Articles | Volume 19, issue 2
https://doi.org/10.5194/acp-19-973-2019
https://doi.org/10.5194/acp-19-973-2019
Research article
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24 Jan 2019
Research article | Highlight paper |  | 24 Jan 2019

Positive matrix factorization of organic aerosol: insights from a chemical transport model

Anthoula D. Drosatou, Ksakousti Skyllakou, Georgia N. Theodoritsi, and Spyros N. Pandis

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Cited articles

Allan, J. D., Williams, P. I., Morgan, W. T., Martin, C. L., Flynn, M. J., Lee, J., Nemitz, E., Phillips, G. J., Gallagher, M. W., and Coe, H.: Contributions from transport, solid fuel burning and cooking to primary organic aerosols in two UK cities, Atmos. Chem. Phys., 10, 647–668, https://doi.org/10.5194/acp-10-647-2010, 2010. 
Brinkman, G., Vance, G., Hannigan, M. P., and Milford, J. B.: Use of synthetic data to evaluate positive matrix factorization as a source apportionment tool for PM2.5 exposure data, Environ. Sci. Technol., 40, 1892–1901, 2006. 
Canonaco, F., Crippa, M., Slowik, J. G., Baltensperger, U., and Prévôt, A. S. H.: SoFi, an IGOR-based interface for the efficient use of the generalized multilinear engine (ME-2) for the source apportionment: ME-2 application to aerosol mass spectrometer data, Atmos. Meas. Tech., 6, 3649–3661, https://doi.org/10.5194/amt-6-3649-2013, 2013. 
Dall'Osto, M., Paglione, M., Decesari, S., Facchini, M. C., O'Dowd, C., Plass-Duellmer, C., and Harrison, R. M.: On the origin of AMS cooking Organic Aerosol at a rural site, Environ. Sci. Technol., 49, 13964–13972, 2015. 
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Short summary
The ability of positive matrix factorization (PMF) factor analysis to identify and quantify the organic aerosol (OA) sources accurately is tested in this modeling study. The estimated uncertainty of the contribution of fresh biomass burning is less than 30 % and of the other primary sources is less than 40 %, when these sources contribute more than 20 % to the OA. Τhe first oxygenated OA factor includes mainly highly aged OA, while the second oxygenated OA factor contains fresher secondary OA.
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