Influence of Functional Groups on Organic Aerosol Cloud Condensation Nucleus Activity

Abstract

Organic aerosols in the atmosphere are composed of a wide variety of species, reflecting the multitude of sources and growth processes of these particles. Especially challenging is predicting how these particles act as cloud condensation nuclei (CCN). Previous studies have characterized the CCN efficiency for organic compounds in terms of a hygroscopicity parameter, κ. Here we extend these studies by systematically testing the influence of the number and location of molecular functional groups on the hygroscopicity of organic aerosols. Organic compounds synthesized via gas-phase and liquid-phase reactions were characterized by high-performance liquid chromatography coupled with scanning flow CCN analysis and thermal desorption particle beam mass spectrometry. These experiments quantified changes in κ with the addition of one or more functional groups to otherwise similar molecules. The increase in κ per group decreased in the following order: hydroxyl ≫ carboxyl > hydroperoxide > nitrate ≫ methylene (where nitrate and methylene produced negative effects, and hydroperoxide and nitrate groups produced the smallest absolute effects). Our results contribute to a mechanistic understanding of chemical aging and will help guide input and parametrization choices in models relying on simplified treatments such as the atomic oxygen:carbon ratio to predict the evolution of organic aerosol hygroscopicity.

Particle hygroscopicity and its link to chemical composition in the urban atmosphere of Beijing, China, during summertime

“…Recently, Richards et al (2013) undertook an extensive review of κ values published in the literature and showed that κ org vs. O:C plot has a large degree of scatter. This indicates that other factors, such as phase state (Pajunoja et al, 2015) and molecular structures (Suda et al, 2014) of organic aerosols (OA) other than oxidation state may also play a role in the determination of the OA hygroscopicity.…”

“…More recently, some studies have been performed to investigate the relationship between particle hygroscopicity and chemical composition in both field measurements and laboratory experiments (Massoli et al, 2010;Wong et al, 2011;Lambe et al, 2011;Rickards et al, 2013;Moore et al, 2012a, b;Suda et al, 2014;Paramonov et al, 2013;Levin et al, 2012). These works specially focused on parametrizing the empirical correlations between the atomic oxygen : carbon (O : C) ratio and organic hygroscopicity parameter (κ) derived from either hygroscopic growth factor (e.g., Wu et al, 2013;Rickards et al, 2013) or cloud condensation nuclei (CCN) activity (e.g., Mei et al, 2013;Wong et al, 2011;Lambe et al, 2011;Chang et al, 2010).…”

“…Rickards et al (2013) recently summarized the literature data and pointed out that the systematic variability in parametrizations between organic κ and the O : C ratio determined from the different studies remains large. A recent work done by Suda et al (2014) tested the influence of the number and location of molecular functional groups on the hygroscopicity of organic aerosols and may improve our understanding the mechanisms of the hygroscopicity of organics.…”

Water uptake by fresh Indonesian peat burning particles is limited by water-soluble organic matter

“…For instance, chemical characteristics of water-soluble organic matter (WSOM) have been intensively investigated, revealing that WSOM predominantly consists of levoglucosan-like species, carboxylic acids, aldehydes, ketones, aliphatic alcohols, and polyacids (Decesari et al, 2000;Peng et al, 2001;Suzuki et al, 2001;MayolBracero et al, 2002;Chan et al, 2005;Psichoudaki and Pandis, 2013). Recently, the important roles of functional groups in water uptake properties were also investigated by both theoretical and experimental approaches (Suda et al, 2014;Petters et al, 2016).…”

Technical Note: Development of chemoinformatic tools to enumerate functional groups in molecules for organic aerosol characterization

“…There have been many proposals for reducing representations in which a mixture of 10 000+ different types of molecules (Hamilton et al, 2004) are represented by some combination of their molecular size, carbon number, polarity, or elemental ratios (Pankow and Barsanti, 2009;Kroll et al, 2011;Daumit et al, 2013;Donahue et al, 2012), many of which are associated with observable quantities (e.g., by aerosol mass spectrometry (AMS; Jayne et al, 2000), gas chromatography-mass spectrometry (GC-MS and GCxGC-MS; Rogge et al, 1993;Hamilton et al, 2004)). Molecular bonds or organic functional groups (FGs), which are the focus of this manuscript, can also be used to provide reduced representations for mixtures and have been shown useful for organic mass (OM) quantification, source apportionment, and prediction of hygroscopicity and volatility (e.g., Russell, 2003;Donahue, 2011;Russell et al, 2011;Suda et al, 2014). Examples of property estimation methods include models for purecomponent vapor pressure (Pankow and Asher, 2008;Compernolle et al, 2011), UNIFAC, and its variations for activity coefficients and viscosity (Ming and Russell, 2001;Griffin et al, 2002;Zuend et al, 2008Zuend et al, , 2011.…”