scholarly journals Modeling kinetic partitioning of secondary organic aerosol and size distribution dynamics: representing effects of volatility, phase state, and particle-phase reaction

2014 ◽  
Vol 14 (10) ◽  
pp. 5153-5181 ◽  
Author(s):  
R. A. Zaveri ◽  
R. C. Easter ◽  
J. E. Shilling ◽  
J. H. Seinfeld
Keyword(s):  
Size Distribution ◽  
Rate Constant ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Diffusion Reaction ◽  
Aerosol Size Distribution ◽  
Particle Phase ◽  
Distribution Dynamics ◽  
Bulk Diffusivity ◽  
New Framework

Abstract. This paper describes and evaluates a new framework for modeling kinetic gas-particle partitioning of secondary organic aerosol (SOA) that takes into account diffusion and chemical reaction within the particle phase. The framework uses a combination of (a) an analytical quasi-steady-state treatment for the diffusion–reaction process within the particle phase for fast-reacting organic solutes, and (b) a two-film theory approach for slow- and nonreacting solutes. The framework is amenable for use in regional and global atmospheric models, although it currently awaits specification of the various gas- and particle-phase chemistries and the related physicochemical properties that are important for SOA formation. Here, the new framework is implemented in the computationally efficient Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) to investigate the competitive growth dynamics of the Aitken and accumulation mode particles. Results show that the timescale of SOA partitioning and the associated size distribution dynamics depend on the complex interplay between organic solute volatility, particle-phase bulk diffusivity, and particle-phase reactivity (as exemplified by a pseudo-first-order reaction rate constant), each of which can vary over several orders of magnitude. In general, the timescale of SOA partitioning increases with increase in volatility and decrease in bulk diffusivity and rate constant. At the same time, the shape of the aerosol size distribution displays appreciable narrowing with decrease in volatility and bulk diffusivity and increase in rate constant. A proper representation of these physicochemical processes and parameters is needed in the next generation models to reliably predict not only the total SOA mass, but also its composition- and number-diameter distributions, all of which together determine the overall optical and cloud-nucleating properties.

scholarly journals Modeling kinetic partitioning of secondary organic aerosol and size distribution dynamics: representing effects of volatility, phase state, and particle-phase reaction

2013 ◽  
Vol 13 (11) ◽  
pp. 28631-28694 ◽  
Author(s):  
R. A. Zaveri ◽  
R. C. Easter ◽  
J. E. Shilling ◽  
J. H. Seinfeld
Keyword(s):  
Size Distribution ◽  
Rate Constant ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Diffusion Reaction ◽  
Aerosol Size Distribution ◽  
Particle Phase ◽  
Distribution Dynamics ◽  
Bulk Diffusivity ◽  
New Formulation

Abstract. This paper describes and evaluates a new formulation for modeling kinetic gas-particle partitioning of secondary organic aerosol (SOA) that takes into account diffusion and chemical reaction within the particle phase. The new formulation uses a combination of: (a) an analytical quasi-steady-state treatment for the diffusion-reaction process within the particle phase for fast-reacting organic solutes, and (b) a two-film theory approach for slow- and non-reacting solutes. The formulation is amenable for use in regional and global atmospheric models, although it currently awaits specification of the actual species and particle-phase reactions that are important for SOA formation. Here, the formulation is applied within the framework of the computationally efficient Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) to investigate the competitive growth dynamics of the Aitken and accumulation mode particles. Results show that the timescale of SOA partitioning and the associated size distribution dynamics depend on the complex interplay between organic solute volatility, particle-phase bulk diffusivity, and particle-phase reactivity (as exemplified by a pseudo-first-order reaction rate constant), each of which can vary over several orders of magnitude. In general, the timescale of SOA partitioning increases with increase in volatility and decrease in bulk diffusivity and rate constant. At the same time, the shape of the aerosol size distribution displays appreciable narrowing with decrease in volatility and bulk diffusivity and increase in rate constant. A proper representation of these physicochemical processes and parameters are needed in the next generation models to reliably predict not only the total SOA mass, but also its composition and number size distribution, all of which together determine its overall optical and cloud-nucleating properties.

scholarly journals Growth Kinetics and Size Distribution Dynamics of Viscous Secondary Organic Aerosol

2018 ◽  
Vol 52 (3) ◽  
pp. 1191-1199 ◽  
Author(s):  
Rahul A. Zaveri ◽  
John E. Shilling ◽  
Alla Zelenyuk ◽  
Jiumeng Liu ◽  
David M. Bell ◽  
...  
Keyword(s):  
Size Distribution ◽  
Growth Kinetics ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Distribution Dynamics

scholarly journals Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol

2021 ◽  
Vol 55 (3) ◽  
pp. 1466-1476
Author(s):  
Yicong He ◽  
Ali Akherati ◽  
Theodora Nah ◽  
Nga L. Ng ◽  
Lauren A. Garofalo ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Phase State ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Distribution Dynamics

scholarly journals Size distribution dynamics reveal particle-phase chemistry in organic aerosol formation

2013 ◽  
Vol 110 (29) ◽  
pp. 11746-11750 ◽  
Author(s):  
M. Shiraiwa ◽  
L. D. Yee ◽  
K. A. Schilling ◽  
C. L. Loza ◽  
J. S. Craven ◽  
...  
Keyword(s):  
Size Distribution ◽  
Organic Aerosol ◽  
Particle Phase ◽  
Aerosol Formation ◽  
Distribution Dynamics ◽  
Phase Chemistry

scholarly journals Evaluation of Anthropogenic Secondary Organic Aerosol Tracers

2016 ◽  
Author(s):  
Ibrahim M. Al-Naiema ◽  
Elizabeth A. Stone
Keyword(s):  
Phthalic Acid ◽  
Secondary Organic Aerosol ◽  
Dicarboxylic Acids ◽  
Organic Aerosol ◽  
Secondary Source ◽  
Particle Phase ◽  
Water Sensitivity ◽  
Nitrobenzyl Alcohol ◽  
Ambient Concentrations ◽  
Highly Correlated

Abstract. Products of secondary organic aerosol (SOA) from aromatic volatile organic compounds (VOC) – 2,3-dihydroxy-4-oxopentanoic acid, dicarboxylic acids, nitromonoaromatics, and furandiones – were evaluated for their potential to serve as anthropogenic SOA tracers with respect to their 1) ambient concentrations and detectability in PM2.5 in Iowa City, IA, USA, 2) gas-particle partitioning behaviour, and 3) source specificity by way of correlations with primary and secondary source tracers and literature review. A widely used tracer for toluene-derived SOA, 2,3-dihydroxy-4-oxopentanoic acid was only detected in the particle phase (Fp = 1) at low, but consistently measureable ambient concentrations (averaging 0.3 ng m−3). Four aromatic dicarboxylic acids were detected at relatively higher concentrations (9.1–34.5 ng m−3), of which phthalic acid was the most abundant. Phthalic acid had a low particle-phase fraction (Fp = 0.26) likely due to quantitation interferences from phthalic anhydride, while 4-methylphthalic acid was predominantly in the particle phase (Fp = 0.82). Phthalic acid and 4-methyl phthalic acid were both highly correlated with 2,3-dihydroxy-4-oxopentanoic acid (rs = 0.73, p = 0.003; rs = 0.80, p < 0.001, respectively), suggesting that they were derived from aromatic VOC. Isophthalic and terephthalic acids, however, were detected only in the particle phase (Fp = 1) and correlations suggested association with primary emission sources. Nitromonoaromatics were dominated by particle-phase concentrations of 4-nitrocatechol (1.6 ng m−3) and 4-methyl-5-nitrocatechol (1.6 ng m−3) that were associated with biomass burning. Meanwhile, 4-hydroxy-3-nitrobenzyl alcohol was detected in a lower concentration (0.06 ng m−3) in the particle phase only (Fp = 1), and is known as a product of toluene photooxidation. Furandiones in the atmosphere have only been attributed to the photooxidation of aromatic hydrocarbons, however the substantial partitioning toward the gas phase (Fp ≤ 0.16) and their water sensitivity limit their application as tracers. The outcome of this study is the demonstration that 2,3-dihydroxy-4-oxopentanoic acid, phthalic acid, 4-methylphthalic acid, and 4-hydroxy-3-nitrobenzyl alcohol are good candidates for tracing SOA from aromatic VOC.

scholarly journals Supplementary material to "Particle-phase processing of α-pinene NO<sub>3</sub> secondary organic aerosol in the dark"

2021 ◽  
Author(s):  
David M. Bell ◽  
Cheng Wu ◽  
Amelie Bertrand ◽  
Emelie Graham ◽  
Janne Schoonbaert ◽  
...  
Keyword(s):  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Particle Phase ◽  
Supplementary Material

scholarly journals Arctic marine secondary organic aerosol contributes significantly to summertime particle size distributions in the Canadian Arctic Archipelago

2019 ◽  
Vol 19 (5) ◽  
pp. 2787-2812 ◽  
Author(s):  
Betty Croft ◽  
Randall V. Martin ◽  
W. Richard Leaitch ◽  
Julia Burkart ◽  
Rachel Y.-W. Chang ◽  
...  
Keyword(s):  
Particle Size ◽  
Size Distribution ◽  
Secondary Organic Aerosol ◽  
Canadian Arctic ◽  
Particle Growth ◽  
Organic Aerosol ◽  
The Arctic ◽  
Canadian Arctic Archipelago ◽  
Size Distributions ◽  
Fractional Error

Abstract. Summertime Arctic aerosol size distributions are strongly controlled by natural regional emissions. Within this context, we use a chemical transport model with size-resolved aerosol microphysics (GEOS-Chem-TOMAS) to interpret measurements of aerosol size distributions from the Canadian Arctic Archipelago during the summer of 2016, as part of the “NETwork on Climate and Aerosols: Addressing key uncertainties in Remote Canadian Environments” (NETCARE) project. Our simulations suggest that condensation of secondary organic aerosol (SOA) from precursor vapors emitted in the Arctic and near Arctic marine (ice-free seawater) regions plays a key role in particle growth events that shape the aerosol size distributions observed at Alert (82.5∘ N, 62.3∘ W), Eureka (80.1∘ N, 86.4∘ W), and along a NETCARE ship track within the Archipelago. We refer to this SOA as Arctic marine SOA (AMSOA) to reflect the Arctic marine-based and likely biogenic sources for the precursors of the condensing organic vapors. AMSOA from a simulated flux (500 µgm-2day-1, north of 50∘ N) of precursor vapors (with an assumed yield of unity) reduces the summertime particle size distribution model–observation mean fractional error 2- to 4-fold, relative to a simulation without this AMSOA. Particle growth due to the condensable organic vapor flux contributes strongly (30 %–50 %) to the simulated summertime-mean number of particles with diameters larger than 20 nm in the study region. This growth couples with ternary particle nucleation (sulfuric acid, ammonia, and water vapor) and biogenic sulfate condensation to account for more than 90 % of this simulated particle number, which represents a strong biogenic influence. The simulated fit to summertime size-distribution observations is further improved at Eureka and for the ship track by scaling up the nucleation rate by a factor of 100 to account for other particle precursors such as gas-phase iodine and/or amines and/or fragmenting primary particles that could be missing from our simulations. Additionally, the fits to the observed size distributions and total aerosol number concentrations for particles larger than 4 nm improve with the assumption that the AMSOA contains semi-volatile species: the model–observation mean fractional error is reduced 2- to 3-fold for the Alert and ship track size distributions. AMSOA accounts for about half of the simulated particle surface area and volume distributions in the summertime Canadian Arctic Archipelago, with climate-relevant simulated summertime pan-Arctic-mean top-of-the-atmosphere aerosol direct (−0.04 W m−2) and cloud-albedo indirect (−0.4 W m−2) radiative effects, which due to uncertainties are viewed as an order of magnitude estimate. Future work should focus on further understanding summertime Arctic sources of AMSOA.

scholarly journals Evaluation of anthropogenic secondary organic aerosol tracers from aromatic hydrocarbons

2017 ◽  
Vol 17 (3) ◽  
pp. 2053-2065 ◽  
Author(s):  
Ibrahim M. Al-Naiema ◽  
Elizabeth A. Stone
Keyword(s):  
Aromatic Hydrocarbons ◽  
Phthalic Acid ◽  
Secondary Organic Aerosol ◽  
Dicarboxylic Acids ◽  
Organic Aerosol ◽  
Secondary Source ◽  
Particle Phase ◽  
Water Sensitivity ◽  
Nitrobenzyl Alcohol ◽  
Ambient Concentrations

Abstract. Products of secondary organic aerosol (SOA) from aromatic volatile organic compounds (VOCs) – 2,3-dihydroxy-4-oxopentanoic acid, dicarboxylic acids, nitromonoaromatics, and furandiones – were evaluated for their potential to serve as anthropogenic SOA tracers with respect to their (1) ambient concentrations and detectability in PM2.5 in Iowa City, IA, USA; (2) gas–particle partitioning behaviour; and (3) source specificity by way of correlations with primary and secondary source tracers and literature review. A widely used tracer for toluene-derived SOA, 2,3-dihydroxy-4-oxopentanoic acid was only detected in the particle phase (Fp = 1) at low but consistently measurable ambient concentrations (averaging 0.3 ng m−3). Four aromatic dicarboxylic acids were detected at relatively higher concentrations (9.1–34.5 ng m−3), of which phthalic acid was the most abundant. Phthalic acid had a low particle-phase fraction (Fp =  0.26) likely due to quantitation interferences from phthalic anhydride, while 4-methylphthalic acid was predominantly in the particle phase (Fp = 0.82). Phthalic acid and 4-methylphthalic acid were both highly correlated with 2,3-dihydroxy-4-oxopentanoic acid (rs = 0.73, p = 0.003; rs = 0.80, p < 0.001, respectively), suggesting that they were derived from aromatic VOCs. Isophthalic and terephthalic acids, however, were detected only in the particle phase (Fp = 1), and correlations suggested association with primary emission sources. Nitromonoaromatics were dominated by particle-phase concentrations of 4-nitrocatechol (1.6 ng m−3) and 4-methyl-5-nitrocatechol (1.6 ng m−3) that were associated with biomass burning. Meanwhile, 4-hydroxy-3-nitrobenzyl alcohol was detected in a lower concentration (0.06 ng m−3) in the particle phase only (Fp = 1) and is known as a product of toluene photooxidation. Furandiones in the atmosphere have only been attributed to the photooxidation of aromatic hydrocarbons; however the substantial partitioning toward the gas phase (Fp  ≤  0.16) and their water sensitivity limit their application as tracers. The outcome of this study is the demonstration that 2,3-dihydroxy-4-oxopentanoic acid, phthalic acid, 4-methylphthalic acid, and 4-hydroxy-3-nitrobenzyl alcohol are good candidates for tracing SOA from aromatic VOCs.

scholarly journals Mapping gas-phase organic reactivity and concomitant secondary organic aerosol formation: chemometric dimension reduction techniques for the deconvolution of complex atmospheric data sets

2015 ◽  
Vol 15 (14) ◽  
pp. 8077-8100 ◽  
Author(s):  
K. P. Wyche ◽  
P. S. Monks ◽  
K. L. Smallbone ◽  
J. F. Hamilton ◽  
M. R. Alfarra ◽  
...  
Keyword(s):  
Phase Composition ◽  
Dimension Reduction ◽  
Gas Phase ◽  
Secondary Organic Aerosol ◽  
Ambient Air ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Particle Phase ◽  
Aerosol Formation ◽  
Holistic View

Abstract. Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i.e. toluene) oxidation and "more realistic" plant mesocosm systems, demonstrates that such an ensemble of chemometric mapping has the potential to be used for the classification of more complex spectra of unknown origin. More specifically, the addition of mesocosm data from fig and birch tree experiments shows that isoprene and monoterpene emitting sources, respectively, can be mapped onto the statistical model structure and their positional vectors can provide insight into their biological sources and controlling oxidative chemistry. The potential to extend the methodology to the analysis of ambient air is discussed using results obtained from a zero-dimensional box model incorporating mechanistic data obtained from the Master Chemical Mechanism (MCMv3.2). Such an extension to analysing ambient air would prove a powerful asset in assisting with the identification of SOA sources and the elucidation of the underlying chemical mechanisms involved.

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