Geoscientific Model Development Identifying the causes of differences in ozone production from the CB 05 and CBMIV chemical mechanisms

An investigation was conducted to identify the mechanistic differences between two versions of the carbon bond gas-phase chemical mechanism (CB05 and CBMIV) which consistently lead to larger ground-level ozone concentrations being produced in the CB05 version of the National Air Quality Forecasting Capability (NAQFC) modeling system even though the two parallel forecast systems utilize the same meteorology and base emissions and similar initial and boundary conditions. Box models of each of the mechanisms as they are implemented in the NAQFC were created and a set of 12 sensitivity simulations was designed. The sensitivity simulations independently probed the conceptual mechanistic differences between CB05 and CBMIV and were exercised over a 45-scenario simulation suite designed to emulate the wide range of chemical regimes encountered in a continental-scale atmospheric chemistry model. Results of the sensitivity simulations indicate that two sets of reactions that were included in the CB05 mechanism, but which were absent from the CBMIV mechanism, are the primary causes of the greater ozone production in the CB05 version of the NAQFC. One set of reactions recycles the higher organic peroxide species of CB05 (ROOH), resulting in additional photochemically reactive products that act to produce additional ozone in some chemical regimes. The other set of reactions recycles reactive nitrogen from less reactive forms back to NO2, increasing the effective NOx concentration of the system. In particular, the organic nitrate species (NTR), which was a terminal product for reactive nitrogen in the CBMIV mechanism, acts as a reservoir species in CB05 to redistribute NOx from major source areas to potentially NOxsensitive areas where additional ozone may be produced in areas remote from direct NOx sources. 1 Introduction The NOAA National Air Quality Forecasting Capability (NAQFC) is a modeling system established in 2004 to provide ground-level ozone (O3) forecasts for the conterminous US (CONUS) (Eder et al., 2009). The NAQFC utilizes the North American Mesoscale (NAM) meteorological model run of the Nonhydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system (WRF-NMM) (Janjic, 2003) to provide meteorological fields to drive the US Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) version 4.6 modeling system (Byun and Schere, 2006) which generates 48-h forecast fields of ground-layer O3. The CMAQ portion of the NAQFC system uses 12 km horizontal grid spacing and 22 vertical layers from the surface to 100 hPa. Emission inputs use the latest available EPA National Emissions Inventory with electric generating units (EGUs) updated with Continuous Emission Monitoring (CEM) data and projections to the current forecast year using data from the Department of Energy’s Annual Energy Outlook. Further details of the operational NAQFC implementation and evaluations of its performance can be obtained from Eder et al. (2009), Otte et al. (2005), and Yu et al. (2010). Since its inception, the operational version of the NAQFC has used a modified implementation of the Carbon Bond Mechanism version IV (CBMIV, Gery et al., 1989) as its gasphase chemical mechanism. An experimental version of the NAQFC has been run in parallel with the operational track to provide a testbed for planned upgrades to the operational system. Since 2008, the experimental NAQFC has employed the updated 2005 version of the Carbon Bond Mechanism (CB05, Yarwood et al., 2005) as its gas-phase mechanism. The two parallel NAQFC tracks use identical emissions base Published by Copernicus Publications on behalf of the European Geosciences Union. 258 R. D. Saylor and A. F. Stein: Identifying the causes of differences in ozone production inventories (with volatile organic carbon compounds speciated appropriately for each mechanism), identical meteorological fields from NAM, and similar initial and boundary conditions. Figure 1 presents a comparison of domainwide daily average O3 biases for 2009 from the two parallel NAQFC systems as compared to US Environmental Protection Agency Air Quality System (AQS) measurements (http://www.epa.gov/ttn/airs/airsaqs/). Both versions of the NAQFC exhibit similar biases throughout the year, climbing from near zero in April to a peak positive bias (i.e., model – measurement) in September. The inherent, similar biases of both NAQFC versions are likely due to a variety of factors, possibly involving anthropogenic or biogenic emissions uncertainties, meteorological input biases, dry or wet deposition processes, or chemical processes common to both CB05 and CBMIV. However, the motivation of the work described here is to understand the causes of the relatively consistent difference between the operational and experimental NAQFC versions, given that the emissions and input data for both systems are identical and that they differ only in the gas-phase chemical mechanisms employed. Since the input data to both the CB05 and CBMIV versions of the NAQFC are essentially the same, it is somewhat surprising that the CB05 version consistently produces higher O3 surface concentrations. The purpose of the work reported here was to identify the mechanistic reasons for these differences so that future work can be undertaken to improve the forecast performance of the CB05 version of the NAQFC with respect to observations. Previous investigations (Luecken et al., 1999; Sarwar et al., 2008; Luecken et al., 2008) have also observed the differences in O3 produced from CMAQ simulations for the two mechanisms. These studies have identified mechanistic differences that might have some potential impact on O3 production, but no overriding explanatory cause emerged. As noted in Luecken et al. (2008), O3 photochemistry is complex and in the framework of a three-dimensional model simulation, numerous temporallyand spatially-varying factors may contribute to the observed differences in O3 fields between the two mechanisms. Consequently, in this work we attempt to focus solely on mechanism differences without the confounding effects of additional model processes (e.g., advection, turbulent diffusion, wet and dry deposition, etc.) that may obscure the underlying mechanistic reasons for the observed differences in O3 concentrations. Using this approach, and recognizing that CB05 is, in some sense, a “modified” version of CBMIV, a relatively simple comparison of the mechanisms was undertaken by performing sensitivity studies with box model versions of each to identify which mechanistic differences between CB05 and CBMIV may account for the O3 differences observed in full CMAQ simulations. In subsequent sections of this paper, we describe the box model implementation of the mechanisms and the sensitivity studies that were designed to probe mechanism differences and then we present selected results from those sensitivity runs to demonstrate our findings. 23 1 2 3 Figure 1. Mean bias of ground-­‐level ozone from parallel versions of the NAQFC. Ozone 4 measurements are from the U. S. EPA Air Quality System (AQS) measurement network. 5 Operational NAQFC (red) and experimental NAQFC (black) mean biases (ppbv) calculated 6 as a CONUS-­‐wide average of (model – AQS) site biases. 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Fig. 1. Mean bias of ground-level ozone from parallel versions of the NAQFC. Ozone measu e ents are from the US EPA Air Quality System (AQS) measurement network. Operational NAQFC (red) and experimental NAQFC (black) mean biases (ppbv) calculated as a CONUS-wide average of (model – AQS) site biases.