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Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand

Meteorological parameters play an important role in determining the prevalence of ambient particulate matter (PM) in the upper north of Thailand. Mae Hong Son is a province located in this region and which borders Myanmar. This study aimed to determine the relationships between meteorological parame...

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Autores principales: Kliengchuay, Wissanupong, Cooper Meeyai, Aronrag, Worakhunpiset, Suwalee, Tantrakarnapa, Kraichat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313660/
https://www.ncbi.nlm.nih.gov/pubmed/30544675
http://dx.doi.org/10.3390/ijerph15122801
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author Kliengchuay, Wissanupong
Cooper Meeyai, Aronrag
Worakhunpiset, Suwalee
Tantrakarnapa, Kraichat
author_facet Kliengchuay, Wissanupong
Cooper Meeyai, Aronrag
Worakhunpiset, Suwalee
Tantrakarnapa, Kraichat
author_sort Kliengchuay, Wissanupong
collection PubMed
description Meteorological parameters play an important role in determining the prevalence of ambient particulate matter (PM) in the upper north of Thailand. Mae Hong Son is a province located in this region and which borders Myanmar. This study aimed to determine the relationships between meteorological parameters and ambient concentrations of particulate matter less than 10 µm in diameter (PM(10)) in Mae Hong Son. Parameters were measured at an air quality monitoring station, and consisted of PM(10), carbon monoxide (CO), ozone (O(3)), and meteorological factors, including temperature, rainfall, pressure, wind speed, wind direction, and relative humidity (RH). Nine years (2009–2017) of pollution and climate data obtained from the Thai Pollution Control Department (PCD) were used for analysis. The results of this study indicate that PM(10) is influenced by meteorological parameters; high concentration occurred during the dry season and northeastern monsoon seasons. Maximum concentrations were always observed in March. The PM(10) concentrations were significantly related to CO and O(3) concentrations and to RH, giving correlation coefficients of 0.73, 0.39, and −0.37, respectively (p-value < 0.001). Additionally, the hourly PM(10) concentration fluctuated within each day. In general, it was found that the reporting of daily concentrations might be best suited to public announcements and presentations. Hourly concentrations are recommended for public declarations that might be useful for warning citizens and organizations about air pollution. Our findings could be used to improve the understanding of PM(10) concentration patterns in Mae Hong Son and provide information to better air pollution measures and establish a warning system for the province.
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spelling pubmed-63136602019-06-17 Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand Kliengchuay, Wissanupong Cooper Meeyai, Aronrag Worakhunpiset, Suwalee Tantrakarnapa, Kraichat Int J Environ Res Public Health Article Meteorological parameters play an important role in determining the prevalence of ambient particulate matter (PM) in the upper north of Thailand. Mae Hong Son is a province located in this region and which borders Myanmar. This study aimed to determine the relationships between meteorological parameters and ambient concentrations of particulate matter less than 10 µm in diameter (PM(10)) in Mae Hong Son. Parameters were measured at an air quality monitoring station, and consisted of PM(10), carbon monoxide (CO), ozone (O(3)), and meteorological factors, including temperature, rainfall, pressure, wind speed, wind direction, and relative humidity (RH). Nine years (2009–2017) of pollution and climate data obtained from the Thai Pollution Control Department (PCD) were used for analysis. The results of this study indicate that PM(10) is influenced by meteorological parameters; high concentration occurred during the dry season and northeastern monsoon seasons. Maximum concentrations were always observed in March. The PM(10) concentrations were significantly related to CO and O(3) concentrations and to RH, giving correlation coefficients of 0.73, 0.39, and −0.37, respectively (p-value < 0.001). Additionally, the hourly PM(10) concentration fluctuated within each day. In general, it was found that the reporting of daily concentrations might be best suited to public announcements and presentations. Hourly concentrations are recommended for public declarations that might be useful for warning citizens and organizations about air pollution. Our findings could be used to improve the understanding of PM(10) concentration patterns in Mae Hong Son and provide information to better air pollution measures and establish a warning system for the province. MDPI 2018-12-10 2018-12 /pmc/articles/PMC6313660/ /pubmed/30544675 http://dx.doi.org/10.3390/ijerph15122801 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kliengchuay, Wissanupong
Cooper Meeyai, Aronrag
Worakhunpiset, Suwalee
Tantrakarnapa, Kraichat
Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand
title Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand
title_full Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand
title_fullStr Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand
title_full_unstemmed Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand
title_short Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand
title_sort relationships between meteorological parameters and particulate matter in mae hong son province, thailand
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313660/
https://www.ncbi.nlm.nih.gov/pubmed/30544675
http://dx.doi.org/10.3390/ijerph15122801
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