CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN
THE U.S. SIMULATED BY AN AIR QUALITY MODEL
Deborah J. Luecken and William T. Hutzell*
1. INTRODUCTION
The U.S. Environmental Protection Agency is examining the concentrations and
deposition of air pollutants that are known or suspected to cause cancer or other serious
health effects in humans. These "air toxics" or "hazardous air pollutants" (HAPs)
include a large number of chemicals, ranging from non reactive (i.e. carbon tetrachloride)
to reactive (i.e. formaldehyde), exist in gas, aqueous, and/or particle phases and are
emitted from a variety of sources. Some HAPs, such as formaldehyde and xylene, also
play an important role in the production of ozone and particulate. In addition,
concentrations of air toxics are required over both shorter (days) as well as longer (a year)
time scales in order to analyze health risks resulting from exposure to these compounds.
These requirements challenge the current capabilities of numerical air quality models
beyond their needs for other pollutants, such as ozone.
Most previous assessments of risks from HAPs have used Gaussian plume dispersion
models to predict concentrations, while ignoring or simplifying the atmospheric chemistry
that affects the concentrations of these pollutants (i.e. Rosenbaum et. al, 1999). Several
HAPs, such as formaldehyde and acetaldehyde, can be produced in the atmosphere in
greater quantities than they are directly emitted, so it is critical to adequately characterize
this complex chemistry. A 3-D photochemical grid model is better suited to account for
atmospheric chemistry, including the time-varying changes in radical concentrations that
affect the ambient concentrations of HAPs.
We have modified a numerical air quality model to simulate the concentration of
toxic air pollutants over large spatial and temporal scales. The application described here
focuses on a subset of HAPSs that exist in the gas phase. We describe the development
and testing of a chemical mechanism appropriate for HAPs; the incorporation of this
chemistry and physics into a chemical transport model; and analysis of the model results.
* U.S. Environmental Protection Agency, MD E243-03, Research Triangle Park, NC.
Luecken.deborah@epa.gov
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D.J. Luecken and W.T. Hutzell
2. MODEL DESCRIPTION
2.1	Model Platform, Domain and Meteorology
The Community Multi-Scale Air Quality Model (CMAQ) version 4.3 (Byun and
Ching, 1999, Byun and Schere, 2004) was the base air quality model used for this
application. In order to provide predictions for a domain that sufficiently covers the
continental U.S., the domain extends at least 450 km beyond the US borders in all
directions. This domain includes 153 horizontal east-west and 117 north-south grid cells,
and 15 vertical layers from the surface to 1.0E4 Pa (~ 12 km) Simulations were
performed on an IBM SP2 for the full year of 2001 with a 10-day spinup period.
Meteorology for the simulation was calculated with the Penn State/NCAR Mesoscale
Model (MM5) ("http://box.mmm.ucar.edu/mm5A. version 3.6.1. The simulation for 2001
meteorology consisted of 34 vertical layers, using ACM parameterization for the PBL,
Kain-Fritsch cumulus parameterization and 4DDA nudging (Alpine Geophysis, 2003).
2.2	Modeled HAPs and Chemical Mechanism
The toxic pollutants simulated represent the gas-phase HAPs that EPA has identified,
under the Urban Air Toxics Program, to pose the highest risk to the U.S. population. To
calculate concentrations of HAPs, we started with a Carbon Bond 4 (CB4) mechanism
(Gery et. al, 1989) with cloud chemistry and minor modifications (Gipson and Young,
1999). The new mechanism, CB4_TX1P, accounts for the additional production and
decay of air toxics, while retaining the full chemistry and radical cycling of the
mechanism. Toxic species were added to the mechanism either by 1) integrating species
production and decay into the full mechanism, or 2) calculating chemical decay at each
time step based on the current model conditions, but with no feedback to the mechanism.
In the first instance, the full chemical mechanism was modified by changing two
existing CB4 model species (FORM and ALD2) so that they simulate only formaldehyde
and acetaldehyde, and adding 7 model species, listed as having feedback in Table 1.
Including primary-only species quantifies the role of atmospheric chemical production on
the total concentrations, as opposed to atmospheric transport of direct emissions of these
species. Reactions which originally produced ALD2 were modified to produce either
acetaldehyde or higher aldehydes, depending on the reactants. Acrolein and 1,3-
butadiene were added to CB4 TX1P using reaction rates from Carter (2000) and product
distributions corresponding to those from mapping the species to CB4 model species
([2.0JOLE for 1,3-butadiene, [0.5]OLE+[1.0]ALD2 for acrolein), with product
coefficients scaled to the reaction rates. Production of acrolein from 1,3-butadiene
reactions were added based on the product yields identified in SAPRC99 (Carter, 2000).
Under the second criteria, sixteen species were added to the chemical mechanism
with no feedback to the chemical mechanism (Table 1). Because these species are present
in small quantities or are relatively non-reactive, they do not affect the overall radical
balance and chemistry, therefore their effect on the chemistry was not included. Their
concentrations were updated at each chemical time step based on the current radical and
environmental conditions. By including them as decay-only, however, the computational
requirements of the model were significantly reduced. These species were included in all
subsequent transport, advection, and deposition calculations of CMAQ.

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CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN THE U.S.	3
Table 1. Species added to CB4, with and without feedback to chemistry calculations
Species
Feedback
Reactions
Definition
Formaldehyde
Yes
Photolysis, OH, NO3, O
Formaldehyde
Form-surrogate
Yes
Photolysis, OH, NO3,0
Species which are not formaldehyde but
are mapped in CB4 as formaldehyde
Prim, formaldehyde
Yes
Photolysis, OH, NO3,0
Formaldehyde from direct emissions only
Acetaldehyde
Yes
Photolysis, OH, NO3,0
Acetaldehyde plus internal olefins that
react immediately to form acetaldehyde
Higher aldehydes
Yes
Photolysis, OH, NO3, 0
Aldehydes with more than 2 carbons
Prim, acetaldehyde
Yes
Photolysis, OH, NO3,0
Acetaldehyde from direct emissions only
Acrolein
Yes
Photolysis, OH, O3, NO3,0
Acrolein
Prim. Acrolein
Yes
Photolysis, OH, 03,N03,0
Acrolein from direct emissions only
1,3-butadiene
Yes
oh,no3, 03,0
1,3-butadiene from direct emissions only
Naphthalene
No
OH, 03, N02, NO3

1,3-dichloropropene
No
OH, 03

Quinoline
No
OH, 03, NO,

Vinyl chloride
No
OH,N03

Acrylonitrile
No
OH, 03, N03,

Trichloroethylene
No
OH

Benzene
No
OH

1,2-dichloropropane
No
OH

Ethylene oxide
No
OH

1,2-dibromoethane
No
OH

1,2-dichloroethane
No
OH

Tetrachloroethylene
No
OH

Carbon tetrachloride
No
OH

Dichloromethane
No
OH

1,1,2,2-
tetrachloroethane
No
OH

Chloroform
No
OH

2.4 Emissions
The simulation included hourly emissions of all relevant organic and inorganic
species. Emissions of HAPs in Table 1 were from the 1999 National Emission Inventory
(NEI) v3 (www.epa.gov/ttn/chief/net/index.html.) Other emissions were from the 1999
NEI v2. The 1999 inventory was chosen because it was the best inventory available at the
time of simulation, and the differences between 1999 and 2001 were not large. Biogenic
VOC emissions were fromBEIS v3.11 (www.epa.gov/asmdnerl/biogen.html). Emissions
were integrated and processed using the SMOKE processing software.
3. RESULTS AND DISCUSSION
3.1 Concentration Distributions
The resulting annual concentrations of formaldehyde at the surface are displayed in
Figure 1. One noticeable characteristic of this figure is the area of higher concentrations
in the Southeast. Formaldehyde is emitted directly as well as produced in the atmosphere

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D.J. Luecken and W.T. Hutzell
via chemical reaction with almost every other VOC in the atmosphere. Formaldehyde is
higher in summer than in winter, but the summer to winter ratio varies across the U.S.,
with highest values in the Midwest (7-10), slightly lower values in the Northeast (5-7) and
lowest values in the West {< 4).
Figures 2 and 3 display the fraction of total formaldehyde resulting from atmospheric
production during winter (Dec., Jan.. Feb.) and summer (June, July. Aug.). In hoth
seasons, over half the total formaldehyde is due to production in the atmosphere, but the
fraction is higher in summer than in winter. The importance of atmospheric production
varies across the domain and by season. In summer, higher photolysis rates, temperatures
and biogenic emissions contribute to the observed high formaldehyde concentrations.
Acetaldehyde concentrations show similar patterns and behavior to formaldehyde.
u JiM t
1
Figure 1. Concentration of total formaldehyde. Annual average, ng/W
Figure 2. Fraction of total formaldehyde due to atmospheric formation in winter. Three-month a\erages.

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( <>\< ENTRATIONS OF TOXIC AIR POLL1TAJMTS IM HE I .S.
5
Figure 3. Fraction of total formaldehyde due to atmospheric formation in summer. Three-month averages,
Annual benzene concentrations are presented in Figure 4. Benzene behaves
differently from formaldehyde because it is less reactive (half life of about 6 days in
summer, vs. 2 hours for formaldehyde) and is not produced in the atmosphere. The
concentration patterns reflect the distribution of emissions. Benzene in summer is less
than half of its winter concentrations over most of the U.S. The major loss process for
atmospheric benzene is reaction with the OH radical, which is lower in winter. Other
factors, such as increased emissions, may also increase winter benzene concentrations.
Figure 4. Concentration of total benzene. Annual average, |j.g/nr
Acrolein distributions are similar to benzene, but acrolein has slightly different
sources as well as competition between atmospheric production (from 1,3-butadiene) and
decay. Figure 5 shows that atmospheric production accounts for about 30-40% of the
total acrolein concentrations, although this varies spatially and temporally.

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D.J. Luecken and W.T. Hutzell
Figure 5. Fraction of Soial acrolein due u> atmospheric formation. Annual averages.
3.2 Comparison of Modeled to Observed Concentrations
We compared model results with HAP concentrations measured in the U.S. in 2001.
Our primary source of observational data was 35 monitors at 8 cities from the Air Toxics
Pilot Study (Battelle. 2003), supplemented with 11 monitors from the Urban Air Toxics
Monitoring Program (Eastern Research Group, 2002). Comparisons between point
measurements made by monitors and volume-average concentrations from grid models
such as CMAQ are difficult to interpret because there is a high degree of environmental
variability within the 1296 km2 area represented by one model cell. To compensate for
short-term variability, we focus on monthly-averaged values. Figure 6 displays scatter
plots of observed vs. modeled concentrations for formaldehyde and benzene.
O .18 monitors. 55 7 monthly maisuremeni:
• femcatiton. 55 ma»;ui-miwn at Grand Junction CO,
St Lou MO. Salt Lake City UT. N«w Brunswick N1.
KtVtfFcugeMI
Observed con: (yg/m3)	Observed cone (jjg/ia3)
J < iiuauiu•, wo iii< Hiuuy iiiniiurninm.
13 monitors. 91 maisyrrmaift at Grand Juntflcn Co,
S*it Lake Cay UT.Hiomix AZ.4 Musuapp
Yellow ?r«gh! M/
O
o
•
•	a
o •
Figure 6. Companion of observations with model predictions of (a.) formaldehyde and (b.) ben/ene. Monthly
averaged concentrations (ng/m1) for all months reporting data. The 1:1, 1:2 and 2:! lines are also shown.

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CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN THE U.S.
7
The model tends to slightly underpredict the formaldehyde measurements, especially
at the highest measured values. Overall, about 56% of the modeled values are within a
factor of two of the observations. However, the model does a much better job in the
spring and summer, with 72% and 62% of the predictions matching within a factor of 2,
versus 43% and 47% in the fall and winter. Greater dependence of formaldehyde
concentrations on atmospheric production in the spring and summer may be a factor for
the better model performance in the warmer months. Differences in meteorological model
performance in the warmer months may also play a role. The majority of monitors that
are severely underpredicted by the model are located at the St. Louis, MO, Salt Lake City,
UT, and Grand Junction, CO sites. There can be large differences in measurements
between multiple monitors sited in the same city, and the model predicts some of these
monitors well and others poorly (such as the River Rouge monitor in Detroit). Overall, the
relative bias is -0.47, although this varies among the states, from +0.48 to -0.82, with the
larger biases at the UT and CO sites.
CMAQ also tends to underpredict benzene concentrations, with the greatest
differences occurring at the monitors in Salt Lake City, UT and Grand Junction, CO, at all
four Mississippi sites and at the Yellow Freight monitor in Detroit. Overall, 60% of the
model predictions fall within a factor of 2, with slightly better prediction in spring and
summer (67% and 62%) versus fall and winter (54% and 48%). The overall relative bias
is -0.54, with individual state bias ranging from +0.48 to -0.95.
4. SUMMARY
The CMAQ model has been adapted to model concentrations of air toxics across the
continental U.S. for the year of 2001. A large portion of the modeled values are within a
factor of 2 of the observations.
Formaldehyde concentrations across the continental U.S. are largely due to
production in the atmosphere from other VOCs. While direct emissions of formaldehyde
play a role, especially in urban areas in winter, their influence is generally smaller than
atmospheric production. This has implications for the development of strategies to
control toxic concentrations of formaldehyde - control efforts must identify the
contributing VOCs, whether toxic or not. Isoprene emitted from biogenic sources can be
a major source of formaldehyde, which complicates control efforts. Formaldehyde is
approximately 5 times larger in summer than winter months, due to enhanced formation
rates, increased emissions of biogenic VOCs and increased volatilization of organics.
Benzene concentration distributions are influenced primarily by direct emissions of
benzene, because there is no gas phase production. It is critical to obtain accurate and
complete emission inventories in order to predict benzene concentrations and test the
results of control strategies. High density source areas of benzene, which result in "hot
spots" of concentration, are not predicted well by the model, which distributes emissions
uniformly within a grid cell. The role of OH in benzene decay, and the substantial diurnal
and seasonal variation in OH concentrations indicate that accurately accounting for
atmospheric OH is essential for benzene predictions. Concentrations are larger in winter
than summer largely due to increased OH in summer.
Acrolein concentrations have a significant secondary contribution, but the majority of
acrolein is from direct emissions. Acrolein is modulated by OH concentrations in two

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D.J. Luecken and W.T. Hutzell
ways: it is lost through chemical reaction, but it is produced through reaction of OH with
1,3-butadiene. A complete description of OH radical concentrations is also necessary in
order to accurately predict atmospheric acrolein concentrations.
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.
5. REFERENCES
Carter, W.P.L., 2000, Documentation of the SAPRC-99 Chemical Mechanism for VOC Reactivity Assessment.
Final Report to California Air Resources Board Contract No. 92-329, and 95-308. May, 2000. Available
at http://pah.cert.ucr.edU/~carter/absts.htm#saprc99
Byun, D.W. and Ching, J.K.S. (eds), 1999, Science Algorithms of the EPA Models-3 Community Multiscale
Air Quality (CMAQ) Modeling System. EPA-600/R-99/030, U.S. Environmental Protection Agency,
Research Triangle Park, NC.
Byun, D. and Schere, K.L., 2004, Review of the governing equations, computational algorithms, and other
components of the Models-3 Community Multiscale Air Quality (CMAQ) Model. Submitted to Applied
Mechanics Reviews.
Battelle Memorial Institute and Sonoma Technology, Inc., 2003. Phase II: Air Toxics Monitoring Data:
Analyses and Network Design Recommendations. Final report prepared for Lake Michigan Air Directors
Consortium, December 19,2003. Available from http://www.ladco.org/toxics.html.
Eastern Research Group, 2002. 2001 Urban Air Toxics Monitoring Project (UATMP). EPA 454/R-02-010.
Final report prepared for EPA (OAQPS) under contract number 68-D99007, October, 2002.
Gery, M.W., Whitten, G.Z., Killus, J.P., and Dodge, M.C., 1989, A photochemical kinetics mechanism for
urban and regional scale computer modeling, J. Geophys. Res. 94:12925-12956.
Gipson, G.L. and Young, J.O., 1999, Gas-phase chemistry, in: Science Algorithms of the EPA Models-3
Community Multiscale Air Quality (CMAQ) Modeling System, Byun, D.W. and J.K.S. Ching (eds), EPA-
600/R-99/030, U.S. Environmental Protection Agency, Research Triangle Park, NC, pp.8-1 to 8-99.
McNally, D., 2003, Annual Application of MM5 for Calendar Year 2001. Report to U.S. EPA by Alpine
Geophysis, Arvada, CO, March 31,2003.
Rosenbaum, A.S., Axelrad, D.A., Woodruff T.J., Wei, Y.H, Ligocki, M.P. and Cohen, J.P., 1999, National
estimates of outdoor air toxics concentrations, J. Air Waste Manage. Assoc. 49: 1138-1152.

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TECHNICAL REPORT DATA
1. Report No.
2.
4. Title and Subtitle
Concentrations of toxic air pollutants in the U.S. simulated by an air
quality model
5. Report Date
8/04/04
6. Performing Organization Code
7. Author(s)
Deborah J. Luecken and William Hutzell, EPA, Research Triangle
Park, NC
8. Performing Organization
Report No.
9. Performing Organization Name and Address
Atmospheric Modeling Division, NERL, ORD,EPA
10. Program Element No.
PRC 106FB9A
11. Contract/Grant No.
12. Sponsoring Agency Name and Address
Atmospheric Modeling Division, NERL, ORD,EPA
13. Type of Report and Period
Covered
14. Sponsoring Agency Code
15. Supplementary Notes
16. Abstract
This report describes the development of a version of CMAQ, an atmospheric air quality model, that
can simulate the concentrations of toxic air pollutants over the large spatial and temporal scales
required by human exposure models in the National Air Toxics Assessment. In this first application,
we are predicting the concentrations of 20 gas phase HAPs, over the continental U.S., for the entire
period of 2001. We describe the development and testing of the chemical mechanism for these
species, the incorporation of chemical and physical processes for these additional species, analysis of
the model results and a comparison with observed data.
17. KEY WORDS AND DOCUMENT ANALYSIS
A. Descriptors
atmospheric modeling, chemistry,HAPs
B. Identifiers / Open Ended
Terms
C. COSATI

18. Distribution Statement
19. Security Class (This
Report)
21. No. of Pages

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