2026-09-20T13:54:04Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/132638 2026-03-24 col_2142_5131 col_2142_14839 com_2142_5130 com_2142_14838 com_2142_13459 com_2142_8903

application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-12-01 The student, Kyuhaeng Lee, accepted the attached license on 2025-11-12 at 11:01. The student, Kyuhaeng Lee, submitted this Thesis for approval on 2025-11-17 at 10:55. This Thesis was approved for publication on 2025-11-17 at 15:00. DSpace SAF Submission Ingestion Package generated from Vireo submission #22861 on 2026-02-19 at 18:45:41 Single-particle instrument simulator: Bridging experiments and models Lee, Kyuhaeng 2025-11-17 Riemer, Nicole West, Matt Nesbitt, Steve aerosol mixing state mass spectrometer non-negative matrix factorization eng 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. 2025-12 Thesis https://hdl.handle.net/2142/132638 Copyright 2025 Kyuhaeng Lee Climate Meteorology & Atm Sci Atmospheric Sciences University of Illinois Urbana-Champaign M.S. Thesis