Articles | Volume 21, issue 19
https://doi.org/10.5194/acp-21-14703-2021
https://doi.org/10.5194/acp-21-14703-2021
Research article
 | 
05 Oct 2021
Research article |  | 05 Oct 2021

Insight into PM2.5 sources by applying positive matrix factorization (PMF) at urban and rural sites of Beijing

Deepchandra Srivastava, Jingsha Xu, Tuan V. Vu, Di Liu, Linjie Li, Pingqing Fu, Siqi Hou, Natalia Moreno Palmerola, Zongbo Shi, and Roy M. Harrison

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Cited articles

Amato, F. and Hopke, P. K.: Source apportionment of the ambient PM2.5 across St. Louis using constrained positive matrix factorization, Atmos. Environ., 46, 329–337, https://doi.org/10.1016/j.atmosenv.2011.09.062, 2012. 
Amato, F., Pandolfi, M., Escrig, A., Querol, X., Alastuey, A., Pey, J., Perez, N., and Hopke, P. K.: Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2, Atmos. Environ., 43, 2770–2780, https://doi.org/10.1016/j.atmosenv.2009.02.039, 2009. 
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This study presents the source apportionment of PM2.5 performed by positive matrix factorization (PMF) at urban and rural sites in Beijing. These factors are interpreted as traffic emissions, biomass burning, road and soil dust, coal and oil combustion, and secondary inorganics. PMF failed to resolve some sources identified by CMB and AMS and appears to overestimate the dust sources. Comparison with earlier PMF studies from the Beijing area highlights inconsistent findings using this method.
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