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
 | Highlight paper
 | 
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

Related authors

Estimation of secondary organic aerosol formation parameters for the volatility basis set combining thermodenuder, isothermal dilution, and yield measurements
Petro Uruci, Dontavious Sippial, Anthoula Drosatou, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 3155–3172, https://doi.org/10.5194/amt-16-3155-2023,https://doi.org/10.5194/amt-16-3155-2023, 2023
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Modeling the drivers of fine PM pollution over Central Europe: impacts and contributions of emissions from different sources
Lukáš Bartík, Peter Huszár, Jan Karlický, Ondřej Vlček, and Kryštof Eben
Atmos. Chem. Phys., 24, 4347–4387, https://doi.org/10.5194/acp-24-4347-2024,https://doi.org/10.5194/acp-24-4347-2024, 2024
Short summary
Reaction of SO3 with H2SO4 and its implications for aerosol particle formation in the gas phase and at the air–water interface
Rui Wang, Yang Cheng, Shasha Chen, Rongrong Li, Yue Hu, Xiaokai Guo, Tianlei Zhang, Fengmin Song, and Hao Li
Atmos. Chem. Phys., 24, 4029–4046, https://doi.org/10.5194/acp-24-4029-2024,https://doi.org/10.5194/acp-24-4029-2024, 2024
Short summary
Weakened aerosol–radiation interaction exacerbating ozone pollution in eastern China since China's clean air actions
Hao Yang, Lei Chen, Hong Liao, Jia Zhu, Wenjie Wang, and Xin Li
Atmos. Chem. Phys., 24, 4001–4015, https://doi.org/10.5194/acp-24-4001-2024,https://doi.org/10.5194/acp-24-4001-2024, 2024
Short summary
Uncertainties from biomass burning aerosols in air quality models obscure public health impacts in Southeast Asia
Margaret R. Marvin, Paul I. Palmer, Fei Yao, Mohd Talib Latif, and Md Firoz Khan
Atmos. Chem. Phys., 24, 3699–3715, https://doi.org/10.5194/acp-24-3699-2024,https://doi.org/10.5194/acp-24-3699-2024, 2024
Short summary
Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique
Julie Camman, Benjamin Chazeau, Nicolas Marchand, Amandine Durand, Grégory Gille, Ludovic Lanzi, Jean-Luc Jaffrezo, Henri Wortham, and Gaëlle Uzu
Atmos. Chem. Phys., 24, 3257–3278, https://doi.org/10.5194/acp-24-3257-2024,https://doi.org/10.5194/acp-24-3257-2024, 2024
Short summary

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. 
Download
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.
Altmetrics
Final-revised paper
Preprint