Atmospheric Chemistry and Physics (Jan 2025)

Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns

  • O. G. Norman,
  • C. L. Heald,
  • C. L. Heald,
  • C. L. Heald,
  • S. Bililign,
  • P. Campuzano-Jost,
  • H. Coe,
  • H. Coe,
  • M. N. Fiddler,
  • J. R. Green,
  • J. L. Jimenez,
  • K. Kaiser,
  • J. Liao,
  • J. Liao,
  • A. M. Middlebrook,
  • B. A. Nault,
  • B. A. Nault,
  • B. A. Nault,
  • J. B. Nowak,
  • J. Schneider,
  • A. Welti

DOI
https://doi.org/10.5194/acp-25-771-2025
Journal volume & issue
Vol. 25
pp. 771 – 795

Abstract

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Secondary inorganic aerosols (sulfate, nitrate, and ammonium, SNA) are major contributors to fine particulate matter. Predicting concentrations of these species is complicated by the cascade of processes that control their abundance, including emissions, chemistry, thermodynamic partitioning, and removal. In this study, we use 11 flight campaigns to evaluate the GEOS-Chem model performance for SNA. Across all the campaigns, the model performance is best for sulfate (R2 = 0.51; normalized mean bias (NMB) = 0.11) and worst for nitrate (R2=0.22; NMB = 1.76), indicating substantive model deficiencies in the nitrate simulation. Thermodynamic partitioning reproduces the total particulate nitrate well (R2=0.79; NMB = 0.09), but actual partitioning (i.e., ε(NO3-)= NO3- / TNO3) is challenging to assess given the limited sets of full gas- and particle-phase observations needed for ISORROPIA II. In particular, ammonia observations are not often included in aircraft campaigns, and more routine measurements would help constrain sources of SNA model bias. Model performance is sensitive to changes in emissions and dry and wet deposition, with modest improvements associated with the inclusion of different chemical loss and production pathways (i.e., acid uptake on dust, N2O5 uptake, and NO3- photolysis). However, these sensitivity tests show only modest reduction in the nitrate bias, with no improvement to the model skill (i.e., R2), implying that more work is needed to improve the description of loss and production of nitrate and SNA as a whole.