Predicting air quality trends in Malaysia’s largest cities : the role of urban population dynamics and COVID-19 effects

• Autorzy: Wong Ming Wong , Tzeng Shian-Yang , Mo Hao-Fan , Su Wunhong

Identyfikatory

DOI

10.24425/aep.2024.150553

• Języki publikacji: EN

Abstrakty

EN

This paper aims to explore the relationship between the Air Quality Index (AQI), COVID-19 incidence rates, and population density within Malaysia’s ten most populous cities from January 2018 to December 2021. Data were sourced from the Department of Statistics Malaysia, the World Air Quality Index Project, and Our World in Statistics. The methodology integrated population-based city classification and AQI assessment, cluster analysis through SPSS, and Generalized Additive Mixed Model (GAMM) analysis using R Studio despite encountering a data gap in AQI for five months in 2019. Cities were organized into three clusters based on their AQI: Cluster One included Ipoh, Penang, Kuala Lumpur, and Melaka, Cluster Two comprised Kuantan, Seremban, Johor Bahru, and Kota Bharu, Cluster Three featured Kota Kinabalu and Kuching. GAMM analysis revealed prediction accuracies for AQI variations of 58%, 60%, and 41% for the respective clusters, indicating a notable impact of population density on air quality. AQI variations remained unaffected by COVID-19, with a forecasted improvement in air quality across all clusters. The paper presents novel insights into the negligible impact of COVID-19 on AQI variations and underscores the predictive power of population dynamics on urban air quality, offering valuable perspectives for environmental and urban planning.

Słowa kluczowe

EN

air quality index; COVID-19; Malaysia; cluster analysis; generalized additive mixed model

• Wydawca: Institute of Environmental Engineering, Polish Academy of Sciences
• Czasopismo: Archives of Environmental Protection
• Rocznik: 2024
• Tom: Vol. 50, no. 2
• Strony: 65--74
• Opis fizyczny: Bibliogr. 37 poz., rys., tab., wykr.

Twórcy

autor

Wong Ming Wong

• International College, Krirk University, Thailand

• https://orcid.org/0000-0001-8978-0506

autor

Tzeng Shian-Yang

• School of Economics and Management, Quanzhou University of Information Engineering, China

• https://orcid.org/0000-0002-8167-8483

autor

Mo Hao-Fan

• JinWen University of Science and Technology, Taiwan

• https://orcid.org/0000-0003-4870-4472

autor

Su Wunhong

• School of Accounting, Hangzhou Dianzi University, China

• https://orcid.org/0000-0001-8086-6821

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