Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model

Particulate matter is one of the life threathening pollutants that are harmful to human health. The aim of this study is to assess PM2.5 distribution using spatial interpolation techniques of inverse distance weighted (IDW) by predicting their concentrations at distinct unmonitored locations. The ID...

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Published in:IOP Conference Series: Earth and Environmental Science
Main Author: Ismain S.H.A.; Salleh S.A.; Mohammad Sham N.; Wan Azmi W.N.F.; Zulkiflee A.L.; Ab Rahman A.Z.
Format: Conference paper
Language:English
Published: Institute of Physics 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169557503&doi=10.1088%2f1755-1315%2f1217%2f1%2f012033&partnerID=40&md5=e00520e35c33f4799eed282d90e4b879
id 2-s2.0-85169557503
spelling 2-s2.0-85169557503
Ismain S.H.A.; Salleh S.A.; Mohammad Sham N.; Wan Azmi W.N.F.; Zulkiflee A.L.; Ab Rahman A.Z.
Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
2023
IOP Conference Series: Earth and Environmental Science
1217
1
10.1088/1755-1315/1217/1/012033
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169557503&doi=10.1088%2f1755-1315%2f1217%2f1%2f012033&partnerID=40&md5=e00520e35c33f4799eed282d90e4b879
Particulate matter is one of the life threathening pollutants that are harmful to human health. The aim of this study is to assess PM2.5 distribution using spatial interpolation techniques of inverse distance weighted (IDW) by predicting their concentrations at distinct unmonitored locations. The IDW interpolation was developed using Arcmap for Klang Valley area covering six districts in central Peninsular Malaysia. The Department of Environment (DOE) continous air quality monitoring stations (CAQMS) were installed at 6 districts in Klang Valley throughout period of 9 months between January and September 2022 for data collection. The results from IDW showed that PM2.5 concentrations were highest in February and lowest in March. The IDW spatial mapping demonstrated that PM2.5 distributed higher in Seremban and Petaling districts throughout 9 months while Kuala Lumpur and Putrajaya demonstrated contrary lower. The IDW cross-validation results showed an acceptable predictive accuracy with low RMSE values ranging from 1.790 to 5.073 and high R squared value with range from 0.0267 to 0.5081. The results showed a very good fit of the IDW model to the observed points, confirming that the results of these analyses can monitor and predict PM2.5 concentrations with high accuracy. The interpolation maps that result can help identify key regions that require air quality management mitigation strategies. © 2023 Published under licence by IOP Publishing Ltd.
Institute of Physics
17551307
English
Conference paper
All Open Access; Gold Open Access
author Ismain S.H.A.; Salleh S.A.; Mohammad Sham N.; Wan Azmi W.N.F.; Zulkiflee A.L.; Ab Rahman A.Z.
spellingShingle Ismain S.H.A.; Salleh S.A.; Mohammad Sham N.; Wan Azmi W.N.F.; Zulkiflee A.L.; Ab Rahman A.Z.
Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
author_facet Ismain S.H.A.; Salleh S.A.; Mohammad Sham N.; Wan Azmi W.N.F.; Zulkiflee A.L.; Ab Rahman A.Z.
author_sort Ismain S.H.A.; Salleh S.A.; Mohammad Sham N.; Wan Azmi W.N.F.; Zulkiflee A.L.; Ab Rahman A.Z.
title Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
title_short Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
title_full Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
title_fullStr Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
title_full_unstemmed Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
title_sort Spatial Distribution of Particulate Matter (PM2.5) in Klang Valley using Inverse Distance Weighting Interpolation Model
publishDate 2023
container_title IOP Conference Series: Earth and Environmental Science
container_volume 1217
container_issue 1
doi_str_mv 10.1088/1755-1315/1217/1/012033
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169557503&doi=10.1088%2f1755-1315%2f1217%2f1%2f012033&partnerID=40&md5=e00520e35c33f4799eed282d90e4b879
description Particulate matter is one of the life threathening pollutants that are harmful to human health. The aim of this study is to assess PM2.5 distribution using spatial interpolation techniques of inverse distance weighted (IDW) by predicting their concentrations at distinct unmonitored locations. The IDW interpolation was developed using Arcmap for Klang Valley area covering six districts in central Peninsular Malaysia. The Department of Environment (DOE) continous air quality monitoring stations (CAQMS) were installed at 6 districts in Klang Valley throughout period of 9 months between January and September 2022 for data collection. The results from IDW showed that PM2.5 concentrations were highest in February and lowest in March. The IDW spatial mapping demonstrated that PM2.5 distributed higher in Seremban and Petaling districts throughout 9 months while Kuala Lumpur and Putrajaya demonstrated contrary lower. The IDW cross-validation results showed an acceptable predictive accuracy with low RMSE values ranging from 1.790 to 5.073 and high R squared value with range from 0.0267 to 0.5081. The results showed a very good fit of the IDW model to the observed points, confirming that the results of these analyses can monitor and predict PM2.5 concentrations with high accuracy. The interpolation maps that result can help identify key regions that require air quality management mitigation strategies. © 2023 Published under licence by IOP Publishing Ltd.
publisher Institute of Physics
issn 17551307
language English
format Conference paper
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
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