Preprints
https://doi.org/10.5194/amt-2022-221
https://doi.org/10.5194/amt-2022-221
 
23 Aug 2022
23 Aug 2022
Status: this preprint is currently under review for the journal AMT.

Mass spectrometry-based aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol

Markus Thoma, Franziska Bachmeier, Felix Leonard Gottwald, Mario Simon, and Alexander Lucas Vogel Markus Thoma et al.
  • Institute for Atmospheric and Environmental Sciences, Goethe-University Frankfurt, 60438 Frankfurt am Main, Germany

Abstract. Particulate matter (PM) largely consists of secondary organic aerosol (SOA) that is formed via oxidation of biogenic and anthropogenic volatile organic compounds (VOCs). Unambiguous identification of SOA molecules and their assignment to their precursor vapors is a challenge that has so far only succeeded for a few SOA marker compounds, which are now well characterized and (partly) available as authentic standards. In this work, we resolve the complex composition of SOA by a top-down approach based on a newly created aerosolomics database, which is fed by non-target analysis results of filter samples from oxidation flow reactor experiments. We investigated the oxidation products from the five biogenic VOCs α-pinene, β-pinene, limonene, 3-carene, and trans-caryophyllene and from the four anthropogenic VOCs toluene, o-xylene1,2,4-trimethylbenzene, and naphthalene. Using ultra-high performance liquid chromatography coupled to a high-resolution (Orbitrap) mass spectrometer, we determine the molecular formula of 596 chromatographically separated compounds based on exact mass and isotopic pattern. We utilize retention time and fragmentation mass spectra as a basis for unambiguous attribution of the oxidation products to their parent VOCs. Based on the molecular-resolved application of the database, we are able to assign roughly half of the total signal of oxygenated hydrocarbons in ambient suburban PM2.5 to one of the nine studied VOCs. The application of the database enabled us to interpret the appearance of diurnal compound clusters that are formed by different oxidation processes. Furthermore, the application of a hierarchical cluster analysis (HCA) on the same set of filter samples enabled us to identify compound clusters that depend on sulfur dioxide mixing ratio and temperature. This study demonstrates how aerosolomics tools (database and HCA) applied on PM filter samples can improve our understanding of SOA sources, their formation pathways, and temperature-driven partitioning of SOA compounds.

Markus Thoma et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-221', Anonymous Referee #2, 13 Sep 2022
  • RC2: 'Comment on amt-2022-221', Anonymous Referee #1, 27 Sep 2022

Markus Thoma et al.

Markus Thoma et al.

Viewed

Total article views: 374 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
265 102 7 374 33 2 4
  • HTML: 265
  • PDF: 102
  • XML: 7
  • Total: 374
  • Supplement: 33
  • BibTeX: 2
  • EndNote: 4
Views and downloads (calculated since 23 Aug 2022)
Cumulative views and downloads (calculated since 23 Aug 2022)

Viewed (geographical distribution)

Total article views: 408 (including HTML, PDF, and XML) Thereof 408 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 28 Sep 2022
Download
Short summary
We introduce the aerosolomics database and apply it to particulate matter samples. Nine VOCs were oxidized under various conditions in an oxidation flow reactor and the formed SOA was measured using liquid chromatography-mass spectrometry. With the database, an unambiguous top-down attribution of atmospheric oxidation products to their parent VOCs is now possible. Combining the database with hierarchical clustering enables a better understanding on sources, formation and partitioning of SOA.