Simulated phase state and viscosity of secondary organic aerosols over China

• Published in: Atmospheric chemistry and physics Vol. 24; no. 8; pp. 4809 - 4826
• Main Authors: Zhang, Zhiqiang, Li, Ying, Ran, Haiyan, An, Junling, Qu, Yu, Zhou, Wei, Xu, Weiqi, Hu, Weiwei, Xie, Hongbin, Wang, Zifa, Sun, Yele, Shiraiwa, Manabu
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 23.04.2024; Copernicus Publications
• Subjects: Aerosol effects; Aerosols; Air quality; Analysis; Boundary conditions; Chemical partition; Chemical transport; Chemistry; Emissions; Forecasting models; Gases; Glass transition temperature; High altitude; High humidity; Inorganic compounds; Investigations; Liquid phases; Liquids; Meteorological research; Organic chemistry; Organic compounds; Outdoor air quality; Parameterization; Partitioning; Phase transitions; Predictions; Relative humidity; Secondary aerosols; Semisolids; Simulation; Solid phases; Spatial distribution; Summer; Summer monsoon; Time; Transition temperatures; Urban areas; Viscosity; Volatility; Water uptake; Weather forecasting; China; Beijing China; Amazon Basin
• ISSN: 1680-7324; 1680-7316; 1680-7324
• DOI: 10.5194/acp-24-4809-2024

Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states. Chemical transport models (CTMs), however, usually assume that SOA particles are homogeneous and well-mixed liquids, with rapid establishment of gas–particle equilibrium for simulations of SOA formation and partitioning. Missing the information of SOA phase state and viscosity in CTMs impedes accurate representation of SOA formation and evolution, affecting the predictions of aerosol effects on air quality and climate. We have previously developed a parameterization to estimate the glass transition temperature (Tg) of an organic compound based on volatility and to predict viscosity of SOA. In this study, we apply this method to predict the phase state of SOA particles over China in summer of 2018 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The simulated Tg of dry SOA (Tg,org) agrees well with the value estimated from ambient volatility measurements at an urban site in Beijing. For the spatial distributions of Tg,org, simulations show that at the surface the values of Tg,org range from ∼287 to 305 K, with higher values in northwestern China, where SOA particles have larger mass fractions of low-volatility compounds. Considering water uptake by SOA particles, the SOA viscosity shows a prominent geospatial gradient in which highly viscous or solid SOA particles are mainly predicted in northwestern China. The lowest and highest SOA viscosity values both occur over the Qinghai–Tibet Plateau, where the solid phase state is predicted over dry and high-altitude areas and the liquid phase state is predicted mainly in the south of the plateau with high relative humidity during the summer monsoon season. Sensitivity simulations show that, including the formation of extremely low-volatility organic compounds, the percent time that a SOA particle is in the liquid phase state decreases by up to 12 % in southeastern China during the simulated period. With an assumption that the organic and inorganic compounds are internally mixed in one phase, we show that the water absorbed by inorganic species can significantly lower the simulated viscosity over southeastern China. This indicates that constraining the uncertainties in simulated SOA volatility distributions and the mixing state of the organic and inorganic compounds would improve prediction of viscosity in multicomponent particles in southeastern China. We also calculate the characteristic mixing timescale of organic molecules in 200 m SOA particles to evaluate kinetic limitations in SOA partitioning. Calculations show that during the simulated period the percent time of the mixing timescale longer than 1 h is >70 % at the surface and at 500 hPa in most areas of northern China, indicating that kinetic partitioning considering the bulk diffusion in viscous particles may be required for more accurate prediction of SOA mass concentrations and size distributions over these areas.