1.5-Dimensional volatility basis set approach for modeling organic aerosol in CAMx and CMAQ

Highlights

• A new hybrid volatility basis set (VBS) approach to modeling atmospheric organic aerosol is developed.

• The 1.5-D VBS scheme adjusts oxidation state as well as volatility in response to chemical aging.

• The new scheme is implemented in CAMx and CMAQ and evaluated against ambient data.

Abstract

A hybrid volatility basis set (VBS) approach to modeling atmospheric organic aerosol (OA) is developed that combines the simplicity of the 1-dimensional (1-D) VBS with the ability to describe evolution of OA in the 2-dimensional space of oxidation state and volatility. This 1.5-D scheme uses four basis sets to describe varying degrees of oxidation in ambient OA: two basis sets for chemically aged oxygenated OA (anthropogenic and biogenic) and two for freshly emitted OA (from anthropogenic sources and biomass burning). Each basis set has five volatility bins including a zero-volatility bin for essentially non-volatile compounds. The scheme adjusts oxidation state as well as volatility in response to chemical aging by simplifying the 2-dimensional VBS model. The 1.5-D VBS module is implemented in two widely used photochemical grid models (CAMx and CMAQ) and evaluated for summer and winter 2005 episodes over the eastern U.S. CAMx performs reasonably well in predicting observed organic carbon (OC) concentrations while CMAQ under-estimates OC, with differences between models being attributed to science algorithms other than the VBS. Oxygenated OA accounts for less than half of the modeled OA mass in winter but about 80% of total OA in summer due to more rapid chemical aging in summer.

Introduction

Atmospheric organic aerosol (OA) is highly complex, and detailed mechanistic descriptions include hundreds or thousands of compounds and are impractical for use in large-scale photochemical grid models (PGMs) (Johnson et al., 2006). Therefore, PGMs adopt simplified OA modules where organic compounds with similar properties and/or origin are lumped together. Until recently, most PGMs employed a multi-product model introduced by Odum et al. (1996) where multiple (typically two) condensable organic compounds are produced from oxidation of each hydrocarbon precursor and partitioned into a pseudo-ideal solution via absorptive partitioning (Pankow, 1994a, Pankow, 1994b). Although this approach can fit smog chamber data with few parameters, the estimated volatilities of the surrogate products were often inconsistent with the volatility range of ambient OA (Donahue et al., 2009). Another limitation of the 2-product model is that it does not treat volatility change in response to chemical aging of secondary OA (SOA). Primary OA (POA), although traditionally treated as non-volatile in PGMs, is mostly semi-volatile under ambient conditions (Lipsky and Robinson, 2006, Shrivastava et al., 2006) and the vapor-phase portion can undergo photochemical oxidation (Robinson et al., 2007).

The volatility basis set (VBS) approach (Donahue et al., 2006, Robinson et al., 2007) provides a unified framework for gas-aerosol partitioning and chemical aging of both POA and SOA. It uses a set of semi-volatile OA species with volatility equally spaced in a logarithmic scale (the basis set). VBS member species are allowed to react further in the atmosphere (chemical aging) to describe volatility changes (i.e., shifting between volatility bins). The VBS approach has been widely adopted in the air quality modeling community and implemented in many regional- and global-scale models including PMCAMx (Lane et al., 2008, Shrivastava et al., 2008, Murphy and Pandis, 2009, Tsimpidi et al., 2010, Fountoukis et al., 2011), CHIMERE (Hodzic et al., 2010, Zhang et al., 2013), WRF-CHEM (Shrivastava et al., 2011, Ahmadov et al., 2012), EMEP (Bergström et al., 2012), COSMO-ART (Athanasopoulou et al., 2013), GISS GCM II (Farina et al., 2010, Jathar et al., 2011), and GEOS-CHEM (Jo et al., 2013). However, the first generation VBS models use one-dimensional basis sets (1-D VBS) wherein organic compounds are grouped only by volatility and thus are unable to describe varying degrees of oxidation observed in atmospheric OA of similar volatility. A two dimensional VBS (2-D VBS) groups organic compounds by oxidation state as well as volatility (Donahue et al., 2011, Donahue et al., 2012a) and has been used to model chamber experiments (Jimenez et al., 2009, Donahue et al., 2012b, Chacon-Madrid et al., 2012, Chen et al., 2013) and implemented in a Lagrangian trajectory model (Murphy et al., 2011, Murphy et al., 2012) but has yet to be implemented in a PGM because the computational burden would be high.

Here we develop a new OA modeling approach that is based on the 1-D VBS framework but accounts for changes in oxidation state of OA as well as its volatility using multiple reaction trajectories defined in the 2-D VBS space. This 1.5-D VBS scheme is implemented in two widely used PGMs: the Comprehensive Air-quality Model with Extensions (CAMx; ENVIRON, 2011) and Community Multiscale Air Quality (CMAQ) modeling system (Byun and Ching, 1999). Both models were applied to simulate OA in summer and winter months over the eastern U.S. and the model performance is discussed.