Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

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作者
Srishti Jain
Sudhir Kumar Sharma
Nikki Choudhary
Renu Masiwal
Mohit Saxena
Ashima Sharma
Tuhin Kumar Mandal
Anshu Gupta
Naresh Chandra Gupta
Chhemendra Sharma
机构
[1] CSIR-National Physical Laboratory,Environmental Sciences and Biomedical Metrology Division
[2] CSIR-National Physical Laboratory campus,Academy of Scientific and Innovative Research (AcSIR)
[3] University School of Environment Management,undefined
[4] GGS Indraprastha University,undefined
关键词
Receptor model; PCA/APCS; UNMIX; PMF; PSCF; Source apportionment;
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摘要
The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM2.5 was recorded as 121.9 ± 93.2 μg m−3 (range 25.1–429.8 μg m−3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ∼17% of PM2.5. Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM2.5 from the north-west India and Pakistan were mostly pertinent.
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页码:14637 / 14656
页数:19
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