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Statistical Modeling on the Severity of Unhealthy Air Pollution Events in Malaysia

Author

Listed:
  • Nurulkamal Masseran

    (Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia)

  • Muhammad Aslam Mohd Safari

    (Department of Mathematics and Statistics, Faculty of Science, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia)

Abstract

This study proposes the concept of severity as an alternative measure of extreme air pollution events. Information about severity can be derived from the cumulative effect of air pollution events, which can be determined from unhealthy Air Pollution Index (API) values that occur for a consecutive period. On the basis of the severity, an analysis of extreme air pollution events can be obtained through the application of the generalized extreme-value (GEV) model. A case study was conducted using hourly API data in Klang, Malaysia, from 1 January 1997 to 31 August 2020. The block-maxima approach was integrated with information about monsoon seasons to determine suitable data points for GEV modeling. Based on the GEV model, the estimated severity levels corresponding to their return periods are determined. The results reveal that pollution severity in Klang tends to rise with increases in the length of return periods that are measured based on seasonal monsoons as a temporal scale. In conclusion, the return period for severity provides a good basis for measuring the risk of recurrence of extreme pollution events.

Suggested Citation

  • Nurulkamal Masseran & Muhammad Aslam Mohd Safari, 2022. "Statistical Modeling on the Severity of Unhealthy Air Pollution Events in Malaysia," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:3004-:d:893161
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