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Quantifying errors in the aerosol mixing-state index based on limited particle sample size

  • J. T. Gasparik
  • , Q. Ye
  • , J. H. Curtis
  • , A. A. Presto
  • , N. M. Donahue
  • , R. C. Sullivan
  • , M. West
  • , N. Riemer
  • University of Illinois at Urbana-Champaign
  • Carnegie Mellon University
  • Massachusetts Institute of Technology

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This study evaluates the error that is introduced in quantifying observed aerosol mixing states due to a limited particle sample size. We used the particle-resolved model PartMC-MOSAIC to generate a scenario library that encompasses a large number of reference particle populations with a wide range of mixing states quantified by the mixing-state index χ. We stochastically sub-sampled these particle populations using sample sizes of 10 to 10,000 particles and recalculated χ based on the sub-samples. The finite sample size led to a consistent overestimation of χ, with the 95% confidence intervals ranging from −70 to 30 percentage points for sample sizes of 10 particles, and decreasing to ±10 percentage points for sample sizes of 10,000 particles. These findings were experimentally confirmed with single-particle measurements from the Pittsburgh area using a soot-particle aerosol mass spectrometer.

Original languageEnglish
Pages (from-to)1527-1541
Number of pages15
JournalAerosol Science and Technology
Volume54
Issue number12
DOIs
StatePublished - Dec 1 2020

Keywords

  • Kihong Park

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