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2 Archives of Environmental Protection

2 2024

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

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

Archives of Environmental Protection

2024

Vol. 50, no. 2

65--74

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.

Impact of COVID-19 on PM2.5 concentrations in Singapore, Indonesia, and Thailand: Cluster Analysis and Generalized Additive Mixed Models

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

Archives of Environmental Protection

2024

Vol. 50, no. 4

116--126

This paper examines the influence of COVID-19-related factors on PM2.5 concentrations (PM2.5) in Singapore, Indonesia, and Thailand from January 2018 to December 2021. Using data from four sources, cluster analysis based on six socioeconomic indices was employed to select these countries for focused analysis. Generalized Additive Mixed Models (GAMM) were applied to assess associations between PM2.5 and COVID-19 factors, including new cases, deaths, vaccinations, stringency index, time series (STOL), and COVID-19 status (dummy variable). Results show that PM2.5 levels in Singapore and Indonesia were significantly impacted by COVID-19 measures, with F-statistics for new cases (22.875, p < 0.001), deaths (12.563, p = 0.012), as well as significant associations for vaccinations (t = 5.976, p < 0.001), stringency index (t = 5.124, p < 0.001), and the dummy variable (t = 6.624, p < 0.001). In contrast, PM2.5 levels in Thailand were unaffected by these factors, likely due to seasonal pollution sources. The model explains 90.3% of the variation in PM2.5 (adjusted R² = 0.872). This paper offers important insights for policymakers on incorporating air quality into health policies and highlights how pandemic responses varied across countries. By examining the impact of COVID-19 factors on PM2.5 in different nations, the study enhances understanding through detailed data and averaging periods. It reveals differences in how countries’ air quality responded to the pandemic, contributing to discussions on environmental management and public health. These findings inform policy decisions and facilitate discussions on better managing environmental and health challenges during global crises.