Evaluation of an automatic algorithm for fitting the particle number size distributions

The multi log-normal distribution function is widely in use to parameterize the aerosol particle size distributions. The main purpose of such a parameterization is to quantitatively describe size distributions and to allow straightforward comparisons between different aerosol particle data sets. In this study, we developed and evaluated an algorithm to parameterize aerosol particle number size distributions with the multi log-normal distribution function. The current algorithm is automatic and does not need a user decision for the initial input parameters; it requires only the maximum number of possible modes and then it reduces this number, if possible, without affecting the fitting quality. The reduction of the number of modes is based on an overlapping test between adjacent modes. The algorithm was evaluated against a previous algorithm that can be considered as a standard procedure. It was also evaluated against a long-term data set and different types of measured aerosol particle size distributions in the ambient atmosphere. The evaluation of the current algorithm showed the following advantages: (1) it is suitable for different types of aerosol particles observed in different environments and conditions, (2) it showed agreement with the previous standard algorithm in about 90% of long-term data set, (3) it is not time-consuming, particularly when long-term data sets are analyzed, and (4) it is a useful tool in the studies of atmospheric aerosol particle formation and transformation.

Authors

Publication Details

Journal
Boreal Environment Research Journal Archive
Published
2024-12-12
DOI
https://doi.org/10.60910/gkzd-jt7v
Citations
209
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
2.47
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article

Evaluation of an automatic algorithm for fitting the particle number size distributions

Markku Kulmala, Tareq Hussein, Miikka Dal Maso, Tuukka Petäjä et al.
209 citations
Boreal Environment Research Journal Archive
Air Quality Monitoring and Forecasting
2.47
article

Evaluation of an automatic algorithm for fitting the particle number size distributions

Markku Kulmala, Tareq Hussein, Miikka Dal Maso, Tuukka Petäjä, Pentti Paatero, Kaarle Hämeri, Pasi P. Aalto, Ismo Kalevi Koponen
article en
209 citations

Abstract

The multi log-normal distribution function is widely in use to parameterize the aerosol particle size distributions. The main purpose of such a parameterization is to quantitatively describe size distributions and to allow straightforward comparisons between different aerosol particle data sets. In this study, we developed and evaluated an algorithm to parameterize aerosol particle number size distributions with the multi log-normal distribution function. The current algorithm is automatic and does not need a user decision for the initial input parameters; it requires only the maximum number of possible modes and then it reduces this number, if possible, without affecting the fitting quality. The reduction of the number of modes is based on an overlapping test between adjacent modes. The algorithm was evaluated against a previous algorithm that can be considered as a standard procedure. It was also evaluated against a long-term data set and different types of measured aerosol particle size distributions in the ambient atmosphere. The evaluation of the current algorithm showed the following advantages: (1) it is suitable for different types of aerosol particles observed in different environments and conditions, (2) it showed agreement with the previous standard algorithm in about 90% of long-term data set, (3) it is not time-consuming, particularly when long-term data sets are analyzed, and (4) it is a useful tool in the studies of atmospheric aerosol particle formation and transformation.

Boreal Environment Research Journal ArchiveVol. 10(5)
Openalex Percentile: Top 12%
Air Quality Monitoring and Forecasting
2.47
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