Atmospheric Aerosols
Investigating chemical composition of size-resolved aerosol collected over the Yellow Sea during Fatima 2023
Connor Overton
Connor Overton[1], Leyla Salehpoor[1], Cora J. Young[1], Rachel Ying-Wen Chang[2], Betty Croft[2], Gianina Giacosa[2], Harindra Joseph Fernando[3], Edward D. Creegan[4], Seok Lee[5], Trevor C. VandenBoer[1]
York University, Toronto ON, Canada
Aerosols play an important role regulating the atmosphere’s temperature. They impact temperature directly by trapping radiation in the upper atmosphere and indirectly by acting as nucleation sites for condensation. Condensation influences gas partitioning and aerosol mass distribution which makes predicting the chemistry of these systems difficult. This study analyzes the predominant salt ions present in marine boundary layer aerosol as well as trace, reduced-N species in size-resolved samples collected during fog events to better understand fog-aerosol interactions. In this study, marine aerosol samples were collected as part of the 2023 Yellow Sea Fatima campaign using a Micro Orifice Uniform Deposit Impactor (MOUDI). The Yellow Sea is one of the two foggiest regions on earth due to strong tidal mixing and the distribution of low salinity water. The Fatima campaigns aim to better predict and detect marine sea fog by analyzing large weather systems, small-scale atmospheric turbulence and the microphysics of fog droplet growth. Between June 20th and July 9th, 2023, ground-based sampling and analysis instruments were deployed on board the R/V Onnuri, including the MOUDI. This in situ sampler was deployed for multiple periods with aerosol collected in size-bins ranging from 0.18-18 μm, including during fog events. Analysis of reduced nitrogen and major inorganic aerosol water soluble ions was performed using ion chromatography on extracted samples. With this data, we can better understand how impactful on the size and composition of aerosol are on fog formation. This research is one piece of the puzzle for improving the accuracy of weather prediction modeling.
