Draft Final Report

MODELING PROTOCOL FOR THE DENVER 8-HOUR OZONE 

ATTAINMENT DEMONSTRATION MODELING 

Prepared for 

Gerald Dilley 

Denver Regional Air Quality Council 

1445 Market Street, Suite 260 

Denver, Colorado 80202 

Prepared by 

Ralph Morris 

Bo Wang 

Ed Tai 

ENVIRON International Corporation 

773 San Marin Drive, Suite 2115 

Novato, California 94998 

And 

Dennis McNally 

Cyndi Loomis 

Gregory Stella 

T.W. Tesche 

Alpine Geophysics, LLC 

7341 Poppy Way 

Arvada, Colorado 80007 

November 28, 2007 

 773 San Marin Drive, Suite 2115, Novato, CA 94998 415.899.0700 
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TABLE OF CONTENTS 

Page 

1.0 INTRODUCTION................................................................................................................ 1-1 

1.1 Overview.................................................................................................................... 1-1 

1.2 Study Background...................................................................................................... 1-1 

1.3 Lead Agency and Principal Participants.................................................................... 1-2 

1.4 Related Regional Modeling Studies........................................................................... 1-2 

 1.4.1 EPA Regional Regulatory Air Quality Programs ................................................ 1-3 

 1.4.2 Denver EAC SIP Modeling ................................................................................. 1-3 

 1.4.3 WRAP Regional Modeling Center Modeling...................................................... 1-3 

 1.4.4 Four Corners Air Quality Task Force .................................................................. 1-4 

 1.4.5 Environmental Impact Statements (EISs) and Related Modeling ....................... 1-4 

 1.4.6 ROMANS ............................................................................................................ 1-4 

1.5 Overview of Modeling Approach .............................................................................. 1-5 

 1.5.1 Ozone Episode Selection ..................................................................................... 1-5 

 1.5.2 Model Selection ................................................................................................... 1-6 

 1.5.3 Emissions Input Preparation and QA/QC............................................................ 1-6 

 1.5.4 Meteorology Input Preparation and QA/QC........................................................ 1-8 

 1.5.5 Air Quality Modeling Input Preparation and QA/QC.......................................... 1-8 

 1.5.6 Proposed Model Performance Goals ................................................................. 1-10 

 1.5.7 Diagnostic and Sensitivity Studies..................................................................... 1-10 

 1.5.8 Weight of Evidence Analyses............................................................................ 1-13 

 1.5.9 Assessing Model Reliability in Estimating the Effects of Emissions Changes. 1-14 

 1.5.10 Future Year Control Strategy Modeling............................................................. 1-15 

 1.5.11 Future Year Ozone Attainment Demonstration ................................................. 1-15 

1.6 Project Participants and Contacts............................................................................. 1-15 

1.7 Communication........................................................................................................ 1-16 

1.8 Schedule................................................................................................................... 1-17 

2.0 MODEL SELECTION ........................................................................................................ 2-1 

2.1 Regulatory Context for Model Selection ................................................................... 2-1 

 2.1.1 Summary of Recommended Models.................................................................... 2-2 

2.2 Details of the Recommended Models........................................................................ 2-3 

 2.2.1 The MM5 Meteorological Model ........................................................................ 2-3 

 2.2.2. The Emissions Modeling Systems....................................................................... 2-5 

 2.2.3 The CAMx Regional Photochemical Model........................................................ 2-5 

2.3 Justification for Model Selection............................................................................... 2-7 

 2.3.1 MM5 .................................................................................................................... 2-7 

 2.3.2 Emission Models.................................................................................................. 2-8 

 2.3.3. CAMx .................................................................................................................. 2-8 

2.4 Model Limitations...................................................................................................... 2-9

 2.4.1 MM5 .................................................................................................................... 2-9 
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 2.4.2 SMOKE................................................................................................................ 2-9

 2.4.3 CAMx .................................................................................................................2.10 

2.5 Model Input Requirements ...................................................................................... 2-10 

 2.5.1 MM5 .................................................................................................................. 2-10 

 2.5.2 Emissions ........................................................................................................... 2-10

 2.5.3 CAMx ................................................................................................................ 2-11

2.6 Summary of Model Selection and Justification....................................................... 2-11 

2.7 Availability of Model Codes, Analysis Tools and Related Software ...................... 2-11 

3.0 EPISODE SELECTION...................................................................................................... 3-1 

3.1 Overview of EPA Guidance....................................................................................... 3-1 

 3.1.1. Primary Criteria ................................................................................................... 3-1 

 3.1.2 Secondary Criteria ............................................................................................... 3-1 

3.2 Selection of Denver 8-hour Ozone Modeling Episode(s).......................................... 3-2 

 3.2.1 Key Denver Ozone Monitors............................................................................... 3-2 

 3.2.2 Episode Selection Approach................................................................................ 3-3 

 3.2.3 High Ozone Levels from 2002-2007 ................................................................... 3-3 

 3.2.4 Daily 8-Hour Ozone Time Series for 2002-2007................................................. 3-8 

3.3 Final Selection of Denver 8-Hour Ozone Modeling Period .................................... 3-12 

4.0 MODELING DOMAINS AND DATA AVAILABILITY................................................ 4-1 

 4.1 Horizontal Modeling Domain.................................................................................... 4-1 

 4.2 Vertical Modeling Domain ........................................................................................ 4-7 

 4.3 Data Availability........................................................................................................ 4-9 

 4.3.1 Emissions Data..................................................................................................... 4-9 

 4.3.2 Air Quality ........................................................................................................... 4-9 

 4.3.3. Ozone Column Data........................................................................................... 4-12 

 4.3.4 Meteorological Data........................................................................................... 4-12 

 4.3.5 Initial and Boundary Conditions Data ............................................................... 4-12 

5.0 MODEL INPUT PREPARATION PROCEDURES ........................................................ 5-1 

5.1 Meteorological Inputs ................................................................................................ 5-1 

 5.1.1 MM5 Model Science Configuration .................................................................... 5-1 

 5.1.2 MM5 Input Data Preparation Procedures ............................................................ 5-1 

 5.1.3 MM5CAMx Reformatting Methodology ............................................................ 5-4 

 5.1.4 Treatment of Minimum KV .................................................................................. 5-5

5.2 Emission Inputs.......................................................................................................... 5-5 

 5.2.1 Available Emissions Inventory Datasets ............................................................. 5-5 

 5.2.2 Development of CAMx-Ready Emissions Inventories........................................ 5-6 

 5.2.3 Use of the Plume-in-Grid (PiG) Subgrid-Scale Plume Treatment..................... 5-11 

 5.2.4 Products of the Emissions Inventory Development Process.............................. 5-12 

 5.2.5 Future-Year Emissions Modeling...................................................................... 5-13 
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 5.3 Photochemical Modeling Inputs .............................................................................. 5-13 

 5.3.1 CAMx Science Configuration and Input Configuration.................................... 5-13 

6.0 OZONE MODEL PERFORMANCE EVALUATION .................................................... 6-1 

 6.1 Establishing Base Case CAMx Simulations for Denver............................................ 6-1 

 6.1.1 Setting Up and Exercising CAMx Base Cases .................................................... 6-1 

 6.1.2 Use of Sensitivity, Source Apportionment, and 

 Related Diagnostic Probing Tools ....................................................................... 6-2 

 6.2 Evaluation of CAMx Base Cases for the Denver Region.......................................... 6-3 

 6.2.1 Overview.............................................................................................................. 6-3 

 6.2.2 Meteorological Model Evaluation Methodology................................................. 6-5 

 6.2.3 Photochemical Model Evaluation Methodology ................................................. 6-6 

 6.2.4 Available Aerometric Data for the Evaluations................................................... 6-9 

7.0 FUTURE YEAR MODELING ........................................................................................... 7-1

 7.1 Future Year to be Simulated ...................................................................................... 7-1 

 7.2 Future Year Growth and Controls.............................................................................. 7-1 

 7.2.1 Regional Growth and Control Factors ................................................................. 7-1 

 7.2.2 Local Growth and Control Factors ...................................................................... 7-2 

 7.3 Future Model–Ready Emissions Inventory Development and QA ........................... 7-2 

 7.4 Future Year Baseline Air Quality Simulations .......................................................... 7-2 

 7.4.1 Future-Year Initial and Boundary Conditions ..................................................... 7-3 

 7.4.2 Other Future-Year Modeling Inputs .................................................................... 7-3 

 7.5 Emissions Sensitivity Experiments............................................................................ 7-3 

 7.6 Control Strategy Development, Testing and Analysis............................................... 7-4 

8.0 OZONE ATTAINMENT DEMONSTRATION ............................................................... 8-1 

8.1 Ozone Weight of Evidence Analyses ........................................................................ 8-1 

 8.2 8-Hour Ozone Attainment Demonstration Procedures.............................................. 8-1 

 8.3 Exceptions to EPA Guidance..................................................................................... 8-3 

 8.3.1 Current Year Design Value (DVC) Used in Projections ..................................... 8-3 

 8.3.2 Definition of Near the Monitor............................................................................ 8-3 

 8.4 Unmonitored Areas Attainment Test......................................................................... 8-4 

9.0 REFERENCES..................................................................................................................... 9-1 
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TABLES 

Table 1-1 Key participants and contact information for the 

 Denver 8-hour ozone attainment demonstration modeling study...................... 1-16 

Table 1-2 Key deliverables and dates for the Denver 8-hour 

 ozone attainment demonstration modeling study. ............................................. 1-17 

Table 2-1 Factors qualifying MM5 for use in the Denver 8-hour 

 ozone modeling study ........................................................................................ 2-12 

Table 2-2. Factors qualifying SMOKE, CONCEPT and MEGAN 

 emissions models for use in the Denver ozone modeling study. ..................... 2-13 

Table 2-3. Factors qualifying CAMx as the photochemical grid model 

 for use in the Denver ozone modeling study. .................................................. 2-14 

Table 2-4. Factors justifying MM5 as the meteorological model for the 

 Denver ozone modeling study ........................................................................... 2-15 

Table 2-5. Factors justifying SMOKE/CONCEPT/MEGAN as the 

 emissions model for the Denver ozone modeling study .................................... 2-16 

Table 2-6. Factors justifying CAMx as the photochemical model for 

 the Denver ozone modeling study...................................................................... 2-17 

Table 3-1. Fourth highest daily maximum 8-hour ozone concentrations (ppm) 

 at monitoring sites in the Denver area during 2005, 2006 and 2007 

 and 2005-2007 8-hour ozone Design Values....................................................... 3-2 

Table 4-1. Lambert Conformal Projection (LCP) definition for the 

 Denver 36/12/4 km modeling grid....................................................................... 4-6 

Table 4-2. Grid definitions for MM5, Emissions and CAMx............................................... 4-7 

Table 4-3. Vertical layer definition for MM5 simulations (left most 

 columns), and approach for reducing CAMx layers by 

 collapsing multiple MM5 layers (right columns) ................................................ 4-8 

Table 4-4. Overview of routine ambient data monitoring networks ................................... 4-10 

Table 4-5. Ozone monitoring sites within and near the Denver 

 area operating during 2002-2007....................................................................... 4-12 

Table 5-1. MM5 (Version 3.7:4) model configuration ......................................................... 5-2 

Table 5-2. Emissions model configurations.......................................................................... 5-7 

Table 5-3. CAMx (Version 4.5) model configuration......................................................... 5-15 

Table 6-1. Statistical measures and graphical displays used in the 

 MM5 operational evaluation.............................................................................. 6-10 

Table 6-2. Statistical measures and graphical displays used in the 

 MM5 scientific evaluation. (measures and displays 

 developed for each simulation day) ................................................................... 6-11 

Table 6-3. Statistical measures and graphical displays for 1-hour and 

 8-hour ozone concentrations to be used in the screening 

 model performance evaluation (SMPE) of CAMx surface 

 ozone concentrations.......................................................................................... 6-12 

Table 6-4. Statistical measures and graphical displays for 1-hour and 

 8-hour ozone, VOCs, NOx, and indicator species and indicator 

 species. Ratios to be used in the refined model performance 

 evaluation (RMPE) involving multi-species, multi-scale evaluation 

 of CAMx surface and aloft concentrations ........................................................ 6-12 
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FIGURES 

Figure 3-1. Number of days during each of the years 

 from 2002-2007 that the daily maximum 8-hour 

 ozone concentration at any monitor in the Denver 

 area was 85, 75 or 70 ppb or higher..................................................................... 3-4 

Figure 3-2a. Number of days during each of the years from 2002-2007 

 that the daily maximum 8-hour ozone concentration at the 

 Rocky Flats North (RFNO) monitor was 85, 75 or 70 ppb or higher.................. 3-5 

Figure 3-2b. Number of days during each of the years from 2002-2007 

 that the daily maximum 8-hour ozone concentration at the 

 Chatfield (CHAT) monitor was 85, 75 or 70 ppb or higher ................................ 3-6 

Figure 3-2c. Number of days during each of the years from 2002-2007 that 

 the daily maximum 8-hour ozone concentration at the NREL 

 monitor was 85, 75 or 70 ppb or higher............................................................... 3-6 

Figure 3-2d. Number of days during each of the years from 2002-2007 

 that the daily maximum 8-hour ozone concentration at the 

 South Boulder Creek (SBC) monitor was 85, 75 or 70 ppb or higher................. 3-7 

Figure 3-2e. Number of days during each of the years from 2002-2007 

 that the daily maximum 8-hour ozone concentration at the 

 Fort Collins West (FTCW) monitor was 85, 75 or 70 ppb or 

 higher (data only available for 2006 and 2007)................................................... 3-7 

Figure 3-3a. Time series of four highest daily maximum 8-hour ozone 

 concentrations in the Denver area during 2002. .................................................. 3-9 

Figure 3-3b. Time series of four highest daily maximum 8-hour ozone 

 concentrations in the Denver area during 2003 ................................................. 3-10 

Figure 3-3c. Time series of four highest daily maximum 8-hour ozone 

 concentrations in the Denver area during 2004. ................................................ 3-10 

Figure 3-3d. Time series of four highest daily maximum 8-hour ozone 

 concentrations in the Denver area during 2005. ................................................ 3-11 

Figure 3-3e. Time series of four highest daily maximum 8-hour ozone 

 concentrations in the Denver area during 2006. ................................................ 3-11 

Figure 3-3f. Time series of four highest daily maximum 8-hour ozone 

 concentrations in the Denver area during 2007. ................................................ 3-12 

Figure 4-1a. Nested 36/12/4 km modeling domains for the Denver 8-hour 

 ozone modeling study. Blue line domains are for CAMx/SMOKE 

 that are nested in the MM5 red line domains....................................................... 4-2 

Figure 4-1b. Nested 36/12/4 km modeling domains for the Denver MM5 

 meteorological modeling ..................................................................................... 4-3 

Figure 4-1c. Nested 36/12/4 km modeling domains for the Denver CAMx 

 air quality and SMOKE emissions modeling. .................................................... 4-4 

Figure 4-1d. Nested 12/4 km modeling domains for the Denver CAMx air 

 quality and SMOKE emissions modeling............................................................ 4-5 

Figure 4-1e. Denver 4 km modeling domains for the CAMx air quality and 

 SMOKE emissions modeling and locations of ozone monitoring 

 sites within and near the Denver NAA ................................................................ 4-6 

Figure 4-2. Locations of ozone monitoring sites within and near the 

 Denver area ........................................................................................................ 4-11 
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Figure 5-1. Occurrence of reported wildfires in Colorado during the 

 June-July 2006 modeling period broken down by 

 May 25-June 15 (top left), June 10-30 (top right), June 25-July 15 

 (bottom left) and July 10-July 31, 2006 (bottom right) ..................................... 5-10 
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1.0 INTRODUCTION 

1.1 Overview 

This report constitutes the Air Quality Modeling Protocol for the Denver Metropolitan Area 

(DMA) and adjacent regions 8-hour ozone modeling analysis in support of the development of 

an 8-hour ozone State Implementation Plan (SIP) and attainment demonstration. This protocol 

describes the overall modeling activities to be performed in order to demonstrate attainment of 

the 8-hour ozone standard in the DMA and adjacent areas in Colorado. The DMA 8-hour ozone 

modeling is being carried out by a contracting team of ENVIRON International Corporation and 

Alpine Geophysics, LLC (Alpine) (the modeling team) under contract to the Denver Regional 

Air Quality Council (RAQC) which is the lead agency for this project. Providing assistance to 

the RAQC are the Colorado Department of Public Health and Environment (CDPHE), Denver 

Regional Council of Governments (DRCOG), Colorado Department of Transportation (CDOT) 

and the Northern Front Range Metropolitan Planning Organization (NFRMPO). 

A comprehensive modeling protocol for an 8-hour ozone SIP attainment demonstration study 

consists of many elements. Its main function is to serve as a means for planning and 

communicating how a modeled attainment demonstration will be performed before it occurs. 

The protocol guides the technical details of a modeling study and provides a formal framework 

within which the scientific assumptions, operational details, commitments and expectations of 

the various participants can be set forth explicitly and means for resolution of potential 

differences of technical and policy opinion can be worked out openly and within prescribed time 

and budget constraints. 

As noted in the U.S. Environmental Protection Agency’s (EPA) 8-hour ozone modeling 

guidance, the modeling protocol serves several important functions (EPA, 2007): 

• Identify the assistance available to the RAQC and APCD (the lead agencies) to undertake 

and evaluate the analysis needed to support a defensible attainment demonstration; 

• Identify how communication will occur among State, Local and Federal agencies and 

stakeholders to develop a consensus on various issues; 

• Describe the review process applied to key steps in the demonstration; and 

• Describe how changes in methods and procedures or in the protocol itself will be agreed 

upon and communicated with stakeholders and the appropriate U.S. EPA regional Office. 

1.2 Study Background 

Ozone air quality in the DMA has been near the 8-hour ozone National Ambient Air Quality 

Standard (NAAQS) of 0.08 ppm (exceedance defined by values of 85 ppb and higher). In 

December 2002, the RAQC and APCD and others entered into an 8-hour ozone Early Action 

Compact (EAC) with the U.S. Environmental Protection Agency (EPA). EPA’s EAC allows an 

area to submit an enforceable 8-hour ozone SIP by March 2004 that demonstrates attainment of 

the 8-hour ozone standard by 2007. In return EPA will defer the classification of an area as 

nonattainment until 2007. The RAQC and APCD contracted with ENVIRON and Alpine to do 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-2 

the photochemical modeling necessary for the Denver 8-hour ozone EAC. At the outset of the 

EAC modeling, Denver attained the 8-hour ozone NAAQS. However, the monitored ozone 

concentrations during the summer of 2003 resulted in violations of the 8-hour ozone standard. 

Because of the EAC, EPA designated the DMA 8-hour ozone classification as “nonattainment 

deferred” with final designation to be determined after the 2007 ozone season. More details on 

the Denver 8-hour EAC SIP are available at: 

• http://www.raqc.org/ozone/EAC/ozone-eac.htm

Ozone attainment is based on 8-hour ozone Design Values (DVs) that are defined as the threeyear average of the fourth highest 8-hour ozone concentration during a year at a monitor. Based 

on measured ozone concentrations during 2005-2007, the maximum 8-hour ozone DV in the 

DMA was 85 ppb at the Rocky Flats North (RFNO) monitoring site, which exceeds the 8-hour 

ozone NAAQS. Consequently, EPA is expected to designate the DMA as nonattainment for 8-

hour ozone and the RAQC/APCD will need to develop an 8-hour ozone SIP that demonstrates 

the DMA will achieve attainment of the 8-hour ozone NAAQS by 2010. 

On June 20, 2007, EPA proposed new primary and secondary ozone NAAQSs that would likely 

be more stringent than the current 8-hour ozone NAAQS of 85 ppb. EPA requested comments 

on a proposed new 8-hour ozone NAAQS with thresholds in the 0.070 ppm to 0.075 ppm range 

(70-75 ppb) or whether they consider values as low as 0.060 ppm (60 ppb) or keep the threshold 

at the current 0.08 ppm (85 ppb) level. Of the ~14 ozone monitors in the greater DMA, half have 

2005-2007 8-hour ozone DVs that are 75 ppb or higher and all of them, except the downtown 

Denver CAMP monitor, have 8-hour ozone DVs of 70 ppb or higher. 

1.3 Lead Agency and Principal Participants

The Denver RAQC and CDPHE/APCD are the lead agencies in the development of the Denver 

8-hour ozone SIP. Additional participants include the Denver Regional Council of Governments 

(DRCOG), the Colorado Department of Transportation (CDOT), Northern Front Range 

Metropolitan Planning Organization (NFRMPO), and the Colorado Air Quality Control 

Commission (AQCC). EPA Region 8 in Denver is the local regional EPA office that will take 

the lead in the approval process for the Denver 8-hour ozone SIP. The RAQC has contracted 

with ENVIRON International Corporation with their subcontractor Alpine Geophysics, LLC (the 

modeling team) to assist them and the APCD in the 8-hour ozone attainment modeling 

demonstration. 

1.4 Related Regional Modeling Studies 

There are several additional ozone modeling studies that are nearby and related to the Denver 8-

hour ozone modeling analysis whose results may be useful to the Denver 8-hour ozone 

modeling. 
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1.4.1 EPA Regional Regulatory Air Quality Programs

There are several EPA regional regulatory air control initiatives that have either a direct or 

indirect relevance to the Denver 8-hour ozone attainment demonstration SIP. These issues 

include, but are not limited to, the following: 

Clean Air Interstate Rule (CAIR): Although the State of Colorado is not part of the 

CAIR control region for ozone and/or PM2.5 that focuses on the eastern U.S. (e.g., Texas, 

Missouri, Illinois, Wisconsin and Minnesota eastwards), when flow is from the east the 

CAIR controls will likely reduce ozone transport into the DMA somewhat. 

Clean Air Mercury Rule (CAMR): Colorado Electrical Generating Units (EGU) are 

subject to the requirements of the Clean Air Mercury Rule (CAMR). 

Clean Air Visibility Rule (CAVR): The Clean Air Visibility Rule (CAVR) requires 

specific sources that are shown to reasonably contribute to visibility impairment at a 

Class I area to install Best Available Retrofit Technology (BART). The BART 

requirements apply to sources built between 1962 and 1977 that have the potential to emit 

250 tons per year (TPY) of a visibility impairing pollutants (SO2, NOx, PM and/or VOC) 

and are one of 26 specific source categories. EPA has published guidelines for the BART 

component of the CAVR (EPA, 2005c). The APCD has published BART rules that 

would reduce NOx and SO2 emissions from several large sources that may contribute to 

ozone concentrations in the DMA so would benefit the Denver 8-hour ozone problem. 

Details on the Colorado BART rule making can be found at: 

• http://www.cdphe.state.co.us/ap/RegionalHazeBART.html

1.4.2 Denver EAC SIP Modeling

The Denver EAC SIP modeling discussed previously performed 36/12/4/1.33 km photochemical 

modeling of the DMA using the MM5 meteorological, EPS3 emissions and CAMx 

photochemical grid models and a summer 2002 period (see: 

http://www.raqc.org/ozone/EAC/ozone-eac.htm). Although the EAC SIP modeling used grid 

spacing as small as 1.33 km and noted improved meteorological performance at the finer grid 

spacing, there were little benefits in the photochemical modeling using the 1.33 km versus 4 km 

grid spacing. In fact ozone model performance degraded somewhat using the 1.33 km grid and 

the computational requirements increased substantially. Based on these findings the current 

Denver 8-hour ozone modeling is not going down to use a 1.33 km grid and will use a 4 km grid 

for the DMA. 

1.4.3 WRAP Regional Modeling Center Modeling

Five Regional Planning Organizations (RPOs) are performing regional haze modeling using 

photochemical ozone and PM models to support the development of regional haze SIPs due 

December 2007. The Western Regional Air Partnership (WRAP) is the RPO for the western 

states and the modeling is being conducted by the Regional Modeling Center (RMC) that 

consists of the University of California at Riverside (UCR), ENVIRON International 

Corporation and the University of North Carolina (UNC). The RMC has conducted modeling 

for the 2002 annual period and continental U.S. using a 36 km grid and the MM5 meteorological 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-4 

(Kemball-Cook et al., 2005), SMOKE emissions and CMAQ and CAMx photochemical models. 

CMAQ was run for a 2002 base case 2018 future base-year and 2018-control scenarios to predict 

visibility projections in the Federal Class I areas. The WRAP RMC has a website where 

modeling results can be obtained and some of the modeling results have been implemented in the 

WRAP Technical Support System (TSS) website where users can analyze data and modeling 

results. These websites are at: 

• http://pah.cert.ucr.edu/aqm/308/index.shtml

• http://vista.cira.colostate.edu/tss/

1.4.4 Four Corners Air Quality Task Force

The Four Corners Air Quality Task Force (FCAQTF) is conducting emissions and 

photochemical grid modeling of the four corners area to provide information regarding ozone, 

visibility and deposition impacts in the region. The states of Colorado and New Mexico are 

active participants in the FCAQTF. The SMOKE emissions and CAMx air quality models are 

being applied on a 36/12/4 km grid with the 4 km grid focused on northwest New Mexico, 

southwest Colorado and small portions of southeast Utah and northeast Arizona. This region not 

only includes the San Juan basin oil and gas development area but several large coal-fired power 

plants as well (Four Corners and San Juan). The FCAQTF is performing 2005 base case 

modeling as well as 2018 future-year modeling and 2018 sensitivity modeling of several 

mitigation scenarios. More details on the FCAQTF modeling can be found at: 

• http://www.nmenv.state.nm.us/aqb/4C/PublicReview.html

1.4.5 Environmental Impact Statements (EISs) and Related Modeling

Photochemical grid models are also being applied in the general vicinity of the DMA as part of 

the development of Environmental Impact Statements (EISs) for oil and gas development 

projects. The Bureau of Land Management (BLM) has recently completed draft EISs for the 

Moxa Arch, Hiawatha and Pinedale Anticline gas infill projects in southwestern Wyoming that 

used the CAMx photochemical grid model with a 36/12/4 km grid to model the 2002 annual 

period and assess the potential ozone impacts due to the cumulative oil and gas development 

projects in southwestern Wyoming. A new BLM oil and gas production GIS has been initiated 

(Continental Divide – Creston) that will evaluate both the CMAQ and CAMx models and then 

run for 2002, 2005, and 2006. Additional BLM EISs will likely continue to use photochemical 

grid models for such ozone assessments. 

1.4.6 ROMANS

The National Park Service (NPS), CDPHE/APCD and others have initiated the Rocky Mountain 

Atmospheric Nitrogen and Sulfur Study (ROMANS) to study nitrogen deposition and potential 

mitigation scenarios at Rocky Mountains National Park (RMNP). The Rocky Mountain 

Initiative includes data collection, data analysis, modeling and the development of a nitrogen 

deposition reduction plan. Much of the analysis of ROMANS was for the 2006 period that 

corresponds with the Denver 8-hour ozone modeling period that has direct relevance to the 

Denver ozone modeling. Details on the ROMANS study can be found at: 

• http://www.cdphe.state.co.us/ap/rmnp.html
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1.5 Overview of Modeling Approach 

The Denver 8-Hour ozone SIP modeling includes emissions, meteorological and ozone 

simulations using a nested 36/12/4 km grid with the 4-km grid focused on the state of Colorado 

including the DMA and vicinity. 

1.5.1 Ozone Episode Selection

Episode selection is an important component of an 8-hour ozone attainment demonstration. EPA 

guidance recommends that at least 10 days be used to project 8-hour ozone Design Values at 

each critical monitor, with 5 days being an absolute minimum. 

1.5.1.1 EPA Guidance for Episode Selection 

EPA’s current guidance on 8-hour ozone modeling (EPA, 2007) identifies specific criteria to 

consider when selecting one or more episodes for use in demonstrating attainment of the 8-hour 

ozone National Ambient Air Quality Standard (NAAQS). This guidance builds off the 1-hour 

ozone modeling guidance (EPA, 1991) in selecting multiple episodes representing diverse 

meteorological conditions that result in ozone exceedances in the region under study: 

• A variety of meteorological conditions should be covered, this includes the types of 

meteorological conditions that produce 8-hour ozone exceedances in the DMA and 

vicinity; 

• To the extent possible, the modeling data base should include days for which 

extensive data bases (i.e. beyond routine aerometric and emissions monitoring) are 

available; 

• Sufficient days should be available such that relative response factors (RRFs) can be 

based on several (i.e., > 10) days with at least 5 days being the absolute minimum; 

and 

• If possible and appropriate, modeling for an entire ozone season is recommended. 

EPA also lists several “other considerations” to bear in mind when choosing potential 8-hour 

ozone episodes including: 

• Choose periods which have already been modeled; 

• Choose periods which are drawn from the years upon which the current Design 

Values are based; 

• Include weekend days among those chosen; and 

• Choose modeling periods that meet as many episode selection criteria as possible in 

the maximum number of nonattainment areas as possible. 

1.5.1.2 Selection of Denver 8-Hour Ozone Modeling Period 

The June through July 2006 period was selected for the Denver 8-hour ozone SIP modeling. 

Section 3 describes the rationale for selecting this modeling period with the main reasons being: 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-6 

• It is included within the 2005-2007 three-year period which Denver’s 

nonattainment status was based; 

• Includes 8-hour ozone exceedance days at all the key high ozone monitors in the 

DMA; and 

• Includes all exceedance days and most high ozone days in the DMA from 2006, 

which was the summer with the highest number of high 8-hour ozone days from 

the 2005-2007 period. 

1.5.2 Model Selection 

Details on the rationale for model selection are provided in Section 2. The MM5 prognostic 

meteorological model was selected for the Denver ozone modeling using a 36/12/4 km resolution 

grid, but with the 4-km grid covering most of Colorado. Emissions modeling will be performed 

using the SMOKE emissions model for most source categories, but with the CONCEPT 

emissions model used for on-road mobile sources in the DMA to take advantage of the detailed 

traffic information available and the MEGAN model used for biogenic emissions. The CAMx 

photochemical grid model, which supports two-way grid nesting and subgrid-scale Plume-inGrid, will also be used. This is the same SMOKE/MM5/CAMx modeling system used in many 

recent ozone studies including FCAQTF and BLM EISs and is similar to the EPS3/MM5/CAMx 

modeling system used in the Denver 8-hour ozone EAC SIP modeling performed for 2002. 

1.5.3 Emissions Input Preparation and QA/QC

Quality assurance (QA) and quality control (QC) of the emissions datasets are some of the most 

critical steps in performing air quality modeling studies. Because emissions processing is 

tedious, time consuming and involves complex manipulation of many different types of large 

databases, rigorous QA measures are a necessity to prevent errors in emissions processing from 

occurring. The Denver 8-Hour ozone modeling study will perform a multistep emissions 

QA/QC approach. This includes the initial emissions QA/QC by the CDPHE/APCD of their 

emissions for the DMA and surrounding areas, as well as QA/QC by the CDPHE/APCD and the 

modeling team as the dataset is processed and made available for modeling. This multi-step 

process with separate groups involved in the QA/QC of the emissions is designed to detect and 

correct errors prior to the air quality model simulations. 

QA/QC performed as part of the emissions processing includes: 

EPA Input Screening Error Checking Algorithms: Although the SMOKE emissions 

model is the primary tool used for emissions processing contains internal error checking 

and flagging, some additional input error checking algorithms, like those used with the 

EMS and EPS emission models, may be considered to screen the data and identify 

potential emission input errors. Additionally, EPA has issued a revised stack QA and 

augmentation procedures memorandum that will be used to identify and augment any 

outlying stacks. 

SMOKE Error Messages: SMOKE provides various cautionary or warning messages 

during the emissions processing. The SMOKE output will be reviewed for error 

messages. An archive of the log files will be maintained so that the error messages can be 

reviewed at a later date if necessary. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-7 

SMOKE Emissions Summaries: QA functions built into the SMOKE processing system 

will be used to provide summaries of processed emissions as daily totals according to 

species, source category and county and state boundaries. These summaries will then be 

compared with summary data prepared for the pre-processed emissions, e.g., state and 

county totals for emissions from the augmented emissions data. 

CONCEPT QA/QC: The CONCEPT model that will be used for generating the on-road 

mobile source emissions in the DMA was designed to be an open and transparent 

emissions modeling so has extensive QA/QC and error messaging system that will be 

used to QA this portion of the inventory. 

MEGAN QA/QC: The MEGAN biogenic emissions model also includes error messages 

and warnings that need to be examined as part of the QA/QC of the biogenic emissions 

model. One of the most important components of the QA/QC of the biogenic emissions 

is assuring that proper land use data are input and that the MM5 surface temperatures are 

sufficiently accurate and that cloud information is represented correctly. 

After the CAMx-ready emission inputs have been prepared, additional emissions QA/QC will be 

performed as appropriate, such as: 

Spatial Summary: Sum the emissions for all 24 hours to prepare plots showing the spatial 

distribution of daily total emissions using the Package for Analysis and Visualization for 

Environmental (PAVE) data (available from www.cmascenter.org). In our base case 

simulations these plots will be presented as tons per day. Typically emission categories 

are processed using 5 streams of modeling: biogenic, on-road mobile, non-road mobile, 

other low-level anthropogenic and point sources (fires are also analyzed separately when 

available). If possible, separate spatial QA plots will be generated for low-level and 

elevated point sources. The objective of this step is to identify errors in the spatial 

distribution of emissions. 

Short Term Temporal Summary: The total domain emissions for each hour will be 

accumulated and time series plots prepared by source category that display the diurnal 

variation in total hourly emissions. The objective of this step is to identify errors in 

temporal profiles. 

Control Strategy Spatial Displays: Spatial summary plots of the daily total emissions 

differences between a future-year scenarios and base case emissions scenarios will be 

generated. These plots can be used to immediately identify a problem in a control 

strategy. For example, if a state’s NOx emissions control strategy is being analyzed and 

there are changes in emissions for other pollutants or for NOx outside of the DMA, 

problems in emissions processing can be identified prior to the air quality model 

simulation. 

The emissions QA/QC displays will be made available to study participants for review. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-8 

1.5.4 Meteorology Input Preparation and QA/QC

MM5 meteorological modeling of the selected modeling period will include QA/QC and 

evaluation of the meteorological fields. In addition, the modeling team will also perform QA/QC 

of the meteorological data to assure that it has been transferred correctly, to obtain an assessment 

of the quality of the data, and to assist in the interpretation of the air quality modeling results. 

The modeling team will perform the following QA/QC of the MM5 meteorological fields 

developed for the study: 

• Analyses of the various observational input and evaluation data sets to assure that they 

have been transferred correctly; 

• Verification that correct configuration and science options are used in compiling and 

running each module in the MM5 modeling systems (TERRAIN, REGRID, RAWINS, 

INTERPF, etc.); 

• Evaluation of the MM5 fields using the METSTAT program and the comparison of 

model performance statistics against performance benchmarks (see for example the 

WRAP MM5 evaluation at: 

o http://pah.cert.ucr.edu/aqm/308/reports/mm5/DrftFnl_2002MM5_FinalW

RAP_Eval.pdf 

• Evaluation of upper-air MM5 meteorological estimates by comparison to upper-air 

observations and satellite images; 

• Evaluation of MM5 precipitation patterns and intensity against radar and rain-gauge 

analyses available from the Climatic Prediction Center; 

• Comparison of the Denver MM5 simulation performance with those generated for the 

Denver EAC SIP and by WRAP and others; 

• Generation of the CAMx-ready inputs with the MM5CAMx processor, and review of 

summary statistics generated by that program; and 

• Backup and archiving of critical model input/output data. 

1.5.5 Air Quality Modeling Input Preparation and QA/QC

 

Key aspects of QA for the CAMx input and output data include the following: 

• Verification that correct configuration and science options are used in compiling and 

running each module in the CAMx modeling systems, where these include the 

MM5CAMx, TUV, landuse, and initial/boundary condition processors; 

• Evaluation of CAMx results to verify that model output is reasonable and consistent with 

general expectations; 

• Processing and QA of ambient monitoring data for use in the model performance 

evaluation; 

• Evaluation of the CAMx results against concurrent observations and various other CAMx 

simulations; 

• Backup and archiving of critical model input data. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-9 

The most critical elements for CAMx simulations are the QA/QC of the meteorological and 

emissions input files, which are discussed above, and the model performance evaluation. The 

major QA issue specifically associated with the air quality model simulations is verification that 

the correct science options were specified in the model itself and that the correct input files were 

used when running the model. This is accomplished to having multiple team members review 

the job script and job control file for each CAMx run prior to executing the program. Selected 

staff from ENVIRON and Alpine will be charged with reviewing each others CAMx simulation 

control files to assure the proper options and inputs are selected. 

The modeling team will also perform a post-processing QA of the CAMx output files similar to 

that described for the emissions processing. Animated graphic files will be generated 

using PAVE that can be viewed to search for unexpected patterns in the CAMx output files. In 

the case of model sensitivity studies, the animated graphic files will be prepared as difference 

plots for the sensitivity case minus the base case. Often, viewing the animations can discover 

errors in the emissions inputs. Finally, daily maximum 1-hour and 8-hour ozone plots 

with superimposed observations will be produced for each day of the CAMx simulations. This 

will provide a summary that can be useful for quickly comparing various model simulations. 

The Model Performance Evaluation (MPE) is a multi-step process using several different 

techniques: 

ENVIRON Analysis Tools: ENVIRON has developed ozone performance statistical 

techniques, “Soccer Plots”, time series plots, spatial maps and other summary plots that 

displays model performance across networks, episodes, species, models and sensitivity 

tests and compare them against performance goals. These tools can interface with 

Excel® to generate scatter plots and time series plots. It can also interface with 

SURFER® to generate spatial maps of model performance. ENVIRON has also 

developed software to generate 8-hour performance metrics and displays as 

recommended in EPA’s preliminary draft 8-hour ozone modeling guidance (EPA, 1999) 

that analyze predicted and observed daily maximum 8-hour ozone concentrations near 

each monitor. 

UCR Analysis Tools: The University of California at Riverside (UCR) has developed 

Analysis Tools that are used extensively in the CENRAP, VISTAS, and WRAP regional 

haze studies. Graphics are automatically generated using GNUPLOT that generates: (a) 

tabular statistical measures; (b) time Series Plots; and (c) scatter Plots by all sites and all 

days, all days for one site, and all sites for one day. 

The evaluation of the CAMx base case simulations will use the appropriate analysis tools listed 

above to take advantage of their different descriptive and complimentary nature. The use of 

multiple model evaluation tools is also a useful QA/QC procedure to assure that errors are not 

introduced in the model evaluation process. Statistical performance measures for ozone, ozone 

precursors, and products species will be calculated to the extent allowed by the Denver ambient 

monitoring network database. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-10 

1.5.6 Proposed Model Performance Goals

The issue of model performance goals for 8-hour ozone concentrations is an area of ongoing 

research and debate. For 1-hour ozone modeling, EPA has established performance goals for 

unpaired peak performance, mean normalized bias (MNB) and mean normalized gross error 

(MNGE) of <±20%, <±15% and <35%, respectively (EPA, 1991). The EPA 8-hour ozone 

modeling guidance stresses performing corroborative and confirmatory analysis to assure that the 

model is working correctly (EPA, 2007). EPA’s draft 8-hour ozone modeling guidance included 

comparisons of predicted and observed daily maximum ozone concentrations near the monitor 

with a <±20% performance goal (EPA, 1999), however this goal was dropped from the final 

guidance (EPA, 2007). It may still be a useful performance metric and it was used in the Denver 

EAC SIP modeling. In evaluating the ozone and precursor model performance for the Denver 8-

hour ozone modeling, many performance measures and displays will be used to elucidate model 

performance and maximize the probability of uncovering potential problems that can be 

corrected in the final runs. 

1.5.7 Diagnostic and Sensitivity Studies

Rarely does a modeling team find that the first simulation satisfactorily meets all (or even most) 

model performance expectations. Indeed, our experience has been that initial simulations that 

“look very good”, usually do so as the result of compensating errors. The norm is to engage in a 

logical, documented process of model performance improvement wherein a variety of diagnostic 

probing tools and sensitivity testing methods are used to identify, analyze, and then attempt to 

remove the causes of inadequate model performance. This is invariably one of the most 

technically challenging and time consuming phase of a modeling study. Due to the complex 

flows associated with the Denver Front Range meteorology, the CAMx model base case 

simulations will present some performance challenges that may necessitate focused diagnostic 

and sensitivity testing in order for them to be resolved. Below we identify the types of 

diagnostic and sensitivity testing methods that might be employed in diagnosing inadequate 

model performance and devising appropriate methods for improving the model response. 

1.5.7.1 Traditional Sensitivity Testing 

Model sensitivity experiments are useful in three distinct phases or “levels” of an air quality 

modeling study and all will be used as appropriate in the Denver ozone modeling. These levels 

are: 

Level I: Model algorithm evaluation and configuration testing; 

Level II: Model performance testing, uncertainty analysis and compensatory error 

 diagnosis; and 

Level III: Investigation of model output response (e.g., ozone, aerosol, deposition) to 

 changes in precursors as part of emissions control scenario analyses. 

Most of the Level I sensitivity tests with CAMx have already been completed by the model 

developers (e.g., see www.camx.com) and others (e.g., the RPOs). However, given the open 

community nature of the CAMx model, the frequent science updates to the model and supporting 

databases, it is possible that some additional configuration sensitivity testing will be necessary. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-11 

Potential Level II sensitivity analyses might be helpful in accomplishing the following tasks: 

• To reveal internal inconsistencies in the model; 

• To provide a basis for compensatory error analysis; 

• To reveal the parameters (or inputs) that dominate (or do not dominate) the model’s 

operation; 

• To reveal propagation of errors through the model; and 

• To provide guidance for model refinement and data collection programs. 

At this time, it is not possible to identify one or more Level II sensitivity runs that might be 

needed to establish a reliable CAMx base case. The merits of performing Level II sensitivity 

testing will depend upon whether performance problems are encountered in the operational 

evaluation. Also, the number of tests possible, should performance difficulties arise, will be 

limited by resources and schedule. Thus, at this juncture, one cannot be overly prescriptive on 

the number and emphasis of sensitivity runs that may ultimately be desirable. However, from 

past experience with CMAQ, CAMx, UAM and other models, it is possible to identify examples 

of sensitivity runs that could be useful in model performance improvement exercises with the 

CAMx Denver modeling databases. These include: 

• Alternative meteorological realizations of the modeling period; 

• Alternative vertical mixing rates and minimum vertical diffusion coefficient; 

• Alternative (GloBEIS) and for modified biogenic emissions estimates; 

• Modified on-road motor vehicle emissions; 

• Modified air quality model vertical grid structure; 

• Modified boundary conditions; 

• Modified fire emissions; and 

• Modified EGU emissions. 

If desired, Process Analysis outputs can be included in these Level II diagnostic sensitivity 

simulations in order to provide insight into why the model responds in a particular way to each 

input modification. Other “Probing Tools” available in CAMx such as the Decoupled Direct 

Method (DDM) and Ozone Source Apportionment Technology (OSAT) may also be useful 

diagnostic tools to identify model performance issues. Again, the number, complexity, and 

importance of these types of traditional sensitivity simulations can only be determined once the 

initial CAMx base case simulations are executed. 

Level III sensitivity analyses have two main purposes. First, they facilitate the emissions control 

scenario identification and evaluation processes. Today, four complimentary sensitivity 

“Probing Tools” can be used in the CAMx photochemical model: 

• Traditional or “brute force” testing; 

• The Decoupled Direct Method (DDM); 

• Ozone Source Apportionment Technology (OSAT); and 

• Process Analysis (PA). 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-12 

Each method has its strengths and weaknesses and they will be employed where needed and as 

resources are available. The second purpose of Level III sensitivity analyses is to help quantify 

the estimated reliability of the air quality model in simulating the atmosphere’s response to 

significant emissions changes. 

Based on experience in other regional studies, examples of Level III annual sensitivity runs for 

Denver ozone analysis include: 

• Ozone sensitivities to total VOC, NOx, CO and other emissions; 

• Ozone sensitivity to on-road and non-road mobile VOC and NOx emissions; 

• Ozone sensitivities to elevated point source NOx emissions; 

• Ozone sensitivity to emissions due to oil and gas production; and 

• Ozone sensitivity to NOx and VOC emissions from other specific source categories. 

 

The need to perform sensitivity experimentation (Levels I, II, or III) will depend on the outcome 

of the initial Denver ozone operational performance evaluations. If such a need arises, the ability 

to actually carry out selected sensitivity and/or diagnostic experiments will hinge on the 

availability of resources and sufficient time to carry out the analyses. Clearly, selection of the 

specific analysis method will depend upon the nature of the technical question(s) being 

addressed at the time. 

1.5.7.2 Diagnostic Tests 

A rich variety of diagnostic probing tools are available for investigating model performance 

issues and devising appropriate means for improving the model and/or its inputs. In the previous 

section we introduced the suite of “Probing Tools” available for use in the CAMx modeling 

system. Where the need exists (i.e., if performance problems are encountered) and assuming the 

Denver modeling study elects to use probing tool applications, these techniques could be 

employed as appropriate to assist in the model performance improvement efforts associated with 

the Denver ozone base case development. At this time the study has not allocated resources for 

applying the probing tools for the 2006 base case to help diagnose model performance. 

However, there are resources allocated for ozone source apportionment modeling of the 2010 

future-year. 

Below we describe an additional diagnostic method – indicator species and species ratios – that 

is potentially useful not only in model performance improvement activities but also in judging 

the models reliability in estimating the impacts on air quality from future emissions. If, during 

the conducting of the Denver ozone simulations the application of indicator species and species 

ratio techniques would be beneficial to the study, it would be explored for inclusion in the study. 

Beginning in the mid 1990s, considerable interest arose in the calculation of indicator species 

and species ratios as a means of diagnosing photochemical model performance and in assessing 

model credibility in estimating the effects of emissions changes. Major contributions to the 

development and refinement of this general diagnostic method over the past decade have been 

made many scientists including Milford et al., (1994), Sillman (1995, 1999), Sillman et al., 

(1997), Blanchard (2000), Blanchard and Fairley (2001), and Arnold et al., (2003). 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-13 

Recent analytical and numerical modeling studies have demonstrated how the use of ambient 

data and indicator species ratios can be used to corroborate the future year control strategy 

estimates of Eulerian air quality models. Blanchard et al., (1999), for example used data from 

environmental (i.e., smog) chambers and photochemical models to devise a method for 

evaluating the 1-hour ozone predictions of models due to changes in precursor NOx and 

VOC emissions. Reynolds et al., (2003) followed up this analysis, augmented with process 

analysis, to assess the reliability of SAQM photochemical model estimate of 8-hour ozone to 

precursor emissions cutbacks. These researchers used three indicator ratios (or diagnostic 

“probes”) to quantify the model’s response to input changes: 

• The ozone response surface probe [O3/NOx]; 

• The chemical aging probe [NOz/NOy]; and 

• The ozone production efficiency probe [O3/NOz]. 

By closely examining the CMAQ’s response to key input changes, properly focused in time and 

spatial location, Arnold and co-workers (2003) were able to show not only good agreement with 

measurements but also convincingly demonstrated the utility of the method for diagnosing model 

performance in a variety of ways. 

1.5.8 Weight of Evidence Analyses

EPA’s guidance recommends three general types of “weight of evidence” analyses in support of 

the attainment demonstration: (a) use of air quality model output, (b) examination of air quality 

and emissions trends, and (c) the use of corroborative modeling such as observation-based 

(OBM) or observation-driven (OBD) models. Use of these methods in conjunction with the 

CAMx modeling could significantly strengthen the credibility and reliability of the modeling 

available to the states for their subsequent use. The exact details of the weight of evidence 

(WOE) analyses must wait until the Denver ozone modeling study evolves further. It is 

premature to prescribe which, if any of the WOE analyses would be performed since both the 

model’s level of performance for the Denver ozone modeling time and the level of the futureyear projected 8-hour ozone Design Values are not known at this time. EPA requires a WOE 

analysis if the projected maximum future-year 8-hour ozone Design Values lies between 82 and 

87 ppb (EPA, 2007). We believe it is always a good idea to perform WOE analysis to 

corroborate the modeled attainment demonstration. Many of the WOE analyses are independent 

of the photochemical modeling being conducted by the study team and can potentially be 

performed by the project sponsors or interested stakeholders. Below are thoughts regarding what 

would likely be considered as part of the WOE analyses. 

Use of Emissions and Air Quality Trends: Emissions and air quality trend analysis is 

always an important component of a WOE analysis. When combined with 

meteorological analysis of the yearly ozone formation potential, it can be used to 

determine whether actual trends can corroborate the model projected determination of 

whether future-year air quality goals are achieved. 

Use of Corroborative Observational Modeling: While regulatory modeling studies for 

ozone attainment demonstrations have traditionally relied upon photochemical models to 

evaluate ozone control strategies, there has recently been growing emphasis on the use of 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-14 

data-driven models to corroborate the findings of air quality models. As noted, EPA’s 

guidance (EPA, 2007) now encourages the use of such observation-based or observationdriven models (OBMs/ODMs). The merits of using these techniques will be considered 

as supportive weight of evidence. While the OBD/OBM models cannot predict future 

year air quality levels, they do provide useful corroborative information on the extent to 

which ozone formation in specific subregions may be VOC-limited or NOx-limited, for 

example. Information of this type, together with results of DDM, PA and OSAT as well 

as traditional “brute-force” sensitivity simulations, can be extremely helpful in 

postulating emissions control scenarios since it helps focus on which pollutant(s) to 

control. 

Other WOE Analysis: EPA’s 8-hour ozone guidance (EPA, 2007) lists additional 

analysis that can be performed as part of the WOE including analysis of other studies, use 

of alternative models and the calculations of alternative model statistics. The use of all of 

these other techniques will be explored as appropriate. 

1.5.9 Assessing Model Reliability in Estimating the Effects of Emissions Changes

EPA identifies three methods (e.g., EPA, 2001, pg. 228) potentially useful in quantifying a 

model’s reliability in predicting air quality response to changes in model inputs, e.g., emissions. 

These include: 

• Examination of conditions for which substantial changes in (accurately estimated) 

emissions occur; 

• Retrospective modeling, that is, modeling before and after historical significant changes 

in emissions to assess whether the observed air pollution changes are adequately 

simulated; and 

• Use of predicted and observed ratios of “chemical indicator species”. 

We note that in some urban-scale analyses, the use of weekday/weekend information has been 

helpful in assessing the model’s response to emissions changes. Such analysis should be 

examined to determine whether it is appropriate for the Denver area. 

The use of indicator species and ratios offers some promise, and was described earlier in Section 

1.5.7.2. The first two methods have actually been considered for over 15 years and were the 

subject of intensive investigations in the early 1990s in Southern California in studies sponsored 

by the South Coast Air Quality Management District (Tesche, 1991) and the American 

Petroleum Institute (Reynolds et al., 1996). To date, neither method has proven useful largely 

because of the great difficulty in developing historical emissions inventories of sufficient quality 

to make such an analysis credible and the difficulties in removing the influences of different 

meteorological conditions such that the modeling signal reflects only the model’s response to 

emissions changes. It is difficult enough to construct reliable emissions inventories using 

today’s modeling technology let alone construct retrospective inventories 5-10 years ago prior to 

the implementation of significant emissions control programs, major land use changes and 

widespread adoption of Continuous Emissions Monitors. 

The 2004 Denver 8-hour EAC SIP modeling offers a relevant example a retrospective type 

analysis of model performance. The Denver EAC SIP CAMx modeling of the summer of 2002 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-15 

projected that the current (2001-2003) observed maximum 8-hour ozone DV of 87 ppb at the 

Rocky Flats North (RFNO) monitor would be 85 ppb in 2007. With the conclusion of the 

summer 2007 ozone season, the measured 8-hour ozone DV based on the 2005-2007 period at 

RFNO is in fact also 85 ppb. 

1.5.10 Future Year Control Strategy Modeling

Future-year modeling for ozone will be performed for 2010. The Denver area is expected to be 

designated as a Marginal 8-hour ozone nonattainment area by EPA on November 20, 2007 under 

Subpart 2 of the Clean Air Act Amendments (CAAA). 

1.5.11 Future Year Ozone Attainment Demonstration

The Denver modeling results will be used to demonstrate attainment of the 8-hour ozone 

NAAQS. The procedures to be used to demonstrate attainment of the ozone NAAQS will follow 

EPA guidance. Guidance procedures for demonstrating attainment of the 8-hour ozone standard 

has been finalized (EPA, 2007). These procedures use the modeling results in a relative fashion 

to scale the observed 8-hour ozone Design Values using Relative Reduction Factors (RRFs). 

RRFs are the ratio of the future-year to current-year modeling results and are used to scale the 

current-year 8-hour ozone Design Values to project future-year Design Values that are compared 

against the 8-hour ozone NAAQS to determine whether attainment has been demonstrated. EPA 

has developed the Modeled Attainment Test Software (MATS) tool that includes the EPA 

guidance 8-hour ozone DV projection techniques. Section 8 of this Protocol provides more 

details on the 8-hour ozone attainment demonstration modeling approach and details on EPA’s 

new MATS tool can be found at: 

• http://www.epa.gov/scram001/modelingapps_mats.htm

1.6 Project Participants and Contacts 

The Denver Regional Air Quality Council (RAQC) and Colorado Department of Public Health 

and the Environment (CDPHE) Air Pollution Control Division (APCD) are the lead agencies in 

the development of the Denver 8-hour ozone SIP. They will work closely with other local 

agencies, including the Denver Regional Council of Governments (DRCOG) and Colorado 

Department of Transportation (CDOT), and EPA Region 8 in the SIP development, including the 

sharing of interim results as they become available. The Denver RAQC has contracted with a 

modeling team of ENVIRON International Corporation (ENVIRON) and Alpine Geophysics, 

LLC (Alpine) to perform the Denver 8-hour attainment demonstration modeling under the 

direction and with assistance from the RAQC and CDPHE/APCD. RAQC/APCD will also work 

with local agencies and stakeholders in the Denver SIP development, where stakeholders include 

environmental groups and industry. Key participants in the Denver 8-hour ozone study and their 

contact information are provided in Table 1-1. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-16 

Table 1-1. Key participants and contact information for the Denver 8-hour ozone attainment 

demonstration modeling study. 

Organization Individual(s) [Roll] Address Contact Numbers 

U.S. EPA Region 8

Mr. Kevin Golden 

[EPA Contact] 

Regional Meteorologist 

EPA Region VIII 

Denver, CO 

bus: (303) 312-6442 

fax: (303) 312-6064 

e-mail: golden.Kevin@epa.gov

Regional Air Quality Council

Mr. Kenneth Lloyd Executive Director 

1445 Market Street, Suite 260 

Denver, CO 80202 

bus: (303) 629-5450 

fax: (303) 629-5822 

e-mail: klloyd@raqc.org

Mr. Gerald Dilley 

[RAQC Project Manager] 

Technical Program Manager 

1445 Market Street, Suite 260 

Denver, CO 80202 

bus: (303) 629-5450, ext. 240 

fax: (303) 629-5822 

e-mail: jdilley@raqc.org

Colorado Department of Public Health and Environment Air Pollution Control Division

Mr. Kevin Briggs 

[APCD Modeling] 

Air Pollution Control Division 

4300 Cherry Creek Dr. South 

Denver, CO 80222 

bus: (303) 692-3222 

fax: (303) 782-5493 

e-mail: 

krbriggs@smtpgate.dphe.state.co

.us

Mr. Dale Wells 

[APCD Emissions] 

Air Pollution Control Division 

4300 Cherry Creek Dr. South 

Denver, CO 80222 

bus: (303) 692-3237 

fax: (303) 782-5493 

e-mail: 

DMWELLS@SMTPGATE.DPHE.

STATE.CO.US

Colorado Department of Transportation (CDOT)

Ms. Gail Hoffman 

[MPO and Regional 

Planner] 

4201 E. Arkansas 

Shumate Building 

Denver, CO 80222-3406 

bus: (303) 757-9700 

fax: (303) 757-9727 

e-mail:

Gail.Hoffman@dot.state.co.us 

Denver Regional Council of Governments (DRCOG)

Mr. Eric Sabina 1290 Broadway, Suite 700 

Denver, CO 80203-5606 

bus: (303) 480-6789 

fax: (303) 480-6790 

e-mail: esabina@drcog.org 

Contractors (modeling team)

ENVIRON 

International 

Corporation 

Mr. Ralph Morris 

[Project Manager and CoPrincipal Investigator] 

Managing Principal 

773 San Marin Dr., Suite 2115 

Novato, CA 94998 

bus: (415) 899-0708 

fax: (415) 899-0707 

e-mail: rmorris@environcorp.com

Alpine 

Geophysics, 

LLC 

Mr. Dennis McNally 

[Co-Principal Investigator] 

Senior Scientist 

7341 Poppy Way 

Arvada, CO 80007 

bus: (303) 421- 4221 

fax: (303) 421- 9553 

e-mail: 

dem@alpinegeophysics.com

1.7 Communication 

Frequent communication between the RAQC/APCD and EPA, and the modeling team as needed, 

is anticipated. These communications will include e-mails, conference calls and face-to-face 

meetings. The RAQC/APCD envisions that EPA and others will review interim products as they 

become available so that comments can be received during the study to allow for corrective 

action as necessary. These interim deliverables would include, but not be limited to, preliminary 

MM5 evaluation, preliminary current and future-year emissions assumptions and results, 

preliminary CAMx model performance evaluation and preliminary 8-hour ozone projections. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec1_Intro1.doc 1-17 

1.8 Schedule 

Table 1-2 lists the schedule for key deliverables under the Denver 8-hour ozone modeling study. 

We intend to develop a fast track preliminary base case inventory for the June-July 2006 period 

by December 2007. Consequently we will rely on existing information and use the SMOKE 

emissions model for all anthropogenic emission sources. A more refined base case inventory 

will be developed by February 2008 that will include detailed on-road mobile source emissions 

for the DMA using CONCEPT. The schedule is driven by the need to propose an 8-hour ozone 

SIP control plan to the Colorado Air Quality control commission by September 2008. These 

dates will be updated as the study evolves. 

Table 1-2. Key deliverables and dates for the Denver 8-hour ozone attainment demonstration 

modeling study. 

Deliverable (Type) Date 

Preliminary Draft Modeling Protocol (Report) October 23, 2007 

Modeling Protocol Meeting (PPT and Presentation) October 25, 2007 

Draft Modeling Protocol (Report) October 31, 2007 

Initial MM5 36/12/4 km Jun-Jul 2006 Simulation (Inputs) November 30, 2007 

Preliminary Fast Track 3612/4 km Emissions (Inputs) December 19, 2007 

MM5 Sensitivity Tests (Inputs) January 17, 2008 

Initial Run and Preliminary CAMx Sensitivity Tests (PPT) January 24, 2008 

Final MM5 Optimal Configuration Run (PPT) February 15, 2008 

Final 2006 36/12/4 km Actual Emissions Base Case (Inputs) February 22, 2008 

Final CAMx Sensitivity Tests (PPT) February 29, 2008 

Final 2006 36/12/4 km Typical Emissions Base Case (Inputs) March 21, 2008 

Final 2006 36/12/4 km Actual CAMx Base Case Simulation (PPT) March 21, 2008 

Summary Report on Sensitivity Modeling and MPE (Report) April 18, 2008 

2010 36/12/4 km Base Case Emissions (Inputs) April 18, 2008 

2010 CAMx Base Case Simulation and Ozone Projections (PPT) April 30, 2008 

2010 Ozone Source Apportionment Modeling Results (PPT) May 23, 2008 

2010 Emission Reductions Sensitivity Results (PPT) June 13, 2008 

2010 Control Strategy Modeling Results (PPT) August 8, 2008 

Summary Report on 2010 Modeling (Report) August 22, 2008 

Draft Denver SIP Air Quality Technical Support Document (Report) September 12, 2008 

Final Denver SIP Air Quality Technical Support Document (Report) September 26, 2008* 

2020 Emissions and CAMx Modeling Results (PPT) September 30, 2008 

Disk Drives with Model Inputs, Databases, Models and Key Model Outputs 

(Disks) September 30, 2008 

* Assumes comments on draft Air Quality TSD received within one week.

PPT=Power Point Presentation
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-1

2.0 MODEL SELECTION 

This section introduces the models to be used in the Denver 8-hour ozone modeling study. The 

selection methodology presented in this chapter rigorously adheres to EPA’s guidance for 

regulatory modeling in support of ozone attainment demonstrations (EPA, 2007). Unlike 

previous ozone modeling guidance, the agency now recommends that models be selected for SIP 

studies on a “case-by-case” basis with appropriate consideration being given to the candidate 

models’: 

• Technical formulation, capabilities and features; 

• Pertinent peer-review and performance evaluation history; 

• Public availability; and 

• Demonstrated success in similar regulatory applications. 

All of these considerations should be examined for each class of models to be used (e.g., 

emissions, meteorological, and photochemical) in part because EPA no longer recommends a 

specific model or suite of photochemical models for regulatory application as it did sixteen years 

ago (EPA, 1991). After identifying the models we believe are best suited to the requirements of 

the Denver 8-hour ozone SIP modeling study, the justification for their selection is discussed. 

The actual science configurations recommended for each model in this study are introduced in 

Chapter 5. 

EPA’s new guidance on model selection and justification requires a substantial effort to 

document the past evaluation studies, peer-reviews and application efforts associated with the 

models recommended for use. Many of the relevant citations are presented in the References 

section of this protocol. 

2.1 Regulatory Context for Model Selection 

A comprehensive modeling protocol for the Denver 8-hour ozone attainment demonstration 

study consists of many elements. Its main function is to serve as a means for planning and 

communicating how a modeled attainment demonstration will be performed before it occurs 

(EPA, 1999; 2007). The protocol guides the technical details of a modeling study and provides a 

formal framework within which the scientific assumptions, operational details, commitments and 

expectations of the various participants can be set forth explicitly and means for resolution of 

potential differences of technical and policy opinion can be worked out openly and within 

prescribed time and budget constraints. 

The modeling protocols for regulatory applications all too often fall short of providing sufficient 

detail in the description of the modeling assumptions and procedures to be employed (Roth et al., 

2005). They are seldom updated as the modeling program ensues, notwithstanding declarations 

that they are “living documents”. Part of the reason for this is that resource and schedule 

limitations necessitate greater emphasis on performing the modeling studies satisfactorily and on 

time and in addressing unexpected challenges that invariably arise; refining the protocol becomes 

a lower priority. As the cognizant lead agencies, the RAQC/APCD have the responsibility 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-2

for updating relevant portions of this chapter of the protocol as new information is gained 

relative to the suitability of the models recommended for use in the Denver 8-hour ozone 

modeling. 

2.1.1 Summary of Recommended Models 

To develop new 8-hour ozone modeling episodes for the Denver area, the following state-ofscience regional meteorological, emissions and air quality models will be used. The science 

features of these models and the justification for their selection are given later in this section. 

For the Denver 8-hour ozone modeling, we propose to use the MM5/SMOKE-CONCEPTMEGAN/CAMx modeling system. This is almost the same modeling system that is being used 

to address ozone issues in southwest Colorado and northwest New Mexico in the FCAQTF 

study, by the NPS to address nitrogen deposition at RMNP as part of ROMANS and in 

southwest Wyoming for several oil and gas development EISs, and is similar to the 

MM5/EPS3/CAMx modeling systems used in the Denver and several other recent 8-hour ozone 

EAC SIPs that have been approved by EPA (e.g., San Antonio, Austin, Tyler-Longview Texas; 

Tulsa and Oklahoma City, Oklahoma; San Juan New Mexico). 

MM5: The Fifth Generation Pennsylvania State University (PSU) National Center for 

Atmospheric Research (NCAR) Mesoscale Model (MM5) is a nonhydrostatic, prognostic 

meteorological model routinely used for urban- and regional-scale photochemical, fine 

particulate, and regional haze regulatory modeling studies (Dudhia, 1993; Seaman, 2000). 

Developed in the 1970s, the MM5 modeling system maintains its status as a state-of-thescience model through enhancements provided by a broad user community worldwide 

(Stauffer and Seaman, 1990; Xiu and Pleim, 2000; Byun et al., 2005a,b). MM5 is used 

nearly exclusively for regulatory air quality applications in the U.S. In recent years, the 

modeling system has been successfully applied in continental scale annual simulations. 

SMOKE: The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system is 

an emissions modeling system that generates hourly gridded speciated emission inputs of 

mobile, non-road, area, point, fire and biogenic emission sources for photochemical grid 

models (Coats, 1995; Houyoux and Vukovich, 1999). As with most ‘emissions models’, 

SMOKE is principally an emission processing system and not a true emissions modeling 

system in which emissions estimates are simulated from ‘first principles’. This means 

that, with the exception of mobile and biogenic sources, its purpose is to provide an 

efficient, modern tool for converting an existing base emissions inventory data into the 

hourly gridded speciated formatted emission files required by an air quality simulation 

model. SMOKE will be used to prepare emission inputs for non-road mobile, area, point 

and on-road mobile sources outside of the DMA. 

CONCEPT: The Consolidated Community Emissions Processing Tool (CONCEPT) is a 

new emissions modeling system that will be used to generate on-road mobile source 

emissions covered by the link-based Travel Demand Model (TDM) activity data within 

the DMA. The CONCEPT on-road mobile source component can make full use of 

linked-based vehicle miles traveled (VMT) data including temporal and spatial variations 

in speeds and fleet distributions. Details on the CONCEPT emissions model including 

user’s guides, codes and related documentation is available at: 

• http://www.conceptmodel.org
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-3

MEGAN: Biogenic emissions would be modeled using the Model of Emissions of Gases 

and Aerosols from Nature (MEGAN). MEGAN is the latest biogenic emissions model 

developed by researchers from the National Center for Atmospheric Research (NCAR) 

incorporates the full range of ozone and PM precursor species (Guenther and 

Wiedinmyer, 2004). In addition, the latest version of MEGAN includes biogenic species 

not found in other biogenic emissions model that are used by the latest CAMx secondary 

organic aerosol (SOA) module. MEGAN is a fairly new biogenic emissions model so we 

would also generate biogenic emissions using the BEIS algorithms that have been used in 

SIP modeling that would be used in a sensitivity test. Details on the MEGAN biogenic 

emissions model can be found at: 

• http://bai.acd.ucar.edu/Megan/

• http://acd.ucar.edu/~christin/megan1.0_userguide.pdf

CAMx: The Comprehensive Air quality Model with Extensions (CAMx) is a state-ofscience “One-Atmosphere” photochemical grid model capable of addressing ozone, 

particulate matter (PM), visibility and acid deposition at regional scale for periods up to 

one year (ENVIRON, 2006). CAMx is a publicly available open-source computer 

modeling system for the integrated assessment of gaseous and particulate air pollution. 

Built on today’s understanding that air quality issues are complex, interrelated, and reach 

beyond the urban scale, CAMx is designed to (a) simulate air quality over many 

geographic scales, (b) treat a wide variety of inert and chemically active pollutants 

including ozone, inorganic and organic PM2.5 and PM10 and mercury and toxics, (c) 

provide source-receptor, sensitivity, and process analyses and (d) be computationally 

efficient and easy to use. The U.S. EPA has approved the use of CAMx for numerous 

ozone and PM State Implementation Plans throughout the U.S. (including the Denver 8-

hour ozone EAC SIP), and has used this model to evaluate regional mitigation strategies 

including those for most recent regional rules (e.g., CAIR, NOx SIP Call, etc.). 

2.2 Details of the Recommended Models 

Further details of the models we propose for use in the Denver 8-hour ozone modeling effort are 

described below. More information on these models may be obtained from the WRAP, 

VISTAS, CENRAP, and other modeling protocols (Morris et al., 2004a,b; Tesche et al., 2005b) 

and the literature references cited therein. 

2.2.1 The MM5 Meteorological Model

The non-hydrostatic MM5 model (Dudhia, 1993; Grell et al., 1994) is a three-dimensional, 

limited-area, primitive equation, prognostic model that has been used widely in regional air 

quality model applications (Seaman, 2000). The basic model has been under continuous 

development, improvement, testing and open peer-review for more than 20 years (Anthes and 

Warner, 1978; Anthes et al., 1977) and has been used world-wide by hundreds of scientists for a 

variety of mesoscale studies, including cyclogenesis, polar lows, cold-air damming, coastal 

fronts, severe thunderstorms, tropical storms, subtropical easterly jets, mesoscale convective 

complexes, desert mixed layers, urban-scale modeling, air quality studies, frontal weather, lakeeffect snows, sea-breezes, orographically induced flows, and operational mesoscale forecasting. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-4

MM5 is based on the prognostic equations for three-dimensional wind components (u, v, and w), 

temperature (T), water vapor mixing ratio (qv), and the perturbation pressure (p'). Use of a 

constant reference-state pressure increases the accuracy of the calculations in the vicinity of 

steep terrain. The model uses an efficient semi-implicit temporal integration scheme and has a 

nested-grid capability that can use up to ten different domains of arbitrary horizontal and vertical 

resolution. The interfaces of the nested grids can be either one-way or two-way interactive. The 

model is also capable of using a hydrostatic option, if desired, for coarse-grid applications. 

 

MM5 uses a terrain-following non-dimensionalized pressure, or "sigma", vertical coordinate 

similar to that used in many operational and research models. In the non-hydrostatic MM5 

(Dudhia, 1993), the sigma levels are defined according to the initial hydrostatically-balanced 

reference state so that the sigma levels are also time-invariant. The gridded meteorological fields 

produced by MM5 are directly compatible with the input requirements of “one atmosphere” airquality models using this coordinate (e.g., CMAQ and CAMx). MM5 fields can be easily used 

in other regional air quality models with different coordinate systems (e.g., CAMx) by 

performing a vertical interpolation, followed by a mass-conservation re-adjustment. 

Distinct planetary boundary layer (PBL) parameterizations are available for air-quality 

applications, all of which represent sub-grid-scale turbulent fluxes of heat, moisture and 

momentum. These parameterizations employ various surface energy budget equations to 

estimate ground temperature (Tg), based on the insolation, atmospheric path length, water vapor, 

cloud cover and longwave radiation. The surface physical properties of albedo, roughness 

length, moisture availability, emissivity and thermal inertia are either defined as functions of 

land-use for numerous categories via a look-up table, or are provided as input fields from various 

terrestrial and large-scale analysis datasets. 

Initial and lateral boundary conditions are specified from mesoscale three-dimensional analyses 

developed at 3-hour intervals on the outermost grid mesh selected by the user. Additional 

surface fields are also available at three-hour intervals. A Cressman-based technique is used to 

include standard surface and radiosonde observations into the analyses to improve local 

mesoscale representations. The lateral boundary data are introduced into MM5 using a 

relaxation technique applied in the outermost five rows and columns of the most coarse grid 

domain. 

A major feature of the MM5 is its use of state-of-science methods for Four Dimensional Data 

Assimilation (FDDA). The theory underlying this approach and details on how it has been 

applied in a variety of applications throughout the country are described in depth elsewhere 

(Stauffer and Seaman, 1990, 1996; Seaman et al., 1992, 1995, 1996). 

Results of detailed performance evaluations of the MM5 modeling system in regulatory air 

quality application studies have been widely reported in the literature (e.g., Emery et al., 1999; 

Tesche and McNally, 1996b, 1997c, 1999, 2001; Sistla et al., 2001;Nielsen-Gammon, et al., 

2005; Olerud and Sims, 2004a,b) and many have involved comparisons with other prognostic 

models such as RAMS. The MM5 enjoys a far richer application history in regulatory modeling 

studies compared with RAMS or other models. Furthermore, in evaluations of these models in 

over 60 recent regional scale air quality application studies since 1995, it has generally been 

found that MM5 model tends to produce somewhat better photochemical model inputs than 

alternative models (Tesche et al., 2002). 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-5

2.2.2 The Emissions Modeling Systems

Emissions modeling for the Denver 8-hour ozone modeling will be conducted using three 

separate emissions models: MEGAN model for biogenic sources; CONCEPT model for on-road 

mobile sources in the DMA and SMOKE model for everything else. 

2.2.2.1 SMOKE Emissions Modeling System 

SMOKE will be used to perform the emissions modeling for non-road mobile, area and point 

source emissions as well as on-road mobile outside of the DMA. SMOKE has been available 

since 1996, and it has been used for emissions processing in a number of regional air quality 

modeling applications. In 1998 and 1999, SMOKE was redesigned and improved with the 

support of the U.S. Environmental Protection Agency (EPA), for use with EPA's Models3/CMAQ (http://www.epa.gov/asmdnerl/models3) and is currently maintained and available 

from the CMAS center (http://www.cmascenter.org). 

As an emissions processing system, SMOKE has far fewer ‘science configuration’ options 

compared with the MM5 and CAMx models. SMOKE will be configured using the same spatial 

and temporal allocation profiles as used in the WRAP and FCAQTF modeling, updated to local 

conditions as appropriate. 

2.2.2.2 MEGAN Biogenic Emissions Model 

MEGAN will be used to generate VOC and NOx emissions for the 36/12/4 km grid from 

biogenic emission sources. MEGAN generates biogenic emissions using land cover database of 

biomass type and density and hourly meteorological data. NCAR has prepared a global database 

of land use data for use with MEGAN, the MEGAN 

Driving Variable Database (MDVD Version 2.1). Surface temperatures will come from the 

MM5 modeling. 

2.2.2.3 CONCEPT Emissions Modeling 

Although CONCEPT is a complete emissions modeling system for all source categories, we will 

just be using the on-road mobile source component. CONCEPT was developed by ENVIRON 

and Alpine Geophysics and designed to be an open transparent emissions modeling system. The 

on-road mobile of CONCEPT is the most advanced emissions treatment available making full 

use of link-based VMT data. 

2.2.3 The CAMx Regional Photochemical Model

The Comprehensive Air quality Model with Extensions (CAMx) is a publicly available 

(www.camx.com) three-dimensional multi-scale photochemical/aerosol grid modeling system 

that is developed and maintained by ENVIRON International Corporation. CAMx was 

developed with all new code during the late 1990s using modern and modular coding practices. 

This has made the model an ideal platform to treat a variety of air quality issues including ozone, 

particulate matter (PM), visibility, acid deposition, and air toxics. The flexible CAMx 

framework has also made it a convenient and robust host model for the implementation of a 

variety of mass balance and sensitivity analysis techniques including Process Analysis (IRR, 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-6

IPR, and CPA), Decoupled Direct Method (DDM), and the Ozone/PM Source Apportionment 

Technology (OSAT/PSAT). Designed originally to address multiscale ozone issues 

from the urban- to regional-scale, CAMx has been widely used in recent years by a variety 

regulatory agencies for 1-hour and 8-hour ozone SIP modeling studies. Key attributes of the 

CAMx model for simulating gas-phase chemistry include the following: 

• Two-way grid nesting that supports multiple levels of fully interactive grid nesting (e.g., 

36/12/4/1.33 km); 

• CB05, CB4 or SAPRC99 chemical mechanisms; 

• Two chemical solvers, the CAMx Chemical Mechanism Compiler (CMC) Fast Solver or 

the highly accurate Implicit Explicit Hybrid (IEH) solver; 

• Multiple numerical algorithms for horizontal transport including the Piecewise Parabolic 

Method (PPM) and Bott advection solvers; 

• Subgrid-scale Plume-in-Grid (PiG) algorithm to treat the near-source plume dynamics 

and chemistry from NOx, VOC SOx, and/or PM point source plumes; 

• Ability to interface with a variety of meteorological models including the MM5, WRF 

and RAMS prognostic hydrostatic meteorological models and the CALMET diagnostic 

meteorological model (others also compatible); 

• The Ozone Source Apportionment Technology (OSAT) and PM Source Apportionment 

Technology (PSAT) that identifies the ozone or PM contribution due to geographic 

source regions and source categories (e.g., mobile, point, biogenic, etc.); and 

• The Decoupled Direct Method (DDM) sensitivity method is implemented for emissions 

and IC/BC to obtain first-order sensitivity coefficients for all gas-phase and particlephase species. 

Culminating from extensive model development efforts at ENVIRON and other participating 

groups, the CAMx Versions 4.5 will be released in 2007 as a truly “One-Atmosphere” model 

that rigorously integrates the gas-phase ozone chemistry with the simulation of primary and 

secondary fine and coarse aerosols. This extension of CAMx to treat PM involved the addition 

of several science modules to represent important physical processes for aerosols. Noteworthy 

among these are: 

• Two separate treatments of PM: Mechanism 4 (CF) uses two static size sections and 

science modules comparable to CMAQ (e.g., RADM aqueous-phase chemistry and 

ISORROPIA equilibrium); and Mechanism 4 (CMU) uses a multi-section “full-science” 

approach using aerosol modules developed at Carnegie Mellon University (CMU). 

• The size distribution in the CMU approach is represented using the Multi-component 

Aerosol Dynamics Model (MADM), which uses a sectional approach to represent the 

aerosol particle size distribution (Pilinis et al., 2000). MADM treats the effects of 

condensation/evaporation, coagulation and nucleation upon the particle size distribution. 

• Inorganic aerosol thermodynamics can be represented using ISORROPIA (Nenes et al, 

1998; 1999) equilibrium approach within MADM, or a fully dynamic or hybrid approach 

can also be used. 

• Secondary organic aerosol thermodynamics are represented using the semi-volatile 

scheme of Strader and co-workers (1999). 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-7

• Aqueous-phase chemical reactions are modeled either using the RADM module (like 

CMAQ) or the Variable Size-Resolution Model (VRSM) of Fahey and Pandis (2001), 

which automatically determines whether water droplets can be represented by a single 

“bulk” droplet-size mode or whether it is necessary to use fine and coarse droplet-size 

modes to account for the different pH effects on sulfate formation. 

• The PM Source Apportionment Technology (PSAT) “Probing Tool” can separately track 

PM source apportionment for SO4/NO3/NH4, SOA, Primary PM and Hg families of 

tracers. 

In 2007 ENVIRON is releasing CAMx v4.5 that will be the most current version of CAMx 

available on the website (www.camx.com). Version 4.5 includes several improvements geared 

mainly toward improved PM simulations over earlier versions including updates to the SOA 

module to include SOA from isoprene and sesquiterpene emissions from the MEGAN biogenic 

emissions model. 

2.3 Justification for Model Selection 

2.3.1 MM5 

The most commonly used prognostic meteorological models to support air quality modeling are 

the MM5 and the Regional Atmospheric Modeling System (RAMS). The new Weather 

Research Forecast (WRF) model shows promise as a meteorological driver for air quality 

models, but it needs further demonstration before it can be used in a regulatory modeling study. 

A number of recent studies inter-compare the theoretical formulations and operational features of 

the MM5 and RAMS models and evaluate their performance capabilities under a range of 

atmospheric conditions. There have also been a number of studies involving “side-by-side” 

comparative performance evaluations of MM5 and RAMS for the OTAG and LMOS episodes. 

Consistent with these evaluation studies, the MM5 is recommended as the prognostic 

meteorological modeling component for the Denver ozone study for the following reasons: 

• All of the available state-of-science regional photochemical models identified in 

EPA’s 8-hour modeling guidance can be operated without difficulty using inputs 

supplied by the MM5; however, some ozone models such as MAQSIP and Models3/CMAQ cannot be run easily with the RAMS polar stereographic map projection. In 

some cases, costly software development would be needed to allow this coupling 

between RAMS and certain air quality models. 

• In recent scientific model inter-comparisons examining over sixty air quality 

applications across the country, the MM5 model was found to perform somewhat 

better than RAMS, particularly for surface and aloft winds and surface temperatures. 

• The MM5 model has a far richer application history in regulatory ozone modeling 

studies compared with RAMS. While RAM’s principal air quality applications have 

been in OTAG and SAMI, the MM5 has been employed in a much wider range of 

regional studies including CAIR, CAMR, SAMI, NARSTO, SARMAP, SCOS, 

SCAQS, VISTAS, MANE-VU, CENRAP, MRPO, and WRAP as well as in a number 

of urban-scale SIP applications (e.g., Pittsburgh, Cincinnati, San Juan, Kansas City, 

St. Louis, Denver, Tulsa, Houston, Dallas, Central California, Phoenix, Boise, etc.). 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-8

• While MM5 and RAMS meteorological models have been used for air quality 

modeling in different urban and regional-scale studies, in most regulatory ozone 

applications the MM5 model has been the preferred system. 

2.3.2 Emissions Models

The MEGAN, CONCEPT and SMOKE emissions modeling systems are the recommended 

emissions models for the Denver 8-hour ozone modeling study for the following reasons: 

• MEGAN is the latest biogenic emissions model and incorporates the latest scientific 

knowledge. It also includes biogenic precursor emissions to support the new SOA 

module in CAMx. It has been tested for a variety of applications including the 

FCAQTF . 

• CONCEPT will be used for modeling on-road mobile sources. It is the most 

advanced link-based on-road emissions modeling system that has been extensively 

tested using 19 link-based networks in the Midwest as well as Las Vegas. This is in 

contrast to the SMOKE link-based module that has only been used once (by 

ENVIRON for the St. Louis 8-hour ozone SIP) which requires constant vehicle 

speeds and fleet mixes across all links. 

• The SMOKE emissions model has been operational for over a decade and is fully 

supported by the EPA through the CMAS Center (www.cmascenter.org). It is the 

most computationally efficient of the emissions models and is being used by WRAP 

and the FCAQTF. 

2.3.3 CAMx 

 

During the NARSTO Critical Tropospheric Ozone Assessment, two major reviews of 

photochemical modeling were performed. Russell and Dennis (2000) compared the scientific 

and operational features of essentially all current recent Eulerian photochemical models in use up 

to that time. In parallel, Roth et al. (1998, 2005) reviewed more than twenty regulatory 

applications of photochemical models in the U.S. and Canada. From these reviews, and the 

modeling team’s experience with each of these models, we recommend CAMx as the ozone 

modeling tool for the Denver study for the following reasons: 

• CAMx is a state-of-science “one-atmosphere” model; 

• CAMx has undergone extensive successful testing by a variety of groups for nearly a 

decade. 

• CAMx is unique among state-of-science “one-atmosphere” air quality models in its 

ability to offer ozone and particulate source apportionment technology (OSAT, 

PSAT), Process Analysis, and the DDM sensitivity analysis scheme. 

• CAMx has been used extensively for numerous recent 8-hour ozone SIPs including 

Denver, Oklahoma, St. Louis, and areas in Texas and other regulatory modeling 

including the EPA to support for regulatory decision making (e.g., CAIR, NOx SIP 

Call, etc.). 

• CAMx is a public-domain model, available free of charge, without restriction 

(www.camx.com).
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-9

2.4 Model Limitations 

All mathematical models possess inherent limitations owing to the necessary simplifications and 

approximations made in formulating the governing equations, implementing them for numerical 

solution on fast computers, and in supplying them with input data sets and parameters that are 

themselves approximations of the full state of the atmosphere and emission processes. Below, 

we list the more important limitations of the various modeling systems to be employed in the 

Denver 8-hour ozone study. 

2.4.1 MM5

In VISTAS (Morris et al., 2004a,b), four different configurations of the MM5 Land Soil Model 

(LSM) and Planetary Boundary Layer (PBL) were evaluated. Depending on the meteorological 

variable (e.g., winds, temperature, moisture) and location (e.g., mountains, coastal, east, west), 

different LSM_PBL configurations performed better. For VISTAS, the Pleim-Xiu PBL scheme 

(Xiu and Pleim, 2000) was selected because it was consistently the top performing configuration 

across the VISTAS domain. However, detailed research in Houston by UH/IMAQS (Byun et al., 

2005a,b) have revealed that their modified MRF PBL scheme appears to better match the local 

meteorological conditions of their study region. The proper treatment of vertical turbulent 

mixing and the estimate of the PBL heights are among the important current science limitations 

in the model. 

2.4.2 SMOKE

All emissions modeling systems have uncertainties and limitations. Foremost among these are 

the initial emissions estimates provided as input to the emissions models. However, even with 

exact emission estimates as inputs (an unlikely event) the emissions models still have numerous 

limitations just because of the shear volume of data that needs to be characterized and processed 

and the limited amount of data available to make the characterization: 

Spatial Allocation: Emissions modeling system use surrogate distributions to spatially 

distribute county-level emissions. For example agricultural land use category would be 

used to spatially distribute agricultural equipment emissions, population may be used for 

a variety of home related emissions (e.g., home heating, aerosol sprays, etc.). The 

accuracy of these surrogate distributions will likely vary by source category. 

Temporal Allocation: The allocation of annual average emissions to months and across 

the diurnal cycle use typical distributions by source category. The accuracy of these 

temporal allocations varies by source type within broader categories (e.g., heavy-duty 

diesel vs. light duty gas within the on-road category). They may also vary over different 

days. For example, a typical temporal distribution for a Sunday may be quite different on 

days when the Denver Broncos are in town. 

Chemical Speciation: Emission models need to chemically speciate the VOC emissions 

into the photochemical mechanism (e.g., CB4) used in the photochemical grid model 

based on industrial codes. There are actually a limited number of speciation profiles and 

individual source tests have not been conducted for all different types of sources; 

consequently speciation profiles are assigned to “similar” sources that have source profile 

measurements. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-10

Emission Projections: Projecting emissions introduce the largest layer of uncertainty. 

Emission projections include growing emissions from a current (e.g., 2006) to future 

(e.g., 2010 and 2020) year and then the application of any appropriate controls. Both of 

these steps are characterized by potentially huge limitations. 

2.4.3 CAMx 

Like all air quality models, there are a number of conceptual, physical, chemical, computational 

and operational challenges that CAMx model developers and the user community face to one 

extent or another. One current limitation is the treatment of vertical turbulent mixing where 

there are alternative means for estimating the time and space variation in turbulent mixing. 

Another common drawback of CAMx is the extensive emissions, meteorological and IC/BC 

inputs needed to operate the model. Treatment of clouds and wet deposition is an area of current 

research that needs to be updated. A practical limitation of CAMx is the computational 

requirements, including the need of significant disk space. 

None of the current limitations identified in the MM5, SMOKE/CONCEPT/MEGAN and CAMx 

models render any of these models inappropriate for their use in this study, and are in fact 

common to all current models available for this type of application. However, such limitations 

need to be recognized and accounted for in the interpretation of the modeling results. 

2.5 Model Input Requirements 

Each of the modeling system components has significant data base requirements. These data 

needs fall into two categories: those required for model setup and operation, and those required 

for model evaluation and testing. Below, we identify the main input data base requirements for 

the meteorological, emissions, and air quality models. Details on the sources of the required data 

and how they will be used to construct model inputs are discussed in Chapter 5. 

2.5.1 MM5

The databases required to set up, exercise, and evaluate the MM5 model consists of various fixed 

and variable inputs including: (a) topography, (b) vegetation type, (c) land use, (d) atmospheric 

data, (e) water temperature, (f) clouds and precipitation; and (g) multi-Scale FDDA data. Much 

of this data is available from the NCAR website. 

2.5.2 Emissions

The databases required to set up and operate SMOKE for the Denver non-road, area and point 

source emissions modeling are as follows (a) area source emissions in IDA format, (b) non-road 

mobile source emissions in IDA format, (c) stationary point source emissions in IDA format, (d) 

CEM emissions, day specific, and (e) wildfire emissions, day specific. Also required are data 

files specific for temporal allocation, spatial allocation, and chemical speciation. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 2-11

To operate the CONCEPT model for on-road mobile sources emissions in the DMA we need 

2006, 2010 and 2020 link-based VMT data with temporal and spatial variations in speeds and 

fleet mix and MOBILE6 inputs for the three years and local fuel characteristics. We also need 

the fraction of counties covered by the TDM link-based data. For outside of the DMA 

we need county-level 2006, 2010 and 2020 VMT data and appropriate MOBILE6 inputs. We 

also need meteorological data, which would come from MM5. 

For the MEGAN biogenic emissions modeling detailed land cover data is needed to characterize 

biomass type and density and hourly meteorological data (MM5). 

2.5.3 CAMx 

Major CAMx model inputs include: (a) three-dimensional hourly meteorological fields generated 

by MM5 via the MM5CAMx interface tool, (b) three-dimensional hourly emissions generated by 

SMOKE/CONCEPT/MEGAN, (c) initial conditions and boundary conditions (IC/BC), (d) 

photolysis rates look up table, (e) albedo/haze/ozone Column input file, and (f) land use. 

2.6 Summary of Model Selection and Justification 

In summary, the MM5, SMOKE/CONCEPT/MEGAN and CAMx regional models are 

recommended for use in the Denver 8-hour ozone modeling study. In this chapter, we have 

introduced the models in the context of the current state-of-science in emissions, meteorological, 

and photochemical modeling and have provided brief technical summaries of each one. In 

addition, we have presented the rationale underpinning the selection of this specific suite of 

models for the Denver 8-hour ozone photochemical modeling study. 

We conclude the model selection discussion by presenting in Tables 2-1 through 2-4 the six (6) 

criteria set forth in EPA’s draft 8-hour modeling guidance (EPA, 2005a; 2007) for determining 

whether a candidate model is appropriate for use in an ozone attainment demonstration study. 

Associated with each of the six criteria are the reasons why we believe the three models selected 

are indeed suitable candidates for this application. Tables 2-5 through 2-8 list the five (5) criteria 

that EPA has established for actually justifying the use of a model in the proposed study. 

Collectively, the information presented in Tables 2-1 though 2-8 supports our recommendation 

that the MM5, SMOKE/CONCEPT/MEGAN and CAMx models are logical choices given the 

specific technical, regulatory, schedule and resource aspects of the Denver 8-hour ozone 

modeling study. 

2.7 Availability of Model Codes, Analysis Tools and Related Software 

 The source codes, user’s guides, analysis tools, documentation and related software for 

all models used in this study are publicly available. These models and their pre- and postprocessor programs and test data bases may be obtained from the following websites: 

MM5: http://www.mmm.ucar.edu/mm5/overview.html

SMOKE: http://www.cmascenter.org

CONCEPT: http://www.conceptmodel.org

MEGAN: http://bai.acd.ucar.edu/Megan/

CAMx: http://www.camx.com
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 

Table 2-1. Factors qualifying MM5 for use in the Denver 8-hour ozone modeling study. 

Consideration QualificationThe model has received a scientific peer review. 

Formal scientific reviews of the MM5 model have been widely carried out in the U.S. and abExamples include Pielke (1984); Emery et al., (1999, 2001); Barchet and Dennis (1990); TesPielke and Pierce (1994); and Seaman (1995, 2000, 2005). More than one hundred governand private modeling groups in the U.S. and abroad have reviewed the model code as part oexercise, and quality assurance activities. 

The model can be demonstrated to be applicable to the problem on a theoretical basis. 

By design, MM5 explicitly or implicitly represents the various physical and microphysical pro

prediction of mesoscale atmospheric phenomena. The model has been used world-wide by variety of mesoscale studies, including cyclogenesis, polar lows, cold-air damming, coastal f

tropical storms, subtropical easterly jets, mesoscale convective complexes, desert mixed layair quality studies, frontal weather, lake-effect snows, sea-breezes, orographically induced flmesoscale forecasting. The features and capabilities of the MM5 modeling system are consa combined urban- and regional-scale, as required in the Denver study. 

Date bases needed to perform the analysis are available and adequate. 

The surface and upper air meteorological data required to exercise and evaluate MM5 are aNational Weather Service. Large-scale databases needed for model initialization and boundfrom the National Center for Environmental Prediction (NCEP) and the National Center for A(NCAR). These data sets include surface and aloft wind speed, wind direction, temperatureHourly surface data for model evaluation are available from many “Class I” airports, i.e., largairports operating 24-hour per day. The standard set of upper air data are provided by rawinby the NWS every 12 hours from numerous sites across the continent. In addition, NOAA/Nhourly RADAR profiler sites that report upper-air meteorological measurements at approximcentral U.S. Model inputs will be prepared following the guidelines recommended by the moadequacy of the input data bases will be assessed as part of the MM5 model performance e

Available past appropriate performance evaluations have shown the model is not biased toward underprediction. 

A number of studies have examined the theoretical formulation and operational features of tKuo, 1998; Seaman, 1995, 1996; Pielke and Pearce, 1994), the performance of the model uconditions (e.g., Cox et al., 1998; Hanna et. al., 1998; Seaman et al., 1992, 1995, 1996), anmodel when compared with other models (e.g., RAMS) for various regional modeling episodLMOS episodes (Tesche and McNally, 1996b; Tesche et. al., 1997a; Tesche et al., 1999a). bias in the model’s estimates of state variables has been encountered. MM5 is one of two sprognostic meteorological models actively used in the U.S. and abroad as input to regional pemissions models. The MM5 model has been used extensively in the Denver and nearby aROMANS study and FCAQTF modeling. 

A protocol on methods and procedures to be followed has been established. 

The protocol is outlined in this document. The MM5 modeling will be performed in a manneestablished practice and EPA guidelines regarding air quality modeling related to the 8-hr oz

The developer of the model must be willing to make the source code available to users for free or for a reasonable cost, and the model cannot otherwise be proprietary. 

MM5 has been in the public domain since its original development in the early 1980s. Free user’s guide, and test model inputs can be obtained from the National Center for AtmospherPennsylvania State University, and the U.S. EPA Office of Research and Development. Comodel applications and evaluation software are available from various governmental agenciResources Board), academic institutions, National Laboratories and consulting firms. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 

Table 2-2. Factors qualifying SMOKE, CONCEPT and MEGAN emissions models for use in the Denver ozone mod

 Consideration QualificationThe model has received scientific peer review. 

A formal scientific review of the SMOKE modeling system has been continuous since its firsbeing performed as part of the CMAS Center operations (www.cmascenter.org). Numerous and private modeling groups in the U.S. and abroad have engaged in ongoing review, testinSMOKE model code as part of training, model set-up, exercise, and quality assurance activihave performed extensive testing and peer-review of the SMOKE modeling system and the training on its use. The CONCEPT emissions model is in the process of undergoing a more detailed review. Thcomponent of CONCEPT to be used in the Denver study has undergone detailed testing an19 link-based networks in the Midwest and Las Vegas. The MEGAN biogenic emissions model has undergone extensive testing and peer review siScientists at ENVIRON and Alpine have reviewed the code. 

The model can be demonstrated to be applicable to the problem on a theoretical basis. 

The SMOKE and CONCEPT emissions modeling systems were explicitly designed to treat aanthropogenic and biogenic emissions source in a modeling framework suitable for input to photochemical dispersion models. The model provides hourly resolved, gridded, chemically category specific emissions estimates for the important known precursors of photochemicalland CONCEPT are two of the four state-of-science regional emissions models actively used (others are EMS and EPS). The features and capabilities of the SMOKE and CONCEPT mo

with the application on a combined urban- and regional-scale, as required in the Denver momodel represents the most up-to-date and advanced biogenic emissions modeling system abiogenic emissions model that provides sufficient information for the advanced SOA module 

Date bases needed to perform the analysis are available and adequate. 

Key input data bases to the SMOKE, CONCEPT and MEGAN emissions modeling systems vehicle sources plus biogenic sources) are available from the CDPHE/APCD, EPA and WRAprepared following published User’s Guidelines, the development of the APCD, WRAP, CENinventories, and those used by EPA in the development of the CAIR modeling. The adequadeveloped by these various sources will be assessed as part of the emissions QA process. 

Available past appropriate performance evaluations have shown the model is not biased toward underprediction. 

There are very limited data sets with which to verify emissions models. Major point source ecommonly based on continuous emissions monitoring (CEM). On road motor vehicle emissthe EPA MOBILE6. Non-road mobile sources emissions are based on EPA’s NONROAD mo

A protocol on methods and procedures to be followed has been established. 

The protocol is outlined in this document. The SMOKE, CONCEPT and MEGAN emissions a manner that is consistent with established practice and EPA guidelines regarding air qualitozone standard. 

The developer of the model must be willing to make the source code available to users for free or for a reasonable cost, and the model cannot otherwise be proprietary. 

SMOKE, CONCEPT and MEGAN emission models are all in the public domain and can be dSMOKE: http://www.cmascenter.org

CONCEPT: http://www.conceptmodel.orgMEGAN: http://bai.acd.ucar.edu/Megan/
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 

Table 2-3 Factors qualifying CAMx as the photochemical grid model for use in the Denver ozone modeling study. 

 Consideration QualificationThe model can be demonstrated to be applicable to the problem on a theoretical basis. 

The CAMx modeling system represents either explicitly or implicitly the physical and chemiccurrently known to influence the formation and transport of ozone as well as the emissions, dispersion of ozone precursor pollutants. The features and capabilities of the CAMx modelithe application on a combined urban- and regional-scale, as required in the Denver study. 

Date bases needed to perform the analysis are available and adequate. 

The CAMx modeling system requires several different types of input data including land usemeteorological, and demographic. All of these data sets are routinely available from state oinputs will be prepared following EPA guidelines and the adequacy of the input data bases wthe CAMx model performance evaluation. 

Available past appropriate performance evaluations have shown the model is not biased toward underprediction. 

The CAMx modeling system has undergone extensive third party review and performance tevaluations and applications. Examples of recent model performance evaluations with CAMsection. Collectively, these evaluation studies do not reveal the presence of significant, une

bias for ground-level ozone concentrations. 

A protocol on methods and procedures to be followed has been established. 

The protocol is outlined in this document. The CAMx modeling will be performed in a mannestablished practice and EPA guidelines regarding air quality modeling related to the 8-hr o

The developer of the model must be willing to make the source code available to users for free or for a reasonable cost, and the model cannot otherwise be proprietary. 

CAMx has been in the public domain since its original development in the mid 1990s. Free user’s guide, and test model inputs can be obtained from the model developer’s website at 

ancillary data sets and model applications and evaluation software are available not only fro(ENVIRON International) but also from various governmental agencies (e.g., TCEQ), acadeconsulting firms. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 

Table 2-4. Factors justifying MM5 as the meteorological model for the Denver ozone modeling study.

Consideration QualificationNature of air quality problem leading to non-attainment of the ozone NAAQS should first be assessed, and the selected model should have the attributes and capabilities consistent with the perceived nature of the problem. 

The MM5 modeling system is expected to allow a physically realistic, dynamically consistencirculations over the Denver study area as well as other mesoscale features including convconvection, complex terrain effects and so on. The nested grid feature of MM5 will directly 

regional-scale nesting schemes in CAMx. 

Availability, documentation and past performance should be satisfactory. 

The MM5 modeling system is publicly available and has been regularly used in support of Cacross the country. It has also been successfully used for several air quality studies in the 

SCOS, and SARMAP studies. It has been used in 1-hr ozone attainment demonstrations in Valley and Cincinnati-Hamilton areas, numerous 8-hr ozone EAC studies (e.g., Denver/NorKansas City/Missouri region). MM5 is the model used in all of the RPO studies currently beHaze. Versions of the MM5 have been used for the past 20 years in support of a variety of projects. Results of numerous model evaluation studies with the MM5 reveal that the modethan any other mesoscale, applications-oriented, public domain model (Seaman, 2000, 200

Relevant experience of available staff and contractors should be consistent with choice of a model. 

The MM5 modeling will be performed by ENVIRON who are thoroughly knowledgeable of tmesoscale research applications as well as in regulatory photochemical modeling studies. 

Time and resource constraints may be considered. 

Use of the MM5 model is consistent with the Denver 8-hour ozone SIP development sched

Consistency of the model with what was used in adjacent regional applications should be considered. 

MM5 has been applied in several photochemical modeling studies (e.g., Denver EAC studyEvaluation Study in Lower Lake Michigan, the SARMAP study in California, various stakehthe OTAG, EPA NOx SIP Call, and EPA Tier II/Sulfur modeling analyses, the Pittsburgh-BeCincinnati-Hamilton SIP, and in a half dozen other regional ozone modeling studies.) The sapplied in the Peninsular Florida 8-hr Ozone Study, the Kansas City/Missouri 8-hr ozone mozone studies in Missouri, Texas and Oklahoma. MM5 was also recently used for regionalsoutheastern U.S., with emphasis on Atlanta, Birmingham, and the eastern Gulf Coast. It wOzone Study and ATMOS. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 

Table 2-5. Factors justifying SMOKE/CONCEPT/MEGAN as the emissions model for the Denver ozone modeling 

Consideration QualificationNature of air quality problem leading to non-attainment of the ozone NAAQS should first be assessed, and the selected model should have the attributes and capabilities consistent with the perceived nature of the problem. 

SMOKE/CONCEPT/MEGAN were designed for the preparation of detailed urban- and regiomodeling inventories such as is required for the Denver study. CONCEPT emissions modeaccurate and detailed representation of on-road mobile sources ever. MEGAN is the most biogenic emissions model. SMOKE has been used extensively by the RPOs and others fostudies. 

Availability, documentation and past performance should be satisfactory. 

SMOKE, CONCEPT, MEGAN and MOBILE6.2 are publicly available at no charge. One or been successfully used in a variety of regional modeling studies including 1-hour ozone atthour ozone EAC SIPs, OTAG, SAMI, the EPA NOx SIP Call, CAIR, CAMR and CAVR. 

Relevant experience of available staff and contractors should be consistent with choice of a model. 

The emissions modeling tasks for the Denver study will be performed by ENVIRON and Alpexperience in using these models and are the developers of CONCEPT. 

Time and resource constraints may be considered. Use of the SMOKE, CONCEPT, MEGAN and MOBILE6.2 models is consistent with the DeConsistency of the model with what was used in adjacent regional applications should be considered. 

SMOKE, CONCEPT, MEGAN, and MOBILE6.2 models (or their predecessors) have been photochemical modeling studies in adjacent areas including the FCAQTF, WRAP, ROMANBLM EIS photochemical modeling. 
F:\Denver_O3_2008\Protocol\draft#2\Sec2_Models1.doc 

Table 2-6. Factors justifying CAMx as the photochemical model for the Denver ozone modeling study.

Consideration QualificationNature of air quality problem leading to non-attainment of the ozone NAAQS should first be assessed, and the selected model should have the attributes and capabilities consistent with the perceived nature of the problem. 

Based on an analysis of the observed 1-hr and 8-hr ozone data and review of climatological dDenver, the potential 8-hr ozone nonattainment problems in the region include both regional acomponents and are usually strongly influenced by the complex meteorology of the Front RaThe CAMx photochemical modeling system is well suited for this application in that its urban- scale grid nesting scheme appropriately addresses the various time and space scales relevamesoscale processes involved in 8-hr ozone episodes. Utilizing meteorological inputs from a prognostic model (MM5), CAMx can directly simulate the local processes involved in 8-hr ozotogether with the influence of imported ozone and precursor species from upwind (regional-scregions. The use of detailed meteorological inputs and grid nesting will allow proper treatmencomplex terrain circulations (e.g., upslope/downslope), convective circulations, vertical mixing processes. The process-analysis, ozone source apportionment, and direct decoupled sensitialgorithms (DDM) in CAMx can allow a more rigorous evaluation of model performance and aanalysis. 

Availability, documentation and past performance should be satisfactory. 

The CAMx modeling system is publicly available at no cost. Full user documentation can be the website: www.camx.com. The CAMx model has been widely evaluated by numerous gro

The model has undergone extensive successful testing by a variety of groups (see, for examand Kumar, 1997; McNally and Tesche, 1998a, McNally et al., 1998a-c; Tesche and McNallyet al., 1998c,e,f). Model performance for ozone has consistently been comparable to or betteother contemporary model such as the CMAQ, UAM-V, SAQM, and URM. 

Relevant experience of available staff and contractors should be consistent with choice of a model. 

The CAMx modeling will be performed by ENVIRON, who developed the CAMx model, and Ahave extensive experience in its application. 

Time and resource constraints may be considered. Use of the CAMx model is consistent with the Denver 8-hour ozone project schedule. Consistency of the model with what was used in adjacent regional applications should be considered. 

CAMx has or is being applied in several recent nearby photochemical modeling studies includEAC SIP, FCAQTF, WRAP, ROMANS, and BLM EIS modeling. 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-1 

3.0 EPISODE SELECTION 

3.1 Overview of EPA Guidance 

EPA 8-hour modeling guidance (EPA, 2007) contains recommendations for selecting modeling 

episodes, while also referencing EPA’s 1-hour ozone modeling guidance for episode selection 

(EPA, 1991). 

3.1.1 Primary Criteria

EPA’s guidance on 8-hour ozone modeling (EPA, 2007) identifies specific criteria to consider 

when selecting one or more episodes for use in demonstrating attainment of the 8-hour ozone 

National Ambient Air Quality Standard (NAAQS). The 8-hour ozone guidance builds off the 1-

hour ozone guidance in selecting multiple episodes representing diverse meteorological 

conditions that result in ozone exceedances in the region under study, and includes the following 

criteria: 

• A variety of meteorological conditions should be covered, including the types of 

meteorological conditions that produce 8-hour ozone exceedances in the Denver area; 

• Choose episodes having days with monitored 8-hour daily maximum ozone 

concentrations close to the observed fourth highest value; 

• To the extent possible, the modeling data base should include days for which extensive 

data bases (i.e. beyond routine aerometric and emissions monitoring) are available; and 

• Sufficient days should be available such that relative response factors (RRFs) can be 

based on several (i.e., > 10) days with at least 5 days being the absolute minimum. 

3.1.2 Secondary Criteria

EPA also lists several “other considerations” to bear in mind when choosing potential 8-hour 

ozone episodes including: 

• Choose periods which have already been modeled; 

• Choose periods that are drawn from the years upon which the current Design Values 

are based; 

• Include weekend days among those chosen; and 

• Choose modeling periods that meet as many episode selection criteria as possible in 

the maximum number of nonattainment areas as possible. 

EPA suggests that modeling an entire summer ozone season would be a good way to assure that 

a variety of meteorological conditions are captured and that sufficient days are available to 

construct robust RRFs for the 8-hour ozone Design Value projections. 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-2 

3.2 Selection of Denver 8-hour Ozone Modeling Episode(s) 

Measured ozone air quality data in the Denver area from the 2002 to 2007 six year period were 

analyzed to determine an optimal modeling period for performing 8-hour ozone Design Value 

projections for the 2010 future-year. 

3.2.1 Key Denver Ozone Monitors

Table 3-1 displays the fourth highest 8-hour ozone concentrations at monitors in the Denver area 

for the years 2005 through 2007 and the 2005-2007 8-hour ozone Design Values (DVs). 

Locations of these monitors are given in Figures 4-1e and 4-2 and Table 4-5. The Rocky Flats 

North (RFNO) monitor to the northwest of downtown Denver has a 2005-2007 8-hour ozone 

Design Value (DV) of 85 ppb that exceeds the ozone NAAQS (85 ppb or higher). Observations 

from this monitor are why EPA is expected to designate the Denver area as an ozone 

nonattainment area in November 2007. The next highest 8-hour ozone DV is 84 at the Chatfield 

(CHAT) site south of Denver followed by NREL (82 ppb) west of downtown Denver and South 

Boulder Creek site (SBC; 81 ppb) that is a little further northwest of downtown Denver than 

RFNO. Although it only has two years of monitoring data so a valid three-year 8-hour ozone 

Design Value cannot be constructed, the Fort Collins West (FTCW) site is also recording high 

ozone levels and the average of the fourth highest 8-hour ozone over two years (2006-2007) of 

monitoring is 86 ppb that exceeds the NAAQS. Thus any future ozone air quality planning 

should also consider the FTCW monitoring site in the analysis. 

Table 3-1. Fourth highest daily maximum 8-hour ozone concentrations (ppm) at monitoring 

sites in the Denver area during 2005, 2006 and 2007 and 2005-2007 8-hour ozone Design 

Values. 

Site Name 

2005

4th Maximum 

8-Hour Average 

Value (ppm) 

2006

4th Maximum 

8-Hour Average 

Value (ppm) 

2007 (thru 8/31)

4th Maximum 

8-Hour Average 

Value (ppm) 

2005 - 2007 

3-Year Average 

4th Maximum 

Value (ppm) 

Welby 0.073 0.069 0.070 0.070 

Highland 0.080 0.081 0.075 0.078 

S. Boulder Creek 0.076 0.082 0.085 0.081 

Denver – CAMP 0.051 0.062 0.057 0.056 

Carriage 0.074 0.072 0.076 0.074 

Chatfield State Park 0.084 0.086 0.082 0.084 

USAF Academy 0.077 0.072 0.071 0.073 

Manitou Springs 0.075 0.076 0.072 0.074 

Arvada 0.078 0.082 0.078 0.079 

Welch 0.064 0.081 0.080 0.075 

Rocky Flats North 0.077 0.090 0.090 0.085 

NREL 0.079 0.083 0.085 0.082 

Fort Collins – West --- 0.087 0.085 --- 

Fort Collins 0.076 0.078 0.069 0.074 

Greeley – Weld 

Tower 0.078 0.082 0.074 0.073 

Rocky Mountains NP 0.075 0.076 0.078* 0.076* 

* RMNP 2007 data only through July 31, 2007 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-3 

3.2.2 Episode Selection Approach

We focus our episode selection to periods that occurred over the last 6 years (2000-2007). Daily 

maximum 8-hour ozone concentrations were analyzed from May 1 to August 31 over these six 

years to determine the optimal period for 8-hour ozone modeling. There is a preference for 

modeling a more recent year to reflect current emission conditions including fleet turnover and 

the implementation of the EAC SIP control measures. Episodes that occur during the 2005-2007 

period that determined whether Denver would be a nonattainment area will be preferred 

(although the Denver ozone nonattainment classification is based on the 2001-2003 DVs). There 

is also a preference to model an entire or most of one summer during which ozone exceedances 

and high ozone levels occurred at all of the key ozone monitors. 

3.2.3 High Ozone Levels from 2002-2007

Figure 3-1 displays the number of days during each year from 2002-2007 that the highest daily 

maximum 8-hour ozone concentration at any monitor in the Denver area was greater than or 

equal to 70, 75 and 85 ppb. 2003 has the most 8-hour ozone exceedance days in the Denver area 

with 22, whereas 2004 and 2005 have the least number of 8-hour ozone exceedance days with 0 

and 3, respectively. 2002, 2006 and 2007 all have the more typical nine 8-hour ozone 

exceedance days. 

When performing 8-hour ozone projections, EPA guidance recommends using modeling results 

from at least 10 modeling days (with a minimum of 5 modeling days) with elevated ozone 

concentrations at each monitoring site (EPA, 2007). Initially, EPA recommends selecting 

modeling days for use in 8-hour ozone projections for days when the base case modeled ozone 

concentration near a monitor is 85 ppb or greater, but this threshold is allowed to be relaxed to as 

low as 70 ppb in order to increase the number of modeling days used in the projections to meet 

the EPA recommended minimums of 5 or 10 days. Figure 3-1 also includes the number of days 

daily maximum 8-hour ozone concentrations in the Denver area were greater than a 70 and 75 

ppb threshold. Again, the 2004 and 2005 years are relatively clean years with much fewer days 

greater than the 75 ppb (10 and 28 days) and 70 ppb (29 and 49 days) concentration thresholds 

than the other years. 2002, 2003 and 2006 have approximately 40 days greater than 75 ppb 

compared to ~30 days for 2005 and 2007. The 2006 year has the most days greater than 70 ppb 

(~70 days) with 2002, 2003 and 2007 having ~60 days, 2005 ~50 days and again 2004 being 

unusually clean with only ~30 days ≥ 70 ppb. 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-4 

Denver: Num of Days When Ozone Concentration >= Threshold 

0

10

20

30

40

50

60

70

80

2002 2003 2004 2005 2006 2007

Year

Number of Days .

85ppb

75ppb

70ppb

Figure 3-1. Number of days during each of the years from 2002-2007 that the daily maximum 

8-hour ozone concentration at any monitor in the Denver area was 85, 75 or 70 ppb or higher. 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-5 

The RFNO, CHAT, NREL, SBC and FTCW monitoring sites have been identified as key ozone 

monitors in the Denver area for the 8-hour ozone projections since they all have current (2005-

2007) 8-hour ozone DVs in excess of 80 ppb. Figure 3-2 lists similar information as Figure 3-1 

only separately for each of these key monitoring sites. As shown previously in Figure 3-1, the 

years 2004 and 2005 have the lowest number of days with high ozone concentrations at these key 

monitors (Figure 3-2) and it would be difficult to obtain a sufficient number of high ozone days 

to meet EPA’s minimal criteria for ozone projections. Thus, ozone episodes from the 2004 and 

2005 years are not considered for the Denver 8-hour ozone attainment demonstration modeling. 

The other years appear that they could have sufficient modeled days to meet EPA’s minimal day 

criteria. 

RFN: Num of Days When Ozone Concentration >= Threshold 

0

10

20

30

40

50

60

2002 2003 2004 2005 2006 2007

Year

Number of Days .

85 ppb

75 ppb

70 ppb

Figure 3-2a. Number of days during each of the years from 2002-2007 that the daily maximum 

8-hour ozone concentration at the Rocky Flats North (RFNO) monitor was 85, 75 or 70 ppb or 

higher
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-6 

Chatfield: Num of Days When Ozone Concentration >= Threshold 

0

5

10

15

20

25

30

35

40

45

50

2002 2003 2004 2005 2006 2007

Year

Number of Days .

85 ppb

75 ppb

70 ppb

Figure 3-2b. Number of days during each of the years from 2002-2007 that the daily maximum 

8-hour ozone concentration at the Chatfield (CHAT) monitor was 85, 75 or 70 ppb or higher

NREL: Num of Days When Ozone Concentration >= Threshold 

0

5

10

15

20

25

30

35

40

2002 2003 2004 2005 2006 2007

Year

Number of Days .

85 ppb

75 ppb

70 ppb

Figure 3-2c. Number of days during each of the years from 2002-2007 that the daily maximum 

8-hour ozone concentration at the NREL monitor was 85, 75 or 70 ppb or higher.
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-7 

S.Bldr.: Num of Days When Ozone Concentration >= Threshold 

0

5

10

15

20

25

30

2002 2003 2004 2005 2006 2007

Year

Number of Days .

85 ppb

75 ppb

70 ppb

Figure 3-2d. Number of days during each of the years from 2002-2007 that the daily maximum 

8-hour ozone concentration at the South Boulder Creek (SBC) monitor was 85, 75 or 70 ppb or 

higher

FtC West: Num of Days When Ozone Concentration >= Threshold 

0

5

10

15

20

25

30

35

40

45

50

2002 2003 2004 2005 2006 2007

Year

Number of Days .

85 ppb

75 ppb

70 ppb

Figure 3-2e. Number of days during each of the years from 2002-2007 that the daily maximum 

8-hour ozone concentration at the Fort Collins West (FTCW) monitor was 85, 75 or 70 ppb or 

higher (data only available for 2006 and 2007).
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-8 

3.2.4 Daily 8-Hour Ozone Time Series for 2002-2007

Figure 3-3a through 3-3f display time series of daily maximum 8-hour ozone concentrations 

from the four highest monitors for each day and the years 2002-2007. For each day, the daily 

maximum 8-hour ozone concentrations across the DMA are ranked and then the four highest 

values are plotted in these figures. Thus, the lines in these figures do not necessarily represent 

specific monitoring sites but rather the highest through fourth highest values that occurred on 

each day. These figures help indicate the magnitude and spatial extent of each high ozone day 

during the year and whether groups of high ozone days (episodes) occur in bunches so they can 

be connected by a contiguous modeling period. 

For 2002 (Figure 3-3a), most of the high ozone events occurred during June and July with no 8-

hour ozone exceedances occurring before June 1 or after July 31 so the June-July 2002 period is 

a candidate episode for this year. Note that a portion of this period was modeled as part of the 

Denver EAC SIP modeling and 2002 was also modeled by the WRAP, CENRAP, MRPO, 

VISTAS and MANE-VU RPOs so satisfies the EPA secondary criteria to select periods already 

modeled. However, we believe 2002 is too old for the current Denver 8-hour ozone SIP 

modeling as there have been significance changes in emissions since then, including fleet 

turnover, implementation of the EAC SIP control measures and expansion of oil and gas 

production activity in the region. 

In 2003 there are a few isolated 8-hour ozone exceedance days in May, but a vast majority of 

them occur in between July 8 and August 21, 2003 (Figure 3-3b). Although 2003 has the most 

8-hour ozone exceedance events of any of the years studied, the severity of the ozone exceedance 

events during this year is a cause for concern with 8-hour ozone exceedances of 119 and 115 ppb 

occurring on July 11 and 12, 2003 that were the highest events during the six year period studied 

(2002-2007). Recall one of the EPA criteria for episode selection is 8-hour ozone concentrations 

near the current observed maximum DV (85 ppb). Of the 22 exceedance days in 2003 over half 

have maximum daily maximum 8-hour ozone concentrations in excess of 90 ppb. Like 2002, the 

2003 is also likely too old for the current round of Denver 8-hour ozone attainment 

demonstration modeling. 

The daily 8-hour ozone concentration time series for 2004 (Figure 3-3c) and 2005 (Figure 3-3d) 

confirm the results in Figures 3-1 and 3-2 that these two years are relatively clean ozone years 

and do not offer good modeling periods for the Denver 8-hour ozone modeling. 

The final two years, 2006 (Figure 3-3e) and 2007 (Figure 3-3f), appear to be good candidates for 

Denver 8-hour ozone attainment demonstration modeling as they both have extended periods of 

multiple days with elevated ozone concentrations. For 2006 the period of June 1 through July 31 

captures all of the 8-hour ozone exceedance days during 2006 as well as a dramatic clean out 

event of July 5-12, 2006. The modeling of periods of high and low ozone concentrations is 

desirable as it tests the model’s ability to simulate both high and low ozone conditions; a model 

that is unable to simulate low ozone conditions may perform well in a base case but be unable to 

respond to future-year emission controls correctly. The 2007 year also has a good candidate 

modeling period of June 14 through July 31 with periods of high and low ozone concentrations 

that can be used to test the model. There is also a high (95 ppb) isolated ozone exceedance event 

on August 25, 2007. Although the extension of the 2007 episode almost a whole another month 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-9 

to capture a single 8-hour ozone exceedance day does not appear to be good use of 

computational resources. 

Based on the observed ozone concentrations in the Denver area and using EPA’s episode 

selection criteria, either the June-July 2006 or June-July 2007 modeling periods capture 

sufficient 8-hour ozone episodes and appear to be appropriate modeling periods for the Denver 

8-hour ozone SIP attainment demonstration modeling. 

Denver Four Highest Ozone in Year 2002

35

40

45

50

55

60

65

70

75

80

85

90

95

100

1-May-02

8-May-02

15-May-0222-May-0229-May-02

5-Jun-02

12-Jun-0219-Jun-02

26-Jun-02

3-Jul-02

10-Jul-0217-Jul-0224-Jul-0231-Jul-02

7-Aug-02

14-Aug-02

21-Aug-02

28-Aug-02

Date

Ozone (ppb)

1st

2nd

3rd

4th

Figure 3-3a. Time series of four highest daily maximum 8-hour ozone concentrations in the 

Denver area during 2002. 
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-10 

Denver Four Highest Ozone in Year 2003

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

1-May-038-May-03

15-May-03

22-May-0329-May-03

5-Jun-03

12-Jun-0319-Jun-03

26-Jun-03

3-Jul-03

10-Jul-03

17-Jul-03

24-Jul-03

31-Jul-03

7-Aug-03

14-Aug-0321-Aug-0328-Aug-03

Date

Ozone (ppb)

1st

2nd

3rd

4th

Figure 3-3b. Time series of four highest daily maximum 8-hour ozone concentrations in the 

Denver area during 2003.

Denver Four Highest Ozone in Year 2004

30

35

40

45

50

55

60

65

70

75

80

85

90

95

1-May-04

8-May-04

15-May-04

22-May-04

29-May-04

5-Jun-04

12-Jun-04

19-Jun-04

26-Jun-04

3-Jul-04

10-Jul-04

17-Jul-04

24-Jul-04

31-Jul-04

7-Aug-04

14-Aug-04

21-Aug-04

28-Aug-04

Date

Ozone (ppb)

1st

2nd

3rd

4th

Figure 3-3c. Time series of four highest daily maximum 8-hour ozone concentrations in the 

Denver area during 2004.
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-11 

Denver Four Highest Ozone in Year 2005

30

35

40

45

50

55

60

65

70

75

80

85

90

95

1-May-05

8-May-05

15-May-0522-May-0529-May-05

5-Jun-05

12-Jun-0519-Jun-05

26-Jun-05

3-Jul-05

10-Jul-0517-Jul-0524-Jul-0531-Jul-05

7-Aug-05

14-Aug-05

21-Aug-05

28-Aug-05

Date

Ozone (ppb)

1st

2nd

3rd

4th

Figure 3-3d. Time series of four highest daily maximum 8-hour ozone concentrations in the 

Denver area during 2005.

Denver Four Highest Ozone in Year 2006

35

40

45

50

55

60

65

70

75

80

85

90

95

100

1-May-06

8-May-06

15-May-06

22-May-06

29-May-06

5-Jun-06

12-Jun-06

19-Jun-06

26-Jun-06

3-Jul-06

10-Jul-06

17-Jul-06

24-Jul-06

31-Jul-06

7-Aug-06

14-Aug-06

21-Aug-06

28-Aug-06

Date

Ozone (ppb)

1st

2nd

3rd

4th

Figure 3-3e. Time series of four highest daily maximum 8-hour ozone concentrations in the 

Denver area during 2006.
F:\Denver_O3_2008\Protocol\draft#2\Sec3_Episode1.doc 3-12 

Denver Four Highest Ozone in Year 2007

35

40

45

50

55

60

65

70

75

80

85

90

95

100

1-May-07

8-May-07

15-May-0722-May-0729-May-07

5-Jun-07

12-Jun-0719-Jun-07

26-Jun-07

3-Jul-07

10-Jul-0717-Jul-0724-Jul-0731-Jul-07

7-Aug-07

14-Aug-07

21-Aug-07

28-Aug-07

Date

Ozone (ppb)

1st

2nd

3rd

4th

Figure 3-3f. Time series of four highest daily maximum 8-hour ozone concentrations in the 

Denver area during 2007.

3.3 Final Selection of Denver 8-Hour Ozone Modeling Period 

Based on being current and having sufficient number of 8-hour ozone exceedance and high 

ozone days either the June-July 2006 or June-July 2007 episodes would be appropriate for the 

Denver 8-hour ozone attainment demonstration modeling. The June-July 2006 modeling period 

was selected for modeling over the June-July 2007 episode because: 

• The June-July 2006 episode has more 8-hour ozone exceedance days (9) than the 

June-July 2007 episode (8); 

• The June-July 2006 episode has substantially more high (> 70 ppb and > 75 ppb) 

8-hour ozone days than the June-July 2007 episode (see Figure 3-1); 

• There is potentially additional special study data available during the 2006 

episode including VOC samples, ozonesondes and ROMANS data; and 

• Since it is so recent, not all data will be available for June-July 2007 modeling 

period in the timeframe required by this study. 

This last issue is critical as the 2007 ozone observations will not be fully QA’d for several 

months and the IMPROVE data for RMNP likely won’t be available until some time 2008. Even 

some of the data needed to run and evaluate the MM5 model may not all be available to properly 

simulate the 2007 episode. 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-1 

4.0 MODELING DOMAINS AND DATA AVAILABILITY 

This chapter summarizes the model domain definitions for the Denver 8-hour ozone modeling, 

including the domain coverage, resolution, map projection, and nesting schemes for the high 

resolution sub-domains. It also discusses the emissions and aerometric data available from 

various State and federal agencies for use in model input preparation and performance testing. 

4.1 Horizontal Modeling Domain 

Figure 4-1a displays the 36/12/4 km modeling domains that will be used in the MM5 

meteorological and the CAMx/SMOKE air quality/emissions modeling. The 36 km continental 

United States (U.S.) horizontal domain for CAMx air quality and SMOKE/CONCEPT/MEGAN 

emissions modeling will be identical to what is used by several Regional Planning Organizations 

(RPOs) for their regional haze modeling (e.g., WRAP, CENRAP and VISTAS). This 36 km 

modeling domain covers the continental U.S. as well as large portions of Mexico and Canada. 

The MM5 will first be operated on the 36/12 km grid for the May 25 through July 31, 2006 

period using two-way grid nesting with feedback (Figure 4-1b). The MM5 results from the 12 

km simulation would be used to provide boundary conditions for the 4 km grid that would be 

operated using one-way grid nesting. MM5 sensitivity simulations will be carried out for the 

July 20-30, 2006 period and the 4 km grid domain to identify the optimal MM5 configuration for 

ozone modeling of the Denver area. 

The CAMx 36/12/4 km modeling domains are shown in Figure 4-1c. The CAMx 12 km 

modeling domain includes all of Colorado, Utah, Kansas, Nebraska, and portions of Oklahoma, 

Texas, New Mexico, Arizona, Nevada, Idaho, Wyoming and South Dakota (Figure 4-1d). The 

CAMx 4 km modeling domain covers almost all of Colorado (Figure 4-1e). 

The CAMx air quality and SMOKE/CONCEPT/MEGAN emissions modeling 36/12/4 km 

modeling domains are aligned within the MM5 domains. The MM5 modeling domains are 

offset (larger) from the CAMx/emissions modeling domains by at least 6 grid cells in each 

direction (Figure 4-1a). These grids are based on a Lambert Conformal Projection (LCP) using 

the same projection as adopted by the RPOs. The LCP is defined by the projection parameters 

listed in Table 4-1. 

There is a possibility of boundary noise effects resulting from boundary conditions coming into 

dynamic balance with MM5’s algorithms. The larger MM5 domain is designed to sequester 

such errors from the air quality simulation. The buffer region used here exceeds the EPA 

suggestion of at least 5 grid cell buffer at each boundary. 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-2 

-2880-2520-2160-1800-1440-1080 -720 -360 0 360 720 1080 1440 1800 2160 2520 2880

-2160

-1800

-1440

-1080

-720

-360

0

360

720

1080

1440

1800

2160

MM5 36 km

MM5 12km

MM5 4km

CAMx 36 km

CAMx 12km

CAMx 4

36 km: 165 x 129 dot points (-2952, -2304) to (2952, 2304)

12 km: 187 x 157 dot points (-1836, -936) to ( 396, 936)

04 km: 151 x 136 dot points ( -984, -324) to ( -384, 216)

Denver Modeling Domain

MM5 Domain

CAMx Domain

36 km: 148 x 112 (-2736, -2088) to (2592, 1944)

12 km: 167 x 92 (-1704, -624) to ( 300, 480)

04 km: 119 x 119 ( -940, -292) to ( -464, 184)

Figure 4-1a. Nested 36/12/4 km modeling domains for the Denver 8-hour ozone modeling 

study. Blue line domains are for CAMx/SMOKE that are nested in the MM5 red line domains.
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-3 

-2880-2520-2160-1800-1440-1080 -720 -360 0 360 720 1080 1440 1800 2160 2520 2880

-2160

-1800

-1440

-1080

-720

-360

0

360

720

1080

1440

1800

2160

MM5 36 km

MM5 12km

MM5 4km

Denver MM5 Domain

36 km: 165 x 129 dot points (-2952, -2304) to (2952, 2304)

12 km: 187 x 157 dot points (-1836, -936) to ( 396, 936)

04 km: 151 x 136 dot points ( -984, -324) to ( -384, 216)

Figure 4-1b. Nested 36/12/4 km modeling domains for the Denver MM5 meteorological 

modeling.
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-4 

CAMx 36 km

CAMx 12km

CAMx 4

36 km: 148 x 112 (-2736, -2088) to (2592, 1944)

12 km: 167 x 92 (-1704, -624) to ( 300, 480)

04 km: 119 x 119 ( -940, -292) to ( -464, 184)

Denver CAMx Modeling Domain

-2520 -2160 -1800 -1440 -1080 -720 -360 0 360 720 1080 1440 1800 2160 2520

-1800

-1440

-1080

-720

-360

0

360

720

1080

1440

1800

Figure 4-1c. Nested 36/12/4 km modeling domains for the Denver CAMx air quality and 

SMOKE emissions modeling. 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-5 

-1680-1560-1440-1320-1200-1080 -960 -840 -720 -600 -480 -360 -240 -120 0 120 240

-600

-480

-360

-240

-120

0

120

240

360

480

CAMx 12km

CAMx 4km

Denver CAMx 12 and 4 km Domain

Figure 4-1d. Nested 12/4 km modeling domains for the Denver CAMx air quality and SMOKE 

emissions modeling.
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-6 

-920 -880 -840 -800 -760 -720 -680 -640 -600 -560 -520 -480

-280

-240

-200

-160

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-80

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0

40

80

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160

SBC

ACAD

 ARVA NREL 

RMNP

FTCW

 GREE

CHAT

MANI

FTCO

WCTO

 CARR

WELB

HIGH

CAMP

 RFNO

WELC

LOOK

Denver Ozone Monitoring Sites in the 4 km Domain

Figure 4-1e. Denver 4 km modeling domains for the CAMx air quality and SMOKE emissions 

modeling and locations of ozone monitoring sites within and near the Denver NAA.

Table 4-1. Lambert Conformal Projection (LCP) definition for the Denver 36/12/4 km modeling 

grid.

Parameter Value 

Projection Lambert-Conformal 

1st True Latitude 33 degrees N 

2nd True Latitude 45 degrees N 

Central Longitude -97 degrees W 

Central Latitude 40 degrees N 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-7 

Table 4-2. Grid definitions for MM5, Emissions and CAMx. 

MODEL

COLUMNS

DOT(CROSS) 

ROWS 

DOT(CROSS) 

XORIGIN

(KM) 

YORIGIN

(KM) 

MM5 

 36 km grid 

 12 km grid 

 4 km grid

165 (164) 

187 (186) 

151 (150) 

129 (128) 

157 (156) 

136 (135) 

-2952.0 

-1836.0 

-984.0 

 

-2304.0 

-936.0 

-324.0 

Emissions/CAMx 

 36 km grid 

 12 km grid 

 4 km grid 

(148) 

(167) 

(119)

(112) 

(92) 

(119) 

-2736.0 

-1704.0 

-940.0 

-2088.0 

-624.0 

-940.0 

Table 4-2 lists the number of rows and columns and the definition of the X and Y origin (i.e., the 

southwest corner) for the 36/12/4 km domains to be used by MM5, CAMx and the SMOKE, 

CONCEPT and MEGAN emissions models. In Table 4-2 “Dot” refers to the grid mesh defined 

at the vertices of the grid cells while “Cross” refers to the grid mesh defined by the grid cell 

centers. Thus, the dimension of the dot mesh is equal to the cross mesh plus one. 

4.2 Vertical Modeling Domain 

The CAMx vertical structure is primarily defined by the vertical grid used in the MM5 modeling. 

The MM5 model employs a terrain following coordinate system defined by pressure, using 

multiple layers that extend from the surface to 100mb (approximately 15 km AGL). A layer 

averaging scheme is adopted for CAMx simulations to reduce the air quality computational time. 

The effects of layer averaging were evaluated by WRAP and VISTAS and found to have a 

relatively minor effect on the model performance metrics when both 34 layer and 19 layer 

CMAQ model simulations were compared to ambient monitoring data (Morris et al., 2004a). 

For the Denver ozone modeling, 19 vertical layers will be used. Table 4-3 lists the mapping 

from the MM5 vertical layer structure to the CAMx vertical layers. This MM5 structure was 

taken from the WRAP, VISTAS and CENRAP RPO configuration and the same 19 layer CAMx 

structure is also being used in the RPO modeling. 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-8 

Table 4-3. Vertical layer definition for MM5 simulations (left most columns), and approach for 

reducing CAMx layers by collapsing multiple MM5 layers (right columns). 

MM5 CAMx

Layer Sigma Pres (mb) Height (m) Depth (m) Layer Pres (mb) Height (m) Depth (m) 

34 (top) 0.000 100 18123 2856 19 100 18123 9160 

33 0.050 145 15267 2097 

32 0.100 190 13170 1659 

31 0.150 235 11510 1374 

30 0.200 280 10136 1173 

39 0.250 325 8963 1024 18 325 8963 3492 

28 0.300 370 7938 909 

27 0.350 415 7030 817 

26 0.400 460 6213 742 

25 0.450 505 5471 680 17 505 5471 1890 

24 0.500 550 4791 627 

23 0.550 595 4163 582 

22 0.600 640 3581 543 16 640 3581 1053 

21 0.650 685 3038 509 

20 0.700 730 2528 386 15 730 2528 664 

19 0.740 766 2142 278 

18 0.770 793 1864 269 14 793 1864 443 

17 0.800 820 1596 174 

16 0.820 838 1421 171 13 838 1421 338 

15 0.840 856 1251 167 

14 0.860 874 1083 164 12 874 1083 163 

13 0.880 892 920 161 11 892 920 161 

12 0.900 910 759 79 10 910 759 158 

11 0.910 919 680 78 

10 0.920 928 601 78 9 928 601 155 

9 0.930 937 524 77 

8 0.940 946 447 76 8 946 447 76 

7 0.950 955 371 75 7 955 371 76 

6 0.960 964 295 75 6 964 295 75 

5 0.970 973 220 74 5 973 220 74 

4 0.980 982 146 37 4 982 146 37 

3 0.985 987 109 37 3 987 109 37 

2 0.990 991 73 36 2 991 73 36 

1 0.995 996 36 36 1 996 36 36 

0 (ground) 1.000 1000 0 0 0 0 0 0 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-9 

4.3 Data Availability 

The CAMx modeling systems requires emissions, meteorology, surface characteristics, initial 

and boundary conditions (IC/BC), and ozone column data for defining the inputs. 

4.3.1 Emissions Data

The base year emissions inventory for ozone modeling of the 4 km Colorado domain (Figure 4-

1e) will be based upon the 2006 emissions for the Denver NAA provided by the CDPHE/APCD 

and projected 2006 emissions from the latest 2002 emission inventories developed by the RPOs 

and their states (e.g., Strait, Roe and Vukovich, 2004; MACTEC, 2006; ERG, 2006a,b). For 

purposes of air quality model performance evaluation, actual day-specific hourly NOx and SO2 

emissions for Electrical Generating Units (EGU) and other large stationary sources that have 

Continuous Emissions Monitoring (CEM) systems will be used. If appropriate and as data are 

available, day-specific fire activity data will be also be used in the base case simulations used for 

model evaluation. For strategy and future year emission runs, “typical year” emissions for these 

categories will be processed for the base and future years. 

For outside of Colorado in the 36 km and 12 km domains we will use 2006 VMT data and the 

SMOKE-MOBILE6 model for on-road mobile sources. 2006 CEM data will be used for all 

large stationary sources (Primarily EGUs). The MEGAN biogenic emissions model will be used 

with the 2006 MM5 data to generate biogenic emissions for the 36/12/4 km domains. Existing 

2005 project emissions for area, non-road mobile and non-EGU point sources for the portions of 

the 36/12 km domains outside of Colorado. 

Emissions will be converted to Inventory Data Analyzer (IDA) format and the data will be 

processed for air quality modeling using Version 2.3 of the SMOKE emissions modeling system. 

The exception to this is for on-road mobile sources in the Denver nonattainment area (NAA) and 

biogenic emissions. On-road mobile sources in the Denver NAA will be generated using the 

CONCEPT emissions model and link-based vehicle miles traveled (VMT) data from a travel 

demand model (TDM) and biogenic emissions will be generated using the MEGAN biogenic 

emissions model. Included in these runs will be the temporal and speciation profiles and crossreference data provided with SMOKE, augmented with any recommended and approved 

emission profile data obtained from EPA, or prepared by the study team prior to initial emissions 

modeling. Spatial allocation of the emissions will be based on profiles and allocation factors 

developed for the modeling grid. Additional description of emissions processing is described in 

Chapter 5. 

4.3.2 Air Quality

Data from ambient monitoring networks for gas species are used in the model performance 

evaluation. Table 4-4 summarizes routine ambient gaseous and PM monitoring networks 

available in the U.S. Figure 4-2 displays the ozone monitoring sites within and near the Denver 

area that are also summarized in Table 4-5. Special air quality and air quality related 

measurements collected in the general Denver area during 2006 include VOC sampling by 

CDPHE, ozonesondes by NOAA (Cooper et. al., 2007) and data collected as part of the 

ROMANS study. 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 

Table 4-4. Overview of routine ambient data monitoring networks. 

Monitoring Network Chemical Species Measured Sampling Period Data Availability/Source The Interagency Monitoring of Protected Visual Environments (IMPROVE) 

Speciated PM25 and PM10 (see 

species mappings) 

1 in 3 days; 24 hr average http://vista.cira.colostate.edu/improve/Data/IM

Clean Air Status and Trends Network (CASTNET) 

Speciated PM25, Ozone (see 

species mappings) 

Approximately 1-week average http://www.epa.gov/castnet/data.html

National Atmospheric Deposition Program (NADP) 

Wet deposition (hydrogen (acidity as pH), sulfate, nitrate, ammonium, chloride, and base cations (such as calcium, magnesium, potassium and sodium)), Mercury 1-week average http://nadp.sws.uiuc.edu/

Air Quality System (AQS) or Aerometric Information Retrieval System (AIRS) 

CO, NO2, O3, SO2, PM25, PM10, 

Pb 

Typically hourly average http://www.epa.gov/air/data/

Speciation Trends Network (STN) Speciated PM 24-hour average http://www.epa.gov/ttn/amtic/amticpm.html Southeastern Aerosol Research and Characterization (SEARCH) (Southeastern US only) 

24-hr PM25 (FRM Mass, OC, BC, SO4, NO3, NH4, Elem.); 24-hr PM coarse (SO4, NO3, NH4, elements); Hourly PM2.5

(Mass, SO4, NO3, NH4, EC, TC); Hourly gases (O3, NO, NO2, NOy, HNO3, SO2, CO) 

Hourly or 24-hour average, depending on parameter. 

Electric Power Research Institute (EPRI), Southern Company, and other companies. http://www.atmospheric-research.com

EPA Particulate Matter Supersites(Includes St. Louis, Pittsburgh, Baltimore, Atlanta and New York in the Denver modeling domain) Speciated PM25 http://www.epa.gov/ttn/amtic/supersites.htmlPhotochemical Assessment Monitoring Stations (PAMS) 

Varies for each of 4 station types. http://www.epa.gov/ttn/amtic/pamsmain.html

National Park Service Gaseous Pollutant Monitoring Network 

Acid deposition (Dry; SO4, NO3, 

HNO3, NH4, SO2), O3, meteorological data Hourly http://www2.nature.nps.gov/ard/gas/netdata1.h
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-11 

-800 -760 -720 -680 -640 -600

-120

-80

-40

0

40

80

120

SBC

ACAD

 ARVA

NREL 

RMNP

FTCW

 GREE

CHAT CHAT

MANI

FTCO

WCTO

 CARR

WELB

HIGH

CAMP

 RFNO

WELC

LOOK

Denver Ozone Monitoring Sites

Figure 4-2. Locations of ozone monitoring sites within and near the Denver area. 
F:\Denver_O3_2008\Protocol\draft#2\Sec4_Domains1.doc 4-12 

Table 4-5. Ozone monitoring sites within and near the Denver area operating during 2002-2007. 

ID Number Site Name Site ID 2002 2003 2004 2005 2006 2007 Lat Long 

080013001 Welby WELB x x x x x x 39.838 -104.950 

080050002 Highland HIGH x x x x x x 39.568 -104.957 

080130011 S. Boulder Creek SBC x x x x x x 39.957 -105.238 

080310002 CAMP CAMP x x x 39.751 -104.988 

080310014 Carriage CARR x x x x x x 39.752 -105.031 

080350002 Chatfield #1 CHAT x x x 39.538 -105.065 

080350004 Chatfield #2 CHAT x x x x 39.534 -105.070 

080410013 USAF Academy ACAD x x x x x x 38.958 -104.817 

080410016 Manitou Springs MANI x x x x 38.853 -104.901 

080590002 Arvada ARVA x x x x x x 39.800 -105.100 

080590005 Welch WELC x x x x x x 39.639 -105.139 

080590006 RFN RFNO x x x x x x 39.913 -105.189 

080590011 NREL NREL x x x x x x 39.744 -105.178 

080590012 Lookout Mountain LOOK x 39.727 -105.247 

080690007 RMNP RMNP x x x x x x 40.277 -105.545 

080690011 FtC West FTCW x x 40.593 -105.141 

080691004 Ft. Collins FTCO x x x x x x 40.577 -105.079 

081230007 Greeley GREE x 40.416 -104.692 

081230009 Weld Co. Tower WCTO x x x x x x 40.386 -104.737 

4.3.3 Ozone Column Data

Additional data used in the air quality modeling include ozone column data from the Total Ozone 

Mapping Spectrometer (TOMS) satellite platform. TOMS data are available for 24-hour average time 

periods, and are obtained from http://toms.gsfc.nasa.gov/eptoms/ep.html. The TOMS data are used in 

the CAMx (TUV) radiation models to calculate photolysis rates. Frequently TOMS ozone column 

data are missing for extended periods so data needs to be filled. The CAMx TUV processor allows for 

the use of episode average data. If there are large periods of missing TOMS data during a Denver 

June-July 2006 modeling period, then we may use monthly or episode average TOMS data to work 

around the missing data. 

4.3.4 Meteorological Data

Meteorological data are being generated using the MM5 prognostic meteorological model. MM5 runs 

will be performed on the 36/12/4 km domains and the June-July 2006 period. Initialization days prior 

to the Denver modeling period will be run on the 36-km grid for 5 days prior to the start of the Denver 

modeling period. The MM5 model will be started approximately 12 hours prior to the first hour that 

the data will be used by CAMx. 

4.3.5 Initial and Boundary Conditions Data

For the Denver ozone simulations we will use a minimum 5-day initialization period on the 36-km grid 

to eliminate the contribution of initial concentrations. Clean or other appropriate initial conditions 

(ICs) will be used at the start of the 5-day initialization period. We will determine an appropriate 

source for the CAMx boundary conditions (BCs) along the lateral boundaries of the 36 km continental 

U.S. modeling domain. BCs for the 12 km CAMx domain will be based on the 36 km domain CAMx 

simulations results using one-way nesting. For most simulations the CAMx 12/4 km grid 

configuration will be run using two-way interactive grid nesting. However, some sensitivity 

simulations may also be run using just the 4 km grid with BCs based on the 12 km CAMx simulation. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-1 

5.0 MODEL INPUT PREPARATION PROCEDURES 

This section describes the procedures to be used in developing the meteorological, emissions, 

and air quality inputs to the CAMx model for the Denver 8-hour ozone modeling on the 36/12/4 

km grids. The development of the CAMx meteorological and emissions inputs are discussed 

together with the science options recommended for MM5 and CAMx models. The procedures 

for developing the initial and boundary conditions and photolysis rates inputs are also discussed 

along with the model application procedures. 

The procedures set forth here are consistent with EPA guidance (e.g., EPA, 1991; 1999; 2005a; 

2007), other recent 8-hour ozone modeling studies conducted for various State and local agencies 

using these or other state-of-science modeling tools (see, for example, Morris et al., 2004a,b, 

2005a,b; Tesche et al., 2005a,b), as well as the methods used by EPA in support of the recent 

Clean Air Interstate Rule (EPA, 2005b) and the Clean Air Mercury Rule (EPA, 2005c). 

5.1 Meteorological Inputs 

5.1.1 MM5 Model Science Configuration 

The MM5 model configuration will be based on recent modeling research and sensitivity testing 

carried out with the MM5 in the western U.S. for WRAP (Kemball-Cook et al., 2004), the 

Denver EAC (McNally, Tesche and Morris, 2003) and the ROMANS study (Gebhart et al., 

2007), work at the Iowa Department of Natural Resources (Johnson, 2004; 2007), Olerud and coworkers with the VISTAS program (Olerud and Sims, 2004a,b), EPA CAIR modeling (McNally, 

2003) and MM5 modeling to support 8-hour ozone EAC SIP development in Texas, Oklahoma, 

and New Mexico (Morris et al., 2005d). 

5.1.2 MM5 Input Data Preparation Procedures

A brief summary of the MM5 input data preparation procedures we will use are listed below and 

provided in Table 5-1. 

Model Selection: The current version of the non-hydrostatic MM5 (version 3.7) will be 

used. The MM5 TERRAIN, PREGRID/REGRID, RAWINS/little_r, and INTERPF 

processors will be used to develop model inputs. We considered using the new Weather 

Research Forecast (WRF) model that is a replacement to MM5. Although it has been 

extensively applied for forecast applications, its applications for modeling historical air 

pollution episodes have been limited. 

 

Horizontal Domain Definition: The computational domain on which MM5 will be 

applied will be sufficiently sized to accommodate the air quality and emissions modeling 

grids as defined in Figure 4-1 and Tables 4-1 and 4-2 and earlier. The MM5 36/12/4 km 

domains are defined with at least a 6 grid cell buffer in all directions from the air quality 

modeling domains. 

 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 

Table 5-1. MM5 (Version 3.7:4) model configuration. 

Science Options Configuration Details Model Code MM5 version 3.7.4 (MPP) -- 16 Oct. '06 Dudhia (1993), Grell et al., (1994) Horizontal Grid Mesh 36/12/4 km  36 km grid 145 x 101 cells Cross Points (add one for dot point 12 km grid 163 x 130 cells  4 km grid 227 x 88 cells Vertical Grid Mesh 34 Layers; Surface layer ~ 35 m deep Vertically varying; sigma pressure c Domain Depth Surface to ~15 km AGL Top defined by 100 mb Grid Interaction Feedback Two-way nesting with feedback Initialization EDAS Eta Data Assimilation System Boundary Conditions EDAS 40 km resolution Microphysics Mixed Phase Moisture Scheme Reisner II in 36/12/4 km grids Cumulus Scheme Kain-Fritsch 2 subgrid scale cumulus 36/12 km grids only Planetary Boundary Layer ACM Asymmetric Convective Mixing with Radiation RRTM Rapid Radiative Transfer Model Vegetation & Land Use USGS 24 Category Scheme  36 km grid 10 min (~18 km) global data Geophysical Data Center  12 km grid 5 min (~9 km) global data Geophysical Data Center  4 km grid High-Resolution (30 sec) NCAR Land Surface Model Pleim-Xiu LSM (ISOIL = 3) Soil moisture from EDAS fields, not Topographic Input 36/12/4 km grid Updated NCAR/PSU data bases Supplied with MM5 Shallow Convection None Sea Surface Temperature EDAS skin temperature Spatially varying 4D Data Assimilation 36 km grid Analysis nudging wind, temp and moisture above PBL, only wind below PBL Wind, temp coeff = 2.5x10-4; mixing  12 km grid Analysis nudging wind, temp and moisture above PBL, only wind below PBL Wind, temp coeff = 2.5x10-4; mixing  4 km grid 

Analysis nudging wind, temp and moisture above PBL, only wind below PBL. Surface wind observation nudging. 

Wind, temp coeff = 2.5x10-4; mixing 

Spin-up Spin-up time typically ~12 hrs Spin-up prior to ozone episode simu
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-3

Vertical Domain Definition: The MM5 modeling will employ 34 vertical layers with an 

approximately 36 meter deep surface layer, based upon the configuration used in the 

CENRAP modeling. The MM5 vertical domain is presented in both sigma and height 

coordinates in Table 4-3. 

Topographic Inputs: Topographic information for the MM5 will be developed using the 

NCAR and the U.S. Geological Survey (USGS) terrain databases. The 36-km grid will 

be based the 10 min (~18 km) Geophysical Data Center global data. The 12-km grid will 

be developed from the 5 min (~9 km) Geophysical Data Center global data, whereas the 

4-km terrain heights will be based on 30 second data (~1 km resolution). Terrain data will 

be interpolated to the model grid using the TERRAIN pre-processor. 

Vegetation Type and Land Use Inputs: Vegetation type and land use information will be 

developed for the 36/12/4 km grids using the most recently released NCAR/PSU 

databases provided with the MM5 distribution. Standard MM5 surface characteristics 

corresponding to each land use category will be employed. 

Atmospheric Data Inputs: Initialization, boundary conditions and FDDA nudging fields 

will be based on the 40 km Eta Data Assimilation System (EDAS) fields. 

Water Temperature Inputs: The EDAS “skin temperature” field will be used for water 

temperature inputs. 

FDDA Data Assimilation: Standard FDDA data assimilation techniques will be used in 

this study (see, for example, Johnson 2004, 2007; Nielson-Gammon et al., 2005; Olerud 

and Simms, 2004a,b;and Gao et al., 2000; Kemball-Cook et al., 2005). The MM5 

simulations will use the three-dimensional analysis-nudging technique where the 

predictions are nudged toward a field prepared by regridding the EDAS. For these 

simulations a nudging coefficient of 2.5x10-4 will be used for winds and temperature and 

1x10-5 for mixing ratio on the 36/12/4 km grids. Thermodynamic variables will not be 

nudged within the boundary layer (i.e., only winds will be nudged within the PBL). In 

the 4-km grid, surface observation nudging will be performed for winds only. 

Nesting Configuration: MM5 will first be run for the May 25 – July 31, 2006 period on 

the 36/12 km grids using two-way nesting with feedback. The 12 km MM5 output will 

be processed to generate boundary conditions (BCs) for the 4 km Colorado grid. MM5 

will then be run for the June-July 2006 period on the 4 km grid using one-way nesting. 

Run Segments: The MM5 simulation will be performed using overlapping 51⁄2 day run 

segments initialized off of the Eta analysis fields and observed soil moisture. The first 

half day of the 51⁄2 day run segments would not be used in the CAMx modeling.

Physics Options: The initial MM5 model physics to be used in the MM5 simulations will 

be as follows: 

• Kain Fritsch II cumulus parameterization; 

• ACM PBL that is compatible with the PX LSM; 

• Plein-Xiu (P-X) Land Surface Model; 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-4

• Reisner II Mixed Ice Moisture Scheme; and 

• RRTM Atmospheric Radiation Scheme. 

Sensitivity Tests: MM5 sensitivity tests will be conducted for the July 20-30, 2006 

period and the 4 km grid. The following variables will be considered in the sensitivity 

modeling: 

• Planetary Boundary Layer (PBL) scheme (e.g., ACM, MRF, Blackadar, Eta). 

• Land Surface Module (LSM) (e.g., PX, NOAH). 

• Cumulus Parameterization (e.g., KF2, KF1, none). 

• Moisture (e.g., Reisner 1 and 2). 

• Data Assimilation (analysis only, surface wind observations). 

Other 

Final MM5 Simulation: The MM5 configuration that performs best will be rerun on the 

4 km grid for the entire June-July 2006 modeling period. Performance would be based 

on both the MM5 meteorological and CAMx air quality model performance for the July 

20-30, 2006 period. 

5.1.3 MM5CAMx Reformatting Methodology

 

The MM5CAMx processor maps MM5 meteorological fields to the format required by CAMx. 

It also calculates turbulent vertical exchange coefficients (Kz) that define the rate and depth of 

vertical mixing in CAMx. Steps in the MM5CAMx processing include: 

• Reading in meteorological model output files; 

• Extracting meteorological data for CAMx domain; 

• Collapsing meteorological data if coarser vertical resolution data is requested in 

CAMx than used in MM5; 

• Computing vertical diffusivities (Kz) using three options available to the user; 

When feasible it is desirable to use the same layer structure in the air quality model as in the 

MM5 to prevent errors associated with averaging layer data, and to maintain consistency 

between data produced by the meteorological model and those used by the chemistry-transport 

model. However, vertical layer collapsing is typically used to reduce computational costs 

associated with using large number of vertical layers. We propose to reduce the number of 

vertical layers in the CAMx modeling from 34 to 19. Further details on the CAMx modeling 

domain definitions were provided in Chapter 4 (Table 4-3). 

Two sets of vertical turbulent diffusivity options will be invoked in MM5CAMx from the MM5 

ACM/P-X runs: (a) the O’Brien scheme (OB70), and (b) the CMAQ-like scheme. A third option 

(the TKE method) could also be invoked if the MM5 Eta PBL is used in a sensitivity test. 

MM5CAMx will be operated initially with a 0.1 m2

/s minimum KV (Kz_min) value. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-5

5.1.4 Treatment of Minimum KV

The minimum KV value (Kz_min) is an area of ongoing investigation by the CAMx model 

developers and the scientific user community (e.g., CMAQ developers). EPA initially 

recommended a 1.0 m2/s Kz_min for CMAQ modeling. However in their ozone forecasting, 

EPA uses Kz_min values that vary from 0.1 to 2.0 m2/s depending on the amount of urban land 

use present. To maximize flexibility we will process the MM5 data using MM5CAMx using a 

0.1 m2

/s Kz_min and then test other Kz_min values (e.g., 1.0 m2/s). The CAMx modeling 

system contains a utility that produces enhanced minimum Kz (Kz_min) values near the surface 

to account for increased mixing due to roughness and the urban heat island. The selection of the 

Kz profiles (O’Brien or CMAQ) and Kz_min approach will be based on the latest thinking, 

CAMx sensitivity tests and model performance and will be justified in the interim and final 

documentation on the modeling. 

5.2 Emission Inputs 

5.2.1 Available Emissions Inventory Datasets

Two 2006 baseline emissions inventories will be developed corresponding to “Actual” and 

“Typical” emissions. The differences in the Actual and Typical 2006 base case emissions will be 

in the emissions from large stationary sources with Continuous Emissions Monitoring (CEM) 

systems and, possibly, wildfire emissions. In the 2006 Actual base case emissions scenario the 

actual day-specific hourly SO2 and NOx emissions from the CEM systems will be used. 

Whereas in the 2006 Typical base case we will analyze the CEM and generate typical summer 

emissions for when the source is typically operating. The 2006 Actual base case modeling 

results are compared against the concurrent ambient ozone observations in the model 

performance evaluation. The 2006 Typical emissions are projected to the future-years for the 

2010 and 2020 base case emission scenarios. Modeling results from the 2006 Typical base case 

emissions scenario are used with results from the future-year emission scenario to project 8-hour 

ozone Design Values. There is no analogue to the 2006 Actual base case for the future-year 

emission scenarios. For the WRAP modeling of the 2002 year they also developed Actual and 

Typical emissions for wildfires because 2002 was an abnormally high year for wildfires in the 

western U.S. and smoke from wildfires heavily influences visibility at many western Class I 

areas. However, our preliminary examination of wildfires during the June-July 2006 Denver 

ozone episode indicates they do not play an important roll in ozone formation in the area, so we 

would likely just use one set of Actual wildfire emissions for both the 2006 Actual and Typical 

base case emissions scenarios. 

The emissions inventories developed for the Denver 8-hour ozone modeling study will be based 

on several sources. For the Denver nonattainment area (NAA) the CDPHE/APCD will provide 

2006 VOC, NOx and CO emissions. For other pollutants in the Denver NAA (e.g., SO2, NH3 

and PM) and emissions outside of the Denver NAA the latest 2002 emissions database, as 

updated by States and the RPOs, will be projected to 2005/2006. For on-road mobile source 

emissions in the Denver metropolitan area (DMA), local traffic demand model (TDM) output 

from the Denver Regional Council of Governments (DRCOG) will be used to generate linkbased emissions which will then be gridded for the modeling. For point sources, day-specific 

hourly NOx and SO2 emissions for sources with Continuous Emissions Monitoring (CEM) 

systems (e.g., Electrical Generating Units, EGUs) would be used for the 2006 Actual base 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-6

case simulation used in the model performance evaluation. For the 2006 Typical base case 

used in the future-year ozone projections the CEM data will be processed to obtain typical 2006 

summer emissions for these sources. 

Biogenic emissions will be day-specific and based the MM5 model-derived temperatures using 

the MEGAN biogenic emissions model (Guenther and Wiedinmeyer, 2004). MM5 temperature 

fields will be reviewed and statistically analyzed for the presence of any daytime temperature 

bias. If a significant bias exists that cannot be removed through any re-configuration of the 

model, an alternative means of providing gridded temperature fields from observational analyses 

will be developed. We would also generate biogenic emissions using the GloBEIS biogenic 

emissions model that incorporates the BEIS biogenic emissions algorithms that will be used in a 

sensitivity test. The latest version of MEGAN has not yet been used in a SIP application, 

whereas GloBEIS has been used extensively for SIPs so would serve as a backup in case issues 

with the MEGAN biogenic emissions arise. 

All emissions, except for on-road mobile source emissions in the DMA will be converted to the 

Inventory Data Analyzer (IDA) format used by the SMOKE emissions model; the DMA on-road 

emissions will be generated and gridded using the CONCEPT MV model as discussed below. 

5.2.2 Development of CAMx-Ready Emissions Inventories

CAMx-ready emissions will be generated by the SMOKE, CONCEPT and MEGAN suite of 

emissions models. Table 5-2 summarizes the emissions modeling configuration to be used. 

Emissions inventory development for episodic 8-hour ozone modeling must address several 

source categories including: (a) stationary point sources, (b) area sources, (c) on-road mobile 

sources, (d) non-road mobile sources, (e) biogenic sources and (f) fire sources. For this analysis, 

these estimates must be developed for the June-July 2006 modeling period and the 36, 12 and 4 

km grids. 

CAMx requires two emission input files: (1) low level gridded emissions that are emitted directly 

into the first layer of the model from sources at the surface with little or no plume rise; and (2) 

elevated point sources (stacks) with plume rise calculated from stack parameters and 

meteorological conditions. For ozone modeling alone, hourly emissions are required for NO, 

NO2, CO, several classes of VOCs and other pollutants as available. The VOC classes used will 

depend upon the chemical mechanism selected. CAMx will be operated using the CB05 

chemical mechanism that will define the VOC classes to be used in the modeling. CAMx will 

also be configured to provide particulate matter (PM) estimates, as well as visibility and 

deposition. Thus, additional PM precursor species are needed as emissions input which includes 

SO2, NH3, SO4, NO3, EC, OMC, other primary PM2.5 and coarse PM (PM2.5-10). 

A preliminary 36/12/4 km emissions inventory for the June-July 2006 episode will be developed 

by December 2007 to allow model testing and evaluation. To meet this ambitious schedule the 

focus will be on the 2006 emissions in the 4 km Colorado domain. The preliminary inventory 

will use the SMOKE-MOBILE6 module for on-road mobile source emissions everywhere, 

whereas a refined 2006 on-road mobile source emissions inventory for the DMA will be 

developed using CONCEPT by February 2008. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 

Table 5-2. Emissions model configurations.

Emissions Component Configuration Details Model Code 

SMOKE Versions 2.3 CONCEPT Version .60 MEGAN 

www.cmascenter.orghttp://www.conceptmodel.orghttp://bai.acd.ucar.edu/Megan/

Horizontal Grid Mesh 36/12/4 km  36 km grid 148 x 112 cells  12 km grid 167 x 92 cells  4 km grid 119 x 119 Area Source Emissions 

2006 CDPHE/APCD for Denver NAA Projected 2002 RPO outside Denver NAA SMOKE processing 

On-Road Mobile Sources 

Denver TDM CONCEPT and MOBILE6 SMOKE-MOBILE6 outside of Denver 

CONCEPT processing of link-based TDM data County HPMS VMT and SMOKE-MOBILE6 out

Point Sources 

2006 day-specific CEM Projected 2002 RPO outside Denver 

Use 2006 day-specific hourly CEM for actual anTypical 2006 emissions 

Off-Road Mobile Sources 

2006 CDPHE/APCD for Denver NAA Projected 2002 RPO outside Denver NAA 

Emissions Data Sources 2006 CDPHE/APCS for Denver NAA 

2002 Plan02b WRAP States Project to 2006 

2002 Base G CENRAP States Project to 2006 

2002 Base M MRPO States Project to 2006 2002 Base G VISTAS States Project to 2006 2006 TDM VMT for Denver NAA Process with CONCEPT-MOBILE6 

2006 HPMS for outside Denver NAA Process with SMOKE-MOBILE6 

Updated Oil and Gas production emissions 

WRAP Phase II inventory for 2005 and western CDPHE/APCD permits for Colorado (2006) IPAMS 2005 O&G update for eastern Colorado 

Acid Rain Database for CEM data Large stationary source NOx and SO2 WRAP Wind Blown Dust (WBD) WRAP WBD Model with 2006 MM5 meteorolog

WRAP Ammonia 

WRAP NH3 Model with 2006 MM5 meteorology data 

Biogenic Sources MEGAN Temporal Adjustments Seasonal, day, hour Based on latest collected information Chemical Speciation Revised CB05 Chemical Speciation EPA updated in 2007 Gridding Spatial Surrogates based on landuse Growth and Controls TBD 2010 and 2020 future years Quality Assurance 

QA Tools in SMOKE and CONCEPT; PAVE plots; Summary reports 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-8

5.2.2.1 Day-Specific On-Road Mobile Source Emissions 

The inputs needed to perform on-road mobile sources modeling for the Denver June-July 2006 

modeling period on the 36/12/4 km grids include the county-level 2006 vehicle miles traveled 

(VMT) for the entire modeling domain (36-km grid) and the link-based VMT for the urbanized 

portion of the Denver area from a travel demand model (TDM). In addition to the link-based 

VMT data, GIS-based data specifying the locations of the links from transportation modeling are 

required. Two different emission models will be used to generate on-road mobile source 

emissions, SMOKE-MOBILE6 for the entire 36/12/4 km modeling domain, and CONCEPTMOBILE6 for the portion of the DMA that is covered by the link-based TDM VMT data. 

5.2.2.1.1 SMOKE On-Road Mobile Emissions for 36/12/4 km Domains

The SMOKE-MOBILE6 emissions model would be used to generate on-road mobile source 

emissions for the entire 36/12/4 km grids using the 2006 county-level VMT, 2006 MOBILE6 

inputs and gridded surrogates. 

5.2.2.1.2 CONCEPT On-Road Emissions for the DMA

The Consolidated Community Emissions Processing Tool Motor Vehicle (CONCEPT MV) 

emissions model will be used to estimate link-level on-road emissions and then grid them for the 

model input. DRCOG will provide ENVIRON with 2005 TransCAD model output for the 

DMA. The data provided will be link-specific capacities, volumes, and speeds for a typical 

weekday for the 10 time periods in each day in the TransCAD model (3 morning peak, 3 

afternoon peak, and 4 off-peak time). CONCEPT MV will disaggregate the TDM results for the 

10 time periods of the day, and estimate hourly link volumes for weekend days, using total 

volume temporal profiles by roadway type to be derived by ENVIRON from analysis of 

Colorado Department of Transportation (CDOT) automated traffic recorder (ATR) monitoring 

data. CONCEPT MV will then estimate the congested speeds for each link for each hour using 

the hourly volume/capacity ratios and a formula to be provided by DRCOG. Total volume for 

each link for each hour will be disaggregated into eight vehicle classes using temporal profiles 

for VMT mix to be derived by ENVIRON from analysis of CDOT vehicle classification 

monitoring data as well as a special study of Denver-area roadways VMT mix data recently 

compiled. 

CONCEPT MV is a database application and computing resource intensive. Not all days in the 

June-July 2006 time period will be run. Rather, ENVIRON will work with CDPHE to define the 

set of days to be run through CONCEPT MV (e.g., Key high ozone days). The CONCEPT 

output is gridded CAMx-ready emissions. 

5.2.2.2 Episodic Biogenic Source Emissions 

Biogenic emissions will be generated using the MEGAN biogenic emissions model. MEGAN 

uses high resolution GIS data on plant types and biomass loadings and the MM5 surface 

temperature fields, and solar radiation (modeled or satellite-derived) to develop hourly emissions 

for biogenic species on the 36/12/4 km grids. MEGAN generates gridded, speciated, temporally 

allocated emission files. One feature that is included in MEGAN is that it generates biogenic 

VOC precursor emission species for the new secondary organic aerosol (SOA) module in 

CAMx. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-9

5.2.2.3 Point Source Emissions 

2006 point source emissions for the Denver NAA will be provided by CDPHE/APCD. Outside 

of the Denver NAA point sources will be developed in two categories – CEM and non-CEM 

point source emissions. For point sources with continuous emissions monitoring (CEM) data 

day-specific hourly NOx and SO2 emissions will be used for the 2006 Actual base case 

emissions scenario. The VOC, CO and PM emissions for point sources with CEM data would be 

based on the hourly heat input. The locations of the point sources will be converted to the LCP 

coordinate system used in the modeling. They will be processed by SMOKE to generate the 

temporally varying (i.e., day-of-week and hour-of-day) speciated emissions needed by CAMx, 

using standard SMOKE default profiles by source category. 

For large point sources with CEM data, we would also developed typical summer emissions for 

when the source is operating representative of the 2005-2007 planning period that would be used 

for the 2002 Typical base case. The CAMx results for the 2006 Actual base case are compared 

against the 2006 measurements in the model performance evaluation, whereas the CAMx results 

for the 2006 Typical base case are used with the 2010 CAMx results for the 8-hour ozone Design 

Value projections. 

For point source emissions without CEM data, the 2006 emissions inventory will be represented 

by the existing 2005 point source inventory projected from the RPO 2002 over the 12/36K 

modeling domain. The portions of the 4 km domain not covered in the Denver NAA will be 

adjusted to 2006 using Colorado specific projection factors developed in conjunction with 

CDPHE/APCD 

5.2.2.4 Area and Non-Road Source Emissions 

County level area source emissions have been taken from the RPO 2002 emissions inventory and 

projected to 2005 and will be used for the 2006 inventory for the 36/12 km domains. 

CDPHE/APCD will provide 2006 area and non-road emissions for the Denver NAA. The 

portions of the 4 km domain not covered in the Denver NAA will be adjusted to 2006 using 

Colorado specific projection factors developed in conjunction with CDPHE/APCD 

The area and non-road sources will be spatial allocated to the grid using an appropriate surrogate 

distribution (e.g., population for home heating, etc.). In the 4 km domain, specialized spatial 

surrogates will need to be developed to account for the split of Larimer and Weld counties 

between the attainment and non-attainment areas. The area sources will be temporally allocated 

by month and by hour of day using the SMOKE default source-specific temporal allocation 

factors. 

The SMOKE source-specific temporal and CBO5 speciation allocation profiles will be used. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-10

5.2.2.5 Wildfires, Prescribed Burns, Agricultural Burns 

 

If there are indications of any fires present near the Denver area that may affect ozone air quality 

during June-July 2006 they will be accounted for in the model as information, resources and time 

are available. We have performed an initial survey of the reporting of fires during the modeling 

period as documented on the National Fire and Aviation Management website (FAMWEB; 

http://fam.nwcg.gov/fam-web/). The occurrence of reported fires within the 4 km Colorado grid 

by 20 day increments during the modeling period are shown in Figure 5-1. The only fire 

reported near the DMA during the June-July 2006 modeling period was in southwestern 

Jefferson County during the first quarter of the modeling period (May 25-June 15). This period 

includes one of the nine 8-hour ozone exceedance days during the modeling period. This 

exceedance day (June 12, 2006) was a minor exceedance day with measured exceedances 

occurring only at the Fort Collins West monitor far north of the reported fire that is southwest of 

the DMA. This preliminary analysis suggests that emissions from fires did not play a pivotal 

role in the 2006 summer’s ozone exceedances in the DMA and vicinity. Further analysis is 

needed to verify this, but if true then emissions from fires may not need to be modeled. 

Figure 5-1. Occurrence of reported wildfires in Colorado during the June-July 2006 modeling period 

broken down by May 25-June 15 (top left), June 10-30 (top right), June 25-July 15 (bottom left) and 

July 10-July 31, 2006 (bottom right).
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-11

5.2.2.6 QA/QC and Emissions Merging 

The emissions will be processed by major source category in several different “streams”, 

including area sources, on-road mobile sources, non-road mobile sources, biogenic sources, nonCEM point sources, CEM point sources using day-specific hourly emissions (Actual), CEM 

sources using average emissions (Typical) and, as available, emissions from fires. Separate 

Quality Assurance (QA) and Quality Control (QC) will be performed for each stream of 

emissions processing and in each step. SMOKE includes advanced quality assurance features 

that include error logs when emissions are dropped or added. In addition, we will generate visual 

displays that include: 

• Spatial plots of the hourly emissions for each major species (e.g., NOx, VOC, 

some speciated VOC, SO2, NH3, PM and CO); 

• Vertical average emissions plots for major species and each of the grids; 

• Diurnal plots of total emissions by major species; and 

• Summary tables of emissions for major species for each grid and by major source 

category. 

This QA information will be examined against the original point and area source data and 

summarized in an overall QA/QC assessment. 

Scripts to perform the emissions merging of the appropriate biogenic, on-road, non-road, area, 

low-level, fire, and point emission files will be written to generate the CAMx-ready twodimensional day-specific hourly speciated gridded emission inputs. The point source and, as 

available elevated fire, emissions would be processed into the day-specific hourly speciated 

emissions in the CAMx-ready point source format. 

The resultant CAMx model-ready emissions will be subjected to a final QA using spatial maps, 

vertical plots and diurnal plots to assure that: (1) the emissions were merged properly; (2) CAMx 

inputs contain the same total emissions; and (3) to provide additional QA/QC information. 

5.2.3 Use of the Plume-in-Grid (PiG) Subgrid-Scale Plume Treatment

The Plume-in-Grid (PiG) sub-model treats the early plume chemistry and dynamics of emissions 

from point sources and then releases the emissions into the grid model farther downwind at such 

time that the plume is adequately resolved by the grid. There are currently two PiG options in 

the CAMx model: 

• GREASD PiG: The Greatly Reduced Execution and Simplified Dynamics 

(GREASD) Plume-in-Grid (PiG) module treats the early plume dynamics and 

inorganic NOx chemistry, and releases the emissions from the PiG to the grid 

model when organic chemistry starts being important; and 

• IRON PiG: The Incremental Reactions for Organics and NOx PiG module treats 

the full chemistry at all downwind distances. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-12

The GREASD PiG was designed for large NOx point source plumes, where the early evolution 

of the plume is dominated by NOx and inorganic chemistry. Because of the high NOx in these 

plumes, the mass they carry are typically released to the grid model at the time that organic 

chemistry becomes important. 

The IRON PiG uses full chemistry and is appropriate for both NOx and VOC plumes. Currently 

the CAMx model can only use one PiG module in each run (i.e., it cannot run point source X 

with GREASD PiG and point source Y with IRON PiG in the same run). 

Large NOx plumes will be selected for treatment by the subgrid-scale PiG module. The 

selection of which sources to be treated by the PiG module will be made after a review of the 

inventory. Tests may be conducted to determine the sensitivity of the ozone estimates in the 

Denver area to the use of the different PiG modules. 

5.2.4 Products of the Emissions Inventory Development Process

In addition to the CAMx-ready input files generated for each hour of all days modeled in the 

Denver June-July 2006 modeling period, a number of quality assurance (QA) files will be 

prepared and used to check for gross errors in the emissions inputs. Importing the model-ready 

emissions into PAVE and looking at both the spatial and temporal distribution of the emission 

provides insight into the quality and accuracy of the emissions inputs. 

• Visualizing the model-ready emissions with the scale of the plots set to a very low value, 

we can determine whether there are areas omitted from the raw inventory or if emissions 

sources are erroneously located in water cells; 

• Spot-checking the holiday emissions files to confirm that they are temporally allocated 

like Sundays; 

• Producing pie charts emission summaries that highlight the contribution of each 

emissions source component (e.g. nonroad mobile); 

• Normalizing the emissions by population for each state will illustrate where the 

inventories may be deficient and provide a reality check of the inventories. 

State inventory summaries prepared prior to the emissions processing will be used to compare 

against SMOKE output report totals generated after each major step of the emissions generation 

process. To check the chemical speciation of the emissions to CB05 species, we will compare 

reports generated with SMOKE to target these specific areas of the processing. For speciation, 

the inventory state import totals will be compared against the same state totals with the 

speciation matrix applied. 

The quantitative QA analyses often reveal significant deficiencies in the input data or the model 

setup. It may become necessary to tailor these procedures to track down the source of each 

major problem. As such, one can only outline the basic quantitative QA steps that we will 

perform in an attempt to reveal the underlying problems with the inventories or processing. 

Following are some of the reports that may be generated to review the processed emissions: 

• State and county inventory totals for each source category. 

• State and county totals after spatial allocation for each source category. 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-13

• State and county totals by day after temporal allocation for each source category for 

representative days. 

• State and county totals by model species after chemical speciation for each source 

category. 

• State and county model-ready totals (after spatial allocation, temporal allocation, and 

chemical speciation) for each source category and for all source categories combined. 

• If elevated source selection is chosen by user, the report indicating which sources have 

been selected as elevated and plume-in-grid will be included. 

• Totals by source category code (SCC) from the inventory for area, mobile, and point 

sources. 

• Totals by state and SCC from the inventory for area, mobile, and point sources. 

• Totals by county and SCC from the inventory for area, mobile, and point sources. 

• Totals by SCC and spatial surrogates code for area and mobile sources. 

• Totals by speciation profile code for area, mobile, and point sources. 

• Totals by speciation profile code and SCC for area, mobile, and point sources. 

• Totals by monthly temporal profile code for area, mobile, and point sources. 

• Totals by monthly temporal profile code and SCC for area, mobile, and point sources. 

• Totals by weekly temporal profile code for area, mobile, and point sources. 

• Totals by weekly temporal profile code and SCC for area, mobile, and point sources. 

• Totals by diurnal temporal profile code for area, mobile, and point sources. 

• Totals by diurnal temporal profile code and SCC for area, mobile, and point sources. 

• PAVE plots of gridded inventory pollutants for all pollutants for area, mobile, and point 

sources. 

5.2.5 Future-Year Emissions Modeling

Future-year emission inputs will be generated by SMOKE by projecting the current year (e.g., 

2006) inventory using growth and control factors. Growth and control factors representative of 

Colorado and the DMA would be determine with input from the RAQC, CDPHE/APCD and 

modeling team.

5.3 Photochemical Modeling Inputs 

5.3.1 CAMx Science Configuration and Input Configuration

This section describes the model configuration and science options to be used in the Denver 8-

hour ozone modeling effort. Table 5-3 summarizes the CAMx configuration to be used. The 

latest version of CAMx (Version 4.5) will be used in the Denver modeling. The model will be 

configured to predict both ozone and PM species. 

As indicated in the CAMx model setup defined in Table 5-3, three grids will be employed. 

CAMx would be initially run for the 2006 base case on the 36 km continental U.S. grid for the 

May 25 through July 31, 2006 period and output three-dimensional concentrations of all modeled 
F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 5-14

species. The 36 km continental U.S., CAMx outputs would be processed to define hourly initial 

concentrations (ICs) for June 1, 2006 and boundary conditions (BCs) for June 1 through 

July 31, 2006 period and the 12 km grid. CAMx would then be run for the 2006 Actual base 

case on the 12/4 km grid using two-way interactive grid nesting and the IC/BC from the 36 km 

CAMx simulation. The PPM advection solver will be used along with the spatially varying 

(Smagorinsky) horizontal diffusion approach. K-theory will be used for vertical diffusion. 

The CB05 gas-phase chemical mechanism is selected because it includes the very latest chemical 

kinetic rates and represents improvements over the CBM-IV and SAPRC99 chemical 

mechanisms. Additional CAMx inputs will be as follows: 

Meteorological Inputs: The MM5-derived meteorological fields will be prepared for 

CAMx using MM5CAMx. Several alternative vertical diffusivity options will be 

generated for CAMx input and evaluated in sensitivity tests, as described earlier. 

Initial/Boundary Conditions: The IC/BC for the 36 km continental U.S. simulation would 

be based on the latest available information. Currently the RPOs are using IC/BC for the 

same domain based on a 2002 GEOS-CHEM global chemistry model simulation. We are 

aware of the availability of 2006 MOZART global model output that may be used to 

define BCs for the outer 36 km modeling domain. A processor will need to be written to 

interpolate from the MOZART horizontal and vertical coordinate system to the CAMx 

LCP coordinate system and map the MOZART chemical species to the CB05 chemical 

mechanism. 

Photolysis Rates: The modeling team will prepare the photolysis inputs as well as 

albedo/haze/ozone/snow inputs for CAMx based on Total Ozone Mapping Spectrometer 

(TOMS) data. For CAMx the TUV processor will be used. If there are periods of more 

than a couple of days where daily TOMS data are unavailable, monthly average TOMS 

data will be used. 

Landuse: The team will generate landuse fields based on USGS GIRAS data and localspecific land use data available from the APCD. 

Spin-Up Initialization: Five days of spin up will be specified (May 25-30, 2006) using 

the 36 km continental U.S. configuration before the first day of the modeling period (June 

1, 2006). The first 8-hour ozone exceedance day in the Denver area is June 12 which 

gives us 17 days of spin up on the 36 km grid and 11 days of spin up on the 12/4 km grid, 

which should be more than sufficient. 
 Table 5-3. CAMx (Version 4.5) model configuration. 

Science Options Configuration Details Model Code CAMx (v4.5) – 2007 Release Available at: www.camx.comHorizontal Grid Mesh 36/12/4 km  36 km grid 148 x 112 cells One-way nest with 12 km grid  12 km grid 167 x 92 cells BCs from 36 km run  4 km grid 119 x 119 Two-way nesting with 12/4 km gridVertical Grid Mesh 19 vertical layers, defined by MM5 Layer 1 thickness ~ 35 m Grid Interaction 36/12 km one-way and 12/4 km two-way nestingInitial Conditions Default – 5 day spin-up on 36 km grid Boundary Conditions 36 km TBD; 12 km from 36 km simulation Monthly average diurnally varying 

available for 36 km grid 

Emissions  Baseline Emissions Processing SMOKE  Sub-grid-scale Plumes Plume-in-Grid for major NOx sources and potentially VOC sources GREASD-PiG NOx chemistry plum

IRON-PiG full chemistry plume mo

Chemistry  Gas Phase Chemistry CB05 Latest chemical reactions and kineMeteorological Processor MM5CAMx Compatible with CAMx v4.5 Horizontal Diffusion Spatially varying K-theory with Kh grid size dependeVertical Diffusion Kv (O'Brien '70, CMAQ, TKE methods) Sensitivity tests to Kz methods  Diffusivity Lower Limit Kz-min = 0.1 to 1.0 m2/s Run MM5CAMx with Kz_min = 0.1 

Kz_min 

Deposition Schemes  Dry Deposition Wesley resistance scheme Wesley (1989)  Wet Deposition CAMx-specific formulation rain/snow/graupel Numerics  Gas Phase Chemistry Solver Chemical Mechanism Compiler-- Fast Solver ENVIRON (2006)  Vertical Advection Scheme Fully implicit scheme  Horizontal Advection Scheme Piecewise Parabolic Method (PPM) scheme Integration Time Step Wind speed dependent ~0.5-1 min (4-km), 1-5 min (12-km

F:\Denver_O3_2008\Protocol\draft#2\Sec5_Inputs1.doc 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-1 

6.0 MODEL PERFORMANCE EVALUATION 

This chapter describes the model performance evaluation from which to establish reliable CAMx 

8-hour ozone modeling for the Denver area. In general terms, this process consists of the 

following cycle: 

• Exercise the modeling system for the base case, attempting to replicate the time and 

space behavior of the observed 1-hour and 8-hour ozone concentration fields as well 

as concentrations of precursor and product species; 

• Evaluate the model’s fidelity in simulating ozone and precursor/product species using 

a two-step process consisting of: (a) an initial “screening model performance 

evaluation” (SMPE) process, and if the modeling results pass the screening analysis, 

(b) a “refined model performance evaluation” (RMPE) consisting of progressively 

more stressful testing procedures involving multi-species, multi-scale surface and 

aloft model performance evaluation (MPE); 

• Identify sources of error and/or compensating biases, through evaluation of 

preprocessor models (MM5, SMOKE, CONCEPT, MEGAN), air quality model 

inputs, concentrations aloft, mass budgets and conservation, process analysis, etc; 

• Through a documented process of diagnostic and sensitivity investigation, pinpoint 

and correct the performance problems via model refinement, additional data 

collection and/or analysis, or theoretical considerations; 

• Re-run the model for the base case and re-evaluate performance until adequate, 

justifiable performance is achieved or the modeling period is declared unsuited for 

further use based on documented performance problems. 

To an extent, some or all of these steps will be taken by the modeling team for the June-July 

2006 period ideally culminating in a modeling database demonstrated to exhibit sufficiently 

minimal bias and error that they may be used reliably to evaluate 8-hour ozone control strategies 

and to perform an 8-hour ozone attainment demonstration. In the following subsection, we 

briefly identify the steps that will be taken by the modeling team in constructing and evaluating 

the CAMx base cases for 8-hour ozone SIP development in Denver. 

6.1 Establishing Base Case CAMx Simulations for Denver 

6.1.1 Setting Up and Exercising CAMx Base Cases

The modeling team will select the final model configurations for the CAMx base case simulation 

for June-July 2006 (see Chapter 5). The modeling team will define the recommended final 

model configurations based on results from the initial configuration runs (see Tables 5-1 through 

5-4) and a series of model sensitivity tests. The series of model sensitivity tests will be 

conducted for the July 20-30, 2006 period on the 4 km grid to identify the optimal MM5 

meteorological, SMOKE/CONCEPT/MEGAN emissions and CAMx air quality model 

configurations for simulating ozone formation in the Denver area. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-2 

The optimal model configurations will be identified based on the following factors: 

• Model performance obtained using the initial model configurations and input data; 

• Model performance for base case sensitivity tests; 

• The modeling team’s knowledge of the CAMx model configurations and associated 

attributes; 

• Experience performing sensitivity tests and model performance evaluation for the 

Denver 8-hour ozone EAC SIP, New Mexico 8-hour ozone EAC SIP, FCAQTF 

CAMx, BLM EIS CAMx and CMAQ, WRAP, CENRAP, VISTAS, MRPO, and 

numerous other modeling studies carried out by the modeling team; and 

• Comments from RAQC, APCD, EPA, Stakeholders and other participants. 

The objective in identifying optimum model configurations is to obtain the best performance for 

the right reasons consistent with sound science and EPA guidance. Sometimes, decisions must 

be made that trade off better/poorer model performance for one pollutant against another. For 

example, although the focus of the model evaluation is on ozone and ozone precursor and 

product species, we will also evaluate the model for PM2.5, PM species (e.g., SO4, NO3, NH4, 

EC, OMC, Soil and CM), deposition and visibility but the primary focus will be for ozone. 

These factors will be considered and potential issues discussed among the modeling team, 

RAQC, APCD, EPA and others. Based on the analysis and comments from RAQC, APCD, EPA 

and other interested parties, the modeling team will select the final model configurations. 

6.1.2 Use of Sensitivity, Source Apportionment, and Related Diagnostic Probing Tools

The Denver ozone study may utilize several diagnostic and probing tools to further test and 

understand the CAMx base case ozone simulations. The use of these tools is discussed below. 

Traditional Sensitivity Testing: Traditional sensitivity testing will be performed using 

the CAMx model. Once each model is operating properly for each base case, sensitivity 

runs may be performed to explore response to emissions changes as well as changes in 

key input parameters. These sensitivity runs serve two purposes: 

• To assist in improving model performance; 

• Aid in helping to define appropriate emissions control scenarios; and 

• Provide episode-specific model uncertainty information that may be used later in 

“Weight of Evidence” analyses in support of the 8-hour ozone attainment 

demonstration. 

Ozone Source Apportionment: Focused use of ozone source apportionment technology 

(OSAT) for selected episodes may be employed to better understand model response and 

to aid in the design of control strategies. Source apportionment modeling will be 

conducted for subsequent stages of the Denver modeling study for the 2010 emission 

scenario and these calculations will help to: 

• Assess the contribution of sources in the Denver NAA, Colorado and surrounding 

areas to ozone concentrations at key Denver receptor locations; and 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-3 

• Identify the particular source categories that may contribute the most to elevated 

8-hour ozone concentrations in the Denver NAA. 

DDM Sensitivity Modeling: Another type of sensitivity that may be performed entails 

the use of the Direct Decoupled Method (DDM) technology in CAMx. DDM may be set 

up and exercised for a potion of the Denver modeling period to produce a numerically 

intensive, direct sensitivity/uncertainty analysis. DDM can provide information on the 

sensitivity of ozone to model inputs (e.g., IC, BC, specific emissions). For example, it 

was used in the Houston area to identify where locations of potential highly reactive 

VOC emissions would be that could explain the rapid rise in ozone at a particular time 

and location (i.e., assuming that VOC emissions are missing from the inventory, what 

emissions locations would best explain observed high ozone levels?). 

Process Analysis: Process Analysis is a tool in CAMx to extract additional information 

about the various physical and chemical processes in the model that produced the ozone 

concentrations. Information on VOC-limited versus NOx-limited ozone formation, 

importance of local production versus entrainment of ozone aloft and identification of the 

contributions of individual VOC species to ozone formation are the types of information 

that can be obtained with Process Analysis. It can be a powerful tool for diagnosing the 

causes of poor model performance. 

For the 2006 base case modeling and model performance evaluation, only traditional sensitivity 

tests will be utilized to help improve model performance due to resource and time constraints. 

Source apportionment modeling will be use with the 2010 modeling to assist in control strategy 

development. 

6.2 Evaluation of CAMx Base Cases for the Denver Region 

This section describes the procedures for evaluating the performance of the meteorological and 

photochemical models using the available aerometric data sets for the Denver ozone episodes. 

6.2.1 Overview

Model performance evaluation (MPE) is the process of testing a model’s ability to accurately 

estimate observed atmospheric properties over a range of synoptic and geophysical conditions. 

When conducted thoughtfully and thoroughly, the process focuses and directs the continuing 

cycle of model development, data collection, model testing, diagnostic analysis, refinement, and 

re-testing. Below we summarize the philosophy and objectives that will govern the evaluation of 

the MM5, SMOKE/CONCEPT/MEGAN and CAMx models for the Denver 8-hour ozone 

application. Specific evaluation methods are identified that will be employed to judge the 

suitability of the meteorological and air quality models for regulatory applications, using 

common statistical measures and graphical procedures to elucidate model performance. This 

evaluation plan conforms to the procedures recommended by the EPA (1991; 1999; 2005a; 

2007) for 1-hour and 8-hour ozone attainment demonstration modeling. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-4 

We begin by establishing a framework for assessing whether the 

SMOKE/CONCEPT/MEGAN/MM5/CAMx modeling system (i.e., the emissions, 

meteorological and chemical dispersion models and their supporting data sets) perform with 

sufficient reliability to justify their use in developing 8-hour ozone control strategies for the 

Denver nonattainment area. The models’ reliability will be assessed given consideration to the 

following principals: 

The Model Should be Viewed as a System: When we refer to evaluating a "model", we 

mean this in the broad sense. This includes not only the CAMx photochemical model, 

but its various components: companion preprocessor models (i.e., the SMOKE, 

CONCEPT and MEGAN emissions and the MM5 meteorological models), the 

supporting aerometric and emissions data base, and any other related analytical and 

numerical procedures used to produce modeling results. A principal emphasis in the 

model testing process is to identify and correct flawed model components; 

Model Acceptance is a Continuing Process of Non-Rejection: Over-reliance on explicit 

or implied model "acceptance" criteria should be avoided for the reasons identified by 

Roth et al. (2005). This includes EPA’s ozone performance goals (EPA, 1991). Models 

should be accepted gradually as a consequence of successive non-rejections. Over time, 

confidence in a model builds as it is exercised in a number of different applications 

(hopefully involving stressful performance testing) without encountering major or fatal 

flaws that cause the model to be rejected; 

Criteria for Judging Model Performance Must Remain Flexible: The criteria for judging 

the acceptability of model performance should remain flexible, recognizing the 

challenging requirement of simulating air quality in the Denver Front Range region; and 

Previous Experience Used as a Guide: Previous photochemical modeling experience 

serves as a primary guide for judging model acceptability. Interpretation of the CAMx 

modeling results for each episode, against the backdrop of previous modeling experience, 

will aid in identifying potential performance problems and suggest whether the model 

should be tested further or rejected. 

A rigorous ozone model evaluation in typical regulatory applications consists of two 

components. The operational evaluation entails an assessment of the model’s ability to correctly 

estimate surface meteorological or air quality variables largely independent of whether the actual 

process descriptions in the model are accurate. The operational evaluation essentially tests 

whether the predicted surface meteorological and air quality fields are reasonable, consistent and 

agree adequately with routinely available observations. In this study, the operational evaluations 

focus on the various model’s reliability in reproducing hourly-average surface wind speed, wind 

direction, temperature, mixing ratio and ozone and precursor concentrations within and nearby 

the Denver area. However, we will also evaluate the modeling system for meteorological 

variables, ozone, PM mass, PM species and other species concentrations, deposition and 

visibility across the Colorado 4 km and larger Western U.S. 12 km grid. 

The scientific evaluation addresses the realism of the meteorological and air quality processes 

simulated by the models through testing the model as an entire system (i.e., not merely focusing 

on surface wind, temperature or ozone predictions) as well as its component parts. The scientific 

evaluation seeks to determine whether the model’s behavior, in the aggregate and in its 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-5 

component modules, is consistent with prevailing theory, knowledge of physical processes, and 

observations. The main objective is to reveal the presence of bias and internal (compensating) 

errors in the model that, unless discovered and rectified or at least quantified, may lead to 

erroneous or fundamentally incorrect decisions based on model usage. Ideally, the scientific 

evaluation consists of a series of diagnostic and mechanistic tests aimed at: (a) examining the 

existence of compensatory errors, (b) determining the causes of failure of a flawed model, (c) 

stressing a model to ensure failure if indeed the model is flawed, and (d) providing additional 

insight into model performance beyond that supplied through routine, operational evaluation 

procedures. 

Practically, a rigorous scientific evaluation is seldom feasible due to the absence of the specific 

measurements needed to test the process modules (e.g., soil moisture, Reynold’s stress 

measurements, PBL heights, trace gas species, and so on). Accordingly, the overall model 

performance evaluation in this study is constrained mainly to operational testing of the MM5 

models’ primary meteorological outputs (i.e., wind speed, wind direction, temperature, and 

moisture) and the CAMx model’s predictions of ozone, NOx, CO and potentially VOC, PM 

mass, PM species, visibility and deposition. However, some components of the scientific 

evaluation of the air quality model are possible through examination of ground-level and aloft 

primary and product species and species ratios. In addition, corroborative analyses involving 

joint analysis of emissions inventory estimates, air quality model predictions and ambient 

measurements add to the scientific evaluation.

6.2.2 Meteorological Model Evaluation Methodology

Meteorological inputs required by the CAMx model include hourly estimates of the threedimensional distribution of winds, temperatures, mixing ratio, pressure, clouds, and 

precipitation, and other physical parameters or diagnosed quantities such as turbulent mixing 

rates (i.e., eddy diffusivities) and planetary boundary layer heights. Accordingly, the objective 

of the MM5 performance evaluation is to assess the adequacy of the surface and aloft 

meteorological fields for the Denver ozone modeling episodes. 

6.2.2.1 Components of the Denver MM5 Evaluation 

The MM5 modeling system is well-established with a rich development and refinement history 

spanning more than two decades (Seaman, 2000). The model has seen extensive use worldwide 

by many agencies, consultants, university scientists and research groups. Thus, the current 

version of the model, as well as its predecessor versions, has been extensively "peer-reviewed" 

and considerable algorithm development and module testing has been carried out with all of the 

important process components. Given that the MM5 model code and algorithms have already 

undergone significant peer review, performance testing of the MM5 model in this study will be 

focused on an operational evaluation. Note that further develop of the MM5 model has been 

stopped and development efforts are now focused on Weather Research Forecast (WRF) 

meteorological model. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-6 

Typically, the scope of the scientific evaluation is limited by the availability of special 

meteorological observations (radar profiler winds, turbulence measurements, PBL heights, 

precipitation and radiation measurements, inert tracer diffusion experiments, and so on). 

Unfortunately, since these types of measurements may be limited over Denver during the 

modeling episode, a meaningful scientific evaluation of the MM5 may not be possible in this 

study. However, if the operational evaluation presented in subsequent chapters is performed 

thoroughly, they are expected to be sufficient to serve as the basis for judging whether the model 

is operating with sufficient reliability over the Denver domain to be used in the photochemical 

modeling portion of this study. 

6.2.2.2 Data Supporting Meteorological Model Evaluation 

Hourly surface meteorological observations will be obtained from the National Center for 

Atmospheric Research and other sources to support the evaluation of MM5 near-surface 

temperature, water vapor, and wind speed fields. The specific NCAR data set used for this 

purpose is DS472.0 which is the hourly airways surface data. The primary data set available for 

comparing model performance aloft is the NOAA Forecast Systems Lab and National Climatic 

Data Center’s Radiosonde Data of North America. These data sets will be collected in 

performing the Denver MM5 model evaluation. For precipitation the Climate Prediction Center 

historical archives will be used. 

6.2.2.3 Evaluation Tools 

The primary tool used for evaluating the MM5 meteorological model in air quality modeling 

study is the METSTAT program developed by ENVIRON. METSTAT calculates a suite of 

model performance statistics using surface wind speed, wind direction, temperature and water 

vapor mixing ratio for use specified subdomains. Tables 6-1 and 6-2 list some of the model 

performance evaluation metrics to be used in evaluating the MM5 model. We will use both 

regional as well as local subdomains in the METSTAT analysis. Regional domains would 

include those used by WRAP (Kemball-Cook et al., 2005), CENRAP (Johnson, 2007) and others 

so that the Denver MM5 performance can be compared with other MM5 performance in the 

same subdomains to help put the results into context and against meteorological model 

performance benchmarks (Emery, Tai and Yarwood, 2001). Local domains would include the 

Denver area and possibly even more refined subdomains. The evaluation of the MM5 aloft 

meteorological estimates with upper-air observations would be accomplished using the RAOBS 

program developed by the State of Iowa (Johnson, 2007). Additional comparisons of the spatial 

patterns of precipitation and clouds may also be made using satellite and radar-based data. 

6.2.3 Photochemical Model Evaluation Methodology

The CAMx performance evaluations will follow the procedures recommended in the EPA 

photochemical modeling guidance documents (EPA, 1991; 1999; 2005a; 2007). The evaluation 

will be carried out in two sequential phases, beginning with the simplest comparisons of 

modeled and observed ground-level ozone concentrations, progressing to potentially more 

illuminating analyses if necessary (e.g., examination of available precursor and product species, 

comparisons of pollutant ratios and groupings, comparison against PM species, deposition and 

visibility). That is, the specific two-step ozone evaluation process is: 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-7 

• An initial “screening model performance evaluation” (SMPE) process, and if the 

modeling results pass the screening analysis; 

• A “refined model performance evaluation” (RMPE) consisting of progressively more 

stressful testing procedure involving multi-species, multi-scale surface and aloft MPE; 

Below we describe how this evaluation will be conducted. The formal procedures outlined in 

EPA recent 8-hour modeling guidance (EPA, 2007) will be used to evaluate CAMx for the 

Denver modeling episode. The modeling team will consider all six means for assessing 

photochemical model performance as specified in the draft guidance are as follows: 

• Use of computer generated graphics; 

• Use of ozone metrics in statistical comparisons; 

• Comparison of predicted and observed precursor emissions or species concentrations; 

• Comparison of observed and predicted ratios of indicator species; 

• Comparison of predicted source category contribution factors with estimates obtained 

using observational models as available; and 

• Use of retrospective analyses in which air quality differences predicted by the model are 

compared with observed trends. 

Obviously, a comprehensive measurement database for ozone and precursors from an extensive 

monitoring network is needed to fully support all six of these analyses. This may not be possible 

with the current air quality data collected in the Denver area, particularly in regards to precursor 

measurements, since limited measurements were conducted in this area during the proposed 

modeling period. During 2006 there were two routine monitoring sites collected NO2 

measurements (Denver CAMP and Welby) and 13 monitors for CO. 

We are aware of three “field study” campaigns in the general Denver area during 2006 that may 

provide additional data to evaluate the modeling system: 

• The CDPHE/APCD collected VOC samples during 2006 that will assist in evaluating this 

important ozone precursor. Most VOC samples were collected in the morning (6-9am 

MDT) with samples for the following sites available during some days of the June-July 

2006 modeling episode: 

o CAMP 

o Welby 

o Fort Lupton 

o Platteville 

o Rocky Flats North 

o Fort Collins West 

• During portions of 2006, NOAA launched daily ozonesondes at numerous sites 

throughout the U.S., including Boulder. The ozonesonde measurements will provide 

valuable information on the vertical structure of ozone concentrations, including the 

potential identification of an ozone reservoir aloft. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-8 

• Finally, the NPS and CDPHE collected special measurements as part of the ROMANS 

study during 2006. 

The modeling team is in the process of acquiring this special study so they can assess their own 

usefulness in the Denver ozone study model performance evaluation. To the extent possible, 

each of the performance procedures described by EPA’s 8-hour guidance will be addressed, and 

at a minimum, an explanation of why certain components cannot be fulfilled will be provided. 

Initial screening of the CAMx base case ozone predictions (i.e., the SMPE) will be performed 

for the initial base case and each sensitivity test in an attempt to identify obviously flawed model 

simulations and to implement and identify improvements to the model input files in a logical, 

defensible manner. The screening SMPE will employ some of the more appropriate ozone 

performance statistics and plots listed in Table 6-3. Examples of the types of graphical displays 

that may be helpful in the SMPE include the following for both 1-hour and 8-hour ozone 

concentrations: 

• Spatial mean ozone time series plots; 

• Ozone time series plots; 

• Ground-level ozone isopleths; 

• Ozone concentration scatter plots; 

• Bias and error stratified by concentration; and 

• Bias and error stratified by time. 

Experience in photochemical modeling is the best basis upon which to identify obviously flawed 

simulation results. Efforts to improve photochemical model performance, where necessary and 

warranted (i.e., to reduce the discrepancies between model estimates and observations), should 

be based on sound scientific principles. A "curve-fitting" or "tuning" activity is to be avoided. 

The following principals will govern the model performance improvement process (to the fullest 

extent possible given the project schedule): 

• Any significant changes to the model or its inputs must be documented and discussed 

with key participants (e.g., RAQC, APCD, EPA); 

• Any significant changes to the model or its inputs must be supported by scientific 

evidence, analysis of new data, or by re-analysis of the existing data where errors or 

misjudgments may have occurred; and 

• All significant changes to the model or its inputs should be reviewed by the project 

sponsors and/or other advisory group(s). 

If the initial screening of the CAMx ozone results does not reveal obvious flaws, the refined 

model performance evaluation will be carried out. If significant performance issues are 

uncovered in the SMPE, further model diagnosis and quality assurance of the input files and 

related model performance improvement analyses will be performed. That is, the full refined 

model performance evaluation will not be carried out on obviously flawed model simulations as 

it would be wasteful of project resources and schedule. 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-9 

Assuming the SMPE is satisfactory, the formal operational evaluation in the RMPE will 

commence. First, the graphical displays utilized previously for ozone may be generated for 

NOx, VOC, and key product species (e.g., HNOx, PAN) as available. Note that model 

performance for VOC and many product species may be limited since there are little relevant 

ambient measurements collected in the Denver area. But even so, the graphical displays for 

ozone precursor and product species will be examined for obvious flaws that may be readily 

apparent even in the absence of measurements. Should these be detected, the model diagnosis 

and performance improvement efforts may be needed to fully identify, correct (if possible) and 

document the noted problems. Table 6-4 lists performance evaluation techniques for a RMPE. 

Second, diagnostic analysis and testing, including a limited number of model sensitivity and/or 

uncertainty simulations, will likely be performed to help elucidate model performance and 

response to changes in key inputs. Sensitivity analysis, often an important component of the 

evaluation process, will be performed to aid in understanding the air quality model’s response to 

key input parameter uncertainties. They provide evidence that the model is responding as 

expected relative to local understanding of the conditions leading to high ozone (i.e., conceptual 

models). The extent to which sensitivity simulations with CAMx will be needed can only be 

assessed after the initial model evaluations are performed. With the advent more sophisticated 

one-atmosphere models, certain sensitivity runs historically carried out older models (e.g., UAM 

family) are no longer feasible, needed, or appropriate (e.g., zero IC/BC or zero-emissions runs). 

Other, more insightful and physically meaningful experiments are used (e.g., NOx and VOC 

emission changes, vertical eddy diffusivity and grid changes, alternative chemistry mechanisms, 

alternative meteorological realizations, etc.). 

Emission sensitivity tests are particularly relevant as they provide: (1) a reality check that the 

model is responding as expected; (2) information on which emission source components are 

important; and (3) initial quantification of potential impacts of controls. 

Sensitivity experiments will be conduced as part of the CAMx model performance evaluation 

analysis to assist in identifying the optimal model configurations for simulating ozone formation 

in the Denver area. As noted previously, in order to maximize the potential number of 

sensitivity tests they will focus on the July 20-30, 2006 period and the 4 km grid. However, 

performing sensitivity tests for other model periods may also be performed and the final model 

simulations will be for the full June-July, 2006 modeling period on the 36/12/4 km modeling 

grids. The potential need for and nature of these simulations would be discussed among the 

modeling team and RAQC/APCD after the operational evaluation results have been reviewed. 

6.2.4 Available Aerometric Data for the Evaluations

Limited concentration measurements and meteorological parameters are available for the Denver 

area. These will be used to the fullest extent possible in the evaluation of the MM5 and CAMx 

models. Table 4-4 presented previously discusses the availability of gaseous and particle air 

quality measurements from routine monitoring networks operating in the U.S. Examples of 

available air quality data available for the evaluation are summarized as follows: 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-10 

AIRS Surface Air Quality Data: Data files containing hourly-averaged concentration 

measurements at a wide variety of state and EPA monitoring networks are available in 

the AIRS/AQS database. These data sets will be reformatted for use in the model 

evaluation software. Typical surface measurements at the ground level routine AIRS 

monitoring stations include ozone, NO2, NOx and CO. Figure 4-2 and Table 4-2 

presented previous displays the ozone monitoring sites within and near the Denver NAA. 

IMPROVE Monitoring Network: The National Park Service (NPS) operates an 

IMPROVE monitor at Rocky Mountain National Park (RMNP) that measures PM mass 

and PM2.5 speciation 

Other Monitoring Networks: There may be special air quality measurements collected by 

private industry or public agencies in the area. These include the CDPHE/APCD VOC 

sampling, NOAA ozonesonde and ROMANS studies discussed earlier. The modeling 

team will work with the RAQC and APCD to obtain as much data as are available for the 

model performance evaluation. 

Table 6-1. Statistical measures and graphical displays used in the MM5 operational evaluation. 

Statistical Measure Graphical Display 

Surface Winds (m/s)

Vector mean observed wind speed 

Vector mean modeled and observed wind speeds as a 

function of time 

Vector mean predicted wind speed 

Scalar mean modeled and observed wind speeds as a 

function of time 

Scalar mean observed wind speed 

Modeled and observed mean wind directions as a 

function of time 

Scalar mean predicted wind speed 

Modeled and observed standard deviations in wind 

speed as a function of time 

Mean observed wind direction RMSE, RMSEs, and RMSEu errors as a function of time 

Mean predicted wind direction Index of Agreement as a function of time 

Standard deviation of observed wind speeds 

Surface wind vector plots of modeled and observed 

winds every 3-hrs 

Standard deviation of predicted wind speeds Upper level wind vector plots every 3-hrs 

Standard deviation of observed wind directions 

Standard deviation of predicted wind directions 

Total RMSE error in wind speeds 

Systematic RMSE error in wind speeds 

Unsystematic RMSE error in wind speeds 

Index of Agreement (I) in wind speeds 

SKILLE skill scores for surface wind speeds 

SKILLvar skill scores for surface wind speeds 

Surface Temperatures (Deg-C)

Maximum region-wide observed surface temperature Normalized bias in surface temperature estimates as a 

function of time 

Maximum region-wide predicted surface temperature Normalized error in surface temperature estimates as a 

function of time 

Normalized bias in hourly surface temperature Scatterplot of hourly observed and modeled surface 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-11 

Statistical Measure Graphical Display 

temperatures 

Mean bias in hourly surface temperature Scatterplot of daily maximum observed and modeled 

surface temperatures 

Normalized gross error in hourly surface temperature Standard deviation of modeled and observed surface 

temperatures as a function of time 

Mean gross error in hourly surface temperature Spatial mean of hourly modeled and observed surface 

temperatures as a function of time 

Average accuracy of daily maximum temperature 

estimates over all stations 

Isopleths of hourly ground level temperatures every 3-

hr 

Variance in hourly temperature estimates Time series of modeled and observed hourly 

temperatures as selected stations 

Surface Mixing Ratio (G/kg) 

Maximum region-wide observed mixing ratio Normalized bias in surface mixing ratio estimates as a 

function of time 

Maximum region-wide predicted mixing ratio Normalized error in surface mixing ratio estimates as a 

function of time 

Normalized bias in hourly mixing ratio Scatterplot of hourly observed and modeled surface 

mixing ratios 

Mean bias in hourly mixing ratio Scatterplot of daily maximum observed and modeled 

surface mixing ratios 

Normalized gross error in hourly mixing ratio Standard deviation of modeled and observed surface 

mixing ratios as a function of time 

Mean gross error in hourly mixing ratio Spatial mean of hourly modeled and observed surface 

mixing ratios as a function of time 

Average accuracy of daily maximum mixing ratio Isopleths of hourly ground level mixing ratios every 3-hr 

Variance in hourly mixing ratio estimates Time series of modeled and observed hourly mixing 

ratios at selected stations 

Table 6-2. Statistical measures and graphical displays used in the MM5 scientific evaluation. 

(measures and displays developed for each simulation day). 

Statistical Measure Graphical Display

Aloft Winds (m/s)

Vertically averaged mean observed and predicted 

wind speed aloft for each sounding 

Vertical profiles of modeled and observed horizontal 

winds at each NWS sounding location and at each 

NOAA continuous upper-air profiler location in the 36, 

12, and 4-km grid. 

Vertically averaged mean observed and predicted 

wind direction aloft for each sounding 

Aloft Temperatures (Deg-C)

Vertically averaged mean temperature observations 

aloft for each sounding 

Vertical profiles of modeled and observed 

temperatures at each sounding location 

Vertically averaged mean temperature predictions 

aloft for each sounding 
 F:\Denver_O3_2008\Protocol\draft#2\Sec6_MPE1.doc 6-12 

Table 6-3. Statistical measures and graphical displays for 1-hour and 8-hour ozone concentrations 

to be used in the screening model performance evaluation (SMPE) of CAMx surface ozone 

concentrations. 

Statistical Measure on 36/12/4 km grids Graphical Display on all grids 

Maximum observed concentration 

Modeled and observed spatial mean concentrations as a 

function of time 

Maximum modeled concentration Measures of peak estimation accuracy (ATS, AT, AS, AU, A) 

Maximum modeled concentration at a monitoring 

station Normalized bias as a function of time 

Ratio of maximum modeled to observed 

concentrations Normalized gross error as a function of time 

Accuracy of peak estimation (paired in time and 

space) Normalized bias as a function of concentration level 

Accuracy of peak estimation (unpaired in time and 

space) Normalized gross error as a function of concentration level 

Average accuracy over all stations Scatterplot of hourly concentration pairs 

Normalized bias in hourly concentrations Scatterplot of daily maximum concentration pairs 

Mean bias in hourly concentrations Quartile plots of hourly species concentrations 

Normalized gross error in hourly concentrations Daily maximum ground-level concentration isopleths 

Mean gross error in hourly concentrations 

Variance in hourly concentrations 

Table 6-4. Statistical measures and graphical displays for 1-hour and 8-hour ozone, VOCs, 

NOx, and indicator species and indicator species. Ratios to be used in the refined model 

performance evaluation (RMPE) involving multi-species, multi-scale evaluation of CAMx surface 

and aloft concentrations. 

Statistical Measure on 36/12/4 km grids Graphical Display on all grids 

Maximum observed concentration 

Modeled and observed spatial mean concentrations as 

a function of time 

Maximum modeled concentration 

Measures of peak estimation accuracy (ATS, AT, AS, 

AU, A) 

Maximum modeled concentration at a monitoring 

station Normalized bias as a function of time 

Ratio of maximum modeled to observed 

concentrations Normalized gross error as a function of time 

Accuracy of peak estimation (paired in time and 

space) Normalized bias as a function of concentration level 

Accuracy of peak estimation (unpaired in time and 

space) 

Normalized gross error as a function of concentration 

level 

Average accuracy over all stations Scatterplot of hourly concentration pairs 

Normalized bias in hourly concentrations Scatterplot of daily maximum concentration pairs 

Mean bias in hourly concentrations Quartile plots of hourly species concentrations 

Normalized gross error in hourly concentrations Daily maximum ground-level concentration isopleths 

Mean gross error in hourly concentrations 

Variance in hourly concentrations 

Mean, maximum, minimum, standard deviation, bias 

and error of observed and modeled aloft 

concentrations (e.g., ozone, NOx) along individual 

aircraft paths 

Modeled and observed time series of ozone and 

NOx concentrations along individual aircraft flight paths 
F:\Denver_O3_2008\Protocol\draft#2\Sec7_FY1.doc 7-1

7.0 FUTURE YEAR MODELING 

This chapter discusses the future year modeling procedures to be performed by the modeling 

team for the Denver June through July 2006 ozone modeling period for use in 8-hour hour ozone 

attainment demonstration modeling. Note that the modeling team, RAQC and APCD are still 

developing the approach for performing future-year emission projections and more details will 

be reported in the future. 

7.1 Future Year to be Simulated 

Denver is expected to be designated as a Marginal 8-hour ozone nonattainment area under 

Subpart 2 of the Clean Air Act Amendments (CAAA) in November 2007 and will be required to 

attain the current 8-hour ozone standard by 2010. Thus, the 2010 future year will be modeled for 

the attainment demonstration. 

7.2 Future Year Growth and Controls 

Several RPOs, including WRAP, CENRAP, VISTAS, WRAP and the MRPO, have performed 

refined future year modeling inventories for 2018 and some have also modeled 2009 (VISTAS 

and MRPO) and even 2012 (MRPO). EPA has developed future year inventories for 2010 and 

2015 as part of their CAIR/CAMR analysis. These regional growth and control factors will be 

the starting point for the 2010 future year inventory development augmented by local data as 

available. 

7.2.1 Regional Growth and Control Factors

Coordinating with the WRAP, CENRAP, MRPO, VISTAS, MANE-VU and EPA, the modeling 

team will review and refine national and regional growth factors, MOBILE6 input files, and 

control program reduction estimates that are consistent with Denver’s 2010 future year base case 

for the attainment demonstration. 

The files prepared will include all federally promulgated rules for the 36 km regional-scale 

domain and will be largely based on data prepared by the RPOs (e.g., WRAP, CENRAP, MRPO 

and VISTAS), States (e.g., Colorado) and EPA. This information is based on the latest publicly 

available information from EPA’s federal rulemaking process and at the time of this writing are 

deemed to be the most recent information available on the topic. Each reviewed rule and 

regulation found applicable to the U.S. modeling domain relevant to ozone abatement will be 

documented with cite, geographic coverage, source categories of impact, and associated and 

expected emission reduction potential. Additional synchronization with EPA and WRAP’s sister 

RPOs will be conducted to ensure consistent, if not comparable, application of these programs. 

Using summary files prepared to present this information in an easily reviewable format, the 

modeling team will contact individually identified or otherwise interested regional 

representatives to solicit comment on the originally presented growth and control factors. Upon 

review and comment of these factors, the team will revise the regional growth and control factors 
F:\Denver_O3_2008\Protocol\draft#2\Sec7_FY1.doc 7-2

consistent with the comments collected. The control factor lists will then be compared to the 

base year emission inventory to determine which, if any, of these programs may already 

be accounted for in the emission estimates. The factors will be converted to create a complete 

set of growth and control packets allowing the generation of future year controlled emissions. 

7.2.2 Local Growth and Control Factors

The modeling team will work with the RAQC, CDPHE/APCD and others to develop local 

emissions inventory for the DMA representation of 2010. TDM output of 2010 link-based VMT, 

speeds, fleet distributions, etc. will be used with the MOBILE6 2010 emissions factor in the 

CONCEPT model to generate 2010 on-road mobile source emissions for the DMA. The EPA 

NONROAD model along with the SMOKE emissions model will be used to generate 2010 nonroad emissions for the DMA. Area and point sources will be projected to 2010 using growth and 

control factors reviewed by RAQC and APCD. 2010 oil and gas production emissions will be 

generated for the area. 

7.3 Future Model–Ready Emissions Inventory Development and QA 

Future year emissions will be processed into the gridded speciated hourly three-dimensional 

emissions inputs for the CAMx photochemical model using the SMOKE emissions model for all 

sources except on-road mobile sources in the DMA for which the CONCEPT model will be 

utilized. The same MEGAN (or alternative) biogenic emissions as used in the 2006 base year 

modeling will be used for the future-year modeling. This assumes that the same land use and 

biomass distribution as used in the base case emissions would exist in the future-year emission 

scenarios. The effects of changes in Denver landuse (growth), agriculture, deforestation, etc. 

between the current and future-year would not be accounted for. We are looking at this issue 

more closely to see whether changes in land use can be accounted for in the future year 

modeling. Typical-year EGU and fire emissions (if fires were included in the base year 

emissions scenario) would also be used in the future-year. 

Similar QA/QC will be performed on the future year model-ready emissions inventories as were 

utilized in checking the base year datasets described in Chapter 5. Standard inventory 

assessment methods will be employed to generate the future year emissions data including, but 

not limited to: (a) visualizing the model-ready emissions graphically, (b) spot-checking the 

holiday emissions files to confirm that they are temporally allocated like Sundays, (c) producing 

pie charts emission summaries for each source category, (d) normalizing the emissions by 

population for each state to reveal where the future year inventories may be suspect and (e) spotchecks of the vertical allocation of point sources using PAVE. The additional QA analyses and 

reports that we may find particularly useful for the future year emissions files are given in 

Section 5.2.4. 

7.4 Future Year Baseline Air Quality Simulations 

The Denver future-year modeling will use the MM5 meteorological conditions developed for the 

Denver June-July 2006 modeling period. That is, the meteorological conditions for the futureyear are assumed to be the same as for the 2006 base year ozone episode. This will allow for the 

comparison of the changes in 8-hour ozone concentrations in the study area from the current to 
F:\Denver_O3_2008\Protocol\draft#2\Sec7_FY1.doc 7-3

future-year due to changes in emissions only. This means that the effects of inter-annual 

variability, land use variations and climatic variations will not be accounted for in the future-year 

meteorological inputs. Several other decisions concerning the future-year to be modeled, 

model(s) to be used, and modifications to the model inputs to reflect future years, need to be 

made, as described below. 

7.4.1 Future-Year Initial and Boundary Conditions

The same initial conditions as used in the base year would be used in the future-year modeling. 

Because a minimum 5-day spin up period is being used on the 36 km grid, initial conditions 

should have minimal if any influence on the model estimated concentrations. 

2010 boundary conditions (BCs) for the 2010 CAMx 36 km simulations will be consistent with 

those developed for the 2006 base case modeling discussed in Chapter 5. The exact definition of 

the 2010 BCs for the 36 km domain cannot be specified at this time, but because the relative 

changes in the modeling results between 2006 and 2010 are used then the BCs for the two years 

must be consistent. 

7.4.2 Other Future-Year Modeling Inputs

All other future-year CAMx modeling inputs will be identical to the base year simulation, 

including meteorology, photolysis rates, landuse, and other inputs. Thus, the only changes 

between the 2006 and 2010 CAMx modeling databases will be anthropogenic emissions and 

possibly BCs. 

7.5 Emissions Sensitivity Experiments 

Model sensitivity experiments are a vital and mandatory component of an 8-hour ozone SIP 

attainment demonstration analysis – both for the base case performance assessment (see Chapter 

6) as well as in the future year control strategy assessment and uncertainty analysis. 

Turning specifically to the future year assessments, sensitivity analyses are designed to facilitate 

the emissions control scenario identification and evaluation process. Today, four complimentary 

“Probing Tools” can be used in the CAMx regional photochemical model. These methods 

include: (a) traditional or “brute force” testing, (b) the direct decoupled method (DDM) 

sensitivity, (c) Ozone Source Apportionment Technology (OSAT), and (d) Process Analysis 

(PA). The Denver modeling team will use at least two types of emissions sensitivity testing 

methods with the CAMx 2010 future year simulations. 

Traditional Sensitivity Testing: The modeling team will perform across-the-board 

emission reduction sensitivity runs on the 4 km grid for the July 5-30, 2006 period 

reducing anthropogenic VOC or NOx emissions (separately) by 20% from the 2010 base 

case conditions for the following source categories: 

• On-road mobile sources; 

• Non-road mobile sources; 

• Oil and gas production sources; 
F:\Denver_O3_2008\Protocol\draft#2\Sec7_FY1.doc 7-4

• Other area sources; and 

• Point sources. 

In addition, we would perform an on-road mobile sources 20% co-emissions reduction 

sensitivity test. This results in eleven (11) 2010 emission reduction sensitivity tests. Two 

more additional 2010 sensitivity tests will be performed to be determined. These 

sensitivity runs serve two purposes, (a) they aid in helping to define more refined 

emissions control scenarios, and (b) they provide episode-specific model uncertainty 

information that may be used later in the “Weight of Evidence” analyses in support of the 

8-hour ozone attainment demonstrations. 

Ozone Source Apportionment: Ozone source apportionment will be used to obtain more 

refined ozone source-receptor relationships in the Denver region. The Anthropogenic 

Precursor Culpability Assessment (APCA) version of the Ozone Source Apportionment 

Technology (OSAT) will be used for 2010 base case emissions to: (a) assess the 

contribution of sources in the Colorado and surrounding states to ozone concentrations in 

key receptor areas in the Denver area, and (b) identify the particular source categories 

that may contribute the most to future-year elevated 8-hour ozone concentrations at 

various nonattainment monitors. Details on the CAMx ozone source apportionment are 

available in the CAMx User’s Guide (ENVIRON, 2006; www.camx.com). 

7.6 Control Strategy Development, Testing and Analysis 

The general approach to be followed in assessing whether the Denver region is likely to be in 

attainment of the 8-hour ozone standard or whether and to what extent additional VOC and NOx 

emissions reductions will be required to achieve attainment will be consistent with the 

methodologies stipulated in EPA’s recent 8-hour ozone modeling guidance (EPA, 2007). The 

procedure to be followed in performing the ozone attainment demonstrations is discussed in 

Chapter 8. The main theme of this approach is to use the model in a relative sense through 

model-derived site-specific relative response factors (RRFs) that are used to scale the current 

observed 8-hour ozone Design Values. 

The CAMx 2010 future-year 8-hour ozone simulations will reveal the extent to which further 

emissions reductions are needed in the region to provide for attainment of the 8-hour ozone 

NAAQS by 2010. Should ozone violations be projected in the region in the future year 

simulation, the severity, location, and spatial extent of the modeled exceedances will be studied 

in order to postulate candidate emissions reductions strategies within and upwind of the 

nonattainment area. That is, should the future year modeling reveal a nonattainment problem, 

then an attainment demonstration analysis will be performed that will include the 8-hour ozone 

modeled attainment test, specific screening analysis and supplemental corroborative analyses set 

forth in the EPA guidance. These attainment demonstration procedures for ozone are described 

in detail in the following Chapter 8. 

It is difficult when a modeling study protocol is first prepared to specify precisely the nature of 

the future year local and regional ozone control scenarios that may be required; indeed, the 

application of existing and mandated regional and local controls “on the books” and “on the 

way” (e.g., the effects of fleet turnover) could potentially and dramatically change the current 
F:\Denver_O3_2008\Protocol\draft#2\Sec7_FY1.doc 7-5

attainment picture in the region. The RAQC and APCD will likely provide the modeling team 

with several alternative 2010 emission control strategies that will be modeled using the CAMx 

model and used to project 2010 8-hour ozone DVs for the Denver area following the procedures 

given in Section 8. 
F:\Denver_O3_2008\Protocol\draft#2\Sec8_Attain1.doc 8-1 

8.0 OZONE ATTAINMENT DEMONSTRATION 

The ultimate objective of the Denver ozone modeling study is the development of modeling 

databases that can be used to define emissions control strategies that demonstrate future-year 

attainment of the 8-hour ozone National Ambient Air Quality Standard (NAAQS). This section 

describes the procedures for demonstrating future-year attainment of 8-hour ozone NAAQS. 

8.1 Ozone Weight of Evidence Analyses 

A central theme of EPA’s 8-hour ozone modeling guidance document is the use of supporting 

corroborative analyses to bolster confidence that the selected control plan will in fact achieve 

attainment in the future-year (EPA, 2007). This corroborative analysis is part of the Weight of 

Evidence (WOE) used in a State Implementation Plan (SIP) to support the final control plan 

selection. Details of the WOE and types of corroborative analysis that can be used in an ozone 

attainment demonstration have been discussed earlier in Section1.5.8. 

8.2 8-Hour Ozone Attainment Demonstration Procedures 

The procedures for performing a modeled ozone attainment demonstration are outlined in EPA’s 

8-hour ozone modeling guidance (EPA, 2007). These procedures involve the use of the model in 

a relative sense to scale the observed site-specific 8-hour ozone Design Values (DVs) based on 

the relative changes in the modeled 8-hour ozone concentration between the current-year 2006 

and 2010 future-year. The model-derived scaling factors are called Relative Response Factors 

(RRFs) and are based on the relative changes in the modeling results between the 2006 base case 

and the 2010 future-year emission scenarios. 

The EPA guidance procedures for performing 8-hour ozone DV projections (EPA, 2007) have 

been codified in EPA’s Modeled Attainment Test Software (MATS) tool. MATS includes 

ambient ozone air quality data and the user provides modeling results for the current year base 

case and the future year. MATS performs two types of 8-hour ozone DV projections: (a) 

projections at monitoring sites with observed 8-hour ozone Design Values; and (b) unmonitored 

area screening analysis 8-hour ozone projections that interpolates the observed 8-hour ozone 

DVs across the modeling domain to obtain gridded fields of 8-hour ozone DV projections. 

The general procedures for projecting 8-hour ozone DVs at a monitoring site given in EPA’s 

guidance are as follows (EPA, 2007): 

• The starting point for the 8-hour ozone DV projections is the current year Design Value 

(DVC) that EPA guidance suggests should be based on the average of three 3-year 

periods of 8-hour ozone DVs centered on the modeling year. This results in a DVC that 

is a “5-year DV” that is used as the starting point for the 8-hour ozone DV projections. 

For the 2006 modeling year, this would mean averaging the 2004-2006, 2005-2007 and 

2006-2008 8-hour ozone DVs at each ozone monitoring site in Denver. As data for 2008 

are not yet available, we proposed at alternative approach to just use the standard 3-year 

DV from 2005-2007 as the starting point for the projections; 
F:\Denver_O3_2008\Protocol\draft#2\Sec8_Attain1.doc 8-2 

• Perform 2006 base year modeling on the 36/12/4 km grid for the June-July 2006 episode 

using the 2006 Typical base case emissions; 

• Perform 2010 future-year base case and control strategy modeling on the 36/12/4 km grid 

for the June-July, 2006 meteorological conditions; 

• Develop RRFs, defined as the ratio of the average of 8-hour daily maximum ozone 

concentrations “near” each monitor for the 2010 future year emission scenarios to the 

2006 base year for all days in which the 2006 base case ozone values are above a 

“threshold” value: 

o Here, “near” the monitor is defined as a grid cell size dependent array of 

cells centered on a monitor, where EPA guidance suggest that the arrays 

be 1x1 for 36 km, 3x3 for 12 km and 7x7 for 4-km grid cells. However, 

given the complex terrain in the Denver region and close proximity of 

some of the monitoring sites, a 7x7 array of 4 km grid cells may be too 

large and not capture local-specific conditions of a monitor. Thus, we 

intend to examine the effects of using different array sizes for the purpose 

of performing 8-hour ozone DV projections and conduct sensitivity 

analysis of this parameter. 

o EPA’s 8-hour ozone guidance specifies that RRFs should be calculated 

using all days with base-year ozone concentrations near the monitor 

greater or equal to 85 ppb, and also recommends that at least 10 modeling 

days should be included – these two recommendations may be in conflict: 

 In the event that there are less than 10 modeling days with base 

year daily maximum 8-hour ozone concentrations near the monitor 

> 85 ppb threshold then: 

• The threshold is successively reduced by 1 ppb (e.g., 84 

ppb, 83 ppb, etc.) until 10 modeling days are obtained; or 

• A 70 ppb threshold floor is imposed; 

 If there are still less than 10 days upon reaching the 70 ppb 

threshold then: 

• If there are 5 or more days, proceed with the attainment 

demonstration but the results should be analyzed carefully 

to be sure no single day is producing unusual model 

signals; or 

• If there are less than 5 days the issue will be discussed with 

RAQC, CDPHE/APCD and EPA; 

• Apply the modeled-derived RRFs to the DVC at each ozone monitor to obtain a projected 

future year 8-hour ozone DV (DVF); 

• Truncate the future-year DVF to the nearest ppb; 

• Compare the projected 8-hour ozone at each monitor (DVF) with the 8-hour ozone 

standard, where if all projected 8-hour ozone values are 84 ppb or lower then attainment 

has been demonstrated;

• Even if the modeled future-year 8-hour ozone DVF is 85 ppb or higher, a WOE 

attainment demonstration may be possible using supportive, corroborative and additional 

analysis:
F:\Denver_O3_2008\Protocol\draft#2\Sec8_Attain1.doc 8-3 

o In fact, EPA recommends that the WOE analysis be conducted with 

projected 8-hour ozone DVFs in the 82 to 87 ppb range;

o EPA notes that for projected 8-hour ozone DVFs of 88 ppb or higher no 

amount of supportive information would likely be convincing for an 

attainment demonstration.

8.3 Exceptions to EPA Guidance 

There are two exceptions we are making to the recommended future-year 8-hour ozone DV 

projection procedures in the EPA guidance. 

8.3.1 Current Year Design Value (DVC) Used in Projections

EPA guidance recommends using an average of three years of 8-hour ozone DVs centered on the 

modeling year as the current year Design Value (DVC) starting point for the future year 8-hour 

ozone projections (“5-year DV”). For the June-July 2006 modeling period this would include 

observed ozone from 2004-2008 period and since 2008 data have not yet been collected this is 

not possible. A possible alternative to this would be to use a “4-year DV” based on 2004-2007 

data as the DVC starting place for the 8-hour ozone projections. However, this would include 

the relative clean years of 2004 and 2005 in the DVCs and in fact would result in all DVCs being 

below the 8-hour ozone NAAQS which would make the reliability of the 8-hour ozone 

projection procedure highly questionable. Thus, we propose to use the normal 3-year 8-hour 

ozone DVs from 2005-2007 as the DVCs, which is the period that determined whether the 

Denver area is an ozone nonattainment area or not. 

Even with the DVCs based on the 2005-2007 3-year period, the Fort Collins West (FTCW) 

monitor would still not have any 8-hour ozone projections since data has only been collecting 

data for the 2006 and 2007 years. However, based on these two years of data the FTCW is the 

second most critical monitor, behind RFNO, so cannot be neglected. The modeling team will 

discuss this issue with RAQC, APCD and EPA and develop an appropriate DVC for FTCW so 

that 8-hour ozone projection sensitivity tests can be conducted for the FTCW monitor. 

8.3.2 Definition of Near the Monitor

When 4 km grid spacing is used, EPA recommends that RRFs be based on the modeled highest 

daily maximum 8-hour ozone concentrations located within a 7x7 array of 4 km grid cells 

centered on the monitor. Given the complex flow conditions in the Denver, there are quite 

different characteristics between ozone monitors located in close proximity to each other and use 

of such a large array of cells could fail to capture some unique local characteristics of a specific 

monitor. For example, the RFNO and SBC monitors are located in fairly close proximity to each 

other yet record very different ozone levels and use of a 7x7 array of cells to define near the 

monitor would essentially result in using the same modeled ozone results in the RRFs for these 

two monitors failing to account for their individuality. Thus, we propose to perform array size 

sensitivity tests in the monitored 8-hour ozone projection sensitivity tests using arrays sizes of 

1x1, 3x3, 5x5 and 7x7 around each monitor to define “near the monitor.” 
F:\Denver_O3_2008\Protocol\draft#2\Sec8_Attain1.doc 8-4 

8.4 Unmonitored Areas Attainment Test 

The MATS tool includes an unmonitored area attainment test to examine for potential 8-hour 

ozone hotspots away from the monitors. Given the uncertainties in these procedures, EPA 

guidance is clear that projected 8-hour ozone DVs exceeding the NAAQS away from the 

monitors do not necessarily imply that the NAAQS would be violated, rather they suggest an 

unmonitored location where high ozone could be occurring and additional ozone monitors should 

be deployed to determine whether the location is a potential trouble spot. 

The MATS procedures for conducting the unmonitored area attainment test are as follows: 

• Interpolate the DVCs from the monitoring sites to each grid cell in the modeling 

domain; 

• Calculate gridded RRFs for each grid cell using the ratio of the average modeled 

future-year to current-year concentrations in each grid cell for all days in which 

the current-year daily maximum 8-hour ozone concentrations exceeds a threshold 

value (again a threshold of 85 ppb is used initially that is reduced until at least 10 

days are included in the RRFs with a 70 ppb threshold floor); and 

• The gridded RRFs are applied to the gridded DVCs to obtain an array of gridded 

future-year projected DVs (DVFs). 

Note that it is likely that portions of the modeling domain will have no projected DVFs because 

there were insufficient ozone days above 70 ppb to construct an RRF. 

For the Denver 2010 ozone modeling, we will perform the MATS unmonitored area attainment 

test using the 2005-2007 DVCs discussed previously. 
F:\Denver_O3_2008\Protocol\draft#2\Sec9_Refs1.doc 9-1 

9.0 REFERENCES 

Air Sciences. 2007a. Development of 2000-04 Baseline Period and 2018 Projection Year 

Emission Inventories. Air Sciences, Denver, Colorado and ECR, Inc., North Carolina. 

May. http://www.wrapair.org/forums/fejf/documents/task7/Phase3-

4EI/WRAP_Fire_Ph3-4_EI_Report_20070515.pdf. 

Air Sciences. 2007. Inter-RPO 2002 National Wildfire Emission Inventory. Air Sciences, 

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