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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 iden...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315821/ https://www.ncbi.nlm.nih.gov/pubmed/35886248 http://dx.doi.org/10.3390/ijerph19148394 |
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author | Di, Guoqing Wang, Yihang Yao, Yao Ma, Jiangang Wu, Jian |
author_facet | Di, Guoqing Wang, Yihang Yao, Yao Ma, Jiangang Wu, Jian |
author_sort | Di, Guoqing |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9315821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93158212022-07-27 Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise Di, Guoqing Wang, Yihang Yao, Yao Ma, Jiangang Wu, Jian Int J Environ Res Public Health Article 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. MDPI 2022-07-09 /pmc/articles/PMC9315821/ /pubmed/35886248 http://dx.doi.org/10.3390/ijerph19148394 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Di, Guoqing Wang, Yihang Yao, Yao Ma, Jiangang Wu, Jian Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise |
title | Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise |
title_full | Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise |
title_fullStr | Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise |
title_full_unstemmed | Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise |
title_short | Influencing Factors Identification and Prediction of Noise Annoyance—A Case Study on Substation Noise |
title_sort | influencing factors identification and prediction of noise annoyance—a case study on substation noise |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315821/ https://www.ncbi.nlm.nih.gov/pubmed/35886248 http://dx.doi.org/10.3390/ijerph19148394 |
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