Predictions of diffusion rates of large organic molecules in secondary organic aerosols using the Stokes–Einstein and fractional Stokes–Einstein relations

Evoy, Erin; Maclean, Adrian M.; Rovelli, Grazia; Liu, Ying; Tsimpidi, Alexandra P.; Karydis, Vlassis A.; Kamal, Saeid; Lelieveld, Jos; Shiraiwa, Manabu; Reid, Jonathan P.; Bertram, Allan K.

doi:10.5194/acp-19-10073-2019

Cited by 45 publications

(77 citation statements)

References 94 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These results may be important for predicting the cloud nucleating ability of anthropogenic SOA since the presence of an organic-rich outer phase at high-RH values can lower the supersaturation with respect to water required for cloud droplet formation (Petters et al, 2006;Hodas et al, 2016;Renbaum-Wolff et al, 2016;Rastak et al, 2017;Ovadnevaite et al, 2017;Liu et al, 2018). The presence of two liquid phases at RH values as low as ∼ 70 % may also impact heterogeneous chemistry, growth, and optical properties of SOA (Zuend et al, 2010;Zuend and Seinfeld, 2012;Shiraiwa et al, 2013b;Freedman, 2017;Fard et al, 2018;Zhang et al, 2018). We conclude that LLPS should be considered when predicting the cloud nucleating ability, reactivity, growth, and optical properties of SOA from anthropogenic emissions.…”

Section: Discussionmentioning

confidence: 99%

Liquid–liquid phase separation and viscosity within secondary organic aerosol generated from diesel fuel vapors

et al. 2019

Self Cite

View full text Add to dashboard Cite

Abstract. Information on liquid–liquid phase separation (LLPS) and viscosity (or diffusion) within secondary organic aerosol (SOA) is needed to improve predictions of particle size, mass, reactivity, and cloud nucleating properties in the atmosphere. Here we report on LLPS and viscosities within SOA generated by the photooxidation of diesel fuel vapors. Diesel fuel contains a wide range of volatile organic compounds, and SOA generated by the photooxidation of diesel fuel vapors may be a good proxy for SOA from anthropogenic emissions. In our experiments, LLPS occurred over the relative humidity (RH) range of ∼70 % to ∼100 %, resulting in an organic-rich outer phase and a water-rich inner phase. These results may have implications for predicting the cloud nucleating properties of anthropogenic SOA since the presence of an organic-rich outer phase at high-RH values can lower the supersaturation with respect to water required for cloud droplet formation. At ≤10 % RH, the viscosity was ≥1×108 Pa s, which corresponds to roughly the viscosity of tar pitch. At 38 %–50 % RH, the viscosity was in the range of 1×108 to 3×105 Pa s. These measured viscosities are consistent with predictions based on oxygen to carbon elemental ratio (O:C) and molar mass as well as predictions based on the number of carbon, hydrogen, and oxygen atoms. Based on the measured viscosities and the Stokes–Einstein relation, at ≤10 % RH diffusion coefficients of organics within diesel fuel SOA is ≤5.4×10-17 cm2 s−1 and the mixing time of organics within 200 nm diesel fuel SOA particles (τmixing) is 50 h. These small diffusion coefficients and large mixing times may be important in laboratory experiments, where SOA is often generated and studied using low-RH conditions and on timescales of minutes to hours. At 38 %–50 % RH, the calculated organic diffusion coefficients are in the range of 5.4×10-17 to 1.8×10-13 cm2 s−1 and calculated τmixing values are in the range of ∼0.01 h to ∼50 h. These values provide important constraints for the physicochemical properties of anthropogenic SOA.

show abstract

Section: Discussionmentioning

confidence: 99%

Liquid–liquid phase separation and viscosity within secondary organic aerosol generated from diesel fuel vapors

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…where C and t are empirical fit parameters. Evoy et al [296] find a best fit to their and literature data for C = 1.66 and t = 0.93. The SER is known to break down for glassy polymer systems in the limit of T g or high viscosity (e.g., [298,299]).…”

Section: Organic Aerosol Diffusivity Modelsmentioning

confidence: 79%

“…Evoy et al [296] consider the application of the Stokes-Einstein relation (SER) for predicting the diffusivity of SOA organics. SOA was represented by proxies consisting of citric acid, sorbitol and a sucrose-citric acid mixture.…”

Section: Organic Aerosol Diffusivity Modelsmentioning

confidence: 99%

Current State of Atmospheric Aerosol Thermodynamics and Mass Transfer Modeling: A Review

Semeniuk

Dastoor

2020

Atmosphere

View full text Add to dashboard Cite

A useful aerosol model must be able to adequately resolve the chemical complexity and phase state of the wide particle size range arising from the many different secondary aerosol growth processes to assess their environmental and health impacts. Over the past two decades, significant advances in understanding of gas-aerosol partitioning have occurred, particularly with respect to the role of organic compounds, yet aerosol representations have changed little in air quality and climate models since the late 1990s and early 2000s. The gas-aerosol partitioning models which are still commonly used in air quality models are separate inorganics-only thermodynamics and secondary organic aerosol (SOA) formation based on absorptive partitioning theory with an assumption of well-mixed liquid-like particles that continuously maintain equilibrium with the gas phase. These widely used approaches in air quality models for secondary aerosol composition and growth based on separated inorganic and organic processes are inadequate. This review summarizes some of the important developments during the past two decades in understanding of gas aerosol mass transfer processes. Substantial increases in computer performance in the last decade justify increasing the process detail in aerosol models. Organics play a central role during post-nucleation growth into the accumulation mode and change the hygroscopic properties of sulfate aerosol. At present, combined inorganic-organic aerosol thermodynamics models are too computationally expensive to be used online in 3-D simulations without high levels of aggregation of organics into a small number of functional surrogates. However, there has been progress in simplified modeling of liquid-liquid phase separation (LLPS) and distinct chemical regimes within organic-rich and inorganic-rich phases. Additional limitations of commonly used thermodynamics models are related to lack of surface tension data for various aerosol compositions in the small size limit, and lack of a comprehensive representation of surface interaction terms such as disjoining pressure in the Gibbs free energy which become significant in the small size limit and which affect both chemical composition and particle growth. As a result, there are significant errors in modeling of hygroscopic growth and phase transitions for particles in the nucleation and Aitken modes. There is also increasing evidence of reduced bulk diffusivity in viscous organic particles and, therefore, traditional secondary organic aerosol models, which are typically based on the assumption of instantaneous equilibrium gas-particle partitioning and neglect the kinetic effects, are no longer tenable.

show abstract

“…The effective diffusion coefficient for IEPOX through the organic coating (Dorg) was then calculated using the Stokes-Einstein Equation (refer to Eq. (1)), assuming that = 1 nm (Evoy et al, 2019;Ullmann et al, 2019). = 0 .…”

Section: Phase State and Its Impact On Reactive Uptake: Overviewmentioning

confidence: 99%

Predicting Secondary Organic Aerosol Phase State and Viscosity and its Effect on Multiphase Chemistry in a Regional Scale Air Quality Model

Schmedding¹,

Rasool²,

Zhang³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOA) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their: glass transition temperature (Tg), Oxygen to Carbon (O : C) ratio, concentrations relative to sulfate concentrations; and meteorological conditions were implemented into the Community Multiscale Air Quality Modeling (CMAQ) System version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core-shell morphology i.e. aqueous inorganic core surrounded by organic coating, 68.5 % of the time for continental United States. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 102–1012 Pa ⋅ s which resulted in organic mass being decreased due to diffusion limitation. The organic phase was primarily liquid where aerosol liquid water was dominant (eastern United States and at surface), with a viscosity

show abstract

Predictions of diffusion rates of large organic molecules in secondary organic aerosols using the Stokes–Einstein and fractional Stokes–Einstein relations

Cited by 45 publications

References 94 publications

Liquid–liquid phase separation and viscosity within secondary organic aerosol generated from diesel fuel vapors

Liquid–liquid phase separation and viscosity within secondary organic aerosol generated from diesel fuel vapors

Current State of Atmospheric Aerosol Thermodynamics and Mass Transfer Modeling: A Review

Predicting Secondary Organic Aerosol Phase State and Viscosity and its Effect on Multiphase Chemistry in a Regional Scale Air Quality Model

Contact Info

Product

Resources

About