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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: review article 20 Jan 2020

Submitted as: review article | 20 Jan 2020

Review status
A revised version of this preprint is currently under review for the journal AMT.

Assessment of particle size magnifier inversion methods to obtain particle size distribution from atmospheric measurements

Tommy Chan1,2, Runlong Cai1,2, Lauri R. Ahonen2, Yiliang Liu3, Ying Zhou1, Joonas Vanhanen4, Lubna Dada1,2, Yan Chao1,2, Yongchun Liu1, Lin Wang3, Markku Kulmala1,2, and Juha Kangasluoma1,2 Tommy Chan et al.
  • 1Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
  • 2Institute for Atmospheric and Earth System Research / Physics, Faculty of Science, University of Helsinki, Helsinki 00014 Finland
  • 3Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
  • 4Airmodus Ltd., Erik Palménin aukio 1, Helsinki 00560, Finland

Abstract. Determining the particle size distribution of atmospheric aerosol particles is an important component to understand nucleation, formation and growth. This is particularly crucial at the sub 3 nm range because of the growth of newly-formed nanoparticles. The challenge in recovering the size distribution is due its complexity and the fact that not many instruments currently measure at this size range. In this study, we used the particle size magnifier (PSM) to measure atmospheric aerosols. Each event was classified into one of the three types: new particle formation (NPF), non-event and haze events. We then compared four inversion methods (step-wise, kernel, Hagen and Alofs and expectation-maximization) to determine its feasibility to recover the particle size distribution. In addition, we proposed a method to pre-treat measured data and introduced a simple test to estimate the efficacy of the inversion itself. Results showed that all four methods inverted NPF events well; but the step-wise and kernel methods fared poorly when inverting non-event and haze events. This was due to their algorithm, such that when encountering noisy data (e.g. air mass fluctuations) and under the influence of larger particles, these methods overestimated the size distribution and reported artificial particles during inversion. Therefore, using a statistical hypothesis test to discard noisy scans prior to inversion is an important first step to achieve a good size distribution. As a first step after inversion, it is ideal to compare the integrated concentration to the raw estimate (i.e., the concentration difference at the lowest supersaturation and the highest supersaturation) to ascertain whether the inversion itself is sound. Finally, based on the analysis of the inversion methods, we provide recommendations and codes related to the PSM data inversion.

Tommy Chan et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Tommy Chan et al.

Model code and software

PSM-Inversion T. Chan

Tommy Chan et al.


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Publications Copernicus
Short summary
Using the Particle Size Magnifier (PSM; Airmodus Oy, Finland), we determined the particle size distribution using four inversion methods and compared each method to one another to find their pros and cons. Furthermore, we provide a step-by-step procedure on how to invert measured data using the PSM. Finally, we provide recommendations and code related to the data inversion. This is an important paper as no operating procedure has been written on how to process measured PSM data.
Using the Particle Size Magnifier (PSM; Airmodus Oy, Finland), we determined the particle size...