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Published August 2004 | public
Journal Article

The Scanning DMA Transfer Function

Abstract

The scanning differential mobility analyzer (DMA) has been widely employed for measurement of rapidly evolving aerosol size distributions. Interpretation of data from scanning DMAs is greatly facilitated when an exponential voltage ramp is prescribed, since the shape of the instrumental transfer function remains constant throughout a scan. However, that transfer function may differ significantly from that expected for fixed voltage operation. Because no simple analytical description of the scanning DMA transfer function exists, it has been evaluated numerically by simulating particle trajectories within a TSI 3081 cylindrical DMA. These computations yield transfer functions for the DMA up scan that are roughly triangular but with widths significantly greater than those for fixed voltage operation, and transfer functions for the down scan that are highly asymmetric. The impact of these distortions is most obvious when the size distribution of the measured aerosol is narrow, but errors in recovered size and concentration can be significant even when the aerosol size distribution is much broader than the transfer function. The magnitude of these errors is dependent upon the ratio of the mean gas residence time to the exponential voltage time constant, the sheath-to-aerosol-flow ratio, and the technique used to determine the instrument plumbing time. Experimental results for scans across broad and narrow size distributions compare favorably with predictions based on the simulated transfer functions. Simplified corrections are provided that can be used to adjust the concentration and mobility of size distributions recovered using a fixed voltage transfer function.

Additional Information

© 2004 American Association for Aerosol Research. Received 13 February 2004; accepted 24 June 2004. We are grateful for support received from the NSF Atmospheric Chemistry and Physical Meteorology Programs through grant ATM-0094342. The authors wish to thank Patrick Chuang and Jian Wang for their assistance during the data collection. We would also like to thank the reviewers of this article for their insightful and extremely helpful suggestions.

Additional details

Created:
August 19, 2023
Modified:
October 23, 2023