Chemical characteristics and source apportionment of PM 2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

• Published in: Environmental science and pollution research international 2017-06, Vol.24 (17), p.14637
• Main Authors: Jain, Srishti, Sharma, Sudhir Kumar, Choudhary, Nikki, Masiwal, Renu, Saxena, Mohit, Sharma, Ashima, Mandal, Tuhin Kumar, Gupta, Anshu, Gupta, Naresh Chandra, Sharma, Chhemendra
• Format: Article
• Language: English
• Subjects: Air Pollutants; Cities; Environmental Monitoring; India; Pakistan; Particulate Matter; Trace Elements; Vehicle Emissions
• ISSN: 1614-7499
• DOI: 10.1007/s11356-017-8925-5

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 (PM ) and scrutinized their emission sources for urban region of Delhi. The 135 PM samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM was recorded as 121.9 ± 93.2 μg m (range 25.1-429.8 μg m ), 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 PM . Strong seasonal variation was observed in PM mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM 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 PM 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 PM 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 PM from the north-west India and Pakistan were mostly pertinent.