Enter Note Done
Go to previous page in this tab
Session
  • Presentation | A51K: Advancing Understanding of Terrestrial-Atmospheric Interfaces: Linking Trace Gases, VOCs, and Aerosol Processes Across Scales II Poster
  • Poster
  • Bookmark Icon
  • A51K-0866: Characterizing the ice nucleation potential of particles in Bankhead National Forest: Investigating the contributions and impacts of bioaerosols and biogenic particles
  • Schedule
    Notes
  • Board 0866‚ Hall EFG (Poster Hall)
    NOLA CC
    Set Timezone

Generic 'disconnected' Message
Author(s):
Katie Chan, University of California Los Angeles (First Author, Presenting Author)
Nurun Nahar Lata, Pacific Northwest National Laboratory
Swarup China, Pacific Northwest National Laboratory


Ice-nucleating particles help form ice in clouds, which can affect weather patterns and how much precipitation occurs. Biological particles in the air, known as bioaerosols, include pollen, fungal spores, bacteria, and plant debris. These bioaerosols can act as effective ice-nucleating particles at temperatures warmer than −15 °C. However, scientists do not fully understand how these particles form ice, especially in the Southeastern U.S. where intense thunderstorms are common. This lack of knowledge limits how accurately weather and climate models represent cloud processes. This study focuses on Bankhead National Forest in Alabama, where the natural forested environment may produce large amounts of bioaerosols that influence cloud formation and storm development. Air samples were collected during four days in June 2025 at a research site in the forest. Sampling was conducted during both daytime and nighttime to study how changes in biological activity affect the efficiency of ice-nucleating particles. We also examined how local pollen species such as white oak, scarlet oak, and buttercup contribute to ice formation. Using a precise instrument called NIPA, we measured how well these particles form ice. These results improve understanding of bioaerosol impacts on clouds and support better predictions of weather patterns.



Scientific Discipline
Neighborhood
Type
Main Session
Discussion