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Environmental Modeling
Parameterized yields of semi-volatile products from isoprene oxidation under different NOx levels: impacts of chemical aging and wall-loss of reactive gases Li Xing, ManishKumar Shrivastava, T. -M. Fu, Pontus Roldin, Yun Qian, Lu Xu, Nga Lee Ng, John E. Shilling, Alla Zelenyuk, and Christopher David Cappa Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00373 • Publication Date (Web): 20 Jul 2018 Downloaded from http://pubs.acs.org on July 21, 2018
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Parameterized yields of semi-volatile products from
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isoprene oxidation under different NOx levels:
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impacts of chemical aging and wall-loss of reactive
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gases
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Li Xing,†,‡,§ Manish Shrivastava,*, ‡ Tzung-May Fu,*, † Pontus Roldin,|| Yun Qian, ‡ Lu Xu,⊥,# Nga
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L. Ng,⊥,▽ John Shilling,‡ Alla Zelenyuk,‡ and Christopher D. Cappa○
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†
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Atmosphere Studies, School of Physics, Peking University, Beijing, 100871, China
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‡
Pacific Northwest National Laboratory, Richland, Washington, 99352, USA
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§
Key Lab of Aerosol Chemistry & Physics, State Key Laboratory of Loess and Quaternary
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Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, 710061, China
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||
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⊥
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Department of Atmospheric and Oceanic Sciences and Laboratory for Climate and Ocean-
Division of Nuclear Physics, Lund University, P.O. Box 118, 221 00 Lund, Sweden School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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#
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California 91125, USA
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena,
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▽
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30332, USA
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○
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California, 95616, USA
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* Corresponding authors: M. Shrivastava (
[email protected]) and T.-M. Fu
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(
[email protected])
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia
Department of Civil and Environmental Engineering, University of California, Davis,
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ABSTRACT:
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We developed a parameterizable box model to empirically derive the yields of semi-volatile
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products from VOC oxidation using chamber measurements, while explicitly accounting for the
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multigenerational chemical aging processes (such as the gas-phase fragmentation and
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functionalization and aerosol-phase oligomerization and photolysis) under different NOx levels
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and the loss of particles and gases to chamber walls. Using the oxidation of isoprene as an
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example, we showed that the assumptions regarding the NOx-sensitive, multigenerational aging
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processes of VOC oxidation products have large impacts on the parameterized product yields
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and SOA formation. We derived sets of semi-volatile product yields from isoprene oxidation
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under different NOx levels. However, we stress that these product yields must be used in
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conjunction with the corresponding multigenerational aging schemes in chemical transport
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models. As more mechanistic insights regarding SOA formation from VOC oxidation emerge,
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our box model can be expanded to include more explicit chemical aging processes and help
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ultimately bridge the gap between the process-based understanding of SOA formation from VOC
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oxidation and the bulk-yield parameterizations used in chemical transport models.
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Abstract Art:
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INTRODUCTION
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Many volatile organic compounds (VOCs) oxidize in the atmosphere to produce lower
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volatility products that form secondary organic aerosols (SOA).1-4 Laboratory studies have
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shown that the oxidation pathways of VOCs are sensitive to ambient NOx levels, and that the
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molecular complexity and aging of VOC oxidation products have large impacts on the yields and
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formation timescales of SOA.1-3,5,6 Many current chemical transport models simulated the SOA
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formation from VOC oxidation using parameterized yields derived from simple empirical
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theories.7,8 At the same time, an increasing number of those same models are implementing
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complex chemical aging processes based on new mechanistic insights on SOA formation gained
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from laboratory studies.9-11 This discrepancy between the implementation of detailed chemical
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mechanism and the use of simplified parameterized yields in models have so far been overlooked.
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Here, we presented a new way to parameterize the product yields from VOC oxidation using
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chamber measurements, taking isoprene oxidation as a specific example. We showed that the
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explicit accounting of chemical aging and chamber wall-loss processes changed the
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parameterized yields and volatility distribution of products, which will in turn affect the SOA
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simulation in chemical transport models.
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The volatility basis set (VBS) framework, which expands on the two-product model,12 is a
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widely used empirical approach for modeling SOA formation.13-16 Under the VBS framework, a
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VOC precursor oxidizes to produce semi-volatile and intermediate volatility (SV/IV) products,
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which are lumped into n (typically between 4 and 8) bins of effective volatility (represented by
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bins of effective saturation vapor concentration, C*i, i = 1 to n).8,9,13 These SV/IV products then
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partition into the aerosol phase according to their respective volatility. To date, most studies
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parameterized the effective stoichiometric mass yields (αi) of the SV/IV products by fitting to
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smog chamber measurements using Eq (1),7,8
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≡
OA
ROG
= ∑ ∙
∗
Eq (1)
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where ξ was the aerosol mass fraction (AMF), which was the bulk yield of SOA mass from a
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reacted VOC precursor measured in the chamber. ∆ROG was the reacted VOC precursor mass,
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and ∆COA was the total SOA mass formed (adjusted for particle wall-loss). Ci* was the effective
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saturation vapor concentration of products in the volatility bin i, and COA was the total SOA
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mass. Typically, a series of experiments were performed by injecting different initial amounts of
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the VOC precursor into a chamber to be oxidized, and the values of ξ were calculated using the
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measured time series of the SOA mass and the reacted VOC mass. The product yields in
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different volatility bins (αi, i = 1 to n) were then determined by fitting to the resulting series of ξ
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values.8,9,17
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A frequently overlooked fact is that the yields empirically obtained from fitting Eq (1) were
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theory-specific. It was assumed that (1) all wall-losses of particles during the measurement were
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accounted for prior to the fitting; (2) no SV/IV gases were lost to the walls; (3) the volatility of
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SV/IV products can be lumped into one single, static set of VBS products, which allowed no
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evolution of their volatility by chemical aging; and (4) the gas/aerosol partitioning of the SV/IV
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products followed the absorptive partitioning theory. Recent laboratory results have shown that
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these assumptions pertaining to Eq (1) may not apply.1,18-20 For example, SV/IV gases might be
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lost to chamber walls during the experiments, leading to a factor of 2 to 10 underestimation of
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the product yields, especially when the seed-to-chamber surface area ratio was relatively low,21-23
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although SOA mass yields may not be affected by vapor wall-loss if the SOA formation was
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governed by fast quasi-equilibrium growth on seed particles.24
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More importantly, the product yields parameterized from Eq (1) were based only on the total
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SOA mass formed, with little relevance to the changes of volatility distribution due to aging
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either within or beyond the chamber experiment timescale (typically a few hours). In reality, the
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SV/IV products from VOC oxidation undergo mutigenerational aging processes that were highly
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sensitive to NOx, within the timescale of the chamber experiments and also beyond,1,19 leading to
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significant changes in volatility and thus SOA yields. For example, under low-NOx (HO2-
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dominant) conditions, chamber experiments of isoprene oxidation showed that SOA mass began
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to decline once all isoprene was consumed.1,5 This decline of SOA mass may be due to the
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photolysis of hydroperoxides in the aerosol phase, or the evaporation of SOA mass once gas-
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phase compounds were reacted away.5,6 At the same time, the mean SOA oxidation state
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(represented by 2O/C-H/C)25 continued to increase during an 18-hour experiment under low-NOx
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conditions1, indicating the formation of highly oxidized (and potentially less volatile) molecules
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containing one or more peroxy, hydroxyl, or carbonyl function groups.1,26-28 On the other hand,
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in chamber experiments under high-NOx conditions, SOA mass continued to increase even after
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all the isoprene has reacted. The mean oxidation state of SOA was higher than that of low-NOx
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experiment and remained nearly constant during an 18-hour experiment under high-NOx
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conditions.1
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Several model studies have tried to incorporate these new mechanistic insights gained from
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chamber experiments to improve the simple VBS n-product scheme.15,16,23,29 One way to do this
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was to allow the generation-one VBS products to further oxidize and undergo
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functionalization/fragmentation at assumed branching ratios.15,16 This approach allowed the
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formation of higher-generation oxidation products with evolving volatility profiles.15,29 In so
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doing, the great complexity of the multigenerational aging of thousands of oxidation products
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was reduced and represented with a small set of lumped VBS products. To date, models using
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such VBS-plus-aging schemes have used products yields empirically obtained from Eq (1) and
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added subsequent multigenerational aging processes.15,16 However, if multigenerational aging
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was not included during the parameterization of product yields, it could bias the product yields
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that serve as initial concentrations for subsequent chemistry. Consequently, there is strong
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potential for the VBS-plus-aging schemes to overestimate SOA.29,30
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In this study, we constructed a box model that included multigenerational chemistry of
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isoprene oxidation and the losses of gas and particles to chamber walls. We then ran the box
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model with different chemical aging scenarios to fit the measured time series of SOA mass
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concentrations from chamber experiments under different NOx level. In this way, we investigate
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the effects of chemical aging and gas wall losses on the parameterized yields and SOA formation
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from isoprene.
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METHODOLOGY
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Chamber experiment results from Xu et al.1 We used the time series of SOA mass
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concentrations in the isoprene oxidation experiments by Xu et al.1, which were conducted in the
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Pacific Northwest National Laboratory (PNNL) dual 10.6 m3 Teflon environmental chambers
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with different initial concentrations of isoprene and NOx. The chambers were flushed with pure
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air prior to each experiment and no seed particles were used. UV lamps initiated the
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photochemical reactions. A proton transfer reaction mass spectrometer (PTR-MS) measured the
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concentrations of isoprene and two of its major oxidation products, methacrolein (MACR) and
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methyl vinyl ketone (MVK). A scanning mobility particle sizer (SMPS) measured the aerosol
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size distribution between 14.1 and 710.5 nm every five minutes. SOA mass concentrations were
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calculated from the aerosol volume concentrations measured by the SMPS, assuming particle
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densities of 1.3 g cm-3 (experiment 2) and 1.4 g cm-3 (experiments 6 and 8). We analyzed results
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from three experiments with different initial NO/isoprene ratios: ~0, 3.0, and 7.3 (experiments 2,
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6, and 8 in Xu et al.1) to examine the impact of NOx. In experiment 2, the NOx concentration was
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below the detection limit (1 ppb) throughout the experiment, such that organic peroxy radicals
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(RO2) mainly reacted with HO2; this was referred to as an “HO2-dominant” experiment. In
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experiments 6 and 8, NO was injected into the chambers and RO2 radicals may react with HO2,
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NO, and NO2. We referred to experiments 6 and 8 as “intermediate-NOx mixed” and “high-NOx
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mixed” experiments, respectively. Measurements from the other five experiments in Xu et al.1
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were used for validation (supporting information).
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Box model for SOA formation from isoprene oxidation. We constructed a parameterizable
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box model to simulate the oxidation of isoprene and the subsequent multigenerational chemistry
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of the gas and aerosol products. Our box model was built on the framework of the Model for
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Simulating Aerosol Interactions and Chemistry (MOSAIC),31 which was a discretized-size-bin
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model originally developed to describe the chemical and microphysical evolution of inorganic
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aerosols. Here we included a multigenerational aging scheme for isoprene oxidation using the
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modified VBS aging scheme developed by Shrivastava et al.15 Fig. 1 and Table S1 show the gas-
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and aerosol-phase reactions and gas-particle mass transfer pathways in the model. Isoprene
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reacts with OH (reaction R1, rate constant k1=1.0×10-10 cm3 molecule-1 s-1)32 to produce
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generation-one semi-volatile gas products (G1,i, i=1 to 4) in four effective saturation vapor
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concentration bins (C*i, i=1 to 4): 0.1, 1, 10, and 100 µg m-3 at yields αi (i=1 to 4), respectively.
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Some intermediate-volatility products with saturation vapor concentrations between 103-105 µg
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m-3 may potentially oxidize to form SOA.33 However, the maximum SOA concentration
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measured during the experiments by Xu et al.1 was
