1.5-Dimensional volatility basis set approach for modeling organic aerosol in CAMx and CMAQ
Graphical abstract
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.
Section snippets
Model description
Ambient aerosol mass spectrometer (AMS) measurement data have identified four characteristic groups of OA based on oxidation state: Hydrocarbon-like OA (HOA), biomass-burning OA (BBOA), and semi- and low-volatile oxygenated OA (SV-OOA and LV-OOA) (Jimenez et al., 2009). The VBS framework developed here uses four basis sets to represent these ambient OA groups: Two for anthropogenic and biogenic SOA or oxygenated POA (OPOA), one for fresh POA from anthropogenic sources, and one for fresh POA
Model evaluation
The 1.5-D VBS scheme was implemented in CAMx version 5.41 and CMAQ version 5.0.1. The two models were then applied to two month-long (February and August) episodes based on the EPA's Cross-State Air Pollution Rule (CSAPR) base year (2005) modeling database (EPA, 2011a) for model evaluation. The modeling domain consists of a 36-km horizontal grid covering the entire continental U.S. and a 12-km nested grid over the eastern U.S. (Fig. 2). Meteorological conditions and biogenic emissions were
Results and discussion
Fig. 3 shows the summer and winter OC performance of the 1.5-D VBS scheme implemented in CAMx and CMAQ. The evaluation was performed for each of the four U.S. Regional Planning Organization (RPO) regions within the 12-km modeling grid: Central Regional Air Planning Association (CENRAP), Midwest Regional Planning Organization (MRPO), Mid-Atlantic/Northeast Visibility Union (MANE-VU), and Visibility Improvement State and Tribal Association of the Southeast (VISTAS). The CAMx base case scenario
Acknowledgments
We thank Neil Donahue, Allen Robinson, and Spyros Pandis at Carnegie Mellon University for valuable discussions on the VBS implementation. This research was supported by the Electric Power Research Institute (EPRI) EP-P38705/C17224.
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