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Volume 16, issue 8
Atmos. Chem. Phys., 16, 5357–5381, 2016
https://doi.org/10.5194/acp-16-5357-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 16, 5357–5381, 2016
https://doi.org/10.5194/acp-16-5357-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 29 Apr 2016

Research article | 29 Apr 2016

Seasonal variability of PM2.5 composition and sources in the Klang Valley urban-industrial environment

Norhaniza Amil1,2, Mohd Talib Latif1,3, Md Firoz Khan4, and Maznorizan Mohamad5 Norhaniza Amil et al.
  • 1School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
  • 2School of Industrial Technology (Environmental Division), Universiti Sains Malaysia, 11800 Penang, Malaysia
  • 3Institute for Environmental and Development (LESTARI), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
  • 4Centre for Tropical Climate Change System (IKLIM), Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
  • 5Malaysian Meteorological Department, Jalan Sultan, 46667 Petaling Jaya, Selangor, Malaysia

Abstract. This study investigates the fine particulate matter (PM2.5) variability in the Klang Valley urban-industrial environment. In total, 94 daily PM2.5 samples were collected during a 1-year campaign from August 2011 to July 2012. This is the first paper on PM2.5 mass, chemical composition and sources in the tropical environment of Southeast Asia, covering all four seasons (distinguished by the wind flow patterns) including haze events. The samples were analysed for various inorganic components and black carbon (BC). The chemical compositions were statistically analysed and the temporal aerosol pattern (seasonal) was characterised using descriptive analysis, correlation matrices, enrichment factor (EF), stoichiometric analysis and chemical mass closure (CMC). For source apportionment purposes, a combination of positive matrix factorisation (PMF) and multi-linear regression (MLR) was employed. Further, meteorological–gaseous parameters were incorporated into each analysis for improved assessment. In addition, secondary data of total suspended particulate (TSP) and coarse particulate matter (PM10) sampled at the same location and time with this study (collected by Malaysian Meteorological Department) were used for PM ratio assessment. The results showed that PM2.5 mass averaged at 28 ± 18 µg m−3, 2.8-fold higher than the World Health Organisation (WHO) annual guideline. On a daily basis, the PM2.5 mass ranged between 6 and 118 µg m−3 with the daily WHO guideline exceeded 43 % of the time. The north-east (NE) monsoon was the only season with less than 50 % sample exceedance of the daily WHO guideline. On an annual scale, PM2.5 mass correlated positively with temperature (T) and wind speed (WS) but negatively with relative humidity (RH). With the exception of NOx, the gases analysed (CO, NO2, NO and SO2) were found to significantly influence the PM2.5 mass. Seasonal variability unexpectedly showed that rainfall, WS and wind direction (WD) did not significantly correlate with PM2.5 mass. Further analysis on the PM2.5 ∕ PM10, PM2.5 ∕ TSP and PM10 ∕ TSP ratios reveal that meteorological parameters only greatly influenced the coarse particles (particles with an aerodynamic diameter of greater than 2.5 µm) and less so the fine particles at the site. Chemical composition showed that both primary and secondary pollutants of PM2.5 are equally important, albeit with seasonal variability. The CMC components identified were in the decreasing order of (mass contribution) BC > secondary inorganic aerosols (SIA) > dust > trace elements > sea salt > K+. The EF analysis distinguished two groups of trace elements: those with anthropogenic sources (Pb, Se, Zn, Cd, As, Bi, Ba, Cu, Rb, V and Ni) and those with a crustal source (Sr, Mn, Co and Li). The five identified factors resulting from PMF 5.0 were (1) combustion of engine oil, (2) mineral dust, (3) mixed SIA and biomass burning, (4) mixed traffic and industrial and (5) sea salt. Each of these sources had an annual mean contribution of 17, 14, 42, 10 and 17 % respectively. The dominance of each identified source largely varied with changing season and a few factors were in agreement with the CMC, EF and stoichiometric analysis, accordingly. In relation to meteorological–gaseous parameters, PM2.5 sources were influenced by different parameters during different seasons. In addition, two air pollution episodes (HAZE) revealed the influence of local and/or regional sources. Overall, our study clearly suggests that the chemical constituents and sources of PM2.5 were greatly influenced and characterised by meteorological and gaseous parameters which vary greatly with season.

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This study investigates the PM2.5 variability in the Klang Valley urban-industrial environment. Source apportionment analysis reveals two major contributors of PM2.5 in the study area: secondary inorganic aerosols and biomass burning. The chemical constituents and sources of PM2.5 in this study area were greatly influenced and characterised by meteorological and gaseous parameters which largely vary with season.
This study investigates the PM2.5 variability in the Klang Valley urban-industrial environment....
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