Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia
Air pollution had turned into one of the major environmental issues in Malaysia due to the heavy transportation activities in logistics and automobile dependencies, industrial activities and transboundary pollution from the neighbouring countries. The emission from such events such as infrastructure...
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| Format: | Article |
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Blue Eyes Intelligence Engineering & Sciences Publication
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/79716/ |
| _version_ | 1848858742562488320 |
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| author | Sahrir, Syazwani Abdullah, Ahmad Makmom Ponrahono, Zakiah Sharaai, Amir Hamzah |
| author_facet | Sahrir, Syazwani Abdullah, Ahmad Makmom Ponrahono, Zakiah Sharaai, Amir Hamzah |
| author_sort | Sahrir, Syazwani |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Air pollution had turned into one of the major environmental issues in Malaysia due to the heavy transportation activities in logistics and automobile dependencies, industrial activities and transboundary pollution from the neighbouring countries. The emission from such events such as infrastructure works, traffic (road, sea, air) and industry are directly responsible for air pollution. The objective of this study was to determine the significant pollutant parameters contributing to air quality issues and to identify air quality pattern at five air monitoring stations in Klang Valley, Malaysia for the years of 2010 until 2014 (five years). This dataset was derived from the Department of Environment, Malaysia (DOE). Air pollution index (API) such as SO2, CO2, NO2, O3, and PM10 were examined in this study. Environmental metric techniques used was cluster analysis (CA) to determine the air quality pattern based on yearly and specific monthly basis. Discriminant analysis (DA) was applied to a distinctive different class. The study identifies that there were different variables or predictors between each class. Principal component analysis (PCA) was used to identify the significant pollutant parameters based on five pollutants in air pollution index (API) which cause by many activities either internal or external factors. This study identified that SO2, CO2, NO2, and PM10 are the primary pollutants contributing to the deteriorating of air pollution in Klang Valley. By using the environmetric technique for analysing the data, it contributes to a better understanding of air quality pattern and clearly identified the vital of atmospheric pollutant parameters. |
| first_indexed | 2025-11-15T12:18:17Z |
| format | Article |
| id | upm-79716 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T12:18:17Z |
| publishDate | 2019 |
| publisher | Blue Eyes Intelligence Engineering & Sciences Publication |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-797162022-10-25T08:39:43Z http://psasir.upm.edu.my/id/eprint/79716/ Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia Sahrir, Syazwani Abdullah, Ahmad Makmom Ponrahono, Zakiah Sharaai, Amir Hamzah Air pollution had turned into one of the major environmental issues in Malaysia due to the heavy transportation activities in logistics and automobile dependencies, industrial activities and transboundary pollution from the neighbouring countries. The emission from such events such as infrastructure works, traffic (road, sea, air) and industry are directly responsible for air pollution. The objective of this study was to determine the significant pollutant parameters contributing to air quality issues and to identify air quality pattern at five air monitoring stations in Klang Valley, Malaysia for the years of 2010 until 2014 (five years). This dataset was derived from the Department of Environment, Malaysia (DOE). Air pollution index (API) such as SO2, CO2, NO2, O3, and PM10 were examined in this study. Environmental metric techniques used was cluster analysis (CA) to determine the air quality pattern based on yearly and specific monthly basis. Discriminant analysis (DA) was applied to a distinctive different class. The study identifies that there were different variables or predictors between each class. Principal component analysis (PCA) was used to identify the significant pollutant parameters based on five pollutants in air pollution index (API) which cause by many activities either internal or external factors. This study identified that SO2, CO2, NO2, and PM10 are the primary pollutants contributing to the deteriorating of air pollution in Klang Valley. By using the environmetric technique for analysing the data, it contributes to a better understanding of air quality pattern and clearly identified the vital of atmospheric pollutant parameters. Blue Eyes Intelligence Engineering & Sciences Publication 2019 Article PeerReviewed Sahrir, Syazwani and Abdullah, Ahmad Makmom and Ponrahono, Zakiah and Sharaai, Amir Hamzah (2019) Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia. International Journal of Recent Technology and Engineering, 8 (1 spec.). pp. 17-24. ISSN 2277-3878 https://www.ijrte.org/download/volume-8-issue-1s/ |
| spellingShingle | Sahrir, Syazwani Abdullah, Ahmad Makmom Ponrahono, Zakiah Sharaai, Amir Hamzah Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia |
| title | Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia |
| title_full | Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia |
| title_fullStr | Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia |
| title_full_unstemmed | Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia |
| title_short | Environmetric study on air quality pattern for assessment in Klang Valley, Malaysia |
| title_sort | environmetric study on air quality pattern for assessment in klang valley, malaysia |
| url | http://psasir.upm.edu.my/id/eprint/79716/ http://psasir.upm.edu.my/id/eprint/79716/ |