Three-year Long Source Apportionment Study of Airborne Particles in Ulaanbaatar Using X-ray Fluorescence and Positive Matrix Factorization

• Published in: Aerosol and Air Quality Research 2019-05, Vol.19 (5), p.1056-1067
• Main Authors: Gunchin, Gerelmaa, Manousakas, Manousos, Osan, Janos, Karydas, Andreas Germanos, Eleftheriadis, Konstantinos, Lodoysamba, Sereeter, Shagjjamba, Dagva, Migliori, Alessandro, Padilla-Alvarez, Roman, Streli, Christina, Darby, Iain
• Format: Article
• Language: English
• ISSN: 1680-8584; 2071-1409
• DOI: 10.4209/aaqr.2018.09.0351

The capital city of Mongolia, Ulaanbaatar, suffers from high levels of pollution due to excessive airborne particulate matter (APM). A lack of systematic data for the region has inspired investigation into the type, origin and seasonal variations of this pollution, the effects of meteorological conditions and even the time-dependence of anthropogenic sources. This work reports source apportionment results from a large data set of 184 samples each of fine (PM_(2.5)) and coarse (PM_(2.5-10)) fraction atmospheric PM collected over a three-year period (2014-2016) in Ulaanbaatar, Mongolia. Positive Matrix Factorization (PMF) was applied using the concentrations of 16 elements measured by an energy dispersive X-ray fluorescence spectrometer along with the black carbon content measured by a reflectometer as input data. The PMF results revealed that whereas mixed sources dominate the coarse fraction, soil and traffic sources are the principle contributors to the fine fraction. The source profiles and the seasonal variations of their contributions indicate that fly ash emanating from coal combustion mixes with traffic emissions and resuspended soil, resulting in variable chemical source profiles. Four sources were identified for both fractions, namely, soil, coal combustion, traffic and oil combustion, which respectively contributed 35%, 16%, 41% and 8% to the coarse fraction and 31%, 27%, 31% and 11% to the fine fraction. Additionally, the probable source contributions from long-range transport events were assessed via concentration-weighted trajectory analysis.