University of Illinois Urbana-Champaign

Single-particle instrument simulator: Bridging experiments and models

Lee, Kyuhaeng

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https://hdl.handle.net/2142/132638

Description

Title
Single-particle instrument simulator: Bridging experiments and models
Author(s)
Lee, Kyuhaeng
Issue Date
2025-11-17
Director of Research (if dissertation) or Advisor (if thesis)
  • Riemer, Nicole
  • West, Matt
Committee Member(s)
Nesbitt, Steve
Department of Study
Climate Meteorology & Atm Sci
Discipline
Atmospheric Sciences
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • aerosol
  • mixing state
  • mass spectrometer
  • non-negative matrix factorization
Abstract
Aerosol mixing state, the distribution of chemical species across individual aerosol particles, is crucial for quantifying aerosol optical, chemical, and micro-physical properties. For example, a particle’s absorptivity depends on whether light-absorbing components such as black carbon are externally or internally mixed. Particle-resolved models such as PartMC track the mass of each species per particle, whereas single-particle mass spectrometers report ion signals as a function of mass-to-charge ratios. Since ion signals depend not only non-linearly on species mass but also on species-specific ionization efficiencies, fragmentation patterns, and overlapping signals, there is no straightforward mapping between mass spectra and model species masses. To bridge this gap, we develop SPIN-sim (Single-Particle Instrument Simulator), a framework that converts mass spectrometer ion signals into model-comparable composition estimates. SPIN-sim uses Non-negative Matrix Factorization (NMF) to decompose the measured mass spectra and estimate the fractional contribution of individual species in mixed particles. Tests on synthetic mixtures show that SPIN-sim can reconstruct species fractions with errors below 5% for most particles. Tests with two contrasting systems, NaCl + ammonium sulfate and NaCl + KI, show that accurate interpretation requires instrument-specific calibration, since signal–composition relationships differ even in simple binary mixtures. By providing a path towards a quantitative mapping between single-particle measurements and particle-resolved model outputs, SPIN-sim enables direct evaluation of mixing state representation in models. This approach advances model-measurement integration in aerosol science and supports improved characterization of aerosol impacts on climate and air quality.
Graduation Semester
2025-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/132638
Copyright and License Information
Copyright 2025 Kyuhaeng Lee

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Graduate Theses and Dissertations at Illinois