Literature DB >> 19673247

Sampling nanoparticles for chemical analysis by low resolution electrical mobility classification.

Peter H McMurry1, Ajaya Ghimire, Hyo-Kueh Ahn, Hiromu Sakurai, Katharine Moore, Mark Stolzenburg, James N Smith.   

Abstract

The use of electrostatic classification to collect samples of aerosol nanoparticles for chemical analysis is discussed. Our technique exposes the aerosol to negative ions in a unipolar charger with subsequent mobility classification at low resolution and high sampling rate. The negative unipolar charger produces high charged fractions. The low-resolution mobility classifier enables the delivery of high mass concentrations in a well-defined mobility range. The mobility-classified particles are collected by electrostatic precipitation. We summarize experimental and computational work on the performance of the unipolar charger, and we describe the performance of the overall system when used to sample atmospheric particles. For a size distribution measured in Atlanta during a new particle formation event, calculated mass sampling rates of approximately 8 nm particles were about 150 pg/h.

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Year:  2009        PMID: 19673247     DOI: 10.1021/es8029335

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  3 in total

1.  Observations of aminium salts in atmospheric nanoparticles and possible climatic implications.

Authors:  James N Smith; Kelley C Barsanti; Hans R Friedli; Mikael Ehn; Markku Kulmala; Donald R Collins; Jacob H Scheckman; Brent J Williams; Peter H McMurry
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-07       Impact factor: 11.205

2.  Increasing the Performance of Portable Ion Mobility Analyzers: Development of the Periodic Focusing Differential Mobility Analyzer (PFDMA).

Authors:  Kent J Gillig; Chung-Hsuan Chen
Journal:  Mass Spectrom (Tokyo)       Date:  2014-05-01

3.  Atmospheric fungal nanoparticle bursts.

Authors:  Michael J Lawler; Danielle C Draper; James N Smith
Journal:  Sci Adv       Date:  2020-01-15       Impact factor: 14.136

  3 in total

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