Identification of Polymers as Major Components of Atmospheric Organic Aerosols

Kalberer, Markus; Paulsen, D.; Sax, M.; Steinbacher, Martin; Dommen, Josef; Prévôt, A. S. H.; Fisseha, R.; Weingärtner, E.; Frankevich, Vladimir; Zenobi, Renato; Baltensperger, Urs

doi:10.1126/science.1092185

Cited by 1,024 publications

(1,147 citation statements)

References 27 publications

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“…35 As a result, in addition to van der Waals interactions, it should ideally form hydrogen bonds with solutes which undergo such a type of interaction, particularly via the surface chains. Secondary organic aerosol (SOA) polymers originated from oxidation of aromatic species could potentially undergo similar interactions, based on the molecular structures proposed by Kalberer et al 34 Holmgren et al 48 proposed several polymer− air ppLFER models including those for cellulose-based materials and polyurethane. A urethane unit has a number of sites which could participate in H-bonding; therefore, one could expect polyurethane to simulate molecular interactions similar to those anticipated for cellulose and SOA polymers.…”

Section: Environmental Science and Technologymentioning

confidence: 99%

Evaluation of a Conceptual Model for Gas-Particle Partitioning of Polycyclic Aromatic Hydrocarbons Using Polyparameter Linear Free Energy Relationships

Shahpoury

Lammel

Albinet

et al. 2016

Environ. Sci. Technol.

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ABSTRACT:A model for gas-particle partitioning of polycyclic aromatic hydrocarbons (PAHs) was evaluated using polyparameter linear free energy relationships (ppLFERs) following a multiphase aerosol scenario. The model differentiates between various organic (i.e., liquid water-soluble (WS)/organic soluble (OS) organic matter (OM), and solid/semisolid organic polymers) and inorganic phases of the particulate matter (PM). Dimethyl sulfoxide and polyurethane were assigned as surrogates to simulate absorption into the abovementioned organic phases, respectively, whereas soot, ammonium sulfate, and ammonium chloride simulated adsorption processes onto PM. The model was tested for gas and PM samples collected from urban and nonurban sites in Europe and the Mediterranean, and the output was compared with those calculated using single-parameter linear free energy relationship (spLFER) models, namely JungePankow, Finizio, and Dachs-Eisenreich. The ppLFER model on average predicted 96 ± 3% of the observed partitioning constants for semivolatile PAHs, fluoranthene, and pyrene, within 1 order of magnitude accuracy with root-mean-square errors (RMSE) of 0.35−0.59 across the sites. This was a substantial improvement compared to Finizio and Dachs-Eisenreich models (37 ± 17 and 46 ± 18% and RMSE of 1.03−1.40 and 0.94−1.36, respectively). The JungePankow model performed better among spLFERs but at the same time showed an overall tendency for overestimating the partitioning constants. The ppLFER model demonstrated the best overall performance without indicating a substantial intersite variability. The ppLFER analysis with the parametrization applied in this study suggests that the absorption into WSOSOM could dominate the overall partitioning process, while adsorption onto salts could be neglected.

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Section: Environmental Science and Technologymentioning

confidence: 99%

Evaluation of a Conceptual Model for Gas-Particle Partitioning of Polycyclic Aromatic Hydrocarbons Using Polyparameter Linear Free Energy Relationships

Shahpoury

Lammel

Albinet

et al. 2016

Environ. Sci. Technol.

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“…Aromatic peroxy radicals (RO 2 ) react with HO 2 under low NO x conditions to form non-volatile SOA while they reacted with NO under high NO x conditions to form semi-volatile SOA. In addition, the Base model treats the acid enhancement of isoprene SOA (Surratt et al, 2007) and irreversible particle-phase oligomerization (Kalberer et al, 2004), which converts semi-volatile condensed-phase species into non-volatile species. We do not consider SOA formation from IVOCs or via aqueous-phase processing.…”

Section: Base Soa Modelmentioning

confidence: 99%

“…The UCD/CIT air quality model is a regional chemical transport model (CTM) (Kleeman and Cass, 2001) that has been extensively used for predicting regional aerosol concentrations, including SOA (Chen et al, 2010;Kleeman et al, 2007). The UCD/CIT model simulates the emissions, transport, gas-phase chemistry, aerosol physics and chemistry (dynamic gas/particle partitioning, coagulation, thermodynamics and deposition) in the lower troposphere.…”

Section: -D Air Quality Modelmentioning

confidence: 99%

Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model

et al. 2015

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Abstract. Multi-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multigenerational SOA formation. In this work, we integrated the statistical oxidation model (SOM) into SAPRC-11 to simulate the multi-generational oxidation and gas/particle partitioning of SOA in the regional UCD/CIT (University of California, Davis/California Institute of Technology) air quality model. In the SOM, evolution of organic vapors by reaction with the hydroxyl radical is defined by (1) the number of oxygen atoms added per reaction, (2) the decrease in volatility upon addition of an oxygen atom and (3) the probability that a given reaction leads to fragmentation of the organic molecule. These SOM parameter values were fit to laboratory smog chamber data for each precursor/compound class. SOM was installed in the UCD/CIT model, which simulated air quality over 2-week periods in the South Coast Air Basin of California and the eastern United States. For the regions and episodes tested, the two-product SOA model and SOM produce similar SOA concentrations but a modestly different SOA chemical composition. Predictions of the oxygen-tocarbon ratio qualitatively agree with those measured globally using aerosol mass spectrometers. Overall, the implementation of the SOM in a 3-D model provides a comprehensive framework to simulate the atmospheric evolution of organic aerosol.

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“…Such difficulties likely arise from complexity in the sources (including both primary combustion emissions, POA, and secondary production SOA), composition, and chemistry of OA. While traditionally SOA has been thought to consist of products from a few classes of compounds (terpenes and aromatics), recent studies have identified both additional precursors [Kroll et al, 2005;Lim and Ziemann, 2009;Robinson et al, 2007;Volkamer et al, 2009] and additional formation pathways [Carlton et al, 2007;Kalberer et al, 2004]. Once formed in the atmosphere, the pool of OA remains dynamic, through both reversible partitioning and continued atmospheric oxidation.…”

Section: Introductionmentioning

confidence: 99%

A simplified description of the evolution of organic aerosol composition in the atmosphere

Heald

Kroll

Jimenez

et al. 2010

Geophysical Research Letters

528

588

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Organic aerosol (OA) in the atmosphere consists of a multitude of organic species which are either directly emitted or the products of a variety of chemical reactions. This complexity challenges our ability to explicitly characterize the chemical composition of these particles. We find that the bulk composition of OA from a variety of environments (laboratory and field) occupies a narrow range in the space of a Van Krevelen diagram (H:C versus O:C), characterized by a slope of ∼−1. The data show that atmospheric aging, involving processes such as volatilization, oxidation, mixing of air masses or condensation of further products, is consistent with movement along this line, producing a more oxidized aerosol. This finding has implications for our understanding of the evolution of atmospheric OA and representation of these processes in models.

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Identification of Polymers as Major Components of Atmospheric Organic Aerosols

Cited by 1,024 publications

References 27 publications

Evaluation of a Conceptual Model for Gas-Particle Partitioning of Polycyclic Aromatic Hydrocarbons Using Polyparameter Linear Free Energy Relationships

Evaluation of a Conceptual Model for Gas-Particle Partitioning of Polycyclic Aromatic Hydrocarbons Using Polyparameter Linear Free Energy Relationships

Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model

A simplified description of the evolution of organic aerosol composition in the atmosphere

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