Summary Report of 

Air Quality Modeling 

Research Activities for 2006

R E S E A R C H A N D D E V E L O P M E N T
EPA /600/R-07/103 

09/2007 

NOAA Technical 

Memorandum 

OAR ARL-259 

10/2007

Summary Report of 

Air Quality Modeling 

Research Activities for 2006

S.T. Rao, Robin Dennis, Valerie Garcia, Alice Gilliland, Rohit Mathur, David Mobley, Thomas Pierce, and Kenneth Schere

Atmospheric Modeling Division 

National Exposure Research Laboratory 

U.S. Environmental Protection Agency 

Research Triangle Park, NC, 27711 

and 

Atmospheric Sciences Modeling Division 

Air Resources Laboratory 

National Oceanic and Atmospheric Administration 

Silver Spring Maryland, 20910 

National Oceanic and Atmospheric Administration 

Office of Oceanic and Atmospheric Research 

Silver Spring, Maryland, 20910 

Notice: Although this work was reviewed by EPA and NOAA and approved for publication, it may not necessarily 

reflect official EPA or NOAA policy. Mention of trade names and commercial products does not constitute 

endorsement or recommendation for use. 

U.S. Environmental Protection Agency 

Office of Research and Development 

Washington, DC 20460 
iii 

Notice 

The research presented here was performed under the Memorandum of Understanding and 

Memorandum of Agreement between the U.S. Environmental Protection Agency (EPA) and the U.S. 

Department of Commerce’s (DOC’s) National Oceanic and Atmospheric Administration (NOAA). It has 

been subjected to EPA and NOAA peer and administrative review and has been approved for publication as 

a joint EPA-NOAA document. Mention of trade names or commercial products does not constitute 

endorsement or recommendation for use. 
iv 

Abstract

Through a Memorandum of Understanding (MOU) and Memorandum of Agreement (MOA) between 

the Department of Commerce (DOC) and U.S. Environmental Protection Agency (EPA), the Atmospheric 

Sciences Modeling Division (ASMD) of National Oceanic and Atmospheric Administration’s (NOAA’s) 

Air Resources Laboratory (ARL) develops advanced modeling and decision support systems for effective 

forecasting and management of the Nation's air quality. As a division within the EPA organizational 

structure, ASMD is known as the Atmospheric Modeling Division (AMD). The Division is responsible for 

providing a sound scientific and technical basis for regulatory policies to improve ambient air quality. The 

models developed by the Division are being used by EPA, NOAA, and the air pollution community in 

understanding and forecasting not only the magnitude of the air pollution problem, but also in developing 

emission control policies and regulations. This report summarizes research and operational activities of the 

Division for the year 2006.
v 

Contents

Notice ........................................................................................................................................................... iii 

Abstract .........................................................................................................................................................iv 

Acknowledgements .................................................................................................................................... viii 

Chapter 1: Introduction ...................................................................................................................................1 

Chapter 2: Providing Scientifically-Advanced Models and Tools to Support Environmental .......................4 

Policy Decisions .............................................................................................................................................4 

Introduction .............................................................................................................................................4 

Research Description ...............................................................................................................................4 

Accomplishments ....................................................................................................................................5 

Next Steps ...............................................................................................................................................6 

Impacts and Transition of Research to Applications................................................................................6 

Chapter 3: Evaluating the Impact of Regulatory Policies on Air Quality and Ecosystems ............................9 

Introduction .............................................................................................................................................9 

Research Description ...............................................................................................................................9 

Accomplishments ..................................................................................................................................10 

Next Steps .............................................................................................................................................10 

Impacts and Transition of Research to Applications..............................................................................10 

Chapter 4: Linking Sources to Human Exposure .........................................................................................12 

Introduction ...........................................................................................................................................12 

Research Description .............................................................................................................................12 

Accomplishments ..................................................................................................................................12 

Next Steps .............................................................................................................................................13 

Impacts and Transition of Research to Applications .............................................................................13 

Chapter 5: Linking Sources to Ecosystem Exposure.....................................................................................14 

Introduction ...........................................................................................................................................14 

Research Description .............................................................................................................................14 

Accomplishments ..................................................................................................................................15 

Next Steps .............................................................................................................................................16 

Impacts and Transition of Research to Applications .............................................................................16 

Chapter 6: Providing Air Quality Forecast Guidance for Health Advisories ................................................18 

Introduction ...........................................................................................................................................18 

Research Description .............................................................................................................................18 

Accomplishments ..................................................................................................................................18 

Next Steps .............................................................................................................................................19 

Impacts and Transition of Research to Applications..............................................................................19 

Chapter 7: Understanding the Relationships between Climate Change and Air Quality ..............................21 

Introduction ...........................................................................................................................................21 

Research Description .............................................................................................................................21 

Accomplishments ..................................................................................................................................21 

Next Steps .............................................................................................................................................22 

Impacts and Transition of Research to Applications .............................................................................22 

Appendix A: Division Staff Roster ..............................................................................................................23 

Appendix B: Division and Branch Descriptions............................................................................................27 

Appendix C: Awards and Recognition..........................................................................................................28 

Appendix D: Publications .............................................................................................................................29 
vi 

Figures

Number Page

1-1 The Division’s role in the Source-Exposure-Dose-Effects Continuum ..................................................2 

1-2 Strategy to meet user needs.....................................................................................................................3 

2-1 Schematic of CMAQ modeling system, including meteorology, emissions, and air quality models .....7 

2-2 Schematic of particulate matter/aerosol module in CMAQ model .........................................................7 

2-3 Comparisons of monthly average PM2.5 species components observed at eastern U.S. STN sites 

 with comparable results from CMAQv4.5 and CMAQv4.6 (from eastern U.S. simulation with 

 12-km grids)............................................................................................................................................8 

3-1 Back trajectories show Ohio River Valley as source region for high ozone levels at a site in 

 the northeast (green trajectories indicate source regions of low ozone days and black 

 trajectories indicate source regions of high ozone days) during the 2002 summer...............................11 

3-2 NOx SIP Call evaluation showing maximum 8-hr ozone concentrations at 95th percentile for 

 summer 2002 and summer 2004 ...........................................................................................................11 

4-1 Multiple scales in air quality modeling.................................................................................................13 

5-1 CMAQ annual average wet plus dry, oxidized plus reduced nitrogen deposition (in kg-N/ha) 

 across the U.S. based on 3 years of meteorology - one dry, one wet, and one average 

 precipitation year - across the Eastern U.S. ..........................................................................................17 

6-1 Forecast surface-level 8-hour maximum O3 concentrations on August 1, 2006 ...................................20 
vii 

Acknowledgements 

The authors thank Teri Conner of the National Exposure Research Laboratory and Patricia McGhee of 

the Air Resources Laboratory for their technical editing and manuscript preparation. The report would not 

have been possible without their contributions.
1 

Chapter 1 

Introduction

September 2005 marked the 50th Anniversary of the 

collaboration between the U.S. Department of Commerce’s 

National Oceanic and Atmospheric Administration (NOAA) 

and the U.S. Environmental Protection Agency (EPA), and 

their predecessor agencies on air quality modeling research 

and its application. The relationship between NOAA and EPA 

began when the Air Pollution Unit of the Public Health 

Service, which later became part of the EPA, requested the 

Weather Bureau to provide it with meteorological expertise. 

Thus, a special Weather Bureau air pollution unit was formed 

in 1955 and integrated with the Public Health Service. It was 

located in Cincinnati, Ohio, until it moved in 1969 to Raleigh, 

North Carolina. Now called the NOAA Atmospheric Sciences 

Modeling Division (ASMD), it works within the framework of 

the Memorandum of Understanding and Memorandum of 

Agreement between the U.S. Department of Commerce and 

EPA. These agreements are implemented through long-term 

Interagency Agreements DW13938483 and DW13948634 

between EPA and NOAA. 

The Division is organized into five research branches: 

• Atmospheric Model Development Branch 

• Model Evaluation and Applications Research Branch 

• Air-Surface Processes Modeling Branch 

• Air Quality Forecasting Research Branch 

• Applied Modeling Branch 

The first four branches listed above comprise the Atmospheric 

Modeling Division (AMD) of the National Exposure Research 

Laboratory of the Office of Research and Development (ORD) 

within EPA’s organizational structure. The fifth branch listed 

is part of the Air Quality Assessment Division of the Office of 

Air Quality Planning and Standards (OAQPS) within EPA’s 

organizational structure. Throughout this report, these 

NOAA-EPA branches will be collectively referred to as “the 

Division.” A listing of employees and division and branch 

descriptions are located in the appendix along with a listing of 

awards and publications. 

The Division’s role within the source-to-outcome continuum 

is to conduct research that improves the Agency’s 

understanding of the linkages from source to exposure, as 

depicted in Figure 1-11

. Through its research branches, the 

Division provides atmospheric sciences expertise, air quality 

forecasting support, and technical guidance on the 

meteorological and air quality modeling aspects of air quality 

management to various EPA offices, including OAQPS 

Regional Offices, state and local pollution control agencies, 

and other federal agencies. 

The Division provides this technical support and expertise 

using an interdisciplinary approach emphasizing integration 

and partnership with EPA and public and private research 

communities. Specific research and development activities 

are conducted in-house and externally via contracts and 

cooperative agreements. 

In 2006, the Division completed a major strategic planning 

process begun in 2002. Six outcome-oriented theme areas 

were identified:

• Providing scientifically-advanced models and tools to 

support environmental policy decisions 

• Evaluating the impact of regulatory policies on air 

quality and ecosystems 

• Linking sources to human exposure 

• Linking sources to ecosystem exposure 

• Providing air quality forecast guidance for health 

advisories 

• Understanding the relationships between climate 

change and air quality. 

Research tasks were developed within each theme area, 

considering these questions: 

• Over the next 2-3 years, who are the major clients 

and what are their needs? 

• What research investments are needed to further the 

science in a way that helps the client(s)? How will 

we lead or influence the science in this area? 

• What personnel expertise, resources, and partners are 

needed to do this work? 

 

1 Exposure Science Research: A Conceptual Framework, November 2006 

Draft by EPA’s National Exposure Research Laboratory. 
2 

• Does the proposed work fall within the current scope 

and plans of existing projects, or would people 

resources need to be shifted from other projects to 

make this happen? 

The result is a research strategy to meet user needs built 

around six major theme areas and supported by the five 

branches of the Division, as depicted in Figure 1-2. The 

Division’s Applied Modeling Branch in turn supports these 

research and development-focused branches by facilitating the 

transition of atmospheric modeling systems and other research 

tools to regulatory applications. 

This report summarizes research and operational activities of 

the Division for the year 2006. It includes descriptions of 

research and operational efforts in air pollution meteorology, 

meteorology and air quality model development, model 

evaluation and applications, and air pollution abatement and 

compliance programs. The report is organized by the major 

program themes presented in Figure 1-2. 

Figure 1-1. The Division’s role in the Source-Exposure-Dose-Effects Continuum.

Division’s Role 

Ambient 

Concentrations 

Source / Origin 

Fate and 

Transport 

Exposure 

Dose 

Early Signs of 

Effects 

Adverse 

Outcome 

Source-to-Outcome Continuum 
3 

Figure 1-2. Strategy to meet user needs.
4 

Chapter 2 

Providing Scientifically-Advanced Models and Tools to Support 

Environmental Policy Decisions 

Introduction 

Air quality management in the U.S. is implemented for criteria 

pollutants through the National Ambient Air Quality 

Standards (NAAQS). The states must submit state 

implementation plans (SIPs) for areas that do not meet the 

NAAQS, demonstrating how additional emissions controls 

will bring their areas into compliance with the NAAQS. The 

principal tools that EPA and the states use to demonstrate this 

compliance are air quality simulation models. Current 

NAAQS exist for tropospheric ozone (O3), fine particulate 

matter (PM2.5), coarse particulate matter (PM10), and other 

criteria pollutants. EPA performs a review of each NAAQS 

every 5 years, and proposes changes if the most current 

science on health and ecological effects suggest changing the 

standards. In 2006, EPA revised the standards for daily 

average PM2.5 from 65 to 35 μg/m3

, and dropped the annual 

average standard for PM10, leaving only the daily standard of 

150 μg/m3. When areas of the country are designated as 

exceeding the NAAQS for a particular pollutant, the states 

have at least three years to submit a SIP, including a modeling 

demonstration illustrating how they intend to mitigate 

emissions to achieve compliance with the standards. 

In addition to the NAAQS for the criteria pollutants, EPA and 

the states also study mitigation strategies for other types of 

pollutants, such as hazardous air pollutants (HAPS, or air 

toxics) and global pollutants, such as mercury. While there 

are a range of air quality policy-related issues that are tracked 

separately for individual pollutants, chemistry, and sources 

involved in producing these air quality conditions are interrelated. Therefore, a multi-pollutant model is needed that can 

simulate the atmospheric processes and emission source inputs 

that contribute to all of these chemical species and conditions. 

The Division develops, evaluates, applies, and refines such 

models. The principal modeling platform, the Community 

Multiscale Air Quality (CMAQ) modeling system, includes 

components for meteorology, emissions, air quality, and 

analysis with visualization (see Figure 2-1). 

Research Description 

The principal elements of the modeling program are Model 

Development and Model Evaluation. These elements are 

inter-related, as model evaluation provides information for 

improving the models, models are improved through research 

and development, improved models are re-evaluated, and 

improved models are then available for regulatory application. 

Hence, the development and evaluation of the models form an 

iterative process. 

Through the Model Development program element, the 

Division develops and improves the CMAQ air quality model 

for a variety of spatial (urban through continental) and 

temporal (days to years) scales and for a variety of pollutants 

(O3, PM, air toxics, mercury, visibility, acid deposition). The 

multi-pollutant model approach permits the testing of 

emissions control strategy impacts on the target pollutant, as 

well as collateral impacts on other pollutants. 

Focus areas of model development include the following: 

• Turbulence and diffusion within the planetary 

boundary layer in the meteorological and air quality 

models 

• Data assimilation 

• Consistent linkage of the meteorology model with the 

air quality and emissions models 

• Source emissions modeling including biogenic, 

wildfire, dust, ammonia, and other anthropogenic 

emissions 

• Gas- and aqueous-phase chemistry 

• Aerosol chemistry, physics and thermodynamics 

• Sub-grid parameterization and modeling techniques 

• Numerical advection and other solution techniques 

• Code parallelization and efficiency. 

Integrating meteorology and chemistry modeling is a new 

program priority to provide feedback from air quality 

parameters (e.g., aerosols) that affect meteorological 

parameters (e.g., radiation). Developmental areas are guided 

by the model evaluation results and by model sensitivity and 
5 

uncertainty tests. New CMAQ model versions are released for 

public access roughly on a 1-2 year frequency. Workgroups 

have been formed to focus around these research topics: 

• Atmospheric Chemistry and Aerosols 

• Two-way interactive Meteorology-Chemical 

Transport Modeling 

• Weather Research and Forecast Model 

• Air Toxics Modeling 

Through the Model Evaluation program element, the 

Division evaluates the models to characterize the accuracy of 

model predictions and to identify improvements needed in 

model processes or model inputs. This requires comparisons 

against observational data. Different CMAQ simulations (e.g., 

different model versions, different chemical mechanisms, 

different vertical layer structuring) are compared to identify 

the impact of model changes or options on model 

performance. Uncertainties in meteorological predictions and 

emission estimates are considered to help identify where 

improvements are needed. Regulatory Applications of CMAQ 

are evaluated by comparing model-predicted changes in ozone 

and aerosols to changes in emission precursors. Model 

evaluation is conducted through workgroups dealing with 

these issues: 

• Operational evaluations supporting the CMAQ model 

releases 

• Model diagnostics (chemistry, meteorology) 

• Model dynamics (i.e., tracking simulated and 

observed changes in air quality over time) 

• Probabilistic evaluation (exploring limits to the 

deterministic use of model predictions) 

• Spatial and temporal analyses of modeled and 

observed air pollutants

Through these efforts, the Division facilitates the transition of 

research to the regulatory community. 

Accomplishments 

During FY-2006, the Division released several new versions 

of the CMAQ model system to the model user community. 

CMAQv4.5, released in October 2005, included several 

advancements in PM2.5 modeling capabilities. New to this 

version of the model were sea-salt aerosol emissions from 

wind and wave action, along with thermodynamic equilibrium 

for the phase partitioning of these aerosols in the fine mode (0-

2.5 μm diameter). Figure 2-2 illustrates the treatment of 

particulate matter in the CMAQ model. Chemical reactions 

involving chlorine were added to the gas-phase chemistry of 

the CMAQ model as well. This model release also included a 

carbon source apportionment version of the model, in which 

explicit tracers are added from various emissions source 

sectors to track the incremental contributions of these sectors 

to primary carbon aerosol. 

CMAQv4.5 was used to simulate a full year (2001) over the 

continental U.S. using 36-km grid size in the horizontal and 14 

vertical layers extending to 100 mb. Model results for O3

were compared with data from EPA’s Air Quality System 

network data; model results for PM2.5 were compared with 

data from several surface-based monitoring networks. 

CMAQv4.5.1, released in March 2006, extended model 

capabilities to simulate atmospheric mercury (Hg) 

concentrations and deposition. The additional processes 

included elemental mercury (Hg0

), reactive gaseous mercury 

(RGM), and particulate mercury (Hg(p)) emissions, as well as 

the chemical reaction pathways to transform Hg0

 into RGM. 

When deposited in water bodies, RGM produces toxic forms 

of methylated Hg, which can enter the food chain through 

ingestion by fish. While the Division had been using research 

versions of CMAQ-Hg for several years, this was the first time 

these capabilities were included in a public release version of 

the model. The Division is participating in the North 

American Mercury Model Intercomparison Study, a 

collaboration among several groups in the U.S. and Canada, to 

compare the results of different atmospheric models for Hg. 

CMAQv4.6, released in September 2006, contained several 

improvements to the chemistry and turbulent diffusion 

modules. The Carbon Bond 2005 (CB05) chemical kinetic 

mechanism was added to the model. The new CB05 

mechanism, containing 52 species and 156 reactions, provides 

an extended inorganic reaction set and better representations 

of O3 and PM2.5 precursor species compared with the previous 

version. In addition, the latest data on the reaction efficiency 

of the N2O5 hydrolysis reaction was incorporated into CMAQ. 

This heterogeneous reaction is important in the production of 

HNO3 and particulate NO3. The CMAQ model was also 

extended to include new hazardous air pollutants (air toxics) 

including several toxic metals (beryllium, cadmium, lead, 

manganese, nickel, and chromium) and diesel exhaust 

components. A new turbulent diffusion module was 

developed to include both local and non-local components of 

convective turbulence for mixing of pollutants in the planetary 

boundary layer. CMAQv4.6 was evaluated by simulating one 

month in each season of 2001 on a continental U.S. domain 

(36-km grid cells) and nested eastern U.S. domain (12-km grid 

cells), using both 14 and 34 vertical layers. Figure 2-3 

provides information on July 2001 performance of CMAQ for 

PM2.5 components. Note that the results show reasonably 

good performance for inorganic species and under predictions 

for organic aerosols. Note also that, about 25% of the PM2.5

mass is classified as other (i.e., unknown constituents) in both 

observations and model predictions. 

In FY 2006, CMAQ model evaluations included more detailed 

analyses of model performance based on different synoptic 

weather patterns, chemical mechanisms, vertical resolution, 

and chemical boundary conditions. These analyses have 
6 

shown that chemical boundary conditions, the depth of the 

model’s first layer, and the representation of clouds in the 

model play roles in over predictions of ozone at low observed 

concentrations. More detailed analyses of the contribution of 

individual aerosol species to the total PM2.5 have identified 

that the PM “other” category is contributing substantially to 

over predictions of PM2.5 during the fall and winter, 

suggesting uncertainty in the primary PM2.5 emission 

inventory. Source apportionment or process analysis 

diagnostic methods have also identified biases in the 

emissions inventory inputs to the CMAQ model for several 

primary PM2.5 sources. 

New advancements in diagnostic evaluation methods have 

also been emerging. For example, the analysis of CMAQ’s 

particulate NO3 predictions effectively informed model 

developers of issues in the chemistry, which were addressed, 

in part, in the CMAQv4.6 release. In addition, a new metric 

has been developed to estimate the change in aerosol NO3

with changes in gaseous SO2 and NH3 emissions in the winter. 

The recent NOx emissions reductions from eastern U.S. coalfired power plants present a unique opportunity to assess 

model response to emissions changes. CMAQ was used to 

apply these NOx emission changes to simulate ambient O3

concentrations. A new probabilistic model evaluation project 

was begun to explore CMAQ model prediction sensitivities to 

model physics and chemistry options, and ultimately develop 

an ensemble of CMAQ predictions. 

Next Steps 

Over the next several years, science and technology 

advancements planned for the CMAQ model system include 

emissions modeling and additional model system evaluation. 

These are some of the planned milestones: 

FY-2007 

• Incorporate Weather Research and Forecast (WRF) 

meteorological model into CMAQ modeling system 

as a new meteorological driver 

FY-2008: 

• Release and evaluate new version of CMAQ model 

system that will include improved simulations of 

aerosol processes, especially secondary organic 

aerosol production 

• Develop prototype of two-way integrated 

meteorology/chemistry simulation model based on 

WRF and CMAQ models 

FY-2009 

• Add fugitive wind-blown dust emission module to 

CMAQ modeling system 

Impacts and Transition of Research to 

Applications 

The Division releases versions of the CMAQ model and 

associated programs to the public through the ORD-supported 

Community Modeling and Analysis System (CMAS) Center. 

The Center also provides user support and training. The 

community air quality modeling concept, the CMAQ model in 

particular, have seen growing acceptance since the model was 

first released in 1998. An annual CMAQ model-users 

workshop now attracts over 200 people each year from North 

America, Europe, and Asia. 

EPA’s Office of Air Quality Planning and Standards 

(OAQPS) and the states use the CMAQ model for assessments 

in national air quality rulemaking and in their State 

Implementation Plans (SIPs), respectively. OAQPS has used 

the CMAQ model to assess the potential effectiveness of the 

Clean Air Interstate Rule and the Clean Air Mercury Rule as a 

part of EPA’s rule making process. The states, through their 

Regional Planning Organizations, are using the CMAQ model 

for visibility assessments in support of the Regional Haze Rule 

and for upcoming SIP assessments for O3 and PM2.5. The 

CMAQ model is also being used in Canada, the U.K., Spain, 

Eastern European Countries, China, Korea, and many other 

nations in programs to improve regional air quality 

management. NOAA’s National Weather Service, in a 

collaborative project with EPA, is using the CMAQ model to 

make publicly-available short-term (next-day) forecasts of 

ozone air quality across the eastern U.S. (See Chapter 6). 

The effects of all of these efforts will be to better inform the 

public on current air quality conditions (forecasting 

applications) to help them make decisions on health-related 

exposures to air pollution, and to better inform policy makers 

(air quality model assessments) to guide them in the best longterm emissions control decisions to reduce air pollution. 

The part of the Division organizationally associated with 

OAQPS oversees and facilitates the process of transitioning 

tools to regulatory applications, thus providing the foundation 

for scientifically sound regulatory decisions. 
7 

CMAQ Modeling System

SMOKE

Anthro and Biogenic 

Emissions processing

Fifth Generation 

Mesoscale Model (MM5)

(transition to WRF model)

CMAQ AQ ModelChemical-Transport 

Computations

Met-Chem Interface 

Processor (MCIP)

Met. data prep

NOAA Weather 

Observations

EPA Emissions 

Inventory

Hourly 3-D Gridded

Chemical Concentrations

Figure 2-1. Schematic of CMAQ modeling system, including meteorology, emissions, and air quality models. 

• Trimodal size distribution

• Gas/particle interactions treated

for fine modes only

• Fine-modes coagulate

• Coarse mode, fine EC (black) &

other fine PM (brown) are inert

CMAQ Aerosol Module

NO3

-

NH4

+

SO4

=

Na+

ClH2O

POA

SOAa

SOAb

EC

Other

SVOCs

HNO3

NH3

H2O

Na+, Cl-, SO4

2-

Soil, Other

COARSE MODE 2 FINE MODES

H2SO4

Aromatics

Monoterpenes

HCl

Figure 2-2. Schematic of particulate matter/aerosol module in CMAQ model. 
8 

July Average PM2.5 vs STN

Figure 2-3. Comparisons of monthly average PM2.5 species components observed at eastern U.S. STN sites with comparable results from 

CMAQv4.5 and CMAQv4.6 (from eastern U.S. simulation with 12-km grids). 
9 

Chapter 3 

Evaluating the Impact of Regulatory Policies on Air Quality and Ecosystems

Introduction 

The majority of the criteria pollutants are transported across 

state boundaries, complicating the non-attainment issue. 

Recent EPA rulemakings have recognized that this transport 

must be considered in meeting NAAQS, requiring a regional 

perspective when developing strategies for air pollution nonattainment. 

In 1998, EPA finalized a rule known as the “NOx SIP Call,” 

requiring 22 states and the District of Columbia to submit SIPs 

that address the regional transport of ground-level ozone. The 

actions directed by these plans include reducing emissions of 

nitrogen oxides (NOx), a precursor to ozone formation, 

thereby decreasing the formation and transport of ozone across 

state boundaries. 

The recent Clean Air Rules are a suite of actions designed to 

improve air quality. Three of the rules specifically address the 

transport of pollution across state borders. The Clean Air 

Interstate Rule (CAIR) will permanently cap emissions of 

sulfur dioxide and nitrogen oxides from utilities in the eastern 

United States. When fully implemented in 2015, CAIR will 

reduce SO2 emissions in these states by over 70 percent and 

NOx emissions by over 60 percent from their 2003 levels. The 

Clean Air Mercury Rule (CAMR) will build on the CAIR to 

reduce mercury emissions from coal-fired power plants. The 

Non-Road Diesel Rule will reduce emissions from future nonroad diesel engines by changing the way diesel engines 

function to remove emissions and the way diesel fuel is 

refined to remove sulfur. 

Deposition of atmospheric nitrogen, sulfur, and mercury to 

land and water surfaces contributes significant loadings to 

receiving water bodies, affecting ecosystems health. For 

example, atmospheric deposition of nitrogen accounts for 

about 30% of the nitrogen coming into the Chesapeake Bay. 

CAA regulations, including the NOx SIP Call, CAIR, and 

CAMR are expected to reduce atmospheric deposition of these 

pollutants. 

Research Description 

Given the significant costs associated with these rules and 

control measures, it is important to demonstrate their 

effectiveness. The Division has demonstrated reductions in 

observed and modeled ozone concentrations resulting from 

actions of the NOx SIP Call. Research will continue to 

develop ways to systematically track and periodically assess 

our progress in attaining national, state, and local air quality 

goals - particularly those related to criteria pollutants regulated 

under the NAAQS and the Clean Air Rules. 

Research under this Theme area falls into two categories: 

• Evaluating changes in ambient pollutant 

concentrations and atmospheric deposition due to the 

implementation of emission reductions 

• Investigating relationships between emissions, 

ambient pollutant concentrations, human exposure, 

and human health endpoints. 

The major research questions addressed by this research 

include the following: 

• Did our control strategies result in the anticipated 

emission reductions? 

• Did our models accurately predict the changes in 

pollutant concentrations and atmospheric deposition 

due to the control strategies? 

• What are the human and ecosystem health 

consequences of these reductions? 

This research will support the accountability program to 

develop tools and techniques for assessing the effectiveness of 

control strategies. The CMAQ model will be used to 

characterize air quality before and after the implementation of 

a target regulation and to evaluate relationships between 

changes in emissions and pollutant concentrations or 

atmospheric deposition. Various scenarios will be modeled to 

estimate the anthropogenic contribution to total ambient 

concentrations and the impact of not promulgating the 

regulation. Methods will also be developed to differentiate 

changes attributable to emission reductions from those 

resulting from other factors, such as weather and annual and 

seasonal variations. 

Research will initially focus on NOx and SO2 where emissions 

monitoring data are available. Later, research will investigate 

using other sources of information (e.g., remote sensing, 

surrogate measures) to evaluate pollutants such as particulate 
10 

matter and mercury where emissions data are sparse or 

uncertain. 

In addition, the relationship between meteorology and the 

regional-scale transport of pollutants will be investigated. 

Specifically, the effect of a target regulation on downwind 

concentrations will be assessed. Trajectory analysis, using 

NOAA's HYSPLIT model, will be performed to investigate 

the transport of primary and secondary pollutants from their 

source to downwind regions, as illustrated in Figure 3-1. 

Source regions responsible for atmospheric deposition to 

water bodies downwind will be investigated using similar 

methods. 

Methods to statistically combine modeled and observed data 

will be developed to improve the characterization of air 

quality and deposition. These enriched air quality 

concentration and deposition maps will be used to improve 

and track pollutant control programs and their impact on 

ecosystem and human health. The enriched surface maps will 

also be used with exposure models to estimate the probability 

that a population will be exposed to an atmospheric pollutant. 

Accomplishments 

In FY 2006, substantial progress was made in comparing the 

ozone levels before and after the implementation of the NOx

SIP Call (see Figure 3-2 for example). The analysis of NOx

emissions data from Electric Generating Units (EGUs) 

indicated that utility NOx emissions at both the source and at 

downwind monitors were reduced substantially by May 2004 

because of the implementation of the NOx SIP Call. 

The influence of meteorology was assessed by analyzing 

ozone and meteorological data collected at the CASTNET 

sites, a national monitoring network for data on dry acidic 

deposition and rural, ground-level ozone, and controlling for 

meteorology in CMAQ model runs. In addition to reduced 

NOx emissions, the changes in the meteorologically-adjusted 

ozone concentrations between the pre- and post- NOx SIP Call 

periods indicated that the NOx SIP Call resulted in a reduction 

to the secondary formation of ozone at sites downwind from 

the reduced emissions. The results from the trajectory 

analysis supported this potential source-receptor relationship 

and revealed that NOx and ozone can be transported hundreds 

of kilometers from their sources aloft via the nocturnal jet 

stream. The results of this investigation indicated that 

emission controls on EGUs in the Midwest have contributed 

toward the improvement of ozone air quality in downwind 

regions, especially east and northeast of the Ohio River 

Valley. 

Next Steps 

Research conducted under this Theme Area will evaluate 

changes in pollutant concentrations resulting from regulatory 

actions and investigate relationships among sources of 

emissions, pollutant concentrations, atmospheric deposition, 

and human and ecosystem health. The following major 

milestones are planned: 

FY-2008 

• Develop methods to quantify the impact of the NOx

SIP Call on ambient ozone concentrations and 

atmospheric transport of pollutants, including 

impacts of not implementing the regulation and 

quantifying the anthropogenic contribution. 

FY-2009 

• Develop methods to quantify the probability of ozone 

exposure above exceedance levels to populations 

before and after the NOx SIP call was implemented. 

• Conduct a prototype risk assessment to examine the 

health impact of simulated emission scenarios. 

FY-2010 

• Develop approaches for characterizing the magnitude 

of changes in hospital admissions in New York State 

resulting from the NOx SIP Call. 

FY-2012 

• Apply prototype ambient concentration tracking 

method to evaluate impact of the CAIR on ambient 

and deposition concentrations. 

• Apply prototype deposition approach to evaluate 

impact of CAIR on ecological exposure endpoints in 

major water bodies. 

Impacts and Transition of Research to 

Applications 

Quantifying the improvement in air quality and human and 

ecological health brought about by costly regulations is critical 

in evaluating whether these actions are making the difference 

originally anticipated. This research will evaluate the impact 

and effectiveness of specific regulatory actions. Methods 

developed for these evaluations will also provide a framework 

for assessing future regulatory actions. These methods will 

include 

• data combination techniques 

• model evaluations for different regulatory and 

emission scenarios 

• approaches for tracking trends embedded within 

spatial and temporal signals and confounded by 

factors such as meteorology 

• evaluation of the impacts of regulatory actions on 

human and ecological exposure and health. 

This effort transitions research to applications by 

demonstrating the use of CMAQ, HYSPLIT, and various 

statistical techniques to evaluate the impact of regulations 

implemented to improve air quality. 
11 

Figure 3-2. NOx SIP Call evaluation showing daily maximum 8-hr ozone concentrations at 95th percentile for (a) summer 2002, 

and (b) summer 2004. 

Figure 3-1. Back trajectories show Ohio River Valley as source 

region for high ozone levels at a site in the northeast (green 

trajectories indicate source regions of low ozone days and black 

trajectories indicate source regions of high ozone days) during the 

2002 summer.
12 

Chapter 4 

Linking Sources to Human Exposure

Introduction 

The Clean Air Act requires EPA to assess which hazardous air 

pollutants pose the greatest risk to humans in the United 

States, and to develop strategies for controlling harmful 

concentrations of these compounds. These assessments 

typically involve the application of different models 

depending on program objectives – national, regional, urban, 

or locale scale (Figure 4-1). Performing these assessments 

requires a link between ambient air quality and human 

exposure models. The Division conducts research to build this 

link by combining the features of grid-based, regional-scale, 

chemical transport models and urban-scale, dispersion models. 

This research facilitates the use of air quality model 

concentrations in human exposure models, which historically 

have relied upon monitored concentrations at a central site. 

For exposure assessments, air quality modeling should include 

local-scale features, long-range transport, photochemistry, and 

deposition to provide the best estimates of air concentrations. 

Generally speaking, there are two major types of air quality 

models: source-based gaussian dispersion models and gridbased chemical transport models. Chemical transport models, 

such as the CMAQ model, can provide estimates of 

photochemically formed pollutants typically at 12-km grid 

dimensions, but not local-level details. CMAQ provides 

volume-average concentration values for each grid cell in the 

modeling domain for given conditions. Emissions are 

assumed to be instantaneously well-mixed within the grid cell 

in which they are emitted. While grid-based models are the 

platform of choice for this simulation of chemically-reactive 

airborne pollutants, there are various dispersion models (such 

as AERMOD2

) that have been developed to simulate the fate 

of airborne pollutants that are relatively chemically inert. 

Research Description 

To incorporate the salient features of both modeling 

approaches, the Division has been testing a hybrid approach 

that combines results from a regional grid model with a local 

plume model. The regional grid model provides the regional 

background concentrations and urban-scale photochemistry, 

and the local plume dispersion model provides the air 

concentrations due to local emission sources. The results of 

 

2 Cimorelli, A.J., S.G. Perry, A. Venkatram, J.C. Weil, R.J. Paine, R.B. 

Wilson, R.F. Lee, W.D. Peters, and R.W. Brode. AERMOD: A Dispersion 

Model for Industrial Source Applications. Part I: General Model Formulation 

and Boundary Layer Characterization. Journal of Applied Meteorology, 44, 

682–693 (2005). 

both model simulations are combined to provide the total 

ambient air concentrations for use in exposure models. The 

advantage of using this modeling approach is that it 

incorporates the spatial and temporal variation of air pollution 

within a study area in lieu of dense ambient monitoring 

networks. This hybrid approach is currently being explored in 

several studies, including the air quality and exposure study in 

Detroit and the accountability study in New Haven, CT. 

The goal of this research theme is to reduce uncertainties in 

quantifying the link between sources of atmospheric pollution 

and human exposure. The Division’s work in this theme is 

broken into the following research tasks: 

• Multi-scale modeling of toxic air pollutants 

• Near-roadway modeling 

• Homeland security support 

Accomplishments 

The CMAQ modeling system has been modified to include 

HAPS, and its results have been coupled with the near-field 

dispersion model AERMOD to account for urban-scale 

gradients of air toxics. In addition, outputs from this coupled 

system have been successfully linked to the Stochastic Human 

Exposure and Dose Simulation (SHEDS) exposure model and 

the Hazardous Air Pollutant Exposure Model (HAPEM). This 

research has been performed in collaboration with scientists 

from NERL’s Human Exposure and Atmospheric Sciences 

Division (HEASD) and OAR’s Office of Air Quality Planning 

and Standards (OAQPS). 

During FY-2006, the Division embarked upon the NearRoadway and School Infiltration Research Initiative. The 

overall goal of this EPA ORD-sponsored effort is to examine 

the contribution of roadway air pollutants to sensitive 

populations living near roadways. As part of this initiative, 

the Division started a numerical and physical modeling study 

to examine the impact of typical road configurations on 

downwind concentration patterns. The road configurations 

being studied include noise barriers, road cuts, and elevated 

highways. This study was motivated by a lack of 

parameterizations in current roadway dispersion models. To 

complement work in the meteorological wind tunnel, the 

Quick Urban Industrial Complex (QUIC) model is being 

applied to help in developing parameterizations and to explore 

field monitoring in Raleigh, NC, and Las Vegas, NV. 

Because of a decrease in funding, research related to 

Homeland Security received less attention in FY-2006 than in 

previous years. A 1:400 scale model of midtown Manhattan 

has been constructed for insertion in the meteorological wind 

tunnel, when and if resources allow. 
13 

Next Steps 

During the next few years, the Division is expected to build in 

the areas of near-roadway modeling and linkage of air quality 

models with human exposure models to assess human health. 

Planned milestones include the following: 

FY-2008 

• Characterization of near roadway dispersion 

FY-2009 

• CMAQ model system release and evaluation, 

including concurrent multi-pollutant modeling 

capability (O3, PM, air toxics, Hg) 

FY-2010 

• Development of line source algorithms for near-field 

and hybrid models 

FY-2012 

• Improved CMAQ modeling system for use in urbanscale applications. 

Impacts and Transition of Research to 

Applications 

The Division conducts research to link ambient air quality and 

human exposure models. Application of these linked models 

helps policy-makers to develop control strategies targeting 

those hazardous air pollutants identified as posing the greatest 

risk to humans. 

Figure 4-1. Multiple scales in air quality modeling. 
14 

Chapter 5 

Linking Sources to Ecosystem Exposure 

Introduction 

Ecosystems provide resources and services that contribute to 

our social and economic welfare. A long-term goal of 

environmental management is to achieve sustainable 

ecological resources through a comprehensive assessment of 

current and projected ecosystem health. Such an assessment 

must include identification of the major threats (in the form of 

specific stressors) to ecosystem health, the source of those 

stressors, and how they move through the environment. This 

is fundamentally a problem of multimedia pollution. 

The overall objective of this work is to develop the 

atmospheric components of multimedia modeling and 

assessment tools to allow better management and protection of 

ecosystems and their associated resources and services. The 

Division is developing a suite of linked models, tools, and 

technology to provide long-range ecological forecasts and a 

scientific basis for decision-making to protect aquatic 

ecosystems. This research supports EPA’s expanded 

definition of air quality management that includes ecosystem 

protection in regulatory assessments of air pollution 

regulations, i.e., setting of secondary NAAQS. It also 

supports EPA’s renewed emphasis on linking sources to 

exposure in a multi-pollutant context and developing 

capabilities for ecosystem risk assessment. 

The interaction between the atmosphere and the underlying 

surface is increasingly being recognized as an important factor 

in multimedia issues. Atmospheric deposition is an important 

source of ecosystem stressors, in particular for acidification, 

eutrophication of coastal estuaries due to excess nitrogen, and 

bioaccumulation of mercury. Critical load is the amount of 

deposition above which natural resources can be negatively 

affected and is intended as a protective threshold. The 

National Academy of Sciences (NAS) has recommended that 

EPA consider a critical load approach to ecosystem 

management.3

 In support of this recommendation, the 

 

3

 Committee on Air Quality Management in the United States, National 

Research council. 2004. Air Quality Management in the United States. 

Washington, DC: National Academy of Sciences. 

Division conducts research to provide the most accurate 

atmospheric deposition estimates possible. 

The Clean Water Act administered by the EPA requires states 

to develop Total Maximum Daily Load limits (TMDLs), the 

maximum amount of a pollutant that a body of water can 

receive while still meeting water quality standards. While the 

atmosphere is an important contributor to stressors such as 

excess nutrients, atmospheric deposition is seldom considered 

in the development of TMDLs. The Division’s research has 

been improving our understanding of the atmospheric 

contribution of stressors to TMDLs. 

Research Description 

For this research theme, the Division has identified research 

areas that have the greatest potential to reduce critical 

uncertainties in atmospheric deposition, assess program 

accountability, and link atmospheric deposition to ecosystem 

resources and services. 

Specific research tasks are grouped under one of the following 

research program elements: 

• Air-Surface Research and Development 

• Multimedia Applications 

• Multimedia Tool Development 

Through the Air-Surface Research and Development

program element, the Division develops and advances airsurface exchange modules for CMAQ and advances the 

linkage between CMAQ and the underlying land-use 

categories to facilitate improved interactions with ecosystem 

models. The Division also develops and advances air-surface 

exchange modules for monitoring network operations using an 

inferential method for dry deposition, focusing primarily on 

sulfur, nitrogen, and mercury species. Bi-directional airsurface exchange process is a new feature of this program 

element. 

Focus areas of Air-Surface Research and Development

include the following: 

• Dry deposition of fine particles 
15 

• Uni-directional deposition of gases 

• Bi-directional flux (air-surface exchange) of 

ammonia 

• Bi-directional flux of mercury 

• Land-surface interface within the CMAQ system to 

support bi-directional fluxes 

• Land-use specific flux determination by CMAQ for 

linkage with ecosystem models 

• Dry deposition and bi-directional flux module 

adaptations for network operations 

Through the Multimedia Applications program element, the 

Division develops and improves linkages between air and 

water models and connections to ecosystem resources and 

services through participation with partners in multimedia 

assessments. National coverage of deposition estimates is an 

important output for these efforts (see Figure 5-1). 

Focus areas of Multimedia Applications include the 

following: 

• Chesapeake Bay 2007/2008 Re-evaluation and 2010 

TMDL assessment 

• Tampa Bay assessment 

• Coastal air-water model linkage development to 

address water quality issues 

• Gulf of Mexico studies 

Through the Multimedia Tool Development program 

element, the Division develops tools for specialized 

multimedia analyses and applications involving atmospheric 

models. The need for specialized tools is especially pertinent 

to bringing atmospheric components together with watershed 

components for multimedia management analyses. Most offthe-shelf tools do not address the specialized needs or 

applications encountered in analyzing data from a multimedia 

perspective. Significant effort is often required to analyze 

observations and model results and provide them in a form 

required to support management decisions. 

Focus areas of multimedia tool development include the 

following: 

• Allocation of spatial data to a CMAQ-useable 

gridded form 

• Watershed deposition tool to overlay gridded CMAQ 

output onto a selected set of watershed segment 

polygons 

• Updating CMAQ visualization tools to be based on 

Java 

Accomplishments 

The Division collaborated with Canadian colleagues to 

compare their respective models that estimate dry deposition 

for network operations, the Routine Deposition Model (RDM) 

for Canada and the Multi-Layer Model (MLM) for EPA’s 

Clean Air Status and Trends Network (CASTNET). Required 

input data for each model were measured at the same 

monitoring site in Canada. These measured concentrations 

agreed quite well with each other. However, there were large 

differences in the deposition velocities calculated by MLM 

and RDM due to different assumptions about how to 

parameterize the dry deposition velocities. These differences 

are now being investigated. 

An evaluation of the MLM for estimating dry deposition used 

in CASTNET pointed to areas for model improvement. In 

response, the Division developed the Multilayer Biochemical 

Model (MLBC) as a replacement for the MLM mode, and 

made progress towards implementing the MLBC for network 

operations. 

The Division partnered with the Chesapeake Bay Program 

Office to provide a series of CMAQ estimates of future 

atmospheric nitrogen deposition out to 2020 simulating 

growth and implementation of new air regulations. The new 

regulations include the Clean Air Interstate Rule (CAIR) the 

Clean Air Mercury Rule (CAMR) and the Clean Air Visibility 

Rule (CAVR). Figure 5-1 shows the 2001 base-case nitrogen 

deposition against which the future scenarios are compared. A 

significant decrease in nitrogen deposition from NOx emission 

reductions is expected, but the growth in ammonia emissions 

erodes these benefits. 

The Division used CMAQ to estimate the relative contribution 

of NOx emissions from mobile sources, power plants, and 

industry to nitrogen deposition in the Chesapeake Bay 

watershed. The Division also investigated uncertainties in the 

CMAQ model for estimating dry deposition of nitrogen to the 

Chesapeake Bay watershed, specifically examining the 

uncertainty in the efficiency of the N2O5 hydrolysis reaction 

that produces nitric acid and uncertainty in the deposition rate 

for ammonia. After reviewing the results, the uncertainties in 

the dry deposition estimates provided to the Chesapeake Bay 

watershed modeling team were deemed to be within 

acceptable bounds. An analysis of ammonia sources and sinks 

with CMAQ showed that the uncertainty in ammonia dry 

deposition rate can significantly affect the area of influence of 

a region of high ammonia emissions. 

The Division completed the evaluation of CMAQ-UCD, a 

sectional version of CMAQ with code developed at the 

University of California, Davis (UCD) that incorporates sea 

salt influences. Model estimates compared well with the Bay 

Regional Air Chemistry Experiment (BRACE) aircraft data. 

The finding that almost half the total nitrate budget in Tampa 

Bay is associated with coarse particle sea salt also agreed with 

the observations. These comparisons set the stage for the 

Tampa Bay assessment to be completed in FY 2007. 

The Watershed Deposition Tool (WDT) is designed to allow 

users to read seasonally- or annually-averaged CMAQ files in 

native format, and calculate a weighted-average deposition or 

change in deposition for selected watershed hydrologic units. 

The Division made improvements to the WDT, adding the 
16 

capability to export GIS Shape files and to continue from the 

point of exit from a previous work session. The revised WDT 

received favorable reviews. Public release of the revised 

WDT is planned for spring 2007. 

Next Steps 

Over the next several years, advancements are planned for the 

multi-media theme area to investigate more sophisticated 

futures scenarios for air-water linkages and to adapt the 

CMAQ modeling system, to calculate bi-directional exchange 

of ammonia and mercury and to more closely couple to 

ecosystems models. Some of the planned milestones are: 

FY-2007 

• Release of MLBCNet to the public, coordinated by 

EPA’s Clean Air Markets Division (CAMD) of the 

Office of Air Programs

• Additional Chesapeake Bay scenarios commissioned 

by the Bay Program. Source responsibility 

calculations re-evaluated

• Completion of the Tampa Bay Assessment for the 

Tampa Bay National Estuary Program

• Bi-directional NH3 flux algorithms incorporated into 

CMAQ

• Release of the Watershed Deposition Tool to the 

public

• Spatial Allocator configured to grid the new National 

Land Cover Data (NLCD) to CMAQ grids

FY-2008 

• Chesapeake Bay futures scenarios simulated with 12-

km grid cell sizes for the eastern US 

• Bi-directional NH3 flux version of CMAQ run for 

Chesapeake Bay sensitivity 

• New mosaic land-use interface incorporated in 

CMAQ for better communication with ecosystem 

models 

• Bi-directional Hg flux paradigm defined 

FY-2009 

• Chesapeake Bay scenarios run with mercury in 

addition to sulfur and nitrogen 

• Advanced land-surface layer to support bi-directional 

flux calculations incorporated in a science version of 

CMAQ 

• Preliminary regional air-water model linkage pilot 

study completed for nitrogen and mercury 

Impacts and Transition of Research to 

Applications 

The Clean Air Status and Trends Network (CASTNET) 

monitors concentration and dry deposition at sites across the 

country to assess long-term trends in air quality, dry 

deposition, and environmental protection resulting from 

regulatory policies and emission reductions required under the 

Clean Air Act. CASTNET is considered the primary source 

for estimates of dry acidic deposition and is vital to the 

Agency’s efforts in the protection of terrestrial and aquatic 

ecosystems. The Division’s development of an improved 

model (MLBC) for dry deposition estimates is a key 

component of CASTNET’s success. 

The major connection between the atmosphere and ecosystems 

is through air-surface exchange, which includes deposition, 

and for some pollutants also includes a bi-directional flux. 

Significant ecosystem stressors that result from air-surface 

exchange include acidifying deposition of nitrogen and sulfur, 

neutralizing deposition of base cations, and eutrophying 

deposition of reduced and oxidized nitrogen. EPA program 

offices such as Office of Water and Office of Air and 

Radiation and states use this information to support their 

policy decisions affecting TMDLs, atmospheric emissions, 

and coastal management. 

Estimates of the expected changes in atmospheric deposition 

to the Chesapeake Bay watershed contribute significant 

information on nitrogen loading that is used by the 

Chesapeake Bay Program to manage the Chesapeake Bay. 

This supports the Chesapeake Bay Program’s commitment to 

reducing nitrogen loads in the Chesapeake Bay by 2010 with 

the help of reductions in atmospheric deposition. In addition, 

this work provides an important test bed for linking 

atmospheric models with watershed models and is a flagship 

of multimedia planning and benefits assessment for a coastal 

estuary. 

Air deposition reductions are a key element of the Tampa Bay 

TMDL implementation strategy required by the Clean Water 

Act. This work will significantly reduce the uncertainty in the 

estimates of nitrogen loading due to atmospheric deposition to 

Tampa Bay watershed basins and bay segments used in the 

Tampa Bay TMDL. The model-estimated effect of courtordered nitrogen oxide (NOx) emissions reductions from two 

electric generating plants adjacent to the bay will provide 

Tampa the best estimate of nitrogen deposition reductions 

across the bay and the watershed attributable to known NOx

emission reductions expected to occur by 2010. The modelestimated effects of deposition reductions due to the recent 

clean air rules will assess whether these rules are keeping up 

with or out-pacing the effects of growth. 

Addressing multimedia issues often requires working with 

multiple types of models and data sets. Proper software tools 

allow environmental scientists and managers to perform their 

work with less effort and allow them to develop insights that 

they might have missed. The software tools developed by this 

project are for community use, but will allow EPA and the 

states to conduct their work more effectively and efficiently 

and provide for a more complete multimedia approach. These 

tools will allow new users to be able to take advantage of the 

results of the more advanced air quality models for multimedia 

applications. The tools will also allow ecosystem and 

watershed managers to take atmospheric deposition into 

account in their planning. 
17 

Figure 5-1. CMAQ annual average (wet plus dry and oxidized plus reduced) nitrogen deposition (in kg-N/ha) across the U.S. based on 3 years of 

differing meteorology - one dry, one wet, and one average precipitation year - across the Eastern U.S. 

2001 Emissions: Annual Total Deposition of Nitrogen (kg-N/ha)

CMAQ Air Quality Model 

Continental Coverage at 36 km x 36 km 
18 

Chapter 6 

Providing Air Quality Forecast Guidance for Health Advisories

Introduction 

An increasing number of clinical and epidemiological studies 

have associated adverse health effects in humans with 

exposure to ambient O3 and fine particulate matter (particles 

with diameter less than 2.5 μm, also called PM2.5). As a result, 

local air quality agencies need accurate forecasts of 

atmospheric pollutant concentrations to alert the sensitive 

populations on the onset, severity, and duration of unhealthy 

air, and to encourage the public and industry to reduce 

emissions-producing activities. The ability to forecast local 

and regional air pollution events is challenging since the 

processes governing the production and accumulation of 

ozone and fine particulate matter are complex and non-linear. 

Comprehensive atmospheric models provide a scientificallysound tool for providing air quality forecast guidance. These 

models represent as much detail as possible the various 

dynamical, physical, and chemical processes regulating the 

atmospheric transport and fate of pollutants. The Division 

develops, applies, evaluates, and improves such models to 

provide robust tools to forecast the day-to-day variability in air 

pollutant concentrations. The principal modeling platform is 

the CMAQ modeling system linked with the North American 

Mesoscale (NAM) model, NOAA/National Weather Service’s 

operational weather prediction model. 

Research Description 

In 2003, EPA and NOAA signed a Memorandum of 

Agreement to collaborate on the design and implementation of 

a system to produce daily air quality modeling forecast 

information. The Division has linked together NOAA’s 

operational NAM-meteorological model and EPA’s CMAQ 

model to form the core of this forecast system. The 

preliminary system provided ground-level ozone predictions 

over the Northeastern United States. Through an on-going 

collaborative program of phased development and testing with 

the National Weather Service, the Division is expanding the 

system’s capability. As of August 31, 2005, the operational 

domain was extended over the entire eastern United States. In 

2006, the domain coverage for experimental O3 predictions 

was expanded to cover the entire continental United States 

(figure 6-1), and the Division began developmental testing for 

PM2.5 forecasts over the continental United States. Over the 

next few years, the Division will expand the operational model 

domain to the continental U.S., and will add PM2.5 to the 

model forecast capability. The Division has already begun 

developmental testing of both of these capabilities. 

NOAA is supporting the basic infrastructure for air quality 

forecasting, with NOAA-EPA/AMD personnel providing 

much of that support. The Division 

• Contributes to the CMAQ model improvements 

through comprehensive diagnostic analyses of model 

forecasts 

• Builds an air quality forecast database at EPA/RTP 

consisting of the daily meteorological, emissions, and 

air quality outputs from the NAM-CMAQ forecast 

system 

• Improves the accuracy of predicted pollutant 

distributions through development and application of 

bias-adjustment methods to correct model errors in 

forecasts either in real-time or in post-process 

• Makes these data available to the air quality 

management community and the general public 

• Provides value-added analyses of the data contained 

in this long-term database (e.g., reanalysis or data 

fusion with observations to create long-term archive 

of ambient air quality and deposition surfaces for 

linkage with exposure studies, analysis of long-term 

spatial and temporal trends in ambient air quality and 

deposition, exploring relationships between ambient 

concentrations and meteorological conditions). 

Accomplishments 

During FY-2006, several major changes were implemented in 

the air quality forecast modeling system: 

• In 2006, the Eta model was replaced by the Weather 

Research and Forecasting Non-hydrostatic Mesoscale 

Model (WRF-NMM) as the operational North 

American Mesoscale meteorological model. To 

reflect this change, modifications were introduced in 

the air quality forecast system to link CMAQ with the 

new version of the NAM. 
19 

• Since the coordinate systems used in the WRF-NMM 

are different from those used in CMAQ, the initial 

linkage between the models was based on 

interpolation of meteorological data from the WRFNMM coordinate structure to that used in CMAQ – a 

method known as “loose coupling.” To reduce errors 

associated with this loose coupling, the interface 

between the WRF-NMM model and CMAQ was 

modified so that the two models would use the same 

vertical coordinate systems for their calculations. 

The updated system provides a more accurate 

representation of the 3-dimensional (3-D) 

meteorological fields. Efforts are underway to also 

include consistent coupling between the horizontal 

coordinate and grid system between the two models. 

• The emission inventories used by the Air Quality 

Forecast system were updated to represent the 2006 

conditions. Continuous Emission Monitoring (CEM) 

data from 2004 were used to generate a base year of 

emission estimates for NOx and SO2 from Electric 

Generating Units. For other pollutants and nonElectric Generating Units, base year 2001 emissions 

were used. Annual Energy Outlook data from the 

Department of Energy was used to project energyrelated emissions from the base year to 2006. 

Vehicle Miles Traveled projected out to 2006, along 

with updated 2006 fleet information, were used to 

estimate mobile source emissions. The emissions 

inventory was also augmented with updated emission 

information from some states. 

• Diagnostic tracers were added to CMAQ to track and 

quantify the influence of lateral boundary conditions 

specified for O3. Analysis of simulated tracer 

distributions indicated that the simulated surfacelevel background O3 is highly dependent on lateral 

boundary conditions specified in the free troposphere. 

Additional analyses of the 3-D O3 and diagnostic 

tracer fields with extensive ozonesonde 

measurements from the 2006 INTEX Ozonesonde 

Network Study are underway. 

Extensive evaluation of archived forecasts results from the 

summer of 2004 were also conducted through comparisons 

with a variety of measurements from surface sites as well as 

aircraft deployed during the 2004 International Consortium for 

Atmospheric Research on Transport and Transformation field 

study. 

Continuous evaluation of particulate matter forecasts results 

from the developmental simulations was performed through 

detailed comparisons with measurements from a variety of 

surface networks. Performance characteristics for PM2.5

forecast over an entire year were investigated with emphasis 

on understanding seasonal biases. A detailed comparison of 

PM2.5 and constituent concentrations forecasts with 

measurements from different surface networks was conducted 

to characterize model performance during the winter-time. 

The Division developed and tested a method to characterize 

real-time emissions from wildfires using satellite information 

from the Hazard Mapping System to detect the location of 

fires. The Division also developed a method to estimate the 

emissions of gaseous and particulate matter constituents from 

these fires for input to CMAQ. Initial testing indicates the 

new wildfire estimates improved CMAQ model performance 

for both O3 and PM2.5 in regions impacted by pollution plumes 

from the fires. 

Next Steps 

FY-2007 

• Continue populating the air quality data archive at 

EPA/RTP with WRF-NMM-CMAQ daily air quality 

forecasts and meteorological data for 2007 

• Conduct initial testing of WRF-NMM-CMAQ 

linkage on the native WRF model E-Grid structure 

• Development and evaluation of post-processing biasadjustment techniques to achieve improved model 

forecasts 

FY-2008 

• Analysis and evaluation of developmental PM 

forecast simulations over the Continental United 

States 

FY-2009 

• Experimental testing of daily PM forecast 

simulations (with NOAA/National Weather Service) 

• Improved methods to specify lateral chemical 

boundary conditions for forecast applications through 

linkage with global models 

Impacts and Transition of Research to 

Applications 

Since early 2003, the Division has worked with NOAA’s 

National Weather Service to develop and deploy a modelbased national air quality forecast guidance system, which 

currently operates at the National Weather Service. Hourly 

ozone forecasts through midnight of the following day are 

available online, providing information on the onset, severity, 

and duration of poor air quality to more than 290 million 

people across the country. Local and state air quality 

forecasters use this tool to create daily air quality outlooks and 

issue air quality alerts, using EPA’s health-based Air Quality 

Index. 

Analysis of model forecasts of air quality will allow EPA and 

NOAA researchers to continuously assess and improve model 

performance. Forecast guidance products have also been used 

for in-field guidance for flight planning during specialized 

field campaigns such as the 2004 International Consortium for 

Atmospheric Transport and Transformation and the 2006 

Texas Air Quality Study. Detailed post-mission analyses of 

model forecast results with extensive measurements from 
20 

these field campaigns have also provided diagnostic 

information on model performance, helping improve the 

science in CMAQ. 

EPA’s archive of the forecast products provides a rich 

repository of daily air quality information that can potentially 

be used for to understand long-term trends in air quality, the 

effectiveness of emission control programs in reducing 

population exposure, and relationships between air pollution 

and human health. 

 

Figure 6-1. Forecast surface-level 8-hour maximum O3 concentrations on August 1, 2006. 
21 

Chapter 7 

Understanding the Relationships between Climate Change and Air Quality 

Introduction 

It is well-known that meteorology has a strong influence on 

ozone and aerosol variability, both spatially and temporally. 

Meteorology over many decades includes variations on 

synoptic, seasonal, and interannual time scales. In addition to 

the long-term, interannual variability, research suggests the 

presence of an increasing trend in temperature over the past 

century and this trend is projected to continue into the future. 

It is important to understand potential impacts from climate 

change on air quality compared with projected improvements 

in air quality stemming from regulatory programs. In addition 

to understanding the responses of air quality to potential 

climate change, the air quality influences on climate must also 

be understood. For example, sulfate aerosols can have a 

cooling effect on the atmosphere through radiation scattering; 

thus, emission controls resulting in substantial decreases in 

sulfate concentrations are likely to affect climate change. 

Using modeling tools that can simulate these interactions 

between climate and air quality, key goals of this theme area 

are to improve our understanding of the impacts of changing 

climate in the future for air quality and to identify potential 

influences on climate from major changes in aerosol loadings. 

Research Description 

The focus of the Climate Impacts on Regional Air Quality 

(CIRAQ) project is characterizing potential effects of climate 

change on regional air quality between now and 2050. The 

results from the CIRAQ project have been generated using a 

coupled global-to-regional downscaled modeling approach. 

Modeling results suggest that a mid-range climate scenario 

fifty years into the future could introduce a moderate increase 

in ozone and a decrease in aerosols in the Eastern United 

States; however, future emission scenarios would introduce a 

much larger difference that has an uncertain direction in both 

magnitude and direction. The CIRAQ project will investigate 

future emission scenarios and test model sensitivity to 

estimate the range of emissions and the resulting impacts on 

air quality. The results from the first series of simulations will 

contribute to the 2007 U.S. EPA national air quality 

assessment report; the emission scenario tests will contribute 

to the 2010 EPA national air quality assessment report. 

Results of CIRAQ will support two of the Synthesis and 

Assessment reports planned for the Climate Change Science 

Program (CCSP), a multi-agency program aimed at improving 

our understanding of the science of climate change and its 

potential impacts. 

In addition to the series of simulations and analyses developed 

under the current CIRAQ project, future research plans 

include additional downscaled regional climate simulations 

using the NOAA Geophysical Fluid Dynamics Laboratory 

(GFDL) global scale models. GFDLs global models are 

regularly scientifically updated, and together with the 

Division’s regional-scale models would provide an advanced 

global to regional scale modeling tool for this research. 

Preliminary linkages and tests are underway, and current 

planning under the NOAA air quality and climate programs 

may provide additional support for this effort. 

The Weather, Research and Forecasting (WRF) model, a new 

generation mesoscale weather model, will be used to produce 

meteorology for CMAQ air quality simulations. The WRFCMAQ model will provide direct feedbacks from aerosols in 

CMAQ to radiation predictions in WRF. The Division will 

use this integrated modeling tool to conduct sensitivity 

simulations to evaluate the potential impact of future air 

quality programs on regional climate. For example, largescale reductions in sulfate concentrations may contribute to 

warming in the United States. 

Accomplishments 

During the next three years, the CIRAQ project members have 

collaborated with Pacific Northwest National Laboratory 

(PNNL) and Harvard University to develop and evaluate a 

series of 10 years of current and 10 years of future (2050) 

down-scaled regional climate simulations. Dr. Ruby Lueng 

(PNNL) led the effort to generate the downscaled climate 

scenarios. 

Approximately four terabytes of regional climate model output 

(i.e., a large volume of data) was transferred and archived 

within the Division. 

A series of scientific papers has been prepared by the Division 

to evaluate these simulations for current time periods and 
22 

characterize the differences from the current to future year 

predictions. 

During 2006, 5 years of current and 5 years of future (2050) 

air quality simulations were developed using these downscaled 

regional climate simulations. 

Next Steps 

FY-2008 

• Development of air quality emission scenarios for 

2050 time period (in collaboration with the National 

Risk Management Research Laboratory) 

FY-2009 

• Completion of 5 years of CMAQ simulations with 

future emission scenarios 

FY-2010 

• Development of manuscript and written contributions 

to the 2010 national air quality assessment report (led 

by EPA’s National Center for Environmental 

Assessment) 

FY-2011 

• Test linkages with the GFDL global-scale climate 

and chemical transport models. 

Impacts and Transition of Research to 

Applications 

Air quality planning procedures rely on present meteorological 

conditions when developing future emission control strategies. 

The research conducted under this theme area will help for 

future years identify the uncertainty introduced when future 

climate influences are not included in the analysis. Modeling 

tools including WRF-CMAQ and global model linkages 

developed in this research will be made available for use in air 

quality management to consider climate variability and trends. 

Sensitivity studies will provide an additional assessment of the 

role of short-lived pollutants on the radiative budget. 
23 

Appendix A 

Division Staff Roster 

Office of the Director 

S. T. Rao, Director 

Patricia McGhee, Assistant to the Director 

Veronica Freeman-Green, Secretary 

Sherry Brown, Support Specialist 

Val Garcia, Deputy Director 

Linda Green, Budget Analyst 

John Irwin (contractor) 

David Mobley (EPA), Associate Director 

Bill Peterson (contractor) 

Dev Roy, (EPA) Post-Doc 

Jeff West, QA Manager 

Atmospheric Model Development Branch 

Ken Schere, Chief 

Shirley Long (SEEP), Secretary 

Prakash Bhave 

Russ Bullock 

Simon Clegg (visiting scientist) 

Rob Gilliam 

Jim Godowitch 

Alan Huber 

Bill Hutzell (EPA) 

Deborah Luecken (EPA) 

Tanya Otte 

Jon Pleim 

Adam Reff (EPA), Post-Doc 

Shawn Roselle 

Golam Sarwar (EPA) 

John Streicher 

David Wong 

Jeff Young 

Yang Zhang (ORISE, Oak Ridge Science and Education 

Program) 

Model Evaluation and Application Research 

Branch 

Alice Gilliland, Chief 

Melanie Ratteray (SEEP), Secretary 

Wyat Appel 

Jerry Davis (ORISE) 

Brian Eder 

Kristen Foley (EPA), Post-Doc 

Steve Howard 

Sergey Napelenok 

Chris Nolte 

Rob Pinder 

Jenise Swall 

Alfreida Torian 

Gary Walter 

Air-Surface Processes Modeling Branch 

Tom Pierce, Chief 

Jane Coleman (SEEP, Senior Environmental Employee 

Program), Secretary 

Bill Benjey 

Jason Ching 

Ellen Cooter 

Robin Dennis 

Vlad Isakov 

George Pouliot 

Donna Schwede 

George Bowker, Fluid Modeling Facility 

David Heist, Fluid Modeling Facility 

Steve Perry, Fluid Modeling Facility 

Ashok Patel (SEEP), Fluid Modeling Facility 

John Rose (SEEP), Fluid Modeling Facility 

Air Quality Forecasting Research Branch 

Rohit Mathur, Chief 

Ann Marie Carlton 

Dale Gillette 

Jerry Herwehe 

Daiwen Kang (contractor) 

Hsin-mu Lin (contractor) 

Daniel Tong (contractor) 

Shaocai Yu (contractor) 

Applied Modeling Branch

Mark Evangelista, Chief 

Dennis Atkinson 

Desmond Bailey 

Pat Dolwick 

Rich Mason 

Brian Orndorff 

Joe Touma
30 

Appendix B 

Division and Branch Descriptions 

Division 

The Division implements the Memorandum of 

Understanding (MOU) and Memorandum of Agreement 

(MOA) between the Department of Commerce (DOC) and 

the Environmental Protection Agency (EPA). In this 

capacity the Division develops and evaluates predictive 

atmospheric models on all spatial and temporal scales for 

forecasting the Nation's air quality, and for assessing 

changes in air quality and air pollutant exposures, as 

affected by changes in ecosystem management and 

regulatory decisions. The Division is responsible for 

providing a sound scientific and technical basis for 

regulatory policies to improve ambient air quality. The 

models developed by the Division are being used by EPA, 

NOAA, and the air pollution community in understanding 

and forecasting not only the magnitude of the air pollution 

problem, but also in developing emission control policies 

and regulations. Established in 1955, the Division serves as 

the vehicle for implementing the agreements between 

NOAA and EPA, which funds the research efforts. 

The Division conducts atmospheric research in-house and 

through contract and cooperative agreements with other 

agencies, academia, and the private sector. With a staff of 

NOAA and EPA scientists, the Division provides technical 

information, observational and forecasting support, and 

consulting on all meteorological and modeling aspects of 

the air pollution control program. In addition to facilitating 

research in the fields of air pollution meteorology and 

atmospheric modeling, The Division interacts extensively 

with academic and other scientific institutions in the U.S. 

and abroad to help support NOAA's and EPA's missionoriented efforts as well as to ensure that the environmental 

community has the benefit of the highest quality peerreviewed science in dealing with air pollution problems. 

Atmospheric Model Development Branch 

The Atmospheric Model Development Branch (AMDB) 

develops, tests, and refines analytical, statistical, and 

numerical models used to describe and assess relationships 

between air pollutant source emissions and resultant air 

quality, deposition, and pollutant exposures to humans and 

ecosystems. The models are applicable to spatial scales 

ranging from local/urban and mesoscale through regional, 

including linkage with global models. AMDB is a key 

advocate in the meteorological modeling community for air 

quality applications. AMDB adapts and extends 

meteorological models to couple effectively with chemicaltransport models to create comprehensive air quality 

modeling systems, including the capability for two-way 

communication and feedback between the models. AMDB 

conducts studies to describe the atmospheric processes 

affecting the transport, diffusion, transformation, and 

removal of pollutants in and from the atmosphere using 

theoretical approaches as well as from analyses of 

monitoring and field study data. The AMDB converts these 

and other study results into models for simulating the 

relevant physical and chemical processes and for 

characterizing pollutant transport and fate in the 

atmosphere. AMDB conducts model exercises to assess the 

sensitivity and uncertainty associated with model input 

databases and applications results. AMDB’s modeling 

research is designed to produce tools to serve the nation's 

need for science-based air quality decision-support systems. 

Model Evaluation and Application Research 

Branch 

The Model Evaluation and Applications Branch (MEARB) 

develops and applies advanced methods for evaluating the 

performance of models in reproducing the observed air 

quality. MEARB provides routine and high performance 

computing support needed by the Division in the 

development, evaluation, and application of environmental 

models. The Branch applies the Division's models to 

important environmental problems, providing scientific 

guidance on their use in air quality decision making. The 

Branch fosters the application of new computational 

techniques and tools to environmental simulation modeling 

and contributes to the interagency Information Technology 

Research and Development program. 

Air-Surface Processes Modeling Branch 

The Air-Surface Processes Modeling Branch (APMB) 

performs process-based modeling research for the 

Division’s atmospheric pollutant models, with a focus on 

three research themes: (1) emissions modeling, (2) 

deposition onto sensitive ecosystems, and (3) linkage of air 

quality with human exposure. APMB’s emissions modeling 

effort (with a special emphasis on natural sources such as 

wind-blown fugitive dust, wildfires, and biogenic 

emissions) helps ensure that meteorologically influenced 

emissions are properly considered in air quality models. 

APMB’s deposition research uses state-of-the-art trace gas 

flux measurements to develop tools for assessing nutrient 

loadings and ecosystem vulnerability. APMB’s urban-scale 

modeling program (which includes collection and 

integration of experimental data from its Fluid Modeling 
31 

Facility is focused on building “hot-spot” air toxic analysis 

algorithms and linkages to human exposure models. 

Air Quality Forecasting Research Branch 

The Air Quality Forecasting Research Branch (AQFRB) 

fosters collaborations between NOAA and EPA in 

developing, applying, and evaluating comprehensive models 

for operational use for providing short-term air quality 

forecast guidance. Through the continuous application of 

the linked meteorological and chemistry-transport models 

and analysis of its predictions, AQFRB develops diagnostic 

information on model performance to guide further 

development and enhancement of physical and chemical 

process representations in the models. AQFRB also works 

on extending the utility of the daily air quality forecast 

model data being produced by NOAA’s National Weather 

Service (NWS) as part of the NOAA-EPA collaboration in 

air quality forecasting, to EPA mission-oriented activities. 

These include developing and maintaining a long-term 

database of air quality modeling results (ozone and PM2.5), 

performing periodic analysis and assessments using the 

data, and making the air quality database available and 

accessible to States, Regions, RPO’s and others to use as 

input data for regional/local scale air quality modeling for 

policy/regulatory purposes. 

Applied Modeling Branch

The Applied Modeling Branch (AMB) evaluates, modifies, 

and improves atmospheric modeling systems and simulation 

techniques to ensure appropriateness and consistency with 

established scientific principles. The Branch evaluates the 

effect of meteorological conditions on air quality and on the 

environmental decisions that are based upon air quality 

assessments and simulations. 
32 

Appendix C 

Awards and Recognition 

Distinguished Career Award

• Dale Gillette - For Outstanding Theoretical and 

Empirical Contributions - International Conference 

on Aeolian Research 

NOAA Silver Medal 

• Ken Schere, Jon Pleim, George Pouliot, Tanya 

Otte, and Jeff Young - CMAQ Air Quality Forecast 

Team 

EPA Bronze Medals 

• David Mobley and Jeff West - NARSTO Emission 

Inventory Assessment 

• Joe Touma and Rich Mason - 2002 National Air 

Toxics Assessment 

• Mark Evangelista and Desmond Bailey - Modeling 

guidance for the Best Available Retrofit 

Technology Rule 

EPA Administrator’s Award for Excellence 

• Pat Dolwick - Economic Analysis Tool 

Development Team 

 

EPA Special Act/Time Off Awards 

• David Mobley, Adam Reff, Golam Sarwar, and 

Prakash Bhave - SPECIATE Update 

• Deborah Luecken - CB05 Development 

• George Bowker - Sand Flux Modeling Papers 

• Dev Roy - Remote Sensing Support and Analysis 

• Bill Hutzell - Addition of toxic species to CMAQ 

NERL Special Achievement Awards 

• Ken Schere - Goal 2: Promote High-Performing 

Organization 

• Robin Dennis - Goal 3: Leadership in the 

Environmental Research Community 

• Prakash Bhave - Goal 4: Science Integration - 

Inter-divisional-laboratory research 

• Alice Gilliland and Vlad Isakov - Goal 5: 

Identifying and Addressing Future Issues 

• Jeff West - Quality Assurance Award 

• David Heist and Steve Perry - Health and Safety 

Award 

NOAA CIYA/Special Act/Time-Off Awards 

• Wyat Appel - Testing new evaluation methods to 

better account for the nature of the data and model 

• Sherry Brown - Analysis and resolution of NOAA 

property records and issues 

• Russ Bullock - Facilitating a major collaborative 

intercomparison of models and model simulation 

results for atmospheric mercury 

• Ellen Cooter - Programmatic and technical support 

to the CIRAQ program 

• Mark Evangelista - Program and policy support for 

model applications 

• Veronica Freeman-Green - Provided exemplary 

support in budget, human resources, and 

purchasing 

• Val Garcia and Linda Green - Resolution of longstanding billing issues associated with the IAG 

• Rob Gilliam - Evaluating the meteorological model 

used for CIRAQ 

• Jim Godowitch - Analysis on the effectiveness of 

major reductions in NOx emissions on ozone 

concentrations 

• Rohit Mathur - Transition of NOAA-EPA Air 

Quality Forecast System to the WRF-NMM system

• Trish McGhee - Exemplary support to the Division 

• Chris Nolte - Completing CMAQ simulations to 

study air quality sensitivities to future climate 

scenarios as part of CIRAQ (Congressional APM) 

• Tom Pierce - Development of research program in 

linking sources to human exposure 

• Evelyn Poole-Kober - Analysis and reconciliation 

of NOAA and EPA peer review database 
33 

Appendix D 

Publications 

(Division authors in bold) 

Journal Articles 

Allen, J.O., P.V. Bhave, J.R. Whiteaker, and K.A. Prather. 

Instrument busy time and mass measurement using aerosol 

time-of-flight mass spectrometry. Aerosol Science and 

Technology, 40:615-626 (2006). 

Arnold, J.R., and R.L. Dennis. Testing CMAQ chemistry 

sensitivities in base case and emissions control runs at 

SEARCH and S0S99 surfaces sites in the southeastern U.S. 

Atmospheric Environment, 40(26):5027-5040 (2006). 

Bowker, G.E., D.A. Gillette, G. Bergametti, and B. 

Marticorena. Modeling flow patterns in a small vegetated 

area in the Northern Chihuahuan Desert using QUIC (Quick 

Urban & Industrial Complex). Environmental Fluid 

Mechanics, 6:359-384 (2006). 

Byun, D., and K.L. Schere. Review of the governing 

equations, computational algorithms, and other components 

of the Models-3 Community Multiscale Air Quality 

(CMAQ) modeling system. Applied Mechanics Reviews,

59:51-77 (2006). 

Ching, J., J. Herwehe, and J. Swall. On joint deterministic 

grid modeling and sub-grid variability conceptual 

framework for model evaluation. Atmospheric Environment, 

40(26):4935-4945 (2006). 

Davis, J.M., and J.L. Swall. An examination of the CMAQ 

simulations of the wet deposition ammonium from a 

Bayesian perspective. Atmospheric Environment,

40(24):4562-4573 (2006). 

Eder, B., D. Kang, R. Mathur, S.Yu, and K. Schere. An 

operational evaluation of the Eta-CMAQ air quality forecast 

model. Atmospheric Environment 40(26):4894-4905 (2006) 

Eder, B., and S. Yu. A performance evaluation of the 2004 

release of Models-3 CMAQ. Atmospheric Environment, 

40(26):4811-4824 (2006). 

Gillette, D.A., J.E. Herrick, and G.A. Herbert. Wind 

characteristics of mesquite streets in the Northern 

Chihuahuan Desert, New Mexico, USA. Environmental 

Fluid Mechanics, 6:241-275 (2006). 

Gilliam, R.C., C. Hogrefe, and S.T. Rao. New methods for 

evaluating meteorological models used in air quality 

applications. Atmospheric Environment, 40(26):5073-5086 

(2006). 

Gilliland, A.B., K.W. Appel, R.W. Pinder, and R.L. Dennis. 

Seasonal NH3 emissions: Inverse model estimation and 

evaluation. Atmospheric Environment, 40(26):4986-4998 

(2006). 

Hanna, A., and W. Benjey. Preface. Special issue on model 

evaluation: Evaluation of urban and regional Eulerian air 

quality models. Atmospheric Environment, 40(26):4809-

4810 (2006). 

Hanna, S.R., M.J. Brown, F.E. Camelli, S.T. Chan, W.J. 

Coirier, O.R. Hansen, A.H. Huber, S. Kim, and R.M. 

Reynolds. Detailed simulations of atmospheric flow and 

dispersion in urban downtown areas by Computational Fluid 

Dynamics (CFD) Models – An application of five CFD 

Models to Manhattan. Bulletin of the American 

Meteorological Society, 87(12):1699-1712. (2006). 

Hogrefe, C., P.S. Porter, E. Gego, A. Gilliland, R. Gilliam, J. 

Swall, J. Irwin, and S.T. Rao. Temporal features in 

observed and simulated meteorology and air quality over the 

Eastern United States. Atmospheric Environment, 

40(26):5041 -5055 (2006). 

Huber, A.H. Development of CEO simulations in support of 

air quality studies. Wind Engineering Research Center, 

Tokyo Polytechnic University. Wind Effects Bulletin, 5:8-10 

(2006). 
34 

Huber, A.H., M. Freeman, R. Spencer, W. Schwartz, B. Bell, 

and K. Kuehlert. Pollution dispersion in urban landscapes. 

Fluent News, XV(2): 13-16 (2006). 

Isakov, V., and A. Venkatram. Resolving neighborhood scale 

in air toxics modeling: a case study in Wilmington, 

California. Journal of Air & Waste Management 

Association, 56:559-568 (2006). 

lsakov, V., S. Graham, J. Burke, and H. Ozkaynak. Linking 

air quality and exposure models. Environmental Manager, 

September, 26-29 (2006). 

Luecken, D., W. Hutzell, and G. Gipson. Development and 

analysis of air quality modeling simulations for hazardous 

air pollutants. Atmospheric Environment special issue on 

Model Evaluation: Evaluation of Urban and regional 

Eulerian Air Quality Models, 40(26):5087-5096 (2006). 

Miller, A.C., G. Hidy, J. Hales, C.E. Kolb, A. S. Werner, B. 

Haneke, D. Parrish, H. C. Frey, L. Rojas-Bracho, M. 

Deslauriers, B, Pennell, and J.D. Mobley. Air emission 

inventories in North America: A critical assessment. Air & 

Waste Management Association, 56:1115-1129 (2006). 

Okin, G., and D.A. Gillette. Multi-scale controls on and 

consequences of aeolian processes in landscape change in 

arid and semi-arid environments. Journal of Arid 

Environments, 65:253-275 (2006). 

Pennell, W., and D. Mobley. The case for improving emission 

inventories in North America. Environmental Manager,

January: 24-27 (2006). 

Phillips, S.B., and P.L Finkelstein. Comparison of spatial 

patterns of pollutant distribution with CMAQ predictions. 

Atmospheric Environment, 40(26):4999-5009 (2006). 

Pinder, R.W., P.J. Adams, S.N. Pandis, and A.B. Gilliland. 

Temporally resolved ammonia emission inventories: 

Current estimates, evaluation tools, and measurement needs. 

Journal of Geophysical Research-Atmospheres, 111(Dl 

6310): 1-14 (2006). 

Pinto, J.P., L.D. Grant, A.F. Vette, and A.H. Huber. 

Evaluation of potential human exposures to airborne 

particulate mailer following the collapse of the World Trade 

Center towers. In Urban Aerosols and Their Impacts--

Lessons Learned from the World Trade Center Tragedy. J.S. 

Gaffney, and NA. Marley (Eds.). American Chemical 

Society, Washington, DC, 190-237 (2006). 

Pleim, J.E. A simple efficient solution of flux-profile 

relationships in the atmospheric surface layer. Journal of 

Applied Meteorology and Climatology, 45:341-347 (2006). 

Qin, X., P.V. Bhave, and K.A. Prather. Comparison of two 

methods for obtaining quantitative mass concentrations 

from aerosol time-of-flight mass spectrometry 

measurements. Analytical Chemistry, 78:6169-6178 (2006). 

Rao, S.T. Understanding the relationships between air quality 

and human health. Environmental Manager, September, 6-7 

(2006). 

Swall, J.L., and J.M. Davis. A Bayesian statistical approach 

for the evaluation of CMAQ. Atmospheric Environment, 

40(26):4883-4893 (2006). 

Touma, J.S., V. lsakov, J. Ching, and C. Seigneur. Air 

quality modeling of hazardous pollutants: Current status and 

future directions. Journal of Air & Waste Management 

Association, 56:547-558 (2006). 

Yu. S., B. Eder, R. Dennis, S. H.Chu, and S.E. Schwartz. 

New unbiased symmetric metrics for evaluation of air 

quality models. Atmospheric Science Letters, 7:26-34 

(2006). 

Yu, S., R. Mathur, D. Kang, K. Schere, B. Eder, and J. 

Pleim. Performance and diagnostic evaluation of ozone 

predictions by the Eta-Community Multiscale Air Quality 

Forecast System during the 2002 New England Air Quality 

Study. Journal of the Air & Waste Management 

Association, 56:1459-1471, (2006). 

Yuan, J., A. Venkatram, and V. lsakov. Dispersion from 

ground-level sources in a shoreline urban area. Atmospheric 

Environment, 40:1361-1372 (2006). 

Zhang, KM., E.M. Khipping, A.S. Wexler, P.V. Bhave, and 

G.S. Tonnesen. Reply to comment on “Size distribution of 

sea-salt emissions as a function of relative humidity.” 

Atmospheric Environment, 40:591-592 (2006). 

Book Chapters 

Gillette, D.A., and H.C. Monger. Eolian processes on the 

Jornada Basin. In Structure and Function of a Chihuahuan 

Desert Ecosystem. Jornada Long Term Ecological Research 

Volume. Chapter 9. Havstad, KM., L.F. Huenneke, and 

W.H. Schlesinger (Eds.). Oxford University Press, New 

York, 189-210 (2006). 

Conference Papers and Proceedings 

Appel, W. K., and A.B. Gilliland. Effects of vertical-layer 

structure and boundary conditions on CMAQ v4.5 and v4.6 

model performance. 5th Annual CMAS Models – 3 User’s 

Conference, Chapel Hill, NC, Oct. 16-18, 2006. 
35 

Bowker, G.E., D.K. Heist, S.G. Perry, L.A. Brixey, R.S. 

Thompson, and R.W. Wiener. The influence of a tall 

building on street canyon flow in an urban neighborhood. 

Preprints, 28th NATO/CCMS International Technical 

Meeting on Air Pollution Modeling and its Application, 

Leipzig, Germany, pp. 58-59, May 15-19, 2006. 

Brown, M.J., S.U. Pal, W. Coiner, S. Kim, A. Huber, M.A. 

Nelson, P. Klein, M. Freeman, and A. Gowardhan. 

Experimental and model-computed area-averaged vertical 

profiles of wind speed for evaluation of mesoscale urban 

canopy schemes. Preprints, 6th Symposium on Urban 

Environment, Atlanta, Georgia. American Meteorological 

Society, Boston, Paper J1 .7, available online 

http://ams.confex.com/ams/pdfpapers/105229.pdf, Jan. 29-

Feb. 2, 2006. 

Bullock, O.R., Jr., D. Atkinson, T. Braverman, A. Dastoor, 

D. Davignon, N. Eckley Selin, D. Jacob, K. Lohman, C. 

Seigneur, K. Vijayaraghavan, T. Myers, K. Civerolo, and C. 

Hoprefo. The North American Mercury Model Intercomparison Study (NAMMIS). Preprints, 28th NATO/CCMS 

International Technical Meeting on Air Pollution Modeling 

and its Application, Leipzig, Germany, pp. 60-61, May 15-

19, 2006. 

Bullock, O. R., Jr., and T. Braverman. Application of the 

CMAQ mercury model for U.S. EPA regulatory support. 

Preprints, 28th NATO/CCMS International Technical 

Meeting on Air Pollution Modeling and its Application, 

Leipzig, Germany, pp. 62-69, May 15-19, 2006. 

Ching, J., V. lsakov, MA. Majeed, and J.S. Irwin. An 

approach for incorporating sub-grid variability information 

into air quality modeling. Proceedings, 14th Joint 

Conference on the Applications of Air Pollution 

Meteorology with the Air and Waste Management 

Association, Atlanta, GA, pp. 11, Jan. 28- Feb. 2, 2006. 

Cooter, E.J., R. Gilliam, W. Benjey, C. Nolte, J. Swall, and 

A. Gilliland. Examining the impact of changing climate on 

regional air quality over the United States. Preprints, 28th

NATO/CCMS International Technical Meeting on Air 

Pollution Modeling and its Application, Leipzig, Germany, 

pp. 100-113, May 15-19, 2006. 

Godowitch, J., A.B. Gilliland, S.T. Rao, F. Gego, and P.S. 

Porter. Integrated observational and modeling approaches 

for evaluating the impact of emission control policies. 

Preprints, 28th NATO/CCMS International Technical 

Meeting on Air Pollution Modeling and its Application, 

Leipzig, Germany, pp. 198, May 15-19, 2006. 

Godowitch, J.M. and R.R. Draxler. Linking the CMAQ and 

HYSPLIT modeling systems: Interface program and 

example application. 5th Annual CMAS Models – 3 User’s 

Conference, Chapel Hill, North Carolina, Oct. 16-18, 2006. 

Huber, A.H., M. Freeman, R. Spencer, B. Bell, K. Kuehlert, 

and W. Schwarz. Development and applications of CFD 

simulations supporting urban air quality and homeland 

security. Preprints, 6th Symposium on Urban Environment, 

Atlanta, Georgia. American Meteorological Society, 

Boston, Paper J7.4, available online at 

http://ams.confex.com/ams/pdfpapers/105308.pdf, Jan. 29-

Feb. 2, 2006. 

Huber, A.H. A framework for fine-scale computational fluid 

dynamics air quality modeling and analysis. 5th Annual 

CMAS Models – 3 User’s Conference, Chapel Hill, NC, 

Oct. 16-18, 2006. 

 

Hutzell, W.T., G. Pouliot, and D.J. Luecken. Changes to the 

chemical mechanisms for hazardous air pollutants in CMAQ 

version 4.6. 5th Annual CMAS Models – 3 User’s 

Conference, Chapel Hill, North Carolina, Oct. 16-18, 2006. 

Kang, D., R. Mathur, S. Yu, and K. Schere. Performance 

characteristics of Eta-CMAQ 03 forecast over different 

regions of the Continental United States. Preprints, 28th

NATO/CCMS International Technical Meeting on Air 

Pollution Modeling and its Application, Leipzig, Germany, 

pp. 314-321, May 15-19, 2006. 

Otte, T.L. The value of nudging in the meteorological model 

for retrospective CMAQ simulations. 5th Annual CMAS 

Models – 3 User’s Conference, Chapel Hill, NC, Oct. 16-18, 

2006. 

Pleim, J.E. A new combined local and non-local PBL model 

for meteorology and air quality modeling. 5th Annual CMAS 

Models – 3 User’s Conference, Chapel Hill, NC, Oct. 16-

18, 2006. 

 Pleim, J.E., S. Roselle, P. Bhave, R. Bullock, Jr., W. 

Hutzell, D. Luecken, C. Nolte, G. Sarwar, K. Schere, J. 

Young, J. Godowitch, and W. Appel. The 2006 CMAQ 

release and plans for 2007. 5th Annual CMAS Models – 3 

User’s Conference, Chapel Hill, NC, Oct. 16-18, 2006. 

Porter, P.S., E. Gego, A. Gilliland, C. Hogrefe, J. Godowitch, 

and S.T. Rao. Modeling assessment of the impact of 

nitrogen oxide emission reductions on ozone air quality in 

the eastern United States: Offsetting increases in energy use. 

28th NATO/CCMS International Technical Meeting on Air 

Pollution Modeling and its Application, Leipzig, Germany, 

May 15-19, 2006. 

Porter, P.S. and S.T. Rao. The relationship between 

meteorology and NOx emissions from electrical generating 

units in the U.S. 28th NATO/CCMS International Technical 

Meeting on Air Pollution Modeling and its Application, 

Leipzig, Germany, May 15-19, 2006. 
36 

Sarwar, G., D. Luecken, and G. Yarwood. Developing and 

implementing an updated chlorine chemistry into the 

Community Multiscale Air Quality model. Preprints, 28th

NATO/CCMS International Technical Meeting on Air 

Pollution Modeling and its Application, Leipzig, Germany, 

pp. 497-504, May 15-19, 2006. 

Schere, K., V. Bouchet, G. Grell, J. McHenry, and S. 

McKeen. The emergence of numerical air quality 

forecasting models and their application. Preprints, 14th

Joint Conference on the Applications of Air Pollution 

Meteorology with the Air & Waste Management 

Association, and 86th Conference on Atmospheric 

Chemistry, Atlanta, Georgia. American Meteorological 

Society, Boston, Paper J10.1, available online at 

http://ams.confex.com/ams/pdfpapers/102293.pdf, Jan. 29-

Feb. 2, 2006. 

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