# Modeling for North American Background Concentrations

Final Report

Contract No. EP-C-09-009 Work Assignment 2-55

October 28, 2011

Prepared for
U.S. EPA National Center for Environmental Assessment Research Triangle Park, NC 27711

Prepared by
ICF International 101 Lucas Valley Road, Suite 260 San Rafael, CA 94903 415.507.7164

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# Table of Contents

1. Introduction .................................................................................................................. ......... 1

2. Description of GEOS-Chem ................................................................................................. 3

3. GEOS-Chem Model Application Methodology ................................................................... 5 3.1. Modeling Domain .......................................................................................................... 5 3.2. Simulation Periods ........................................................................................................ 7 3.3. Input Acquisition and Preparation ................................................................................. 7 Meteorological Inputs

.............................................................................................................................. ............ 7 Emission Inputs

.............................................................................................................................. ....................... 8 Terrain, Land-Use, Chemistry and Other Inputs ........................................................................................ 8 

### 3.4. Model Options and Parameter Specifications .............................................................. 9 3.5. Scenarios ...................................................................................................................... 9

4. Model Performance Evaluation Procedures & Results ................................................... 11 4.1. Comparison with Observed Air Quality Data .............................................................. 11 Summary Model Performance Results for 2006 ...................................................................................... 12 Summary Model Performance Results for 2007 ...................................................................................... 49 Summary Model Performance Results for 2008 ...................................................................................... 88 Year-to-Year Variations in Model Performance ...................................................................................... 127 

### 4.2. Case Studies ............................................................................................................ 127 Case Study #1: 21 April 2006 ....................................................................................................................... 128 Case Study #2: 14 July 2006 ........................................................................................................................ 129 Case Study #3: 17-20 August 2006 ............................................................................................................ 131 Additional Case Studies

.............................................................................................................................. ... 134 

### 4.3. Summary of Model Performance .............................................................................. 134

5. Estimation of North American Background Ozone (NAB Scenario) ........................... 137

6. Additional Scenarios and Comparisons ......................................................................... 155 6.1. U.S. and Natural Background Scenarios .................................................................. 155 6.2. Comparison of North American and Natural Background Ozone Concentrations .... 175

7. Attributes and Limitations ................................................................................................ 183

8. References .................................................................................................................... ..... 185



## List of Figures

Figure 3-1. GEOS-Chem Nested-Grid Mo deling Domain for North Amer ica. .......................................................... ....... 5 Figure 4-1. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Each Season and the Entire Year, Averaged Over All Sites in Entire Continental U.S.: 2006. ............... 23 Figure 4-2. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the We st Coast Subreg ion: 20 06. ............................................................... 24 Figure 4-3. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Intermountain West Subregion: 2006. ................................................... 26 Figure 4-4. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Site s in Central States Subregion: 2006. ................................................................. 27 Figure 4-5. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Great Lakes Subr egion: 2006. .............................................................. 29 Figure 4-6. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Southeast Subregion: 2006. .................................................................. 31 Figure 4-7. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Northeast Subreg ion: 20 06. .................................................................. 32

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11-035Figure 4-8. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Each Season and the Entire Year, Averaged Over All Sites in Entire Continental U.S.: 2007. ............... 59 Figure 4-9. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the We st Coast Subreg ion: 20 07. ............................................................... 60 Figure 4-10. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Intermountain West Subregion: 2007. ................................................... 61 Figure 4-11. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Site s in Central States Subregion: 2007. ................................................................. 63 Figure 4-12. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Great Lakes Subr egion: 2007. .............................................................. 65 Figure 4-13. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Southeast Subregion: 2007. .................................................................. 66 Figure 4-14. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Northeast Subreg ion: 20 07. .................................................................. 68 Figure 4-15. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Each Season and the Entire Year, Averaged Over All Sites in Entire Continental U.S.: 2008. ............... 98 Figure 4-16. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the We st Coast Subreg ion: 20 08. ............................................................... 99 Figure 4-17. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Intermountain West Subregion: 2008. ................................................. 100 Figure 4-18. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Site s in Central States Subregion: 2008. ............................................................... 102 Figure 4-19. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Great Lakes Subr egion: 2008. ............................................................ 104 Figure 4-20. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Southeast Subregion: 2008. ................................................................ 105 Figure 4-21. Comparison of the Mean Simulated an d Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Northeast Subreg ion: 20 08. ................................................................ 107 Figure 4-22. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for the Lassen NP CASTNet Site for 11-29 Ap ril 2006. .................................................................................. . 128 Figure 4-23. Vertical Profiles of Simulated and Obse rved Ozone Concentrations (ppb) for Trinidad Head for 21 April 2006. Observed Profile is Based on Oz onesonde Data from the INTEX-B Program. ................... 129 Figure 4-24. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for the Rocky Mountain NP CASTNet Site for 8- 20 July 20 06. ........................................................................ 130 Figure 4-25. Vertical Profiles of Simulated and Observ ed Ozone Concentrations (ppb) for Boulder for 14 July 2006. Observed Profile is Based on Ozones onde Data from the INTEX-B Pr ogram. ........................... 131 Figure 4-26. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for the Lassen Volcanic NP and Pinnacles NM CAST Net Sites for 12-25 August 2006. ................................. 132 Figure 4-27. Vertical Profiles of Simulated and Obse rved Ozone Concentrations (ppb) for Trinidad Head for 17- 20 August 2006. Observed Profile is Based on Ozonesonde Data from t he INTEX-B Pr ogram. .......... 133 Figure 5-1. Mean MDA8 Ozone Concentrations (ppb) fo r the Base (Current Atmosphere) and North American Background Scenarios, Based on the 2006, 2007, and 2008 Simula tion Peri od. ................................. 137 Figure 5-2. Mean MDA8 Ozone Concentrations (ppb) for the North American Background Scenario, Based on the 2006, 2007, and 2008 Simulation Period. ................................................................................... .... 138 Figure 5-3. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Lassen Volcanic NP, CA. ............................................................................ 147 Figure 5-4. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios fo r Pinedale , WY. ........................................................................................ ..... 148 Figure 5-5. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios fo r Big Bend NP, TX. ..................................................................................... .. 149 Figure 5-6. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Perkinstown, WI. ..................................................................................... .... 150 Figure 5-7. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Great Smoky Mountain s NP, TN

. ............................................................... 151 Figure 5-8. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Bl ackwater NW R, MD. ................................................................................ 1 52 Figure 6-1. Mean MDA8 Ozone Concentrations (ppb) fo r the Base (Current Atmosphere), NAB, USB and NB Scenarios, Based on the 2006, 2007, and 2008 Simulati on Peri od. ..................................................... 155 Figure 6-2. Mean MDA8 Ozone Concentrations (ppb) fo r the U.S. Background Scenario, Based on the 2006, 2007, and 2008 Simu lation Pe riod. ............................................................................................. .......... 157 Figure 6-3. Mean MDA8 Ozone Concentrations (ppb) for the Natural Background Scenario, Based on the 2006, 2007, and 2008 Simu lation Pe riod. ............................................................................................. .......... 158

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11-035Figure 6-4. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Lassen Volcanic NP, CA. ............................................................................ 167 Figure 6-5. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios fo r Pinedale , WY. ........................................................................................ ..... 168 Figure 6-6, Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios fo r Big Bend NP, TX. ..................................................................................... .. 169 Figure 6-7. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Perkinstown, WI. ..................................................................................... .... 170 Figure 6-8. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Great Smoky Mountain s NP, TN

. ............................................................... 171 Figure 6-9. Mean MDA8 Ozone Concentrations (ppb) for the Current Atmosphere and North American Background Scenarios for Bl ackwater NW R, MD. ................................................................................ 1 72 Figure 6-10. Simulated vs. Observed MDA8 Ozone Concent rations (ppb) for the Intermountain West CASTNet sites. The Box-and-Whisker Plots (Minimum, 25 th , 50 th , 75 th Percentiles, and Maximum) Summarize NAB and NB for 10-ppb Bins of Observ ed Ozone Concentration: 2006-20 08. ..................................... 176 Figure 6-11. Simulated vs. Observed MDA8 Ozone Concent rations (ppb) for the Great Lakes CASTNet sites. The Box-and-Whisker Plots (Minimum, 25 th , 50 th , 75 th Percentiles, and Maximum) Summarize NAB and NB for 10-ppb Bins of Observed Ozone Concentration: 2006-20 08. ............................................. 177 Figure 6-12. Simulated vs. Observed MDA8 Ozone Concentra tions (ppb) for the Southeast CASTNet sites. The Box-and-Whisker Plots (Minimum, 25 th , 50 th , 75 th Percentiles, and Maximum) Summarize NAB and NB for 10-ppb Bins of Observed Ozone Concentration : 2006-20 08. .................................................... 178 Figure 6-13. Simulated vs. Observed MDA8 Ozone Concentra tions (ppb) for the Northeast CASTNet sites. The Box-and-Whisker Plots (Minimum, 25 th , 50 th , 75 th Percentiles, and Maximum) Summarize NAB and NB for 10-ppb Bins of Observed Ozone Concentration : 2006-20 08. .................................................... 179 Figure 6-14. Frequency Distributions of MDA8 Ozone C oncentrations (ppb) for March – August 2006, 2007 & 2008 for Low-Elevation (<1.5 km) and High-Elevatio n (>1.5 km) CASTNet Sites. Observed Values are in Black; Model Re sults are in Red, NAB is in Blue , and NB is in Gr een (Dash ed). ....................... 180



## List of Tables

Table 3-1. GEOS-Chem Reduced Vertical Grid Interf ace Levels Based on 47 Sigm a-Pressure Levels. ....................... 6 Table 3-2. Background Methane Concentrations (ppb) in GEOS-Chem Simu lations. ................................................... 9 Table 4-1. Definition and Description of Measures/Metrics for GEOS-Chem Model Performance Evaluation. ............ 12 Table 4-2. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Cur rent Atmosphere Scenario) Using CASTNet Data: 2006.

............................................................................................................................... ........................ 14 Table 4-3. Seasonal and Annual GEOS-CHEM Model Perfo rmance Statistics for Maximum Daily 8-hour Average (MDA8) Ozone Concentration (ppb) for the Base Case (Current Atmosphere Scenario) Using CASTNet Da ta: 2006.

........................................................................................................... .................. 19 Table 4-4. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmosphere Scenario) Us ing AQS Data : 2006. .......... 34 Table 4-5. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average NO 2 Concentration (ppb) for the Base Case (C urrent Atmosphere Scenario): 2006. ..................................... 37 Table 4-6. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average SO 2 Concentration (ppb) for the Base Case (C urrent Atmosphere Scenario): 2006. ..................................... 40 Table 4-7. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average CO Concentration (ppm) for the Base Case (C urrent Atmosphere Scenario): 2006. .................................... 43 Table 4-8. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average PM 2.5 Concentration ( μ gm -3 ) for the Base Case (Current At mosphere Scenar io): 200 6. .................................. 46 Table 4-9. Annual GEOS-CHEM Model Performance Statis tics for Dry Deposition (kg/ha) for the Base Case (Current Atmosphere Scenario) for the Continental U.S.: 200 6. ............................................................. 49 Table 4-10. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmos phere Scenario) Using CASTNet Data: 2007. ..... 50 Table 4-11. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for Maximum Daily 8-hour Average (MDA8) Ozone Concentration (ppb) for the Base Case (Current Atmosphere Scenario) Using CASTNet Data: 2007.

..................................................................................................... .............. 55 Table 4-12. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmosphere Scenario) Us ing AQS Data : 2007. .......... 70 Table 4-13. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average NO 2 Concentration (ppb) for the Base Case (C urrent Atmosphere Scenario): 2007. ..................................... 73

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11-035 Table 4-14. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average SO 2 Concentration (ppb) for the Base Case (C urrent Atmosphere Scenario): 2007. ..................................... 77 Table 4-15. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for 24-hour Average CO Concentration (ppm) for the Base Case (C urrent Atmosphere Scenario): 2007. .................................... 80 Table 4-16. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average PM 2.5 Concentration ( μ gm -3 ) for the Base Case (Current At mosphere Scenar io): 200 7. .................................. 84 Table 4-17. Annual GEOS-CHEM Model Performance Statisti cs for Dry Deposition (kg/ha) for the Base Case (Current Atmosphere Scenario) for the Continental U.S.: 200 7. ............................................................. 87 Table 4-18. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmos phere Scenario) Using CASTNet Data: 2008. ..... 89 Table 4-19. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for Maximum Daily 8-hour Average (MDA8) Ozone Concentration (ppb) for the Base Case (Current Atmosphere Scenario) Using CASTNet Data: 2008.

..................................................................................................... .............. 94 Table 4-20. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmosphere Scenario) Us ing AQS Data: 2008. ........ 109 Table 4-21. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average NO 2 Concentration (ppb) for the Base Case (C urrent Atmosphere Scenario): 2008. ................................... 112 Table 4-22. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average SO 2 Concentration (ppb) for the Base Case (C urrent Atmosphere Scenario): 2008. ................................... 116 Table 4-23. Seasonal and Annual GEOS-CHEM Model Pe rformance Statistics for 24-hour Average CO Concentration (ppm) for the Base Case (C urrent Atmosphere Scenario): 2008. .................................. 119 Table 4-24. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average PM 2.5 Concentration ( μ gm -3 ) for the Base Case (Current At mosphere Scenar io): 200 8. ................................ 123 Table 4-25. Annual GEOS-CHEM Model Performance Statisti cs for Dry Deposition (kg/ha) for the Base Case (Current Atmosphere Scenario) for the Continental U.S.: 200 8. ........................................................... 126 Table 5-1. GEOS-Chem-Derived Seasonal and Annual Mean 24-Hour Average Observed, Current Atmosphere, and NAB Ozone Concentrations (ppb), Based on the 2006, 2007 and 2008 Simulation Period. .......... 139 Table 5-2. GEOS-Chem-Derived Seasonal and Annual Me an MDA8 Observed, Current Atmosphere, and NAB Ozone Concentrations (ppb), Based on the 2 006, 2007 and 2008 Simu lation Pe riod. ......................... 143 Table 5-3. GEOS-Chem-Derived Seasonal and Annual Me an MDA8 Observed, Current Atmosphere, and NAB Ozone Concentrations (ppb) for Selected CASTNet Sites, Based on the 2006, 2007 and 2008 Simulation Period.............................................................................................................. .................... 153 Table 6-1. GEOS-Chem-Derived Seasonal and Annual Mean 24-Hour Average Observed, Current Atmosphere, NAB, USB, and NB Ozone Concentrations (ppb), Based on the 2006, 2007 and 2008 Simulation Period. ....................................................................................................................... ........................... 159 Table 6-2. GEOS-Chem-Derived Seasonal and Annual Mean MDA8 Observed, Current Atmosphere, NAB, USB, and NB Ozone Concentrations (ppb), Based on t he 2006, 2007 and 2008 Simulation Pe riod. ............ 163 Table 6-3. GEOS-Chem-Derived Seasonal and Annual Mean MDA8 Observed, Current Atmosphere, NAB, USB, and NB Ozone Concentrations (ppb) for the Sp ring, Summer, and Annual Periods for Selected CASTNet Sites, Based on the 2006, 2007 and 2008 Simula tion Peri od. .............................................. 173

# 1. Introduction

Sections 108 and 109 of the Clean Air Act require the U.S. Environmental Protection Agency (EPA) to conduct periodic reviews of the National Ambient Air Quality Standards (NAAQS) for criteria pollutants. These periodic reviews are part of an Integrated Science Assessment (ISA). Currently, the National Center for Environmental Assessment (NCEA), which is part of EPA’s Office of Research and Development (ORD), is reviewing the NAAQS for ozone (O 3 

### ) and other oxidants. This document summarizes modeling work conducted by ICF International, in collaboration with Harvard University, to support this assessment.

An important aspect of the O 3 

### ISA is the estimation of policy relevant background (PRB) ozone concentrations. The concentrations are defined as those that would occur in the absence of all anthropogenic sources in continental North America, hereafter referred to as North American background (or NAB) concentrations. For this assessment, NAB O 3 

### was estimated using the GEOS-Chem model and includes contributions fr om 1) all natural sources (throughout the world) and 2) all anthropogenic sources outside of North America.

GEOS-Chem is a global chemical transport model (CTM) that simulates reactions of photochemical precursor emissions of oxides of nitrogen (NO x 

### ), volatile organic compounds (VOCs), and carbon monoxide (CO). The GEOS -Chem model is driv en by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) and is able torepresent long-range transport (for example, from outside CNA) as well as stratospherictropospheric exchange processes. For this asse ssment, GEOS-Chem was applied to estimate NAB O 3 

### and its variability as well as the relative contribution of natural versus anthropogenic emissions to NAB O 3


### . This study represents the latest in a series of assessments of PRB ozone concentrations. Previous studies have used measurements and transport models to estimate PRB ozone concentrations. EPA (2006) noted that the use of models has the advantage of being able to explicitly account for long-range transport and to apportion the contributions to PRB ozone between natural and anthropogenic sources.

The most recent PRB O 3 

### assessment was completed in 2008. For this assessment, estimates of NAB ozone concentrations were based on output from the GEOS-Chem model using a 2001 simulation period with horizontal resolution of 2°×2.5° (degrees of longitude and latitude) (Fiore et al., 2003). NAB O 3 

### concentrations for the eastern U.S. were estimated to be generally within the range of 15 to 35 parts per billion (ppb) during the summer months and higher in the springtime due to enhanced contributions from pollution sources outside North America and stratospheric ozone intrusion.

Following this, Wang et al. (2009) also modeled NAB O 3 

### concentrations using GEOS-Chem. This later modeling was done for 2001 at higher spatial resolution (1°×1°) using the GEOS-3 meteorological data. The resulting NAB O 3 

### concentrations are estimated to be generally within the range of 18 to 35 ppb for summer, and are consistent with those reported by Fiore et al. (2003).

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### For the current analysis, GEOS-Chem was applied using nested grids with 2°×2.5° horizontal resolution at the global scale and 0.5°×0.667° horizontal resolution over North America using the most recent version of the GEOS-5 meteorological data. The model was applied for the years 2006, 2007 and 2008. Zhang et al. (2011) recently completed a similar study for North America, using the same grid configuration but a different version of the GEOS-Chem model.

This report summarizes the GEOS-Chem application and results and includes a description of the GEOS-Chem model, an overview of t he model application and evaluation methods, an assessment of model performance for the base ca se simulations, modeling results for NAB O 3 

### and other simulations, and a discussion of the attributes and limitations of the modeling methods and results.

# 2. Description of GEOS-Chem

The GEOS–Chem model is a three-dimensional gl obal-scale chemical transport model (CTM). It was developed and continues to be refined by resear chers at Harvard University, as well as numerous other institutions. The GEOS-Chem model simulates the emission, chemical transformation, transport, and deposition of air pollutants throughout and above the troposphere. The model incorporates detailed emission inventories of anthropogenic and biogenic emissions that account for fossil fuel combustion and usage, biomass burning, biofuel burning, biogenic, and aerosol emissions.

The GEOS-Chem chemical mechanism is desig ned to simulate tropospheric chemistry and includes reactions that represent the photochemical production of ozone as well as a detailed representation of aerosol formation. The chemic al mechanism is described in some detail by Evans et al. (2003) and Mao et al. (2010). A list of species included in the GEOS-Chem model is provided in the on-line user’s guide (Y antosca and Carouge, 2011). GEOS-Chem includes a state-of-the-science photolysis routine (FAST–J) and the SMVGEAR II chemistry solver package. The ozone in the stratosphere is represented by a linearized ozone (Linoz) parameterization (McLinden et al., 2000).

Advection and transport within the model are driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling Assimilation Office . GEOS–Chem includes the state-of-the-art transport (TPCORE) routine.

As summarized by Bey et al. (2001), dry deposition is treated with an enhanced resistance in series method (Wesley, 1989; Wang et al., 1998). Deposition velocities are calculated based on local surface types and meteorological conditi ons. Wet deposition is based on the algorithm developed by Liu et al. (2001). The algorithm a ccounts for scavenging by convective clouds and large-scale precipitation.

Version 9-01-01 of the GEOS-Chem model was applied for this study. Compared to the prior version of the model, version 9-01-01 includes several updates. Two of the updates that are likely to affect the simulated ozone concentrations are 1) a correction for the yield of isoprene nitrates that increases the lifetime of NO x 

### and may result in greater ozone production, and 2) a correction for lightning NO x 

### emissions (which may also increase ozone). A full list of updates is provided in the release notes for this version of the model (http://acmg.seas.harvard.edu/geos/doc/man/appendix_9.html)

.

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# 3. GEOS-Chem Model Application Methodology

3.1. Modeling Domain

For the current analysis, Version 9-01-01 of GEOS-Chem was applied using nested grids with 2°×2.5° horizontal resolution at the global scale and 0.5°×0.667° horizontal resolution over North America (140°-40°W, 10°-70°N). In addition, a coarser resolution grid (4°×5°) is also being used for the start-up simulation period—an annual simulation period run to spin up the model and to ensure a reasonable representation of long-range (global) transport. The global domain is illustrated by Bey et al. (2001). The nested-grid modeling grid domain for North America is illustrated in Figure 3-1 and the grid spacing at different grid resolution is shown.

Figure 3-1. GEOS-Chem Nested-Grid Modeling Domain for North America. (a) 4°×5° Global-Scale Resolution (Spin-Up Period Only).

(b) 2°×2.5° Global-Scale Resolution.

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(c) 0.5°×0.667° Continental-Scale Resolution.

Source (Zhang, 2011, pers. comm.)


### The modeling domain includes 47 vertical layers that increase in thickness with height above ground. The top of the modeling domain is at approximately 80 kilometers (km) with layers defined as shown in Table 3-1

.

Table 3-1. GEOS-Chem Reduced Vertical Grid In terface Levels Based on 47 Sigma-Pressure Levels.

Level Altitude (km) Pressure (hPa)

47 80.581 0.01
46 68.392 0.066
45 59.924 0.211
44 51.788 0.617
43 44.286 1.651
42 37.574 4.077
41 31.716 9.293
40 26.596 19.792
39 24.24 28.368
38 22.004 40.175
37 19.855 56.388
36 17.773 78.512
35 16.753 92.366
34 15.731 108.663
33 14.706 127.837
32 13.674 150.393
31 12.633 176.93
30 11.578 208.244
29 10.504 245.246
28 9.409 288.927
27 8.32 339.005

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11-035 Level Altitude (km) Pressure (hPa)
26 7.582 377.07
25 6.905 415.155
24 6.277 453.269
23 5.692 491.401
22 5.142 529.55
21 4.623 567.706
20 4.132 605.88
19 3.665 644.054
18 3.219 682.239
17 2.932 707.699
16 2.654 733.16
15 2.382 758.621
14 2.118 784.088
13 1.86 809.556
12 1.659 829.929
11 1.51 845.211
10 1.363 860.493

9 1.218 875.776
8 1.075 891.059
7 0.934 906.342
6 0.795 921.626
5 0.657 936.911
4 0.521 952.195
3 0.387 967.48
2 0.254 982.765
1 0.123 998.051
0 -0.006 1013.25



# 3.2. Simulation Periods

The GEOS-Chem model was applied for the years 2006, 2007 and 2008. In addition, the modeling was run for a one-year spin-up period (2005).



# 3.3. Input Acquisition and Preparation

Meteorological Inputs
As noted earlier, the GEOS-Chem model is driven by assimilated meteorological observations from the Goddard Earth Observing System (G EOS) and is able to represent long-range transport as well as stratospheric-tropospheric exchange processes. For this analysis, meteorological inputs for the four simulation years were provided by a researcher from the Harvard University Atmospheric Chemistry Modeling (ACM) Group (Zhang, 2011, pers. comm.). The version of the model used for this study utilizes the GEOS-5 data product from NASA’sModeling for North American Background Concentrations GEOS-Chem Model Application Methodology



### Global Modeling and Assimilation Office (GMAO) . Data used by GEOS-Chem include surface albedo, parameters defining properties at the surface including moisture content and land type, various precipitation measures, cloud fraction, heat and radiation fluxes, PBL thickness, air temperature, tropopause pressure, ground (skin) temperature, U and V wind components, friction velocity, specific humidity and others. More information can be found at http://wiki.seas.harvard.edu/geos-chem/index.php/Overview_of_GMAO_met_data_products

. 

## Emission Inputs
Baseline emission inputs were also provided by Zhang (2011, pers. comm.). The emission inventories include both anthropogenic and biogenic emissions, and account for fossil fuel combustion and usage, biomass burning, biofuel burning, and natural aerosol emissions. Examples of categories of emissions included are aircraft emissions, shipping emissions, and soil and fertilizer NO x 

### emissions. The emissions also include estimates for NO x 

### generated by lightning. Various sources of data provide global coverage with the more reliable and highly resolved emissions data sour ces taking precedence. For ex ample, the 2005 EPA National Emission Inventory (NEI) inventory is used in order to enhance the emissions estimates over the United States. Temporal resolution for emissions varies depending on data source from annual to seasonal. Within the model, emissions are introduced at hourly intervals. More information on the emissions can be found at http://wiki.seas.harvard.edu/geoschem/index.php/Anthropogenic_emissions

. Anthropogenic emissions were projected to each simulated year using scale factors. Scale factors were developed for each region of the world based on available information. More detailed information and links to additional documents can be found at http://wiki.seas.harvard.edu/geos-chem/index.php/Scale_factors_for_anthropogenic_emissions

. 

## Terrain, Land-Use, Chemis try and Other Inputs
All other inputs for the application of GEOS-Chem were provided by Zhang (2011, pers. comm.). These include Total Ozone Mapping Spectrometer (TOMS) data, surface UV albedo, dry deposition coefficients, and land use codes. Note that roughness lengths and terrain heights are included in the GEOS-5 data. Other files define the chemical mechanism and provide data for calculating photolysis rates.

The leaf area index used for ozone dry deposition was based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Use of MODIS data is expected to result in less ozone dry deposition and higher ozone concentrations compared to the use of Advanced Very High Resolution Radiometer (AVHRR) derived values.

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# 3.4. Model Options and Parameter Specifications

For this application, version 9-01-01 of the GE OS-Chem model was applied. Some of the key options are listed below:

 Linoz stratospheric ozone chemistry was utilized.

 Sulfate, carbon, dust, and sea salt aerosols were included.

 Both wet and dry depositions were simulated.

 Tropospheric chemistry module was enabled.

 Secondary organic aerosols were not included.



# 3.5. Scenarios

This analysis considered the following ozone air quality/emission scenarios for 2006, 2007, and
2008:

1. Current atmosphere—all anthropogenic and natural emissions for sources throughout the modeling domain.

2. North American background—current atmosphere emissions minus anthropogenic emissions for sources in the U.S., Canada, and Mexico.

3. U.S. background—current atmosphere emissions minus anthropogenic emissions for sources in the U.S.

4. Natural background—all natural emissions for sources throughout the modeling domain.

Background methane concentrations vary stepwise by latitude in GEOS-Chem. For the base case simulations, GEOS-Chem has values built-in for the years 2006 and 2007. For 2008 and for each of the other 3 scenarios, new background methane concentrations were supplied by EPA (Dutton, 2011, pers. comm.). The specific values used for background methane concentration are presented in Table 3-2 . NAB O 3 

### corresponds to the North American background scenario.

Table 3-2. Background Methane Concentrations (ppb) in GEOS-Chem Simulations. (a) 2006

Latitude Current Atmosphere U.S. Background North American Background Natural Background

90 S – 30 S 1726.53 1623.49 1582.60 700

30 S – 0 S 1735.17 1631.62 1590.51 700

0 N – 30 N 1796.30 1689.10 1646.55 700

30 N – 90 N 1848.20 1737.90 1694.12 700 Global Average 1776.55 1670.53 1628.45 700

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Latitude Current Atmosphere U.S. Background North American Background Natural Background

90 S – 30 S 1732.52 1629.13 1588.09 700

30 S – 0 S 1741.68 1637.74 1596.48 700

0 N – 30 N 1801.38 1693.88 1651.21 700

30 N – 90 N 1855.55 1744.81 1700.86 700 Global Average 1782.78 1676.39 1634.16 700

(c) 2008

Latitude Current Atmosphere U.S. Background North American Background Natural Background

90 S – 30 S 1740.56 1636.68 1595.45 700

30 S – 0 S 1747.71 1643.41 1602.01 700

0 N – 30 N 1804.09 1696.42 1653.69 700

30 N – 90 N 1857.41 1746.57 1702.57 700 Global Average 1787.44 1680.77 1638.43 700

# 4. Model Performance Evaluation Procedures & Results

The model performance evaluation of the “Current Atmosphere” scenario for the three simulation years is presented in this section of the report. This evaluation focuses primarily on the ability of the GEOS-Chem model to replicate observed ozone and other pollutant concentrations. The evaluation also includes a qualitative assessment of how well the stratospheric-tropospheric exchange is being simulated and an examination of the effects of interannual variability in meteorology on the simulation results.



# 4.1. Comparison with Observed Air Quality Data

There are several monitoring networks with available data for the U.S. corresponding to the time period and species of interest. The networks generally focus on one or more specific pollutants, either air concentrations or deposition, and specific geographic/demographic regions (i.e., urban, rural, protected environments, etc.). In addition, they may utilize different monitoring techniques, measurement periods, and quality assurance/reporting procedures.

For this analysis, we rely primarily on data from the Clean Air Status and Trends Network (CASTNet) and the EPA’s Air Quality System (AQS) databases. The CASTNet database includes air concentration data for ozone, nitrogen dioxide (NO 2 

### ), and sulfur dioxide (SO 2 

### ) as well as deposition data (fluxes) for nitrogen and sulfur. The network consists of more than 120 sites in the U.S. and is primarily intended to monitor air quality in rural areas and areas where urban influences are minimal. For this study, th ese data are used primarily to examine how well the GEOS-Chem model is able to represent non-urban ozone and other pollutant concentrations for selected regions and sites throughout the U.S. The CASTNet data are also used to examine the reasonableness of the modeled dry deposition amounts for sulfur and nitrogen.

The AQS database includes air concentration data for ozone, NO 2 

### , SO 2 

### , carbon monoxide (CO), and particulate matter (PM 10 

### and PM 2.5 

### ). The network is primarily intended to monitor air quality in areas where people live, and, thus, a large proportion of the sites are located in urban and suburban areas. For this study, these data are us ed primarily to examine how well the GEOSChem model is able to represent the range of ozone and other pollutant concentrations that occur throughout the U.S. during the three-year simulation period, as well as the spatial variability of the ozone concentrations.

Statistical and graphical analyses are used to compare the simulated and observed concentrations. Comparisons are presented for the entire U.S., selected subregions, and individual sites representing key areas in the U.S. that have been identified as important in characterizing background ozone (e.g., Zhang and Jacob, 2011). The subregions include the West Coast (WA, OR, CA), the Intermountain West (ID, MT, WY, NV, UT, CO, AZ, NM), the Central States (ND, SD, MN, NE, IA, KS, MO, OK, AR, TX, LA), the Great Lakes region (WI, IL, IN, OH, MI), the Southeast (KY, WV, VA, TN, NC, SC, MS, AL, GA, FL) and the Northeast (ME, NH, VT, MA, RI, CT, NY, PA, NJ, DE, MD, DC). A variety of graphical and statistical measures and a range of averaging times (daily, mont hly, seasonal, etc.) are considered.

The statistical measures are listed and defined in Table 4-1

.

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11-035 Table 4-1. Definition and Description of Measures/Metrics for GEOS-Chem Model Performance Evaluation.

Metric Definition

# of data pairs The number of observation/simulation data pairs

Mean observation value The average observed concentration

Mean simulation value The average simulated concentration

Mean residual 

# ∑

− ⎟ ⎞ ⎜ ⎛ N 

### OS )( 1

= 

### ⎠⎝ l ll



### N 1 where N is the number of data pairs, and S l and O l are the simulated and observed values at site l, respectively, over a given time interval.

Mean unsigned error 

# ∑

= 

### ⎠ ⎝ l ll



### N 1 

### − ⎟ ⎞ ⎜ ⎛ N 

### OS

1

Normalized bias 

### %100)( 1

1 

### ⎠⎝

= l lll 

### N ⋅− ⎟ ⎞ ⎜ ⎛ 

# ∑ N 

### OOS

Normalized gross error 

### %100 1

1 

### ⎠⎝

= l lll 

### N ⋅− ⎟ ⎞ ⎜ ⎛ 

# ∑ N 

### OOS

Fractional bias 

### %100)(5.0)( 1

1 

### ⎠⎝

= l ll ll 

### N ⋅+

− ⎟ ⎞ ⎜ ⎛ 

# ∑ N 

### OSOS

Fractional error 

### %100)(5.0 1 ⋅+

− ⎟ ⎞ ⎜ ⎛ 

# ∑ N 

### OSOS

1 

### ⎠⎝

= l ll ll 

### N

Coefficient of Determination (R 2 ) R 2 is the square of the correlation (R), which is defined as the sample covariance between two datasets divided by the product of the standard deviations for each dataset



### In calculating the statistical measures, t he GEOS-Chem model output was paired with the observed data for the appropriate locations (grid cells) and time intervals.


## Summary Model Performance Results for 2006
In this section, the GEOS-Chem results for 2006 are compared to observed data for ozone, other gaseous species, fine particulate matter, and dry deposition.



### Ozone
Two metrics were used for the calculation of statistical measures for ozone: 24-hour average ozone and maximum daily 8-hour average (MDA8) ozone. MDA8 is also used for the National Ambient Air Quality Standard (NAAQS) for 8-hour ozone.

Among the datasets available for this study, the CASTNet dataset is best suited to the evaluation of model performance for ozone since the network is designed to monitor rural or background ozone concentrations that are not driven by local urban-scale sources. TheModeling for North American Background Concentrations Model Performance Evaluation Procedures & Results

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### CASTNet data are expected to be reasonably consistent with the spatial and temporal scales simulated by the GEOS-Chem model.

Table 4-2 lists the seasonal and annual performance metrics for 24-hour average ozone for the entire U.S. and each of the six model performance subregions for 2006, calculated using the CASTNet data. Units are ppb.Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsTable 4-2. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case(Current Atmosphere Scenario) Using CASTNet Data: 2006.(a) Entire Continental U.S.TimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)6,90029.3430.781.456.2513.2029.604.6024.500.510Spring(Mar-May)7,21741.9345.353.417.8213.8022.709.2019.000.271Summer(Jun-Aug)6,98241.0551.9810.9313.0536.8040.6025.8030.000.305Fall(Sep-Nov)7,00029.6239.289.6611.3148.7053.4030.1035.500.334Annual28,09935.5541.916.359.6028.0036.5017.4027.200.428ICF International14October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(b) West CoastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)78832.6236.924.309.0932.7044.1017.8030.500.194Spring(Mar-May)81442.3744.311.949.3114.8029.008.0023.900.379Summer(Jun-Aug)80048.8953.194.3010.1117.2027.5010.9022.400.634Fall(Sep-Nov)78136.5443.316.7710.2546.9054.1024.1032.000.493Annual3,18340.1644.474.309.6927.7038.5015.1027.100.537(c) Intermountain WestTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,11740.4539.86-0.595.306.0019.500.4015.100.331Spring(Mar-May)1,18650.0647.53-2.536.25-1.8014.50-4.0013.700.319Summer(Jun-Aug)1,12148.9452.593.657.2211.7018.008.7015.600.295Fall(Sep-Nov)1,16638.8542.894.046.4317.7023.2011.7017.600.289Annual4,59044.6045.721.126.308.4018.804.1015.500.396ICF International15October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(d) Central StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)73330.2731.160.896.1710.0026.702.9022.700.303Spring(Mar-May)72840.3042.612.317.2313.7023.908.0019.100.194Summer(Jun-Aug)73840.6148.928.3211.1134.1039.5021.9027.800.219Fall(Sep-Nov)78330.3836.516.138.5531.1038.1019.9027.700.285Annual2,98235.3139.764.458.2822.4032.2013.3024.400.348(e) Great Lakes StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,11622.1521.10-1.054.81-2.5026.20-9.3027.700.624Spring(Mar-May)1,14437.0842.385.307.3017.4022.5013.2018.700.341Summer(Jun-Aug)1,08337.6154.7017.0817.3649.4050.0036.5037.100.245Fall(Sep-Nov)1,09522.7831.839.0610.5644.4050.9029.3037.300.404Annual4,43829.9337.437.519.9326.9037.2017.2030.000.566ICF International16October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsICF International17October 28, 201111-035(f) SoutheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,86428.3431.853.516.9621.5031.8013.0024.800.291Spring(Mar-May)1,99642.1248.126.008.7719.8025.2014.5020.500.215Summer(Jun-Aug)1,97639.1052.4513.3514.9847.3050.1032.2035.300.151Fall(Sep-Nov)1,87129.1342.9313.8014.4663.6065.5040.1042.200.249Annual7,70734.8644.049.1811.3137.9043.0024.9030.600.321(g) NortheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,28224.8125.740.945.6010.9031.001.1026.900.557Spring(Mar-May)1,34939.2543.934.687.6714.9022.0010.8018.500.231Summer(Jun-Aug)1,26435.3549.4114.0614.4745.7046.6033.5034.500.490Fall(Sep-Nov)1,30423.2336.3313.1014.0670.4074.1042.6047.400.261Annual5,19930.7238.878.1510.4135.3043.3021.9031.700.461Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results



### Based on the 24-hour average ozone metric, ozone is overestimated for most regions and time periods. The greatest amount of overestimation tends to occur during the summer months (June–August) for the eastern portion of the U.S. and during the autumn months (September– November) for the western portion of the U.S. Considering all periods and regions, the best agreement with the observations tends to occu r during the spring months (March–May). Among the subregions, the best performance for 24-hour ozone is achieved for the Intermountain West subregion for which the normalized bias ranges from approximately -2 to 18 percent.

Table 4-3 lists the seasonal and annual performance metrics for maximum daily 8-hour average (MDA8) ozone for the entire U.S. and each of the six model performance subregions for 2006, calculated using the CASTNet data. Units are ppb.

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11-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsTable 4-3. Seasonal and Annual GEOS-CHEM Model Performance Statistics for Maximum Daily 8-hour Average (MDA8) Ozone Concentration (ppb) for the Base Case(Current Atmosphere Scenario) Using CASTNet Data: 2006.(a) Entire Continental U.S.TimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)6,92035.2837.872.595.6512.1020.807.5017.600.536Spring(Mar-May)7,28251.0054.973.977.3610.4016.407.9014.200.396Summer(Jun-Aug)7,05853.3664.6611.3013.6326.5030.1019.8023.700.373Fall(Sep-Nov)7,08438.2548.8410.6011.7435.3037.9025.3028.200.445Annual28,34444.5651.687.119.6021.1026.2015.1020.900.545ICF International19October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(b) West CoastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)79638.3543.274.936.9821.7026.2014.7019.500.393Spring(Mar-May)82151.8753.401.537.396.4016.204.0014.700.564Summer(Jun-Aug)81262.9166.613.7111.518.9020.105.6018.000.618Fall(Sep-Nov)79045.9852.576.589.8624.8030.1016.8022.500.575Annual3,21949.8654.024.168.9315.3023.1010.2018.600.646(c) Intermountain WestTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,12144.1944.570.384.303.7012.001.8010.600.410Spring(Mar-May)1,19256.1554.62-1.525.25-1.509.70-2.409.700.349Summer(Jun-Aug)1,13157.1560.773.617.047.6013.006.2012.200.314Fall(Sep-Nov)1,17444.4649.575.106.3913.7016.4011.4014.200.411Annual4,61850.5252.401.885.755.9012.804.2011.700.517ICF International20October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(d) Central StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)73036.2437.551.315.186.7017.303.4015.600.398Spring(Mar-May)73449.2550.871.626.546.9015.804.4014.000.329Summer(Jun-Aug)74351.8860.078.1911.1423.3028.2016.2021.500.253Fall(Sep-Nov)79439.2044.645.447.3819.0023.6013.8019.000.552Annual3,00144.0848.264.187.5714.1021.309.6017.600.507(e) Great Lakes StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,11528.0829.281.214.987.2021.702.6020.800.555Spring(Mar-May)1,15946.9954.017.028.3217.1019.7013.7016.500.473Summer(Jun-Aug)1,09152.1270.3718.2518.7238.6039.5029.3030.300.324Fall(Sep-Nov)1,11031.9743.4811.5012.3639.9042.8029.0032.500.594Annual4,47539.8049.229.4211.0325.5030.8018.6024.900.672ICF International21October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsICF International22October 28, 201111-035(f) SoutheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,87335.8839.924.046.3016.8022.3011.8017.900.398Spring(Mar-May)2,01752.6358.395.767.6513.9017.1011.1014.400.375Summer(Jun-Aug)2,00251.7064.5612.8514.2331.6033.6023.8026.000.271Fall(Sep-Nov)1,89039.2352.9313.7014.0142.0042.7031.0031.700.448Annual7,78245.1154.219.1010.5626.0028.8019.4022.400.493(g) NortheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,28530.4333.302.875.8814.2024.208.3020.600.413Spring(Mar-May)1,35947.9254.196.278.3514.5018.6011.4015.800.437Summer(Jun-Aug)1,27948.4764.8216.3516.9437.9039.1028.4029.700.594Fall(Sep-Nov)1,32631.4147.1615.7616.4357.0059.0038.6041.100.392Annual5,24939.6049.8910.2911.8830.9035.2021.7026.700.576Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results



### For 2006, MDA8 ozone is overestimated for nearly all regions and time periods but the bias and error statistics suggest reasonably good performanc e. Model performance varies by season and by subregion. Overestimation of ozone during the summer and autumn months is prevalent in the eastern U.S. (Central States, Great Lakes, Southeast, and Northeast subregions). For the western subregions, there is less overestimation of ozone and overall good agreement with the observations.

The best agreement with the observations is achieved for the Intermountain West subregion. The normalized bias for this subregion for the annual period is 5.9 percent, while the corresponding gross error is 12.8 percent. The fractional bias is 4.2 percent and the corresponding fractional error is 11.7 percent.

For the entire U.S., the mean residual or difference between the simulated and observed values ranges from approximately 2.6 to 11.3 ppb for the four seasonal periods and is 7.1 for the annual period. The normalized bias for the annual period is 21.1 percent, while the corresponding gross error is 26.2 percent. The fractional bias is 15.1 percent and the corresponding fractional error is 20.9 percent. Figure 4-1 displays the agreement between the mean simulated and observed MDA8 concentrations for the seasonal and annual periods for the entire U.S.

Figure 4-1. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb ) for Each Season and the Entire Year, Averaged Over All Sites in Entire Continental U.S.: 2006.

Seasonal & Annual Mean Ozone Concentration (ppb)

25 35 45 55 65 75

25 35 45 55 65 75
ObservedGEOS-Chem

Spring Summer Fall Winter Annual



### A subset of the CASTNet sites was selected for a more detailed comparison of the simulated and observed MDA8 ozone concentrations. For each subregion, four sites were selected based on data availability, location within the subregion, and elevation. The criteria used to select the sites included good data coverage for all three modeled years and representation of different portions of each subregion and a range of elevations, as appropriate.

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### Time-series and scatter plots illustrating site-specific model performance for MDA8 ozone concentration for the West Coast subregion are provided in Figure 4-2 . The West Coast sites (listed in order of elevation) are: Pinnacles National Monument (NM), CA (elevation 335 meters (m)) Mount Rainier National Park (NP), WA (elevation 415 m), Joshua Tree NM, CA (elevation 1244 m), and Lassen Volcanic NP, CA (elevation 1756 m). In the time series plots, the observed values are in blue and the simulated values are in green. The range scale used for MDA8 ozone is 0 to 100 ppb, with a few exceptions.

Figure 4-2. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the West Coast Subregion: 2006. (a) Pinnacles NM

CASTNet Site Pinnacles NM, CA (PIN414) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Pinnacles NM, CA (PIN414) MDA8: 2006

R 2 = 0.5112

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100Simulated

Observed

(b) Mount Rainier NP

CASTNet Site Mount Rainier NP, WA (MOR409) MDA8: 2006

R 2 = 0.5498

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated CASTNet Site Mount Rainier NP, WA (MOR409) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs SimModeling for North American Background Concentrations Model Performance Evaluation Procedures & Results

(c) Joshua Tree NM

CASTNet Site Joshua Tree NM, CA (JOT403) MDA8: 2006

0 20 40 60 80 100 120 140

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Joshua Tree NM, CA (JOT403) MDA8: 2006

R 2 = 0.7288

0 20 40 60 80 100 120 140

0 20 40 60 80 100 120 140

ObservedSimulated

(d) Lassen Volcanic NP

CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2007

R 2 = 0.4956

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100 110

ObservedSimulated



### Time-series and scatter plots for the Intermountain West subregion are provided in Figure 4-3

. The Intermountain West sites are: Chiricahua NM, AZ (elevation 1570 m), Great Basin NP, NV (elevation 2060 m), Pinedale, WY (elevation 2388 m), and Rocky Mountain NP, CO (elevation 2743 m).

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Figure 4-3. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Intermoun tain West Subregion: 2006. (a) Chiricahua NM

CASTNet Site Chiricahua NM, AZ (CHA467) MDA8: 2006

R 2 = 0.4144

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated CASTNet Site Chiricahua NM, AZ (CHA467) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim

(b) Great Basin NP

CASTNet Site Great Basin NP, NV (GRB411) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Great Basin NP, NV (GRB411) MDA8: 2006

R 2 = 0.5271

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Pinedale

CASTNet Site Pinedale, WY (PND165) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Pinedale, WY (PND165) MDA8: 2006

R 2 = 0.5716

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(d) Rocky Mountain NP

CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: 2006

R 2 = 0.4177

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Central States subregion are provided in Figure 4-4 . The Central States sites are: Caddo Valley, AR (elevation 71 m), Konza Prairie, KS (elevation 348 m), Theodore Roosevelt NP, ND (elevation 850 m), and Big Bend NP, TX (elevation 1052 m).

Figure 4-4. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in Central States Subregion: 2006. (a) Caddo Valley

CASTNet Site Caddo Valley, AR (CAD150) MDA8: 2006

R 2 = 0.5406

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated CASTNet Site Caddo Valley, AR (CAD150) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim

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(b) Konza Prairie

CASTNet Site Konza Prairie, KS (KNZ184) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Konza Prairie, KS (KNZ184) MDA8: 2006

R 2 = 0.7493

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Theodore Roosevelt NP

CASTNet Site Theodore Roosevelt NP, ND (THR422) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Theodore Roosevelt NP, ND (THR422) MDA8: 2006

R 2 = 0.6613

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Big Bend NP

CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2006

R 2 = 0.3867

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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### Time-series and scatter plots for the Great Lakes subregion are provided in Figure 4-5 . The Great Lakes sites are: Salamonie Reservoir, IN (elevation 250 m), Ann Arbor, MI (elevation 267 m), Oxford, OH (elevation 284 m), and Perkinstown, WI (elevation 472 m).

Figure 4-5. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Great Lakes Subregion: 2006. (a) Salamonie Reservoir

CASTNet Site Salamonie Reservoir, IN (SAL133) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Salamonie Reservoir, IN (SAL133) MDA8: 2006

R 2 = 0.6938

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(b) Ann Arbor

CASTNet Site Unionville, MI (ANA115) MDA8: 2006

R 2 = 0.7056

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated CASTNet Site Unionville, MI (ANA115) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim

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(c) Oxford

CASTNet Site Oxford, OH (OXF122) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Oxford, OH (OXF122) MDA8: 2006

R 2 = 0.6417

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120

ObservedSimulated

(d) Perkinstown

CASTNet Site Perkinstown, WI (PRK134) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Perkinstown, WI (PRK134) MDA8: 2006

R 2 = 0.6848

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Southeast subregion are provided in Figure 4-6 . The Southeast sites are: Sumatra, FL (elevation 14 m), Cadiz, KY (elevation 189 m), Sand Mountain, AL (elevation 352 m), and Great Smoky Mountain NP, TN (elevation 793 m).

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Figure 4-6. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Southeast Subregion: 2006. (a) Sumatra

CASTNet Site Sumatra, FL (SUM156) MDA8: 2006

R 2 = 0.387

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated CASTNet Site Sumatra, FL (SUM156) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim

(b) Cadiz

CASTNet Site Cadiz, KY (CDZ171) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Cadiz, KY (CDZ171) MDA8: 2006

R 2 = 0.5638

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Sand Mountain

CASTNet Site Sand Mountain, AL (SND152) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Sand Mountain, AL (SND152) MDA8: 2006

R 2 = 0.7116

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(d) Great Smoky Mountain NP

CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2006

R 2 = 0.6712

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Northeast subregion are provided in Figure 4-7 . The Northeast sites are Blackwater National Wildlife Refuge (NWR), MD (elevation 4 m), Acadia NP, ME (elevation 158 m), Penn State, PA (elevation 378 m), and Huntington Wildlife Forest, NY (elevation 502 m).

Figure 4-7. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Northeast Subregion: 2006. (a) Blackwater NWR

CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2006

R 2 = 0.7252

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120

ObservedSimulated CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim

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(b) Acadia NP

CASTNet Site Acadia NP, ME (ACA416) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Acadia NP, ME (ACA416) MDA8: 2006

R 2 = 0.4467

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120 130

ObservedSimulated

(c) Penn State

CASTNet Site Penn State, PA (PSU106) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Penn State, PA (PSU106) MDA8: 2006

R 2 = 0.6058

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Huntington Wildlife Forest

CASTNet Site Huntington Wildlife Forest, NY (HWF187) MDA8: 2006

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Huntington Wildlife Forest, NY (HWF187) MDA8: 2006

R 2 = 0.4047

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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### For the more urban sites included in the AQS network, only 24-hour average ozone was considered. Due to the relatively coarse grid resolution used for both the emissions and the modeling, some of the diurnal features of urban-scale ozone concentrations (including high daytime peaks and near zero concentrations at night) are not well simulated and model performance is worse than for the CASTNet sites. The 24-hour ozone concentrations are overestimated for all subregions and periods.

Table 4-4 lists the seasonal and annual performance metrics for 24-hour average ozone for the entire U.S. and each of the six model performance subregions for 2006, calculated using the AQS data. Normalized bias and error statistics are not included in this table since they are not applicable for very low concentrations, such as those that sometimes characterize urban-scale ozone. Units are ppb.

Table 4-4. Seasonal and Annual GEOS-CHEM Model Performa nce Statistics for 24-hour Av erage Ozone Concentration (ppb) for the Base Case (Current Atmosp here Scenario) Using AQS Data: 2006. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 50,917 22.11 31.12 9.02 10.62 38.30 45.40 0.258

Spring (Mar-May) 89,599 35.34 44.46 9.12 10.85 24.20 28.50 0.215

Summer (Jun-Aug) 106,135 35.68 51.49 15.81 16.83 37.60 40.10 0.251

Fall (Sep-Nov) 82,734 25.19 40.84 15.65 16.18 49.90 51.50 0.271

Annual 329,385 30.85 43.75 12.90 14.08 37.10 40.60 0.345

(b) West Coast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 14,320 20.05 32.33 12.27 13.47 55.50 59.30 0.194

Spring (Mar-May) 15,774 33.65 40.43 6.78 9.93 18.90 27.60 0.234

Summer (Jun-Aug) 17,753 36.98 47.45 10.47 13.77 22.30 31.20 0.311

Fall (Sep-Nov) 16,442 27.24 41.14 13.90 15.05 44.80 47.70 0.292

Annual 64,289 29.90 40.74 10.84 13.09 34.60 40.80 0.334

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,813 24.85 35.96 11.11 12.62 44.70 48.90 0.143

Spring (Mar-May) 10,809 39.23 45.44 6.21 9.23 16.80 23.50 0.162

Summer (Jun-Aug) 12,560 42.57 52.74 10.17 11.59 22.40 25.30 0.154

Fall (Sep-Nov) 10,876 27.98 42.64 14.66 15.25 45.30 46.80 0.112

Annual 43,058 34.42 44.92 10.50 12.13 31.30 35.10 0.316

(d) Central States

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 12,193 23.20 29.08 5.88 7.66 25.20 32.80 0.295

Spring (Mar-May) 16,192 34.40 41.86 7.47 8.88 21.60 25.00 0.333

Summer (Jun-Aug) 17,933 35.28 50.33 15.05 15.67 39.00 40.30 0.436

Fall (Sep-Nov) 15,546 26.52 37.97 11.45 12.00 37.50 39.30 0.429

Annual 61,864 30.47 40.82 10.35 11.39 31.30 34.60 0.469

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,991 17.03 19.22 2.20 4.70 10.90 32.20 0.697

Spring (Mar-May) 12,164 33.28 44.26 10.98 11.81 29.60 31.70 0.207

Summer (Jun-Aug) 17,151 34.37 55.03 20.66 20.78 46.40 46.60 0.187

Fall (Sep-Nov) 9,998 20.59 36.75 16.16 16.39 55.80 57.10 0.366

Annual 42,304 29.57 45.08 15.51 16.02 41.30 43.80 0.416

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(f) Southeast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 7,287 25.04 37.01 11.98 12.78 41.10 43.80 0.194

Spring (Mar-May) 21,817 36.63 48.84 12.21 13.05 30.30 32.20 0.182

Summer (Jun-Aug) 24,048 33.69 52.53 18.84 19.27 46.60 47.40 0.199

Fall (Sep-Nov) 18,264 25.85 46.20 20.35 20.49 58.80 59.20 0.220

Annual 71,416 31.70 48.20 16.50 17.02 44.20 45.40 0.238

(g) Northeast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,313 19.58 23.06 3.48 6.59 21.70 39.70 0.521

Spring (Mar-May) 12,843 35.27 44.71 9.44 11.12 24.20 28.50 0.183

Summer (Jun-Aug) 16,690 33.90 51.09 17.19 17.68 41.60 42.70 0.378

Fall (Sep-Nov) 11,608 20.95 37.77 16.82 17.25 58.00 60.10 0.251

Annual 46,454 29.40 42.79 13.39 14.49 38.60 42.80 0.415



### NO 2 

### , SO 2 

### , CO, and PM 2.5 

### NO 2 

### , SO 2 

### , CO and PM 2.5 

### data from the AQS network were also used to examine model performance for these species. NO 2 

### , SO 2 

### , CO concentrations at the urban AQS sites are typically characterized by diurnal profiles that reflect subgrid-scale traffic and activity patterns within the urban area. Concentrations can vary considerably in time and space. Due in part to the relatively coarse grid resolution used for both the emissions and the modeling, the spatial and temporal variability of these species are not captured. Nevertheless, simulated and observed 24-hour average concentrations for th ese species are examined and compared. PM 2.5 

### is a secondary pollutant and is characterized by concentration patterns that are less variable in time and space. A key regulatory metric for PM 2.5 

### is 24-hour average PM 2.5 

### , thus this metric is also used for the statistical calculations for PM 2.5


### .

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### Table 4-5 lists the seasonal and annual performance metrics for 24-hour average NO 2 

### for the entire U.S. and each of the six model performance subregions for 2006, calculated using the AQS data. Normalized bias and error statistics are not included in this table since they are not applicable for very low concentrations, such as those found in the NO 2 

### , SO 2 

### , and CO data. Units are ppb.

Table 4-5. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average NO 2 Concentration (ppb) for the Base Case (Current Atmosphere Scenario): 2006. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 33,487 14.84 7.56 -7.28 8.29 -54.80 73.90 0.283

Spring (Mar-May) 35,436 10.54 5.15 -5.39 6.19 -57.40 77.20 0.307

Summer (Jun-Aug) 36,115 9.35 5.00 -4.35 5.41 -50.10 74.30 0.263

Fall (Sep-Nov) 34,446 12.66 6.16 -6.50 7.35 -58.80 76.70 0.296

Annual 139,484 11.79 5.94 -5.85 6.78 -55.20 75.50 0.312

(b) West Coast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,877 17.38 6.99 -10.39 10.86 -80.90 90.60 0.317

Spring (Mar-May) 9,037 10.72 5.21 -5.51 6.16 -69.80 82.00 0.340

Summer (Jun-Aug) 9,004 11.07 5.43 -5.64 6.28 -67.40 78.70 0.416

Fall (Sep-Nov) 8,762 16.25 6.13 -10.12 10.42 -86.80 92.70 0.354

Annual 35,680 13.82 5.93 -7.89 8.41 -76.10 86.00 0.359

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,105 16.55 4.42 -12.14 12.38 -93.00 113.60 0.496

Spring (Mar-May) 4,452 10.17 3.15 -7.03 7.30 -80.50 106.20 0.487

Summer (Jun-Aug) 4,641 8.36 3.13 -5.23 5.54 -74.80 97.10 0.372

Fall (Sep-Nov) 4,404 12.05 3.66 -8.39 8.66 -82.70 105.10 0.458

Annual 17,602 11.65 3.57 -8.09 8.36 -82.50 105.30 0.469

(d) Central States

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,078 10.50 6.68 -3.82 5.31 -29.50 59.70 0.256

Spring (Mar-May) 8,368 7.59 4.80 -2.79 4.09 -30.40 61.60 0.203

Summer (Jun-Aug) 8,385 6.88 5.79 -1.09 3.83 -11.90 59.50 0.118

Fall (Sep-Nov) 8,326 9.29 6.13 -3.17 4.74 -28.20 59.30 0.242

Annual 33,157 8.55 5.84 -2.71 4.48 -24.90 60.00 0.215

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 1,751 16.86 11.66 -5.20 6.17 -29.30 41.80 0.449

Spring (Mar-May) 1,952 15.58 7.56 -8.02 8.34 -59.30 66.10 0.460

Summer (Jun-Aug) 2,081 13.08 6.21 -6.87 7.27 -60.00 68.80 0.346

Fall (Sep-Nov) 1,866 15.47 9.40 -6.07 6.55 -43.50 51.60 0.489

Annual 7,650 15.17 8.58 -6.59 7.11 -48.80 57.70 0.408

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(f) Southeast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,631 11.47 7.25 -4.22 5.56 -33.50 58.80 0.320

Spring (Mar-May) 4,967 9.36 4.62 -4.74 5.46 -53.40 72.80 0.212

Summer (Jun-Aug) 4,996 7.75 4.01 -3.73 4.49 -42.40 71.40 0.144

Fall (Sep-Nov) 4,847 10.01 5.41 -4.60 5.46 -49.00 69.00 0.276

Annual 19,441 9.61 5.29 -4.32 5.23 -44.70 68.10 0.277

(g) Northeast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,045 17.84 10.84 -6.99 8.41 -46.40 60.90 0.299

Spring (Mar-May) 6,660 13.65 6.62 -7.02 8.01 -59.70 76.20 0.255

Summer (Jun-Aug) 7,008 10.81 5.14 -5.66 6.19 -57.70 73.10 0.349

Fall (Sep-Nov) 6,241 13.83 7.70 -6.13 7.29 -54.00 69.30 0.300

Annual 25,954 13.90 7.47 -6.43 7.44 -54.70 70.10 0.333



### For 2006, the 24-hour average NO 2 

### concentrations are underestimated for all subregions and time periods. Model performance is worst for the West Coast and Intermountain West subregions. Elsewhere, the fractional bias indicates that the modeled values are within a factor of two (67 percent) of the observed values.

Table 4-6 lists the seasonal and annual performance metrics for 24-hour average SO 2 

### for the entire U.S. and each of the six model performance subregions for 2006, calculated using the AQS data. Units are ppb.

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Table 4-6. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average SO 2 Concentration (ppb) for the Base Case (Current Atmosphere Scenario): 2006. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 42,217 4.13 6.12 1.99 3.97 49.40 88.80 0.178

Spring (Mar-May) 43,555 3.15 4.41 1.27 3.06 51.90 93.80 0.127

Summer (Jun-Aug) 42,983 2.69 4.45 1.76 3.06 63.50 97.80 0.131

Fall (Sep-Nov) 42,583 3.07 5.21 2.14 3.59 65.00 97.50 0.150

Annual 171,338 3.25 5.04 1.79 3.41 57.50 94.50 0.157

(b) West Coast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,142 1.46 1.60 0.14 1.06 33.70 86.20 0.152

Spring (Mar-May) 3,302 1.07 1.28 0.21 0.99 60.30 105.10 0.066

Summer (Jun-Aug) 3,306 1.36 1.54 0.18 0.99 51.20 92.00 0.144

Fall (Sep-Nov) 3,270 1.40 1.62 0.22 1.00 40.20 87.50 0.208

Annual 13,020 1.32 1.51 0.19 1.01 46.50 92.80 0.144

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,856 2.64 0.94 -1.70 2.17 -30.40 111.20 0.009

Spring (Mar-May) 2,926 1.85 0.77 -1.07 1.60 -4.00 120.40 0.032

Summer (Jun-Aug) 2,938 1.82 0.80 -1.02 1.52 -9.20 113.70 0.015

Fall (Sep-Nov) 2,834 2.05 0.87 -1.18 1.63 -13.40 108.10 0.052

Annual 11,554 2.09 0.84 -1.24 1.73 -14.10 113.40 0.026

(d) Central States

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,766 2.24 3.23 0.98 2.67 72.40 106.30 0.033

Spring (Mar-May) 9,075 2.04 2.52 0.48 2.22 70.20 110.60 0.032

Summer (Jun-Aug) 8,931 1.66 2.93 1.27 2.36 87.40 115.40 0.053

Fall (Sep-Nov) 8,813 1.98 3.06 1.07 2.58 82.10 113.50 0.058

Annual 35,585 1.98 2.93 0.95 2.45 78.00 111.40 0.041

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,075 4.83 8.69 3.86 5.42 71.50 87.60 0.064

Spring (Mar-May) 8,327 4.18 6.51 2.33 4.18 62.80 86.20 0.064

Summer (Jun-Aug) 8,180 3.46 6.52 3.06 4.37 75.90 95.10 0.025

Fall (Sep-Nov) 8,205 3.83 7.86 4.04 5.15 83.70 98.50 0.094

Annual 32,787 4.07 7.39 3.31 4.77 73.50 91.80 0.067

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(f) Southeast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,629 4.28 7.11 2.83 4.71 70.20 89.40 0.084

Spring (Mar-May) 9,891 3.58 5.55 1.97 3.73 65.20 89.30 0.088

Summer (Jun-Aug) 9,636 3.15 5.48 2.33 3.70 72.60 94.60 0.091

Fall (Sep-Nov) 9,494 3.66 6.18 2.53 4.21 73.80 94.90 0.119

Annual 38,650 3.67 6.08 2.41 4.09 70.40 92.00 0.099

(g) Northeast

Time Period # Data Pairs Mean Observed

(ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned

Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,749 6.57 9.15 2.58 4.85 30.30 64.00 0.197

Spring (Mar-May) 10,034 4.01 5.73 1.72 3.44 37.50 73.90 0.149

Summer (Jun-Aug) 9,992 3.29 5.52 2.23 3.25 57.80 81.90 0.224

Fall (Sep-Nov) 9,967 3.89 6.90 3.01 4.27 61.50 83.10 0.147

Annual 39,742 4.43 6.81 2.38 3.95 46.80 75.80 0.208



### For 2006, model performance for 24-hour average SO 2 

### concentrations varies by subregion. SO 2 

### is underestimated in the Intermountain West, where observed values are low and overestimated elsewhere, including in the East where observed values are higher. For three of the subregions (West Coast, Intermountain West, and Northeast), the fractional bias values indicate that the modeled values are within a factor of two (67 percent) of the observed values. For the remaining three subregions, the bias values are generally somewhat higher than this threshold. The R 2


### values for SO 2 

### are very low.

Table 4-7 lists the seasonal and annual performance metrics for 24-hour average CO for the entire U.S. and each of the six model performance subregions for 2006, calculated using the AQS data. Units are parts per million (ppm).

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Table 4-7. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average CO Concentration (ppm) for the Base Case (Current Atmosphere Scenario): 2006. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 32,771 0.58 0.27 -0.31 0.37 -51.50 78.50 0.015

Spring (Mar-May) 32,816 0.42 0.23 -0.19 0.24 -39.70 69.80 0.026

Summer (Jun-Aug) 31,289 0.38 0.23 -0.15 0.21 -27.90 69.50 0.017

Fall (Sep-Nov) 31,633 0.48 0.24 -0.24 0.29 -43.00 76.60 0.043

Annual 128,509 0.47 0.24 -0.22 0.28 -40.60 73.60 0.032

(b) West Coast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 7,459 0.69 0.27 -0.42 0.44 -68.50 83.00 0.107

Spring (Mar-May) 7,613 0.43 0.24 -0.18 0.23 -39.30 64.00 0.052

Summer (Jun-Aug) 6,994 0.35 0.24 -0.11 0.20 -23.10 70.00 0.032

Fall (Sep-Nov) 6,677 0.51 0.26 -0.25 0.30 -46.70 74.80 0.073

Annual 28,743 0.50 0.25 -0.24 0.29 -44.70 72.90 0.070

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,475 0.74 0.19 -0.55 0.56 -98.80 106.10 0.124

Spring (Mar-May) 5,824 0.42 0.17 -0.26 0.27 -64.90 84.80 0.099

Summer (Jun-Aug) 5,167 0.34 0.17 -0.17 0.21 -41.70 77.70 0.007

Fall (Sep-Nov) 6,055 0.53 0.17 -0.36 0.38 -75.10 94.20 0.084

Annual 23,521 0.52 0.17 -0.34 0.36 -71.80 91.50 0.101

(d) Central States

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,469 0.40 0.22 -0.18 0.26 -28.30 79.90 0.013

Spring (Mar-May) 4,691 0.34 0.19 -0.15 0.21 -29.00 77.50 0.002

Summer (Jun-Aug) 4,436 0.31 0.18 -0.12 0.19 -21.60 79.90 0.003

Fall (Sep-Nov) 4,482 0.35 0.19 -0.16 0.23 -25.20 82.50 0.003

Annual 18,078 0.35 0.19 -0.15 0.22 -26.10 80.00 0.000

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,298 0.47 0.36 -0.11 0.24 -19.20 56.00 0.004

Spring (Mar-May) 3,383 0.45 0.27 -0.19 0.25 -35.70 62.60 0.000

Summer (Jun-Aug) 3,330 0.41 0.26 -0.14 0.21 -26.60 60.10 0.000

Fall (Sep-Nov) 3,288 0.47 0.29 -0.18 0.25 -32.60 63.20 0.022

Annual 13,299 0.45 0.29 -0.16 0.24 -28.60 60.50 0.006

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(f) Southeast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,241 0.56 0.27 -0.29 0.33 -51.30 70.10 0.025

Spring (Mar-May) 5,205 0.47 0.23 -0.24 0.28 -46.50 69.20 0.000

Summer (Jun-Aug) 5,155 0.47 0.24 -0.23 0.26 -52.90 66.60 0.001

Fall (Sep-Nov) 5,067 0.54 0.24 -0.30 0.32 -56.60 73.20 0.018

Annual 20,668 0.51 0.24 -0.27 0.30 -51.80 69.80 0.012

(g) Northeast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned

Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,829 0.49 0.37 -0.12 0.24 -10.20 59.00 0.194

Spring (Mar-May) 6,100 0.41 0.28 -0.13 0.20 -16.90 58.40 0.176

Summer (Jun-Aug) 6,207 0.38 0.29 -0.08 0.19 -2.50 59.60 0.110

Fall (Sep-Nov) 6,064 0.43 0.31 -0.13 0.22 -10.60 64.30 0.213

Annual 24,200 0.43 0.31 -0.11 0.21 -10.00 60.30 0.190



### For 2006, CO concentrations are underestimated for all regions and time periods. The modeled values exhibit less seasonal variation than the observed values and this results in very low correlation (R 2 

### ). The best performance for CO is for the Northeast subregion. The worst performance is for the West and Intermountain West subregions for the wintertime period.

Table 4-8 lists the seasonal and annual performance metrics for 24-hour average PM 2.5 

### for the entire U.S. and each of the six model performance subregions for 2006, calculated using the AQS data. Units are micrograms per cubic meter ( μ gm -3 

### ).

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Table 4-8. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average PM 2.5

Concentration ( μ gm -3

) for the Base Case (Current At mosphere Scenario): 2006. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 35,399 11.21 9.88 -1.34 5.24 -13.30 49.00 0.116

Spring (Mar-May) 34,570 10.54 11.35 0.81 4.68 10.50 43.50 0.179

Summer (Jun-Aug) 33,872 14.13 9.62 -4.51 7.43 -42.00 61.00 0.080

Fall (Sep-Nov) 33,477 10.79 9.93 -0.86 4.83 -10.50 47.60 0.223

Annual 137,318 11.66 10.20 -1.46 5.54 -13.70 50.20 0.117

(b) West Coast

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,658 16.03 6.61 -9.41 10.88 -66.70 81.30 0.018

Spring (Mar-May) 3,305 8.72 9.91 1.19 4.09 12.10 44.30 0.410

Summer (Jun-Aug) 3,039 11.01 7.16 -3.85 4.82 -41.20 53.20 0.181

Fall (Sep-Nov) 3,352 12.96 8.25 -4.71 6.89 -41.70 60.10 0.047

Annual 13,354 12.31 7.96 -4.34 6.82 -35.10 60.40 0.047

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,693 10.52 4.76 -5.76 7.34 -61.60 80.00 0.010

Spring (Mar-May) 3,628 6.55 11.31 4.76 6.40 44.10 63.50 0.025

Summer (Jun-Aug) 3,648 8.10 5.06 -3.04 4.39 -45.50 62.40 0.000

Fall (Sep-Nov) 3,611 7.81 4.62 -3.19 4.40 -44.00 62.30 0.013

Annual 14,580 8.26 6.43 -1.83 5.64 -26.90 67.10 0.000

(d) Central States

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,278 9.23 9.75 0.52 4.05 4.80 43.00 0.156

Spring (Mar-May) 6,304 10.70 9.96 -0.74 4.28 -3.10 41.40 0.089

Summer (Jun-Aug) 6,162 13.03 7.97 -5.05 7.14 -55.40 68.50 0.109

Fall (Sep-Nov) 5,847 10.17 9.11 -1.07 4.21 -9.40 43.90 0.218

Annual 24,591 10.78 9.21 -1.58 4.92 -15.70 49.20 0.105

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,145 12.33 14.12 1.78 4.89 12.40 37.40 0.289

Spring (Mar-May) 4,884 11.64 12.55 0.91 4.77 13.80 39.80 0.242

Summer (Jun-Aug) 4,795 15.07 10.09 -4.98 7.02 -41.40 56.70 0.160

Fall (Sep-Nov) 4,725 11.70 12.82 1.13 4.24 12.20 36.20 0.426

Annual 19,549 12.68 12.43 -0.25 5.22 -0.50 42.40 0.204

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(f) Southeast

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 10,073 10.17 9.01 -1.17 3.73 -13.00 39.80 0.258

Spring (Mar-May) 9,916 12.69 11.35 -1.34 4.40 -8.60 35.80 0.092

Summer (Jun-Aug) 9,791 17.18 10.49 -6.69 9.47 -52.50 66.20 0.027

Fall (Sep-Nov) 9,476 11.71 9.34 -2.37 4.49 -21.60 43.00 0.246

Annual 39,256 12.93 10.05 -2.88 5.51 -23.80 46.20 0.093

(g) Northeast

Time Period # Data Pairs Mean Observed

( μ gm -3

) Mean Simulated

( μ gm -3

) Mean Residual ( μ gm -3

) Mean Unsigned

Error ( μ gm -3

) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,552 11.93 13.28 1.35 4.77 11.40 39.20 0.376

Spring (Mar-May) 6,533 9.69 12.97 3.28 4.76 35.10 45.70 0.473

Summer (Jun-Aug) 6,437 15.11 11.84 -3.26 6.80 -19.40 50.30 0.228

Fall (Sep-Nov) 6,466 10.15 13.50 3.35 5.34 28.30 46.70 0.449

Annual 25,988 11.71 12.90 1.19 5.41 14.00 45.50 0.301



### For 2006, model performance for 24-hour average PM 2.5 

### is mixed. For many of the regions and time periods, the bias and error statistics indicate good model performance. Most troubling is that the seasonal concentration pattern that is characterized by higher concentrations during the summer months is not replicated by the model. The modeled values tend to be lowest during the summer months and consistently underestimate the observed values. This cyclical mismatch could be due to the fact that different meteorological processes affect PM 2.5 

### in the winter and the summer months and that GEOS-Chem is less able to simulate the summertime conditions. Local stability and low wind speeds generally contribute to high PM 2.5 

### concentrations throughout the year but are especially important during the winter months, while regional-scale transport can be important during the summer months.

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ICF International 

### 49 October 28, 2011

11-035 

### Dry Deposition Modeled dry deposition amounts are compared with data from the CASTNet sites in Table 4-9

. Dry deposition data are available for approximately 80 sites within the U.S. for the following species: nitric acid (HNO 3 

### ), ammonium (NH 4 

### ), particulate nitrate (NO 3 

### ), ozone, SO 2 

### , and sulfate (SO 4 

### ). Table 4-8 compares the simulated and observed annual deposition amounts and provides summary annual performance metrics for each of these deposition species for the entire U.S. Units are kilograms per hectare (kg/ha).

Table 4-9. Annual GEOS-CHEM Model Pe rformance Statistics for Dry Depositi on (kg/ha) for the Base Case (Current Atmosphere Scenario) for the Continental U.S.: 2006.

Time Period # Data Pairs Mean Observed

(kg/ha) Mean Simulated

(kg/ha) Mean Residual (kg/ha) Mean Unsigned

Error (kg/ha) Fractional Bias (%) Fractional Error (%) R2

Nitric acid (HNO 3 ) 82 4.88 6.44 1.57 2.73 23.50 52.70 0.275 Ammonium (NH 4 ) 82 0.32 0.23 -0.09 0.13 -33.40 53.60 0.516 Particulate nitrate (NO 3 ) 82 0.27 0.30 0.03 0.18 6.00 80.20 0.205 Ozone (O 3 ) 81 40.24 35.60 -4.64 12.81 -10.00 34.50 0.064 Sulfur dioxide (SO 2 ) 82 3.36 4.33 0.97 1.58 40.10 51.80 0.536 Sulfate (SO 4 ) 82 0.96 0.45 -0.51 0.54 -70.20 77.10 0.468



### Overall, model performance for dry deposition for 2006 is quite good. Dry deposition of ozone is underestimated by the model, which could contribute to overestimation of the ozone concentrations. Ammonium and sulfate dry deposition are also underestimated.


## Summary Model Performance Results for 2007
In this section, the GEOS-Chem results for 2007 are compared to observed data for ozone, other gaseous species, fine particulate matter, and dry deposition.



### Ozone

The two metrics used for the calculation of stat istical measures for ozone are: 24-hour average ozone and MDA8 ozone.

Table 4-10 lists the seasonal and annual performance metrics for 24-hour average ozone for the entire U.S. and each of the six model performance subregions for 2007, calculated using the CASTNet data. Units are ppb.Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsTable 4-10. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case(Current Atmosphere Scenario) Using CASTNet Data: 2007.(a) Entire Continental U.S.TimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)6,91028.4830.171.696.1714.7030.605.5024.800.452Spring(Mar-May)7,15642.2445.703.467.3513.4021.309.3017.900.370Summer(Jun-Aug)7,12340.3151.8411.5313.3039.5042.8027.5031.100.356Fall(Sep-Nov)7,11232.1641.259.0910.6543.8047.8027.3031.800.406Annual28,30135.8642.336.479.3927.9035.7017.5026.400.458ICF International50October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(b) West CoastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)76532.1135.573.468.4431.6043.6015.8029.200.176Spring(Mar-May)81644.9046.441.548.1213.9026.007.3020.700.591Summer(Jun-Aug)80147.7951.293.5010.0220.1032.2011.1024.700.689Fall(Sep-Nov)75436.2143.347.1310.4661.7068.4026.8034.100.506Annual3,13640.4344.283.859.2531.3042.1015.1027.000.604(c) Intermountain WestTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,10139.0638.95-0.114.634.3015.601.0013.300.285Spring(Mar-May)1,14048.3147.91-0.405.362.3013.000.4012.000.391Summer(Jun-Aug)1,16547.6552.825.178.0014.9020.1011.5017.000.270Fall(Sep-Nov)1,16539.8143.683.876.4318.0023.6011.3017.400.334Annual4,57143.7545.922.186.1310.0018.206.1015.000.401ICF International51October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(d) Central StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)73628.1731.092.917.0528.7041.5013.0028.100.184Spring(Mar-May)76038.4942.473.987.4917.6025.1011.9020.100.209Summer(Jun-Aug)72236.1646.8810.7211.5439.5041.6027.5029.700.205Fall(Sep-Nov)81130.0438.148.109.6846.1050.4026.6031.300.154Annual3,02933.1639.606.438.9433.1039.8019.8027.300.266(e) Great Lakes StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,13423.4621.43-2.045.05-9.1024.40-15.2028.000.576Spring(Mar-May)1,13638.4942.754.277.0713.5020.809.7017.900.399Summer(Jun-Aug)1,16938.1655.0716.9117.0448.5048.8036.1036.400.362Fall(Sep-Nov)1,13528.4038.339.9310.9938.9043.3027.5032.800.599Annual4,57432.1839.527.3410.0923.1034.4014.7028.800.581ICF International52October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsICF International53October 28, 201111-035(f) SoutheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,87626.5930.904.317.0926.2034.9016.3026.100.253Spring(Mar-May)1,95644.1048.694.598.1415.3021.9011.3018.400.198Summer(Jun-Aug)1,93540.2653.3713.1014.6546.8049.4031.4034.300.182Fall(Sep-Nov)1,96532.6643.5410.8712.0545.5048.1031.1033.900.349Annual7,73235.9844.238.2510.5033.5038.6022.6028.200.393(g) NortheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,29824.6325.570.945.279.7028.901.3025.600.536Spring(Mar-May)1,34838.0643.335.277.6017.4023.0013.1019.200.327Summer(Jun-Aug)1,33133.6048.9415.3415.6154.4055.0038.0038.700.461Fall(Sep-Nov)1,28226.7438.8812.1412.7756.9059.6036.7040.000.469Annual5,25930.8639.288.4210.3134.5041.5022.2030.800.479Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results



### Model performance is similar to that for 2006 and 24-hour average ozone is overestimated for most regions and time periods. The greatest amount of overestimation tends to occur during the summer and autumn months, and the best performance for 24-hour ozone is achieved for the western subregions.

Table 4-11 lists the seasonal and annual performance metrics for maximum daily 8-hour average (MDA8) ozone for the entire U.S. and each of the six model performance subregions for 2007, calculated using the CASTNet data. Units are ppb.

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11-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsTable 4-11. Seasonal and Annual GEOS-CHEM Model Performance Statistics for Maximum Daily 8-hourAverage (MDA8) Ozone Concentration (ppb) for the Base Case(Current Atmosphere Scenario) Using CASTNet Data: 2007.(a) Entire Continental U.S.TimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)6,92833.9436.682.745.6513.4022.008.1018.200.462Spring(Mar-May)7,23051.4455.574.137.1010.5015.608.2013.700.514Summer(Jun-Aug)7,22652.5464.4311.8913.8228.6031.6021.2024.500.446Fall(Sep-Nov)7,16041.4451.4710.0311.0231.5033.5023.0025.200.552Annual28,54444.9652.207.249.4321.0025.7015.2020.400.596ICF International55October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(b) West CoastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)76837.5141.664.156.5921.0026.4013.6019.400.316Spring(Mar-May)82354.4856.471.997.746.5015.804.4014.500.637Summer(Jun-Aug)81561.4065.203.8012.0610.5022.906.3020.100.672Fall(Sep-Nov)75744.7352.888.1410.6234.7038.7021.3025.500.557Annual3,16349.8154.264.459.2617.8025.7011.1019.700.666(c) Intermountain WestTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,12442.7543.530.793.803.9010.502.509.600.342Spring(Mar-May)1,16754.3554.860.514.672.009.201.308.800.458Summer(Jun-Aug)1,18455.5261.245.728.3712.0016.309.8014.500.257Fall(Sep-Nov)1,17245.5750.835.266.6814.7017.4011.6014.600.430Annual4,64749.6352.733.105.918.2013.406.4011.900.511ICF International56October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(d) Central StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)73833.8136.843.036.2518.5027.3010.2020.400.230Spring(Mar-May)76347.7750.742.986.269.8015.807.1013.600.394Summer(Jun-Aug)73346.9457.5510.6111.6326.3028.4020.8023.100.382Fall(Sep-Nov)81339.1147.138.029.1227.9030.4019.9022.500.387Annual3,04741.8848.056.178.3120.7025.5014.6019.900.468(e) Great Lakes StatesTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,13028.9028.64-0.274.54-0.4017.60-3.4018.400.529Spring(Mar-May)1,14649.1355.246.117.9214.1017.8011.3015.400.599Summer(Jun-Aug)1,17652.5770.5617.9918.3537.9038.6029.4030.100.415Fall(Sep-Nov)1,15039.1451.2112.0612.4934.8036.2026.6028.200.736Annual4,60242.5551.619.0610.9021.8027.7016.1023.100.704ICF International57October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsICF International58October 28, 201111-035(f) SoutheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,87833.1438.465.327.1321.9026.5016.0021.000.318Spring(Mar-May)1,97054.6658.884.226.849.9014.008.1012.500.436Summer(Jun-Aug)1,97153.1365.5412.4113.6432.0033.7023.0024.800.352Fall(Sep-Nov)1,97043.0953.7010.6011.5131.1032.6023.9025.600.540Annual7,78946.1654.338.179.8123.7026.7017.8021.000.584(g) NortheastTimePeriod#Data PairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias(%)NormalizedGross Error(%)FractionalBias(%)FractionalError(%)R2Winter(Dec-Feb)1,29029.7932.132.345.1713.8023.807.0019.200.422Spring(Mar-May)1,36146.4653.817.358.9318.3021.4014.4017.700.517Summer(Jun-Aug)1,34746.7163.5416.8317.2042.2042.9030.7031.400.575Fall(Sep-Nov)1,29836.7750.7814.0114.3345.0046.1031.9033.100.619Annual5,29640.0950.2610.1711.4429.8033.5021.0025.300.627Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results



### Model performance for MDA8 for 2007 is similar to that for 2006. Again, the 8-hour average ozone concentrations are overestimated for most regions and time periods but the bias and error statistics suggest reasonably good performanc e. Model performance varies by season and by subregion. Overestimation of ozone during the summer and autumn months is prevalent in the eastern U.S. (Central States, Great Lakes, Southeast, and Northeast subregions). For the western subregions, there is a mix of over- and underestimation of ozone and overall very good agreement with the observations.

The best agreement with the observations is achieved for the Intermountain West subregion. The normalized bias for this subregion for the annual period is 8.2 percent, while the corresponding gross error is 13.4 percent. The fractional bias is 6.4 percent and the corresponding fractional error is 11.9 percent.

For the entire U.S., the mean residual or difference between the simulated and observed values ranges from approximately 2.7 to 11.9 ppb for the four seasonal periods and is 7.2 ppb for the annual period. The normalized bias for the annual period is 21 percent, while the corresponding gross error is 25.7 percent. The fractional bias is 15.2 percent and the corresponding fractional error is 20.4 percent. Figure 4-8 summarizes the agreement between the mean simulated and observed MDA8 concentrations for the seasonal and annual periods for the entire U.S.

Figure 4-8. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb ) for Each Season and the Entire Year, Averaged Over All Sites in Entire Continental U.S.: 2007.

Seasonal & Annual Mean Ozone Concentration (ppb)

25 35 45 55 65 75

25 35 45 55 65 75
ObservedGEOS-Chem

Spring Summer Fall Winter Annual



### Time-series and scatter plots illustrating site-specific model performance for MDA8 ozone concentrations for the West Coast subregion are provided in Figure 4-9 . The West Coast sites (listed in order of elevation) are: Pinnacles NM, CA (elevation 335 meters (m)) Mount Rainier NP, WA (elevation 415 m), Joshua Tree NM, CA (elevation 1244 m), and Lassen Volcanic NP, CA (elevation 1756 m). In the time series plots, the observed values are in blue and the simulated values are in green. Note that the scale varies by site, based on concentration.

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11-035 Figure 4-9. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the West Coast Subregion: 2007. (a) Pinnacles NM

CASTNet Site Pinnacles NM, CA (PIN414) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Pinnacles NM, CA (PIN414) MDA8: 2007

R 2 = 0.4348

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100Simulated

Observed

(b) Mount Rainier NP

CASTNet Site Mount Rainier NP, WA (MOR409) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Mount Rainier NP, WA (MOR409) MDA8: 2007

R 2 = 0.4205

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Joshua Tree NM

CASTNet Site Joshua Tree NM, CA (JOT403) MDA8: 2007

0 20 40 60 80 100 120 140

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Joshua Tree NM, CA (JOT403) MDA8: 2007

R 2 = 0.789

0 20 40 60 80 100 120 140

0 20 40 60 80 100 120 140

ObservedSimulatedModeling for North American Background Concentrations Model Performance Evaluation Procedures & Results

(d) Lassen Volcanic NP

CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2007

R 2 = 0.4956

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100 110

ObservedSimulated



### Time-series and scatter plots for the Intermountain West subregion are provided in Figure 4-10

. The Intermountain West sites are: Chiricahua NM, AZ (elevation 1570 m), Great Basin NP, NV (elevation 2060 m), Pinedale, WY (elevation 2388 m), and Rocky Mountain NP, CO (elevation 2743 m).

Figure 4-10. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Intermoun tain West Subregion: 2007. (a) Chiricahua NM

CASTNet Site Chiricahua NM, AZ (CHA467) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Chiricahua NM, AZ (CHA467) MDA8: 2007

R 2 = 0.4573

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(b) Great Basin NP

CASTNet Site Great Basin NP, NV (GRB411) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Great Basin NP, NV (GRB411) MDA8: 2007

R 2 = 0.7021

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Pinedale

CASTNet Site Pinedale, WY (PND165) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Pinedale, WY (PND165) MDA8: 2007

R 2 = 0.5893

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Rocky Mountain NP

CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: 2007

R 2 = 0.4325

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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### Time-series and scatter plots for the Central States subregion are provided in Figure 4-11 . The Central States sites are: Caddo Valley, AR (elevation 71 m), Konza Prairie, KS (elevation 348 m), Theodore Roosevelt NP, ND (elevation 850 m), and Big Bend NP, TX (elevation 1052 m).

Figure 4-11. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in Central States Subregion: 2007. (a) Caddo Valley

CASTNet Site Caddo Valley, AR (CAD150) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Caddo Valley, AR (CAD150) MDA8: 2007

R 2 = 0.5407

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(b) Konza Prairie

CASTNet Site Konza Prairie, KS (KNZ184) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Konza Prairie, KS (KNZ184) MDA8: 2007

R 2 = 0.5434

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(c) Theodore Roosevelt NP

CASTNet Site Theodore Roo sevelt NP, ND (THR422) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Theodore Roosevel t NP, ND (THR422) MDA8: 2007

R 2 = 0.5871

0 10 20 30 40 50 60 70 80 90 100

0 2 0 4 0 6 0 8 0 1 0 0

ObservedSimulated

(d) Big Bend NP

CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Big Bend NP, TX, (BBE401) MDA8: 2007

R 2 = 0.3571

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Great Lakes subregion are provided in Figure 4-12 . The Great Lakes sites are: Salamonie Reservoir, IN (elevation 250 m), Ann Arbor, MI (elevation 267 m), Oxford, OH (elevation 284 m), and Perkinstown, WI (elevation 472 m).

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Figure 4-12. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Great Lakes Subregion: 2007. (a) Salamonie Reservoir

CASTNet Site Salamonie Reservoir, IN (SAL133) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Salamonie Reservoir, IN (SAL133) MDA8: 2007

R 2 = 0.7525

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(b) Ann Arbor

CASTNet Site Unionville, MI (ANA115) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Unionville, MI (ANA115) MDA8: 2007

R 2 = 0.5991

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Oxford

CASTNet Site Oxford, OH (OXF122) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Oxford, OH (OXF122) MDA8: 2007

R 2 = 0.7834

0 10 20 30 40 50 60 70 80 90 100 110 120

0 2 0 4 0 6 0 8 0 1 0 0 1 2 0

ObservedSimulated

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(d) Perkinstown

CASTNet Site Perkinstown, WI (PRK134) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Perkinstown, WI (PRK134) MDA8: 2008

R 2 = 0.4394

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Southeast subregion are provided in Figure 4-13 . The Southeast sites are: Sumatra, FL (elevation 14 m), Cadiz, KY (elevation 189 m), Sand Mountain, AL (elevation 352 m), and Great Smoky Mountain NP, TN (elevation 793 m).

Figure 4-13. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Southeast Subregion: 2007. (a) Sumatra

CASTNet Site Sumatra, FL (SUM156) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Sumatra, FL (SUM156) MDA8: 2007

R 2 = 0.3899

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(b) Cadiz

CASTNet Site Cadiz, KY (CDZ171) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Cadiz, KY (CDZ171) MDA8: 2007

R 2 = 0.7331

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Sand Mountain

CASTNet Site Sand Mountain, AL (SND152) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Sand Mountain, AL (SND152) MDA8: 2007

R 2 = 0.6845

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Great Smoky Mountain NP

CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2007

R 2 = 0.6863

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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### Time-series and scatter plots for the Northeast subregion are provided in Figure 4-14 . The Northeast sites are Blackwater NWR, MD (elevation 4 m), Acadia NP, ME (elevation 158 m), Penn State, PA (elevation 378 m), and Huntington Wildlife Forest, NY (elevation 502 m).

Figure 4-14. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Northeast Subregion: 2007. (a) Blackwater NWR

CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2007

R 2 = 0.6889

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120

ObservedSimulated

(b) Acadia NP

CASTNet Site Acadia NP, ME (ACA416) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Acadia NP, ME (ACA416) MDA8: 2007

R 2 = 0.4028

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120 130

ObservedSimulated

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(c) Penn State

CASTNet Site Penn State, PA (PSU106) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Penn State, PA (PSU106) MDA8: 2007

R 2 = 0.7081

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Huntington Wildlife Forest

CASTNet Site Huntington Wildlife Forest, NY (HWF187) MDA8: 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Huntington Wildlife Forest, NY (HWF187) MDA8: 2007

R 2 = 0.5308

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### For the more urban sites included in the AQS network, only 24-hour average ozone was considered. The results are similar to those for 2006 and the 24-hour ozone concentrations are overestimated for all subregions and periods.

Table 4-12 lists the seasonal and annual performance metrics for 24-hour average ozone for the entire U.S. and each of the six model performance subregions for 2007, calculated using the AQS data. Normalized bias and error statistics are not included in this table. Units are ppb.

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Table 4-12. Seasonal and Annual GEOS-CHEM Model Performa nce Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmosp here Scenario) Using AQS Data: 2007. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R2

Winter (Dec-Feb) 51,714 22.02 30.28 8.26 9.97 35.70 43.20 0.247 Spring(MarMay) 91,020 36.47 44.92 8.45 10.20 22.10 26.30 0.263
Summer (Jun-Aug) 107,622 34.35 50.56 16.21 17.12 38.90 41.30 0.280Fall (SepNov) 84,132 26.90 42.13 15.23 15.74 47.30 48.70 0.316
Annual 334,515 31.14 43.77 12.62 13.78 35.90 39.40 0.352

(b) West Coast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R2

Winter (Dec-Feb) 14,826 20.99 31.13 10.15 11.53 46.70 51.10 0.196 Spring (Mar-May) 16,454 35.24 42.31 7.07 10.13 18.90 26.80 0.265
Summer (Jun-Aug) 18,184 34.12 43.79 9.67 12.96 20.90 30.70 0.345Fall (SepNov) 16,740 26.07 40.36 14.29 15.34 46.80 49.70 0.239
Annual 66,204 29.42 39.72 10.30 12.54 32.70 39.10 0.323

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(c) Intermountain West

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R2

Winter (Dec-Feb) 9,333 24.63 35.24 10.61 11.84 43.10 46.60 0.143 Spring (Mar-May) 11,612 39.38 46.37 6.99 9.33 18.70 23.70 0.165
Summer (Jun-Aug) 13,576 40.97 52.52 11.56 12.68 25.50 27.90 0.138Fall (SepNov) 11,700 29.61 42.63 13.02 13.77 40.40 42.30 0.176
Annual 46,221 34.40 44.98 10.59 11.95 31.10 34.30 0.325

(d) Central States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 12,495 21.49 27.45 5.97 7.74 28.70 36.20 0.332 Spring (Mar-May) 16,455 34.31 42.10 7.78 9.11 21.60 25.00 0.277
Summer (Jun-Aug) 17,996 29.05 46.85 17.80 17.95 49.70 50.10 0.424Fall (SepNov) 15,878 26.10 39.63 13.53 13.87 43.80 44.90 0.378
Annual 62,824 28.18 39.92 11.74 12.57 36.70 39.40 0.388

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(e) Great Lakes States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,950 18.81 19.93 1.12 5.07 3.20 30.90 0.549 Spring (Mar-May) 12,226 35.92 45.12 9.20 10.42 23.80 26.80 0.282
Summer (Jun-Aug) 17,249 34.87 55.45 20.58 20.63 45.80 45.90 0.282Fall (SepNov) 10,062 26.81 42.95 16.14 16.33 47.90 48.80 0.516
Annual 42,487 32.15 47.05 14.90 15.60 37.00 40.10 0.410

(f) Southeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,702 24.13 36.93 12.81 13.56 44.00 46.60 0.150 Spring (Mar-May) 21,524 38.43 48.78 10.35 11.42 25.30 27.60 0.200
Summer (Jun-Aug) 23,822 34.97 53.53 18.55 19.05 44.80 45.70 0.172Fall (SepNov) 18,079 27.91 45.87 17.96 18.20 52.10 52.60 0.317
Annual 70,127 33.18 48.51 15.33 15.96 40.60 42.00 0.264

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(g) Northeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,435 20.90 23.32 2.41 5.65 15.80 33.80 0.578 Spring (Mar-May) 12,749 35.54 43.99 8.45 10.14 22.30 26.60 0.305
Summer (Jun-Aug) 16,795 33.64 51.19 17.55 17.97 41.70 42.70 0.341Fall (SepNov) 11,673 25.14 41.22 16.08 16.48 50.90 52.40 0.368
Annual 46,652 30.55 43.48 12.93 14.02 35.70 39.70 0.406



### NO 2 

### , SO 2 

### , CO, and PM 2.5


### Table 4-13 lists the seasonal and annual performance metrics for 24-hour average NO 2 

### for the entire U.S. and each of the six model performance subregions for 2007, calculated using the AQS data. Normalized bias and error statistics are not included in this table. Units are ppb.

Table 4-13. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average NO 2 Concentration (ppb) for the Base Case (Current Atmosphere Scenario): 2007. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 33,420 14.31 7.48 -6.83 7.85 -52.20 72.10 0.280 Spring (Mar-May) 34,583 10.62 5.36 -5.26 6.09 -53.20 75.60 0.347
Summer (Jun-Aug) 34,685 8.79 5.10 -3.68 4.93 -41.80 70.70 0.260Fall (SepNov) 33,899 12.03 6.08 -5.95 6.97 -52.60 75.60 0.292
Annual 136,587 11.41 5.99 -5.41 6.45 -49.90 73.50 0.315

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(b) West Coast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,826 16.52 6.66 -9.86 10.25 -80.00 89.50 0.364 Spring (Mar-May) 9,120 11.58 5.57 -6.01 6.72 -68.70 81.10 0.378
Summer (Jun-Aug) 9,133 10.12 5.53 -4.59 5.39 -57.70 71.70 0.410Fall (SepNov) 9,043 14.99 6.23 -8.76 9.19 -80.20 88.80 0.392
Annual 36,122 13.27 5.99 -7.28 7.87 -71.60 82.70 0.381

(c) Intermountain West

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,084 15.83 4.49 -11.34 11.61 -88.00 107.70 0.472 Spring (Mar-May) 4,170 10.15 3.19 -6.95 7.18 -77.80 106.60 0.498
Summer (Jun-Aug) 3,820 8.50 3.32 -5.18 5.51 -77.40 93.70 0.398Fall (SepNov) 3,882 12.90 3.98 -8.92 9.17 -83.70 103.20 0.498
Annual 15,956 11.88 3.75 -8.13 8.40 -81.70 103.00 0.476

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(d) Central States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,112 10.35 7.04 -3.32 4.95 -24.00 57.50 0.261 Spring (Mar-May) 8,422 7.78 5.20 -2.58 4.03 -22.40 62.10 0.260
Summer (Jun-Aug) 8,372 6.47 6.11 -0.36 3.51 4.30 59.00 0.190Fall (SepNov) 8,240 8.88 6.17 -2.71 4.52 -21.00 58.90 0.232
Annual 33,146 8.35 6.12 -2.23 4.25 -15.70 59.40 0.237

(e) Great Lakes States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 1,706 17.76 11.98 -5.78 6.96 -30.00 43.80 0.402 Spring (Mar-May) 1,888 14.90 7.77 -7.13 7.76 -51.40 62.50 0.430
Summer (Jun-Aug) 1,848 12.74 6.15 -6.59 7.03 -54.50 65.30 0.358Fall (SepNov) 1,472 15.70 9.04 -6.66 7.28 -45.30 54.90 0.350
Annual 6,914 15.20 8.64 -6.55 7.26 -45.60 57.00 0.389

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(f) Southeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,624 11.06 7.06 -4.00 5.37 -34.80 59.60 0.274 Spring (Mar-May) 4,756 8.79 4.38 -4.41 5.06 -50.90 71.60 0.321
Summer (Jun-Aug) 4,784 6.96 3.91 -3.05 4.00 -37.20 68.40 0.093Fall (SepNov) 4,769 8.61 5.03 -3.58 5.02 -32.20 70.30 0.155
Annual 18,933 8.84 5.08 -3.76 4.86 -38.80 67.50 0.252

(g) Northeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,068 16.92 10.38 -6.54 7.88 -43.60 58.80 0.278 Spring (Mar-May) 6,227 13.49 6.81 -6.68 7.50 -56.40 71.10 0.299
Summer (Jun-Aug) 6,728 10.23 4.84 -5.39 5.84 -57.30 73.70 0.376Fall (SepNov) 6,493 13.08 7.12 -5.96 7.01 -52.40 70.60 0.250
Annual 25,516 13.34 7.22 -6.12 7.03 -52.60 68.70 0.333



### For 2007, the 24-hour average NO 2 

### concentrations are underestimated for all subregions and time periods. As for 2006, model performance is worst for the West Coast and Intermountain West subregions. Elsewhere, the fractional bias indicates that the modeled values are well within a factor of two (67 percent) of the observed values.

Table 4-14 lists the seasonal and annual performance metrics for 24-hour average SO 2 

### for the entire U.S. and each of the six model performance subregions for 2007, calculated using the AQS data. Units are ppb.

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Table 4-14. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average SO 2 Concentration (ppb) for the Base Case (Current Atmosphere Scenario): 2007. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 41,856 3.78 6.15 2.37 4.14 55.70 92.70 0.125 Spring (Mar-May) 43,300 3.00 4.49 1.49 3.09 54.30 93.80 0.128
Summer (Jun-Aug) 42,637 2.63 4.44 1.81 3.09 64.00 98.70 0.125Fall (SepNov) 42,319 3.03 4.98 1.95 3.45 61.80 96.00 0.125
Annual 170,112 3.11 5.01 1.90 3.44 59.00 95.30 0.131

(b) West Coast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,310 1.36 1.48 0.12 1.09 33.70 94.10 0.132 Spring (Mar-May) 3,605 1.07 1.24 0.17 0.86 40.70 97.80 0.154
Summer (Jun-Aug) 3,583 1.07 1.43 0.36 0.89 55.20 95.30 0.158Fall (SepNov) 3,604 1.17 1.59 0.42 0.92 45.80 87.00 0.244
Annual 14,102 1.17 1.44 0.27 0.94 44.00 93.50 0.166

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(c) Intermountain West

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,772 2.19 0.94 -1.26 1.78 -9.60 107.00 0.011 Spring (Mar-May) 2,863 1.93 0.70 -1.23 1.62 -8.80 115.00 0.050
Summer (Jun-Aug) 2,737 2.01 0.74 -1.26 1.63 -17.00 113.30 0.066Fall (SepNov) 2,720 2.09 0.86 -1.23 1.73 3.00 111.20 0.063
Annual 11,092 2.05 0.81 -1.24 1.69 -8.20 111.70 0.039

(d) Central States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,700 2.17 3.50 1.32 2.87 79.80 109.90 0.020 Spring (Mar-May) 9,130 1.96 2.60 0.64 2.29 72.10 113.10 0.030
Summer (Jun-Aug) 9,105 1.62 3.06 1.43 2.51 88.90 117.50 0.020Fall (SepNov) 9,131 2.10 3.02 0.92 2.62 77.10 112.40 0.029
Annual 36,066 1.96 3.04 1.08 2.57 79.50 113.30 0.024

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(e) Great Lakes States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 7,804 4.24 9.05 4.81 5.94 83.10 95.20 0.038 Spring (Mar-May) 7,766 3.87 6.97 3.10 4.51 74.80 91.40 0.052
Summer (Jun-Aug) 7,444 3.39 6.77 3.38 4.64 81.80 99.00 0.025Fall (SepNov) 7,306 4.10 7.77 3.67 5.33 79.70 96.40 0.017
Annual 30,320 3.91 7.65 3.75 5.11 79.80 95.40 0.035

(f) Southeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,252 4.12 7.28 3.16 4.83 72.20 90.90 0.067 Spring (Mar-May) 9,813 3.51 5.36 1.85 3.54 63.80 88.60 0.123
Summer (Jun-Aug) 9,652 3.15 5.54 2.39 3.74 77.70 96.60 0.106Fall (SepNov) 9,416 3.44 6.01 2.58 3.95 76.90 94.80 0.131
Annual 38,133 3.55 6.03 2.48 4.00 72.60 92.70 0.106

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(g) Northeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 10,018 5.96 8.73 2.77 5.14 34.30 69.70 0.106 Spring (Mar-May) 10,123 3.90 6.06 2.15 3.67 44.20 74.80 0.124
Summer (Jun-Aug) 10,116 3.28 5.42 2.14 3.18 54.80 78.10 0.213Fall (SepNov) 10,142 3.81 6.61 2.80 3.98 55.60 78.40 0.181
Annual 40,399 4.23 6.70 2.47 3.99 47.30 75.20 0.169



### For 2007, model performance for 24-hour average SO 2 

### concentrations varies by subregion. SO 2 

### is underestimated in the Intermountain West, where observed values are low and overestimated elsewhere, including in the East where observed values are higher. Fractional error values are high and R 2 

### values are very low. Overall the best agreement with the observed values is for the Northeast.

Table 4-15 lists the seasonal and annual performance metrics for 24-hour average CO for the entire U.S. and each of the six model performance subregions for 2007, calculated using the AQS data. Units are ppm.

Table 4-15. Seasonal and Annual GEOS-CHEM Model Performa nce Statistics for 24-hour Average CO Concentration (ppm) for the Base Case (Current Atmosphere Scenario): 2007. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 31,070 0.51 0.27 -0.24 0.31 -39.80 71.70 0.016 Spring (Mar-May) 31,016 0.40 0.24 -0.16 0.22 -30.80 65.80 0.034
Summer (Jun-Aug) 30,176 0.34 0.23 -0.11 0.19 -19.60 67.30 0.012Fall (SepNov) 31,088 0.43 0.23 -0.20 0.25 -38.60 71.30 0.051
Annual 123,350 0.42 0.24 -0.18 0.24 -32.30 69.10 0.032

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(b) West Coast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,828 0.60 0.27 -0.33 0.36 -56.80 75.00 0.112 Spring (Mar-May) 6,991 0.39 0.26 -0.13 0.19 -25.10 60.80 0.121
Summer (Jun-Aug) 6,907 0.31 0.24 -0.07 0.17 -18.00 66.10 0.018Fall (SepNov) 7,013 0.49 0.26 -0.23 0.27 -49.90 68.40 0.127
Annual 27,739 0.45 0.26 -0.19 0.25 -37.40 67.50 0.088

(c) Intermountain West

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,891 0.65 0.19 -0.46 0.47 -85.50 96.60 0.127 Spring (Mar-May) 5,175 0.40 0.17 -0.23 0.25 -54.10 79.90 0.094
Summer (Jun-Aug) 4,468 0.30 0.17 -0.14 0.19 -26.50 77.50 0.009Fall (SepNov) 5,418 0.47 0.17 -0.29 0.32 -62.00 88.60 0.099
Annual 20,952 0.47 0.18 -0.29 0.32 -59.10 86.30 0.107

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(d) Central States

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,266 0.37 0.23 -0.14 0.23 -20.10 74.50 0.001 Spring (Mar-May) 4,398 0.33 0.19 -0.13 0.20 -20.60 75.40 0.001
Summer (Jun-Aug) 4,498 0.29 0.18 -0.11 0.16 -21.60 69.40 0.031Fall (SepNov) 4,465 0.34 0.19 -0.15 0.20 -30.10 71.00 0.018
Annual 17,627 0.33 0.20 -0.13 0.20 -23.10 72.50 0.007

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,950 0.44 0.36 -0.08 0.21 -14.40 51.30 0.016 Spring (Mar-May) 3,088 0.41 0.27 -0.14 0.19 -30.70 50.70 0.035
Summer (Jun-Aug) 2,919 0.38 0.25 -0.14 0.19 -24.40 55.00 0.009Fall (SepNov) 2,762 0.44 0.26 -0.18 0.24 -35.00 65.20 0.008
Annual 11,719 0.42 0.29 -0.14 0.21 -26.00 55.30 0.016

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(f) Southeast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,090 0.48 0.27 -0.21 0.27 -38.40 63.40 0.015 Spring (Mar-May) 5,122 0.44 0.23 -0.21 0.24 -44.90 63.90 0.012
Summer (Jun-Aug) 5,087 0.41 0.23 -0.18 0.23 -34.60 67.10 0.007Fall (SepNov) 5,197 0.44 0.22 -0.22 0.26 -47.10 68.90 0.012
Annual 20,496 0.44 0.24 -0.21 0.25 -41.30 65.90 0.007

(g) Northeast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,045 0.42 0.36 -0.06 0.21 -0.70 56.80 0.122 Spring (Mar-May) 6,242 0.39 0.29 -0.10 0.20 -9.80 59.50 0.072
Summer (Jun-Aug) 6,297 0.34 0.28 -0.06 0.19 3.40 63.10 0.059Fall (SepNov) 6,233 0.37 0.28 -0.09 0.19 -3.30 62.50 0.119
Annual 24,817 0.38 0.30 -0.08 0.19 -2.60 60.50 0.096



### For 2007, CO concentrations are underestimated for all regions and time periods. Again, the modeled values exhibit less seasonal variation than the observed values. The best performance for CO is for the Northeast subregion.

Table 4-16 lists the seasonal and annual performance metrics for 24-hour average PM 2.5 

### for the entire U.S. and each of the six model performance subregions for 2007, calculated using the AQS data. Units are μ gm -3



### .

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Table 4-16. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average PM 2.5

Concentration ( μ gm -3

) for the Base Case (Current At mosphere Scenario): 2007. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 34,581 11.87 10.18 -1.69 5.16 -14.80 46.20 0.166 Spring (Mar-May) 37,027 11.26 11.43 0.17 4.98 6.80 42.70 0.141
Summer (Jun-Aug) 36,252 13.93 10.74 -3.19 7.01 -29.20 55.90 0.102Fall (SepNov) 36,120 11.42 9.55 -1.87 5.04 -16.40 47.70 0.186
Annual 143,980 12.12 10.48 -1.64 5.55 -13.30 48.10 0.138

(b) West Coast

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,619 15.21 6.37 -8.84 10.57 -58.50 77.80 0.009 Spring (Mar-May) 3,731 9.36 9.65 0.29 4.47 8.50 44.70 0.147
Summer (Jun-Aug) 3,539 9.22 8.49 -0.73 4.16 -10.40 46.60 0.162Fall (SepNov) 3,784 13.81 8.52 -5.29 7.89 -35.20 58.10 0.048

Annual 14,673 11.92 8.27 -3.65 6.78 -23.90 56.80 0.030

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,251 11.72 4.62 -7.10 8.44 -65.70 83.00 0.023 Spring (Mar-May) 3,654 6.32 10.34 4.02 5.96 31.00 58.30 0.022
Summer (Jun-Aug) 3,455 9.30 8.66 -0.64 6.27 -18.90 62.20 0.053Fall (SepNov) 3,315 8.46 5.56 -2.91 5.07 -39.80 63.50 0.020
Annual 13,675 8.88 7.40 -1.48 6.41 -21.80 66.40 0.005

(d) Central States

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,694 11.11 11.46 0.35 3.84 4.10 36.60 0.462 Spring (Mar-May) 6,065 10.87 10.56 -0.32 4.20 1.70 39.00 0.181
Summer (Jun-Aug) 6,119 12.76 9.59 -3.17 6.65 -35.40 60.90 0.077Fall (SepNov) 5,914 10.43 8.71 -1.71 4.63 -15.40 48.70 0.176
Annual 23,792 11.30 10.07 -1.24 4.85 -11.50 46.50 0.187

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(e) Great Lakes States

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,361 14.11 15.03 0.92 4.52 4.70 32.20 0.446 Spring (Mar-May) 6,000 12.91 13.75 0.84 5.05 13.10 39.40 0.342
Summer (Jun-Aug) 5,938 14.52 11.34 -3.18 6.13 -27.60 49.10 0.220Fall (SepNov) 5,807 13.23 12.22 -1.01 5.15 -3.80 41.00 0.275
Annual 23,106 13.68 13.04 -0.64 5.23 -3.50 40.60 0.295

(f) Southeast

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,925 10.01 8.77 -1.24 3.46 -12.80 37.40 0.283 Spring (Mar-May) 10,522 13.95 10.94 -3.01 5.41 -15.80 39.00 0.138
Summer (Jun-Aug) 10,156 16.56 9.82 -6.74 8.68 -50.60 63.90 0.053Fall (SepNov) 10,123 11.36 8.54 -2.82 4.59 -27.20 46.60 0.265
Annual 40,726 13.00 9.54 -3.46 5.55 -26.60 46.70 0.144

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(g) Northeast

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,731 12.04 12.47 0.43 4.83 3.10 40.30 0.342 Spring (Mar-May) 7,055 9.93 12.50 2.57 4.57 28.20 43.50 0.411
Summer (Jun-Aug) 7,045 15.68 13.41 -2.27 6.37 -15.60 44.80 0.323Fall (SepNov) 7,177 11.27 11.96 0.69 4.30 10.10 38.90 0.407
Annual 28,008 12.23 12.58 0.36 5.02 6.50 41.90 0.348



### For 2007, model performance for 24-hour average PM 2.5 

### is a mix of over and underestimation of the observed values. For many of the regions and time periods, the bias and error statistics indicate good model performance. However, as for 2006, the annual cycle of PM 2.5 

### concentrations indicated by the observations is not replicated by the model.


### Dry Deposition

Table 4-17 compares the simulated and observed annual deposition amounts and provides summary annual performance metrics for dry deposition species for the entire U.S. for 2007.

Table 4-17. Annual GEOS-CHEM Model Performance Statisti cs for Dry Deposition (kg/ha) for the Base Case (Current Atmosphere Scenario) for the Continental U.S.: 2007.

Time Period # Data Pairs Mean Observed

(kg/ha) Mean Simulated

(kg/ha) Mean Residual (kg/ha) Mean Unsigned Error (kg/ha) Fractional Bias (%) Fractional Error (%) R 2

Nitric acid (HNO 3 ) 82 5.12 6.56 1.43 2.71 24.40 51.30 0.284
Ammonium (NH 4 ) 82 0.35 0.23 -0.13 0.16 -40.60 60.90 0.479
Particulate nitrate (NO 3 ) 82 0.29 0.31 0.02 0.19 -0.80 80.30 0.171 Ozone (O 3 ) 80 37.78 35.77 -2.01 11.32 -4.60 32.10 0.100
Sulfur dioxide (SO 2 ) 82 3.03 4.33 1.30 1.75 44.30 54.40 0.456 Sulfate (SO 4 ) 82 1.02 0.44 -0.58 0.61 -73.60 82.40 0.453

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11-035 

### Model performance for dry deposition for 2007 is similar to that for 2006, but is characterized by less underestimation of ozone dry deposition. The modeled results are about the same for both years; the observed values are different.


## Summary Model Performance Results for 2008
In this section, the GEOS-Chem results for 2008 are compared to observed data for ozone, other gaseous species, fine particulate matter, and dry deposition.



### Ozone

The two metrics used for the calculation of stat istical measures for ozone are: 24-hour average ozone and MDA8 ozone. Table 4-18 lists the seasonal and annual performance metrics for 24- hour average ozone for the entire U.S. and each of the six model performance subregions for 2008, calculated using the CASTNet data. Units are ppb.Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsTable 4-18. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case(Current Atmosphere Scenario) Using CASTNet Data: 2008.(a) Entire Continental U.S.TimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)6,99329.2730.421.156.0411.6027.504.3023.200.479Spring(Mar-May)7,09741.9644.562.597.6511.7022.107.3018.900.257Summer(Jun-Aug)6,90738.7550.7412.0013.6842.3045.3029.4032.800.308Fall (SepNov)6,96030.3139.999.6810.9746.6050.5029.2033.700.394Annual27,95735.0941.416.329.5627.9036.2017.5027.100.401ICF International89October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(b) West CoastTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)62735.2535.310.067.8413.3031.504.4025.000.165Spring(Mar-May)70446.8345.45-1.387.853.1020.00-0.6018.100.399Summer(Jun-Aug)58952.0854.772.6910.2212.1024.606.7020.700.634Fall (SepNov)63438.5445.627.089.7447.5052.8023.1029.000.594Annual2,55443.1445.152.018.8618.7032.008.2023.100.558(c) Intermountain WestTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,14340.4139.04-1.364.850.9015.10-2.3013.200.300Spring(Mar-May)1,13350.4947.81-2.676.64-1.8015.10-4.2014.200.229Summer(Jun-Aug)1,16446.0850.884.807.8817.1022.8011.8018.000.283Fall (SepNov)1,14638.2143.475.256.9228.6032.6015.2019.500.316Annual4,58643.7945.321.536.5811.2021.405.2016.200.328ICF International90October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(d) Central StatesTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)86628.9731.752.796.6319.6031.1011.0024.300.204Spring(Mar-May)89338.7441.542.807.0314.8023.609.6019.300.235Summer(Jun-Aug)87835.1245.3810.2611.5641.7044.6027.4030.700.127Fall (SepNov)88929.7936.897.108.5035.6039.8022.4027.100.274Annual3,52633.1838.925.748.4327.9034.8017.6025.300.259(e) Great Lakes StatesTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,16923.7822.75-1.035.26-0.5025.60-6.6025.900.432Spring(Mar-May)1,18338.4640.752.306.797.3019.204.2018.100.316Summer(Jun-Aug)1,12735.5752.2616.6916.8150.2050.5037.6037.900.286Fall (SepNov)1,10725.6635.189.5210.7839.6045.2028.1034.900.542Annual4,58630.9237.656.739.8323.6034.8015.4029.000.486ICF International91October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsICF International92October 28, 201111-035(f) SoutheastTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,86927.0330.793.766.8421.7031.4013.9025.100.335Spring(Mar-May)1,87240.6547.036.389.3123.3029.0016.6022.800.173Summer(Jun-Aug)1,78737.1551.5714.4315.6253.9056.0036.1038.400.166Fall (SepNov)1,87930.1943.2613.0713.9257.6060.0037.4040.000.276Annual7,40733.7143.079.3611.3839.0044.0025.9031.500.320(g) NortheastTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,31925.0226.041.025.3611.4030.001.5025.100.542Spring(Mar-May)1,31239.2343.223.997.2413.0020.909.3018.100.266Summer(Jun-Aug)1,36233.7949.9916.2016.3455.6055.9040.0040.300.480Fall (SepNov)1,30523.8535.6911.8412.7159.4063.1038.3042.700.295Annual5,29830.5138.838.3210.4635.0042.6022.4031.600.445Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results



### Model performance is similar to that for 2006 and 2007. Ozone is overestimated for most regions and time periods and the greatest amount of overestimation tends to occur during the summer months and autumn months.

Table 4-19 lists the seasonal and annual performance metrics for maximum daily 8-hour average (MDA8) ozone for the entire U.S. and each of the six model performance subregions for 2008, calculated using the CASTNet data. Units are ppb.

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11-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsTable 4-19. Seasonal and Annual GEOS-CHEM Model Performance Statistics for Maximum Daily 8-hourAverage (MDA8) Ozone Concentration (ppb) for the Base Case(Current Atmosphere Scenario) Using CASTNet Data: 2008.(a) Entire Continental U.S.TimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)6,98134.7537.072.335.6412.4021.207.3017.400.487Spring(Mar-May)7,18250.3553.963.607.5610.3017.407.4015.000.320Summer(Jun-Aug)6,99550.1963.2313.0414.8631.9034.6024.0027.000.392Fall (SepNov)7,02038.8249.7010.8711.8134.6036.7025.5027.800.518Annual28,17843.5751.017.449.9522.2027.4016.0021.800.514ICF International94October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(b) West CoastTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)63040.7541.680.935.647.5017.604.1015.000.300Spring(Mar-May)70955.9555.19-0.767.160.8013.60-1.0013.000.473Summer(Jun-Aug)59768.1370.682.5513.567.0021.203.6019.400.579Fall (SepNov)63748.2055.427.2210.5526.8031.9017.2022.700.602Annual2,57353.1455.532.409.1110.3020.905.8017.400.632(c) Intermountain WestTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError(ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,14344.1443.60-0.543.940.609.90-0.609.400.387Spring(Mar-May)1,15056.2954.60-1.705.51-1.3010.70-2.6010.300.270Summer(Jun-Aug)1,17353.7759.035.268.1412.8017.709.7015.000.258Fall (SepNov)1,16243.8250.506.687.5218.9020.8014.7016.700.464Annual4,62849.5251.972.456.307.8014.805.4012.900.420ICF International95October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & Results(d) Central StatesTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)86734.4937.683.196.0519.7027.2010.1018.500.266Spring(Mar-May)90947.4649.592.136.518.5016.505.8014.400.317Summer(Jun-Aug)89144.8356.1211.2912.4531.2033.5022.9025.400.243Fall (SepNov)89838.3445.557.218.4123.9026.7017.8020.900.524Annual3,56541.3547.315.968.3620.8025.9014.1019.800.415(e) Great Lakes StatesTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,16329.0930.101.015.267.1020.503.4019.200.340Spring(Mar-May)1,18947.2852.094.817.6811.2017.508.5015.700.448Summer(Jun-Aug)1,14048.0467.6019.5619.7442.9043.3033.4033.800.419Fall (SepNov)1,11435.1847.4912.3013.0437.5040.0028.6031.600.696Annual4,60639.9549.269.3111.3524.4030.1018.2024.900.629ICF International96October 28, 201111-035Modeling for North AmericanBackground ConcentrationsModel Performance Evaluation Procedures & ResultsICF International97October 28, 201111-035(f) SoutheastTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,86633.7538.394.646.7318.6024.1013.8019.900.417Spring(Mar-May)1,89650.0256.656.628.7318.1021.6013.9017.600.274Summer(Jun-Aug)1,81948.8363.2814.4515.1237.4038.4028.1029.100.329Fall (SepNov)1,89139.5752.9813.4113.8840.7041.8030.4031.500.493Annual7,47243.0252.779.7511.0928.7031.4021.5024.500.490(g) NortheastTimePeriod# DataPairsMeanObserved(ppb)MeanSimulated(ppb)MeanResidual(ppb)MeanUnsignedError (ppb)NormalizedBias (%)NormalizedGross Error(%)FractionalBias (%)FractionalError (%)R2Winter(Dec-Feb)1,31230.3033.092.795.6215.9025.408.0019.500.425Spring(Mar-May)1,32947.4353.576.148.4914.8019.5011.3016.500.375Summer(Jun-Aug)1,37546.3964.4718.0818.3242.9043.3032.8033.300.578Fall (SepNov)1,31832.2346.2113.9814.5148.4049.9034.4036.200.430Annual5,33439.1949.5210.3311.8130.6034.6021.7026.400.570Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results



### Model performance for MDA8 for 2008 is about the same as that for 2006 and 2007, only very slightly worse overall. Again, the 8-hour average ozone concentrations are overestimated for nearly all regions and time periods but the bias and error statistics suggest reasonably good performance.

Similar to the other years, model performance varies by season and by subregion and the best agreement with the observations is achieved for the Intermountain West subregion. The normalized bias for this subregion for the annual period is 7.8 percent, while the corresponding gross error is 14.8 percent. The fractional bias is 5.4 percent and the corresponding fractional error is 12.9 percent.

For the entire U.S., the mean residual or difference between the simulated and observed values ranges from approximately 2.3 to 13 ppb for the four seasonal periods and is 7.4 for the annual period. The normalized bias for the annual period is 22.2 percent, while the corresponding gross error is 27.4 percent. The fractional bias is 16 percent and the corresponding fractional error is 21.8 percent. Figure 4-15 displays the agreement between the mean simulated and observed MDA8 concentrations for the seasonal and annual periods for the entire U.S.

Figure 4-15. Comparison of the Mean Simulated and Mean Observed MDA8 Oz one Concentrations (ppb) for Each Season and the Entire Year, Averaged Over All Sites in Entire Continental U.S.: 2008.

Seasonal & Annual Mean Ozone Concentration (ppb)

25 35 45 55 65 75

25 35 45 55 65 75
ObservedGEOS-Chem

Spring Summer Fall Winter Annual



### Time-series and scatter plots illustrating site-specific model performance for MDA8 ozone concentration for the West Coast subregion are provided in Figure 4-16 . The West Coast sites (listed in order of elevation) are: Pinnacles NM, CA (elevation 335 meters (m)) Mount Rainier NP, WA (elevation 415 m), Joshua Tree NM, CA (elevation 1244 m), and Lassen Volcanic NP, CA (elevation 1756 m). In the time series plots, the observed values are in blue and the simulated values are in green. Note that the scale varies by site, based on concentration.

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Figure 4-16. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the West Coast Subregion: 2008. (a) Pinnacles NM

CASTNet Site Pinnacles NM, CA (PIN414) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Pinnacles NM, CA (PIN414) MDA8: 2008

R 2 = 0.6047

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100Simulated

Observed

(b) Mount Rainier NP

CASTNet Site Mount Rainier NP, WA (MOR409) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Mount Rainier NP, WA (MOR409) MDA8: 2008

R 2 = 0.3282

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Joshua Tree NM

CASTNet Site Joshua Tree NM, CA (JOT403) MDA8: 2008

0 20 40 60 80 100 120 140

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Joshua Tree NM, CA (JOT403) MDA8: 2008

R 2 = 0.6758

0 20 40 60 80 100 120 140

0 20 40 60 80 100 120 140

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(d) Lassen Volcanic NP

CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2008

R 2 = 0.502

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100 110

ObservedSimulated



### Time-series and scatter plots for the Intermountain West subregion are provided in Figure 4-17

. The Intermountain West sites are: Chiricahua NM, AZ (elevation 1570 m), Great Basin NP, NV (elevation 2060 m), Pinedale, WY (elevation 2388 m), and Rocky Mountain NP, CO (elevation 2743 m).

Figure 4-17. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Intermoun tain West Subregion: 2008. (a) Chiricahua NM

CASTNet Site Chiricahua NM, AZ (CHA467) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Chiricahua NM, AZ (CHA467) MDA8: 2008

R 2 = 0.5026

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(b) Great Basin NP

CASTNet Site Great Basin NP, NV (GRB411) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Great Basin NP, NV (GRB411) MDA8: 2008

R 2 = 0.512

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Pinedale

CASTNet Site Pinedale, WY (PND165) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Pinedale, WY (PND165) MDA8: 2008

R 2 = 0.3767

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Rocky Mountain NP

CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: 2008

R 2 = 0.3914

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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### Time-series and scatter plots for the Central States subregion are provided in Figure 4-18 . The Central States sites are: Caddo Valley, AR (elevation 71 m), Konza Prairie, KS (elevation 348 m), Theodore Roosevelt NP, ND (elevation 850 m), and Big Bend NP, TX (elevation 1052 m).

Figure 4-18. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in Central States Subregion: 2008. (a) Caddo Valley

CASTNet Site Caddo Valley, AR (CAD150) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Caddo Valley, AR (CAD150) MDA8: 2008

R 2 = 0.3452

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(b) Konza Prairie

CASTNet Site Konza Prairie, KS (KNZ184) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Konza Prairie, KS (KNZ184) MDA8: 2008

R 2 = 0.5428

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(c) Theodore Roosevelt NP

CASTNet Site Theodore Roo sevelt NP, ND (THR422) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Theodore Roosevelt NP, ND (THR422) MDA8: 2008

R 2 = 0.5645

0 10 20 30 40 50 60 70 80 90 100

0 2 0 4 0 6 0 8 0 1 0 0

ObservedSimulated

(d) Big Bend NP

CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2008

R 2 = 0.4607

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Great Lakes subregion are provided in Figure 4-19 . The Great Lakes sites are: Salamonie Reservoir, IN (elevation 250 m), Ann Arbor, MI (elevation 267 m), Oxford, OH (elevation 284 m), and Perkinstown, WI (elevation 472 m).

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Figure 4-19. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Great Lakes Subregion: 2008. (a) Salamonie Reservoir

CASTNet Site Salamonie Reservoir, IN (SAL133) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Salamonie Reservoir, IN (SAL133) MDA8: 2008

R 2 = 0.7053

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(b) Ann Arbor

CASTNet Site Unionville, MI (ANA115) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Unionville, MI (ANA115) MDA8: 2008

R 2 = 0.596

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Oxford

CASTNet Site Oxford, OH (OXF122) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Oxford, OH (OXF122) MDA8: 2008

R 2 = 0.6467

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120

ObservedSimulated

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(d) Perkinstown

CASTNet Site Perkinstown, WI (PRK134) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Perkinstown, WI (PRK134) MDA8: 2008

R 2 = 0.4394

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### Time-series and scatter plots for the Southeast subregion are provided in Figure 4-20 . The Southeast sites are: Sumatra, FL (elevation 14 m), Cadiz, KY (elevation 189 m), Sand Mountain, AL (elevation 352 m), and Great Smoky Mountain NP, TN (elevation 793 m).

Figure 4-20. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Southeast Subregion: 2008. (a) Sumatra

CASTNet Site Sumatra, FL (SUM156) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Sumatra, FL (SUM156) MDA8: 2008

R 2 = 0.3979

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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(b) Cadiz

CASTNet Site Cadiz, KY (CDZ171) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Cadiz, KY (CDZ171) MDA8: 2008

R 2 = 0.5764

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(c) Sand Mountain

CASTNet Site Sand Mountain, AL (SND152) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Sand Mountain, AL (SND152) MDA8: 2008

R 2 = 0.556

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Great Smoky Mountain NP

CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2008

R 2 = 0.6463

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

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### Time-series and scatter plots for the Northeast subregion are provided in Figure 4-21 . The Northeast sites are Blackwater NWR, MD (elevation 4 m), Acadia NP, ME (elevation 158 m), Penn State, PA (elevation 378 m), and Huntington Wildlife Forest, NY (elevation 502 m).

Figure 4-21. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for Selected CASTNet Sites in the Northeast Subregion: 2008. (a) Blackwater NWR

CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2008

R 2 = 0.704

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120

ObservedSimulated

(b) Acadia NP

CASTNet Site Acadia NP, ME (ACA416) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Acadia NP, ME (ACA416) MDA8: 2008

R 2 = 0.3558

0 10 20 30 40 50 60 70 80 90 100 110 120

0 10 20 30 40 50 60 70 80 90 100 110 120 130

ObservedSimulated

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(c) Penn State

CASTNet Site Penn State, PA (PSU106) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Penn State, PA (PSU106) MDA8: 2008

R 2 = 0.6704

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated

(d) Huntington Wildlife Forest

CASTNet Site Huntington Wildlife Forest, NY (HWF187) MDA8: 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361
Dayppb

Obs Sim CASTNet Site Huntington Wildlife Forest, NY (HWF187) MDA8: 2008

R 2 = 0.4002

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

ObservedSimulated



### For the AQS sites, only 24-hour average ozone was considered. The results are similar to those for 2006 and 2007 in that the 24-hour ozone concentrations are overestimated for all subregions and periods.

Table 4-20 lists the seasonal and annual performance metrics for 24-hour average ozone for the entire U.S. and each of the six model performance subregions for 2008, calculated using the AQS data. Normalized bias and error statistics are not included in this table. Units are ppb.

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Table 4-20. Seasonal and Annual GEOS-CHEM Model Performa nce Statistics for 24-hour Average Ozone Concentration (ppb) for the Base Case (Current Atmosp here Scenario) Using AQS Data: 2008. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 52,990 22.73 30.63 7.90 9.75 34.50 41.80 0.246 Spring (Mar-May) 91,203 36.45 43.73 7.28 9.49 19.70 25.00 0.242
Summer (Jun-Aug) 108,009 33.95 50.15 16.20 17.05 39.80 41.80 0.262Fall (SepNov) 83,873 25.46 41.23 15.77 16.25 49.40 51.00 0.286
Annual 336,075 30.73 43.10 12.36 13.65 35.90 39.60 0.320

(b) West Coast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 15,086 20.78 30.78 10.01 11.80 47.50 53.20 0.152 Spring (Mar-May) 16,582 35.95 41.18 5.23 8.90 15.30 24.40 0.246
Summer (Jun-Aug) 18,523 36.74 47.47 10.73 13.93 23.60 31.60 0.325Fall (SepNov) 16,919 27.01 42.45 15.44 16.43 48.30 50.90 0.280
Annual 67,110 30.50 40.90 10.40 12.84 33.10 39.50 0.328

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(c) Intermountain West

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,587 26.08 35.34 9.26 11.21 38.40 43.60 0.188 Spring (Mar-May) 11,651 42.11 46.36 4.25 8.32 11.50 20.00 0.120
Summer (Jun-Aug) 13,743 41.04 51.12 10.08 11.41 22.60 25.40 0.167Fall (SepNov) 11,765 28.84 43.01 14.17 14.68 43.00 44.40 0.163
Annual 46,746 35.17 44.66 9.49 11.42 28.20 32.60 0.297

(d) Central States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 13,043 22.91 28.64 5.73 7.27 26.10 32.30 0.341 Spring (Mar-May) 17,211 34.71 40.64 5.93 7.97 17.30 22.50 0.255
Summer (Jun-Aug) 18,926 29.03 45.81 16.78 16.96 47.20 47.60 0.356Fall (SepNov) 16,001 25.69 38.78 13.09 13.53 41.90 43.50 0.314
Annual 65,181 28.48 39.28 10.80 11.81 33.80 36.90 0.319

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(e) Great Lakes States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,937 19.53 20.97 1.44 5.22 6.50 29.00 0.483 Spring (Mar-May) 12,201 35.33 43.12 7.79 9.15 20.60 24.40 0.228
Summer (Jun-Aug) 16,984 33.01 52.13 19.12 19.17 44.70 44.90 0.243Fall (SepNov) 9,796 23.67 39.55 15.88 16.22 49.90 51.70 0.430
Annual 41,918 30.56 44.39 13.83 14.59 36.20 39.40 0.358

(f) Southeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,652 25.21 37.00 11.79 12.58 39.90 42.70 0.185 Spring (Mar-May) 20,489 35.98 46.97 11.00 11.91 28.50 30.60 0.279
Summer (Jun-Aug) 22,919 32.18 52.02 19.84 20.12 50.40 50.90 0.213Fall (SepNov) 17,453 25.42 45.13 19.71 19.82 58.20 58.60 0.262
Annual 67,513 30.90 47.23 16.33 16.81 44.80 45.90 0.245

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(g) Northeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,685 20.77 24.09 3.32 6.17 19.20 34.50 0.514 Spring (Mar-May) 13,069 36.34 44.34 8.00 9.77 20.60 25.20 0.292
Summer (Jun-Aug) 16,914 34.18 52.89 18.70 18.92 43.70 44.20 0.361Fall (SepNov) 11,939 21.34 36.87 15.53 15.95 53.70 55.70 0.309
Annual 47,607 29.95 43.09 13.13 14.14 36.90 40.70 0.440



### NO 2 

### , SO 2 

### , CO, and PM 2.5


### Table 4-21 lists the seasonal and annual performance metrics for 24-hour average NO 2 

### for the entire U.S. and each of the six model performance subregions for 2008, calculated using the AQS data. Normalized bias and error statistics are not included in this table. Units are ppb.

Table 4-21. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average NO 2 Concentration (ppb) for the Base Case (Current Atmosphere Scenario): 2008. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 33,591 13.33 7.48 -5.85 7.04 -45.90 68.40 0.294 Spring (Mar-May) 34,088 9.97 5.31 -4.66 5.68 -48.10 73.00 0.333
Summer (Jun-Aug) 34,130 8.19 5.20 -2.99 4.50 -32.10 68.60 0.262Fall (SepNov) 32,825 11.74 6.30 -5.44 6.63 -45.60 73.10 0.296
Annual 134,634 10.79 6.07 -4.72 5.95 -42.90 70.70 0.317

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(b) West Coast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,525 14.96 6.95 -8.02 8.57 -70.70 82.10 0.347 Spring (Mar-May) 9,606 11.04 5.51 -5.53 6.32 -62.80 79.10 0.388
Summer (Jun-Aug) 9,334 9.76 5.76 -4.00 5.00 -48.70 67.60 0.377Fall (SepNov) 9,337 15.34 6.47 -8.87 9.46 -73.50 85.50 0.340
Annual 37,802 12.77 6.17 -6.61 7.34 -63.90 78.60 0.355

(c) Intermountain West

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,695 14.83 4.66 -10.18 10.49 -76.40 100.10 0.482 Spring (Mar-May) 3,773 9.22 3.18 -6.04 6.32 -75.60 99.10 0.489
Summer (Jun-Aug) 3,654 7.12 3.08 -4.03 4.41 -65.60 88.60 0.394Fall (SepNov) 3,668 11.35 3.98 -7.37 7.64 -72.40 99.00 0.497
Annual 14,790 10.63 3.72 -6.91 7.22 -72.50 96.70 0.486

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(d) Central States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,376 9.37 6.55 -2.82 4.53 -21.60 56.00 0.253 Spring (Mar-May) 8,376 6.99 4.82 -2.17 3.67 -20.70 60.60 0.229
Summer (Jun-Aug) 8,350 5.50 5.66 0.16 3.24 12.50 61.90 0.170Fall (SepNov) 7,920 8.44 5.91 -2.54 4.34 -15.60 61.60 0.284
Annual 33,022 7.57 5.73 -1.84 3.94 -11.30 60.00 0.236

(e) Great Lakes States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 1,499 17.12 11.89 -5.23 6.34 -28.20 40.60 0.398 Spring (Mar-May) 1,546 14.41 7.94 -6.47 7.31 -44.40 58.10 0.354
Summer (Jun-Aug) 1,782 11.96 6.61 -5.36 5.98 -45.00 56.80 0.415Fall (SepNov) 1,572 15.00 9.70 -5.30 6.04 -36.80 47.30 0.457
Annual 6,399 14.51 8.93 -5.58 6.40 -38.90 51.00 0.410

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(f) Southeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,240 10.23 7.13 -3.10 4.87 -26.70 58.80 0.276 Spring (Mar-May) 4,076 7.97 4.62 -3.35 4.49 -40.30 68.50 0.226
Summer (Jun-Aug) 4,150 6.54 4.31 -2.23 3.80 -22.10 68.90 0.042Fall (SepNov) 4,047 8.33 5.61 -2.72 4.63 -21.90 67.30 0.169
Annual 16,513 8.28 5.43 -2.85 4.45 -27.70 65.80 0.224

(g) Northeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,256 16.44 10.41 -6.03 7.68 -40.10 58.50 0.230 Spring (Mar-May) 6,711 12.76 6.66 -6.10 7.25 -51.40 71.00 0.262
Summer (Jun-Aug) 6,860 9.93 5.20 -4.73 5.45 -48.40 70.20 0.341Fall (SepNov) 6,281 12.14 7.48 -4.66 6.14 -43.90 64.30 0.257
Annual 26,108 12.75 7.37 -5.38 6.61 -46.10 66.20 0.301



### For 2008, the 24-hour average NO 2 

### concentrations are underestimated for all subregions and time periods. Model performance is worst for the West Coast and Intermountain West subregions. Elsewhere, the fractional bias indica tes that the modeled values are well within a factor of two (67 percent) of the observed values.

Table 4-22 lists the seasonal and annual performance metrics for 24-hour average SO 2 

### for the entire U.S. and each of the six model performance subregions for 2008, calculated using the AQS data. Units are ppb.

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Table 4-22. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average SO 2 Concentration (ppb) for the Base Case (Current Atmosphere Scenario): 2008. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 36,649 3.41 5.78 2.37 3.96 58.30 95.30 0.121 Spring (Mar-May) 40,166 2.72 4.23 1.50 3.10 57.20 99.00 0.098
Summer (Jun-Aug) 39,697 2.45 4.35 1.89 3.17 68.10 103.10 0.093Fall (SepNov) 38,290 2.58 4.90 2.32 3.57 69.40 103.70 0.102
Annual 157,802 2.79 4.81 2.02 3.45 63.20 100.20 0.110

(b) West Coast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,737 1.05 1.46 0.41 0.96 37.40 92.80 0.121 Spring (Mar-May) 3,607 1.01 1.23 0.21 0.81 33.70 91.80 0.158
Summer (Jun-Aug) 3,617 1.01 1.42 0.41 0.84 48.80 89.10 0.160Fall (SepNov) 3,647 1.15 1.59 0.43 0.98 44.30 89.80 0.175
Annual 14,608 1.06 1.42 0.37 0.90 41.00 90.90 0.153

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(c) Intermountain West

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,576 2.13 0.89 -1.24 1.77 -6.60 106.90 0.018 Spring (Mar-May) 2,599 1.62 0.64 -0.98 1.43 0.60 117.20 0.025
Summer (Jun-Aug) 2,510 1.94 0.68 -1.26 1.68 2.20 117.90 0.115Fall (SepNov) 2,448 2.42 0.84 -1.58 2.02 -15.80 106.80 0.051
Annual 10,133 2.02 0.76 -1.26 1.72 -4.80 112.20 0.047

(d) Central States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,832 2.27 3.21 0.94 2.83 72.90 106.50 0.013 Spring (Mar-May) 9,118 1.94 2.39 0.45 2.35 75.10 117.60 0.017
Summer (Jun-Aug) 8,792 1.58 2.83 1.24 2.53 93.50 123.80 0.008Fall (SepNov) 8,310 1.73 3.04 1.32 2.53 90.70 117.50 0.045
Annual 35,052 1.88 2.86 0.98 2.56 82.90 116.30 0.017

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(e) Great Lakes States

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 6,777 4.21 8.58 4.38 5.69 83.70 97.20 0.049 Spring (Mar-May) 6,821 3.66 6.54 2.88 4.43 77.90 94.30 0.053
Summer (Jun-Aug) 6,767 3.19 6.55 3.36 4.49 83.30 99.50 0.028Fall (SepNov) 6,617 3.23 7.65 4.43 5.34 93.30 105.90 0.037
Annual 26,982 3.57 7.33 3.76 4.98 84.50 99.20 0.045

(f) Southeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 8,154 3.82 7.23 3.41 4.84 78.70 94.30 0.067 Spring (Mar-May) 8,189 3.48 5.51 2.03 3.80 66.90 90.10 0.075
Summer (Jun-Aug) 8,247 3.28 5.64 2.36 4.01 76.10 98.60 0.051Fall (SepNov) 7,903 3.17 6.29 3.11 4.41 83.90 101.60 0.082
Annual 32,493 3.44 6.16 2.72 4.26 76.30 96.10 0.069

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(g) Northeast

Time Period # Data Pairs Mean Observed (ppb) Mean Simulated (ppb) Mean Residual

(ppb) Mean Unsigned Error (ppb) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,573 5.06 8.70 3.64 5.13 51.40 75.30 0.132 Spring (Mar-May) 9,832 3.15 5.79 2.64 3.72 59.10 85.70 0.142
Summer (Jun-Aug) 9,764 2.77 5.60 2.83 3.55 66.30 87.80 0.207Fall (SepNov) 9,365 3.07 6.42 3.36 4.22 68.50 90.50 0.161
Annual 38,534 3.51 6.62 3.11 4.15 61.30 84.80 0.181



### For 2008, model performance for 24-hour average SO 2 

### concentrations varies by subregion. Again SO 2 

### is underestimated in the Intermountain West, where observed values are low and overestimated elsewhere, including in the East where observed values are higher.

Table 4-23 lists the seasonal and annual performance metrics for 24-hour average CO for the entire U.S. and each of the six model performance subregions for 2008, calculated using the AQS data. Units are ppm.

Table 4-23. Seasonal and Annual GEOS-CHEM Model Performa nce Statistics for 24-hour Average CO Concentration (ppm) for the Base Case (Current Atmosphere Scenario): 2008. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 30,496 0.46 0.27 -0.19 0.26 -33.30 67.80 0.029 Spring (Mar-May) 29,941 0.35 0.23 -0.12 0.18 -22.90 61.40 0.026
Summer (Jun-Aug) 29,093 0.31 0.23 -0.08 0.18 -11.50 64.70 0.009Fall (SepNov) 29,651 0.39 0.23 -0.16 0.23 -27.30 69.50 0.039
Annual 119,181 0.38 0.24 -0.14 0.21 -23.90 65.80 0.033

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(b) West Coast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 7,603 0.53 0.28 -0.25 0.29 -49.40 64.30 0.088 Spring (Mar-May) 7,675 0.36 0.24 -0.11 0.17 -24.20 55.90 0.064
Summer (Jun-Aug) 7,446 0.30 0.26 -0.05 0.16 -9.40 59.00 0.035Fall (SepNov) 7,274 0.46 0.27 -0.19 0.24 -38.80 63.10 0.125
Annual 29,998 0.41 0.26 -0.15 0.22 -30.50 60.60 0.083

(c) Intermountain West

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,432 0.57 0.19 -0.38 0.39 -77.10 90.90 0.071 Spring (Mar-May) 4,713 0.35 0.17 -0.18 0.21 -47.70 75.70 0.078
Summer (Jun-Aug) 3,965 0.33 0.16 -0.17 0.20 -46.40 76.80 0.003Fall (SepNov) 5,087 0.46 0.17 -0.29 0.31 -65.80 85.70 0.044
Annual 19,197 0.44 0.17 -0.26 0.29 -60.60 82.90 0.073

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(d) Central States

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,670 0.31 0.21 -0.09 0.19 -10.70 67.80 0.000 Spring (Mar-May) 4,526 0.27 0.18 -0.09 0.14 -18.00 60.20 0.013
Summer (Jun-Aug) 4,497 0.22 0.17 -0.05 0.12 -1.50 62.30 0.048Fall (SepNov) 4,476 0.29 0.18 -0.10 0.17 -12.50 70.30 0.028
Annual 18,169 0.27 0.19 -0.09 0.16 -10.70 65.20 0.016

(e) Great Lakes States

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 2,526 0.45 0.32 -0.13 0.23 -20.20 56.80 0.016 Spring (Mar-May) 2,589 0.44 0.26 -0.18 0.23 -33.60 57.70 0.024
Summer (Jun-Aug) 2,705 0.36 0.25 -0.11 0.18 -18.80 56.90 0.000Fall (SepNov) 2,661 0.39 0.26 -0.13 0.21 -21.70 60.30 0.016
Annual 10,481 0.41 0.27 -0.14 0.21 -23.50 57.90 0.019

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(f) Southeast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,351 0.44 0.27 -0.17 0.24 -28.10 64.00 0.006 Spring (Mar-May) 4,306 0.38 0.22 -0.15 0.20 -28.20 63.00 0.003
Summer (Jun-Aug) 4,332 0.37 0.23 -0.14 0.21 -26.30 66.40 0.000Fall (SepNov) 4,078 0.38 0.23 -0.15 0.22 -26.80 66.80 0.009
Annual 17,067 0.39 0.24 -0.15 0.22 -27.40 65.00 0.006

(g) Northeast

Time Period # Data Pairs Mean Observed

(ppm) Mean Simulated

(ppm) Mean Residual

(ppm) Mean Unsigned Error (ppm) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,914 0.41 0.35 -0.05 0.20 3.90 55.80 0.132 Spring (Mar-May) 6,132 0.31 0.28 -0.04 0.15 7.50 54.70 0.103
Summer (Jun-Aug) 6,148 0.29 0.28 -0.01 0.16 21.30 63.50 0.084Fall (SepNov) 6,075 0.32 0.27 -0.05 0.18 11.10 64.90 0.119
Annual 24,269 0.33 0.30 -0.04 0.17 11.00 59.80 0.130



### For 2008, CO concentrations are underestimated for all regions and time periods.

Table 4-24 lists the seasonal and annual performance metrics for 24-hour average PM 2.5 

### for the entire U.S. and each of the six model performance subregions for 2008, calculated using the AQS data. Units are μ gm -3



### .

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Table 4-24. Seasonal and Annual GEOS-CHEM Model Performance Statistics for 24-hour Average PM 2.5

Concentration ( μ gm -3

) for the Base Case (Current At mosphere Scenario): 2008. (a) Entire Continental U.S.

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 35,672 11.12 10.03 -1.09 4.80 -10.60 45.60 0.197 Spring (Mar-May) 36,306 9.86 11.92 2.06 4.33 17.90 39.40 0.202
Summer (Jun-Aug) 36,395 12.68 10.50 -2.18 6.37 -24.20 53.20 0.055Fall (SepNov) 36,686 10.29 10.16 -0.13 4.75 -2.50 47.20 0.175
Annual 145,059 10.99 10.66 -0.33 5.07 -4.80 46.40 0.122

(b) West Coast

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 4,039 13.56 5.68 -7.88 8.67 -60.10 75.00 0.091 Spring (Mar-May) 3,772 8.87 10.85 1.98 4.96 17.50 47.30 0.141
Summer (Jun-Aug) 3,501 12.53 8.74 -3.79 6.46 -24.10 51.80 0.040Fall (SepNov) 3,963 12.89 7.62 -5.27 7.07 -41.50 60.80 0.050
Annual 15,275 11.99 8.16 -3.83 6.83 -27.90 59.20 0.027

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(c) Intermountain West

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 3,544 10.12 4.03 -6.09 6.77 -64.70 78.30 0.118 Spring (Mar-May) 3,618 7.18 11.62 4.44 6.28 33.10 54.50 0.095
Summer (Jun-Aug) 3,730 7.89 6.61 -1.28 5.45 -31.40 64.00 0.005Fall (SepNov) 3,768 7.97 4.35 -3.63 4.44 -48.10 63.60 0.028
Annual 14,660 8.28 6.64 -1.63 5.72 -27.80 65.00 0.009

(d) Central States

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,368 10.37 11.11 0.75 3.75 6.10 36.00 0.442 Spring (Mar-May) 5,560 9.90 11.06 1.16 3.75 13.40 36.40 0.177
Summer (Jun-Aug) 5,398 11.25 8.42 -2.83 5.83 -35.90 60.00 0.066Fall (SepNov) 5,386 10.22 10.09 -0.13 4.21 -0.10 43.00 0.300
Annual 21,712 10.43 10.18 -0.25 4.38 -4.00 43.80 0.213

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(e) Great Lakes States

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 5,623 13.31 13.84 0.53 4.57 4.80 34.60 0.328 Spring (Mar-May) 5,803 10.85 13.44 2.59 4.36 24.80 37.80 0.389
Summer (Jun-Aug) 5,894 12.81 11.87 -0.94 5.17 -13.10 44.30 0.228Fall (SepNov) 5,890 11.25 13.16 1.90 4.59 21.50 41.50 0.412
Annual 23,210 12.05 13.06 1.02 4.68 9.50 39.60 0.316

(f) Southeast

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 9,828 9.29 9.47 0.17 3.51 1.40 38.00 0.193 Spring (Mar-May) 10,109 10.95 11.04 0.09 3.21 1.20 30.00 0.276
Summer (Jun-Aug) 10,236 14.20 10.22 -3.97 7.40 -37.80 56.90 0.010Fall (SepNov) 10,270 10.55 9.92 -0.62 3.86 -7.50 39.10 0.248
Annual 40,443 11.27 10.17 -1.10 4.51 -10.80 41.10 0.082

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(g) Northeast

Time Period # Data Pairs Mean Observed

( μ gm -3 ) Mean Simulated

( μ gm -3 ) Mean Residual ( μ gm -3 ) Mean Unsigned Error ( μ gm -3 ) Fractional Bias (%) Fractional Error (%) R 2

Winter (Dec-Feb) 7,270 11.84 12.75 0.91 4.35 6.60 36.20 0.461 Spring (Mar-May) 7,444 9.58 13.43 3.86 4.87 33.80 42.90 0.406
Summer (Jun-Aug) 7,636 14.35 13.38 -0.97 6.09 -6.90 43.80 0.170Fall (SepNov) 7,409 9.22 12.80 3.58 5.46 31.60 48.30 0.202
Annual 29,759 11.27 13.09 1.83 5.20 16.20 42.80 0.262



### For 2008, model performance for 24-hour average PM 2.5 

### is a mix of over and underestimation of the observed values. Again the annual cycle of PM 2.5 

### concentrations indicated by the observations is not replicated by the model, but for many of the regions and time periods, the bias and error statistics indicate good model performance.


### Dry Deposition

Table 4-25 compares the simulated and observed annual deposition amounts and provides summary annual performance metrics for dry deposition species for the entire U.S. for 2008

Table 4-25. Annual GEOS-CHEM Model Performance Statisti cs for Dry Deposition (kg/ha) for the Base Case (Current Atmosphere Scenario) for the Continental U.S.: 2008.

Time Period # Data Pairs Mean Observed

(kg/ha) Mean Simulated

(kg/ha) Mean Residual (kg/ha) Mean Unsigned Error (kg/ha) Fractional Bias (%) Fractional Error (%) R 2

Nitric acid (HNO 3 ) 82 4.34 6.27 1.93 2.73 30.70 53.00 0.294
Ammonium (NH 4 ) 82 0.30 0.24 -0.06 0.10 -26.10 46.40 0.546
Particulate nitrate (NO 3 ) 82 0.27 0.34 0.06 0.19 11.20 79.40 0.246 Ozone (O 3 ) 80 37.81 35.39 -2.42 11.96 -6.20 34.90 0.084
Sulfur dioxide (SO 2 ) 82 2.77 4.38 1.61 1.92 52.80 61.00 0.453 Sulfate (SO 4 ) 82 0.87 0.46 -0.41 0.44 -62.60 69.40 0.491

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### Overall model performance for dry deposition for 2008 is slightly better than for the other two years. Again dry deposition of ozone is underestimated. The modeled results are about the same for all three years but the observed values are different.



## Year-to-Year Variations in Model Performance
Model performance for ozone is similar for a ll three years. Both 24-hour average and MDA8 ozone concentrations are overestimated for most regions and time periods. Statistics for MDA8 are similar for 2006 and 2007, and very slightly worse overall for 2008. For all three years, the MDA8 bias and error statistics suggest reasonably good performance and the best performance for ozone is achieved for the western subregions.

Model performance for NO 2 

### , SO 2 

### , and CO is also similar among the years. For all three years, 24-hour average NO 2, 

### and CO concentrations are generally underestimated while SO 2 

### concentrations are generally overestimated (except for the Intermountain West subregion).

Model performance for 24-hour average PM 2.5 

### is a mix of over and underestimation of the observed values and the bias and error statistics indicate good model performance for many of the subregions for all three years. The annual cycle of PM 2.5 

### concentrations indicated by the observations is not replicated by the model and this finding is also consistent among the modeled years.

Model performance for dry deposition is similar fo r all three years (slightly better for 2008). The statistical measures indica te generally good model performance. Dry deposition for ozone is underestimated for all three years, but to varying degrees. The modeled results are about the same for all three years but the observed values are different.



# 4.2. Case Studies

A more detailed examination of the GEOS-Chem results and the vertical distribution of ozone simulated by GEOS-Chem was conducted for selected case study periods. One objective was to examine how well the GEOS-Chem model is able to re present the vertical distribution of ozone in the troposphere under a variety of conditions, including, possibly, conditions associated with the stratospheric intrusion of ozone. Thus, this component of the model evaluation focused primarily on the western U.S., since stratospheric ozone intrusion is most likely to occur in this region and influence the vertical ozone profiles (Wimmers et al., 2003). The case study periods were selected based the availability of ozonesonde data from the INTEX-B (Thompson et al., 2008 and Thompson et al., 2011) and ARCTAS (ARC-IONS) (Thompson et al., 2011) programs with emphasis on data availability for the western U.S. and the simultaneous occurrence of high ozone concentrations at one or more of the CASTNet sites in the West Coast and Intermountain West subregions. Five periods were selected. At least one springtime period was desired, since springtime conditions can be conducive to stratospheric intrusion. One springtime period met the selection criteria given above. The remaining periods are summer periods that are primarily characterized by synoptic-scale high-pressure and stagnation over the western U.S. For each

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### case study period, the reasonableness of the GEOS-Chem ozone concentrations at both the surface and aloft, relative to the observed data, was examined.


## Case Study #1: 21 April 2006
Several CASTNet sites in California experienced relatively high ozone concentrations on 20 and 21 April. Ozonesonde data from the INTEX-B program are available for 21 April for Trinidad Head, CA. This day is the focus of the first case study analysis.

Regional weather conditions over California on 21 April 2006 were influenced by an upper-level ridge centered over the western states and an upper-level trough located off southern California, with moderate southwesterly winds aloft over t he Trinidad Head area. A weak surface cold front moved across northern California throughout the day as the upper-level low moved inland over central California, resulting in very light precipitation along the California/Oregon border.

The nearest CASTNet site to Trinidad Head is Lassen Volcanic NP. Figure 4-22 illustrates the simulated and observed MDA8 ozone for a multi-day day period that includes the case study day.

Figure 4-22. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for the Lassen NP CASTNet Site for 11-29 April 2006.

CASTNet Site Lassen Vol NP, CA (LAV410) MDA8: April 2006

0 10 20 30 40 50 60 70 80 90 100

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Dateppb

Obs Sim



### The model shows reasonably good skill in replicat ing the daily ozone concentrations, including the higher values during 19-21 April.

Figure 4-23 compares the simulated and observed vertical concentration profiles for Trinidad Head for 21 August. The simulated values match the time of the sounding. The ozonesonde data are plotted in blue and the GEOS-Chem-derived values for each model layer are plotted in gold. Note that in the output files used for this analysis, GEOS-Chem values are only available below the tropopause. The ozonesonde data are from the INTEX-B program data archive (Thompson et al., 2008 and Thompson et al., 2011).Modeling for North American Background Concentrations Model Performance Evaluation Procedures & Results

Figure 4-23. Vertical Profiles of Simulated and Observed Oz one Concentrations (ppb) for Trinidad Head for 21 April 2006. Observed Profile is Based on Ozones onde Data from the INTEX-B Program.

Ozone Profile for Trinidad Head, CA: 21 April 2006 (2000-2100 GMT)

0 2 4 6 8 10 12 14

0 20 40 60 80 100 120 140 160
Ozone (ppb)Alt (km)



### The simulated values are similar to the observ ed values between approximately 1 and 3 km in the vertical, and greater than the observed values at other levels, including near the surface. One might surmise from the observed ozone prof ile that high ozone concentrations in the upper troposphere may be associated with stratospheric ozone. The simulated ozone concentration profile does not follow the observed profile at these levels.


## Case Study #2: 14 July 2006
CASTNet sites in Arizona and Colorado experienced relatively high ozone concentrations during 13-15 July. Ozonesonde data from the INTEX-B progr am are available for 14 July for Boulder, CO. This day is the focus of the second case study analysis.

Regional weather over Colorado on 14 July 2006 was influenced by a broad, upper-level ridge centered over the Utah/Colorado area that covered the majority of the western U.S., resulting in very light and variable winds aloft. At the surface, the area was influenced by a large high pressure system centered over Colorado with light winds, above normal temperatures, and no precipitation.

The nearest CASTNet site to Boulder is Rocky Mountain NP. Figure 4-24 illustrates the simulated and observed MDA8 ozone for a multi-day day period that includes the case study day.

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Figure 4-24. Comparison of the Mean Simulated and Mean Observed MDA8 Oz one Concentrations (ppb) for the Rocky Mountain NP CASTNet Site for 8-20 July 2006.

CASTNet Site Rocky Mtn NP, CO (ROM406) MDA8: July 2006

0 10 20 30 40 50 60 70 80 90 100

8 9 10 11 12 13 14 15 16 17 18 19 20

Dateppb

Obs Sim



### The model overestimates the observed ozone concent rations by quite a lot but captures the day-to-day variations in ozone, especially during the days of interest for this case study.

Figure 4-25 compares the simulated and observed vertical concentration profiles for Boulder for 14 July. Again, the simulated values match the time of the sounding. The ozonesonde data are plotted in blue and the GEOS-Chem-derived values for each model layer are plotted in gold. The ozonesonde data are from the INTEX-B program data archive (Thompson et al., 2008 and Thompson et al., 2011).

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Figure 4-25. Vertical Profiles of Si mulated and Observed Ozone Concentrati ons (ppb) for Boulder for 14 July 2006. Observed Profile is Based on Ozonesond e Data from the INTEX-B Program.

Ozone Profile for Boulder, CO: 14 July 2006 (1800-1900 GMT)

0 2 4 6 8 10 12 14

0 20 40 60 80 100 120 140 160
Ozone (ppb)Alt (km)



### The simulated values are lower than observed between approximately 3 and 5 km in the vertical and greater than the observed values further aloft. The simulated ozone concentration profile does not resemble the observed profile.


## Case Study #3: 17-20 August 2006
CASTNet sites in California experienced relatively high ozone concentrations during midAugust. Ozonesonde data from the INTEX-B program are available for several areas and several days in August. Here we focus on 17- 20 August for Trinidad Head.

Weather conditions over the western U.S. during this period were influenced by a weak upperlevel trough situated over the Pacific Northwest and a weak upper-level ridge centered over the southeast U.S. By the end of the period, the weak trough had filled and moved eastward, replaced by a broad weak ridge that was centered over the central U.S. Over California, the winds aloft were moderate and westerly at the beginning of the period, and weak and southwesterly at the end of the period, with only a trace of rain measured along the coastal area of the California/Oregon border on the last day of the period.

The nearest CASTNet site to Trinidad Head is Lassen Volcanic NP. However, the highest ozone was observed at Pinnacles NM. Figure 4-26 illustrates the simulated and observed MDA8 ozone for both sites for a multi-day day period that includes 17-20 August.

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Figure 4-26. Comparison of the Mean Simulated and Mean Observed MDA8 Ozone Concentrations (ppb) for the Lassen Volcanic NP and Pinnacles NM CASTNet Sites for 12-25 August 2006. (a) Lassen Volcanic NP (b) Pinnacles NM

CASTNet Site Lassen Vol NP, CA (LAV410) MDA8: Aug 2006

0 10 20 30 40 50 60 70 80 90 100

12 13 14 15 16 17 18 19 20 21 22 23 24 25

Dateppb

Obs Sim CASTNet Site Pinnacles NM, CA (PIN414) MDA8: Aug 06

0 10 20 30 40 50 60 70 80 90 100

12 13 14 15 16 17 18 19 20 21 22 23 24 25

Dateppb

Obs Sim



### Model performance at the surface is very good for both sites and captures the (slight) increase in ozone at Lassen NP on the 20 th 

### and the more dramatic increase at Pinnacles NM during 18– 20 August.

Figure 4-27 compares the simulated and observed vertical concentration profiles for Trinidad Head for each of the four days. The simulated values match the time of the sounding. The ozonesonde data are plotted in blue and the GEOS-Chem-derived values for each model layer are plotted in gold. The ozonesonde data are from the INTEX-B program data archive (Thompson et al., 2008 and Thompson et al., 2011).

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Figure 4-27. Vertical Profiles of Si mulated and Observed Ozone Concentrati ons (ppb) for Trinidad Head for 17-20 August 2006. Observed Profile is Based on Ozonesonde Data from the INTEX-B Program. (a) 17 August (b) 18 August

Ozone Profile for Trinidad Head, CA:

17 August 2006 (2000-2100 GMT)

0 2 4 6 8 10 12 14

0 20 40 60 80 100 120 140 160
Ozone (ppb)Alt (km) Ozone Profile for Trinidad Head, CA: 18 August 2006 (2000-2100 GMT)

0 2 4 6 8 10 12 14

0 20 40 60 80 100 120 140 160
Ozone (ppb)Alt (km)

(a) 19 August (b) 20 August

Ozone Profile for Trinidad Head, CA:

19 August 2006 (1900-2000 GMT)

0 2 4 6 8 10 12 14

0 20 40 60 80 100 120 140 160
Ozone (ppb)Alt (km) Ozone Profile for Trinidad Head, CA: 20 August 2006 (1900-2000 GMT)

0 2 4 6 8 10 12 14

0 20 40 60 80 100 120 140 160
Ozone (ppb)Alt (km)

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### Both the simulated and observed ozone profiles are quite complicated. While the detailed vertical structure of observed profiles is not well simulated, the model results show layers of high ozone in the middle troposphere on all four days, consistent with the observations.



## Additional Case Studies
Two additional case studies were examined: 26-30 June and 8-9 July 2008. The ozonesonde data for 2008 are from the ARCTAS (ARC-IONS) program data archive (Thompson et al., 2011). The results are within the range of those presented in the previous sections and are therefore not shown here. Overall, the simulated vertical profiles show poor agreement with the observations for these days, most similar to the July 2006 example.



# 4.3. Summary of Model Performance

A variety of graphical and statistical methods were used to examine GEOS-Chem model performance for the three-year period 2006, 2007 and 2008. The performance evaluation focused on ozone but also included a variety of other air concentration and deposition species. Key findings from the model performance evaluation are:

 Model performance for all species is cons istent among the three modeled years.

 Ozone concentrations are overestimated by t he GEOS-Chem model for all three years and nearly all regions and time periods considered in this analysis.

 Overestimation is greater for 24-hour average ozone than for 8-hour average ozone (MDA8).

 Model performance for ozone varies by season and by subregion.

 As expected, given the grid resolution, ozone concentrations are better represented for the more rural CASTNet sites compared to the more urban AQS sites.

 Based on comparison with the CASTNet data, the bias and error statistics for MDA8 ozone suggest reasonably good performance. Overestimation of ozone during the summer and autumn months is most prevalent in the eastern U.S. (Central States, Great Lakes, Southeast, and Northeast subregions). For the western subregions, there is less overestimation of ozone and overall good agreement with the observations. The best agreement with the observations is achieved for the Intermountain West subregion.

 Site-specific model performance for MDA8 ozone concentration (again for the CASTNet sites) indicates that for some sites, especially those in the west, the annual variation in ozone concentration is very well replicated. For most of the subregions, model performance improves with site elevation.

 The spatial and temporal variability of NO 2 

### , SO 2 

### , CO data from the AQS network are not well characterized. NO 2 

### concentrations are underestimated for all subregions and time periods. SO 2 

### is underestimated in the Intermountain West, where observed values are low and overestimated elsewhere, including in the East where observed values are higher. Simulated CO is only weakly correlated with the observed concentrations, and concentrations are underestimated for all regions and time periods. The modeled values

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### exhibit less seasonal variation than the observed values. These results are perhaps understandable, especially for NO 2 

### and CO, given the coarse grid resolution and the probable strong response of AQS monitors to local emissions.

 Model performance for 24-hour average PM 2.5 

### is mixed. For many of the regions and time periods, the bias and error statistics indicate good model performance. However, the seasonal variation in PM 2.5 

### that is characterized by higher concentrations during the summer months is not replicated by the model.

 Overall, model performance for dry deposition is quite good. Dry deposition of ozone is underestimated by the model, which could contribute to overestimation of the ozone concentrations.

 Comparison of simulated and observed ozone profiles for five case-study periods (a total of 12 days) and several locations within the western U.S. gives mixed results. For some cases, the simulated vertical profiles show poor agreement with the observations. For other cases the results are more promising in that although the detailed vertical structure of observed profiles is not well simulated, the model results show layers of high ozone in the middle troposphere, consistent with the observations.

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# 5. Estimation of North American Background Ozone (NAB Scenario)

The North American background scenario for which the emission inventory does not include anthropogenic emissions from the U.S., Canada, and Mexico provides an estimate of NAB O 3


### . Figure 5-1 displays the mean MDA8 ozone concentration for the base (current atmosphere) and North American background scenarios, based on all three simulation years. The concentrations for the North American background scenario are the estimated NAB O 3 

### values relevant to the MDA8 metric.

Figure 5-1. Mean MDA8 Ozone Conc entrations (ppb) for the Base (Curre nt Atmosphere) and North American Background Scenarios, Based on the 2006, 2007, and 2008 Simulation Period. (a) Current Atmosphere Scenario (b ) North American Background Scenario



### For the current atmosphere scenario, mean MDA8 ozone ranges from 21.3 to 82.6 ppb within the modeling grid. For the North American background scenario, mean MDA8 ozone ranges from 17.4 to 42.9 ppb. Thus on an annual basis and within the full modeling grid, NAB ozone ranges from 17.4 to 42.9 ppb, depending upon the location. It is of interest that the concentration patterns differ between the two scenarios and the highest NAB O 3 

### values do not necessarily occur in the areas with the highest overall ozone concentrations. The highest NAB O 3 

### values are found over the western U.S.

The modeling results for NAB O 3 

### vary by season, as illustrated in Figure 5-2

.

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Figure 5-2. Mean MDA8 Ozone Concentrations (ppb) for the North American Background Scenario, Based on the 2006, 2007, and 2008 Simulation Period. (a) Winter (December–February) (b) Spring (March–May)

(c) Summer (June–August) (d) Fall (September–November)



### For most areas within the domain, the highest NAB O 3 

### values tend to occur during the spring period (March–May). High values also occur during the summer months in the western U.S., especially over the more mountainous regions. For all four periods, the highest NAB O 3 

### values are simulated over (approximately) this same area.

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### Table 5-1 lists the seasonal and annual mean NAB O 3 

### values relevant to 24-hour average ozone for the entire U.S. and each of the six model performance subregions, based on the CASTNet sites and the three-year simulation period. Averages were computed over all CASTNet sites in the region and each day of the three-year simulation period that corresponds to the averaging period. For comparison purpos es, the mean observed and base-case (current atmosphere) concentrations are also included in the table. Units are ppb.

Table 5-1. GEOS-Chem-Derived Seasonal and Annual Mean 24-Hour Average Observed, Current Atmosphere, and NAB Ozone Concentrations (ppb ), Based on the 2006, 2007 and 2008 Simulation Period. (a) Entire Continental U.S.

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 29.03 30.46 29.21 Spring (Mar-May) 42.04 45.20 29.05
Summer (Jun-Aug) 40.04 51.52 24.73Fall (SepNov) 30.70 40.17 24.72
Annual 35.50 41.88 26.93

(b) West Coast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 33.33 35.94 32.00 Spring (Mar-May) 44.70 45.40 33.07
Summer (Jun-Aug) 49.59 53.08 27.50Fall (SepNov) 37.10 44.09 30.21
Annual 41.24 44.63 30.74

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(c) Intermountain West

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 39.97 39.28 33.93 Spring (Mar-May) 49.62 47.75 36.75
Summer (Jun-Aug) 47.55 52.10 34.91Fall (SepNov) 38.96 43.34 31.75
Annual 44.04 45.65 34.33

(d) Central States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 29.14 31.33 26.70 Spring (Mar-May) 39.17 42.21 27.84
Summer (Jun-Aug) 37.29 47.06 27.90Fall (SepNov) 30.07 37.18 23.21
Annual 33.88 39.42 26.37

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(e) Great Lakes States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 23.13 21.76 27.47 Spring (Mar-May) 38.01 41.96 27.30
Summer (Jun-Aug) 37.11 54.01 22.93Fall (SepNov) 25.61 35.11 22.45
Annual 31.01 38.20 25.07

(f) Southeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 27.32 31.18 27.46 Spring (Mar-May) 42.29 47.95 25.56
Summer (Jun-Aug) 38.83 52.46 21.72Fall (SepNov) 30.66 43.24 22.29
Annual 34.85 43.78 24.25

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(g) Northeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 24.82 25.79 29.06 Spring (Mar-May) 38.85 43.49 27.37
Summer (Jun-Aug) 34.25 49.45 18.43Fall (SepNov) 24.61 36.97 21.84
Annual 30.70 38.99 24.18



### The annual average NAB O 3 

### concentration for the entire U.S. (relevant to 24-hour average ozone concentration) is estimated to be 26.9 ppb. This varies among the regions. For the western U.S. (West Coast and Intermountain West subregions), the estimated range is 30.7 to 34.3 ppb. For the eastern U.S. (Central States, Great Lakes, Southeast, and Northeast subregions), the estimated range is 24.2 to 26.4 ppb.

For the spring months (March–May), the average NAB O 3 

### concentration relevant to 24-hour average ozone is estimated to be 29.1 ppb for the entire U.S.; it ranges from 33.1 to 36.8 ppb for the western U.S. and from 25.6 to 27.8 ppb for the eastern U.S.

For the summer months (June–August), the average NAB O 3 

### concentration relevant to 24-hour average ozone is estimated to be 24.7 ppb for the entire U.S.; it ranges from 27.5 to 34.9 ppb for the western U.S. and from 18.4 to 27.9 ppb for the eastern U.S.

Table 5-2 lists the seasonal and annual mean NAB O 3 

### values relevant to MDA8 ozone for the entire U.S. and each of the six model performance subregions, based on the CASTNet sites and the three-year simulation period. The mean observed and base-case (current atmosphere) concentrations are also included in the table. Units are ppb.

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Table 5-2. GEOS-Chem-Derived Seasonal and Annual Mean MDA8 Observed, Current Atmosphere, and NAB Ozone Concentrations (ppb), Based on the 2006, 2007 and 2008 Simulation Period. (a) Entire Continental U.S.

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 34.66 37.21 32.23 Spring (Mar-May) 50.93 54.83 33.20
Summer (Jun-Aug) 52.03 64.11 30.04Fall (SepNov) 39.50 50.00 28.68
Annual 44.37 51.63 31.04

(b) West Coast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 38.87 42.20 35.39 Spring (Mar-May) 54.10 55.02 37.77
Summer (Jun-Aug) 64.14 67.50 33.86Fall (SepNov) 46.31 53.62 34.61

Annual 50.94 54.61 35.45

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(c) Intermountain West

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 43.69 43.90 37.16 Spring (Mar-May) 55.59 54.69 41.73
Summer (Jun-Aug) 55.48 60.34 40.39Fall (SepNov) 44.62 50.30 36.42
Annual 49.89 52.37 38.94

(d) Central States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 34.85 37.36 30.27 Spring (Mar-May) 48.16 50.40 32.60
Summer (Jun-Aug) 47.88 57.92 34.23Fall (SepNov) 38.88 45.77 27.80
Annual 42.44 47.87 31.18

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(e) Great Lakes States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 28.69 29.34 30.42 Spring (Mar-May) 47.80 53.78 31.27
Summer (Jun-Aug) 50.91 69.51 27.75Fall (SepNov) 35.43 47.39 26.40
Annual 40.77 50.03 28.98

(f) Southeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 34.26 38.92 30.32 Spring (Mar-May) 52.44 57.97 29.31
Summer (Jun-Aug) 51.22 64.46 27.03Fall (SepNov) 40.63 53.20 25.80
Annual 44.76 53.77 28.11

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(g) Northeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb)

Winter (Dec-Feb) 30.17 32.84 31.59 Spring (Mar-May) 47.27 53.86 30.83
Summer (Jun-Aug) 47.19 64.28 22.88Fall (SepNov) 33.47 48.05 25.19
Annual 39.63 49.89 27.61



### The annual average NAB O 3 

### concentration for the entire U.S. (relevant to MDA8 ozone concentration) is estimated to be 31.0 ppb. This varies among the regions. For the western U.S., the estimated range is 35.5 to 38.9 ppb. For the eastern U.S., the estimated range is 27.6 to 31.2 ppb.

For the spring months (March–May), the average NAB O 3 

### concentration relevant to MDA8 ozone is estimated to be 33.2 ppb for the entire U.S.; it ranges from 37.8 to 41.7 ppb for the western U.S. and from 29.3 to 32.6 ppb for the eastern U.S.

For the summer months (June–August), the average NAB O 3 

### concentration relevant to 24-hour average ozone is estimated to be 30.0 ppb for the entire U.S.; it ranges from 33.9 to 40.4 ppb for the western U.S. and from 22.9 to 34.2 ppb for the eastern U.S.

Plots comparing MDA8 ozone for the current atmosphere and North American background scenarios for selected CASTNet sites are provided in Figure 5-3 through Figure 5-8

.

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11-035 Figure 5-3. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Lassen Volcanic NP, CA. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2006

Base NAB 0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2007

Base NAB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2008

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11-035 Figure 5-4. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Pinedale, WY. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Pinedale, WY (PND165) MDA8: 2006

Base NAB 0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Pinedale, WY (PND165) MDA8: 2007

Base NAB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Pinedale, WY (PND165) MDA8: 2008

Base NABModeling for North American Background Concentrations Estimation of North American B ackground Ozone (NAB Scenario)

Figure 5-5. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Big Bend NP, TX. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2006

Base PRB 0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2007

Base PRB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2008

Base PRB

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Figure 5-6. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Perkinstown, WI. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Perkinstown, WI (PRK134) MDA8: 2006

Base PRB 0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Perkinstown, WI (PRK134) MDA8: 2007

Base PRB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Perkinstown, WI (PRK134) MDA8: 2008

Base PRB

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Figure 5-7. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Great Smoky Mountains NP, TN. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2006

Base NAB 0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2007

Base NAB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2008

Base NAB

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Figure 5-8. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Blackwater NWR, MD. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2006

Base NAB 0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2007

Base NAB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2008

Base NAB



### Site-specific estimates of NAB ozone, relevant to MDA8 ozone, are summarized in Table 5-3 . In this table mean MDA8 ozone is presented for each of the CASTNet sites highlighted in Section 4 of this report. Mean values of observed, base (current atmosphere), and NAB O 3 

### (North American background) concentrations, based on the three-year period are provided. Standard deviation values associated with the means are also provided.

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11-035Modeling for North AmericanBackground ConcentrationsEstimation of North American Background Ozone (NAB Scenario)Table 5-3. GEOS-Chem-Derived Seasonal and Annual Mean MDA8 Observed, Current Atmosphere, and NAB Ozone Concentrations (ppb) forSelected CASTNet Sites,Based on the 2006, 2007 and 2008 Simulation Period.SiteWinter (Dec–Feb)Spring (Mar–May)Summer (Jun–Aug)Fall (Sep–Nov)AnnualObs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Mount RainierNP, WAAvg26.4135.3633.0339.1143.3134.5233.6939.1823.6924.1937.5730.7230.8938.8830.48SDev8.294.603.708.015.935.3212.699.475.408.956.384.8211.347.436.40Pinnacles NM,CAAvg37.7442.1333.1351.7650.7434.7357.1350.9628.5048.0252.6532.5448.7149.1532.22SDev5.925.923.119.167.924.7912.1212.717.1211.7211.364.9412.2810.675.68Joshua Tree NM,CAAvg47.2145.2535.7067.4668.0840.6182.8598.8538.7856.5665.1936.4163.5869.4937.89SDev5.445.943.6511.4116.665.5312.7315.158.9010.6817.515.2316.8724.086.44Lassen NP, CAAvg43.6040.3034.6552.2048.6837.2257.9953.3837.9545.7248.6335.4649.9547.7936.33SDev3.874.753.687.117.376.3910.5210.338.2310.279.795.4310.139.596.30Chiricahua NM,AZAvg44.6046.2136.1856.2755.7442.5754.5159.9440.1844.6149.3733.9050.0652.8638.23SDev4.715.014.757.106.525.398.527.637.916.157.396.268.678.597.04Great Basin NP,NVAvg42.8242.1236.0155.1552.5541.7058.4161.9542.1345.1849.1036.4250.5651.4939.28SDev4.204.394.287.257.115.387.009.136.747.469.075.639.3110.486.37Pinedale, WYAvg45.4643.8038.2355.5353.8141.4256.5457.3340.8045.3349.7137.2850.5651.2139.45SDev5.504.284.067.626.015.546.028.286.696.857.815.778.438.445.85Rocky Mtn NP,COAvg47.3345.8039.7756.4256.9142.8360.3265.3439.9547.0152.7037.6352.8255.2540.05SDev5.544.423.857.206.045.218.278.055.646.747.915.439.089.795.41Caddo Valley, ARAvg30.4239.9027.9142.9250.2927.7243.1857.6029.1836.0949.7724.0238.2149.4427.21SDev8.685.564.4410.046.404.6713.058.696.5711.619.034.1212.149.835.39Konza Prairie, KSAvg33.1232.9628.9249.6752.0132.1853.3767.5436.6040.5545.8427.4444.2549.6931.31SDev6.346.565.3910.238.325.0610.128.236.7011.4712.004.6512.5315.346.53TheodoreRoosevelt NP, NDAvg34.4432.7730.2747.2245.6933.7148.4453.0435.8835.1838.4029.5841.2042.5432.38SDev5.046.985.927.385.964.468.178.966.567.539.256.069.6310.986.34Big Bend NP, TXAvg42.9943.8632.7454.4653.1039.0846.3555.2039.5643.6147.7730.4946.8850.0235.50SDev5.954.956.076.735.286.359.018.957.707.786.945.688.758.067.60ICF International153October 28, 201111-035Modeling for North AmericanBackground ConcentrationsEstimation of North American Background Ozone (NAB Scenario)ICF International154October 28, 201111-035SiteWinter (Dec–Feb)Spring (Mar–May)Summer (Jun–Aug)Fall (Sep–Nov)AnnualObs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Obs(ppb)Base(ppb)NAB(ppb)Unionville (AnnArbor), MIAvg28.4226.5930.1946.5650.6431.7648.3668.5727.5232.4944.9526.1739.0147.8128.91SDev7.749.286.0510.3213.405.3311.4514.984.7910.9817.304.9913.3820.525.74SalamonieReservoir, INAvg27.1127.9829.5347.2654.3031.1051.3372.5028.3436.1148.0526.0940.6950.8428.77SDev7.077.985.5810.8613.495.5410.4811.054.9813.4317.664.9114.2820.545.56Oxford, OHAvg27.4227.2229.9648.4856.0830.5653.3075.9227.9637.6350.6926.3741.7352.6228.71SDev7.458.994.9811.8515.465.5011.8211.485.4815.7919.984.9115.6922.645.48Perkinstown, WIAvg31.9532.7531.9548.6749.8232.7744.7952.6427.5033.7742.7327.0839.6844.5529.82SDev6.836.944.818.308.905.1110.0712.475.149.0611.134.6311.1612.665.55Sumatra, FLAvg35.1347.4030.1949.0558.2932.0636.2258.4033.1936.6353.5627.3239.3254.4530.70SDev8.755.964.0510.217.704.5312.199.016.669.867.834.6211.798.915.53Cadiz, KYAvg31.0733.6629.3551.1657.7128.4153.9569.3227.6243.0453.7625.4845.2753.7227.71SDev8.928.174.4810.699.405.1111.737.974.9713.4114.434.4714.2816.474.97Sand Mountain,ALAvg33.7240.1829.1553.5658.7129.0757.7566.2027.8443.4656.2225.1047.2155.4127.79SDev8.727.574.489.846.714.6311.817.476.7112.2611.644.3814.2212.755.39Great SmokyMtns. NP, TNAvg39.7339.6130.3859.9959.1929.4265.0165.2326.9348.4754.4126.1653.3954.6928.22SDev7.357.084.3510.847.004.9711.567.096.8011.7010.554.9514.4112.425.62Blackwater NWR,MDAvg30.8034.8430.1851.9061.2529.3560.5577.0525.4139.4956.2025.9645.5557.4627.72SDev6.917.464.6710.6013.964.9813.1213.176.6411.6016.534.5715.6220.035.67Acadia NP, MEAvg35.6341.9933.1147.4956.5731.4744.2566.7319.8534.9252.3525.9141.1154.4927.56SDev6.089.003.938.4516.175.3313.5723.834.269.4817.824.9611.2719.656.98Penn State, PAAvg29.1229.3431.3548.8855.5530.9452.1065.5624.0936.2848.7925.4741.9049.9327.95SDev7.709.055.0610.3012.615.4112.3913.865.5612.0214.984.7014.2318.406.11Huntington WildlifeForest, NYAvg31.8335.5832.5944.3849.6132.0836.3650.4622.2429.8743.6825.3635.6844.8928.05SDev5.755.674.019.618.644.9910.8813.994.799.2310.595.1910.6211.796.50

# 6. Additional Scenarios and Comparisons

6.1. U.S. and Natural Background Scenarios

The results for two additional scenarios are presented and discussed in this section. These are 1) the U.S. background scenario for which the emission inventory consists of the current atmosphere emissions minus anthropogenic emissions for sources in the onshore areas of the U.S. and 2) the natural background scenario which includes only natural emissions (for all sources throughout the modeling domain). In the remainder of this section these are referred to as USB and NB respectively. For ease of comparison, many of the graphical and tabular summaries include the results for the base-case (current atmosphere), NAB, USB, and NB scenarios.

Figure 6-1 displays the mean MDA8 ozone concentrations for the base (current atmosphere), NAB, USB, and NB scenarios, based on all three simulation years.

Figure 6-1. Mean MDA8 Ozone Concentr ations (ppb) for the Base (Current Atmosphere), NAB, USB and NB Scenarios, Based on the 2006, 2007, and 2008 Simulation Period. (a) Current Atmosphere Scenario (b ) North American Background Scenario

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(c) U.S. Background Scenario (d) Natural Background Scenario



### For the current atmosphere scenario, mean MDA8 ozone ranges from 21.3 to 82.6 ppb within the modeling grid. For the NAB scenario, mean MDA8 ozone ranges from 17.4 to 42.9 ppb. For the USB scenario, mean MDA8 ozone ranges from 19.9 to 73.4 ppb. Compared to the NAB values, the simulated USB values are higher throughout the domain including over the continental U.S. This increase is attributable to Canadian, Mexican and offshore emissions. For the NB scenario, the concentrations are quite a bit lower and mean MDA8 ozone ranges from 12.8 to 30.7 ppb. Within the U.S., the simulated NB ozone concentrations are very low along the northeast corridor and the highest values are found over Colorado.

As for NAB O 3 

### (see Figure 5-2), the modeling results for USB and NB vary by season, as illustrated in Figures 6-2 and 6-3.

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Figure 6-2. Mean MDA8 Ozone Concentrations (ppb) for the U.S. Background Scenario, Based on the 2006, 2007, and 2008 Simulation Period. (a) Winter (December–February) (b) Spring (March–May)

(c) Summer (June–August) (b) Fall (September–November)

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Figure 6-3. Mean MDA8 Ozone Concentr ations (ppb) for the Natural Background Scenario, Based on the 2006, 2007, and 2008 Simulation Period. (a) Winter (December–February) (b) Spring (March–May)

(c) Summer (June–August) (b) Fall (September–November)



### Depending upon locations, the highest USB and NB values tend to occur either during the spring or summer period. In general, the highest values occur offshore (USB only) and over the western U.S. (USB and NB).

Table 5-1 lists the seasonal and annual mean NAB, USB and NB O 3 

### values relevant to 24-hour average ozone for the entire U.S. and each of the six model performance subregions, based on

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### the CASTNet sites and the three-year simulati on period. Averages were computed over all CASTNet sites in the region and each day of the three-year simulation period that corresponds to the averaging period. For comparison purpos es, the mean observed and base-case (current atmosphere) concentrations are also included in the table. Units are ppb.

Table 6-1. GEOS-Chem-Derived Seasonal and Annual Me an 24-Hour Average Observed, Current Atmosphere, NAB, USB, and NB Ozone Concentrations (ppb), B ased on the 2006, 2007 and 2008 Simulation Period. (a) Entire Continental U.S.

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 29.03 30.46 29.21 31.17 19.41 Spring (Mar-May) 42.04 45.20 29.05 32.51 19.88
Summer (Jun-Aug) 40.04 51.52 24.73 28.44 19.55Fall (SepNov) 30.70 40.17 24.72 27.98 17.94
Annual 35.50 41.88 26.93 30.03 19.20

(b) West Coast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 33.33 35.94 32.00 33.56 21.13 Spring (Mar-May) 44.70 45.40 33.07 34.76 21.60
Summer (Jun-Aug) 49.59 53.08 27.50 30.25 20.25Fall (SepNov) 37.10 44.09 30.21 32.68 21.53
Annual 41.24 44.63 30.74 32.85 21.13

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(c) Intermountain West

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 39.97 39.28 33.93 35.66 22.75 Spring (Mar-May) 49.62 47.75 36.75 38.85 25.32
Summer (Jun-Aug) 47.55 52.10 34.91 37.79 27.30Fall (SepNov) 38.96 43.34 31.75 34.44 22.91
Annual 44.04 45.65 34.33 36.69 24.58

(d) Central States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 29.14 31.33 26.70 28.68 17.87 Spring (Mar-May) 39.17 42.21 27.84 31.39 19.79
Summer (Jun-Aug) 37.29 47.06 27.90 31.32 22.86Fall (SepNov) 30.07 37.18 23.21 26.29 17.33
Annual 33.88 39.42 26.37 29.38 19.43

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(e) Great Lakes States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 23.13 21.76 27.47 28.89 18.06 Spring (Mar-May) 38.01 41.96 27.30 30.58 18.73
Summer (Jun-Aug) 37.11 54.01 22.93 26.59 18.53Fall (SepNov) 25.61 35.11 22.45 25.18 16.43
Annual 31.01 38.20 25.07 27.84 17.95

(f) Southeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 27.32 31.18 27.46 29.83 18.39 Spring (Mar-May) 42.29 47.95 25.56 28.77 17.86
Summer (Jun-Aug) 38.83 52.46 21.72 24.15 17.38Fall (SepNov) 30.66 43.24 22.29 25.16 16.23
Annual 34.85 43.78 24.25 26.98 17.46

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(g) Northeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 24.82 25.79 29.06 31.33 19.08 Spring (Mar-May) 38.85 43.49 27.37 33.48 18.20
Summer (Jun-Aug) 34.25 49.45 18.43 25.43 14.56Fall (SepNov) 24.61 36.97 21.84 27.20 15.70
Annual 30.70 38.99 24.18 29.38 16.88



### The annual average USB ozone concentration for the entire U.S. (relevant to 24-hour average ozone concentration) is estimated to be 30.0 ppb and the NB concentration is estimated to be 19.2 ppb.

For the western U.S. (West Coast and Intermountain West subregions), the estimated range in annual average USB concentration is 32.9 to 36.7 ppb and the estimated range in NB concentration is 21.1 to 24.6 ppb. For the eastern U.S. (Central States, Great Lakes, Southeast, and Northeast subregions) the values are lower and the estimated range in USB concentration is 27.0 to 29.4 ppb and the estimated range in NB concentration is 16.9 to 19.4 ppb.

For the spring months, the average USB ozone concentration relevant to 24-hour average ozone is estimated to be 32.5 ppb for the entire U.S.; the corresponding NB concentration is 19.9 ppb.

For the summer months, the average USB ozone concentration relevant to 24-hour average ozone is estimated to be 28.4 ppb for the entire U.S. The NB concentrations are characterized by less variation among the seasons than either the USB or the NAB and the corresponding NB concentration is 19.6 ppb.

Table 5-2 lists the seasonal and annual mean NAB, USB, and NB O 3 

### values relevant to MDA8 ozone for the entire U.S. and each of the six model performance subregions, based on the CASTNet sites and the three-year simulation period. The mean observed and base-case (current atmosphere) concentrations are also included in the table. Units are ppb.

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Table 6-2. GEOS-Chem-Derived Seasonal and Annual Mean MDA8 Observed, Current Atmosphere, NAB, USB, and NB Ozone Concentrations (ppb ), Based on the 2006, 2007 and 2008 Simulation Period. (a) Entire Continental U.S.

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 34.66 37.21 32.23 34.48 21.39 Spring (Mar-May) 50.93 54.83 33.20 37.05 22.84
Summer (Jun-Aug) 52.03 64.11 30.04 34.31 23.84Fall (SepNov) 39.50 50.00 28.68 32.34 20.80
Annual 44.37 51.63 31.04 34.56 22.23

(b) West Coast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 38.87 42.20 35.39 37.02 23.47 Spring (Mar-May) 54.10 55.02 37.77 39.62 24.95
Summer (Jun-Aug) 64.14 67.50 33.86 37.17 25.16Fall (SepNov) 46.31 53.62 34.61 37.23 24.70

Annual 50.94 54.61 35.45 37.79 24.57

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(c) Intermountain West

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 43.69 43.90 37.16 38.94 25.00 Spring (Mar-May) 55.59 54.69 41.73 43.91 28.99
Summer (Jun-Aug) 55.48 60.34 40.39 43.38 31.53Fall (SepNov) 44.62 50.30 36.42 39.18 26.17
Annual 49.89 52.37 38.94 41.37 27.94

(d) Central States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 34.85 37.36 30.27 32.60 20.23 Spring (Mar-May) 48.16 50.40 32.60 36.50 23.28
Summer (Jun-Aug) 47.88 57.92 34.23 37.86 28.18Fall (SepNov) 38.88 45.77 27.80 31.28 20.81
Annual 42.44 47.87 31.18 34.52 23.10

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(e) Great Lakes States

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 28.69 29.34 30.42 32.08 19.92 Spring (Mar-May) 47.80 53.78 31.27 34.94 21.52
Summer (Jun-Aug) 50.91 69.51 27.75 31.96 22.61Fall (SepNov) 35.43 47.39 26.40 29.48 19.36
Annual 40.77 50.03 28.98 32.14 20.86

(f) Southeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 34.26 38.92 30.32 32.90 20.24 Spring (Mar-May) 52.44 57.97 29.31 32.78 20.55
Summer (Jun-Aug) 51.22 64.46 27.03 29.76 21.69Fall (SepNov) 40.63 53.20 25.80 28.91 18.75
Annual 44.76 53.77 28.11 31.09 20.31

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(g) Northeast

Time Period Mean Observed (ppb) Mean Simulated

(Base) (ppb) Mean Simulated

(NAB) (ppb) Mean Simulated

(USB) (ppb) Mean Simulated (NB) (ppb)

Winter (Dec-Feb) 30.17 32.84 31.59 34.62 20.68 Spring (Mar-May) 47.27 53.86 30.83 37.98 20.51
Summer (Jun-Aug) 47.19 64.28 22.88 31.46 18.12Fall (SepNov) 33.47 48.05 25.19 31.67 18.08
Annual 39.63 49.89 27.61 33.95 19.35



### The annual average USB ozone concentration for the entire U.S. (relevant to MDA8 ozone concentration) is estimated to be 34.6 ppb and the NB concentration is estimated to be 22.2 ppb.

For the western U.S. (West Coast and Intermountain West subregions), the estimated range in annual average USB concentration is 37.8 to 41.4 ppb and the estimated range in NB concentration is 24.6 to 27.9 ppb. For the eastern U.S. (Central States, Great Lakes, Southeast, and Northeast subregions) the values are lower and the estimated range in USB concentration is 31.1 to 34.5 ppb and the estimated range in NB concentration is 19.4 to 23.1 ppb.

For the spring months, the average USB ozone concentration relevant to MDA8 ozone is estimated to be 37.1 ppb for the entire US; the corresponding NB concentration is 22.8 ppb.

For the summer months, the average USB ozone concentration relevant to MDA8 ozone is estimated to be 34.3 ppb for the entire U.S. The corresponding NB concentration is 23.8 ppb.

Plots comparing MDA8 ozone for the current atmosphere, NAB, USB, and NB scenarios for selected CASTNet sites are provided in Figure 6-3 through Figure 6-9 . Note that the NAB (green) and USB (gray) lines frequently overlap.

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11-035 Figure 6-4. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Lassen Volcanic NP, CA. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2006

Base NAB USB NB 0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Lassen Volcanic NP, CA (LAV410) MDA8: 2007

Base NAB USB NB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Lassen Vocalnic NP, CA (LAV410) MDA8: 2008

Base NAB USB NBModeling for North American Background Concentrations Additional Scenarios and Comparisons

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11-035 Figure 6-5. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Pinedale, WY. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Pinedale, WY (PND165) MDA8: 2006

Base NAB USB NB 0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Pinedale, WY (PND165) MDA8: 2007

Base NAB USB NB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Pinedale, WY (PND165) MDA8: 2008

Base NAB USB NBModeling for North American Background Concentrations Additional Scenarios and Comparisons

Figure 6-6, Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Big Bend NP, TX. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2006

Base NAB USB NB 0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2007

Base NAB USB NB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Big Bend NP, TX (BBE401) MDA8: 2008

Base NAB USB NB

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Figure 6-7. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Perkinstown, WI. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Perkinstown, WI (PRK134) MDA8: 2006

Base NAB USB NB 0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Perkinstown, WI (PRK134) MDA8: 2007

Base NAB USB NB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Perkinstown, WI (PRK134) MDA8: 2008

Base NAB USB NB

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Figure 6-8. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Great Smoky Mountains NP, TN. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2006

Base NAB USB NB 0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2007

Base NAB USB NB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Great Smoky NP, TN (GRS420) MDA8: 2008

Base NAB USB NB

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Figure 6-9. Mean MDA8 Ozone Concentrations (ppb) fo r the Current Atmosphere and North American Background Scenarios for Blackwater NWR, MD. (a) 2006 (b) 2007

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2006

Base NAB USB NB 0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2007

Base NAB USB NB

(c) 2008

0 10 20 30 40 50 60 70 80 90 100 110 120

1 31 61 91 121 151 181 211 241 271 301 331 361ppb

Day CASTNet Site Blackwater NWR, MD (BWR139) MDA8: 2008

Base NAB USB NB



### Site-specific estimates of NAB ozone, relevant to MDA8 ozone are summarized in Table 5-3 . In this table mean MDA8 ozone is presented for each of the CASTNet sites highlighted in Section 4 of this report. Mean values of observed, base (current atmosphere), NAB, USB, and NB ozone concentrations for the spring, summer, and annual periods, based on three years of modeling results are provided. Standard deviation values associated with the means are also provided.

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11-035Table 6-3. GEOS-Chem-Derived Seasonal and Annual Mean MDA8 Observed, Current Atmosphere, NAB, USB, and NB Ozone Concentrations(ppb) for the Spring,Summer, and Annual Periods for Selected CASTNet Sites, Based on the 2006, 2007 and 2008 Simulation Period.SiteSpring (Mar–May)Summer (Jun–Aug)AnnualObs(ppb)Base(ppb)NAB(ppb)USB(ppb)NB(ppb)Obs(ppb)Base(ppb)NAB(ppb)USB(ppb)NB(ppb)Obs(ppb)Base(ppb)NAB(ppb)USB(ppb)NB(ppb)Mount RainierNP, WAAvg39.1143.3134.5236.4621.6933.6939.1823.6926.5516.2030.8938.8830.4832.5520.06SDev8.015.935.325.183.5812.699.475.406.714.0911.347.436.406.414.17PinnaclesNM, CAAvg51.7650.7434.7336.2322.1457.1350.9628.5029.9420.3548.7149.1532.2233.8521.91SDev9.167.924.794.703.3112.1212.717.127.195.7612.2810.675.685.674.19Joshua TreeNM, CAAvg67.4668.0840.6143.5927.6282.8598.8538.7845.7730.0163.5869.4937.8942.0327.05SDev11.4116.665.536.044.3112.7315.158.907.816.2316.8724.086.446.655.12Lassen NP,CAAvg52.2048.6837.2238.3924.2657.9953.3837.9539.0427.9849.9547.7936.3337.6225.04SDev7.117.376.396.344.4410.5210.338.238.266.7810.139.596.306.245.19ChiricahuaNM, AZAvg56.2755.7442.5746.3330.1754.5159.9440.1846.5332.8450.0652.8638.2343.2428.36SDev7.106.525.394.924.018.527.637.917.656.288.678.597.046.585.84Great BasinNP, NVAvg55.1552.5541.7043.2828.6658.4161.9542.1345.5730.8450.5651.4939.2841.2827.97SDev7.257.115.385.264.227.009.136.746.975.469.3110.486.376.495.59Pinedale, WYAvg55.5353.8141.4243.2228.3656.5457.3340.8042.6931.0550.5651.2139.4541.2227.86SDev7.626.015.545.504.096.028.286.696.535.438.438.445.855.764.88Rocky MtnNP, COAvg56.4256.9142.8344.6630.0760.3265.3439.9541.9331.3052.8255.2540.0541.9628.78SDev7.206.045.215.084.068.278.055.645.784.709.089.795.415.304.51Caddo Valley,ARAvg42.9250.2927.7230.6419.9343.1857.6029.1831.0723.4838.2149.4427.2129.5620.06SDev10.046.404.674.403.2813.058.696.576.575.2712.149.835.395.274.23KonzaPrairie, KSAvg49.6752.0132.1835.2423.4853.3767.5436.6039.1331.1444.2549.6931.3133.7923.75SDev10.238.325.065.254.1810.128.236.706.486.1512.5315.346.536.696.45TheodoreRoosevelt NP,NDAvg47.2245.6933.7137.9722.9848.4453.0435.8840.8929.4941.2042.5432.3835.8123.45SDev7.385.964.465.013.318.178.966.565.886.789.6310.986.347.106.24Big Bend NP,TXAvg54.4653.1039.0847.0429.3646.3555.2039.5647.7032.3746.8850.0235.5043.4927.09SDev6.735.286.355.454.599.018.957.706.626.268.758.067.606.866.34ICF International173October 28, 201111-035Modeling for North AmericanBackground ConcentrationsAdditional Scenarios and ComparisonsICF International174October 28, 201111-035SiteSpring (Mar–May)Summer (Jun–Aug)AnnualObs(ppb)Base(ppb)NAB(ppb)USB(ppb)NB(ppb)Obs(ppb)Base(ppb)NAB(ppb)USB(ppb)NB(ppb)Obs(ppb)Base(ppb)NAB(ppb)USB(ppb)NB(ppb)Unionville(Ann Arbor),MIAvg46.5650.6431.7636.1921.6848.3668.5727.5232.8122.1739.0147.8128.9132.7120.70SDev10.3213.405.335.423.7311.4514.984.796.954.1713.3820.525.746.644.04SalamonieReservoir, INAvg47.2654.3031.1034.5821.6051.3372.5028.3432.3923.3640.6950.8428.7731.8020.92SDev10.8613.495.545.443.9510.4811.054.986.024.4214.2820.545.565.944.27Oxford, OHAvg48.4856.0830.5633.9221.2353.3075.9227.9632.0322.9241.7352.6228.7131.7820.83SDev11.8515.465.505.553.8211.8211.485.486.484.6515.6922.645.485.804.13Perkinstown,WIAvg48.6749.8232.7736.3322.0644.7952.6427.5031.1521.9339.6844.5529.8232.6821.11SDev8.308.905.114.773.2010.0712.475.145.194.5211.1612.665.555.543.70Sumatra, FLAvg49.0558.2932.0636.6522.8336.2258.4033.1935.8626.4439.3254.4530.7034.5722.50SDev10.217.704.534.473.1312.199.016.666.565.4611.798.915.535.534.50Cadiz, KYAvg51.1657.7128.4131.1920.0853.9569.3227.6229.9922.5145.2753.7227.7130.1120.18SDev10.699.405.115.193.3511.737.974.975.144.2014.2816.474.975.023.64SandMountain, ALAvg53.5658.7129.0732.0120.6557.7566.2027.8429.6522.4247.2155.4127.7930.2120.25SDev9.846.714.634.503.1211.817.476.716.775.5514.2212.755.395.354.02Great SmokyMtns NP, TNAvg59.9959.1929.4232.3620.7565.0165.2326.9328.8621.5453.3954.6928.2230.6420.39SDev10.847.004.974.923.1611.567.096.806.935.6314.4112.425.625.633.90BlackwaterNWR, MDAvg51.9061.2529.3535.5719.8660.5577.0525.4130.3320.3845.5557.4627.7232.8219.77SDev10.6013.964.985.852.8313.1213.176.647.105.6315.6220.035.676.143.81Acadia NP,MEAvg47.4956.5731.4747.9420.2844.2566.7319.8547.3315.2141.1154.4927.5644.3518.83SDev8.4516.175.3313.373.1613.5723.834.2617.883.0511.2719.656.9814.193.74Penn State,PAAvg48.8855.5530.9435.9720.8352.1065.5624.0929.2819.1841.9049.9327.9532.0819.72SDev10.3012.615.415.383.3612.3913.865.566.674.7214.2318.406.116.193.77HuntingtonWildlife Forest,NYAvg44.3849.6132.0839.4221.1836.3650.4622.2432.9517.5635.6844.8928.0534.8519.52SDev9.618.644.994.292.9410.8813.994.797.894.0010.6211.796.506.323.61

# 6.2. Comparison of North American and Natural Background Ozone Concentrations

As discussed in the previous sections, there are spatial and seasonal variations in the NAB concentrations and to a lesser extent the NB concentrations. Figures 6-10 through 6-13 show that estimated NAB also varies with observed concentration level, and that this variation is more pronounced for certain regions. NB, on the other hand, is fairly consistent for the range of concentrations simulated for all regions.

Figure 6-10 illustrates this for the Intermountain West subregion, using observed and simulated values for the CASTNet sites within this subregion for all three simulation years. Results for Spring (March – May) and Summer (June – August) are shown in the left and right columns, respectively. The top plot in each column co mpares simulated versus observed MDA8 ozone Concentrations for all sites in the subregion. The box-and-whisker plots that follow summarize NAB and NB for 10-ppb bins of observed oz one concentration. The box-and-whisker plots illustrate the 25 th 

### , 50 th 

### , and 75 th 

### percentile values (lines at the bottom of the box, within the box, and at the top of the box), as well as minimu m and maximum values (lowest and highest values indicated by the whiskers). For this region, the NAB, and to a lesser extent, the NB values increase with concentration.

Figures 6-11 through 6-13 provide the same information for the Great Lakes, Southeast, and Northeast subregions, and indicate less variation in both NAB and NB with observed concentration, especially for the Southeast subregion ( Figure 6-12 ).

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Figure 6-10. Simulated vs. Observed MDA8 Ozone Concentratio ns (ppb) for the Intermountai n West CASTNet sites. The Box-and-Whisker Plots (Minimum, 25 th , 50 th , 75 th

Percentiles, and Maximum) Summarize NAB and NB for 10-ppb Bins of Observed Ozone Concentration: 2006-2008. Spring (March–May) Summer (June–August)

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Intermountain Sites - Spring 2006-2008

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Intermountain Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Intermountain Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Intermountain Sites - Summer 2006

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Intermountain Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Intermountain Sites - Summer 2006-2008

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Figure 6-11. Simulated vs. Observed MDA8 Ozone Concentrations (ppb) for the Great Lakes CASTNet sites. The Boxand-Whisker Plots (Minimum, 25 th , 50 th , 75 th

Percentiles, and Maximum) Summarize NAB and NB for 10-ppb Bins of Observed Ozone Concentration: 2006-2008. Spring (March–May) Summer (June–August)

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Great Lakes Sites - Spring 2006-2008

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Great Lakes Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Great Lakes Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Great Lakes Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Great Lakes Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Great Lakes Sites - Summer 2006-2008

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Figure 6-12. Simulated vs. Observed MDA8 Ozone Concentrat ions (ppb) for the Southeast CASTNet sites. The Box-andWhisker Plots (Minimum, 25 th , 50 th , 75 th

Percentiles, and Maximum) Summari ze NAB and NB for 10-ppb Bins of Observed Ozone Concentration: 2006-2008. Spring (March–May) Summer (June–August)

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Southeast Sites - Spring 2006-2008

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Southeast Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Southeast Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Southeast Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Southeast Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Southeast Sites - Summer 2006-2008

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Figure 6-13. Simulated vs. Observed MDA8 Ozone Concentrat ions (ppb) for the Northeast CASTNet sites. The Box-andWhisker Plots (Minimum, 25 th , 50 th , 75 th

Percentiles, and Maximum) Summari ze NAB and NB for 10-ppb Bins of Observed Ozone Concentration: 2006-2008



### . Spring (March–May) Summer (June–August)

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Northeast Sites - Spring 2006-2008

0 20 40 60 80 100

0 2 0 4 0 6 0 8 0 1 0 0Base Simulated (ppb)

Observed (ppb) CASTNet MDA8 for Northeast Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Northeast Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100PRB Concentration (ppb)

Obs Concentration Range (ppb) NAB Summary for Northeast Sites - Summer 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Northeast Sites - Spring 2006-2008

0 20 40 60 80 100

0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 >100NB Concentration (ppb)

Obs Concentration Range (ppb) NB Summary for Northeast Sites - Summer 2006-2008

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11-035 

### An additional comparison highlights the frequency distribution of the observed and simulated ozone concentrations for sites at different elevations. In this case, the sites are separated into two groups according to site elevation. CASTNet sites with elevations less than 1.5 km are in one group and sites with elevations greater than 1.5 km are in another group. Figure 6-14 illustrates the frequency distribution of observed, base, NAB, and NB concentrations for each group of sites. For each 10-ppb bin, frequency is calculated as the number of days with MDA8 concentrations within that bin divided by the total number of days included in the distribution. All days within the three year simulation period were included. A five-point smoother was applied to each distribution for plotting.

Figure 6-14. Frequency Distributions of MDA8 Ozone Co ncentrations (ppb) for Marc h – August 2006, 2007 & 2008 for Low-Elevation (<1.5 km) and High-Elevat ion (>1.5 km) CASTNet Sites. Observed Values are in Black; Model Results are in Red, NAB is in Blue, and NB is in Green (Dashed).

Low-Elevation Sites

0 0.02 0.04 0.06 0.08 0.1

0 10 20 30 40 50 60 70 80 90 100 110 120 130 14Frequency

O3 Conc (ppb) Frequency Distributions of MDA8 of O3 Conc in March-August 2006-2008: Low Altitude Sites ( <1.5 km)

0

Observed GEOS-Chem NAB NB

High-Elevation Sites

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0 10 20 30 40 50 60 70 80 90 100 110 120 130 14Frequency

O3 Conc (ppb) Frequency Distributions of MDA8 of O3 Conc in March-August 2006-2008: High Altitude Sites ( > 1.5 km)

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Observed GEOS-Chem NAB NBModeling for North American Background Concentrations Additional Scenarios and Comparisons



### The overall frequency distribution of the observed concentrations is better represented at the high-elevations sites, compared to the lower-elevations sites. The offset for the lower-elevation sites indicates that much of the overestimation of ozone indicated by the statistical model performance evaluation is associated with the lower elevation sites.

The distributions are also quite different between the high- and low-elevations sites, with a clear tendency for higher concentrations, including NAB and NB concentrations, at the high-elevation sites.

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# 7. Attributes and Limitations

The GEOS-Chem tool allows the estimation of contributions to background ozone concentrations from a variety of sources and source regions, and the non-linear effects associated with the removal of emissions from selected sources and source regions has been shown to be small.

Attributes and limitations include:

 The grid resolution required for a global simulation is not expected to resolve regional- andurban-scale ozone production in the U.S. and elsewhere and thus may under- or overestimate the anthropogenic contribution to long-range ozone transport.

 The GEOS-CHEM chemical mechanism includes a relatively detailed representation of the reactions and species involved in the production of ozone in the atmosphere. Details of the mechanism are presented in Evans et al. (2003). The mechanism includes hundreds of reactions and more than 80 species. In a comparison of chemical mechanisms, Emmerson and Evans (2008) noted that the GEOS-CHEM mechanism (and the other mechanisms evaluated in their paper) should be able to represent the atmospheric chemistry in the troposphere. Nevertheless, all chemical mechanisms suffer from the necessity to limit the number of reactions and species to a finite set rather than the many thousands of reactions and species actually taking part in the chemistry of the troposphere. Perhaps even more important, limitations in grid resolution of the model can limit the model’s abilit y to properly represent the relative proportions of species. This limitation could result in altera tions in the estimates of ozone production rates compared to what would be simulated with higher grid resolution. Good performance at monitors will not guarantee that alterations in the chemical mix (e.g., by removing a category of emissions) will produce the correct response in ozone production. Hence, the chemical mechanism and the interaction of the chemical mechanism with grid resolution must be considered to be potential sources of uncertainty in the model results.

 Emissions estimates for GEOS-CHEM are based on data available to the model developers. These data are more readily available for some parts of the world (e.g., the U.S., Europe) than others (e.g., developing nations). The m agnitude and distribution of emissions are therefore sources of uncertainty in the model runs, and this uncertainty may be difficult to quantify for many parts of the world. Although the chemical mechanism in GEOS-CHEM includes a wide range of hydrocarbons, the number of emitted species included in the model is much smaller. The speciation of emissions into constituent hydrocarbons is difficult even for domestic US emissions, where relatively robust data are available for making these estimates. For parts of the world where data are lacking, even greater uncertainty is present. The use of a more limited set of emitted species is likely appropriate given that a more detailed speciation of hydrocarbons would necessarily involve some guess work. Uncertainties in the speciation of hydrocarbons introduce another uncertainty into the GEOS-CHEM simulation results.

 Considering the scale and resolution of the modeling domain, parameterizations of smallscale processes, such as boundary layer ventilation and downward mixing of free tropospheric and surface air are key sources of uncertainty in any global model application, including this application of GEOS-Chem.

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###  It is difficult to fully evaluate model performanc e, given the grid resolution and the available data. In particular, it is difficult to confirm that the model reliably simulates the vertical distribution (and transport) of ozone aloft as well as the various processes, such as vertical mixing within the troposphere and stratospheric ozone intrusion, that influence background ozone levels.

The assessment of model performance for this application reveals consistent overestimation of ozone concentrations throughout the U.S., but especially in the eastern U.S. Comparison of simulated and observed ozone profiles for five case-study periods (a total of 12 days) and several locations within the western U.S. gives mixed results. For some cases, the simulated vertical profiles show poor agreement with the observations. For other cases the results are more promising in that although the detailed vertical structure of observed profiles is not well simulated, the model results show layers of high ozone in the middle troposphere, consistent with the observations.

# 8. References

Bey, I., D.J. Jacob, R.M. Yantosca, J.A. Logan, B.D. Field, A.M. Fiore, Q. Li, H.Y. Liu, L.J. Mickley, and M. Schultz. 2001. Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation. J. Geophys. Res. , 106, 23,073– 23,096.

K.M. Emmerson and M.J. Evans. 2008. Comparison of tropospheric chemistry schemes for use within global models. Atmos. Chem. Phys. Discuss ., 8, 19957–19987.

M. Evans, A. Fiore, and D.J. Jacob. 2003. The GEOS-Chem Chemical Mechanism Version 5-7- 08. http://acmg.seas.harvard.edu/geos/wiki_docs/chemistry/geoschem_mech.pdf.

Fiore A., D.J. Jacob, H. Liu, R.M. Yantosca, T.D., Fairlie, and Q. Li. 2003. Variability in surface ozone background over the United States: Implications for air quality policy. J. Geophys. Res ., 108(D24), 4787.

Liu H., D.J. Jacob, I. Bey, and R.M. Yantosca. 2001. Constraints from 210 

### Pb and 7 

### Be on wet deposition and transport in a global three-dim ensional chemical tracer model driven by assimilated meteorological fields. J. Geophys. Res ., 106(12), 109-128.

Mao, J., D.J. Jacob, M.J. Evans, J.R. Olson, X. Ren, H.W. Brune, J.M. Clair, J.D. St., Crounse, K.M. Spencer, M.R. Beaver, P.O. Wennberg, M.J. Cubison, J.L. Jimenez,., A. Fried, P. Weibring, J.G. Walega, S.R. Hall, A.J. Weinheimer, R.C. Cohen, G. Chen, J.H. Crawford, C. McNaughton, A.D. Clarke, L. Jaegl ́e, J.A. Fisher, R.M. Yantosca, P. Le Sager, and C. Carouge. 2010. Chemistry of hydrogen oxide r adicals (HOx) in the Arctic troposphere in spring, Atmos. Chem. Phys ., 10, 5823–5838.

McLinden, C.A, C.S. Olsen, B. Hannegan, O. Wild, M.J. Prather, and O. Sundet. 2000. Stratospheric ozone in 3-D models: A simple chemistry and the cross-tropopause ozone flux. J. Geophys. Res ., 105(14), 653-655.

Thompson, A.M., J.E. Yorks, S.K. Miller, J.C. Whitte, K.M. Dougherty, G.A. Morris, D. Baumgardner, L. Ladino, and B. Rappengluck. 2008. Tropospheric ozone sources and wave activity over Mexico City and Hous ton during MILAGRO/Intercontinental Transport Experiment (INTEX-B) Ozonesonde Network Study, 2006 (IONS-06). Atmos. Chem. Phys.

, 8, 5113-5125.

Thompson, A.M., S.J. Oltmans, D.W. Tarasick, P. von der Gather, H.G.J. Smit, J.C. Witte. 2011. Strategic ozone sounding networks: Review of design and accomplishments. Atmos. Environ ., 45, 2145-2163.

Wang, Y., D.J. Jacob, and J.A. Logan. 1998. Global simulation of tropospheric O3-NOxhydrocarbon chemistry, 1. Model formulation. J. Geophys. Res ., 103(D9), 10,713-10,726.

Wang, H., D.J. Jacob, P. Le Sager, D.G. Streets, R.J. Park, A.B. Gilliland, and A. van Donkelaar. 2009. Surface ozone background in the United States: Canadian and Mexican pollution influences, Atmos. Environ ., 43(1), 310-1,319.

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### Wesley, M.L. 1989. Parameterization of surface resistance to gaseous dry deposition in regional-scale numerical models. Atmos. Environ ., 23, 1293-1304.

Wimmers, A.J., J.L. Moody, E.V. Browell, J.W. Hair, W.B. Grant, C.F. Butler, M.A. Fenn, C.C. Schmidt, J. Li, and B.A. Ridley. 2002. Signatures of tropopause folding in satellite imagery, J. Geosphys. Res ., 108(D4), 8360-8371.

Yantosca and Carouge. 2011. GEOS–Chem v9–01–01 Online User's Guide. http://acmg.seas.harvard.edu/geos/doc/man.

Zhang, L. 2011. Personal communication with Dr. Lin Zhang of the Harvard University Atmospheric Chemistry Modeling (ACM) Group.

Zhang L. and D. Jacob. 2011. Presentation entitled “GEOS-Chem Estimates of PRB Ozone (with focus on Intermountain West).” Prepared for BP, EPRI & NASA.

Zhang, L., D.J. Jacob, N.V. Smith-Downey, D.A. Wood, D. Blewitt, C.C. Carouge, A. vanDonkelaar, D.B.A., Jones, L.T. Murray, Y. Wang. 2011. Improved estimate of the policyrelevant background ozone in the United States using the GEOS-Chem global model with 1/ 2 ° •2/3 ° horizontal resolution over North America. Accepted for publication in Atmospheric Environment.