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Development of a new nanoparticle sizer equipped with a 12-channel multi-port differential mobility analyzer and multi-condensation particle countersopen access

Authors
Lee, Hong KuLee, HandolAhn, Kang-Ho
Issue Date
Apr-2020
Publisher
Copernicus Gesellschaft mbH
Citation
Atmospheric Measurement Techniques, v.13, no.3, pp 1551 - 1562
Pages
12
Indexed
SCIE
SCOPUS
Journal Title
Atmospheric Measurement Techniques
Volume
13
Number
3
Start Page
1551
End Page
1562
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1182
DOI
10.5194/amt-13-1551-2020
ISSN
1867-1381
1867-8548
Abstract
Measuring particle size distributions precisely is an important concern in addressing environmental and human health-related issues. To measure particle size distributions, a scanning mobility particle sizer (SMPS) is often used. However, it is difficult to analyze particle size distributions under fast-changing concentration conditions because the SMPS cannot respond fast enough to reflect current conditions due to the time necessary for voltage scanning. In this research, we developed a new nanoparticle sizer (NPS), which consists of a multi-port differential mobility analyzer (MP-DMA) with 12 sampling ports and multi-condensation particle counters (M-CPCs) that simultaneously measure concentrations of particles classified by the sampling ports. The M-CPC can completely condense particles larger than 10 nm, and the total particle concentrations measured by each CPC in the M-CPCs and an electrometer were in agreement up to 20 000 no. cm(-3). We conducted size distribution measurements under steady-state conditions using an aerosol generator and under unsteady conditions by switching the aerosol supply on or off. The data obtained by the NPS corresponded closely to the SMPS measurement data for the steady-state particle concentration case. In addition, the NPS could successfully capture the changes in particle size distribution under fast-changing particle concentration conditions. Finally, we present NPS measurement results of size distributions in a common situation (cooking) as an exemplary real-world application.
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