Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Di, Guoqing, Wang, Yihang, Yao, Yao, Ma, Jiangang, Wu, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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
_version_ 1784754657039482880
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
work_keys_str_mv AT diguoqing influencingfactorsidentificationandpredictionofnoiseannoyanceacasestudyonsubstationnoise
AT wangyihang influencingfactorsidentificationandpredictionofnoiseannoyanceacasestudyonsubstationnoise
AT yaoyao influencingfactorsidentificationandpredictionofnoiseannoyanceacasestudyonsubstationnoise
AT majiangang influencingfactorsidentificationandpredictionofnoiseannoyanceacasestudyonsubstationnoise
AT wujian influencingfactorsidentificationandpredictionofnoiseannoyanceacasestudyonsubstationnoise