Impact of Thermal Decomposition on Thermal Desorption Instruments: Advantage of Thermogram Analysis for Quantifying Volatility Distributions of Organic Species

Harald Stark, Reddy L.N. Yatavelli, Samantha L. Thompson, Hyungu Kang, Jordan E. Krechmer, Joel R. Kimmel, Brett B. Palm, Weiwei Hu, Patrick L. Hayes, Douglas A. Day, Pedro Campuzano-Jost, Manjula R. Canagaratna, John T. Jayne, Douglas R. Worsnop, Jose L. Jimenez

Research output: Contribution to journalArticlepeer-review

115 Scopus citations

Abstract

We present results from a high-resolution chemical ionization time-of-flight mass spectrometer (HRToF-CIMS), operated with two different thermal desorption inlets, designed to characterize the gas and aerosol composition. Data from two field campaigns at forested sites are shown. Particle volatility distributions are estimated using three different methods: thermograms, elemental formulas, and measured partitioning. Thermogram-based results are consistent with those from an aerosol mass spectrometer (AMS) with a thermal denuder, implying that thermal desorption is reproducible across very different experimental setups. Estimated volatilities from the detected elemental formulas are much higher than from thermograms since many of the detected species are thermal decomposition products rather than actual SOA molecules. We show that up to 65% of citric acid decomposes substantially in the FIGAERO-CIMS, with ∼20% of its mass detected as gas-phase CO2, CO, and H2O. Once thermal decomposition effects on the detected formulas are taken into account, formula-derived volatilities can be reconciled with the thermogram method. The volatility distribution estimated from partitioning measurements is very narrow, likely due to signal-to-noise limits in the measurements. Our findings indicate that many commonly used thermal desorption methods might lead to inaccurate results when estimating volatilities from observed ion formulas found in SOA. The volatility distributions from the thermogram method are likely the closest to the real distributions.

Original languageEnglish
Pages (from-to)8491-8500
Number of pages10
JournalEnvironmental Science and Technology
Volume51
Issue number15
DOIs
StatePublished - Aug 1 2017

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