10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

Abstract View


Direct Sampling of Sub-µm Atmospheric Particulate Organic Matter at Sub-ng m-3 Mass Concentrations by Proton-Transfer-Reaction Mass Spectrometry

MARKUS MUELLER, Andreas Klinger, Gregor Mayramhof, Joris Leglise, Todd Rogers, Armin Wisthaler, IONICON Analytik GmbH., Innsbruck, Austria

     Abstract Number: 92
     Working Group: Instrumentation

Abstract
The chemical characterization of the organic fraction of atmospheric particulate matter is still a challenge. Herein we present the novel modular "Chemical Analysis of Aerosol Online" (CHARON) particle inlet coupled to a new-generation proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF 6000 X2, Ionicon Analytik, Austria). The PTR-TOF 6000 X2 detects organic analytes in real-time at sub-pptV levels by chemical ionization with hydronium reagent ions. The CHARON inlet consists of a gas-phase denuder for stripping off gas-phase analytes (efficiency >99.999%), an aerodynamic lens for particle collimation, an inertial sampler for the particle-enriched flow and a thermodesorption unit for particle volatilization. With an enrichment factor of ~30 for particle diameters (DP) between 120 nm and 1000 nm (lower enrichment for particles in the 60-to-120 nm diameter range), the CHARON PTR-TOF 6000 X2 system detects particulate organic matter online and in real-time down to 200 pg m-3. Proton transfer from hydronium ions quantitatively ionizes almost the full range of organic analytes in the intermediate to low volatility range. The high mass resolution (R > 6000) and mass accuracy (< 10 ppm) of the Ionicon PTR-TOF 6000 X2 allows to assign elemental compositions to organic analyte ions over a large mass range. We will present a detailed characterization of the CHARON PTR-TOF 6000 X2 instrument and first results from ambient air measurements in Innsbruck (Austria).

The development of CHARON was funded through the PIMMS ITN, which was supported by the European Commission’s 7th Framework Programme under grant agreement number 287382. J.L. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 690958 (MARSU).