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https://doi.org/10.5194/acp-2020-829
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-829
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Sep 2020

11 Sep 2020

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This preprint is currently under review for the journal ACP.

Using GECKO-A to derive mechanistic understanding of SOA formation from the ubiquitous but understudied camphene

Isaac Kwadjo Afreh1, Bernard Aumont2, Marie Camredon2, and Kelley Claire Barsanti1 Isaac Kwadjo Afreh et al.
  • 1Department of Chemical and Environmental Engineering and College of Engineering-Center for Environmental Research and Technology (CE-CERT), University of California-Riverside, Riverside, California 92507, USA
  • 2LISA, UMR CNRS 7583, Université Paris-Est-Créteil, Université de Paris, Institut Pierre Simon Laplace, Créteil, France

Abstract. Camphene, a dominant monoterpene emitted from both biogenic and pyrogenic sources, has been significantly understudied, particularly in regard to secondary organic aerosol (SOA) formation. When camphene represents a significant fraction of emissions, the lack of model parameterizations for camphene can result in inadequate representation of gas-phase chemistry and underprediction of SOA formation. In this work, the first mechanistic study of SOA formation from camphene was performed using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). GECKO-A was used to generate gas-phase chemical mechanisms for camphene and two well-studied monoterpenes, α-pinene and limonene; and to predict SOA mass formation and composition based on gas/particle partitioning theory. The model simulations represented observed trends in published gas-phase reaction pathways and SOA yields well under chamber-relevant photooxidation and dark ozonolysis conditions. For photooxidation conditions, 70 % of the simulated α-pinene oxidation products remained in the gas phase compared to 50 % for limonene; supporting model predictions and observations of limonene having higher SOA yields than α-pinene under equivalent conditions. The top 10 simulated particle-phase products in the α-pinene and limonene simulations represented 37–50 % of the SOA mass formed and 6–27 % of the hydrocarbon mass reacted. To facilitate comparison of camphene with α-pinene and limonene, model simulations were run under idealized atmospheric conditions, wherein the gas-phase oxidant levels were controlled. Metrics for comparison included: gas-phase reactivity profiles, time-evolution of SOA mass and yields, and physicochemical property distributions of gas- and particle-phase products. The controlled-reactivity simulations demonstrated that: (1) in the early stages of oxidation, camphene is predicted to form very low volatility products, lower than α-pinene and limonene, which condense at low mass loadings; and (2) the final simulated SOA yield for camphene (46 %) was relatively high, in between α-pinene (25 %) and limonene (74 %). A 50 / 50 (α-pinene / limonene) mixture was then used as a surrogate to represent SOA formation from camphene; while simulated SOA mass and yield were well represented, the volatility distribution of the particle-phase products was not. To demonstrate the potential importance of including a parameterized representation of SOA formation by camphene in air quality models, SOA mass and yield were predicted for three wildland fire fuels based on measured monoterpene distributions, and published SOA parameterizations for α-pinene and limonene. Using the 50 / 50 surrogate mixture to represent camphene increased predicted SOA mass by 43–50 % for black spruce and by 56–108 % for Douglas fir. This first detailed modeling study of the gas-phase oxidation of camphene and subsequent SOA formation provides an opportunity for future measurement-model comparisons and lays the foundation for developing chemical mechanism and SOA parameterizations for camphene that are suitable for air quality modeling.

Isaac Kwadjo Afreh et al.

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Short summary
This is the first SOA modeling study of the ubiquitous but understudied monoterpene, camphene. The explicit chemical model GECKO-A represented chamber data for two well-studied monoterpenes. The predicted camphene SOA yield was relatively high in comparison, ~2× α-pinene. Using 50 / 50 α-pinene / limonene as a surrogate for camphene increased predicted SOA mass from biomass burning fuels by up to ~100 %. The accurate representation of camphene in air quality models can improve predictions of SOA.
This is the first SOA modeling study of the ubiquitous but understudied monoterpene, camphene....
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