Regularized inversion of aerosol hygroscopic growth factor probability density function: application to humidity-controlled fast integrated mobility spectrometer measurements

Zhang, Jiaoshi; Wang, Yang; Spielman, Steven; Hering, Susanne; Wang, Jian

doi:https://doi.org/10.5194/amt-15-2579-2022

Articles | Volume 15, issue 8

https://doi.org/10.5194/amt-15-2579-2022

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

https://doi.org/10.5194/amt-15-2579-2022

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

Articles | Volume 15, issue 8

Research article

|

28 Apr 2022

Research article |

| 28 Apr 2022

Regularized inversion of aerosol hygroscopic growth factor probability density function: application to humidity-controlled fast integrated mobility spectrometer measurements

Jiaoshi Zhang, Yang Wang, Steven Spielman, Susanne Hering, and Jian Wang

Supplement

https://doi.org/10.5194/amt-15-2579-2022-supplement

Data sets

Code and data for "Regularized inversion of aerosol hygroscopic GF-PDF: application to HFIMS measurements" J. Zhang https://doi.org/10.5281/zenodo.6481982

Short summary

New nonparametric, regularized methods are developed to invert the growth factor probability density function (GF-PDF) from humidity-controlled fast integrated mobility spectrometer measurements. These algorithms are computationally efficient, require no prior assumptions of the GF-PDF distribution, and reduce the error in inverted GF-PDF. They can be applied to humidified tandem differential mobility analyzer data. Among all algorithms, Twomey’s method retrieves GF-PDF with the smallest error.