Atmospheric PM2.5 and particle number concentration in semi-urban industrial-residential airshed

Air pollution is one of the crucial factors that cause premature death and health problems. Fine particulate matter (PM2.5) has a high association with adverse health effects due to its capability to penetrate deep into the human respiratory system. The deterioration of air quality in Malaysia, especially Johor Bahru city, is worrying due to the swift industrial, transportation as well as housing expansion. Air pollution has a closer relationship with the particle number concentration (PNC) rather than the particle mass concentration. However, measurement of the PM2.5 is normally reported in particle mass concentration. Due to the light-weighted small particle sizes that dominate the PNC, they are accounted for only a few percent of the total particle mass concentration. Thus, these small particles could be neglected if the toxicological effects are determined primarily by the mass concentration rather than the PNC. This study aims to investigate the 24 h mean PM2.5 mass concentrations, meteorological parameters and PNC, besides determining the concentrations of the trace metals and water-soluble inorganic ions of the PM2.5 pollutant collected at the industrial-residential airshed of Skudai, Johor Bahru. This research analysed the source apportionment of the PM2.5 composition and the relationship of the PM2.5 mass concentrations with PNC. The meteorological variables, PNC data and PM2.5 samples were collected from August 2017 until January 2018. The source apportionment of the PM2.5 composition were determined using Positive Matrix Factorisation (PMF). This study found that the highest 24 h PM2.5 mass concentration is 44.6 µgm-3, with a mean value of 21.85 µgm-3 throughout the SW through the NE monsoon. 43.33% of the daily PM2.5 mass exceeded the 24 h World Health Organization Guideline, while 8.33% of the concentration exceeded the 24 h Malaysia Ambient Air Quality Standard. The ambient temperature throughout the monsoon seasons shows a significant positive correlation (p < 0.05) with PM2.5 mass (r2 = 0.43 to r2 = 0.54), while the wind speed (r2 = -0.23 to r2 = -0.01) and the relative humidity (r2 = -0.47 to r2 = -0.27) show negative correlations. The rainfall on the other hand shows weak correlation towards PM2.5 mass. The accumulation mode particles (0.27 µm < Dp < 1.0 µm) corresponded to 94~98% of the total particle number concentration, with highest hourly mean of 372.20 #cm-3 during the SW monsoon. The accumulation mode has the highest correlation value of r2 = 0.8701 among the other particle size bins. The major trace elements identified were Fe (279.2 ± 69.2 ngm-3), Ba (200.1 ± 57.2 ngm-3), Zn (133.2 ± 67.6 ngm-3), Mg (116.3 ± 43.8 ngm-3) and Al (104.1 ± 30.6 ngm-3). For inorganic ions, the secondary inorganic aerosols (SIA) were highly contributed by NO3- (639.9 ± 138.1 ngm-3), SO42- (556.9 ± 203.0 ngm-3) and NH4+ (424.1 ± 106.1 ngm-3). Despite the anthropogenic activities as the sources of particulates, a minor fraction of pollutants may also due to the regional transboundary transport. The PMF analysis shows that non-combustion traffic source is the main contributor to the ambient PM2.5 (25.4 %). The six predominant sources identified were (1) mineral dust pollution (4.2 %), (2) source of mixed road dust and biomass burning (18.1%), (3) mixed secondary inorganic aerosol and road dust emission (18.1%), (4) emission of the non-combustion traffic source (25.4%), (5) industrial emission (18.1 %) and (6) undefined (16.1 %). The comprehensive findings of this study may support the need to control the PM2.5 sources