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

被引:108
作者
Amil, Norhaniza [1 ,2 ]
Latif, Mohd Talib [1 ,3 ]
Khan, Md Firoz [4 ]
Mohamad, Maznorizan [5 ]
机构
[1] Univ Kebangsaan Malaysia, Fac Sci & Technol, Sch Environm & Nat Resource Sci, Bangi 43600, Selangor, Malaysia
[2] Univ Sains Malaysia, Sch Ind Technol, Environm Div, George Town 11800, Penang, Malaysia
[3] Univ Kebangsaan Malaysia, Inst Environm & Dev LESTARI, Bangi 43600, Selangor, Malaysia
[4] Univ Kebangsaan Malaysia, Ctr Trop Climate Change Syst IKLIM, Inst Climate Change, Bangi 43600, Selangor, Malaysia
[5] Malaysian Meteorol Dept, Jalan Sultan, Petaling Jaya 46667, Selangor, Malaysia
关键词
FINE PARTICULATE MATTER; CHEMICAL MASS-BALANCE; POLYCYCLIC AROMATIC-HYDROCARBONS; POSITIVE MATRIX FACTORIZATION; PARTICLE NUMBER CONCENTRATION; UNITED-STATES IMPLICATIONS; SOURCE APPORTIONMENT; AIR-POLLUTION; BLACK CARBON; TRACE-ELEMENTS;
D O I
10.5194/acp-16-5357-2016
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 28aEuro-+/- aEuro-18aEuro-A mu gaEuro-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 118aEuro-A mu gaEuro-m(-3) with the daily WHO guideline exceeded 43aEuro-% of the time. The north-east (NE) monsoon was the only season with less than 50aEuro-% 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 PM(2.5)aEuro-a center dot aEuro-PM10, PM(2.5)aEuro-a center dot aEuro-TSP and PM(10)aEuro-a center dot aEuro-TSP ratios reveal that meteorological parameters only greatly influenced the coarse particles (particles with an aerodynamic diameter of greater than 2.5aEuro-A mu m) 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) BCaEuro-> aEuro-secondary inorganic aerosols (SIA)aEuro-> aEuro-dustaEuro-> aEuro-trace elementsaEuro-> aEuro-sea salt > aEuro-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 17aEuro-% 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.
引用
收藏
页码:5357 / 5381
页数:25
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