Model–Measurement Comparison of Functional Group Abundance in Α-Pinene and 1,3,5-Trimethylbenzene Secondary Organic Aerosol Formation
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Atmos. Chem. Phys., 16, 8729–8747, 2016 www.atmos-chem-phys.net/16/8729/2016/ doi:10.5194/acp-16-8729-2016 © Author(s) 2016. CC Attribution 3.0 License. Model–measurement comparison of functional group abundance in α-pinene and 1,3,5-trimethylbenzene secondary organic aerosol formation Giulia Ruggeri1, Fabian A. Bernhard1, Barron H. Henderson2, and Satoshi Takahama1 1ENAC/IIE Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland 2Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL, USA Correspondence to: Satoshi Takahama (satoshi.takahama@epfl.ch) Received: 15 January 2016 – Published in Atmos. Chem. Phys. Discuss.: 22 February 2016 Revised: 23 June 2016 – Accepted: 26 June 2016 – Published: 18 July 2016 Abstract. Secondary organic aerosol (SOA) formed by α- 1 Introduction pinene and 1,3,5-trimethylbenzene photooxidation under dif- ferent NOx regimes is simulated using the Master Chemical Atmospheric aerosols are complex mixtures that can con- Mechanism v3.2 (MCM) coupled with an absorptive gas– tain a multitude of chemical species (Seinfeld and Pandis, particle partitioning module. Vapor pressures for individual 2006). While the inorganic fraction comprises a relatively compounds are estimated with the SIMPOL.1 group con- small number of compounds, the organic fraction (or organic tribution model for determining apportionment of reaction aerosol, OA) includes thousands of compounds with diverse products to each phase. We apply chemoinformatic tools to molecular structures (Hamilton et al., 2004). These com- harvest functional group (FG) composition from the simu- pounds take part in multitude of gas phase, aerosol phase, lations and estimate their contributions to the overall oxy- and heterogeneous transformation processes (e.g., Kroll and gen to carbon ratio. Furthermore, we compare FG abun- Seinfeld, 2008; Hallquist et al., 2009; Ziemann and Atkin- dances in simulated SOA to measurements of FGs reported son, 2012) that must be modeled with sufficient fidelity to in previous chamber studies using Fourier transform infrared predict atmospheric concentrations and impacts from various spectroscopy. These simulations qualitatively capture the dy- emission scenarios. namics of FG composition of SOA formed from both α- A mechanism central to these processes is the formation pinene and 1,3,5-trimethylbenzene in low-NOx conditions, of semivolatile organic compounds (SVOCs) through gas- especially in the first hours after start of photooxidation. phase oxidation of volatile organic compound (VOC) precur- Higher discrepancies are found after several hours of sim- sors and their reaction products. α-pinene (APIN) and 1,3,5- ulation; the nature of these discrepancies indicates sources trimethylbenzene (TMB) are examples of biogenic and an- of uncertainty or types of reactions in the condensed or gas thropogenic VOC precursors, respectively, which have been phase missing from current model implementation. Higher studied for their chemical reaction mechanisms and aerosol discrepancies are found in the case of α-pinene photooxida- yields in environmentally controlled chamber experiments tion under different NOx concentration regimes, which are and numerical simulation. APIN is a monoterpene compound reasoned through the domination by a few polyfunctional primarily emitted from coniferous vegetation (Fuentes et al., compounds that disproportionately impact the simulated FG 2000; Tanaka et al., 2012) with high emission rate, reactiv- abundance in the aerosol phase. This manuscript illustrates ity, and secondary organic aerosol (SOA) generation poten- the usefulness of FG analysis to complement existing meth- tial (e.g., Fehsenfeld et al., 1992; Lamb et al., 1993; Chamei- ods for model–measurement evaluation. des et al., 1988; Jenkin, 2004; Tolocka et al., 2004; Sinde- larova et al., 2014). TMB is an aromatic compound emit- ted from vehicular emissions and a major contributor to ur- ban organic aerosol (e.g., Kalberer et al., 2004); its degra- dation mechanism has also been subject of collective eval- Published by Copernicus Publications on behalf of the European Geosciences Union. 8730 G. Ruggeri et al.: MCM functional group analysis uation (Metzger et al., 2008; Wyche et al., 2009; Rickard rapid progress has been made over the past decade with et al., 2010; Im et al., 2014). Gas-phase oxidation reactions Fourier transform infrared spectroscopy (FTIR) (e.g., Sax are modeled with chemically explicit or semi-explicit treat- et al., 2005; Reff et al., 2007; Coury and Dillner, 2008; ment, or alternatively using a basis set approach based on Day et al., 2010; Takahama et al., 2013; Ruthenburg et al., simplified molecular or property descriptors; SOA formation 2014; Takahama and Dillner, 2015), nuclear magnetic reso- is commonly modeled by coupling these reactions with parti- nance (Decesari et al., 2007; Cleveland et al., 2012), spec- tioning of oxidation products to an absorptive organic phase trophotometry (Aimanant and Ziemann, 2013; Ranney and (e.g., Jenkin et al., 1997; Pun et al., 2002; Griffin et al., 2003; Ziemann, 2016), and gas chromatography–mass spectrome- Aumont et al., 2005; Capouet et al., 2008; McFiggans et al., try with derivatization (Dron et al., 2010). The second chal- 2010; Barley et al., 2011; Chen et al., 2011; Murphy et al., lenge is computationally harvesting FG abundance from a 2011; Aumont et al., 2012; Jathar et al., 2015; McVay et al., large set of known molecular structures. To this end, Rug- 2016). SVOCs produced by such reactions can in reality par- geri and Takahama(2016) developed a set of substructure tition among multiple phases (vapor, organic liquid, aque- definitions corresponding to FGs that can be queried against ous, solid), and participate in additional functionalization, arbitrary molecules specified by their molecular graphs. accretion, or fragmentation reactions in one of many phases In this work, we apply these new substructure definitions (Kroll et al., 2011; Cappa and Wilson, 2012; Im et al., 2014; to describe the FG composition of products simulated by gas- Zhang and Seinfeld, 2013; Zhang et al., 2015). These pro- phase reactions prescribed with the Master Chemical Mecha- cesses are represented in models with varying degrees of de- nism (MCMv3.2) (Jenkin et al., 1997; Saunders et al., 2003; tail; simplifying or wholly omitting various mechanisms out Jenkin et al., 2003; Bloss et al., 2005) and SOA constituents of concerns for computational feasibility or lack of sufficient formed by their dynamic absorptive partitioning (Chen et al., knowledge. For instance, in a work we follow closely in this 2011). Three instances of APIN photooxidation under vary- manuscript, Chen et al.(2011) used a fully explicit gas-phase ing initial concentrations of oxides of nitrogen (NOx), and reaction mechanism with absorptive organic partitioning and TMB oxidation in the presence of NOx are studied in ac- evaluated the potential importance of missing heterogeneous cordance with aerosol FG composition characterized by Sax and condensed-phase mechanisms based on discrepancy of et al.(2005) and Chhabra et al.(2011) in chamber studies model simulation and experiments. using FTIR. The model results are analyzed through a suite Our capability to simulate SOA formation is often eval- of FG abundances and model–measurement comparisons of uated against aerosol mass yield, O : C, carbon oxidation measured FGs are presented to hypothesize reasons (includ- state, mean carbon number, volatility, and specific species ing unimplemented mechanisms) for discrepancies where or compound classes when available (e.g., Robinson et al., they occur. 2007; Kroll et al., 2011; Donahue et al., 2012; Nozière et al., 2015). These properties can be measured using var- ious forms of mass spectrometry (e.g., Jayne et al., 2000; 2 Methods Jimenez et al., 2009; Nizkorodov et al., 2011) or through monitoring changes in size distribution in combination with We target our model simulations to mimic SOA formation in isothermal dilution or thermal heating (e.g., Grieshop et al., environmentally controlled chambers for which FG measure- 2009; Cappa, 2010; Epstein and Donahue, 2010; Donahue ments are available. et al., 2012). Functional group (FG) composition is a comple- mentary representation of organic molecules and complex or- 2.1 Systems studied ganic mixtures that offers a balance between parsimony and chemical fidelity for measurement and interpretation. Photooxidation of APIN under “low-NOx” (NOx / APIN FGs represent structural units of molecules that play a of 0.8), “high-NOx” (NOx / APIN of 18), and no-NOx con- central role in chemical transformations and provide insight ditions (designated as lNOx, hNOx, and nNOx, respectively), into evolution of complex organic mixtures without moni- and TMB under “low-NOx” (NOx / TMB ratio of 0.24; des- toring all species explicitly (Holes et al., 1997; Sax et al., ignated as lNOx) conditions were simulated in this study to 2005; Presto et al., 2005; Lee and Chan, 2007; Chhabra compare with available measurements of aerosol FG com- et al., 2011; Zeng et al., 2013). FG abundances have also position in environmental chamber experiments. Simulations been associated with volatility (e.g., Pankow and Asher, were run at 298 K and with conditions closely following ex- 2008), hygroscopicity (e.g., Hemming and Seinfeld, 2001; perimental descriptions summarized in Table1, with a few Suda et al., 2014), and magnitude of nonideal interactions exceptions. In the case of