Statistical signal analysis for optical aerosol spectrometers: Closing the gap between single particle counting and signal fluctuation analysis

Light scattering aerosol spectrometers (also known as optical particle counters, OPCs) are widely used for aerosol quantification. The single particle counting method, which is based on light scattering, can measure the size distribution and the number concentration of the sampled aerosol. However, this method is limited to low concentrations due to coincidence error. At higher concentrations, the particle pulses overlap and cannot be counted individually. It was recently shown that the detector signal of an optical aerosol spectrometer can also be evaluated by fluctuation analysis if the concentration is significantly higher than the coincidence limit of the device. This new mode of operation cannot yet provide a detailed size distribution but itis feasible to measure the median particle size and number concentration independently. The measurement information required for fluctuation analysis is drawn from the intensity distribution of the detector signal instead of individual pulses. Therefore, fluctuation analysis requires a certain average number of particles inside the measuring volume so that the detector output continuously leaves the baseline. Theminimum number concentration of the fluctuation analysis is around a factor of20 higher than the coincidence limit for single particle counting. Consequently, there is a concentration range where neither single particle counting, nor fluctuation analysis can be used. This work introduces a new statistical signal analysis to bridge this gap. The new measurement method was experimentally verified using a monodisperse di-ethyl-hexyl-sebacat aerosol with a particle size range of 0.3 µm to 2.2 µm and a number concentration range of 1 × 10 4 cm −3 to 2 × 10 5 cm −3 . An accuracy of 2 % with respect to median particle size and 5 % with respect to number concentration was achieved. The new method finally closes the gap between single particle counting and fluctuation analysis, enabling light scattering aerosol spectrometers to quantify aerosols at any given concentration. • Statistical fluctuation analysis measures particle size and number concentration. • Bridges the gap between single particle counting and fluctuation analysis. • Validated using DEHS aerosol with a number concentration from 1 × 10 4 cm −3 to 2 × 10 5 cm −3 . • Particle size of the monodisperse aerosol was between 0.3 µm and 2.2 µm. • Measurement accuracy for particle size was 2 % and 5 % for number concentration.

Authors

Institutions

Publication Details

Journal
Journal of Aerosol Science
Published
2025-05-27
DOI
https://doi.org/10.1016/j.jaerosci.2025.106611
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Statistical signal analysis for optical aerosol spectrometers: Closing the gap between single particle counting and signal fluctuation analysis

Daniel Göhler, Benno Wessely, Jens Lienig, Jan Marco Müller et al.
Journal of Aerosol Science
Atmospheric chemistry and aerosols
article

Statistical signal analysis for optical aerosol spectrometers: Closing the gap between single particle counting and signal fluctuation analysis

Daniel Göhler, Benno Wessely, Jens Lienig, Jan Marco Müller, Lukas Oeser, Claudia Jahn-Wolf, Nakul Samala, Lars Hillemann, Andreas Rudolph
article en

Abstract

Light scattering aerosol spectrometers (also known as optical particle counters, OPCs) are widely used for aerosol quantification. The single particle counting method, which is based on light scattering, can measure the size distribution and the number concentration of the sampled aerosol. However, this method is limited to low concentrations due to coincidence error. At higher concentrations, the particle pulses overlap and cannot be counted individually. It was recently shown that the detector signal of an optical aerosol spectrometer can also be evaluated by fluctuation analysis if the concentration is significantly higher than the coincidence limit of the device. This new mode of operation cannot yet provide a detailed size distribution but itis feasible to measure the median particle size and number concentration independently. The measurement information required for fluctuation analysis is drawn from the intensity distribution of the detector signal instead of individual pulses. Therefore, fluctuation analysis requires a certain average number of particles inside the measuring volume so that the detector output continuously leaves the baseline. Theminimum number concentration of the fluctuation analysis is around a factor of20 higher than the coincidence limit for single particle counting. Consequently, there is a concentration range where neither single particle counting, nor fluctuation analysis can be used. This work introduces a new statistical signal analysis to bridge this gap. The new measurement method was experimentally verified using a monodisperse di-ethyl-hexyl-sebacat aerosol with a particle size range of 0.3 µm to 2.2 µm and a number concentration range of 1 × 10 4 cm −3 to 2 × 10 5 cm −3 . An accuracy of 2 % with respect to median particle size and 5 % with respect to number concentration was achieved. The new method finally closes the gap between single particle counting and fluctuation analysis, enabling light scattering aerosol spectrometers to quantify aerosols at any given concentration. • Statistical fluctuation analysis measures particle size and number concentration. • Bridges the gap between single particle counting and fluctuation analysis. • Validated using DEHS aerosol with a number concentration from 1 × 10 4 cm −3 to 2 × 10 5 cm −3 . • Particle size of the monodisperse aerosol was between 0.3 µm and 2.2 µm. • Measurement accuracy for particle size was 2 % and 5 % for number concentration.

Journal of Aerosol ScienceVol. 188
Joyson Safety Systems (Germany) (DE), Technische Universität Dresden (DE)
Openalex Percentile: Top 84%
Atmospheric chemistry and aerosols
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.