Meetings > PI / Science Team Meeting > Posters

Aerosol Elemental and Molecular Mixing State Measurements via Multimodal X-Ray and Electron Microscopy

 
Poster PDF

Authors

Fraund Matthew — University of the Pacific
Don Pham — University of the Pacific
Daniel Bonanno — University of the Pacific
Joseph Charnawskas — Stony Brook University
Harder Tristan — Lawrence Berkeley National Laboratory
Daniel Veghte — Pacific Northwest National Laboratory
Joel Brito —
Suzane Simoes deSa — Harvard University
Samara Carbone — University of Sao Paulo
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Christopher Pohlker — Max Planck Institute for Chemistry
Bingbing Wang — Pacific Northwest National Laboratory
Paulo Artaxo — University of Sao Paulo
Meinrat Andreae — Max Planck Institute of Chemistry
Scot T. Martin — Harvard University
Jian Wang — Washington University in St. Louis
Alexander Laskin — Purdue University
Daniel Knopf — Stony Brook University
Mary Gilles — Lawrence Berkeley National Laboratory
Ryan Moffet — Sonoma Technology Inc.

Category

General topics – Aerosols

Description

This poster will present detailed measurements of mixing and morphology for particles collected during several field campaigns including ACE-ENA, an SGP intensive, and GoAmazon2014/5. Work has been undertaken to combine data sets on a per-particle basis from both Scanning Electron Microscopy coupled with Energy Dispersive X-ray (SEM-EDX) spectroscopy and Scanning Transmission X-ray Microscopy coupled with Near Edge Absorption Fine Structure Spectroscopy (STXM-NEXAFS). Laboratory studies have been undertaken to validate the quantitative capabilities of this approach. A brief summary and discussion of the laboratory validation will be presented. Software and methods related to this technique continue to be developed and applied to unique datasets gathered within the ASR program. From STXM and SEM measurements, elemental mass fractions for both light (C, N, O) and heavy (Z>11) elements have been combined to calculate particle diversity (Di) and mixing state parameters. Cluster analysis for the GoAmazon data set identified 12 particle types across the three sites, with a larger variety of particle types appearing at more anthropogenically influenced sites. A positive correlation between Di and particle size was observed, with particles < 0.5 μm having a Di of 2.4 and > 0.5 μm particles having a Di of 3.6. These likely correspond to fresh and aged aerosols, respectively. Similar methods are currently being applied to particles collected at the ARM SGP field site during an intensive study that took place during September 2016. Furthermore, preliminary data and future directions for the ACE-ENA will be presented.