Source apportionment of PM10 by positive matrix factorization model at a source region of biomass burning. (15th July 2020)

• Record Type: Journal Article
• Authors: Saggu, Gurpreet Singh; Mittal, Susheel Kumar
• Is Part Of: Journal of environmental management. Volume 266(2020)
• Publication Date: 2020-07-15
• Subjects: Source apportionment -- PMF model -- Biomass burning -- HYSPLIT -- PM10; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2020.110545
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: To determine the contribution of different particulate sources in PM10 mass concentration at semi urban site, source apportionment study was carried out from 7 May 2015 to 9 June 2016. PM10 samples were analyzed for 18 species ( NO 3 −, SO 4 2 −, Cl −, Na +, K +, Al, Ti, Mn, Fe, Mg, V, Ni, Cu, Zn, Ba, Pb, Cr, Ca). The study was specifically designed to apportion the sources of air pollution where main exposure is from crop residue burning. The particulate matter (PM10 ) samples were analyzed for mass and chemical composition, with Potassium as biomarker for crop residue burning. Sulfate SO 4 2 − ) and potassium ion ( K + ) species dominated the concentration of characterized species. K + and Cl − were identified as reliable markers for crop residue burning while Zn, Pb, Al, Ni and Cu were identified as markers for vehicular exhaust. The results of Positive matrix factorization (PMF) model gives the five major sources as probable sources of PM10 pollution. The highest contribution in PM10 mass concentration was found to be sulfate (24.39 ± 10.42), and potassium (24.02 ± 09.56) and chloride (07.07 ± 05.47), which combined accounts for nearly 60% of the total PM10 mass fraction. The highest source contribution was from Industrial emission source (22.9%), with almost same contribution from biomass burning (21.2%), and resuspended dust (20.7%) and followed by vehicular emissions (19.0%) and least from secondary aerosols (16.2%). Highlights: Source apportionment study was conducted at semi urban site. Species concentration were greater during night time than the day time values. Industrial emissions contribute more than biomass burning in the study region. Backward trajectories shows long range transport from Afghanistan and Pakistan.