Published February 14, 2025 | Supplemental Material
Journal Article Open

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

  • 1. ROR icon Colorado State University
  • 2. ROR icon State Key Joint Laboratory of Environment Simulation and Pollution Control
  • 3. ROR icon Tsinghua University
  • 4. PSE Healthy Energy, Oakland, California, 94612, United States
  • 5. ROR icon Pacific Northwest National Laboratory
  • 6. ROR icon California Institute of Technology
  • 7. ROR icon University of California, Davis

Abstract

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, aqueous chemistry, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of 4 in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). In addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol number size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model.

Copyright and License

© 2025 American Chemical Society.

Errata

This paper was published January 24, 2025. Due to a production errror, Figure 5 was displayed incorrectly. This has been corrected and the revised version was reposted on January 28, 2025.

Featured In

Published as part of ACS ES&T Air special issue “John H. Seinfeld Festschrift”.

Acknowledgement

This work was supported by the Department of Energy, Office of Science (DE-SC0017975, DE-SC0019000) and partly funded by the National Oceanic and Atmospheric Administration (NA21OAR4310128), National Science Foundation (AGS-2041979), and Assistance Agreement No. R840008 awarded by the U.S. Environmental Protection Agency to Colorado State University. This work has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. MS, RAZ, and JES acknowledge support from the U.S. Department of Energy Atmospheric System Research (ASR) Program under contract DE-AC06-76RLO 1830 at Pacific Northwest National Laboratory (PNNL). PNNL is operated for the U.S. DOE by Battelle Memorial Institute. BZ and SW acknowledge funding from National Natural Science Foundation of China (22188102).

Data Availability

Environmental chamber data in this work are from Dr John Seinfeld’s group at the California Institute of Technology and are now available as part of the Index of Chamber Atmospheric Research in the United States (ICARUS; https://icarus.ucdavis.edu). The latest versions of the Fortran-Python model for SSM and Fortran model for WC-SSM are archived on Github:https://github.com/yicongh/SS-MOSAIC.git and https://github.com/yicongh/WC-SSM.git.

Supplemental Material

Modeling results for environmental chamber data, SOA parameters, and GOAmazon results for OH, volatility, and aerosol size distribution (PDF)

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Additional details

Created:
May 14, 2025
Modified:
May 14, 2025