Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 16, issue 10
Articles | Volume 16, issue 10
https://doi.org/10.5194/amt-16-2471-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-2471-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 10
Research article
 | 
25 May 2023
Research article |  | 25 May 2023

Improved counting statistics of an ultrafine differential mobility particle size spectrometer system

Dominik Stolzenburg, Tiia Laurila, Pasi Aalto, Joonas Vanhanen, Tuukka Petäjä, and Juha Kangasluoma

Supplement

https://doi.org/10.5194/amt-16-2471-2023-supplement

Data sets

Raw Particle Number Size-Distribution Data of twin-DMPS equipped with two CPCs for nanoparticle detection for SMEAR II station, Hyytiälä, Finland, Spring 2017 (Version v0) Dominik Stolzenburg, Tiia Laurila, and Juha Kangasluoma https://doi.org/10.5281/zenodo.7962336

Model code and software

Monte_Carlo analysis of Particle Number Size-Distribution Data of twin-DMPS equipped with two CPCs for nanoparticle detection for SMEAR II station, Hyytiälä, Finland, Spring 2017 (Version v0) Dominik Stolzenburg and Tiia Laurila https://doi.org/10.5281/zenodo.7962563

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Short summary
Size-distribution measurements of ultrafine particles are of special interest as they can be used to estimate the atmospheric significance of new particle formation, a process which is thought to influence the global climate. Here we show that improved counting statistics in size-distribution measurements through the usage of higher sampling flows can significantly reduce the uncertainties in such calculations.
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