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Summary Report of
Air Quality Modeling
Research Activities for 2006
RESEARCH AND DEVELOPMENT
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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
ST. 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
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 National Oceanic and Atmospheric Administration
Office of Research and Development Office of Oceanic and Atmospheric Research
Washington, DC 20460 Silver Spring, Maryland, 20910
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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.
ill
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Abstract
Through a Memorandum of Understanding (MOU) and Memorandum of Agreement (MO A) 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.
IV
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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
ChapterS: 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
v
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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 paniculate 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
VI
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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.
vn
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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 l-l1. 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?
Exposure Science Research: A Conceptual Framework, November 2006
Draft by EPA's National Exposure Research Laboratory.
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• 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.
Source-to-Outcome Continuum
Figure 1-1. The Division's role in the Source-Exposure-Dose-Effects Continuum.
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Strategy to Meet User Needs
/
Sound Science for Environmental Decisions
1
/
Evaluating the impact of regulatory policies on air quality & ecosystems
Linking sources to human exposure
Linking sources to ecosystem exposure
Providing air quality forecasts guidance for health advisories
Und
erstanding the relationships between climate change and air qi
lality
/
Atmospheric Model
Development
Branch
Model Eval. &
Applications
Research Branch
Air- Surface
Processes Modeling
Branch
Air Quality
Forecasting
Research Branch
Applied Modeling
Branch
A
Atmospheric Modeling Division
Figure 1-2. Strategy to meet user needs.
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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 paniculate
matter (PM25), coarse paniculate 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 PM25 from 65 to 35 ug/m3, and dropped the annual
average standard for PM10, leaving only the daily standard of
150 ug/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 inter-
related. 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
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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 PM25 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 um diameter). Figure 2-2 illustrates the treatment of
paniculate 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 PM25 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 (Hg°), reactive gaseous mercury
(ROM), and paniculate mercury (Hg(p)) emissions, as well as
the chemical reaction pathways to transform Hg° into ROM.
When deposited in water bodies, ROM 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 paniculate 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
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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 PM25 have identified
that the PM "other" category is contributing substantially to
over predictions of PM25 during the fall and winter,
suggesting uncertainty in the primary PM25 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 PM25 sources.
New advancements in diagnostic evaluation methods have
also been emerging. For example, the analysis of CMAQ's
paniculate 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. coal-
fired 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 PM25. 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 long-
term 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.
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Figure 2-1. Schematic of CMAQ modeling system, including meteorology, emissions, and air quality models.
CMAQ Aerosol Module
Alrimodal size distribution
Gas/particle interactions treated
for fine modes only
Fine-modes coagulate
Coarse mode, fine EC (black) &
V^other fine PM (brown) are inert
SVOCs
Aromatics
Monoterpenes
HNO,
H2S04
HCI
H2O
COARSE MODE
2 FINE MODES
Figure 2-2. Schematic of particulate matter/aerosol module in CMAQ model.
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July Average PM2 5 vs STN
STN Stacked Barplot for July 2001
CMACM.6
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).
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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 non-
attainment.
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 non-
road 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 paniculate
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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.
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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.
ppbV
ppbV
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.
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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 grid-
based 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
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. Erode. 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 Near-
Roadway 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.
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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
2
Improved CMAQ :
scale applications.
FY-2012
• Improved CMAQ modeling system for use in urban-
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.
Regional scale
Figure 4-1. Multiple scales in air quality modeling.
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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
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 air-
surface 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 air-
surface exchange process is a new feature of this program
element.
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.
Focus areas of Air-Surface Research and Development
include the following:
• Dry deposition of fine particles
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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 off-
the-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
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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 court-
ordered 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 model-
estimated 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.
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20.00112
15.00
12.50
10.00
7.50
5.00
2.50
0.00
kg/ha
PWE
CMAQ Air Quality Model
Continental Coverage at 36 km x 36 km
148
2001 Emissions: Annual Total Deposition of Nitrogen (kg-N/ha)
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.
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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 paniculate matter (particles
with diameter less than 2.5 um, 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 paniculate matter are complex and non-linear.
Comprehensive atmospheric models provide a scientifically-
sound 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
PM25 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 PM25 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.
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• 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 WRF-
NMM 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 non-
Electric Generating Units, base year 2001 emissions
were used. Annual Energy Outlook data from the
Department of Energy was used to project energy-
related 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 surface-
level 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 paniculate matter forecasts results
from the developmental simulations was performed through
detailed comparisons with measurements from a variety of
surface networks. Performance characteristics for PM25
forecast over an entire year were investigated with emphasis
on understanding seasonal biases. A detailed comparison of
PM25 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 paniculate 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 bias-
adjustment 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 model-
based 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
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these field campaigns have also provided diagnostic be used for to understand long-term trends in air quality, the
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
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.
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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 WRF-
CMAQ 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, large-
scale 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
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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.
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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 Finder
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 Cooler
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
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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 mission-
oriented efforts as well as to ensure that the environmental
community has the benefit of the highest quality peer-
reviewed 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 chemical-
transport 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
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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.
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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 Mob ley 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 ClYA/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 Cooler - 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 long-
standing 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 Nolle - Completing CMAQ simulations to
sludy air quality sensitivities lo future climate
scenarios as part of CIRAQ (Congressional APM)
• Tom Pierce - Developmenl of research program in
linking sources lo human exposure
• Evelyn Poole-Kober - Analysis and reconciliation
of NOAA and EPA peer review database
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Appendix D
Publications
(Division authors in bold)
Journal Articles
Allen, J.O., P.V. Bhave, J.R. Whiteaker, and K.A. Prather.
Instalment 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 SOS99 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, RW. Finder, and RL. 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., MJ. 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).
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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).
Isakov, 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).
Finder, RW, 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(D1
6310): 1-14(2006).
Pinto, J.P., L.D. Grant, A.F. Vette, and A.H. Huber.
Evaluation of potential human exposures to airborne
paniculate 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, andNA. 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. Isakov, 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. Isakov. 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 CMASModels - 3 User's
Conference, Chapel Hill, NC, Oct. 16-18, 2006.
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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/CCMSInternational 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 Jl .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 Inter-
comparison 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. Isakov, 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 Gil Mam W. Benjey, C. Nolte, J. Swall, and
A. Gill Hand 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 PEL 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.
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Sarwar, G., D. Luecken, and G. Yarwood. Developing and
implementing an updated chlorine chemistry into the
Community Multiscale Air Quality model. Preprints, 28th
NATO/CCMSInternational 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, 14*
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.
Tang, W., A. Huber, B. Bell, K. Kuehlert, and W. Schwarz.
Application of CFD simulations for short-range atmospheric
dispersion over open fields and within arrays of building.
Preprints, 14th Joint Conference on the Applications of Air
Pollution Meteorology with the Air & Waste Management
Association, Atlanta, Georgia. American Meteorological
Society, Boston, Paper JI .8, available online at
http://ams.confex.com/ams/pdfpapers/104335.pdf. Jan. 29-
Feb. 2, 2006.
Yu, S., R Mathur, K. Schere, D. Kang, J. Pleim, J. Young,
and T. Otte. A study of process contributions to ozone
formation during the 2004 ICARTT period using the Eta-
CMAQ forecast model over the Northeastern U.S. Preprints,
28th NATO/CCMS International Technical Meeting on Air
Pollution Modeling and its Application, Leipzig, Germany,
pp. 608-615, May 15-19, 2006.
36
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United States
Environmental Protection
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PRESORTED STANDARD
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EPA/600/R-07/103
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NOAA Technical
Memorandum
OAR ARL-259
10/2007
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