4.5 Article

Source apportionment of PM10 in Delhi, India using PCA/APCS, UNMIX and PMF

Journal

PARTICUOLOGY
Volume 37, Issue -, Pages 107-118

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.partic.2017.05.009

Keywords

Receptor model; PCA/APCS; UNMIX; PMF; Source apportionment

Funding

  1. Council of Scientific and Industrial Research, New Delhi [PSC-0112]
  2. Department of Science and Technology (DST), New Delhi via an INSPIRE Fellowship

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Source apportionment of particulate matter (PM10) measurements taken in Delhi, India between January 2013 and June 2014 was carried out using two receptor models, principal component analysis with absolute principal component scores (PCA/APCS) and UNMIX. The results were compared with previous estimates generated using the positive matrix factorization (PMF) receptor model to investigate each model's source-apportioning capability. All models used the P-10 chemical composition (organic carbon (OC), elemental carbon (EC), water soluble inorganic ions (WSIC), and trace elements) for source apportionment. The average PM10 concentration during the study period was 249.7 +/- 103.9 mu g/m(3) (range: 61.4-584.8 mu g/m(3)). The UNMIX model resolved five sources (soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), a mixed source of biomass burning (BB) and sea salt (SS), and industrial emissions (IE)). The PCA/APCS model also resolved five sources, two of which also included mixed sources (SD, VE, SD+SS, (SA+BB+SS) and 1E). The PMF analysis differentiated seven individual sources (SD, VE, SA, BB, SS, IE, and fossil fuel combustion (FFC)). All models identified the main sources contributing to PM10 emissions and reconfirmed that VE, SA, BB, and SD were the dominant contributors in Delhi. (C) 2017 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

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