United States
Environmental Protection
Agency
Summary Report of
Air Quality Modeling
Research Activities for
2007
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EPA /600/R-09/025
March 2009
Summary Report of
Air Quality Modeling
Research Activities for
2007
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
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
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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 peer and administrative review and has been approved for publication as an EPA
document. Mention of trade names or commercial products does not constitute endorsement or
recommendation for use.
11
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Abstract
Through a Memorandum of Understanding (MOU) and Memorandum of Agreement (MOA) between
the U.S. Department of Commerce (DOC) and the U.S. Environmental Protection Agency (EPA), the
Atmospheric Sciences Modeling Division (ASMD) of the 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 quality community not only to understand and forecast the magnitude of the air pollution problem,
but also to develop emission control policies and regulations. This report summarizes the research and
operational activities of the Division for fiscal year 2007.
ill
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Contents
Notice ii
Abstract iii
Figures vi
Acknowledgements vii
Chapter 1: Introduction 1
Chapter 2: Providing Scientifically-Advanced Models and Tools to Support Environmental
Policy Decisions 3
Introduction 3
Research Description 3
Accomplishments 4
Next Steps 6
Impacts and Transition of Research to Applications 6
Chapter 3: Evaluating the Impact of Regulatory Policies on Air Quality and Ecosystems 8
Introduction 8
Research Description 8
Accomplishments 9
Next Steps 9
Impacts and Transition of Research to Applications 9
Chapter 4: Linking Sources to Human Exposure 11
Introduction 11
Research Description 12
Accomplishments 12
Next Steps 13
Impacts and Transition of Research to Applications 15
ChapterS: Linking Sources to Ecosystem Exposure 16
Introduction 16
Research Description 16
Accomplishments 17
Next Steps 18
Impacts and Transition of Research to Applications 18
Chapter 6: Providing Air Quality Forecast Guidance for Health Advisories 20
Introduction 20
Research Description 20
Accomplishments 20
Next Steps 21
Impacts and Transition of Research to Applications 21
Chapter 7: Understanding the Relationships between Climate Change and Air Quality 23
Introduction 23
Research Description 23
Accomplishments 23
Next Steps 25
Impacts and Transition of Research to Applications 25
Appendix A: Division Staff Roster 26
Appendix B: Division and Branch Descriptions 27
Appendix C: Awards and Recognition 29
Appendix D: Publications 30
Appendix E: Abbreviations 35
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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 2
2-1 Schematic of CMAQ modeling system, including meteorology, emissions, and air quality models 7
3-1 Assessing the impact of regulations on ecosystems and human health endpoints showing
the indicators (boxes) and process linkages (arrows) associated with the NOX Budget Trading
Program 10
4-1 Multiple scales in air quality modeling 15
5-1 WDT screen capture showing the CMAQ 2002 annual total nitrogen deposition (kg-N/ha)
for the 36-km grid resolution with the overlay of 8-digit Hydrologic Unit Code (HUC) delineations
for the Cape Fear Basin and Albemarle-Pamhco Sound system 19
5-2 WDT screen capture showing the average 2002 annual total nitrogen deposition (kg-N/ha)
to each watershed segment in the Cape Fear Basin and Albemarle-Pamlico Sound system 19
6-1 Forecast surface-level 8-hour maximum O3 concentrations on August 15, 2007. Color-coded
diamonds indicate corresponding observed levels 22
7-1 Average summer (June-August, or JJA) difference between future - current regional climate scenarios
for temperature, isoprene emissions, and solar radiation reaching the surface 24
7-2 Increase (future-current) in O3 concentrations under future climate conditions when comparing the
95th % of the O3 distribution (i.e., high O3 episodes). The summer (JJA) and fall (September and
October) months are compared 24
7-3 Average summer increase (future-current) in O3 when methane concentrations increase from 1.8 ppm
to2.4ppm 25
VI
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Acknowledgments
The authors acknowledge the support of Patricia McGhee of the Division for technical editing and
manuscript preparation.
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Chapter 1
Introduction
The National Oceanic and Atmospheric Administration
(NOAA) Atmospheric Sciences Modeling Division (ASMD)
works within the frameworks of the Memorandum of
Understanding and Memorandum of Agreement between the
U.S. Department of Commerce (DOC) and the U.S. Environ-
mental Protection Agency (EPA). These agreements are
implemented through long-term Interagency Agreements
DW13938483 and DW13948634 between EPA and NOAA.
The Division is organized into four research branches:
Atmospheric Model Development Branch
Model Evaluation and Applications Branch
Air-Surface Processes Modeling Branch
Applied Modeling Branch
The first three branches above constitute the Atmospheric
Modeling Division (AMD) of the National Exposure Research
Laboratory (NERL) of the Office of Research and Devel-
opment (ORD) within EPA's organizational structure. The
fourth 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." The appendices to this report
contain a list of Division employees (Appendix A), descrip-
tions of the Division and its branches (Appendix B), a list of
awards earned by Division personnel (Appendix C), and a list
of Division publications (Appendix D).
The Division's role within the source-to-outcome continuum
is to conduct research that improves the Agency's under-
standing of the linkages from source to exposure (see 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), other federal
agencies, and state and local pollution control agencies.
Adapted from "A Conceptual Framework for U.S. EPA's National Exposure
Research Laboratory," November 2007 Draft by EPA/NERL.
The Division provides this technical support and expertise
using an interdisciplinary approach that emphasizes integra-
tion 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.
The Division has completed a major strategic planning process
begun in 2002. We identified six outcome-oriented Theme
Areas:
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, by
considering these questions:
Over the next two to three years, who are the major
clients and what are their needs?
What research investments are needed to further the
science ways 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?
Does the proposed work fall within the current scope
and plans of existing projects, or would personnel
resources need to be shifted from other projects to
make this happen?
The result is a research strategy for meeting user needs that is
built around the six major Theme Areas and supported by the
four branches of the Division, as depicted in Figure 1-2. The
Division's Applied Modeling Branch also supports the three
research- and development-focused branches by facilitating
the transition of atmospheric modeling systems and other
research tools to regulatory applications.
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This report summarizes the research and operational activities
of the Division for fiscal year 2007. It includes descriptions of
research and operational efforts in air pollution meteorology.
in meteorology and air quality model development, and in
model evaluation and applications. The rest of this report
(Chapters 2 through 7) is organized according to the six major
program themes listed above, also shown in Figure 1-2.
Source-to-Outcome Continuum
Figure 1-1. The Division's role in the source-exposure-dose-effects continuum.
Strategy to Meet User Needs
Sound Science for Environmental Decisions
Providing scientifically-advanced models & tools to support environmental policy decisions
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
Understanding the relationships between climate change and air quality
Figure 1-2. The Division's strategy to meet user needs.
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Chapter 2
Providing Scientifically Advanced Models and Tools to Support
Environmental Policy Decisions
Introduction
The Clean Air Act (CAA) requires that EPA set National
Ambient Air Quality Standards (NAAQS) for air pollutants
considered harmful to public health and the environment.
Thresholds for six criteria pollutants have been established:
carbon monoxide (CO), lead (Pb), nitrogen oxides (NOX), fine
paniculate matter (PM25) and coarse paniculate matter
(PMio), tropospheric ozone (O3), and sulfur oxides (SOX). EPA
reviews each NAAQS every five years, and proposes changes
if the most current science on health and ecological effects
suggests changing the standards. For example, in 2006 EPA
revised the standards for daily average PM25 from 65 to 35
ug/m3, and eliminated the annual average standard for PM10,
leaving only the daily standard of 150 ug/m3.
When a geographic area exceeds the NAAQS for a criteria
pollutant, EPA may designate that area as being in
"nonattainment." In response, the state containing that area
must develop a State Implementation Plan (SIP) that explains
how the state will achieve compliance with the NAAQS. The
principal tools that EPA and the states use to demonstrate this
compliance are air quality simulation models. Each SIP must
include a modeling demonstration illustrating how the state
intends to mitigate emissions (usually through additional
emission controls) to achieve compliance with the standard.
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 (mercury, for example, falls into
both those categories). While there is a range of air quality
policy-related issues that are tracked separately for individual
pollutants, the pollutants' chemistry and the sources involved
in producing harmful air quality conditions are interrelated.
Therefore, a multipollutant 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.
These models represent, in as much detail as possible, the
various dynamical, physical, and chemical processes
regulating the atmospheric transport and fate of pollutants.
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
Within this Theme Area, the principal elements of the
modeling program are Model Development and Model
Evaluation. These elements are interrelated and form an
iterative process: model evaluation provides information for
improving the models; models are then improved through
research and development; the improved models are re-
evaluated; and (assuming successful re-evaluation) the
improved models are then available for regulatory application.
Through the Model Development program element, the
Division develops and improves the CMAQ air quality model
for a variety of spatial scales (urban through continental) and
temporal scales (days to years) and for a variety of pollutants
(O3, PM, mercury and other air toxics, visibility, acid depo-
sition). The multipollutant model approach permits the testing
of emission 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 (PEL) 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 designed to provide feedback from air quality
parameters (e.g., aerosols) that affect meteorological
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parameters (e.g., radiation). Developmental areas are guided
by the model evaluation results and by model sensitivity and
uncertainty tests. New CMAQ model versions are released for
public access roughly every one to two years. Workgroups
have been formed to focus on these research topics:
Atmospheric chemistry and aerosols
Two-way interactive meteorology-chemistry-trans-
port modeling
Weather Research and Forecasting (WRF) 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. We compare different CMAQ sim-
ulations (e.g., different model versions, different chemical
mechanisms, different vertical layer structuring) 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. We conduct model evalu-
ation 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
In the area of model development, a multipollutant version of
the CMAQ modeling system was developed to predict ozone,
PM, and mercury and 38 other HAPs in a single model
configuration. We created this model version in response to
increasing interest in modeling multiple pollutants, including
criteria and hazardous air pollutants, within a single modeling
framework for air quality management. The new model will
support regional and urban studies that assess the potential co-
benefits and effectiveness of various emission control pro-
grams, such as the Clean Air Interstate Rule (CAIR)*, Clean
Air Mercury Rule (CAMR)*, Clean Air Visibility Rule
(CAVR), and various onroad and nonroad mobile source rules.
It will also support future assessment studies based on
Note that CAIR and CAMR are currently in litigation and that the research
programs may be adjusted by the resolution of the legal issues.
integrated national emission inventories containing both HAPs
and criteria pollutants. The multipollutant model was devel-
oped by modifying and merging algorithms for gas-phase
chemistry, aerosols, clouds, and emissions used in the mercury
and HAPs versions of CMAQ. The Carbon Bond 05 (CB05)
chemical mechanism was combined with the chemical
reactions for chlorine, mercury, and HAPs, and implemented
into the CMAQ modeling system. A normalization process
was performed to test the model and to ensure that the
multipollutant model is consistent with the original versions.
Results suggest that consistency is achieved by including the
emissions and chemistry of molecular chlorine (C12) and
hydrochloric acid (HC1) in each model version. The multi-
pollutant model will be included in the 2008 release of
CMAQ.
During 2007, in collaboration with a variety of private and
governmental research organizations, the Division completed
the analysis of results from the North American Mercury
Model Intercomparison Study (NAMMIS). The NAMMIS
employed global-scale modeling of atmospheric mercury to
define initial and boundary conditions for three regional-scale
mercury models that were the primary subjects of the study:
the CMAQ model, developed and applied by the Division; the
Regional Modeling System for Aerosols and Deposition
(REMSAD), developed and applied by ICF International; and
the Trace Element Analysis Model (TEAM), developed by
Atmospheric and Environmental Research, Inc. The CMAQ,
REMSAD, and TEAM simulations of the air concentration
and wet and dry deposition of various mercury species during
the 2001 test period were compared on time scales from
weekly to annual. The simulations of wet deposition of
mercury from CMAQ, REMSAD, and TEAM were also com-
pared against observations from the Mercury Deposition
Network on time scales from weekly to annual. Considerable
model-to-model differences were found for air concentration,
dry deposition, and wet deposition. Statistical agreement
between simulated annual wet deposition and the corre-
sponding observation was found to be largely scaled to the
statistical accuracy of the precipitation data input to all three
models; these data were derived from prior meteorological
modeling. On shorter time scales, the statistical agreement for
mercury wet deposition was weaker than for the input
precipitation data, indicating that the physicochemical
processes controlling the wet deposition of mercury may still
not be accurately treated in any of the models tested. At the
end of 2007, results from the NAMMIS were being described
in two manuscripts intended for publication in peer-reviewed
scientific journals.
We also worked to improve the representation of reactive
nitrogen chemistry in CMAQ. Similar to other air quality
models, the CMAQ model currently accounts for only the
homogeneous chemical reactions of nitrous acid (HONO).
Studies have indicated that air quality models that take into
account only the homogeneous reactions are not adequate to
explain the observed ambient HONO. Recent evidence
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suggests that direct emissions and a heterogeneous reaction
involving nitrogen dioxide and water vapor may play an
important role in HONO chemistry. To improve the model
performance for HONO, these additional sources have been
included in CMAQ. The inclusion of these sources does
indeed improve the model performance for HONO.
During 2007, several advances were made in the simulation of
aerosol chemistry and physics. We focused on heterogeneous
nitrogen chemistry, coarse-particle chemistry, trace-elemental
composition of particles, and aerosol thermodynamics. The
heterogeneous reaction probability of N2O5 on wetted particle
surfaces (y^os) is an influential parameter affecting
wintertime predictions of fine-particulate nitrate (NO3~).
Division scientists discovered a typographical error in the
published parameterization of yN205 that had been translated
into the CMAQ v4.6 code. Correcting that error led to a
degradation in the model predictions of wintertime NO3".
Therefore, a detailed a study of the underlying laboratory data
was conducted and a new yN205 parameterization was devel-
oped. This parameterization is the first to include the effects of
temperature, humidity, particle composition, and phase state
on yN2os- When incorporated into the next version of CMAQ,
the new yN205 parameterization is expected to mitigate current
overpredictions of wintertime NO3" under conditions prevalent
in the midwestern U.S. In a separate effort during 2007, we
made considerable progress in simulating the dynamic
interaction between gaseous species (e.g., nitric acid) and
coarse particles. These thermodynamically driven interactions
are currently neglected in the CMAQ model, resulting in a
gross underprediction of paniculate nitrate and an over-
estimation of paniculate chloride in coastal urban areas. The
interactions have been successfully simulated in a stand-alone
box model of the CMAQ aerosol module and will be
incorporated into the full modeling system next year. Progress
was also made in modeling the source origin of various trace
elements in fine paniculate matter. This development will
introduce a number of new ways to evaluate model perform-
ance for primary PM in urban areas. Finally, we resumed
efforts to improve the numerical stability of the gas/particle
thermodynamic calculations in CMAQ. This work is being
conducted in collaboration with researchers at the Georgia
Institute of Technology.
Efforts were also devoted toward transitioning to the Weather
Research and Forecasting (WRF) model as the meteorological
driver for CMAQ. The Pleim-Xiu land-surface model (PX
LSM), the Asymmetric Convective Model version 2 (ACM2)
boundary layer model and surface layer scheme, historically
used as physics options in the Fifth-Generation Mesoscale
Model (MM5), have been added to the WRF model. We
provided the codes for these models to the National Center for
Atmospheric Research (NCAR) for inclusion in the next
release of WRF (version 3.0), due to be released in the spring
of 2008. Evaluation of WRF simulations using these new
physics components and comparisons to other LSM and PEL
options in the WRF system have shown generally comparable
or better results for temperature, humidity, and winds. This
work has also led to some other significant improvements,
including a new indirect nudging scheme for soil temperature,
improved treatment of seasonal changes in vegetation, and
improved parameterizations for soil, vegetation, and snow heat
capacity. To facilitate the linkage between the WRF and
CMAQ modeling systems, version 3.3 of the Meteorology-
Chemistry Interface Processor (MCIPV3.3) was prepared and
delivered to the Community Modeling and Analysis System
(CMAS) Center for release to the CMAQ user community;
major changes included updates for WRF fields, improve-
ments to dry deposition, removal of outdated science options,
and addition of metadata to MCIP output files. The Division
also completed a systematic investigation of the impacts of
data assimilation in meteorological models on air quality
predictions from CMAQ. Analyzing MM5 and CMAQ
simulations confirmed that the use of nudging throughout the
simulation period leads to improved prediction of ozone.
MM5 simulations maintain nearly constant statistical
performance on average when nudging is used throughout the
simulation period; however, CMAQ predictions of ozone tend
to degrade as the run time in MM5 increases. A two-part paper
summarizing the findings from this investigation was accepted
for publication in the Journal of Applied Meteorology and
Climatology. Additional investigation into this phenomenon
will continue in 2008 using WRF rather than MM5.
Finally, model development efforts were also devoted toward
developing and testing an on-line integrated meteorology-
atmospheric-chemistry modeling system. Integrating meteor-
ology and chemistry modeling is a new program priority
designed to provide feedback from air quality parameters (e.g.,
aerosols) that affect meteorological parameters (e.g., radia-
tion). A coupled WRF-CMAQ system capable of simulta-
neous integration of meteorology and chemistry with two-way
data exchange has been developed and tested. Development
efforts on the feedback effects of aerosols on solar radiation
are progressing.
In the area of model evaluation, the Division continued to
probe the performance of the CMAQ system using opera-
tional, diagnostic, dynamic, and probabilistic evaluation tech-
niques. A number of publications examined performance
under various synoptic regimes, with alternative chemical
mechanisms, and with varying degrees of vertical resolution.
Using operational and diagnostic evaluation techniques, an
examination of CMAQ's PM25 predictions showed that the
PM "other" component was a major contributor to CMAQ's
overprediction of total PM2 5 in the fall and winter. Work is
continuing to reduce the uncertainty of PM "other," by
looking at possible biases in emissions. Another thorny issue
that was tackled during 2007 was how to improve the
comparison between observed and predicted PM25 species to
account for artifacts in the observations that are not accounted
for in the CMAQ predictions. These components include
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nitrate volatilization and retained water mass, which can
significantly impact the measured PM25 mass. The efforts to
account for these artifacts will ultimately provide more
accurate comparisons between observed and predicted PM25
mass.
We made significant progress with probabilistic evaluation
techniques, with an initial focus on CMAQ ozone predictions.
Because all models are a simplification of the phenomena they
aim to represent, it is often more useful to estimate a model
result as a probabilistic range rather than as a single "best"
result. A key challenge is that ensemble approaches require a
large number of expensive simulations of independent
modeling systems. We implemented a computationally effi-
cient method to generate ensembles with hundreds of
members based on several structural configurations of a single
air quality modeling system and using the Decoupled Direct
Method (DDM) to directly calculate how ozone concentrations
change as a result of changes in input parameters. The
modeled probabilistic range was compared to observations and
was shown to perform better than more ad hoc estimates of the
uncertainty in ozone predictions. Because this technique can
generate large ensembles efficiently, it is well suited for
diagnosing structural errors in the air quality modeling system.
Exploration into new statistical methods for evaluating
comparisons of monitoring data with model predictions also
took place. Advanced statistical methods can aid the evaluator
by making the best use of the limited monitoring data
available, accounting for the differences between point-based
measurements (monitors) and grid cell averages (model
output), and assessing the model output for grid cells in which
no monitors are located. While a variety of approaches could
reasonably be utilized, the focus has been on methods that
allow one to better understand and utilize the spatial
correlation of pollutant fields, such as kriging-based methods.
One example is Hierarchical Bayesian Modeling which is used
to investigate the relationship between ammonium wet
deposition and precipitation, and kriging with adjustments for
anisotropy, used to better understand ozone and PM25
concentrations in the northeastern U.S. In addition, we have
recently assessed the impact on model evaluation of
incommensurabilitythat is, the mismatch between point-
based measurements and areal averages (model output). Ideas
for improving regional air quality model evaluation techniques
were explored at an American Meteorological Society (AMS)-
and Division-sponsored workshop during the summer of 2007.
Lastly, the Atmospheric Model Evaluation Tool (AMET) was
made publically available. AMET is a combination of open-
source software that includes a relational database to store
paired observed-predicted values and a statistical program to
create various plots and calculate statistics. AMET is a valu-
able tool that can aid in the evaluation of both meteorological
and air quality simulations. Because AMET utilizes a
relational database, the user can query data in the database
based on any number of criteria, making it ideal for
identifying any specific problems that may exist in the model
predictions. Work to improve AMET and extend its capabili-
ties will continue in the future.
Next Steps
Over the next several years, science and technology
advancements planned for the CMAQ modeling system
include enhanced emissions modeling and additional model
system evaluation. Some of the planned milestones under this
Theme Area are the following:
FY-2008
Release and evaluate new version of CMAQ
modeling system that will include improved simu-
lations of aerosol processes, especially secondary
organic aerosol (SOA) production;
Develop prototype of two-way integrated
meteorology-chemistry simulation model based on
WRF and CMAQ models;
FY-2009
Add fugitive windblown dust emissions module to
CMAQ modeling system;
Investigate the impacts of aerosol feedbacks on radia-
tion on simulated meteorology and air quality using
the integrated WRF-CMAQ modeling system;
FY-2010
Refine the capability in CMAQ to accurately model
the size, composition, and morphology of ultrafine
particles;
Develop improvements in representation of physical,
chemical, and dynamical processes to accurately
represent air quality at fine scales down to 1 km and
finer resolutions.
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
CMAS Center; the Center also provides user support and
training. The community air quality modeling concept,
especially the CMAQ model, has seen growing acceptance
since the model was first released in 1998. An annual CMAQ
model users conference now attracts over 200 people each
year from North and South America, Europe, and Asia.
EPA/OAQPS and the states use CMAQ for assessments
conducted during national air quality rulemaking and in their
SIPs, respectively. OAQPS has used the model to assess the
potential effectiveness of the CAIR and the CAMR. The
states, through their Regional Planning Organizations (RPOs),
are using CMAQ for visibility assessments in support of the
Regional Haze Rule (RHR) 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,
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Korea, and many other nations in programs to improve
regional air quality management. NOAA's National Weather
Service (NWS), in a collaborative project with EPA, is using
CMAQ to make publicly available short-term (next-day)
forecasts of ozone air quality across the eastern United States
(see Chapter 6).
The end result of all of these efforts will be the ability to better
inform (1) the public on current air quality conditions (from
forecasting applications), to help them make decisions on
health-related exposures to air pollution, and (2) policy makers
(from air quality model assessments) to guide them in making
the best long-term emission control decisions to reduce air
pollution.
The part of the Division organizationally associated with
OAQPS oversees and facilitates the process of transitioning
the tools we develop and evaluate to regulatory applications,
thus providing the foundation for scientifically sound
regulatory decisions.
CMAQ Modeling System
Meteorological Model
(WRForMMS)
Weath;
)t Data
EPA Emissions Inve
;ntory
Met-Chem Interface Processor
(MCIP)
Met. Data Processing
CMAQ AQ Model
Chemistry-Transport Computations
SMOKE
Anthropogenic and Biogenic Emissions Processing
Hourly 3-D Gridded Chemical Concentrations
Figure 2-1. Schematic of CMAQ modeling system, including meteorology, emissions, and air quality models.
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Chapter 3
Evaluating the Impact of Regulatory Policies on Air Quality and Ecosystems
Introduction
As discussed in the introduction to Chapter 2, air quality
management in the United States is implemented for criteria
pollutants through NAAQS. States with nonattainment areas
(areas that do not meet the NAAQS for one or more
pollutants) must submit SIPs that demonstrate how the state
will reduce emissions to achieve attainment. Most criteria
pollutants are transported across state boundaries, which
complicates the nonattainment issue. Recent rulemakings have
recognized that this transport must be considered, requiring
that a regional perspective be used when developing strategies
for air pollution nonattainment.
In 1998, EPA finalized a rule known as the NOX Budget
Trading Program (NBP), 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 (which are a
precursor to ozone formation), thereby decreasing the
formation and transport of ozone across state boundaries.
The Clean Air Rules of 2004 are a suite of actions designed to
improve air quality. Three of the rules specifically address the
transport of pollution across state borders. The CAIR* will
permanently cap emissions of sulfur dioxide (SO2) and NOX
from utilities in the eastern United States. When fully
implemented in 2015, CAIR will reduce SO2 emissions in
these states by over 70% and NOX emissions by over 60%
from 2003 levels. CAMR* will build on 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
reduce emissions) and the way diesel fuel is refined (to
remove sulfur).
Note that CAIR and CAMR are currently in litigation and that the research
programs may be adjusted by the resolution of the legal issues.
Deposition of atmospheric nitrogen, sulfur, and mercury to
land and water surfaces contributes significant loadings to
receiving water bodies, affecting the health of ecosystems. For
example, atmospheric deposition of nitrogen accounts for
about 30% of the nitrogen coming into the Chesapeake Bay.
CAA regulations, including the NBP, CAIR, and CAMR, are
expected to reduce the 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 NBP. 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 air pollutant concen-
trations and atmospheric deposition due to the
implementation of emission reductions
Investigating relationships among 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 conse-
quences of these reductions?
The CMAQ modeling system is used to characterize air
quality before and after the implementation of a target
regulation and to evaluate correlations between changes in
emissions and changes in pollutant concentrations or
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atmospheric deposition. Various scenarios are modeled to
estimate the anthropogenic contribution to total ambient
concentrations and the impact of not implementing the
regulation. Methods have been developed to differentiate
changes attributable to emission reductions from those that
result from other factors, such as weather and annual and
seasonal variations in emissions. Trajectory models, such as
NOAA's Hybrid Single Particle Lagrangian Integrated
Trajectory (HYSPLIT) model, are used to investigate the
transport of primary and secondary pollutants from their
sources to downwind regions.
Research is initially focusing on regulations affecting NOX and
SO2, for which emissions monitoring data are available (e.g.,
NBP and CAIR regulations). Later research will investigate
using other sources of information, such as remote sensing, to
evaluate regulations that impact pollutants such as PM and
mercury, for which emissions data are sparse or uncertain.
Specifically, we are developing indicators to assess changes in
emissions and air quality associated with regulatory actions,
and modeling approaches to characterize the processes that
impact the relationships between these indicators (process
linkages). Figure 3-1 indentifies the full suite of indicators and
process linkages associated with the evaluation of the NBP
rules. Previous efforts performed under this Theme Area
developed the indicators characterizing changes in emissions
and ambient NOX and ozone concentration levels. Models and
data analyses were used to relate the changes in emissions to
the changes in ambient NOX (emitted precursor pollutant) and
ozone (secondary pollutant) concentrations by directly relating
the fate and transport of these pollutants to levels downwind
of their sources.
Accomplishments
The results of research under this Theme Area have indicated
that when major point sources of NOX were reduced by the
NBP, this decreased ozone concentration levels by 5-8 parts
per billion (ppb) at downwind locations. In 2007, evaluations
of the chemical and physical processes further indicated that,
while a dramatic reduction in maximum ozone chemical
production rates occurred downwind of major point sources
affected by the NBP, net ozone production efficiency actually
increased due to the greater decrease in reactive nitrogen
product species (NOZ). This and other results indicate that the
chemical regime has shifted toward more NOx-limited
conditions in the plume-impacted areas downwind of the
sources, meaning that relatively small increases in NOX
emissions (e.g., from the transport corridors in the eastern
U.S.) can result in a relatively large increase in ozone, due to
changes in production rate efficiencies. Overall, our research
has shown that emission control programs implemented under
the NBP have been effective in meeting the objective of
reducing interstate ozone transport, and have helped improve
ozone air quality in source areas of the eastern United States.
These results contributed to the annual assessment of the NBP
in Report EPA-430-R-07-009, NOX Budget Trading Program
2006: Program Compliance and Environmental Results.
Next Steps
Research over the next five years will
(1) continue the assessment of the NBP by applying
ambient concentration and exposure indicators to a
health and risk assessment in the greater New York
State area; and
(2) assess the impact of the phased implementation of
CAIR through the application and further develop-
ment of indicators and process linkage methodologies
developed for assessing the NBP.
The process of developing indicators and process linkages for
assessing the NBP will not only establish an approach for
assessing CAIR, but will also establish a baseline description
of the state of the environment before the implementation of
CAIR. Major deliverables anticipated from this research
include the following:
FY-2008
Develop methods to quantify the impact of the NBP
on ambient ozone concentrations and atmospheric
transport of pollutants, including assessing the
impacts of not implementing the regulation, and to
quantify the anthropogenic contribution;
FY-2009
Develop methods to quantify the probability of ozone
exposure above exceedance levels to populations
before and after the NBP 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 NBP;
FY-2012
Apply prototype ambient concentration tracking
method to evaluate impact of CAIR on ambient
concentrations and deposition rates;
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. Research under this Theme Area
evaluates the effectiveness of specific regulatory actions.
Methods developed for these evaluations will also provide a
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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 results to applications by
demonstrating the use of the CMAQ and HYSPLIT models
and statistical techniques to evaluate the impact of regulations
implemented to improve air quality.
Power Industry N Ox Reductions
Ozone Season (2002 vs. 2004)
Linking ambient
concentrations to exposure
Exposure Estimates
for Ozone
Summer 2001
(99Bl percentile)
I
Linking exposure to human
or ecosystems health
Linking directly
between indicators
Monthly Rates of Respiratory
Admissions in NYS
Figure 3-1. Assessing the impact of regulations on ecosystems and human health endpoints showing
the indicators (boxes) and process linkages (arrows) associated with the NOX Budget Trading Program.
10
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Chapter 4
Linking Sources to Human Exposure
Introduction
The goal of this research theme is to reduce uncertainties in
quantifying the link between sources of atmospheric pollution
and human exposure. The CAA requires EPA to assess which
HAPs pose the greatest risk to humans in the United States,
and to develop strategies for controlling harmful concen-
trations of these compounds. These assessments typically
involve the application of different models, depending on
program objectivesglobal, regional, urban, or local scale
(Figure 4-1). Performing these assessments often requires a
linkage between ambient air quality and human exposure
models. The Division conducts research to build this linkage
by combining the features of grid-based, regional-scale
chemistry-transport models and urban-scale dispersion
models. This research facilitates the use of air quality model
concentrations in human exposure modeling and health risk
assessments, which historically have been limited by their
need to rely 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, the two major types of air quality models
are source-based Gaussian dispersion models and grid-based
chemistry-transport models. Chemistry-transport models, such
as CMAQ, can provide estimates of photochemically formed
pollutants typically at a 36- to 4-km grid scale, 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 preferred for simulation of chemically
reactive airborne pollutants, dispersion models (such as the
AMS/EPA Regulatory Model Improvement Committee
[AERMIC] Model [AERMOD] have been developed to
simulate the near-field fate of airborne pollutants that are
relatively chemically inert.
For multipollutant assessments, a suite of toxic compounds
needs to be included in the CMAQ modeling system, and
model results should be evaluated with ambient observational
data. This research need is closely linked to other research
themes within the Division that involve the development and
evaluation of the modeling system, improvements in chemical
and physical characterization of air toxics, and the measure-
ment of ambient air toxics concentrations.
Because exposure assessments are primarily for urban areas,
air quality simulation models should accurately depict the
physical-chemical processes that occur in these areas.
Concentration fields derived from models run at grid resolu-
tions on the order of 4 km or larger (such as CMAQ) do not
account for the variability of high emission gradients typical in
urban areas. Several approaches are available that may yield a
better characterization of urban "hot spots," including brute-
force simulations with finer-scale grid models, hybrid
modeling that combines chemistry-transport models with
dispersion models, and sub-grid variability distribution
estimates of concentrations. Meteorological models such as
the MM5 and WRF modeling systems now include the
capability to assimilate advanced urban canopy descriptions,
including building, vegetation, and street canyon character-
istics. Databases of high-resolution urban morphological
features are needed to support these advanced models for
future urban evaluation and application.
A growing number of health studies have identified adverse
effectsincluding respiratory disease, cancer, and deathfor
populations exposed to air pollution near major roadways, thus
raising concerns about building schools near roadways and the
general health of people living near roads. Performing near-
roadway risk assessments requires characterizing atmospheric
processes in complex urban settings, especially near major
roadways. Near-road air pollution has been selected as a
central theme in EPA/ORD's multiyear clean air research
plan, because it is a problem that is of pressing importance (as
identified by EPA's stakeholders), and it requires an
integrated, multidisciplinary field and laboratory scientific
approach.
Research Description
The Division's work in this Theme Area is broken into the
following two research tasks:
Multiscale modeling of toxic air pollutants
Near-roadway modeling
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Within the first task, multiscale modeling of air toxics
involves
(1) including chemistry and physics for additional toxic
air pollutants in CMAQ;
(2) applying CMAQ with toxics for problems of interest
to Program and Regional Offices, and the transfer of
information to these stakeholders;
(3) reformatting the results from air quality model
simulations for use in the Stochastic Human
Exposure and Dose Simulation (SHEDS) model; and
(4) developing methods and tools that can be used to
predict air pollutant concentrations at urban (or
neighborhood) scales, and using these tools to assess
the magnitude and variability of concentrations to
which urban populations are exposed.
To incorporate the salient features of both grid-based and
plume-dispersion approaches, we have been testing a hybrid
approach that combines results from CMAQ with the
AERMOD model. The CMAQ grid model provides the
regional background concentrations and urban-scale photo-
chemistry, and the AERMOD local plume dispersion model
provides the air concentrations that are due to local emission
sources. The results of both model simulations are combined
to provide ambient air concentrations for use in exposure
models. The advantage of this modeling approach is that
researchers can incorporate the spatial and temporal variation
of air pollution within a study area without having to rely on
dense ambient monitoring networks. This hybrid approach is
currently being explored in several studies, including an air
quality and exposure study in Detroit, MI, and an
accountability study in New Haven, CT.
As a complement to hybrid modeling, we are exploring other
methods to obtain model concentration fields at spatial scales
needed for improved exposure and risk assessments. This
entails running CMAQ with higher-resolution grid meshes
(smaller grid cells) than is the normal practice. We are also
investigating the use of urbanized versions of the MM5 and
WRF models to drive the CMAQ model at 1-km grid
resolutions. In addition, partnerships with external collabora-
tors are being leveraged to study ways to parameterize
concentration distribution statistics to augment CMAQ outputs
at 12- or 4-km grid resolutions, based on outputs of fine-scale
grid models and/or use of hybrid modeling approaches.
To support improved urban-scale meteorological modeling,
the Division is leading the creation of the National Urban
Database and Access Portal Tool (NUDAPT). As part of this
effort, we are conducting collaborative studies with NCAR on
the urbanized version of the WRF model.
Regarding near-roadway modeling, the second task within this
Theme Area: Before 2007, the Division was engaged in a
number of loosely coordinated research projects involving the
near-road environment, including research to support
homeland security efforts. In 2007, EPA/ORD initiated a
cross-laboratory coordinated near-road research program. The
Division is meeting the physical and numerical dispersion
modeling needs of this program, by assisting in the design and
analysis of field experiments, by conducting laboratory
dispersion studies, and by developing improved numerical
algorithms for modeling near-road dispersion of emissions
from major roadways. Our focus is to examine the signifi-
cance of near-road emissions from varied roadway conditions
on human exposure and related health risks, and to develop
tools for addressing this issue.
Accomplishments
The CMAQ modeling system has been modified to include
HAPs, and results from the revised model 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
SHEDS model and the Hazardous Air Pollutant Exposure
Model (HAPEM). This research has been performed in
collaboration with scientists from EPA/ORD/NERL's Human
Exposure and Atmospheric Sciences Division (HEASD) and
EPA/OAQPS.
During the past two years, we have developed the hybrid
approach to estimate concentrations for multiple pollutants
that reflects both local features (hot spots) and regional
transport. The local impacts from mobile sources and signi-
ficant stationary sources are estimated using AERMOD, and
the combined concentrations are used for subsequent human
exposure analysis. During 2007, we demonstrated an
application of this linkage for New Haven, CT. This project is
a collaborative effort with state and local agencies, including
government, academia, and the New Haven community, to
apply and evaluate air quality and human exposure models
that can be used with health data. The project goal is to assess
the feasibility of using this information to conduct an air
accountability study (i.e., to trace the impact of air quality
changes through to human health impacts).
Efforts have continued on methods to derive sub-grid
variability (SGV) distributions from a combination of ~l-km-
grid-resolution CMAQ model simulations and hybrid model
results. With this approach, each 4- or 12-km CMAQ grid cell
is assigned SGV characteristics, such as the type of distri-
bution or the range of concentrations corresponding to user-
prescribed percentile values. Initial efforts have focused on
SGV distribution functions derived from the Wilmington, DE,
and Houston, TX, modeling results. The use of Weibull
distributions seems promising. The SGV approach may prove
useful for applications that can incorporate estimates of SGV
on an a priori basis, such as with population exposure studies.
For urban-scale meteorological modeling, a prototype version
of NUDAPT was completed for the Houston area. NUDAPT's
portal features allow users to adapt processed fields of urban
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canopy parameters and other gridded fields for use with
different grid resolutions and map projections. NUDAPT also
includes sets of advanced urban canopy parameter
implementations for the MM5 and WRF modeling systems. A
workshop of the federal, state, academic, and private
collaborators was conducted in Boulder, CO, during spring
2007 as a means to perform the initial implementation of
NUDAPT. Sensitivity studies using urbanized MM5 and WRF
to drive CMAQ for urban applications were begun. For
Houston, sensitivity runs of MM5 at 1-km resolution are being
performed using both the standard MM5 model and an
urbanized MM5 based on an urban canopy approach.
Similarly, collaborations are underway with NCAR regarding
their urbanized WRF model. Preliminary CMAQ-Toxics
(CMAQ-TX) simulations have been made at 1-km grid
resolution for the Houston and Wilmington domains; the
Delaware modeling is being performed in collaboration with
the State of Delaware. A preliminary survey of the distribution
functions has been conducted from the Wilmington and
Houston CMAQ results. A special session at the 2007 annual
CMAS conference showcased the NUDAPT efforts, including
a demonstration of the NUDAPT initial prototype.
During 2007, the Near-Roadway and School Infiltration
Research Initiative project continued. Fourteen roadway
configurations were identified, and a physical model was
created for each configuration for performing modeling in the
Division's Meteorological Wind Tunnel. The configurations
included a flat roadway with no surrounding obstacles (base
case), noise barriers of varied heights and distances from
roadway, two different porous barriers intended to simulate
rows of vegetation, and depressed and elevated roadways. The
experiments generated three-dimensional data sets comprising
winds, turbulence, and tracer-gas concentrations. Preliminary
results show that the solid noise barriers have a substantial
effect on downwind concentrations. When winds blow across
the roadway, the barriers increase vertical turbulence. This
causes the plume from the roadway to mix more vigorously in
the vertical direction, which results in decreased ground-level
concentrations immediately downwind of the road. For a
single upwind barrier, the downwind concentration (near the
edge of the roadway) decreases by a factor of four compared
to the base case. By adding a second solid barrier on the
downwind edge of the roadway, the downwind concentration
decreases by a factor of six compared to the base case. With
an upwind "vegetation" barrier of 58% porosity, only minor
differences are seen in the downwind concentrations compared
to the base case. Although the simulated upwind vegetation
causes a modest increase in the vertical extent of the plume,
downwind concentrations decrease less than 7% over the base
case. A vegetation barrier with less porosity (23%, repre-
senting more dense vegetation) shows a decrease in near-road
downwind concentrations of about a factor of two. Denser or
taller vegetation would be expected to produce greater
differences in the concentration field. Finally, depressed
roadways are found to affect the downwind concentration
fields in a way similar to the case with noise barriers on both
sides of the road.
A number of journal articles are being prepared using the
results from the wind tunnel, and the data obtained are being
used to verify numerical algorithms and to improve the line-
source algorithm used in near-roadway dispersion models.
Several members of the Division participated in the Raleigh
2006 Pilot Field Study, which was an EPA/ORD multi-
laboratory collaborative effort involving EPA/NERL and
EPA's National Health and Environmental Effects Research
Laboratory (NHEERL) and National Risk Management
Research Laboratory (NRMRL). The Raleigh field study,
conducted in the summer of 2006, was designed to provide
data to characterize the influence of traffic-generated
emissions in the near-road environment, especially to help
assess their impact on air quality and particle toxicity near a
heavily traveled highway. The study included several real-
time and time-integrated sampling devices that measured air
quality concentrations at multiple distances and heights from
the road. Pollutants analyzed included EPA-regulated gases,
paniculate matter (coarse, fine, and ultrafine), and air toxics.
Pollutant measurements were synchronized with real-time
traffic and meteorological monitoring devices to provide
continuous and integrated assessments of the variation of near-
road pollutant concentrations and particle toxicity with
changing traffic and environmental conditions, as well as
distance from the road. This research task helped provide the
analysis used to demonstrate the temporal and spatial impact
of traffic emissions on near-road air quality.
Using funding from the EPA/ORD near-roadway research
initiative, a support contract provided a comprehensive review
of available/operational air quality and emission models. A
final draft report was completed, and work is underway to
transform this report into a review article, possibly for the
Journal of the Air Waste and Management Association. This
review will provide the air quality modeling community with a
convenient summary of the current state-of-science and will
serve as a guide for the research needed to develop improved
near-roadway air quality and emission models.
Next Steps
During the next few years, the Division is expected to increase
emphasis in the areas of near-roadway modeling and linkage
of air quality models with human exposure models to assess
human health. A major effort during 2008 will be to create and
implement a version of the SAPRC07-TX chemical
mechanism within the CMAQ system. This mechanism will
go directly to a "multipollutant" form. We also plan to add
cloud chemistry for chromium compounds and address adding
arsenic compounds into the CMAQ-TX model. If time
permits, we will start studying the inclusion of polycyclic
aromatic hydrocarbons (PAHs) into CMAQ-TX. We hope to
simulate the seven to sixteen PAHs that are suspected of
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causing damage to human health, based on laboratory studies.
Besides requiring revision of model algorithms, PAHs present
an additional difficulty because parts of the emissions inven-
tory for HAPs lump several PAHs into one emissions rate.
Also during 2008, simulations with CMAQ-TX for Baltimore
will be performed, as well as simulations to examine the effect
of alternative mobile-source fuel composition on
concentrations of toxic aldehydes. In 2009, we will analyze
output from the Baltimore simulations and provide the
ambient concentration predictions for input to Environmental
Benefits Mapping and Analysis Program (BenMAP) benefits
model analyses being performed by EPA/OAQPS.
To support urban modeling, a "fine-scale" Division work-
group has been established to develop a more detailed research
plan for investigating the efficacy of adapting WRF/CMAQ to
a grid mesh of less than 4 km for various test beds. This plan
will be used to guide and perhaps redirect research within the
Division during 2008 through 2011.
Via an existing collaboration with the State of Delaware, we
will continue examining and refining the characteristics of the
SGV distributions using both fine-scale and hybrid modeling
approaches. Methods to utilize these distributions will be
investigated for developing parameterization of SGV varia-
tions for coarse (4- and 12-km) grid resolutions. We may also
investigate parameterizations of SGV distributions with either
off-the-shelf or alternative software specifically developed for
deriving parametric forms of the distribution function.
Further, we plan to explore developing an easy-to-use method
to create modeling input files for on-road mobile sources at a
link-based level, and to assess the impact of more spatially
resolved emissions on modeled ambient air pollutant con-
centrations. We will continue conducting uncertainty analyses
to evaluate model results and explore an "ensemble-based"
approach for generating probabilistic concentration fields.
Follow-on collaboration with NCAR will investigate use of
the urbanized version of WRF for driving CMAQ for urban
applications. We will also perform sensitivity studies using
advanced urbanized versions of MM5 and WRF with CMAQ
to examine the impact of using the NUDAPT data in urban
areas.
Follow-on wind tunnel dispersion studies will be conducted
over several years to expand the near-roadway scenarios to
include the influences of wind direction variations, nearby
buildings, and upwind and downwind vegetation. The
Division and NOAA's Air Resources Laboratory (ARL) Field
Research Division (FRD) are planning to perform a tracer-gas
dispersion experiment to enhance a field study that will be
conducted in Las Vegas during 2008-2009. The overall
purpose of the EPA field study is to characterize the spatial
gradient of pollution within -200 m of a major highway. The
research plan envisions the release of SF6 from a 100-m
perforated pipe under various flow regimes. Plans have been
proposed to deploy sonic anemometers near 1-15 in Las Vegas
to characterize the decay of vehicular-induced turbulence as a
function of distance from the roadway. Further discussions
between the Division and FRD will occur during 2008. Design
of the field study will be supported by a wind tunnel study of
the flow and dispersion in a 1:200 scale model of the selected
Las Vegas field site, which will be performed during summer
2008. Data collected in the field and the laboratory, as well as
detailed numerical modeling studies from models such as the
Quick Urban and Industrial Complex (QUIC) model, will be
analyzed and a refined line-source algorithm will be proposed
for inclusion in the AERMOD model.
In future years (2009-2011), the Division plans to return to
wind tunnel studies of urban street canyon flows within a scale
model of a large urban center (Midtown Manhattan). We will
examine the general structure of complex urban boundary
layers. The Midtown Manhattan model provides a "target of
opportunity" because a physical model already exists from an
earlier homeland security project. These data, in combination
with those from similar wind tunnel studies of urban centers
(Lower Manhattan, Oklahoma City, etc.) and from computa-
tional fluid dynamics modeling (existing, from studies
performed outside of the Division) of the same Midtown area,
can be used to characterize the influence of the urban
landscape on grid-average concentrations within regional-
scale modeling analyses, and could provide the basis for
improved urban dispersion algorithms within near-field and
hybrid modeling approaches.
Research under this Theme Area is expected to contribute to
the following research milestones:
FY-2008
Linkage of CMAQ-TX output with BenMAP for the
Baltimore area;
Enhanced air quality and exposure modeling tools to
address finer-scale air toxics concentrations and
exposures (EPA Annual Performance Measure #397);
Report on the NUDAPT Prototype;
Characterization of ambient air quality near roadways
with data collected at the Division's Meteorological
Wind Tunnel and development of recommendations
for improved line-source algorithms for urban-scale
air quality modeling;
CMAQ model system release and evaluation,
including concurrent multipollutant modeling
capability (O3, PM, air toxics, mercury);
FY-2009
Report on model results for Baltimore and on effects
of control strategies intended to reduce harmful
concentrations of multiple pollutants ;
Hybrid modeling results for exposure assessment
studies of interest to health scientists/epidemiologists;
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Report on the sensitivity of alternative fine-scale
meteorological/air quality modeling approaches in
urban areas;
FY-2010
Development and evaluation of an improved line-
source algorithm for characterizing near-roadway
impacts in air quality models;
FY-2011
Improved CMAQ modeling system for use in urban-
scale residual nonattainment areas (joint effort with
the model development and evaluation research
theme discussed in Chapter 2);
FY-2012
Identification and evaluation of assessment tools to
aid urban planners in considering near-road health
effects.
Impacts and Transition of Research to
Applications
Development and application of linked models of ambient air
quality and human exposure will help epidemiologists reduce
uncertainty as they assess the risk of air pollutants to human
health, and will help policy-makers reduce uncertainty as they
develop control strategies that target air pollutants identified
as posing the greatest risk to humans. These uncertainty
reductions should result in more accurate risk assessment
results and in policies that are more likely to protect human
health.
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 us with many life-sustaining benefits
resources and services that contribute to our physical, social,
and economic welfare; examples of ecosystem services
include clean air and water, fertile soil for crop production,
pollination, and flood control. A long-term goal of environ-
mental management is to achieve sustainable ecological
resources through a comprehensive assessment of current and
projected ecosystem health and services. Such an assessment
must include identification of the major threats (the specific
stressors) to ecosystem health, the sources of those stressors,
and how they move through the environment. This is
fundamentally a problem of multimedia pollution.
The overall objective of this Theme Area 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 terrestrial and
aquatic ecosystems. This research supports EPA's expanded
definition of air quality management that includes ecosystem
protection in assessments of air pollution regulations, i.e., in
the setting of secondary NAAQS. It also supports the new
emphasis of EPA's Ecosystem Research Program (ERP) on
linking sources to exposure in a multipollutant context and
developing capabilities for ecosystem services assessments.
The interaction between the atmosphere and the underlying
surface is increasingly being recognized as a significant 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. Managing the nitrogen cycle is a
central issue of the ESRP. Critical-load is the amount of
deposition above which natural resources can be negatively
affected and is intended as a protective threshold. The Nation-
al Academy of Sciences (NAS) has recommended that EPA
consider a deposition-based approach such as critical loads to
ecosystem management.2 In support of the ESRP thrust and
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.
the NAS 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. The
atmosphere is an important contributor to stressors such as
excess nutrients, but atmospheric deposition is seldom
considered in the development of TMDLs. The Division is
conducting research to improve the understanding of the
atmospheric contribution of stressors to TMDLs.
Research Description
For this research theme, the Division has identified research
areas that have the most potential to reduce critical uncertain-
ties in atmospheric deposition, to assess program accounta-
bility, and to link atmospheric deposition to ecosystem
resources and services.
Specific research tasks are grouped under 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 enhances air-
surface exchange modules for CMAQ, and advances the link-
age between CMAQ and the underlying land-use categories to
facilitate improved interactions with ecosystem models. We
also develop and enhance air-surface exchange modules for
monitoring network operations using an inferential method for
dry deposition, focusing primarily on sulfur, nitrogen, and
mercury species. The bidirectional air-surface exchange pro-
cess is a new feature of this program element.
Focus areas of the Air-Surface Research and Development
program element include the following:
Unidirectional deposition of gases and particles
Bidirectional flux (air-surface exchange) of ammonia
Bidirectional flux of mercury
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Land-surface interface within the CMAQ system to
support bidirectional fluxes
Land-use-specific flux determination by CMAQ for
linkage with ecosystem models
Dry deposition and bidirectional flux module adap-
tations for network operations
Through the second program element, Multimedia Applica-
tions, the Division develops and improves linkages between
air and water models, and develops and maintains connections
to ecosystem resources and services through participation with
partners in multimedia assessments. Simulation of deposition
estimates at a National scale is an important output from these
efforts.
Focus areas of Multimedia Applications include the following:
Chesapeake Bay 2007/2008 re-evaluation and 2010
TMDL assessment
Tampa Bay nitrogen deposition assessment (TMDL)
Coastal air-water model linkage development to
address water quality issues
Studies to address management of the nitrogen cycle
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 encoun-
tered in analyzing data from a multimedia perspective.
Significant effort is often required to analyze observations and
model results and provide them in forms that are required for
supporting management decisions.
Focus areas of Multimedia Tool Development include the
following:
Conversion of land-use information to National Land
Cover Data (NLCD) and allocation of spatial data to
a CMAQ-usable gridded form
Development of watershed deposition tool to overlay
gridded CMAQ output onto selected watershed
segment polygons
Updating CMAQ visualization tools to be based on
the Java programming language
Accomplishments
An evaluation of the Multi-Layer Model (MLM) used in
EPA's Clean Air Status and Trends Network (CASTNET) for
estimating dry deposition pointed to areas for model improve-
ment. In response, we developed the Multilayer Biochemical
Model (MLBC) as a replacement for the MLM. New versions
of MLM and MLBC were developed for network operations:
MLMNet and MLBCNet. A new interface capable of running
both models was also developed. We delivered first versions
of the two new model versions and the interface to the
EPA/Office of Air and Radiation (OAR) Clean Air Markets
Division (CAMD) in 2007.
The Division also partnered with EPA's Chesapeake Bay
Program Office (CBPO) to define a series of CMAQ estimates
of future atmospheric nitrogen deposition out to 2030,
simulating growth and implementation of new air quality
regulations. The new regulations include CAIR*, CAMR*, and
CAVR. A significant decrease in nitrogen deposition from
NOX emission reductions is expected, but the growth in
ammonia emissions erodes these benefits. We also partnered
with the CBPO to define a series of desired CMAQ enhance-
ments for air-water model studies.
We used a brute-force sensitivity approach with CMAQ to
estimate the relative contribution of NOX emissions from each
of the six Bay states (Delaware, Maryland, New York,
Pennsylvania, Virginia, and West Virginia, plus the District of
Columbia) to oxidized nitrogen deposition in the Chesapeake
Bay watershed. The brute-force sensitivity approach produced
an unacceptable degree of nonlinearity in the combined esti-
mate of the relative contribution from the Bay states. We then
modified the Decoupled Direct Method in Three Dimensions
(DDM3-D) sensitivity approach in CMAQ, which math-
ematically accounts for the nonlinearities, to include the track-
ing of nitrogen deposition from NOX emissions. Contributions
from mobile sources, power plants, and industry in the Bay
states to nitrogen deposition to the Bay watershed will be re-
simulated with the new DDM3-D implementation in CMAQ
in 2008.
To support development of the nitrogen TMDL for the Tampa
Bay watershed, the Division partnered with the Tampa Bay
Estuary Program (TBEP) to define annual nitrogen deposition
simulations for Tampa Bay watershed segments in order to
improve the understanding of nitrogen deposition to the
watershed. In addition to providing deposition estimates for
current (2002) emission conditions with CMAQ-UCD (a
version of CMAQ that uses a sectional approach to represent
the aerosol size distribution), we performed sensitivity simula-
tions to answer questions about (1) the relative contribution of
within-watershed NOX emissions to watershed nitrogen
deposition, (2) the deposition reduction benefit expected to
result from court-ordered NOX reductions in emissions from
two power plants located alongside Tampa Bay, and (3) the
nitrogen deposition reduction benefit expected to result from
the 23-state CAIR air emission reductions in 2010.
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.
Note that CAIR and CAMR are currently in litigation and that the research
programs may be adjusted by the resolution of the legal issues.
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In 2007 we implemented a second set of improvements to the
WDT and released it to the public via the ASMD web site.
Examples of outputs from the WDT are shown in Figures 5-1
and 5-2. Also in 2007, an initial version of the Visualization
Environment for Rich Data Interpretation (VERDI) was
delivered to the Division. VERDI is an open-source Java tool
for visualizing CMAQ and other environmental data. The
tool's open-source and Java-based aspects will allow many
users to contribute to its development and enhancement.
VERDI is designed to replace the Package for Analysis and
Visualization of Environmental data (PAVE), which is the
current package used for visualizing CMAQ data.
Next Steps
Over the next several years, advancements are planned for the
multimedia Theme Area to investigate more sophisticated
futures scenarios for air-water linkages, and to adapt CMAQ
to calculate bidirectional exchange of ammonia and mercury
and to more closely couple to ecosystems models. Some of the
planned milestones are as follows:
FY-2008
Complete key Chesapeake Bay CMAQ modeling
scenarios with 12-km grid cell size and sea salt
influence for the Chesapeake Bay Program (CBP)
TMDL analysis and ESRP baseline;
Incorporate bidirectional NH3 and mercury flux
algorithms into research version of CMAQ;
Incorporate new mosaic land-use interface in CMAQ
for better communication with ecosystem models;
Complete preliminary air-water model linkage for
Cape Fear River basin in North Carolina;
FY-2009
Convert mosaic land-use interface to NLCD for
consistency with ecosystem models, and test CMAQ
for land-use-change scenario analysis;
Simulate Chesapeake Bay futures scenarios with
CMAQ at 12-km grid cell size, and incorporate NH3
bidirectional exchange influence for Chesapeake
sensitivity;
Complete preliminary air-water model linkage for
North Carolina Albemarle-Pamlico estuarine system;
FY-2010
For ESRP place-based scenario analyses (Carolinas,
Midwest, Tampa), simulate nitrogen, sulfur, and
ozone deposition futures incorporating land-use
changes;
Incorporate into a science version of CMAQ a
generalized land-surface layer to support multi-
pollutant bidirectional flux calculations.
Impacts and Transition of Research to
Applications
CASTNET monitors concentrations and dry depositions 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 CAA. CASTNET is considered the primary source
for estimates of dry acidic deposition and is vital to EPA's
efforts to protect terrestrial and aquatic ecosystems. The
Division's development of MLBC, an improved model for dry
deposition estimates, is key to 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 bidirectional 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 the Office of Water and OAR, and the 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 infor-
mation on nitrogen loading that is used by the CBP to manage
the Bay. This supports the CBP's commitment to reducing
nitrogen loads in the 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
establishing the Tampa Bay TMDL. The model-estimated
effect of court-ordered NOX emissions reductions from two
power 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
allow assessment of whether these rules are keeping up with,
or being outpaced by, 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 more efficiently and enable them to develop insights that
they might otherwise miss. The software tools developed by
the Division are for community use, and will also allow EPA
and the states to conduct their work more effectively and pro-
vide for a more complete multimedia approach. These tools
18
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will allow new users 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.
Figure 5-1. WDT screen capture showing the CMAQ 2002 annual total nitrogen deposition (kg-N/ha)
for the 36-km grid resolution with the overlay of 8-digit Hydrologic Unit Code (HUC) delineations
for the Cape Fear Basin and Albemarle-Pamlico Sound system.
"Watershed Deposition Tool: BaseCase.dat
Figure 5-2. WDT screen capture showing the average 2002 annual total nitrogen deposition (kg-N/ha)
to each watershed segment in the Cape Fear Basin and Albemarle-Pamlico Sound system.
19
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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 expo-
sure to ambient O3 and PM25. Local air quality agencies
therefore need accurate forecasts of atmospheric pollutant
concentrations so they can alert sensitive populations about
the onset, severity, and duration of unhealthy air, and to
encourage the public and industry to reduce emissions-
producing activities. Forecasting local and regional air pollu-
tion events is challenging because the processes governing the
production and accumulation of ozone and fine PM are
complex and nonlinear. Comprehensive atmospheric models
provide a scientifically sound tool for preparing air quality
forecast guidance. The Division uses modeling to forecast the
day-to-day variability in air pollutant concentrations. The
principal modeling platform for this purpose is the CMAQ
modeling system linked with the North American Mesoscale
(NAM) model, a NOAA/NWS operational weather prediction
model.
Research Description
In 2003, EPA and NOAA signed a Memorandum of Agree-
ment to collaborate on the design and implementation of a
system to produce daily air quality modeling forecast infor-
mation. The Division has linked together NOAA's operational
NAM and EPA's CMAQ model to form the core of this fore-
cast system. The preliminary system provided ground-level
ozone predictions over the northeastern United States.
Through an ongoing collaborative program of phased
development and testing with the NWS, we are expanding the
system's capabilities. In August 2005, the operational domain
was extended over the entire eastern United States. In 2007,
based on extensive testing of model upgrades, the operational
domain of the NAM-CMAQ modeling system was expanded
to cover the entire continental United States (Figure 6-1), and
the Division continued developmental testing for PM25
forecasts over the continental United States. Over the next few
years, our research will investigate extending the forecast
guidance period, expanding coverage to include Alaska and
Hawaii, refining the spatial resolution of forecast guidance,
improving the representation of the physical and chemical
processes dictating moderate-to-high ambient O3 levels, and
adding PM2 5 to the model forecast capability.
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
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., re-analysis 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 2007, several major changes were implemented in the
air quality forecast modeling system:
Based on extensive testing of model upgrades
addressing the representation of PEL processes, dry
deposition, cloud mixing, and emission source
specification, the operational domain of the NAM-
CMAQ modeling system was expanded to cover the
entire continental United States. Hour-by-hour ozone
forecasts, through midnight of the following day, are
available online, providing information about the
onset, severity, and duration of poor air quality from
coast to coast.
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To reduce errors associated with interpolation of
meteorological data from the WRF-Nonhydrostatic
Mesoscale Model (NMM) coordinate and grid struc-
ture to that of CMAQ, we improved the coupling and
consistent use of data between the two models. The
first step in this effortimproving the coupling in the
vertical direction such that the CMAQ calculations
are performed with the same hybrid sigma-P vertical
coordinate system that is utilized in the WRF-
NMMwas successfully implemented in 2006, and
further tested in 2007. The updated system provides a
more accurate representation of the three-dimensional
meteorological fields. Efforts are also underway to
include consistent coupling between the horizontal
coordinate and grid system of the two models.
The emission inventories used by the air quality
modeling forecast system were updated to represent
the 2007 conditions. We used Continuous Emission
Monitoring (CEM) data from 2005 to generate a base
year of emission estimates for NOX and SO2 from
electricity generating units (EGUs). For other
pollutants and non-EGUs, base year 2001 emissions
were utilized. Annual Energy Outlook data from the
Department of Energy were used to project energy-
related point-source emissions from the base year to
2007. Vehicle miles traveled projected out to 2007,
along with updated 2007 fleet information, were used
to estimate mobile-source emissions. The emissions
inventory was also augmented with updated emission
information from some states.
We added diagnostic tracers to CMAQ to track and
quantify the influence of lateral boundary conditions
specified for O3. Analysis of simulated tracer distri-
butions indicated that the simulated surface-level
background O3 is highly dependent on lateral
boundary conditions specified in the free troposphere.
We investigated the use of potential vorticity esti-
mates (based on NAM meteorological predictions) as
a surrogate for O3 associated with stratospheric
intrusion events. The impacts were evaluated against
extensive ozonesonde measurements from the 2006
Intercontinental Chemical Transport Experiment
(INTEX) Ozonesonde Network Study.
Extensive evaluation of archived forecast results for a variety
of trace species was also conducted through comparisons with
measurements from surface sites as well as aircraft deployed
during the 2004 International Consortium for Atmospheric
Research on Transport and Transformation field study and the
2006 Texas Air Quality Study.
Through detailed comparisons with measurements from a
variety of surface networks, we performed continuous evalua-
tion of PM forecast results from the developmental
simulations. Performance characteristics for PM25 forecasts
over an entire year were investigated with an emphasis on
understanding seasonal biases. To characterize model perfor-
mance during the wintertime, we completed a detailed
comparison of PM2 5 and constituent concentration forecasts
with measurements from various surface networks.
The Division developed and tested methods to characterize
real-time emissions from wildfires using satellite information
from the Hazard Mapping System to detect the locations of
fires. We also developed a method to estimate the emissions of
gaseous and paniculate matter constituents from these fires for
input to CMAQ. Initial testing indicates that the new wildfire
estimates improved model forecast performance for both O3
and PM2 5 in regions impacted by pollution plumes from the
fires.
An extensive investigation of postprocessing bias-adjustment
techniques that incorporate recent model forecasts with
observations to adjust real-time O3 forecasts was conducted.
We found the methods to be effective in reducing systematic
errors in model O3 forecasts. Extensions to the Kalman filter
bias-adjustment method were investigated to reduce the
unsystematic (random) component of the model forecast error.
Next Steps
FY-2008
Incorporate the updated CB05 chemical mechanism
and updated emission estimates into the NAM-
CMAQ air quality forecasting system;
Continue populating the air quality data archive at
EPA with WRF-NMM-CMAQ daily air quality
forecasts and meteorological data for 2008;
Conduct initial testing of WRF-NMM-CMAQ link-
age on the native WRF model E-Grid structure;
Develop and evaluate postprocessing bias-adjustment
techniques to achieve improved model forecasts;
FY-2009
Develop improvements in representation of PM
processes in air quality forecast models;
Analyze and evaluate developmental PM forecast
simulations over the continental United States;
FY-2010
Conduct experimental testing of daily PM forecast
simulations (with NOAA/NWS);
Create 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/NWS
to develop and deploy a model-based national air quality
forecast guidance system, which currently operates at the
NWS. Hourly ozone forecasts through midnight of the
21
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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, based on EPA's health-
based Air Quality Index.
Analysis of model forecasts of air quality 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 and
comparisons of model forecast results with extensive meas-
urements from these field campaigns have also provided
diagnostic information on model performance, helping
improve the science in CMAQ.
EPA's archive of the forecast products provides a rich
repository of daily air quality information that can potentially
be used to understand long-term trends in air quality, the
effectiveness of emission control programs in reducing
population exposure, and relationships between air pollution
and human health.
Figure 6-1. Forecast surface-level 8-hour-maximum O3 mixing ratios on August 15, 2007.
Color-coded diamonds indicate corresponding observed levels.
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Chapter 7
Understanding the Relationships between Climate Change and Air Quality
Introduction
It is well known that meteorology strongly influences ozone
and aerosol variability, both spatially and temporally.
Meteorology over many decades includes variations on synop-
tic, seasonal, and interannual time scales. In addition to the
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 the potential impacts of climate change on air
quality and how these impacts may influence projected
improvements in air quality from regulatory control programs.
Conversely, we must also understand the influences of air
quality on climate. 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. Using
modeling tools that can simulate these interactions between
climate and air quality, Division personnel work toward this
Theme Area's key goals of improving our understanding of
the impacts of future climate change on air quality, and
identifying potential influences on climate from major changes
in aerosol loadings.
Research Description
The focus of the ongoing 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 this project have been generated using a
coupled global-to-regional downscaled modeling approach.
Modeling results suggest that a midrange climate scenario 50
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 uncertainties in both magnitude and
direction. In the current phase, the CIRAQ project is investi-
gating future emission scenarios developed in collaboration
with EPA/NRMRL and modeling the resulting impacts on air
quality. The results from the first series of simulations contri-
buted to the 2007 U.S. EPA national air quality assessment
report; the emission scenario tests will contribute to the 2012
EPA national air quality assessment report. CIRAQ results
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 advanced global-scale models that were applied for the
recent Intergovernmental Panel on Climate Change (IPCC)
Fourth Assessment Report, such as the NOAA Geophysical
Fluid Dynamics Laboratory (GFDL) global-scale model.
GFDL's global models include scientific updates for climate
and chemistry, 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 WRF mesoscale weather model will be used to produce
meteorological data fields for CMAQ air quality simulations.
The integrated WRF-CMAQ model will provide direct
feedbacks from aerosols in CMAQ to radiation predictions in
WRF. The Division will use this modeling tool to conduct
sensitivity simulations to evaluate the potential impact of
future air quality programs on regional climate. For example,
we will investigate whether large-scale reductions in sulfate
concentrations might contribute to warming in the United
States.
Accomplishments
During the past several 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)
downscaled regional climate simulations. Dr. Ruby Lueng
(PNNL) led the effort to generate the downscaled climate
scenarios. The Division has archived and evaluated these
regional climate model outputs and used these regional
climate scenarios to develop a model sensitivity study of the
impact of future climate on air quality. We have prepared a
series of scientific papers that discuss evaluation of these
simulations for current time periods and characterization of
the differences between the current-year and future-year
predictions.
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With 5 years of current and 5 years of 2050 air quality simula-
tions completed using these downscaled regional climate
simulations, a series of model sensitivity tests and analyses
were conducted in 2007 to assess climate-related air quality
sensitivities. Results from this work have contributed in 2007
to several products, including the EPA National Center for
Environmental Assessment (NCEA) interim report on climate
and air quality, CCSP's Synthesis and Assessment Products
(SAPs) 3.2 and 4.6, and a series of journal articles. The
following results from Nolte et al. (2008) (Figure 7-1) suggest
that increasing temperatures, isoprene emissions, and surface
radiation would increase high O3 events, which are charac-
terized here as the O3 levels in the 95th percentile of the
distribution of O3 mixing ratios (Figure 7-2).
Change in 5-year Temperature (JJA)
4
3
2
1
0.5
0.5
-1
-2
-3
-4
K
10
5
3
1
0.5
-0.5
-1
-3
-5
-10
tond"1
35
30
20
10
5
-5
-10
-20
-30
-35
Win"2
Change in 5-year Daily Isoprene (JJA)
Change in 5-year Surface Radiation (JJA)
Figure 7-1. Average summer (June-August, or JJA) difference
between future - current regional climate scenarios for
temperature, isoprene emissions, and solar radiation reaching
the surface.
-2
-5
-8
PPb
Change in 95th Percentile Ozone (JJA)
Change in 95th Percentile Ozone (Sep-Oct
Figure 7-2. Increase (future - current) in O3 concentrations
under future climate conditions when comparing the 95th% of
the Os distribution (i.e., high Os episodes). The summer (JJA)
and fall (September and October) months are compared.
Unique new findings from this study included the suggestion
of an extension of the O3 season into the fall months (Figure
7-2, lower plot). Another interesting study outcome came from
the sensitivity tests altering the methane concentrations
assumed in CMAQ from current levels to the levels projected
under the IPCC A1B storyline. Results suggest an increase in
O3 of approximately 0.5-1 ppb across the U.S., which suggests
a broad increase in the "background" O3 levels (Figure 7-3).
While global chemistry models had suggested similar impacts
of methane on background O3, this was the first regional-scale
modeling study to demonstrate that.
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Change in 2048 MDA8 Ozone, CH4sens - basec
FY-2009
8
5
2
1
0.5
-0.5
-1
-2
-5
-8
ppb
Figure 7-3. Average summer increase (future - current) in Os
when methane concentrations increase from 1.8 ppm to 2.4
ppm.
Next Steps
FY-2008
Develop air quality emission scenarios for the 2050
time period (in collaboration with EPA/NRMRL);
Prepare a report on the impact of climate change on
U.S. PM concentrations. Conduct model sensitivity
tests and report on the PM concentration changes in
the U.S. under a future climate scenario with and
without future emission scenarios (in collaboration
with EPA/NCEA and EPAMRMRL);
FY-2010
Test model linkage approaches for downscaling
global to regional climate in order to contribute to the
EPA 2012 national air quality assessment report and
to address future modeling tool needs in air quality
management.
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 iden-
tify the uncertainty introduced when future climate influences
are not included in analyses for future years. Modeling tools,
including WPJ-CMAQ and global model linkages developed
in this research, will be made available for use in addressing
air quality management issues that must 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
Atmospheric Modeling Division Staff Roster
As of 12/31/2007
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
Ken Schere, Science Advisor
Gary Walter, Information Technology Manager
Jeff West, Quality Assurance Manager
Air-Surface Processes Modeling Branch
Tom Pierce, Chief
Jane Coleman (SEEP1), Secretary
Jesse Bash
Bill Benjey
Jason Ching
Ellen Cooler
Robin Dennis
Vlad Isakov
Jehn-Yih Junag (ORISE2)
George Pouliot
Donna Schwede
George Bowker, Fluid Modeling Facility
David Heist, Fluid Modeling Facility
Steve Perry, Fluid Modeling Facility
Bill Peterson (contractor), Fluid Modeling Facility
Ashok Patel (SEEP), Fluid Modeling Facility
John Rose (SEEP), Fluid Modeling Facility
Applied Modeling Branch
Mark Evangelista, Chief
Dennis Atkinson
Desmond Bailey
Pat Dolwick
Rich Mason
Brian Orndorff
Joe Touma
'SEEP: Senior Environmental Employee Program
2OPJSE: Oak Ridge Institute for Science and Education
Atmospheric Model Development Branch
Rohit Mathur, Chief
Shirley Long (SEEP), Secretary
Prakash Bhave
Russ Bullock
Ann Marie Carlton
Tianfeng Chai (contractor)
Brian Eder
Rob Gilliam
Jerry Herwehe
Bill Hutzell (EPA)
Jim Kelly (EPA), Postdoc
Daiwen Kang (contractor)
Hsin-mu Lin (contractor)
Deborah Luecken (EPA)
Tanya Otte
Jon Pleim
Adam Reff (EPA), Postdoc
Shawn Roselle
Golam Sarwar (EPA)
John Streicher
Daniel Tong (contractor)
David Wong
Jeff Young
Shaocai Yu (contractor)
Yang Zhang (ORISE)
Model Evaluation and Applications Branch
Alice Gilliland, Chief
Melanie Ratteray (SEEP), Secretary
Wyat Appel
Kristen Foley
Jim Godowitch
Steve Howard
Sergey Napelenok
Chris Nolte
Rob Finder
Jenise Swall
Alfreida Torian
26
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Appendix B
Division and Branch Descriptions
Atmospheric Modeling Division
The Division implements the Memorandum of Understand-
ing and Memorandum of Agreement between the U.S.
Department of Commerce and the U.S. Environmental
Protection Agency. 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 manage-
ment 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 quality community to understand and
forecast the magnitude of the air pollution problem, as well
as to develop 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 contracts 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 con-
sulting 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. The Branch adapts and extends
meteorological models to couple effectively with chemistry-
transport models to create comprehensive air quality model-
ing systems, including the capability for two-way commu-
nication and feedback between the models. AMDB conducts
studies to describe the atmospheric processes affecting the
transport, diffusion, transformation, and removal of pollu-
tants in and from the atmosphere using both theoretical
approaches and analyses of monitoring and field study data.
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. The Branch 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.
The Air Quality Forecasting program fosters collaborations
between NOAA and EPA in developing, applying, and
evaluating comprehensive models for operational use for
providing short-term air quality forecast guidance.
Model Evaluation and Applications Branch
The Model Evaluation and Applications Branch (MEAB)
develops and applies advanced methods for evaluating the
performance of models in reproducing the observed air
quality. MEAB provides routine and high-performance
computing support needed by the Division in the develop-
ment, 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. MEAB fosters the
application of new computational techniques and tools to
environmental simulation modeling and contributes to the
interagency Information Technology Research and Devel-
opment program.
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Air-Surface Processes Modeling Branch
The Air-Surface Processes Modeling Branch (APMB) per-
forms process-based modeling research for the Division's
atmospheric pollutant models, with a focus on three research
themes: (1) emissions modeling, (2) deposition onto sensi-
tive ecosystems, and (3) linkage of air quality with human
exposure. APMB's emissions modeling effort (with a
special emphasis on natural sources such as windblown
fugitive dust, wildfires, and biogenic emissions) helps
ensure that meteorologically influenced emissions are
properly considered in air quality models. APMB's deposi-
tion research uses state-of-the-art trace-gas flux measure-
ments 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 Facility) is
focused on building "hot-spot" air toxic analysis algorithms
and linkages to human exposure models.
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.
28
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Appendix C
Awards and Recognition for 2007
NOAA Administrator's Award
Robin Dennis, Val Garcia, Alice Gilliland, Rohit
Mathur, Tom Pierce, S.T. Rao, and Ken Schere -
Leadership in the Development of "One
Atmosphere" Air Quality Model
EPA Bronze Medals
Prakash Bhave, David Mobley, Adam Reff, and
Golam Sarwar - SPECIATE Version 4 Release
NATO International Technical Meeting
Sergey Napelenok - Best Presentation by Young
Professional
EPA Special Act/Time Off Awards
George Bowker - QUIC Applications for Near
Roadway
Bill Hutzell - Evaluation of Air Toxic Modeling
with CMAQ
Deborah Luecken - VOC Reactivity Support to
OAQPS Regulatory Program
David Mobley - Administrative Support to AMD
Adam Reff - Advancing PM2 5 Source
Appointment Science
Golam Sarwar - Atmospheric Chemistry
Enhancements to CMAQ
NERL Special Achievement Awards
Russ Bullock, Bill Hutzell, Deborah Luecken,
Shawn Roselle, and Golam Sarwar - Goal 1:
Mission Support: Multipollutant Development
Team
David Mobley - Goal 4 Science Integration -
Inter-divisional-laboratory research: SPECIATE
project coordination with OAQPS, NRMRL,
OTAQ, and NERL
Bill Benjey, Ellen Cooler, Rob Gilliam, Alice
Gilliland, and Chris Nolte - Goal 5: Identifying
and Addressing Future Issues: CIRAQ Team
NOAA ClYA/Special Act/Time-Off Awards
Ann Marie Carlton - SOA Module
Ellen Cooler - Leadership of the eco-sy stem
program and APMB
Robin Dennis - Multimedia Modeling
Kristen Foley - Advancing Model Evalualion
Melhods
Rob Gilliam, Tanya Olte, and Jon Pleim -
Transilioning from MM5 to WRF
Jim Godowilch - Support to NOX SIP Call
Evalualion
David Heisl - Fluid Modeling Facility Support to
Near Roadway
Sieve Howard - AMI Air Accountability Projecl
Support
Vlad Isakov - Near Roadway and School
Infillralion Inilialive
Rob Finder - Evalualing NOX Emission Budgels
with CMAQ
Shawn Roselle - Archilecl of CMAQ
Mullipollulanl Model
Joe Touma - Support lo Ihe Mobile Source Air
Toxics Rule
Jeff Young - Oplimizing CMAQ
Val Garcia, Alice Gilliland, Rohil Malhur, Tom
Pierce, S.T. Rao, and Ken Schere - Scientific
Leadership
Recognition
Acting Director of Ihe Ecosystems Research
Division in Athens, GA - Tom Pierce
Acting Branch Chief of APMB-Ellen Cooler
New Zealand Embassy Science Fellow - David
Mobley
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Appendix D
Publications for 2007
(Division authors are in bold)
Journal Articles
Appel, K.W, A.B. Gilliland, G. Sarwar, and R.C.
Gil Mam Evaluation of the Community Multi-scale Air
quality (CMAQ) model version 4.5: Sensitivities impacting
model performance; Parti ozone. Atmospheric Environment,
41(40): 9603-9615 (2007).
Badendreier, I, L.S. Matott, J. Hameedi, R Dennis, C.
Knightes, R Mathur, Y. Mohamoud, J.M. Johnson, G.
Laniak, N. Gaber, P. Pascual, and R. Araujo. Managing
multimedia pollution for a multimedia world. EM: Air and
Waste Management Association Magazine for
Environmental Managers, 6-11(2007).
Bhave, P.V., G.A. Pouliot, and M. Zheng. Diagnostic
model evaluation for carbonaceous PM25 using organic
markers measured in the southeastern U.S. Environmental
Science & Technology 41: 1577-1583 (2007).
Bowker, G.E., R. Baldauf, V. Isakov, A. Khlystov, and W.
Petersen. The effects of roadside structures on the transport
and dispersion of ultrafine particles from highways.
Atmospheric Environment, 41: 8128-8139 (2007).
Bowker, G.E. and H.C. Crenshaw. Electrostatic forces in
wind-pollination: Part 1, Measurement of the electrostatic
charge on pollen. Atmospheric Environment, 41: 1587-1595
(2007).
Bowker, G.E. and H.C. Crenshaw. Electrostatic forces in
wind-pollination: Part 2, simulations of pollen capture.
Atmospheric Environment, 41: 1596-1603 (2007).
Bowker, G.E., D. Gillette, G. Bergametti, B. Maticorena,
and D. Heist. Sand flux simulations at a small scale over a
heterogeneour mesquite area of the northern Chihuahuan
desert. Journal of Applied Meteorology and Climatology
(specialIssue), 46(9): 1410-1422 (2007).
Carlton, A.G., B.J. Turpin, K.E. Eltieri, S. Seitzinger, A.
Reff, H-J. Lim, and B. Ervens. Atmospheric oxalic acid and
SOA production from glyoxal: Results of aqueous photo
oxidation experiments. Atmospheric Environment, 41(35):
7588-7602 (2007).
Chow, J.C., J.G. Watson, HJ. Feldman, J.E. Nolen, B.
Wallerstein, G.M. Hidy, PJ. Lioy, D. Mobley, K. Baugues,
and J. Bachmann. Will the circle be unbroken: A history of
the U. S. National Ambient Air Quality Standards. Journal
of the Air and Waste Management Association, 57: 1151-
1163(2007).
Cook, R., M. Strum, J. Touma, T. Plama, J. Thurman, D.
Ensley, and R. Smith Inhalation exposure and risk from
mobile source air toxics in future years. Journal of Exposure
Analysis & Environmental Epidemiology, 17: 95-105
(2007).
Cook, R., J.S. Touma, A. Fernandez, D. Brzezinski, C.
Bailey, C. Scarbro, J. Thurman, M. Strum, D. Ensley, and
R. Baldauf. Impact of underestimating the effects of cold
temperature on motor vehicle start emissions of air toxics in
the United States. Journal of the Air and Waste
Management Association, 57: 1469-1479(2007).
Cooter, E.J., J. Swall, and R Gilliam Comparison of 700-
hPa NCEP-R1 and AMIP-R2 wind patterns over the
continental United States using cluster analysis. Journal of
Applied Meteorology and Climatology, 46(11): 1744-
1758(2007).
Dennis, R, R. Haeuber, T. Blett, J. Cosby, C. Driscoll, J.
Sickles, and J. M. Johnston. Sulfur and nitrogen deposition
on ecosystems in the United States. EM: Air and Waste
Management Association Magazine for Environmental
Managers, 12-17(2007).
Gego, E., P.S. Porter, A. Gilliland, and S.T. Rao.
Observation-based assessment of the impact of nitrogen
oxides emissions reductions on ozone air quality over the
eastern United States. Journal of Applied Meteorology and
Climatology (special issue), 46(7): 994-1008 (2007).
30
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Hogrefe, C. W. Hao, K. Civerolo, J.-Y. Ku, G. Sistla, R. S.
Gaza. L. Sedefian, K. Schere, A. Gilliland, and R
Mathur. Daily Simulation of ozone and fine particulates
over New York State: Findings and challenges. Journal of
Applied Meteorology and Climatology (special issue),
46(7): 961-979 (2007).
Hudman, R.C., D.J. Jacob, S. Turquety, E.M.
Leibensperger, L.T. Murray, S. WU, A.B. Gilliland, M.
Avery, T.H.Bertram, W. Brune, R.C. Cohen, J.E. Dibb,
P.M. Flocke, A. Fred, J. Holloway, J.A. Neuman, R.
Orville, A. Perring, X. Ren, G.W. Sachse, H.B. Singh, A.
Swanson, and P.J. Wooldridge. Surface and lightning
sources of nitrogen oxides over the United States:
magnitudes, chemical evolution, and outflow. Journal of
Geophysical Research, 112(D12S05):1-14 (2007).
Irwin, J.S., W.B. Petersen, and S. Howard. Probabilistic
characterization of atmospheric transport and diffusioa
Journal of Applied Meteorology and Climatology (special
issue), 46(7): 980-993 (2007).
Isakov, V., J. Irwin, and J. Ching. Using CMAQ for
exposure modeling and characterizing the sub-gird
variability for exposure estimates. Journal of Applied
Meteorology and Climatology (special Issue, 46(9): 1354-
1371 (2007).
Isakov, V., J.S. Touma, A. Khlystov. A method of
assessing air toxics concentrations in urban areas using
mobile platform measurements. Journal of the Air & Waste
Management Association 57: 1286-1295 (2007).
Isakov V., A. Venkatram, J. Touma, D. Koracin, and T.
Otte. Evaluating the use of outputs from comprehensive
meteorological models in air quality modeling applications.
Atmospheric Environment, 41(8): 1689-1705 (2007).
Kang, D., R Mathur, K. Schere, S. Yu, and B. Eder. New
categorical metrics for air quality model evaluation. Journal
of Applied Meteorology and Climatology: Special Issue
NOAA/EPA Golden Jubilee, 46(4): 549-555 (2007).
Koracin, D., A. Panorska, V. Isakov, J.S. Touma, and J.
Swall. A statistical approach for estimating uncertainty in
dispersion modeling: An example of application in
southwestern USA. Atmospheric Environment, 41(3): 617-
628 (2007).
Liao, K.-J., E. Tagaris, K. Manomaiphiboon, S.L.
Napelenok, J-H. Woo, S. He, P. Amar, and A.G. Russell.
Sensitivities of ozone and fine paniculate matter formation
to emissions under the impact of potential future climate
change. Environmental Science and Technology, 41(24):
8355-8361(2007).
Lin, Che-Jen, P. Pongprueksa, O.R Bullock, Jr., S.E.
Lindberg, S.O. Phkonen, C. Jang, T. Braverman, and T.C.
Ho. Scientific uncertainties in atmospheric mercury models
II: Sensitivity analysis in the CONUS domain. Atmospheric
Environment, 41(31): 6544-6560 (2007).
Lindberg, S.,O.R Bullock, Jr, R. Edinghaus, D. Engstrom,
X. Feng, W. Fitzgerald, N. Pirrone, E. Prestbo, and C.
Seigneur. A synthesis of progress and uncertainties in
attributing the sources of mercury in deposition. Ambio, A
Journal of the Human Environment, 36 (1): 19-33 (2007).
Mathur, R, W. Frick, G.G. Lear, and R Dennis.
Ecological forecasting: Microbial contamination and
atmospheric loading of nutrients to land and water. EM: Air
and Waste Management Association Magazine for
Environmental Managers, 36-40(2007).
McKeen, S., S.H. Chung, J. Wilczak, G. Grell, I. Djalalova,
S. Peckham, W. Gong, V. Bouchet, R. Moffet, G.R.
Carmichael, R Mathur, and S. YU. Evaluation of several
PM25 forecast models using data collected during the
ICARTT/NEAQS 2004 field study. Journal of Geophysical
Research, 112: 1-20(2007).
Pennell, W., R. Scheffe, J. Brook, K. Demerjian, G. Hidy, J.
Vickery, and J. West. Implementing accountability within a
multi-pollutant air quality management framework. EM: Air
and Waste Management Association Magazine for
Environmental Managers 21-24 (2007).
Pleim, J.E. A combined local and non-local closure model
for the atmospheric boundary layer. Part 1: Model
description and testing. Journal of Applied Meteorology and
Climatology (special issue). 46(9): 1383-1395 (2007).
Pleim, J.E.A combined local and non-local closure model
for the atmospheric boundary layer. Part 2: Application and
evaluation in a mesoscale meteorology model. Journal of
Applied Meteorology and Climatology (special issue).
46(9): 1396-1409 (2007).
Pour-Biazar, A., R.T. McNider, S.J. Roselle, R. Suggs, G.
Jedlovec, S. Haines, S. Kim, D.W. Byun, J.C. Lin, and T.C.
Ho. Assimilation of GOES satellite data in CMAQ:
Correcting photolysis rates based on observed clouds.
Journal of Geophysical Research, 112:(D10302): 1-17
(2007).
Rao, S.T. Linking Air, Land, and Water Pollution for
Effective Environmental Management. EM: Air and Waste
Management Association Magazine for Environmental
Managers, 5(2007).
Reff, A., B.J. Turpin, J.H. Offenberg, C.P. Weisel, J. Zang,
M. Morandi, T. Stock, S. Colome, and A. Winer. A
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functional Group Characterization of organic PM25
exposure: Results from the RIOPA study. Atmospheric
Environment, 41(22): 4585-4598 (2007).
Reff, A.H., S.I. Eberly, and P. Bhave. Receptor modeling
of ambient paniculate matter data using positive matrix
factorization review of existing methods. Journal of the Air
& Waste Management Association, 57 (2): 146-154, (2007).
Roy, B., G. Pouliot, A. Gilliland, T. Pierce, S. Howard, P.
Bhave, and W. Benjey. Refining fire emissions for air
quality modeling with remotely sensed fire counts: A
wildfire case study. Atmospheric Environment, 41: 655-665
(2007).
Roy, B., R. Mathur, A. Gilliland, and S. Howard. A
comparison of CMAQ-based aerosol properties with
IMPROVE, MODIS and AERONET data. Journal of
Geophysical Research, 112:(D14): 1-17(2007).
Ryaboskapko, A., O.R Bullock, J. Christensen, M. Cohen,
A. Dastoor, I. liyin, G. Petersen, D. Syrakov, R.S. Artz, D.
Davignon, R.R. Draxler, and J. Munthe. Intercomparison
Study of Atmospheric Mercury Models: 1. Comparison of
models with short-term measurements. Science of the Total
Environment, 376: 228-240 (2007).
Ryaboskapko, A., O.R Bullock, J. Christensen, M. Cohen,
A. Dastoor, I. liyin, G. Petersen, D. Syrakov, R.S. Artz, D.
Davignon, R.R. Draxler, and J. Munthe. Intercomparison
study of atmospheric mercury models: 2. Modeling results
vs. long-term observations and comparison of country
atmospheric balances. Science of the Total Environment.
377:319-333 (2007).
Sarwar, G and P.V. Bhave. Modeling the effect of chlorine
emissions on ozone levels over the eastern United States.
Journal of Applied Meteorology and Climatology (special
issue), 46(7): 1009-10190(2007).
Singh, R.B., A.H. Huber, and J.N. Braddock. Sensitivity
analysis and evaluation of MicroFac PM: A microscale
motor vehicle emission factor model for PM emissions.
Journal of the Air & Waste Management Association, 57(4):
420-433 (2007).
Smolarkiewicz, P., R. Sharman, J. Weil, S.G. Perry, D.
Heist, and G. Bowker. Building resolving large- eddy
simulations and comparison with wind tunnel experiments.
Journal of Computational Physics. 227(1): 633-653 (2007).
Stein, Airel F., V. Isakov, J. Godowitch, and R.R. Draxler.
A hybrid modeling approach to resolve pollutant
concentrations in an urban area. Atmospheric Environment,
41(40): 9410-9426 (2007).
Tong, D., R Mathur, K. Schere, D. Kang, and S. Yu. The
use of air quality forecasts to assess impacts of air pollution
on crops: Methodology and case study. Atmospheric
Environment, 41(38): 8772-8784(2007).
Touma, J.S., V. Isakov, A. Cimorelli, B. Anderson, and R.
Erode. Using Prognostic Model Generated Meteorological
Output in the AERMOD dispersion model: An illustrative
application in Philadelphia, PA. Journal of Air & Waste
Management Association, 57(5):586-595, (2007).
Venkatram, A., V. Isakov, E. Thoma, and R. Baldauf.
Analysis of air quality data near roadways using a
dispersion model. Atmospheric Environment, 41: 9481-9497
(2007).
Yu, S., R Mathur, K.L. Schere, D. Kang, J.A. Pleim, and
T.L. Otte. A Detailed Evaluation of the ETA-CMAQ
Forecast Model Performance for O3, Its Related Precursors,
and Meteorological Parameters during The 2004 ICARTT
Study. Journal of Geophysical Research-Atmospheres,
112(D12S14): 1-24, (2007).
Yu, S., P.V. Bhave, RL. Dennis, and R Mathur. Seasonal
and regional variations of primary and secondary organic
aerosols over the continental United States: Semi-empirical
estimates and model evaluation. Environmental Science &
Technology, 41(13): 46904697 (2007).
Zheng J., J.L. Swall, W.M. Cox, and J.M. Davis. Inter-
annual variation in meteorologically adjusted ozone levels
in the eastern United States: A comparison of two
approaches. Atmospheric Environment, 41(4):705-716
(2007).
Published Reports
Rao, S.T., R Dennis, V. Garcia, A. Gilliland, R Mathur,
D. Mobley, T. Pierce, and K. Schere. Summary Report of
Air Quality Modeling Research Activities for 2006. U.S.
Environmental Protection Agency, EPA/600/R-07/103,
(2007).
Conference Papers and Proceedings
Rao, S.T., A.B. Gilliland, K. Foley, and C. Hogrefe.
Evaluating and using Air Quality Models. International
Conference on Urban Air Quality, Limassol, Cyprus, March
29, 2007.
Sarwar, G., S. Roselle, R Mathur, W. Appel, and R.
Philbrick. A comparison of Community Multi scale Air
Quality (CMAQ) Modeling System predictions with
observations from the Northeast oxident and particle study.
100th Air and Waste Management Association Annual
32
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Conference and Exhibition, Pittsburgh, Pennsylvania, June
26-29, 2007
Heist, D.K., S.G. Perry, L. Brixey, and G.E. Bowker.
Wind tunnel simulations of pollution from roadways.
International Workshop on Physical Modeling of Flow
dispersion Penomena (PHYSMOD2007). University of
Orleans, France, August 29-31, 2007.
Pullen, Julie, J. Ching, W. Sailor, W. Thompson, B.
Bornstein, and D. Koracin. Summary and Highlights of the
AMS 7th Conference on Coastal, Atmospheric and, Oceanic
Prediction and Process and 7th Symposium on the Urban
Environment. AMS 7th Conference on Coastal, Atmospheric
and, Oceanic Prediction and Process and 7th Symposium
on the Urban Environment. San Diego, CA, September 9-
13, 2007.
Ching, J. National urban database and access portal tools
(NUDAPT): a project overview. AMS 7th Symposium on the
Urban Environment. San Diego, CA, September 10-13,
2007.
Huber, A. Evaluation study of building-resolved urban
dispersion models. AMS 7th Annual Symposium on the
Urban Environment. San Diego, CA, September 13, 2007.
Huber, A. Preliminary results of CFD simulation for the
scenario of a recent field study in an urbanized domain.
AMS 7th Symposium on the Urban Environment. San Diego,
CA, September 13, 2007.
Bullock, O.R, Jr. The effect of lateral boundary values on
atmospheric mercury simulations with the CMAQ model.
29th NATO/ SPS International Technical Meeting on Air
Pollution Modeling and its Application, Aveiro, Portugal,
September 24-28, 2007.
Davidson, P, K. Schere, R. Draxler, S. Kondragunta, R.A.
Wayland, J. F. Meagher, and R Mathur. Toward a US
national air quality forecast capability: Current and planned
capabilities. 29th NATO/ SPS International Technical
Meeting on Air Pollution Modeling and its Application,
Aveiro, Portugal, September 24-28, 2007.
Gilliam, R., J. Pleim, and A, Xiu. Implementation of the
pleim-xiu land surface model and asymmetric convective
model in the WRF model. 29th NATO/ SPS International
Technical Meeting on Air Pollution Modeling and its
Application, Aveiro, Portugal, September 24-28, 2007.
Gilliland, A.B., J.M. Godowitch, C. Hogrefe, and S.T.
Rao. Evaluating regional-scale air quality models. 29th
NATO/ SPS International Technical Meeting on Air
Pollution Modeling and its Application, Aveiro, Portugal,
September 24-28, 2007.
Hogrefe, C., J. Y. Ku, G. Sistla, A. Gilliland, J.S. Irwin,
P.S. Porter, E. Gego, P. Kasibhatla, and S.T. Rao. Has the
performance of regional-scale photochemical modeling
systems changed over the past decade? 29th NATO/ SPS
International Technical Meeting on Air Pollution Modeling
and its Application, Aveiro, Portugal, September 24-28,
2007.
Isakov, V., H. Ozkaynak. A modeling methodology to
support evaluation of public health impacts of air pollution
programs. 29th NATO/ SPS International Technical Meeting
on Air Pollution Modeling and its Application, Aveiro,
Portugal, September 24-28, 2007.
Luecken, D. Evaluating the effects of emission reductions
on multiple pollutants simultaneously. 29th NATO/ SPS
International Technical Meeting on Air Pollution Modeling
and its Application, Aveiro, Portugal, September 24-28,
2007.
Mathur, R., S. Roselle, and G. Pouliot. Diagnostic analysis
of the three-dimensional sulfur distributions over the
Eastern United States using the CMAQ model and
measurements from the 2004 ICARTT Field experiment.
29th NATO/ SPS International Technical Meeting on Air
Pollution Modeling and its Application, Aveiro, Portugal,
September 24-28, 2007.
Mobley, D., L. Beck, G. Sarwar, A. Reff, and M.
Houyoux. SPECIATE - EPA's Database of Speciated
Emission Profiles. 29th NATO/SPS International Technical
Meeting on Air Pollution Modeling and its Application,
Aveiro, Portugal, September 24-28, 2007.
Napelenok, S.L., R.W. Finder, A.B. Gilliland, and R.V.
Martin. Developing a method for resolving NOx emission
inventory biases using discrete Kalman filter inversion,
direct sensitivities, and satellite-based NO2 columns. 29th
NATO/ SPS International Technical Meeting on Air
Pollution Modeling and its Application, Aveiro, Portugal,
September 24-28, 2007.
Nolte, C., A.B. Gilliland, and C. Hogrefe. Linking global to
regional models to simulate U.S. air quality in the year
2050. 29th NATO/SPS International Technical Meeting on
Air Pollution Modeling and its Application, Aveiro,
Portugal, September 24-28, 2007.
Pleim, J, J. Young, D. Wong, R Gilliam, W. Hutzell, T.
Otte, and J. Walker. Bi-directional surface chemical fluxes
for 2-way coupled meteorology and air quality modeling.
29th NATO/ SPS International Technical Meeting on Air
33
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Pollution Modeling and its Application, Aveiro, Portugal,
September 24-28, 2007.
Roy, B.A., G.A. Poulit, D. Mobley, T. G. Pace, A. J. Soja,
J. J. Szykman, and J. Al-Saadi. Development of an
inventory of fire emissions using satellite data. 29th NATO/
SPS International Technical Meeting on Air Pollution
Modeling and its Application, Aveiro, Portugal, September
24-28, 2007.
Sarwar, G., R. Dennis, and B. Vogel. The effect of
heterogeneous reactions of model performance for nitrous
acid. 29th NATO/ SPS International Technical Meeting on
Air Pollution Modeling and its Application, Aveiro,
Portugal, September 24-28, 2007.
Davis, J.M., P. Bhave, and K. Foley. Parameterization of
N2O5 Reaction probabilities for inclusion in CMAQ. 6th
Annual CMAS Conference Preprints, Chapel Hill, NC,
October 1-3, 2007.
Roselle, S., D.J. Luecken, W.T. Hutzell, O.R. Bullock, G.
Sawar, and K. Schere. Development of a Multi pollutant
version of the Community Multi scale Air Quality (CMAQ)
modeling system. 6th Annual CMAS Conference Preprints,
Chapel Hill, NC, October 1-3, 2007.
Schwede, D., N. Collier, A. Dolph, M.A. Widing, and T.
Howe. A New Tool for analyzing CMAQ modeling results:
Visualization Environment for rich data
interpretation(VERDI). 6th Annual CMAS Conference
Preprints, Chapel Hill, NC, October 1-3, 2007
34
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Appendix E
Abbreviations
ACM Asymmetric Convective Model
AERMIC AMS/EPA Regulatory Model
Improvement Committee
AERMOD AMS/EP A Regulatory Model
AMB Applied Modeling Branch
AMD Atmospheric Modeling Division
AMDB Atmospheric Model Development
Branch
AMET Atmospheric Model Evaluation Tool
AMS American Meteorological Society
APMB Air-Surface Processes Modeling Branch
ARL Air Resources Laboratory
ASMD Atmospheric Sciences and Modeling
Division
BenMAP Benefits Mapping and Analysis Program
CAA Clean Air Act
CAIR Clean Air Interstate Rule
CAMD Clean Air Markets Division
CAMR Clean Air Mercury Rule
CASTNET EPA's Clean Air Status and Trends
Network
CAVR Clean Air Visibility Rule
CB05 CarbonBondOS
CBP Chesapeake Bay Program
CBPO Chesapeake Bay Program Office
CCSP Climate Change Science Program
CEM Continuous Emission Monitoring
CIRAQ Climate Impacts on Regional Air Quality
CIYA Cash In Your Account
CMAQ Community Multiscale Air Quality
Model
CMAQ-TX Community Multiscale Air Quality
Model-Texas
CMAQ-UCD University of California Davis aerosol
module coupled to the Community
Multiscale Air Quality model
CMAS Community Modeling and Analysis
System
DDM Decoupled Direct Method
DDM3 -D Decoupled Direct Method-3 d
DOC Department of Commerce
EGU Electric Generating Units
EPA Environmental Protection Agency
ESRP Ecological Services Research Program
FRD NOAA's Field Research Division
FY Fiscal Year
GFDL Geophysical Fluid Dynamics Laboratory
GHG greenhouse gas
HAPEM Hazardous Air Pollutant Exposure Model
HAPS Hazardous Air Pollutants
HUC Hydrological Cataloging units
HYSPLIT Hybrid Single Particle Lagrangian
Integrated Trajectory
INTEX Intercontinental Chemical Transport
Experiment
IPCC International Panel on Climate Change
MCIP Meteorology-Chemistry Interface
Processor
MEAB Model Evaluation and Applications
Branch
MLB C Multilayer biochemical model
MLM Multi-Llyer Model
MM5 Fifth Generation of the Perm
State/UCAR Mesoscale Model
MOA Memorandum of Agreement
MOU Memorandum of Understanding
NAAQ S National Ambient Air Quality Standard
NAM North American Mesoscale
NAMMIS North American Mercury Model
Intercomparison Study
NAS National Academy of Sciences
NBP NOX Budget Trading Program
NCAR National Center for Atmospheric
Research
NCEA National Centers for Environmental
Prediction
NERL National Exposure Research Laboratory
NHEERL National Health and Environmental
Effects Research Laboratory
NLCD National Land Cover Data
NMM Nonhydrostatic Mesoscale Model
NOAA National Oceanic and Atmospheric
Administration
35
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NRMRL National Risk Management Research
Laboratory
NUDAPT National Urban Database and Access
Portal Tool
NWS National Weather Service
OAQPS Office of Air Quality Planning and
Standards
OAR Office of Oceanic and Atmospheric
Research
ORD Office of Research and Development
PAH Poly cyclic Aromatic Hydrocarbons
PAVE Package for Analysis and Visualization
of Environmental data
PEL planetary boundary layer
PM paniculate matter
PMML Predictive Model Markup Language
ppb parts per billion
ppm parts per million
PXLSM Pleim-Xiu Land Surface Model
QUIC Quick Urban Industrial Complex
REMSAD Regional Modeling System for Aerosols
and Deposition
RHR Regional Haze Rule
RPO Regional Planning Organization
SAP Statewide Air Pollution Research Center
SAPRC07-TX Statewide Air Pollution Research Center
- 2007 toxics version of the chemical
mechanism - Texas
SGV sub-grid variability
SHEDS Stochastic Human Exposure and Dose
Simulation
SIP State Implementation Plans
SMOKE Sparse Matrix Operator Kernel
Emissions
SOA secondary organic aerosol
TBEP Tampa Bay Estuary Program
TEAM Trace Element Analysis Model
TMDL Total Maximum Daily Load
VERDI Visualization Environment for Rich Data
Interpretation
WDT Watershed Deposition Tool
WRF Weather Research and Forecasting
36
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