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Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method

The air quality monitoring system is the most prominent tool for monitoring air pollution levels, especially in areas where forest fires often occur. The South Sumatra Province of Indonesia is one of the greatest contributors to haze events in Indonesia due to peatlands fires. It does not sufficient...

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Main Authors: Muhammad Rendana, Wan Mohd Razi Idris, Sahibin Abdul Rahim
Format: Article
Language:English
English
Published: AIMS Press 2022
Subjects:
TD172-193.5 Environmental pollution
Online Access:https://eprints.ums.edu.my/id/eprint/35102/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/35102/2/FULLTEXT.pdf
https://eprints.ums.edu.my/id/eprint/35102/
http://www.aimspress.com/article/doi/10.3934/environsci.2022043
https://doi.org/10.3934/environsci.2022043
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spelling my.ums.eprints.351022023-02-13T07:31:45Z https://eprints.ums.edu.my/id/eprint/35102/ Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method Muhammad Rendana Wan Mohd Razi Idris Sahibin Abdul Rahim TD172-193.5 Environmental pollution The air quality monitoring system is the most prominent tool for monitoring air pollution levels, especially in areas where forest fires often occur. The South Sumatra Province of Indonesia is one of the greatest contributors to haze events in Indonesia due to peatlands fires. It does not sufficiently possess a ground monitoring system to cover rural areas, and thus, delayed actions can result in severe air pollution within this region. Therefore, the aim of this current study is to analyze the distribution and classification of PM2.5 observed from 2019 to 2021 within the South Sumatra Province, Indonesia. The acquisition of PM2.5 data was from the Merra-2 Satellite with a spatial resolution of 0.5˚ × 0.625˚ and an hourly interval. The hierarchical cluster analysis (HCA) was applied in this study for the clustering method. The result of the study revealed that the daily mean of PM2.5 levels varied from 5.9±0.01 to 21.3±0.03 μg/m3. The study area was classified into three classes: high pollution areas (HPA), moderate pollution areas (MPA) and low pollution areas (LPA), based on the HCA method. The average level of PM2.5 observed in HPA was notably higher, at 16.8±0.02 μg/m3, followed by MPA and LPA. Furthermore, this study indicated that the highest level of PM2.5 was found during 2019, with a severe haze event in the study area due to the intensive burning of forests, bush and peatlands. As a whole, the output of this study can be used by authorities for air quality management due to forest fire events in a certain area. AIMS Press 2022-11-02 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/35102/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/35102/2/FULLTEXT.pdf Muhammad Rendana and Wan Mohd Razi Idris and Sahibin Abdul Rahim (2022) Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method. AIMS Environmental Science, 9. pp. 754-770. ISSN 2372-0352 http://www.aimspress.com/article/doi/10.3934/environsci.2022043 https://doi.org/10.3934/environsci.2022043
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic TD172-193.5 Environmental pollution
spellingShingle TD172-193.5 Environmental pollution
Muhammad Rendana
Wan Mohd Razi Idris
Sahibin Abdul Rahim
Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method
description The air quality monitoring system is the most prominent tool for monitoring air pollution levels, especially in areas where forest fires often occur. The South Sumatra Province of Indonesia is one of the greatest contributors to haze events in Indonesia due to peatlands fires. It does not sufficiently possess a ground monitoring system to cover rural areas, and thus, delayed actions can result in severe air pollution within this region. Therefore, the aim of this current study is to analyze the distribution and classification of PM2.5 observed from 2019 to 2021 within the South Sumatra Province, Indonesia. The acquisition of PM2.5 data was from the Merra-2 Satellite with a spatial resolution of 0.5˚ × 0.625˚ and an hourly interval. The hierarchical cluster analysis (HCA) was applied in this study for the clustering method. The result of the study revealed that the daily mean of PM2.5 levels varied from 5.9±0.01 to 21.3±0.03 μg/m3. The study area was classified into three classes: high pollution areas (HPA), moderate pollution areas (MPA) and low pollution areas (LPA), based on the HCA method. The average level of PM2.5 observed in HPA was notably higher, at 16.8±0.02 μg/m3, followed by MPA and LPA. Furthermore, this study indicated that the highest level of PM2.5 was found during 2019, with a severe haze event in the study area due to the intensive burning of forests, bush and peatlands. As a whole, the output of this study can be used by authorities for air quality management due to forest fire events in a certain area.
format Article
author Muhammad Rendana
Wan Mohd Razi Idris
Sahibin Abdul Rahim
author_facet Muhammad Rendana
Wan Mohd Razi Idris
Sahibin Abdul Rahim
author_sort Muhammad Rendana
title Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method
title_short Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method
title_full Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method
title_fullStr Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method
title_full_unstemmed Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method
title_sort clustering analysis of pm2.5 concentrations in the south sumatra province, indonesia, using the merra-2 satellite application and hierarchical cluster method
publisher AIMS Press
publishDate 2022
url https://eprints.ums.edu.my/id/eprint/35102/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/35102/2/FULLTEXT.pdf
https://eprints.ums.edu.my/id/eprint/35102/
http://www.aimspress.com/article/doi/10.3934/environsci.2022043
https://doi.org/10.3934/environsci.2022043
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score 13.222552

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