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

被引：128

作者：

Jain, Srishti ^{[1
,2
]}

Sharma, Sudhir Kumar ^{[1
,2
]}

Choudhary, Nikki ^{[1
,3
]}

Masiwal, Renu ^{[1
,3
]}

Saxena, Mohit ^{[1
]}

Sharma, Ashima ^{[1
,2
]}

Mandal, Tuhin Kumar ^{[1
,2
]}

Gupta, Anshu ^{[3
]}

Gupta, Naresh Chandra ^{[3
]}

Sharma, Chhemendra ^{[1
]}

机构：

[1] CSIR, Natl Phys Lab, Environm Sci & Biomed Metrol Div, Dr KS Krishnan Rd, New Delhi 110012, India

[2] CSIR, Acad Sci & Innovat Res AcSIR, Natl Phys Lab Campus, New Delhi 110012, India

[3] GGS Indraprastha Univ, Univ Sch Environm Management, New Delhi 110017, India

来源：

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH | 2017年 / 24卷 / 17期

关键词：

Receptor model; PCA/APCS; UNMIX; PMF; PSCF; Source apportionment; POSITIVE MATRIX FACTORIZATION; FINE PARTICULATE MATTER; BALANCE SOURCE APPORTIONMENT; LONG-RANGE TRANSPORT; SOURCE IDENTIFICATION; RECEPTOR MODELS; ATMOSPHERIC AEROSOL; INDUSTRIAL SITES; ELEMENTAL CARBON; SEASONAL TRENDS;

D O I：

10.1007/s11356-017-8925-5

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

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 mu g m(-3) (range 25.1-429.8 mu g 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 similar to 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.

引用

页码：14637 / 14656

页数：20

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