vol 263 (4) ◽  
pp. 2590-2600
Author(s):  
Luiz Henrique Mesa Casa Pereira ◽  
Björn Knöfel ◽  
Jan Troge ◽  
Welf-Guntram Drossel ◽  
Marcel Klein ◽  
...  
Keyword(s):  
Cognitive Performance ◽  
Noise Analysis ◽  
Low Frequency ◽  
Cumulative Effect ◽  
Noise Sources ◽  
Industrial Noise ◽  
Sound Levels ◽  
Office Environments ◽  
High Sound ◽  
High Frequency Content

Research on the relation between exposure to noise and cognitive performance inside industrial environments is not as broad as on office environments. For a better understanding of the specific industrial noise problems, participants performed arithmetic tests inside a hemi anechoic room while they were exposed to sounds of five typical industrial noise sources. The subjects also classified how annoying they perceived the noise signals. The effect of noise on the arithmetic test's performance was larger on accuracy than on velocity, which was verified using a Student t-test. Spectral-temporal characteristics - especially high frequency content and strong low frequency modulation - appear to relate better with lower performance on the test than high sound levels. Subjects that evaluated noise as more annoying performed worse in a final arithmetic test (under silence) after being exposed to the noises, indicating a possible cumulative effect of noise on performance. The findings provide a better insight in the cognitive behavior of people who are exposed to industrial noise. Hence, the study will proceed with the specific noise analysis of single industrial workplaces.

Industrial Noise Exposure, Noise Annoyance, and Serum Lipid Levels in Blue-Collar Workers–The CORDIS Study

1997 ◽  
Vol 52 (4) ◽  
pp. 292-298 ◽  
Author(s):  
Samuel Melamed ◽  
Paul Froom ◽  
Estela Kristal-boneh ◽  
Dafna Gofer ◽  
Joseph Ribak
Keyword(s):  
Serum Lipid ◽  
Noise Exposure ◽  
Blue Collar ◽  
Lipid Levels ◽  
Industrial Noise ◽  
Blue Collar Workers ◽  
Noise Annoyance ◽  
Serum Lipid Levels

Combined road traffic, railway and aircraft noise sources: Total noise annoyance model appraisal from field data

2021 ◽  
Vol 180 ◽  
pp. 108127
Author(s):  
Catherine Marquis-Favre ◽  
Laure-Anne Gille ◽  
Ludovic Breton
Keyword(s):  
Field Data ◽  
Road Traffic ◽  
Aircraft Noise ◽  
Noise Sources ◽  
Noise Annoyance ◽  
Total Noise

Pilot studies of noise annoyance in relation to time, amplitude and frequency characteristics of sound

2021 ◽  
Vol 263 (5) ◽  
pp. 981-986
Author(s):  
Jan Radosz
Keyword(s):  
Work Performance ◽  
Test System ◽  
Frequency Characteristics ◽  
Noise Sources ◽  
Pilot Studies ◽  
3D Sound ◽  
Noise Annoyance ◽  
Sound Environment ◽  
Acoustic Environments ◽  
Reference Environment

Noise is any unwanted sound that may be disruptive or harmful to health or increase the risk of an accident at work. Noise as a stressor can contribute to the development of various types of diseases, cause distraction, make work difficult and reduce its efficiency. Aim of the pilot studies was to asses noise annoyance in relation to time, amplitude and frequency characteristics of sound in typical office environment. The Vienna Test System was used for this purpose. Virtual office acoustic environments were developed with different psychoacoustic parameters, but with a constant A-weighted sound pressure level of 55 dB - environment with conversations, environment with office equipment (computers, printers, telephones), environment D with all office noise sources together. The reference environment was a quiet office room with no additional noise sources. Recorded real noise sources were transferred to a virtual 3D sound environment and converted into binaural sound, which was then played back on headphones. During the exposure to each of the acoustic environments, the subjects performed the ALS test (work performance series) and then assessed the given environment using a questionnaire. The tested acoustic environments were assessed in the range from not at all annoying to very annoying. On average, environments with office noise were rated as moderately annoying. However, subjective feelings of the respondents were not reflected in the results of psychological tests.

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