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Published October 2017 | Supplemental Material
Journal Article Open

Charge distribution uncertainty in differential mobility analysis of aerosols


The inference of particle size distributions from differential mobility analyzer (DMA) data requires knowledge of the charge distribution on the particles being measured. The charge distribution produced by a bipolar aerosol charger depends on the properties of the ions produced in the charger, and on the kinetics of charge transfer from molecular ions or ion clusters to the particles. A single parameterization of a theoretically predicted charge distribution is employed in most DMA analyses regardless of the atmospheric conditions being probed. Deviations of the actual charge distribution from that assumed in the data analysis will bias the estimated particle size distribution. We examine these potential biases by modeling measurements and data inversion using charge distributions calculated for a range of atmospheric conditions. Moreover, simulations were performed using the ion-to-particle flux coefficients predicted for a range of properties of both the particles and ions. To probe the biases over the full range of particle sizes, the measurements were simulated through an atmospheric new particle formation event. The differences between the actual charge distribution and that according to the commonly used parametrization resulted in biases as large as a factor of 5 for nucleation-mode particles, and up to 80% for larger particles. Incorrect estimates of the relative permittivity of the particles or not accounting for the temperature and pressure effects for measurements at 10 km altitude produced biases in excess of 50%; three-fold biases result from erroneous estimates of the ion mobility distribution. We further report on the effects of the relative permittivity of the ions, the relative concentrations of negative and positive ions, and truncation of the number of charge states considered in the inversion.

Additional Information

© 2017 American Association for Aerosol Research. Received 13 May 2016, Accepted 28 May 2017, Accepted author version posted online: 09 Jun 2017, Published online: 28 Jun 2017. This work has been supported by the Magnus Ehrnrooth Foundation, the Jane and Aatos Erkko Foundation, the Emil Aaltonen Foundation, and by NSF grants CBET-1236909 and AGS-1602086.

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