出版社：Chinese Association for Aerosol Research in Taiwan
摘要：Fine particulate matter (PM2.5) poses a higher risk to human health than coarse particulate matter (PM10). This study aims to determine the spatiotemporal variations of PM2.5 and PM10 in Malaysia and their association with other criteria pollutants and meteorological factors. Hourly data from air quality monitoring stations for the year 2018 were retrieved from the Malaysian Department of Environment and analysed for temporal and spatial scales according to different regions in Malaysia. Further statistical analyses, such as Spearman’s Rank Correlation and Principal Component Analysis (PCA), were conducted to study the associations between PM2.5 and PM10 with other main criteria air pollutants, as well as meteorological parameters. Higher mean concentrations of PM2.5 (23 ± 8 µg m–3, range = 4.6–158 µg m–3) and PM10 (32 ± 10 µg m–3, range = 6.0–181 µg m–3) were observed in the central region of the Malaysian Peninsula. The diurnal patterns of PM2.5 and PM10 were in a bimodal pattern and influenced by traffic emissions. The highest mean PM2.5 and PM10 concentrations were recorded during the southwest monsoon season, notably in the central region. The Spearman’s Rank Correlation shows that NO2 and CO have a moderately positive correlation (p < 0.01) with PM2.5 (r = 0.47) and PM10 (r = 0.48) in the central regions while all meteorological parameters show significantly weak to very weak correlations with PM. The PCA analysis indicates that the major sources leading to the formation of particulate matter are from the contribution of secondary aerosols and combustion-related sources. The ratio of PM2.5 to PM10 ranged between 0.51 and 0.76 nationwide with the highest mean recorded in the central region (0.72). This study indicates that there is a higher abundance of fine particulate in the ambient air of the urbanised environment and thus a greater likely risk to human health in more developed areas.
关键词：Particulate matter;Spatiotemporal;Atmospheric gases;Principal Component Analysis;Ratio PM2.5 to PM10
