Topological Characterization of Haze Episodes Using Persistent Homology

Haze is one of the major environmental issues that have continuously vexed countries worldwide, including Malaysia, for the last three decades. Therefore, this study aims to investigate the differences between the topological features of months with and those without haze episodes observed at air qu...

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Bibliographic Details
Published inAerosol and Air Quality Research Vol. 19; no. 7; pp. 1614 - 1624
Main Authors Zulkepli, Nur Fariha Syaqina, Noorani, Mohd Salmi Md, Razak, Fatimah Abdul, Ismail, Munira, Alias, Mohd Almie
Format Journal Article
LanguageEnglish
Published 社團法人台灣氣膠研究學會 01.07.2019
Subjects
Persistent homology
Topological data analysis
Haze
Particulate matter
Time delay embedding
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Summary:Haze is one of the major environmental issues that have continuously vexed countries worldwide, including Malaysia, for the last three decades. Therefore, this study aims to investigate the differences between the topological features of months with and those without haze episodes observed at air quality monitoring stations located in the areas of Jerantut, Klang, Petaling Jaya and Shah Alam. We employ persistent homology, which is a method of topological data analysis (TDA) that focuses on connected components and holes in the data, to characterize the local particulate matter (PM_(10)). The summary statistics reveal drastic changes in the lifetimes of the topological data from every station during haze episodes, highlighting the possibility of developing an early detection system for haze based on our approach.
ISSN:1680-8584
2071-1409
DOI:10.4209/aaqr.2018.08.0315