Cooperative Institute for Research in Environmental Sciences

Atmospheric Chemistry Program Seminar

Monday April 18 2022 @ 12:15 pm

April

18

Mon

2022

12:15 pm

Event Type
Seminar
Availability

Open to Public

Audience
  • CIRES employees
  • Science collaborators
  • Host
    CIRES, CU Boulder

    New approaches to ambient ion analysis reveal chemical trends
    Daniel Katz, ANYL 3rd year,
    Browne group
    "Atmospheric ions control the electrical properties of the atmosphere, influence chemical composition via ion-molecule and/or ion-catalyzed reactions, and affect new particle formation. Understanding the role of ions in these processes requires knowledge of ionic chemical composition. However, determining the chemical composition of these ions is analytically challenging owing to the low concentration of ambient ions in the atmosphere (~100s-1000 ions/cm 3 ). Here, we analyze measurements of the composition of ambient cations and anions collected using an atmospheric pressure interface time-of-flight mass spectrometer (APi-TOF) during the 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land- Ecosystems (HI-SCALE) campaign. We utilize a newly developed technique, binned positive matrix factorization (binPMF), in conjunction with Resolution-enhanced Kendrick Mass Defect (REKMD) analysis. These techniques allowed for improved chemical insight into the trends in ion composition with no requirement for a priori assignments of chemical composition. This advancement is of particular importance for measurements with low signal-to-noise. Mass spectral factors were first identified by binPMF and then analyzed using REKMD plots to elucidate chemical patterns within the factors. REKMD demonstrated that otherwise unidentified compounds were related by repeating units of CH 2 and O. Back trajectories and correlation with other measurements provide insight into potential sources of the various identified factors. Overall, we demonstrate that binPMF in combination with REKMD is a powerful tool to analyze challenging mass spectrometric datasets."