Time series clustering of Malaysia Air quality time series data

Authors

  • Mohd Aftar Abu Bakar Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia
  • Fatin Nur Afiqah Suris Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia
  • Noratiqah Mohd Ariff Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia
  • Kamarulzaman Ibrahim Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia
  • Tan Zhen Jie Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia

DOI:

https://doi.org/10.26555/jifo.v16i2.a25421

Keywords:

Air quality, Cluster analysis, K-means, Time series clustering

Abstract

Air quality is often associated with the area location and activities where air quality in cities is usually more polluted than in rural areas. This study aims to study the pattern of time series data from air quality stations by performing cluster analysis of air quality station based on the particulate matter 10 micrometres or less in diameter (PM10) and particulate matter 2.5 micrometres or less in diameter (PM2.5) time series data. The clusters obtained from the cluster analysis were compared with the station area category and station location. This study which uses air quality data obtained from the Department of Environment, Malaysia from 5 July 2017 until 30 June 2019, shows five types of air quality patterns in Malaysia. The results also show that none of the clusters is dominated by any station's category. Therefore, it is less appropriate to relate the air quality patterns and the station area category. However, the results show that air quality patterns were related to the station's location, where nearby stations have similar air quality patterns.

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Published

2022-05-17

Issue

Section

Articles