Seasonal variations of particle number concentration and its relationship with PM2.5 mass concentration in industrial-residential airshed

• Main Authors: Dahari, Nadhira, Muda, Khalida, Latif, Mohd Talib, Dominick, Doreena, Hussein, Norelyza, Khan, Md Firoz
• Format: Article
• Published: Springer 2022
• Subjects: GE Environmental Sciences; QD Chemistry
• Online Access: http://eprints.um.edu.my/41276/

The smaller particles that dominate the particle number concentration (PNC) in the ambient air only contribute to a small percentage of particulate matter (PM) mass concentration although present in high particle number concentration. These small particles may be neglected upon assessing the health impacts of the PM. Hence, the knowledge on the particle number concentration size distribution deserves greater attention than the particulate mass concentration. This study investigates the measurement of the particle mass concentrations (PM2.5) and PNC of 0.27 mu m < Dp < 4.50 mu m during the southwest (SW), inter-monsoon (IM) and northeast (NE) monsoons in the industrial-residential airshed of Skudai, Johor Bahru, Malaysia. The PM2.5 mass concentrations and PNC were measured using a multi-channel GRIMM Environmental Dust Monitor (GRIMM EDM-SVC 365) equipped with a global positioning system. Diurnal variations, statistical analysis and regression plots were utilised from a six-month hourly data set to examine the patterns of the PNC size distributions and its relationships with the PM2.5 mass concentration. The overall mean PM2.5 mass concentration was 21.85 mu g m(-3), with the 24 h mean values of 26.80 mu g m(-3), 26.08 mu g m(-3) and 13.76 mu g m(-3) for the SW, IM and NE monsoons, respectively. It was found that the hourly mean of PNC was recorded at the highest concentration during the SW monsoon (373.20 # cm(-3)). The particles in the accumulation mode (Dp < 1.0 mu m) were the prevalent form of the particle number concentration (94-98%). The scatter plots between the PM2.5 mass concentration and particle number size distribution showed that the PNC mode of 0.27 < Dp < 1.0 mu m has the highest correlation value of r(2) = 0.87 due to the emission from the anthropogenic activities. The results of this study highlight the importance of the PNC measurement in the seasonal variations of the PM2.5 pollution, indicating the significance of the regional-scale emission control actions in the local air quality management.