Articles | Volume 15, issue 21
https://doi.org/10.5194/amt-15-6419-2022
https://doi.org/10.5194/amt-15-6419-2022
Research article
 | 
08 Nov 2022
Research article |  | 08 Nov 2022

The effect of the averaging period for PMF analysis of aerosol mass spectrometer measurements during offline applications

Christina Vasilakopoulou, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis

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Cited articles

Alfarra, M. R., Prevot, A. S. H., Szidat, S., Sandradewi, J., Weimer, S., Lanz, V. A., Schreiber, D., Mohr, M., and Baltensperger, U.: Identification of the mass spectral signature of organic aerosols from wood burning emissions, Environ. Sci. Technol., 41, 5770–5777, https://doi.org/10.1021/es062289b, 2007. 
Brown, S. G., Eberly, S., Paatero, P., and Norris, G. A.: Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results, Sci. Total Environ., 518–519, 626–635, https://doi.org/10.1016/j.scitotenv.2015.01.022, 2015. 
Budisulistiorini, S. H., Baumann, K., Edgerton, E. S., Bairai, S. T., Mueller, S., Shaw, S. L., Knipping, E. M., Gold, A., and Surratt, J. D.: Seasonal characterization of submicron aerosol chemical composition and organic aerosol sources in the southeastern United States: Atlanta, Georgia,and Look Rock, Tennessee, Atmos. Chem. Phys., 16, 5171–5189, https://doi.org/10.5194/acp-16-5171-2016, 2016. 
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. 
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Short summary
Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols when online AMS measurements are not available. In this study, we examine whether and how the low time resolution (usually 24 h) of the offline technique affects source apportionment results. We concluded that use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis.