Abstract
Air pollution is a major global concern, and its adverse impacts are most likely to affect urban areas. The Klang Valley, located on the southwest coast of Peninsular Malaysia, is also affected by this global issue. As one of the most industrialized and populated areas, controlling air pollution is a challenge. Thus, this paper aims to classify air monitoring stations in the Klang Valley into distinct clusters based on six major air pollutants. Data on pollutant levels collected by the Department of Environment from air monitoring stations throughout the region was utilised. Fourteen stations representing seven areas in Klang Valley were assessed in two weather conditions: the dry season (May-September) and the rainy season (November-March), typically known as monsoon seasons in Malaysia. Two clusters of air monitoring stations were identified using K-Means clustering. The first cluster, comprising four stations, showed better air quality with lower pollutant levels. In contrast, the second cluster, which includes ten stations, showed higher pollutant levels. However, the pollutant levels in both clusters were within the permissible limits according to the Malaysian Ambient Air Quality Guidelines. Furthermore, the location of the monitoring station can influence pollutant levels, whereas seasonal variations (dry or rainy) have a lesser impact. Consistent monitoring is crucial for tracking air pollution changes and adjusting policies accordingly.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Abdul Hamid, Nur Aliah Amira UNSPECIFIED Kamil, Siti Khairun Najwa UNSPECIFIED Mohd Yusop, Noorezatty UNSPECIFIED |
Subjects: | L Education > L Education (General) Q Science > QA Mathematics |
Divisions: | Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus |
Journal or Publication Title: | Journal of Exploratory Mathematical Undergraduate Research (JEMUR) |
ISSN: | 3030-5411 |
Volume: | 2 |
Keywords: | Air pollution, Clustering Algorithm, K-Means Cluster Analysis |
Date: | October 2024 |
URI: | https://ir.uitm.edu.my/id/eprint/105997 |