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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 Jun 2019

Research article | 07 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

RH-dependent organic aerosol thermodynamics via an efficient reduced-complexity model

Kyle Gorkowski1, Thomas C. Preston1,2, and Andreas Zuend1 Kyle Gorkowski et al.
  • 1Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada
  • 2Department of Chemistry, McGill University, Montreal, Quebec, Canada

Abstract. Water plays an essential role in aerosol chemistry, gas-particle partitioning, and particle viscosity, but it is typically omitted in thermodynamic models describing the mixing within organic aerosol phases and the partitioning of semivolatile organics. In this study, we introduce the Binary Activity Thermodynamics (BAT) model, a water-sensitive, reduced-complexity model treating the non-ideal mixing of water and organics. The BAT model can process different levels of physicochemical mixture information enabling its application in the thermodynamic aerosol treatment within chemical transport models, the evaluation of humidity effects in environmental chamber studies, and the analysis of field observations. It is capable of using organic structure information including O:C, H:C, molar mass, and vapor pressure, which can be derived from identified compounds or estimated from bulk aerosol properties. A key feature of the BAT model is predicting the extent of liquid-liquid phase separation occurring within aqueous mixtures containing hydrophobic organics. This is crucial to simulating the abrupt change in water uptake behavior of moderately hygroscopic organics at high relative humidity, which is essential for capturing the correct behavior of organic aerosols serving as cloud condensation nuclei. For gas-particle partitioning predictions, we complement a Volatility Basis Set (VBS) approach with the BAT model to account for non-ideality and liquid-liquid equilibrium effects. To improve the computational efficiency of this approach, we trained two neural networks; the first for the prediction of aerosol water content at given relative humidity, and the second for the partitioning of semivolatile components. The integrated VBS + BAT model is benchmarked against high-fidelity molecular-level gas-particle equilibrium calculations based on the AIOMFAC model. Organic aerosol systems derived from alpha-pinene or isoprene oxidation are used for comparison. Predicted organic mass concentrations agree within less than a 5 % error in the isoprene case, which is a significant improvement over a traditional VBS implementation. In the case of the alpha-pinene system, the error is less than 2 % up to a relative humidity of 94 %, with larger errors past that point. The goal of the BAT model is to represent the bulk O:C and molar mass dependencies of a wide range of water-organic mixtures to a reasonable degree of accuracy. In this context, we discuss that the reduced-complexity effort may be poor at representing a specific binary water-organic mixture perfectly. However, the averaging effects of our reduced-complexity model become more representative when the mixture diversity increases in terms of organic functionality and number of components.

Kyle Gorkowski et al.
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Status: open (until 02 Aug 2019)
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Kyle Gorkowski et al.
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Publications Copernicus
Short summary
We present the new Binary Activity Thermodynamics model, which is a water-sensitive, reduced-complexity organic aerosol thermodynamics model. It can use bulk properties like O:C, molar mass, and RH to predict organic activity coefficients and water uptake behavior. We show applications in RH-dependent organic co-condensation, liquid-liquid phase separation, Kohler curve predictions, and we validate the BAT model against laboratory measurements.
We present the new Binary Activity Thermodynamics model, which is a water-sensitive,...