Cloud condensation nuclei (CCN) activity analysis of low-hygroscopicity aerosols using the aerodynamic aerosol classifier (AAC)

Gohil, Kanishk; Asa-Awuku, Akua A.

doi:https://doi.org/10.5194/amt-15-1007-2022

Articles | Volume 15, issue 4

https://doi.org/10.5194/amt-15-1007-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-15-1007-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 4

Research article

|

25 Feb 2022

Research article |

| 25 Feb 2022

Cloud condensation nuclei (CCN) activity analysis of low-hygroscopicity aerosols using the aerodynamic aerosol classifier (AAC)

Kanishk Gohil and Akua A. Asa-Awuku

Supplement

https://doi.org/10.5194/amt-15-1007-2022-supplement

Model code and software

PyCAT: v1.0 Kanishk Gohil https://doi.org/10.5281/zenodo.6142898

Short summary

This work develops a methodology and software to study and analyze the cloud-droplet-forming ability of aerosols with an aerodynamic aerosol classifier (AAC). This work quantifies the uncertainties in size-resolved measurements and subsequent uncertainties propagated to cloud droplet parameterizations. Lastly, we present the best practices for AAC cloud droplet measurement.