Ying Li

Dr. Ying Li

Department of Chemistry, University of California, Irvine, CA 92625, USA
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Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 April 2017 in Nature Communications
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MSManabu Shiraiwa
Manabu Shiraiwa
Ying LiYing Li
Ying Li
ATAlexandra P. Tsimpidi
Alexandra P. Tsimpidi
VKVlassis A. Karydis
Vlassis A. Karydis
TBThomas Berkemeier
Thomas Berkemeier
UPUlrich Pöschl
Ulrich Pöschl
Secondary organic aerosols (SOA) are a large source of uncertainty in our current understanding of climate change and air pollution. The phase state of SOA is important for quantifying their effects on climate and air quality, but its global distribution is poorly characterized. We developed a method to estimate glass transition temperatures based on the molar mass and molecular O:C ratio of SOA components, and we used the global chemistry climate model EMAC with the organic aerosol module ORACLE to predict the phase state of atmospheric SOA. For the planetary boundary layer, global simulations indicate that SOA are mostly liquid in tropical and polar air with high relative humidity, semi-solid in the mid-latitudes and solid over dry lands. We find that in the middle and upper troposphere SOA should be mostly in a glassy solid phase state. Thus, slow diffusion of water, oxidants and organic molecules could kinetically limit gas–particle interactions of SOA in the free and upper troposphere, promote ice nucleation and facilitate long-range transport of reactive and toxic organic pollutants embedded in SOA.

18 October 2016 in Environmental Science & Technology
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PLPeng Lin
Peng Lin
PAPaige K. Aiona
Paige K. Aiona
Ying LiYing Li
Ying Li
MSManabu Shiraiwa
Manabu Shiraiwa
JLJulia Laskin
Julia Laskin
ALAlexander Laskin
Alexander Laskin

14 March 2016 in Atmospheric Chemistry and Physics
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Journal Article
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Ying LiYing Li
Ying Li
UPUlrich Pöschl
Ulrich Pöschl
MSManabu Shiraiwa
Manabu Shiraiwa
The formation and aging of organic aerosols (OA) proceed through multiple steps of chemical reaction and mass transport in the gas and particle phases, which is challenging for the interpretation of field measurements and laboratory experiments as well as accurate representation of OA evolution in atmospheric aerosol models. Based on data from over 30 000 compounds, we show that organic compounds with a wide variety of functional groups fall into molecular corridors, characterized by a tight inverse correlation between molar mass and volatility. We developed parameterizations to predict the saturation mass concentration of organic compounds containing oxygen, nitrogen, and sulfur from the elemental composition that can be measured by soft-ionization high-resolution mass spectrometry. Field measurement data from new particle formation events, biomass burning, cloud/fog processing, and indoor environments were mapped into molecular corridors to characterize the chemical nature of the observed OA components. We found that less-oxidized indoor OA are constrained to a corridor of low molar mass and high volatility, whereas highly oxygenated compounds in atmospheric water extend to high molar mass and low volatility. Among the nitrogen- and sulfur-containing compounds identified in atmospheric aerosols, amines tend to exhibit low molar mass and high volatility, whereas organonitrates and organosulfates follow high O : C corridors extending to high molar mass and low volatility. We suggest that the consideration of molar mass and molecular corridors can help to constrain volatility and particle-phase state in the modeling of OA particularly for nitrogen- and sulfur-containing compounds.

4 May 2018 in Atmospheric Chemistry and Physics
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WDWing-Sy Wong DeRieux
Wing-Sy Wong DeRieux
Ying LiYing Li
Ying Li
PLPeng Lin
Peng Lin
JLJulia Laskin
Julia Laskin
ALAlexander Laskin
Alexander Laskin
MSManabu Shiraiwa
Manabu Shiraiwa
Secondary organic aerosol (SOA) accounts for a large fraction of submicron particles in the atmosphere. SOA can occur in amorphous solid or semi-solid phase states depending on chemical composition, relative humidity (RH), and temperature. The phase transition between amorphous solid and semi-solid states occurs at the glass transition temperature (Tg). We have recently developed a method to estimate Tg of pure compounds containing carbon, hydrogen, and oxygen atoms (CHO compounds) with molar mass less than 450 g mol−1 based on their molar mass and atomic O : C ratio. In this study, we refine and extend this method for CH and CHO compounds with molar mass up to ∼ 1100 g mol−1 using the number of carbon, hydrogen, and oxygen atoms. We predict viscosity from the Tg-scaled Arrhenius plot of fragility (viscosity vs. Tg∕T) as a function of the fragility parameter D. We compiled D values of organic compounds from the literature and found that D approaches a lower limit of ∼ 10 (±1.7) as the molar mass increases. We estimated the viscosity of α-pinene and isoprene SOA as a function of RH by accounting for the hygroscopic growth of SOA and applying the Gordon–Taylor mixing rule, reproducing previously published experimental measurements very well. Sensitivity studies were conducted to evaluate impacts of Tg, D, the hygroscopicity parameter (κ), and the Gordon–Taylor constant on viscosity predictions. The viscosity of toluene SOA was predicted using the elemental composition obtained by high-resolution mass spectrometry (HRMS), resulting in a good agreement with the measured viscosity. We also estimated the viscosity of biomass burning particles using the chemical composition measured by HRMS with two different ionization techniques: electrospray ionization (ESI) and atmospheric pressure photoionization (APPI). Due to differences in detected organic compounds and signal intensity, predicted viscosities at low RH based on ESI and APPI measurements differ by 2–5 orders of magnitude. Complementary measurements of viscosity and chemical composition are desired to further constrain RH-dependent viscosity in future studies.

13 July 2020 in Atmospheric Chemistry and Physics
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Ying LiYing Li
Ying Li
DDDouglas A. Day
Douglas A. Day
HSHarald Stark
Harald Stark
JJJose L. Jimenez
Jose L. Jimenez
MSManabu Shiraiwa
Manabu Shiraiwa
Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution, and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate the glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2400 organic compounds including oxygenated organic compounds, as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. This prediction method of Tg is applied to ambient observations of volatility distributions at 11 field sites. The predicted Tg values of OA under dry conditions vary mainly from 290 to 339 K and the predicted viscosities are consistent with the results of ambient particle-phase-state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would improve predictions of viscosity, especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer (AMS) data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.

7 May 2019 in Atmospheric Chemistry and Physics
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Ying LiYing Li
Ying Li
MSManabu Shiraiwa
Manabu Shiraiwa
Secondary organic aerosols (SOA) account for a substantial fraction of air particulate matter, and SOA formation is often modeled assuming rapid establishment of gas–particle equilibrium. Here, we estimate the characteristic timescale for SOA to achieve gas–particle equilibrium under a wide range of temperatures and relative humidities using a state-of-the-art kinetic flux model. Equilibration timescales were calculated by varying particle phase state, size, mass loadings, and volatility of organic compounds in open and closed systems. Model simulations suggest that the equilibration timescale for semi-volatile compounds is on the order of seconds or minutes for most conditions in the planetary boundary layer, but it can be longer than 1 h if particles adopt glassy or amorphous solid states with high glass transition temperatures at low relative humidity. In the free troposphere with lower temperatures, it can be longer than hours or days, even at moderate or relatively high relative humidities due to kinetic limitations of bulk diffusion in highly viscous particles. The timescale of partitioning of low-volatile compounds into highly viscous particles is shorter compared to semi-volatile compounds in the closed system, as it is largely determined by condensation sink due to very slow re-evaporation with relatively quick establishment of local equilibrium between the gas phase and the near-surface bulk. The dependence of equilibration timescales on both volatility and bulk diffusivity provides critical insights into thermodynamic or kinetic treatments of SOA partitioning for accurate predictions of gas- and particle-phase concentrations of semi-volatile compounds in regional and global chemical transport models.