Classification of air quality in the Klang Valley using K-Means Clustering / Nur Aliah Amira Abdul Hamid, Siti Khairun Najwa Kamil and Noorezatty Mohd Yusop

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.

Publication Details

Journal
UiTM Institutional Repositories (Universiti Teknologi MARA)
Published
2024-10-01
Primary Topic
Risk Perception and Management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Classification of air quality in the Klang Valley using K-Means Clustering / Nur Aliah Amira Abdul Hamid, Siti Khairun Najwa Kamil and Noorezatty Mohd Yusop

UiTM Institutional Repositories (Universiti Teknologi MARA)
Risk Perception and Management
article

Classification of air quality in the Klang Valley using K-Means Clustering / Nur Aliah Amira Abdul Hamid, Siti Khairun Najwa Kamil and Noorezatty Mohd Yusop

article en

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.

UiTM Institutional Repositories (Universiti Teknologi MARA)
Universiti Teknologi MARA
Life below water, Sustainable cities and communities
Openalex Percentile: Top 33%
Risk Perception and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.