Clustering analysis of PM2.5 concentrations in the South Sumatra Province, Indonesia, using the Merra-2 Satellite Application and Hierarchical Cluster Method

IF 1.6 Q4 ENVIRONMENTAL SCIENCES
Muhammad Rendana, Wan Mohd Razi Idris, S. Abdul Rahim
{"title":"Clustering analysis of PM2.5 concentrations in the South Sumatra Province, Indonesia, using the Merra-2 Satellite Application and Hierarchical Cluster Method","authors":"Muhammad Rendana, Wan Mohd Razi Idris, S. Abdul Rahim","doi":"10.3934/environsci.2022043","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":45143,"journal":{"name":"AIMS Environmental Science","volume":"1 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIMS Environmental Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3934/environsci.2022043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

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.
利用Merra-2卫星应用和分层聚类方法对印尼南苏门答腊省PM2.5浓度进行聚类分析
空气质量监测系统是监测空气污染水平的最重要工具,特别是在经常发生森林火灾的地区。由于泥炭地火灾,印度尼西亚的南苏门答腊省是印度尼西亚雾霾事件的最大贡献者之一。它没有足够的地面监测系统覆盖农村地区,因此,延迟行动可能导致该地区严重的空气污染。因此,本研究的目的是分析2019年至2021年在印度尼西亚南苏门答腊省观测到的PM2.5的分布和分类。PM2.5数据采集自Merra-2卫星,空间分辨率为0.5˚× 0.625˚,时间间隔为h。本研究采用层次聚类分析(HCA)作为聚类方法。研究结果表明,PM2.5的日平均值在5.9±0.01至21.3±0.03 μg/m3之间变化。基于HCA方法,将研究区划分为高污染区(HPA)、中度污染区(MPA)和低污染区(LPA) 3类。HPA区PM2.5平均浓度较高,为16.8±0.02 μg/m3, MPA和LPA次之。此外,该研究表明,2019年PM2.5水平最高,由于森林、灌木和泥炭地的大量燃烧,研究区域出现了严重的雾霾事件。总体而言,本研究的结果可用于某地区森林火灾事件后的空气质量管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
AIMS Environmental Science
AIMS Environmental Science ENVIRONMENTAL SCIENCES-
CiteScore
2.90
自引率
0.00%
发文量
31
审稿时长
5 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信