OVERVIEW OF THE CLIMATE IMPACT
ON REGIONAL AIR QUALITY (CIRAQ) PROJECT
Ellen J. Cooter, Alice Gilliland, William Benjey, Robert Gilliam, Jenise Swall
U.S. EPA, National Exposure Research Laboratory, Atmospheric Modeling Division
Research Triangle Park, NC 27711
e-mail: cooter.ellen@epa.gov
Voice (919)-541 -1334	Fax (919)-541 -1379	EPA/600/A-04/089
1.0 INTRODUCTION
Predicted changes in the global climate
over the next hundred years and more could
create new weather patterns and associated
changes in land use, source emissions, and
tropospheric air quality. The U.S. EPA Climate
Impact on Regional Air Quality (CIRAQ) project,
illustrated below, examines present-day and future
(circa. 2050) global climate scenarios as they
might affect regional and urban tropospheric air
quality in North America. This work supports the
U.S.EPA Global Change Research Program
(GCRP) as well as contributes to U.S. Climate
Change Research Program (CCSP) synthesis
reports dealing with atmospheric composition
(CCSP, 2003). Primary drivers of future air quality
are climate variability, climate change and
emissions. CIRAQ addresses these drivers by first
isolating air quality response to future climate
alone (Phase I). CIRAQ Phase I employs a Global
Climate Model (GCM) to generate downscaled
regional climate conditions under present and
future climate scenarios. These regional climate
modeling scenarios will then be used to drive the
Community Multi-Scale Air Quality (CMAQ) model.
To isolate the effects from potential climate
change, emissions will remain constant for the
Phase I simulations, except for changes that are a
response to climate factors. More detailed model
specifications for these simulations are provided in
following sections. CIRAQ Phase II will revisit
these air quality scenarios using an alternative
emission inventory that includes some estimate of
CIRAQ
Biogenic
emissions
Downscaled Meteorology
CCSP
Synthesis Report 4.5
Air Quality Scenarios
CCSP
Base Program
3. Atmospheric Composition
Air Quality
(Ozone and PM)
CCSP
Synthesis Report 4.6
Socioeconomic Impacts of
Climate Variability
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future economic, population and technological
change in the continental U.S. and, perhaps,
expand the analysis to include additional future
climate scenarios.
CIRAQ represents a first attempt to
perform a detailed analysis of air quality response
to climate variability and change across the full
continental U.S. domain at a regional scale
resolution. As such, it introduces several new
challenges forCMAQ model application, analysis
and interpretation. This study will require
generation of multi-year model simulations and
coordination with, and integration of data and
model results from a variety of new sources. For
example, Global Chemical Transport (GCT) model
output must be linked with the regional-scale
meteorological and air quality models to account
for global scale climate forcing. Also, dynamic
biogeographic models and future emission
projection systems such as the Economic Growth
and Analysis System (EGAS, E.H. Pechan &
Assoc., Inc., 2001) and MOBILE6 (Office of
Transportation and Air Quality, 2002) must all be
integrated to develop future air quality emission
scenarios that go beyond using coarse emission
adjustment factors that were intended for global
scale climate modeling. In addition to these
technical issues, model uncertainties and biases
on the global and regional scales suggest that the
CIRAQ simulations should be considered an
investigative model sensitivity study and that
additional comparisons across different models
would increase our confidence in the results.
These and related research issues are being
addressed by the EPA Global Change Research
Program through CIRAQ, through related projects
in other ORD Laboratories and EPA Program
Offices (e.g. NRMRL, OAQPS), through Science to
Achieve Results (STAR) research grants and
through collaboration with other Federal Agencies
(e.g., DOE, USDA/FS).
2.0 CIRAQ APPLICATION ELEMENTS
The CIRAQ project is made up of several
distinct application elements - all building towards
an integrated, physically consistent description of
future air quality status and change. Primary
Phase I elements include 1) development of
present-day and future regional climate scenarios
(RCM's), 2) development of present and future
climate driven emission scenarios, and 3)
execution, diagnosis and interpretation of CMAQ
results.
2.1 Regional Climate Scenarios
Development of climate scenarios for
regional scale air quality applications presents new
challenges for the climate change research
community. First, even relatively coarse national-
scale policy-relevant air quality studies require
information at horizontal resolutions of
approximately 36km * 36km, and the vertical
resolution of the meteorological fields must
resolves boundary layer processes. GCM
simulations have horizontal resolutions of a few
degrees latitude and longitude typically and
relatively coarse vertical layering as compared to
mesoscale meteorological models; therefore,
regional scale air quality models require a higher
spatial resolution than GCMs provide.
These requirements are addressed
through the use of the Fifth Generation
Pennsylvania State University/National Center for
Atmospheric Research Mesoscale Meteorological
Model (MM5; Grell et al., 1994) to generate
physically consistent downscaled regional climate
scenarios from coarse resolution GCM data.
Downscaling of the NASA Global Institute for
Space Studies (GISS) version II', GCM (Rind and
Lerner, 1996; Rind et al., 1999) has been
performed for CIRAQ through a partnership with
the DOE Pacific Northwest National Laboratory
(Dr. Ruby Leung). The overall goal of this type of
downscaling is to make maximum use of GCM
information, and so MM5 parameterization
schemes were selected to maintain the large-scale
GCM climate patterns and variability while adding
the finer scale detail needed to support CMAQ
applications. MM5 configuration for CIRAQ
includes 23 vertical layers, the medium range
forecast model (MRF) planetary boundary layer
scheme, the Grell cumulus cloud parameterization
scheme, rapid radiative transfer model (RRTM)
and a mixed phase microphysics model, Reisnerl,
without grauple. Since these simulations are
driven by GCM information rather than assimilated
observation or reanalysis, they do not necessarily
reproduce day-to-day and exact year-to-year
observed variations but rather, represents time
periods under the representative climatological
conditions. In addition, without the assimilation of
observed data, model biases in the GCM will be
introduced into the RCM scenarios. Thus, careful
evaluation that is appropriate to the climatological
nature of the scenarios is essential to identify and
to better understand climatological biases that
could impact CMAQ model performance.
Once complete, the downscaled MM5
scenarios are carefully quality controlled and

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processed through the Meteorology-Chemistry
Interface Processor (MCIP) version 2.2. It is the
MCIP scenarios that are evaluated and compared
to observation to facilitate later CMAQ diagnosis
as well as climate scenario study. MCIP scenario
analysis takes three forms; 1) analysis to screen
model output to check for sensible mean and
variability results, 2) timeseries analysis to
characterize the seasonal and interannual
components relevant to specific air quality-related
meteorological conditions and 3) spatial analysis to
study large scale dominant patterns as well as
unusual or extreme patterns of atmospheric
transport relevant to specific air quality-related
meteorological conditions.
2.2 Emissions Scenarios
Baseline (current) and future emission
scenarios specifying the Statewide (California) Air
Pollution Research Center (SAPRC; Carter, 2000)
chemical mechanism with speciation profiles for
criteria pollutants are required for the CIRAQ
analysis. Inventory-based emissions derive from
the most recent 2001 modeling inventory (referred
to as 01 ad) prepared for the Office of Air Quality
Planning and Standards (ref.). Plume rise is
computed for all possible point sources. Major
point sources, such as Electric Generating Unit
stacks, are not separately defined. Instead, annual
electrical generating unit values are disaggregated
with temporal profiles.
Some meteorology-dependent emission
data (i.e. not from an inventory) are modeled
using the same hourly meteorological data used by
CMAQ. These include biogenic emissions
(modeled by the Biogenic Emission Inventory
System, Version 3.12; Pierce, et al., 1998; Pierce
et al., 2002) and on-road mobile source emissions
modeled by the U.S. EPA MOBILE6 mobile source
emission model. The Sparse Matrix Operator
Kernel Emission (SMOKE; Carolina Environmental
Programs, 2003) model will be used to prepare
current and 2050 emission inventories for use with
planned CMAQ model runs.
CIRAQ Phase II captures the direct and
indirect effects of changes of biogenic and
anthropogenic emissions by including projections
of emissions to the year 2050. In order to create a
range of scenarios of projected emission values,
many natural, economic, and technological factors
must be considered. The methodologies to be
used could include (1) modeling of future electric
generation and transportation technologies and
their emission implications, using the MARKAL
model (an energy systems optimization modeling
framework; Seebregts, et al., 2001; Fishbone et
al., 1983) and updates to the MOBILE6 on-road
motor vehicle emission model; (2) the projection of
emissions based on economic growth factors by
emission source category and geographic region,
possibly using an updated version of EGAS; (3)
determination of the most likely land use change
scenarios for North America, including urban-rural
population shifts, principal road network changes,
and commercial development patterns; and (4)
spatial and species composition changes in
vegetation land cover, which in turn affect biogenic
emissions.
2.3 Generation of the Air Quality Scenarios
The air quality modeling scenarios will be
generated using the USEPA Community Multiscale
Air Quality (CMAQ) model, version 4.4 with
SAPRC chemical mechanisms. In agreement with
the regional climate modeling scenarios, the
horizontal domain will cover the contiguous United
States at a 36km x 36 km grid resolution. Using
CMAQ's MCIP version 2.2 processor, the vertical
resolution of the regional climate simulations have
been collapsed to 14 sigma layers with the lowest
layer being 36m thick and the upper bound being
100mb.
To provide initial and boundary conditions
for these CMAQ simulations, a CTM was used that
is driven by the same GCM providing boundary
conditions to MM5 for the RCM simulations
described in Section 2.1, i.e., GISS II'. Online
chemistry has been integrated into GISS II' to
provide ozone and tracer predictions (Mickley et
al., 1999). The resolution for these model
predictions is quite coarse at 4° x 5°. Evaluation of
a related global CTM at this spatial scale has
shown spatial prediction patterns that were quite
good but local maximas that were compromised
(Fiore et al., 2003). Since we are using the global
CTM predictions as background monthly-average
values, the coarse resolution should be sufficient.
An obvious advantage is that these GCM-based
chemical predictions provide chemical boundary
conditions under current and future climate change
scenario forcing.
When comparing current to future
modeling simulations, it is important that we
consider interannual variability as well as climate
trends. Five annual simulations will be performed
for the current and future (2050) time periods.
Again, since the model simulations are based on a
GCM, these will not represent the specific years

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but rather five years that are representative of the
climatological conditions. CMAQ analyses will
attempt to identify climate-related signals in current
versus future air quality predictions. Evaluation of
the current time period will also be performed with
approaches that recognize the climatological
nature of the simulations. It is anticipated that
these Phase I simulations and associated analyses
will be complete by the end of 2006 for inclusion in
the EPA GCRP 2007 report.
3.0 REFERENCES
Carolina Environmental Programs (CEP), 2003:
Sparse Matrix Operator Kernel Emission
(SMOKE) Modeling System, University of North
Carolina, Carolina Environmental Programs,
Research Triangle Park, NC, [Available online at
http://www.cmascenter.org.]
Carter, W.P.L, 2000: Documentation of the
SAPRC-99 Chemical Mechanism for VOC
Reactivity Assessment. Contract 92-329 and
Contract 95-308 Report, prepared for the
California Air Resources Board by the Air
Pollution Research Center and College of
Engineering, University of California, Riverside,
CA.
CCSP, 2003: Strategic Plan for the U.S. Climate
Change Science Program. Climate Change
Science Program Office, Washington,D.C.
E.H. Pechan and Associates, Inc., 2001:
Economic Growth Analysis System: Version 4.0
User's Guide. Pechan Report No.
01.01.003/9008-404, Prepared for the Office of
Air Quality Planning and Standards, U.S.
Environmental Protection Agency by E.H.
Pechan and Associates, Inc., Durham, NC.
Fiore, A.M., D.J. Jacob, R. Mathur, and R.V.
Martin, 2003: Application of empirical orthogonal
functions to evaluate ozone simulations with
regional and global models. J. Geophys. Res.,
108 (D14), 4431.
Fishbone, L.G., G. Giesen, G.A. Goldstein, H.A.
Hymmen, K.J. Stocks, H. Vos, D. Wilde, R.
Zicher, C. Balzer, and H. Abilock, 1983: User's
Guide for MARKAL (BNLIFKA Version 2.0): A
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Energy Systems Analysis. Brookhaven National
Laboratory, Upton, NY, USA.
Grell, G.A., J. Dudhia, and D.R. Stauffer, 1994: A
description of the fifth-generation Penn
State/NCAR mesoscale model (MM5). NCAR
Technical Note, NCAR/TN-298+STR, 117 pp.
Mickley, L. J., P. P. Murti, D. J. Jacob, J. A. Logan,
D. M. Koch, D. Rind, 1999: Radiative forcing
from tropospheric ozone calculated with a
unified chemistry-climate model. J. Geophys.
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Office of Transportation and Air Quality, 2002:
User's Guide to Mobile6.1 and Mobile6.2:
Mobile Source Emission Factor Model.
EPA420-R-02-028, U.S. Environmental
Protection Agency, Ann Arbor, Ml, 264 pp.
Pierce, T., C. Geron, L. Bender, R. Dennis, G.
Tonnesen, and A. Guenther, 1998: Influence of
Increased Isoprene Emissions on Regional
Ozone Modeling. J. Geophys. Res., 103,
25611-25629.
Pierce,T., C. Geron, G. Pouliot, E. Kinnee, and J.
Vukovich, 2002: Integration of the Biogenic
Emissions Inventory System (BEIS3) into the
Community Multiscale Air Quality Modeling
System. In Proceedings of the Annual Meeting
of the Air and Waste Management Association,
Air and Waste Management Association:
Pittsburgh, PA, 2 pp.
Rind, D., and J. Lerner, 1996: Use of on-line
tracers as a diagnostic tool in general circulation
model development 1. Horizontal and vertical
transport in the troposphere. J. Geophys. Res.,
101 (D7), 12667-12684.
Rind, D., J. Lerner, K. Shah, and R. Suozzo, 1999:
Use of on-line tracers as a diagnostic tool in
general circulation model development 2.
Transport between the troposphere and
stratosphere. J. Geophys. Res., 104(D8),
9151-9168.
Seebregts, A.J., G.A. Goldstein, and K. Smekens,
2001: Energy/Environmental Modeling with the
MARKAL Family of Models. In Proceeding of the
OR2001 Conference, University of Duisburg-
Essen, Duisburg, Germany.
DISCLAIMER:
The research presented here was performed under the
Memorandum of Understanding between the U. S.
Environmental Protection Agency (EPA) and U.S.
Department of Commerce's National Oceanic and
Atmospheric Administration (NOAA) and under
agreement number DW13921548. Although it has been
reviewed by EPA and NOAA and approved for
publication, it does not necessarily reflect their policies
or views.

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