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Approaches for Quantifying Aerosol Mixing State Using Single-Particle Mass Spectrometry

Portrait of Ryan Poland, speaker
Ryan Poland
Graduate Student, Department of Chemistry
University of Georgia
iSTEM Building 2, Room 1218
Analytical Seminar

While it is well established that atmospheric aerosols directly interact with solar radiation and indirectly alter cloud physical properties, there remains a sizeable uncertainty in aerosol influence on climate.1 Challenges in constraining aerosol influence arise from their complexity at the individual particle-scale as well as the global-scale. At the particle-scale, aerosols may be internally mixed, being comprised of many different molecular species which alter the particle’s direct and indirect climate effects. On the global scale, external mixing of diverse aerosols may have similar consequences. Based on information-theoretic entropy, Reimer and West (2013) introduced a mixing state index χ, to quantify the extent of internal and external mixing of an aerosol population as the affine ratio of per-particle species diversity Dα and population diversity Dγ.2 Recent studies have used χ to demonstrate the importance of mixing state on the deposition of soot particles in the human respiratory system and to quantify errors in predicting cloud formation and black carbon absorption.3,4 Elucidating Dα requires single-particle measurements for estimating mass fractions of each species present in individual particles. By defining application-based surrogate “species”, such as hygroscopic/nonhygroscopic5, we explore approaches using single-particle mass spectrometry to generate distinct χ values which have different atmospheric relevancies. 



  1. IPCC, 2023: Sections. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 35115.
    doi: 10.59327/IPCC/AR6-9789291691647 
  2. Riemer, N. and West, M. (2013). Quantifying aerosol mixing state with entropy and diversity measures. Atmos. Chem. Phys. 13 (22):11423–11439. doi:10.5194/acp-13-11423-2013. 
  3. Zheng, Z., Curtis, J.H., Yao, Y., Gasparik, J.T., Anantharaj, V.G., Zhao, L., West, M., and Riemer, N. (2021). Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling. Earth Space Sci. 8 (2).
  4. Yao, Y., Curtis, J.H., Ching, J., Zheng, Z., and Riemer, N. (2022). Quantifying the effects of mixing state on aerosol optical properties. Atmos. Chem. Phys. 22 (14):9265–9282.
  5. Ching, J., Fast, J., West, M., and Riemer, N. (2017). Metrics to quantify the importance of mixing state for CCN activity. Atmos. Chem. Phys. 17 (12):7445–7458. 
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