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Statistical modeling on the severity of unhealthy air pollution events in Malaysia


Citation

Masseran, Nurulkamal and Mohd Safari, Muhammad Aslam (2022) Statistical modeling on the severity of unhealthy air pollution events in Malaysia. Mathematics, 10 (16). pp. 1-15. ISSN 2227-7390

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.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
DOI Number: https://doi.org/10.3390/math10163004
Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Environmental analysis; Extreme value; Statistical modeling
Depositing User: Ms. Nuraida Ibrahim
Date Deposited: 20 Nov 2023 07:14
Last Modified: 20 Nov 2023 07:14
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/math10163004
URI: http://psasir.upm.edu.my/id/eprint/103293
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