Diurnal and Seasonal Variations in the Phase State of Secondary Organic Aerosol Material over the Contiguous US Simulated in CMAQ
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The main objective of this research grant project was to investigate the physical-chemical processes and properties of particles and partitioning gases that influence gas/particle (G/P) partitioning and timescales for equilibration, to directly determine the conditions under which equilibrium G/P partitioning theory can be applied to secondary organic aerosol (SOA). SOA constitutes a major component of submicron particles in the atmosphere, which have important implications for air quality, human and ecosystem health, radiation balance, and climate; however SOA formation, evolution and losses are not well understood. Use of novel on-line measurements of chemically-speciated partitioning measurements of both gas-phase and particle-phase components was a central component to advancing these scientific goals. The key approach was to conduct environmental chamber studies with systems of increasing complexity to determine G/P partitioning rates and equilibrium states for chemically-speciated SOA components. The project builds on our previous work on gas-wall partitioning that must be understood in order to study G/P partitioning in chambers, and to help extrapolate the results to be atmospherically relevant. The goal was to employ measurements and modeling to systematically determine when G/P partitioning theory accurately describes the distribution of oxidized organic compounds in the gas and aerosol phases, and when and why it does not (e.g., aerosol phase-state kinetic limitations, non-ideal mixing, phase separation, oligomer formation,), for chemical and physical conditions typically found throughout the continental boundary layer.
The formation, growth and evolution of secondary organic aerosols (SOA) are complex multiphase chemical processes, which represent one of the most challenging and demanding problems in research on atmospheric aerosol processes. The research goal of this project was to advance the fundamental understanding of the interplay between gas-phase chemistry and multiphase processes on phase state and growth dynamics of SOA for better predictivity of aerosol effects on climate and air quality.
Isoprene is an abundant volatile organic compound emitted from broadleaf forests. Under low nitric oxide concentrations, isoprene is photochemically oxidized to form gas-phase isoprene epoxydiols (IEPOX). In the presence of acidified sulfate aerosols, IEPOX enhances the secondary organic aerosol (SOA) formation. Predictions of IEPOX-SOA in regional-scale models, e.g., the Community Multiscale Air Quality Model (CMAQ), are uncertain due to homogeneous aerosol assumptions, underpredictions of water uptake (hygroscopicity), and aerosol surface area. Here, we used experimental measurements of IEPOX-SOA tracers, 2-methyltetrols (2-MT) and 2-methyltetrol sulfates (2-MTS), formed at initial IEPOX-to-inorganic sulfate ratios ranging from 1–10.5, at ∼50% relative humidity to constrain key IEPOX-SOA parameters: phase separation, organic shell diffusivity (D org ), acidity, hygroscopic growth, mass accommodation, and kinetics. The base CMAQ parametrization overpredicted experimental IEPOX-SOA with an average normalized mean bias (NMB average ) of 1.63. CMAQ with phase separation underpredicted IEPOX-SOA (NMB average = −0.71). Using the phase-separated model, CMAQ model performance was optimized (NMB average = 0.077) with an increased D org = 2 × 10 –16 m 2 s –1 and increased rate constants (k 2-MT = 1 × 10 –3 M 2 s –1 , k 2-MTS = 8.83 × 10 –3 M 2 s –1 ). The optimized model explicitly accounted for hygroscopic growth by utilizing experimentally derived growth rates, improving aerosol surface area predictions. Our model highlights the importance of the aerosol mixing state (homogeneous versus phase-separated), aerosol size dynamics, and hygroscopic growth in modeling heterogeneous reactive uptake of IEPOX.
Secondary organic aerosols (SOA) account for a major fraction of particulate matter in the atmosphere, affecting climate, air quality, and public health. SOA formation and evolution are highly complex processes involving both chemical reactions and transport of molecules in air, at particle surfaces, and within particles. The state of the matter, or “phase state,” comprising SOA can vary from a liquid, over an amorphous semi-solid, to a glassy solid, depending on chemical composition, water content, relative humidity (RH), and temperature. The occurrence of glassy and amorphous semi-solid states can pose limitations on the rate of transport of molecules, affecting gas-particle interactions and challenging the treatment of SOA in atmospheric models. The objective of this project was to improve fundamental understanding of the interplay of the phase state of particles and water content on the evolution of SOA formation. We have developed a method to estimate the glass transition temperature (T g ) of organic compounds to predict the phase state and viscosity of SOA. This method has been applied to high resolution mass spectrometry data of various types of SOA, achieving a good agreement with viscosity measurements. In addition, the viscosity estimation method was implemented into a regional model CMAQ to simulate diel and seasonal variations of SOA phase state over the U.S. Applying kinetic multilayer modeling, we analyzed laboratory experiments and ARM field measurements (e.g., HI-SCALE) on kinetic limitations of amine uptake. We have also conducted numerical simulations to estimate equilibration timescales of SOA partitioning. Overall, we have evaluated the impacts of phase state and water content on SOA lifecycle that should contribute to reducing the uncertainty of SOA representation in regional climate and air quality predictions. The project has yielded 17 publications, in which DE-SC0018349 is explicitly acknowledged. Please see the list of publications as below, followed by summary of research activities.
Typical tropospheric temperatures render possible phase states of amorphous organic aerosol (OA) particles of solid, semisolid, and liquid. This will affect the multiphase oxidation kinetics involving the organic condensed-phase and gaseous oxidants and radicals. To quantify this effect, we determined the reactive uptake coefficients (γ) of O 3 , NO 3 , and OH by substrate films composed of single and binary OA surrogate species under dry conditions for temperatures from 213 to 313 K. A temperature-controlled coated-wall flow reactor coupled to a chemical ionization mass spectrometer was applied to determine γ with consideration of gas diffusion transport limitation and gas flow entrance effects, which can impact heterogeneous reaction kinetics. The phase state of the organic substrates was probed via the poke-flow technique, allowing the estimation of the substrates' glass transition temperatures. γ values for O 3 and OH uptake to a canola oil substrate, NO 3 uptake to a levoglucosan and a levoglucosan / xylitol substrate, and OH uptake to a glucose and glucose / 1,2,6-hexanetriol substrate have been determined as a function of temperature. We observed the greatest changes in γ with temperature for substrates that experienced the largest changes in viscosity as a result of a solid-to-liquid phase transition. Organic substrates that maintain a semisolid or solid phase state and as such a relatively higher viscosity do not display large variations in heterogeneous reactivity. From 213 to 293 K, γ values of O 3 with canola oil, of NO 3 with a levoglucosan / xylitol mixture, and of OH with a glucose / 1,2,6-hexanetriol mixture and canola oil, increase by about a factor of 34, 3, 2, and 5, respectively, due to a solid-to-liquid phase transition of the substrate. These results demonstrate that the surface and bulk lifetime of the OA surrogate species can significantly increase due to the slowed heterogeneous kinetics when OA species are solid or highly viscous in the middle and upper troposphere. This experimental study will further our understanding of the chemical evolution of OA particles with subsequent important consequences for source apportionment, air quality, and climate.
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Abstract. Evidence has accumulated that secondary organic aerosols (SOAs) exhibit complex morphologies with multiple phases that can adopt amorphous semisolid or glassy phase states. However, experimental analysis and numerical modeling on the formation and evolution of SOA still often employ equilibrium partitioning with an ideal mixing assumption in the particle phase. Here we apply the kinetic multilayer model of gas–particle partitioning (KM-GAP) to simulate condensation of semi-volatile species into a core–shell phase-separated particle to evaluate equilibration timescales of SOA partitioning. By varying bulk diffusivity and the activity coefficient of the condensing species in the shell, we probe the complex interplay of mass transfer kinetics and the thermodynamics of partitioning. We found that the interplay of non-ideality and phase state can impact SOA partitioning kinetics significantly. The effect of non-ideality on SOA partitioning is slight for liquid particles but becomes prominent in semisolid or solid particles. If the condensing species is miscible with a low activity coefficient in the viscous shell phase, the particle can reach equilibrium with the gas phase long before the dissolution of concentration gradients in the particle bulk. For the condensation of immiscible species with a high activity coefficient in the semisolid shell, the mass concentration in the shell may become higher or overshoot its equilibrium concentration due to slow bulk diffusion through the viscous shell for excess mass to be transferred to the core phase. Equilibration timescales are shorter for the condensation of lower-volatility species into semisolid shell; as the volatility increases, re-evaporation becomes significant as desorption is faster for volatile species than bulk diffusion in a semisolid matrix, leading to an increase in equilibration timescale. We also show that the equilibration timescale is longer in an open system relative to a closed system especially for partitioning of miscible species; hence, caution should be exercised when interpreting and extrapolating closed-system chamber experimental results to atmosphere conditions. Our results provide a possible explanation for discrepancies between experimental observations of fast particle–particle mixing and predictions of long mixing timescales in viscous particles and provide useful insights into description and treatment of SOA in aerosol models.
Organic aerosols (OAs) may serve as ice-nucleating particles (INPs), impacting the formation and properties of cirrus clouds when their phase state and viscosity are in the semisolid to glassy range. However, there is a lack of direct parameterization between aerosol viscosity and their ice nucleation capabilities. In this study, we experimentally measured the ice nucleation rate of 2-methyltetrols (2-MT) aerosols, a key component of isoprene-epoxydiol-derived secondary organic aerosols (IEPOX-SOA), at different viscosities. These results demonstrate that the phase state has a significant impact on the ice nucleation abilities of OA under typical cirrus cloud conditions, with the ice nucleation rate increasing by 2 to 3 orders of magnitude when the phase state changes from liquid to semisolid. An innovative parametric model based on classical nucleation theory was developed to directly quantify the impact of viscosity on the heterogeneous nucleation rate. This model accurately represents our laboratory measurement and can be implemented into climate models due to its simple, equation-based form. Based on data collected from the ACRIDICON-CHUVA field campaign, our model predicts that the INP concentration from IEPOX-SOA can reach the magnitude of 1 to tens per liter in the cirrus cloud region impacted by the Amazon rainforest, consistent with recent field observations and estimations. This novel parameterization framework can also be applied in regional and global climate models to further improve representations of cirrus cloud formation and associated climate impacts.
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The gas-particle partitioning and chemical aging of semi-volatile organic aerosol are presented in a newly developed box model scheme, where its effect on the growth, composition, and mixing state of particles is examined. The volatility-basis set (VBS) framework is implemented into the aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves mass and number aerosol concentrations and in multiple mixing-state classes. The new scheme, MATRIX-VBS, has the potential to significantly advance the representation of organic aerosols in Earth system models by improving upon the conventional representation as non-volatile particulate organic matter, often also with an assumed fixed size distribution. We present results from idealized cases representing Beijing, Mexico City, a Finnish forest, and a southeastern US forest, and investigate the evolution of mass concentrations and volatility distributions for organic species across the gas and particle phases, as well as assessing their mixing state among aerosol populations. Emitted semi-volatile primary organic aerosols evaporate almost completely in the intermediate-volatility range, while they remain in the particle phase in the low-volatility range. Their volatility distribution at any point in time depends on the applied emission factors, oxidation by OH radicals, and temperature. We also compare against parallel simulations with the original scheme, which represented only the particulate and non-volatile component of the organic aerosol, examining how differently the condensed-phase organic matter is distributed across the mixing states in the model. The results demonstrate the importance of representing organic aerosol as a semi-volatile aerosol, and explicitly calculating the partitioning of organic species between the gas and particulate phases.
We developed tgBoost a machine learning model to predict glass transition temperature ( T g) of organic species considering their molecular structure and functionality for better predictions of the phase state of secondary organic aerosols.
Abstract Atmospheric aerosols can assume liquid, amorphous semi-solid or glassy, and crystalline phase states. Particle phase state plays a critical role in understanding and predicting aerosol impacts on human health, visibility, cloud formation, and climate. Melting point depression increases with decreasing particle diameter and is predicted by the Gibbs–Thompson relationship. This work reviews existing data on the melting point depression to constrain a simple parameterization of the process. The parameter $$\xi $$ ξ describes the degree to which particle size lowers the melting point and is found to vary between 300 and 1800 K nm for a wide range of particle compositions. The parameterization is used together with existing frameworks for modeling the temperature and RH dependence of viscosity to predict the influence of particle size on the glass transition temperature and viscosity of secondary organic aerosol formed from the oxidation of $$\alpha $$ α -pinene. Literature data are broadly consistent with the predictions. The model predicts a sharp decrease in viscosity for particles less than 100 nm in diameter. It is computationally efficient and suitable for inclusion in models to evaluate the potential influence of the phase change on atmospheric processes. New experimental data of the size-dependence of particle viscosity for atmospheric aerosol mimics are needed to thoroughly validate the predictions.
This work provides a synopsis of aerosol phase function (F (sub 11)) and polarized phase function (F (sub 12)) measurements made by the Polarized Imaging Nephelometer (PINeph) during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Deep Convection Clouds and Chemistry (DC3) field campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that include trace gases, chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PI-Neph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F (sub 11) and minus F (sub 12) divided by F (sub 11) for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification. Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that, indeed, a strong link exists between the angular scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most cases the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85 percent recall. This result both emphasizes the validity of the ancillary data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.
A linear non-diffusive algorithm for advective transport is developed that greatly improves the detail at which aerosols and clouds can be represented in atmospheric models. Linear advection schemes preserve tracer correlations but the most basic linear scheme is rarely used by atmospheric modelers on account of its excessive numerical diffusion. Higher-order schemes are in widespread use, but these present new problems as nonlinear adjustments are required to avoid occurrences of negative concentrations, spurious oscillations, and other non-physical effects. Generally successful at reducing numerical diffusion during the advection of individual tracers, for example, particle number or mass, the higher-order schemes fail to preserve even the simplest of correlations between interrelated tracers. As a result, important attributes of aerosol and cloud populations including radial moments of particle size distributions, molecular precursors related through chemical equilibria, aerosol mixing state, and distribution of cloud phase are poorly represented. We introduce a new transport scheme, minVAR, that is both non-diffusive and preservative of tracer correlations, thereby combining the best features of the basic and higher-order schemes while enabling new features such as the tracking of sub-grid information at arbitrarily fine scales with high computational efficiency.
The interactions of aerosol particles with light and clouds are among the most uncertain aspects of anthropogenic climate forcings. The effects of aerosol particles on climate depend on their optical properties, heterogeneous chemistry, water uptake behavior, and ice nucleation activity. These properties in turn depend on aerosol physics and chemistry including composition, size, shape, internal structure (morphology), and phase state. The greatest numbers of particles are found at small, submicrometer sizes, and the properties of aerosol particles can differ on the nanoscale compared with measurements of bulk materials. As a result, our focus has been on characterizing the phase transitions of aerosol particles in both supermicrometer and submicrometer particles. The phase transition of particular interest for us has been liquid–liquid phase separation (LLPS), which occurs when components of a solution phase separate due to a difference in solubilities. For example, organic compounds can have limited solubility in salt solutions especially as the water content decreases, increasing the concentration of the salt solution, and causing phase separation between organic-rich and inorganic-rich phases. To characterize the systems of interest, we primarily use optical microscopy for supermicrometer particles and cryogenic-transmission microscopy for submicrometer particles. This Account details our main results to date for the phase transitions of supermicrometer particles and the morphology of submicrometer aerosol. Herein, we have found that the relative humidity (RH) at which LLPS occurs (separation RH; SRH) is highly sensitive to the composition of the particles. For supermicrometer particles, SRH decreases as the pH is lowered to atmospherically relevant values. SRH also decreases when non-phase-separating organic compounds are added to the particles. For submicrometer particles, a size dependence of morphology is observed in systems that undergo LLPS in supermicrometer particles. In the limit of slow drying rates, particles <30 nm are homogeneous and larger particles are phase-separated. This size dependence of aerosol morphology arises because small particles cannot overcome the activation barrier needed to form a new phase when phase separation occurs by a nucleation and growth mechanism. Additionally, the inhibition of LLPS in small particles is observed for mixtures of ammonium sulfate with single organic compounds as well as complex organics like α-pinene secondary organic matter. The morphology of particles affects activation diameters for the formation of cloud condensation nuclei. These results more generally have implications for aerosol properties that affect the climate system. In addition, LLPS is also widely studied in materials and biological chemistry, and our results could potentially translate to implications for these fields.
Gas-particle partitioning is critical for the evolution of secondary organic aerosols (SOA) in the atmosphere. SOA particles evaporate more slowly than expected at nearly size-independent rates, but the underlying mechanism remains controversial. Here, in this study, we apply kinetic multilayer modeling to simulate evaporation of α-pinene SOA, demonstrating that surface crust formation, emerging from accumulation of low-volatility compounds at the particle surface, leads to slow evaporation and reduced size dependence of the evaporation rate. While evaporation induced by decomposition of oligomers would naturally lead to size-independent evaporation rates, we observe and simulate nearly size-independent slow evaporation of polyethylene glycol mixture particles containing polymeric species that do not decompose, confirming the relevance of composition-dependent diffusivity for size-independent, slow evaporation. Slow evaporation of limonene SOA was also observed in environmental chamber experiments, and model simulations demonstrate strong surface crust formation with bulk diffusivity being depressed by up to 5 orders of magnitude compared to the inner bulk. We present experimental evidence using a surface-based mass spectrometry technique that shows that the particle surface becomes enriched in high molecular weight compounds upon evaporation of monomers. Our findings imply that viscous surface crusts may also limit the growth and chemical transformation of SOA particles, influencing their impacts on air quality and climate.