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Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques

Na Phra Lan Subdistrict is a pollution control zone with the highest PM(10) level in Thailand. Major mobile and industrial sources in the area are related to stone crushing, quarrying and mining. This study used statistical techniques to investigate the potential sources influencing high PM(10) leve...

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Autores principales: Sooktawee, Sirapong, Kanabkaew, Thongchai, Boonyapitak, Suteera, Patpai, Aduldech, Piemyai, Nirun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721878/
https://www.ncbi.nlm.nih.gov/pubmed/33288849
http://dx.doi.org/10.1038/s41598-020-78445-5
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author Sooktawee, Sirapong
Kanabkaew, Thongchai
Boonyapitak, Suteera
Patpai, Aduldech
Piemyai, Nirun
author_facet Sooktawee, Sirapong
Kanabkaew, Thongchai
Boonyapitak, Suteera
Patpai, Aduldech
Piemyai, Nirun
author_sort Sooktawee, Sirapong
collection PubMed
description Na Phra Lan Subdistrict is a pollution control zone with the highest PM(10) level in Thailand. Major mobile and industrial sources in the area are related to stone crushing, quarrying and mining. This study used statistical techniques to investigate the potential sources influencing high PM(10) levels in Na Phra Lan. Hourly PM(10) data and related parameters (PM(2.5), PM(coarse) and NO(x)) from 2014–2017 were analysed using time series, bivariate polar plot and conditional bivariate probability function (CBPF). Results of diurnal variation revealed two peaks of PM(10) levels from 06:00–10:00 and 19:00–23:00 every month. For seasonal variation, high PM(10) concentrations were found from October to February associated with the cool and dry weather during these months. The bivariate polar plot and CBPF confirmed two potential sources, i.e., resuspended dust from mobile sources close to the air quality monitoring station (receptor) and industrial sources of mining, quarrying and stone crushing far from the station on the northeast side. While the industrial source areas played a role in background PM(10) concentrations, the influence of mobile sources increased the concentrations resulting in two PM(10) peaks daily. From the study results, we proposed that countermeasure activities should focus on potential source areas, resuspended road dust from vehicles and the industrial sources related to quarrying and mining, rather than distributing equal attention to all sources.
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spelling pubmed-77218782020-12-09 Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques Sooktawee, Sirapong Kanabkaew, Thongchai Boonyapitak, Suteera Patpai, Aduldech Piemyai, Nirun Sci Rep Article Na Phra Lan Subdistrict is a pollution control zone with the highest PM(10) level in Thailand. Major mobile and industrial sources in the area are related to stone crushing, quarrying and mining. This study used statistical techniques to investigate the potential sources influencing high PM(10) levels in Na Phra Lan. Hourly PM(10) data and related parameters (PM(2.5), PM(coarse) and NO(x)) from 2014–2017 were analysed using time series, bivariate polar plot and conditional bivariate probability function (CBPF). Results of diurnal variation revealed two peaks of PM(10) levels from 06:00–10:00 and 19:00–23:00 every month. For seasonal variation, high PM(10) concentrations were found from October to February associated with the cool and dry weather during these months. The bivariate polar plot and CBPF confirmed two potential sources, i.e., resuspended dust from mobile sources close to the air quality monitoring station (receptor) and industrial sources of mining, quarrying and stone crushing far from the station on the northeast side. While the industrial source areas played a role in background PM(10) concentrations, the influence of mobile sources increased the concentrations resulting in two PM(10) peaks daily. From the study results, we proposed that countermeasure activities should focus on potential source areas, resuspended road dust from vehicles and the industrial sources related to quarrying and mining, rather than distributing equal attention to all sources. Nature Publishing Group UK 2020-12-07 /pmc/articles/PMC7721878/ /pubmed/33288849 http://dx.doi.org/10.1038/s41598-020-78445-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Sooktawee, Sirapong
Kanabkaew, Thongchai
Boonyapitak, Suteera
Patpai, Aduldech
Piemyai, Nirun
Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
title Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
title_full Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
title_fullStr Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
title_full_unstemmed Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
title_short Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
title_sort characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721878/
https://www.ncbi.nlm.nih.gov/pubmed/33288849
http://dx.doi.org/10.1038/s41598-020-78445-5
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