Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand

© Int. J. of GEOMATE. Road traffic is the most significant source of noise in an urban city and is considered not only an environmental nuisance but also a threat to public health. Therefore, this study aimed to determine road traffic noise levels in Phuket Province, including Muang Phuket, Thalang,...

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Main Authors: Withida Patthanaissaranukool, Kulnapa Bunnakrid, Tanasri Sihabut
Other Authors: King Chulalongkorn Memorial Hospital, Faculty of Medicine Chulalongkorn University
Format: Article
Published: 2020
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/49896
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spelling th-mahidol.498962020-01-27T15:48:33Z Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand Withida Patthanaissaranukool Kulnapa Bunnakrid Tanasri Sihabut King Chulalongkorn Memorial Hospital, Faculty of Medicine Chulalongkorn University Mahidol University Center of Excellence on Environmental Health and Toxicology (EHT) Agricultural and Biological Sciences Earth and Planetary Sciences Engineering Environmental Science © Int. J. of GEOMATE. Road traffic is the most significant source of noise in an urban city and is considered not only an environmental nuisance but also a threat to public health. Therefore, this study aimed to determine road traffic noise levels in Phuket Province, including Muang Phuket, Thalang, and Kathu District; and to compare them with predicted noise levels using NMTHAI 1.2. Traffic noise level, traffic volume and speed of vehicles were measured on main roads including Yaowarat, Ratsada, Montri, Patipat, Ban Muangmai, Ban Kain, Ban Lipon, Baramee and Vichitsongkram Road. The results showed that traffic noise in Muang Phuket, Thalang and Kathu Districts were 70.0-70.9, 72.9-74.7 and 74.6-74.8 dBA, respectively. The result revealed that traffic noise levels obtained from the model were higher than measured noise at an average of 4.8±2.3 dBA. A high correlation was observed between predicted and measured traffic noise levels (R2 = 0.655, P < 0.01). Speed of vehicles and traffic volume were key variables affecting traffic noise level with a correlation coefficient of 0.752 and 0.702 at 99% confidence level, respectively. The model performed reasonably well under different traffic noise conditions and could predict traffic noise of other cities in Thailand. 2020-01-27T07:29:43Z 2020-01-27T07:29:43Z 2019-01-01 Article International Journal of GEOMATE. Vol.17, No.62 (2019), 133-139 10.21660/2019.62.00305 21862982 2-s2.0-85067619206 https://repository.li.mahidol.ac.th/handle/123456789/49896 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85067619206&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Agricultural and Biological Sciences
Earth and Planetary Sciences
Engineering
Environmental Science
spellingShingle Agricultural and Biological Sciences
Earth and Planetary Sciences
Engineering
Environmental Science
Withida Patthanaissaranukool
Kulnapa Bunnakrid
Tanasri Sihabut
Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand
description © Int. J. of GEOMATE. Road traffic is the most significant source of noise in an urban city and is considered not only an environmental nuisance but also a threat to public health. Therefore, this study aimed to determine road traffic noise levels in Phuket Province, including Muang Phuket, Thalang, and Kathu District; and to compare them with predicted noise levels using NMTHAI 1.2. Traffic noise level, traffic volume and speed of vehicles were measured on main roads including Yaowarat, Ratsada, Montri, Patipat, Ban Muangmai, Ban Kain, Ban Lipon, Baramee and Vichitsongkram Road. The results showed that traffic noise in Muang Phuket, Thalang and Kathu Districts were 70.0-70.9, 72.9-74.7 and 74.6-74.8 dBA, respectively. The result revealed that traffic noise levels obtained from the model were higher than measured noise at an average of 4.8±2.3 dBA. A high correlation was observed between predicted and measured traffic noise levels (R2 = 0.655, P < 0.01). Speed of vehicles and traffic volume were key variables affecting traffic noise level with a correlation coefficient of 0.752 and 0.702 at 99% confidence level, respectively. The model performed reasonably well under different traffic noise conditions and could predict traffic noise of other cities in Thailand.
author2 King Chulalongkorn Memorial Hospital, Faculty of Medicine Chulalongkorn University
author_facet King Chulalongkorn Memorial Hospital, Faculty of Medicine Chulalongkorn University
Withida Patthanaissaranukool
Kulnapa Bunnakrid
Tanasri Sihabut
format Article
author Withida Patthanaissaranukool
Kulnapa Bunnakrid
Tanasri Sihabut
author_sort Withida Patthanaissaranukool
title Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand
title_short Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand
title_full Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand
title_fullStr Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand
title_full_unstemmed Applying mathematical modeling to predict road traffic noise in Phuket Province, Thailand
title_sort applying mathematical modeling to predict road traffic noise in phuket province, thailand
publishDate 2020
url https://repository.li.mahidol.ac.th/handle/123456789/49896
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