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Appendix A
PROTOCOL DOCUMENT FOR URBAN AIRSHED AND
EKMA MODELING IN THE NEW YORK
METROPOLITAN AREA
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Final Report
PROTOCOL DOCUMENT FOR URBAN AIRSHED AND
EKMA MODELING IN THE NEW YORK
METROPOLITAN AREA
SYSAPP-88/149
September 1988
Prepared for
Mr. 3ohn Chamberlin
U.S. Environmental Protection Agency
Office of Policy Planning and Evaluation
Washington, DC 20460
and
Mr. Richard Scheffe
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
Prepared by
Systems Applications, Inc.
101 Lucas Valley Road
San Rafael, CA 94903
(415M72-4011
[)95 10 88 1 36rl
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1 INTRODUCTION
BACKGROUND
Four offices of the U.S. Environmental Protection Agency are involved in a joint
EPA-sponsored research study to investigate urban ozone air quality in a number of
U.S. cities. The offices involved are the following: Office of Air Quality Planning
and Standards (OAQPS), Office of Research and Development (ORD), Office of
Mobile Sources (QMS), and the Office of Policy, Planning and Evaluation (OPPE).
The urban areas to be studied include New York, St. Louis, Philadelphia, Dallas, and
Atlanta. A photochemical modeling analysis will be conducted in each of these urban
areas. This protocol addresses the New York application in particular.
Over 60 urban areas in the United States have failed to meet the legislated deadline
(31 December 1987) for ozone attainment. Possible reasons for this include one or
more of the following: the failure to actually reduce emissions or enforce emission
control requirements, the underestimation of actual urban hydrocarbon emissions,
and/or reliance on overly simplistic modeling approaches for calculating emission
control requirements. In the past, many air quality planners have relied on the
EKMA procedure (Empirical Kinetics Modeling Approach) to provide control
requirements for ozone attainment purposes. The EKMA procedure uses a trajectory
model (OZIPM) to simulate ozone formation of an observed design value concentra-
tion at a downwind monitor. An ozone isopleth diagram is created (from multiple
simulations) that depicts ozone concentrations as a function of initial NOX and VOC
concentration. The diagram can be used to equate emission control requirements to
the required percentage change between the observed ozone design value isopleth
and the isopleth of the National Ambient Air Quality Standard (NAAQS) (0.12 ppm).
An approach to estimating the effectiveness of alternative ozone attainment strate-
gies uses grid models such as the Urban Airshed Model (UAM). The UAM numerically
simulates the effects of emissions, interurban transport of ozone and precursors,
advection, diffusion, chemistry, and surface removal processes on pollutant concen-
trations in a three-dimensional grid covering an urban area. The UAM has been
applied in a number of urban areas across the United States, Europe, and the Far
East but there has been a reluctance by some air quality planners to use the model in
other urban areas mainly because of the time and costs involved in collecting input
data and undertaking extensive performance evaluations. However, depending on the
complexity of the ozone problem of the urban area and the particular needs of the
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air quality planners, extensive data bases and model evaluations may not be neces-
sary for an application of UAM. Indeed, no other air quality model currently in use is
subject to this level of performance evaluation. Moreover, even a "simplified" or
less stringent application of UAM appears desirable because it incorporates a reason-
ably complete mathematical treatment of the physical and chemical processes
believed to govern ozone formation. Furthermore, because this treatment appears to
be capable of reliably reproducing peak ozone concentrations and ozone concentra-
tions under episode conditions, the UAM provides more useful air quality planning
information than does EKMA (Seinfeld, 1988; Burton, 1988). As one aspect of this
study, the application of UAM will follow the simplified approach for the five urban
areas to demonstrate and test the utility of such an approach for air quality planning
purposes and future applications in other urban areas.
In recent years, air quality regulators have found it increasingly difficult to identify
additional urban hydrocarbon emissions that can be controlled in an effort to reduce
ozone concentrations. Yet at the same time there has been interest in using renew-
able fuels such as ethanol, which increase the evaporative emissions from light duty
vehicles while reducing exhaust CO emissions. Automobiles can be operated without
modification using 10 percent ethanol blended into gasoline. Substantial utilization
of ethanol can reduce the need for imported oil, the trade deficit, and farm sub-
sidies, but concern over increased evaporative emissions has hindered its widespread
use, especially in nonattainment areas. A recent EKMA modeling study of ethanol-
blended gasoline in seven urban areas showed a near balance in ozone increases due
to increased evaporative volatile organic compound (VOC) emissions and ozone
decreases from reduced exhaust emissions of carbon monoxide (CO). When the
chemistry of the evaporative emissions was explicitly treated in the model, the .
results always showed a net reduction in ozone associated with the use of ethanol
blends (Whitten, 1988). The results of this study have been questioned by the EPA
(Emison, 1988).
Because there is considerable interest nationwide in the potential benefits from the
expanded use of ethanol as an automotive fuel, more studies are needed to support or
refute the findings of the initial EKMA study. Such studies will provide guidance for
other urban areas. The current effort will use the Urban Airshed Model and EKMA
to examine the effects of using ethanol fuels in the five urban areas. A comparison
of results will be performed to test the reliability of EKMA for such evaluations. In
addition to the ethanol emission sensitivity work, the effects of VOC reactivity in
control strategy evaluation will be examined, and future year control strategy simu-
lations will be performed for the five urban areas.
The version of the UAM used in this project (UAM CBM-IV) contains several
improvements: (1) a new chemical mechanism of ozone formation that is further
extended here to treat ethanol and methanol explicitly; (2) a new numerical integra-
tion scheme for horizontal advection and transport; and (3) revised estimates of dry
deposition.
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STUDY OBJECTIVES
The five key objectives to be accomplished in the overall 5-city study are as follows:
1. Demonstrate the simplified, limited-data application of UAM for air
quality planning;
2. Determine the effects of Reid vapor pressure (RVP) and ethanol-blended
gasoline on urban ozone concentrations in a number of urban areas, and
compare UAM results with those obtained with EKMA;
3. Investigate and clarify the effects of VOC reactivity potential in emis-
sion control strategy evaluation;
4. Perform SIP control strategy simulations with UAM and EKMA for air
quality planning and comparison of the two modeling approaches (this will
be performed by the New York Department of Environmental Conserva-
tion (NYDEC) after acquisition of the modeling data base).
5. Transfer the UAM modeling data bases and application technology to the
5 states and EPA.
PURPOSE OF THE STUDY PROTOCOL
This protocol is intended to serve as the basis for the performance and successful
completion of a photochemical modeling analysis of the New York metropolitan area
(separate protocols will be prepared for each of the 5 urban areas in the overall
study). The purpose of this protocol is to describe the methodologies to be followed
throughout the study. It should be viewed as a set of general guidelines that provide
focus, consistency, and a basis for consensus for all parties involved in the study. It
will be reviewed and approved by all participants at the beginning of the study.
At this time, some portions of the modeling analysis have not been finalized in this
document (e.g., the specific emission sensitivity scenarios). For those items that
have not been finalized, we provide lists of options that may be followed. For some
items, it will be up to the study participants to choose from the list of options as the
study evolves.
OVERVIEW OF THE STUDY
The ozone air quality study in the New York metropolitan area comprises the follow-
ing tasks:
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1. Prepare a protocol document (this document) that describes the back-
ground, purpose, and objectives of the study, and the procedures to be
followed in the remainder of the study. A draft protocol will be prepared
and sent to all participants for consensus and approval before the bulk of
the technical work is initiated.
2. Prepare future base year and ethanol-use sensitivity inventories for the
application of UAM for New York that will use the latest version of the
model containing the Carbon-Bond IV chemical mechanism. (Because of
time constraints, an existing episode created by the state of New York in
the OMNYMAP [Oxidant Modeling in the New York Metropolitan Area
Project] study will be used.) The future year inventories will be prepared
for 1995 and will be projected from the existing 1985 NAPAP inventory.
3. Perform an EKMA analysis for the New York area, following the 1987
EPA modeling guidelines, using the future year base case and ethanol-use
sensitivity inventories.
4. Perform an application of UAM for the future year base case and etha-
nol-use scenarios. Examine the results and compare with those obtained
in the EKMA analysis.
5. Prepare an interim report that will summarize the ethanol sensitivity
studies for EKMA and UAM, and provide an overview of the current
understanding of the factors that influence the effectiveness of precursor
control, such as VOC reactivity, NOX emissions character, timing, and
spatial emission source distribution.
6. Deliver and install a compiled copy of the CBM-IV version of UAM, and
all modeling input files used in the UAM application on the State of New
York's computer system. Provide copies of these input files to the
OAQPS Source Receptor Analysis Branch.
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2 UAM MODELING METHODOLOGY
This section of the protocol provides details of the Urban Airshed Model (UAM)
application in the New York area including input preparation procedures, base case
simulations, and preparation of future year emission scenario inventories. The
results of these simulations will be compared to the results of the EKMA modeling
described in Section 3 of this protocol.
UAM INPUT PREPARATION PROCEDURES
Time constraints do not permit identification of ozone episodes or development of
additional modeling data bases for this project. Instead, an ozone episode simulated
in the original OMNYMAP study by NYDEC (Rao, 1987) will be used in this study.
This episode (8 August 1980) was simulated from 0400 to 2000 LST. Because it is
important in any photochemical modeling application that initial conditions do not
greatly influence the peak calculated concentration, the simulations performed as
part of this project should begin on 7 August. A two-day simulation for the New
York modeling region will also allow investigation into the effects of slower reacting
hydrocarbon species, such as those produced by ethanol blended fuels, on peak ozone
concentrations. Inputs will be created for the hours preceding 0400 LST on 8 August
and 7 August.
The latest version of the UAM containing the Carbon-Bond IV (CBM-IV) chemical
mechanism (Gery et al., 1988) will be applied in this study. To ensure that the
modeling data base for 8 August received from NYDEC has been properly transferred
and converted to our in-house computer system, the base case simulation performed
by NYDEC will be re-run using the Carbon-Bond II version of UAM. All subsequent
modeling will involve the CBM-IV version of UAM.
UAM Modeling Grid Specification
The modeling will be performed on the original OMNYMAP (Rao, 1987) modeling
grid, which consists of 31 by 25 grid cells with a horizontal dimension of 8 km, cover-
ing an area 248 by 200 km. The location of this grid and its relation to other north-
eastern states is presented in Figure 2-1. It covers parts of New Jersey, New York,
and Connecticut. The grid is located in UTM zone 18 with the origin set at
520,000 m Easting and 4,460,000 m Northing.
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New York
UAM
modeling region
FIGURE 2-1. Geographical location of the New York metropolitan area
UAM modeling region (intrastate boundaries denote AQCR's).
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The original vertical structure of the OMNYMAP study contained 4 vertical cells
that were constrained to 3 below and 1 above the hourly mixing height. Vertical
layers above the mixing height that are allowed to become very thick during certain
simulation hours may result in inadequate vertical resolution. Under certain condi-
tions, especially during nighttime hours when mixing heights are low, pollutants from
large point sources that are emitted aloft may be artificially dispersed in such thick
layers. Also, with thick layers, the wind speed and direction, and vertical and hori-
zontal shear above the mixing height may not be appropriately resolved. To appro-
priately resolve the vertical structure, modeling with as many as 8 vertical layers
might be desirable but might also be computationally impractical. To provide a
balance between practicality and appropriate vertical resolution, we recommend a
new vertical grid structure consisting of 5 vertical cells, with 2 below and 3 above
the hourly mixing height. The heights of the vertical layers will vary in thickness
spatially and temporally depending on the hourly mixing height field. The minimum
height of the lower cells is to be 50 m, and the maximum height of the upper cells,
150m.
The following 13 input files are required for UAM modeling analyses:
DIFFBREAK
REGIONTOP
.WIND
METSCALARS
AIRQUALITY
BOUNDARY
This file contains the daytime mixing height or nighttime inversion
height for each column of cells at the beginning and end of each
hour of the simulation.
This file contains the height of each column of cells at the begin-
ning and end of each hour of the simulation. If this height is
greater than the mixing height, the cell or cells above the mixing
height are assumed to be within an inversion.
This file contains the x and y components of the wind velocity for
every grid cell for each hour of the simulation. Also the maximum
wind speed for the entire grid and average wind speeds at each
boundary for each hour are included in this file.
This file contains the hourly values of the meteorological
parameters that do not vary spatially. These scalars are the NC^
photolysis rate constant, the concentration of water vapor, the
temperature gradient above and below the inversion base, the
atmospheric pressure, and the exposure class.
This file contains the initial concentrations of each species for
each grid cell at the start of the simulation.
This file contains the location of the modeling region boundaries.
This file also contains the concentration of each species that is
used as the boundary condition along each boundary segment at
each vertical level.
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TOPCONC This file contains the concentration of each species for the area
above the modeling region. These concentrations are the boundary
conditions for vertical integration.
TEMPERATURE This file contains the hourly temperature for each surface layer
grid cell.
EMISSIONS
PTSOURCE
TERRAIN
CHEMPARAM
SIMCONTROL
This file contains the ground-level emissions of NO, NO2, seven
carbon bond categories, and CO for each grid square for each hour
of the simulation.
This file contains the point source information, including the stack
height, temperature and flow rate, the plume rise, the grid cell
into which the emissions are emitted, and the emissions rates for
NO, NO2» seven carbon bond categories, and CO for each point
source for each hour.
This file contains the value of the surface roughness and deposition
factor for each grid square.
This file contains information regarding the chemical species to be
simulated including reaction rate constants, upper and lower
bounds, activation energy, and reference temperature.
This file contains the simulation control information such as the
time of the simulation, file option information, default informa-
tion, and information on integration and chemistry time steps.
The majority of the input files used in the previous OMNYMAP application of UAM
for 8 August will be used "as is" in this application. However, certain of the files
(e.g., WINDS) will be recreated using new techniques, and one new file (TERRAIN)
will be added. In the original OMNYMAP application, spatially constant default
deposition and surface roughness parameters were used in place of spatially varying
parameters. The new TERRAIN file will contain updated spatially varying
parameters based on land use data. Because of the recommended changes in the ver-
tical layer structure for the new UAM modeling, those files affected by this change
will also be recreated.
The recommended procedures for preparing each of the above input files for the New
York application are summarized in the following subsections.
DIFFBREAK - The upper air sounding data collected at the John F. Kennedy airport
will be examined to provide estimates of daytime hourly mixing heights for
those hours preceding 0400 LST. The methodology followed in arriving at
spatially constant, temporally varying mixing heights for 7 August and the
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nighttime hours of 8 August will be the same as that used in the original
OMNYMAP work (i.e., following procedures developed by Benkley and Schul-
man, 1979; Garret, 1987).
REGIONTOP - The original OMNYMAP application used a temporally varying height
for the top of the region ranging from 1000 m to 1500 m. During the nighttime
hours, with a 1000 m region top, emissions from large point sources may have
plume rises above this level and will not be emitted into the modeling region.
Lowering the region top during the evening hours of 7 August causes artificial
dispersion of pollutants out of the top level of the modeling region that are lost
from the modeling domain. To avoid these potential problems, we recommend
setting the top of the region at a fixed level of 1500 m for all hours of the
simulation.
WIND - The wind fields created for the original OMNYMAP application were tem-
porally varying, spatially constant, based on observed surface and upper air
data. In the new application, we are recommending using a wind model along
with the measured data to derive new wind fields that are both temporally and
spatially varying. Hourly wind speed and direction data will be used along with
the Hybrid Diagnostic Wind Model (HDWM) (Douglas and Kessier, 1988; Morris
et al., 1987) to create new three-dimensional modeling wind fields.
METSCALARS - Meteorological data collected in the modeling region will be used to
complete this file for those hours preceding 0400 LST on 8 August. The
spatially constant, temporally varying parameters include estimates for N©2
photolysis rate, water concentration, exposure class, atmospheric pressure, and
temperature gradients above and below the mixing height.
AIRQUALITY - The species initial concentration field, the AIRQUALITY file, will be
created by using air quality data collected at monitors in the modeling
domain. The values will correspond to the specific initial hour of the simula-
tion, which is not known at this time. The upper-layer initial field will use
values specified in the TOPCONC file. The AIRQUALITY file will be updated
with the new CBM-IV species.
BOUNDARY - Hourly boundary conditions will be specified based on observed air
quality data at monitors both near and outside the inflow boundaries. The flow
regime of 7-8 August is dominated by southwest transport; therefore, the criti-
cal inflow boundaries will be the southern and western boundaries. Boundary
conditions above the mixing height will use the values specified in the TOP-
CONC file. The new CBM-IV species will be added to the BOUNDARY file for
the CBM-IV simulations.
TOPCONC - The original concentrations specified at the top of the modeling region
were based on air quality data derived from aircraft spirals. This data will be
examined to determine whether the values specified for 0400 LST can be used
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for the preceding hours for 8 August and 7 August. CBM-IV species will be
added to this file before the UAM CBM-IV is exercised.
TEMPERATURE - The TEMPERATURE file contains gridded hourly surface tem-
perature information for the modeling region. This file is used in the UAM for
those chemical reactions that are temperature-dependent. Gridded tempera-
ture fields for hours preceding 0400 LST on 8 August will be derived from
observed data collected at National Weather Service and other local air quality
monitoring network sites. The Poisson interpolation method is used in the UAM
system for processing temperature observations. The Poisson method is a dis-
tance-weighted interpolation scheme that is most accurate when a reasonable
estimate is made of the initial field. A set of "pseudo" stations may have to be
used at the edges of the domain or where there are data gaps (e.g., over the
ocean) in the modeling region to ensure a good initial estimate.
EMISSIONS - The original inventory used in the OMNYMAP exercise containing
information on the CBM-II species will be updated to correspond to a CBM-IV
inventory. This will be accomplished by splitting total aromatics (ARO) into
the new CBM-IV species toluene (TOL) and xylene (XYL), and splitting total
carbonyls (CARB) into the new CBM-IV species formaldehyde (FORM) and
other aldehydes (ALD2). The splitting factors for the new CBM-IV species will
be taken from the recently published EKMA guidelines for CBM-IV (Hogo and
Gery, 1988). This 1980 base year CBM-IV inventory is needed for a new 1980
CBM-IV base case simulation to ensure that the changes made to all of the
other input files have been correctly implemented. The methodology for creat-
ing the future year emission scenario inventories is presented in the next sec-
tion.
PTSOURCE - The CBM-II input file containing point source information will be up-
dated for the 1980 CBM-IV base case simulation following the procedure per-
formed for the low level emissions. Methodology for deriving the future year
base case and emission scenario point source files is presented in the next sec-
tion.
TERRAIN - This file will be added to the OMNYMAP modeling data base. It will
contain surface roughness and deposition information as a function of land use
(no terrain height information). The land use data for the OMNYMAP modeling
region will be derived from data obtained from the U.S. Geological Survey.
The deposition values as a function of land use are derived from studies per-
formed by the Argonne National Laboratory (Sheih et al., 1986). These values
are summarized in Table 2-1.
CHEMPARAM - The CHEMPARAM file contains information regarding (1) the
species to be modeled by the UAM; (2) upper and lower bounds on numerical
and steady-state calculations along with species "resistance" to dry deposition;
and (3) the rate constants for the photochemical reactions. Before the CBM-IV
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TABLE 2-1. Surface roughness and deposition factors
based on studies by Argonne National Laboratories.
Land Use Surface Roughness Deposition
Category (meters) Factor
Urban 3.00 0.2
Agricultural . 0.25 0.5
Range 0.05 0.4
Deciduous Forest 1.00 0.4
Coniferous Forest 1.00 0.3
including wetland
Mixed Forest 1.00 0.3
Water 0.0001 0.03
Barren land 0.002 0.2
Nonforest Wetlands 0.15 0.3
Mixed Agricultural 0.10 0.5
and range
Rocky (low shrubs) 0.10 0.3
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1980 base case simulation is performed, the CHEMPARAM file will be updated
to correspond to the new species simulated with the new mechanism.
S1MCONTROL - The SIMCONTROL file controls the actual simulation parameters of
the UAM run (i.e., simulation time period, minimum time steps, output time
intervals). At this time it is not known when the simulation will be initiated;
however, all other information contained in the file will not change from one
simulation to another.
Assessment of Model Performance for the Base Case
After the modeling inputs have been finalized and rendered consistent with UAM
CBM-IV requirements for the 1980 base case simulation, a new base case simulation
will be run. As noted, it is not certain at this time when the simulation will be
initiated; however, the simulation will be run to 2000 LSI on 8 August. Before using
the updated modeling data base in any future year emission scenario simulations, it is
essential that at least a limited assessment of model performance be undertaken,
even in this low-cost, simplified UAM application. The model's ability to predict the
level and spatial orientation of the observed ozone field will be assessed by compar-
ing the UAM-calculated concentrations with the measured data.
We will compute a limited set of model performance statistics that summarize error,
bias, and the model's ability to calculate the peak ozone concentration. In this appli-
cation, no specific performance criteria will be established, and no strict perform-
ance evaluation will be undertaken. However, if the modeling system shows very
poor performance, we may undertake one (or more as time allows) diagnostic simula-
tion^) to identify a range of alternatives for improving model performance. For
example, a diagnostic simulation may involve changes to the three-dimensional wind
field (within the range of the uncertainty of the data used to prepare the field) if
spatial alignment problems occur in the base case simulation. Future year emission
scenario simulations using the CBM-IV modeling data base will be performed only
after there is agreement from participating technical representatives that perform-
ance in the base case is adequate.
Future Year Emission Inventory Development
Improved Urban Airshed Model performance is achieved when emissions data in a
very specific and detailed format is available. UAM requires a spatially
disaggregated and temporally allocated emissions inventory. Performance is
improved if a chemically speciated emissions inventory is obtained, although
speciation could be achieved by using default speciation profiles, as is customarily
done with EKMA. Meeting these requirements often entails the collection of
additional emissions-related information such as population distribution and
industrial activity data.
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In this study we will be using the 1985 NAPAP (National Acid Precipitation Assess-
ment Program) Emissions Inventory as the base year from which all future year emis-
sion scenarios will be developed. The future year selected for use in this study is
1995. The 1985 NAPAP Emissions Inventory consists of annual county-wide area
source emissions (including mobile sources), and annual emissions for large point
sources along with stack parameters (i.e., stack height, diameter, flow rate, and
temperature). The county-wide area source emissions will be disaggregated onto the
gridded modeling domain using the gridded population distribution. Source categories
will be classified as related to the population distribution, inversely related to the
population distribution, or not related at all to population, and gridded accordingly.
The annual emission rates will be adjusted for each source category to summer
weekday emissions by using scaling factors based upon typical values of monthly
throughputs and weekday factors. Likewise, hourly variations in emissions will be
based upon typical diurnal activity levels for each source category.
The stationary source emissions for the 1995 scenario year will be projected from
1985 NAPAP emissions by utilizing growth factors by source category available from
an EPA-sponsored study (Pechan, 1988). Mobile source emissions will be prepared
using scaling factors provided by the EPA Office of Mobile Sources specifically for
each scenario to be analyzed.
Several emissions inventories will be used for the limited performance evaluation of
the UAM and assessment of the effects of alternative fuel use and SIP control
strategies. The following list describes each of the emission scenarios:
CBM-II 1980 case - the inventory used for the past UAM/CBM-II applications.
CBM-IV 1980 case - a modified version of the CBM-II met case for CBM-IV
species. This inventory will be used to verify that the UAM/CBM-IV is opera-
ting properly and predicts ozone patterns comparable to those predicted by the
UAM/CBM-II. This inventory is valid for 1980. The creation of this inventory
was described in the input preparation section above.
1985 NAPAP - gridding of 1985 NAPAP inventory for CBM-IV species, as is, to
the modeling domain.
1995 base case - this inventory is based on the 1985 NAPAP county inventory.
Stationary source emissions are projected to 1995 using growth factors from
Pechan (1988). Mobile source emissions will be based on values provided by
OMS reflecting fleet turnover and present fuel properties. The emission
scenarios will correspond to different assumptions in the mobile source emis-
sions.
1995 Emission Scenarios - these inventories will reflect changes in VOC, NOX,
and CO due to assumptions of future changes in mobile source emission rates
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such as changes in Reid vapor pressure (RVP) and use of ethanol-blended
fuels. For New York, EPA/OPPE has defined 6 separate emission scenarios as
follows:
Scenario //I - 1995 base case with mobile emissions at current RVP values
(11.5 psi) with running losses
Scenario #2 - 1995 base case with mobile emissions at low RVP values
(9.0 psi) with running losses
Scenario #3 - 1995 base case with 100 percent ethanol penetration* and
10 percent ethanol blend at low RVP (10.0 psi) plus 1 psi exemption with
running losses
Scenario #4 - 1995 base case with mobile emissions at current RVP values
(11.5 psi) without running losses
Scenario //5 - 1995 base case with 50 percent ethanol penetration at low
RVP (9.0 psi) plus 1 psi exemption with running losses
Scenario #6 - 1995 base case with current RVP and running losses using
alternative speciation methodology
Emission Scenario Simulations
On the basis of emission scenario options outlined in the previous section, a subset
will be chosen for UAM modeling. In addition to changes in the input emissions files,
the initial condition (AIRQUALITY) and boundary condition (BOUNDARY) files will
be changed to reflect general estimates of future year air quality. Estimates for
initial conditions will be changed (increased/decreased) to reflect changes in the
emission inventory for the New York metropolitan area from 1980 to 1995 based on
projected growth and anticipated future emission controls. To calculate a future
year estimate, the urban background estimate will first be subtracted from the
actual meteorological base year concentration for 1980. The resulting concentration
will be changed in proportion to changes in emissions. The background will then be
added to this concentration to arrive at a future year estimate. Similarly, on the
basis of emission changes in upwind areas (for this episode, New Jersey), the upwind
inflow boundary conditions will be changed to reflect forecasted changes in emissions
* In this context, "penetration" is defined as the change from one type of fuel to
another. A 50 percent ethanol penetration scenario is one in which 50 percent of
fuel used in vehicles is converted from gasoline to an ethanol-blended fuel.
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between 1980 and 1995. Only one set of future year initial and boundary conditions
will be selected and used for all modeling pertaining to a given future year. We will
not use multiple sets that reflect specific differences in emissions between
scenarios.
The results of the UAM simulations will be presented in the form of ozone difference
plots. These plots are created by subtracting the calculated ozone concentration of
the future year base case (for each grid cell, for each hour) from the concentration
obtained in the emission sensitivity simulations. This results in hourly isopleth maps
that show both the magnitude and spatial extent of differences in ozone concentra-
tions due to changes in emissions. Changes in calculated peak ozone will also be
summarized in tabular format.
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3 EKMA MODELING METHODOLOGY
BACKGROUND
A recent study used the simple photochemical modeling approach known as EKMA
(Empirical Kinetics Modeling Approach) to investigate the possible impacts on urban
ozone formation from the use of ethanol-blended gasoline fuels (Whitten, 1988). The
study addressed the comparative reactivities of the relevant ozone precursor emis-
sions affected by the use of ethanol blends. Atmospheric conditions were varied to
represent those found in seven cities. The key finding of the study was a near
balance between ozone increases from enhanced evaporative emissions of VOC and
ozone decreases from reduced exhaust emissions of CO. This was the first study to
consider mitigation of ozone VOC precursors through CO reductions. When the
chemistry of the individual evaporative emissions species was explicitly treated in
the model, the results always showed a net reduction in ozone associated with the
use of ethanol blends. However, the U.S. EPA recommends simplified treatment of
reactivity in the EKMA, whereby the reactivity of all VOC emissions species is
treated as being equal to the reactivity of overall average VOC. While this simpli-
fied treatment overestimates the reactivity of the increased evaporative emissions,
the EKMA modeling results indicated small net reductions in ozone formation from
the use of ethanol blends in some cases, and in others the simplified reactivity
assumption showed a small net increase in ozone. Although the existing EKMA
model can explicitly treat the chemistry of evaporative automotive emissions, the
simplified treatment of reactivity is more consistent with the overall simplified
philosophy embodied in regulatory applications of EKMA.
The negative or positive direction of the small ozone impacts derived from the
simplified treatment of VOC reactivity and the size of the ozone reductions derived
from the explicit chemical treatment of the affected emissions appear to depend on
the mobile-related fraction of total VOC and the ratio of CO emissions to VOC emis-
sions. Areas with low mobile-related VOC fractions and high CO-to-VOC ratios are
expected to show the largest net ozone reductions if ethanol fuels are used because,
under these conditions, the overall ambient increases in VOC will be smaller, and the
decreases in ambient CO concentrations will be larger. However, it is important to
increase the confidence in the preliminary EKMA analyses thus far carried out. Fur-
ther UAM and EKMA evaluations are thus warranted, and will be carried out as a
part of this study.
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The study by Whitten (1988) used EKMA episodes previously set up for 1982 SIP cal-
culations plus CO estimates based on the CO-to-VOC ratios in the NEDS data base.
Also, RVP changes and volatility increases due to ethanol blends were estimated
from a 1987 RVP impact study by the EPA. Since the release of the Whitten study,
new emissions guidelines for alternate fuels have been released by the EPA (29 Janu-
ary 1988). Therefore, new EKMA simulations, which use the new EPA guidelines for
alternate fuels, and are appropriate to 1995 projections in New York, are needed.
COMPARISON OF EKMA AND UAM
Some factors regarding changes in mobile-related emissions cannot be addressed with
the EKMA. These factors can be treated by UAM. For example, the diurnal timing
and location of evaporative emissions are not always equal to those of exhaust emis-
sions. The UAM is capable of treating cold-start, hot-soak, highway-cruising and
congested-traffic emissions separately depending on local data for hourly tempera-
tures, spatially resolved traffic counts, average speeds, and vehicle miles traveled.
Alternatively, EKMA uses constant grams per mile emissions based on data from
standard federal trip and mileage test procedures (FTP) and estimates of local auto-
mobile populations.
The principal differences between EKMA and UAM stem from the trajectory nature
of EKMA versus the grid nature of UAM. EKMA treats the atmospheric chemistry of
a single parcel of air as representative of one reaching an observed ozone maxi-
mum. The model simulation begins at 0800 hours with an initial loading of precur-
sors, and more emissions are added each hour on the basis of county-wide emission
averages. The UAM treats gridded points throughout the urban region (resolved both
horizontally and vertically) for a day or more preceding an ozone episode. Precur-
sors are emitted and move about within the gridded model region according to the
physical equations governing wind flow, dispersion, and surface deposition. The
secondary pollutants (such as ozone) are formed in both models on the basis of atmo-
spheric chemistry. Hence EKMA provides information at one point in time and space
on the basis of a few hours' highly averaged information, whereas UAM provides
information at all points in time and space on the basis of a day or more of highly
resolved information.
It is possible that the UAM will provide results that are significantly different from
those of the EKMA-based study because of UAM's ability to treat spatially varying
emissions. However, this discussion illustrates the vast differences in complexity
and sophistication between the EKMA and UAM models and the potential for some-
what different results.
PURPOSE OF ANALYSIS
The purpose of using EKMA to simulate the same scenarios as those simulated by
UAM is threefold. The first is to use the UAM to support or refute the EKMA results
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obtained in the previous study on the effects of ethanol fuel use on urban ozone con-
centrations in seven U.S. cities (Whitten, 1988).
The second purpose of the EKMA simulations is to estimate the uncertainties invol-
ved in using a trajectory model like EKMA to examine the effects of different emis-
sion scenarios such as alternative fuel use. Even though the changes in the observed
maximum ozone may be in agreement for both models, the different reactivities,
source configurations, and three-dimensional structure of the UAM may result in the
UAM predicting new hot spots of high ozone concentrations occurring outside of the
EKMA trajectory.
The third purpose of the EKMA simulations is to study the effects of reactivity of
VOC emissions on ozone formation. EKMA's use of the default and actual reactivity
of the emission scenarios will provide insight into the uncertainties produced by
these assumptions.
EKMA MODELING METHODOLOGY
Two sets of EKMA calculations will be made for each UAM scenario. The first will
be performed in strict accordance with EPA guidelines for using EKMA for post-1987
State Implementation Plans (SIPs) (Hogo and Gery, 1988). The UAM modeling period
will be viewed as a "design day" in setting up the OZIPM simulation. However, in
keeping with EKMA guidance, none of the UAM inputs will be used for creating the
EKMA inputs. County total emissions of NOX, VOC, CO, and other species (correc-
ted for season and MOBILE 3.9) will be used for each emissions scenario. The VOC
emissions will be speciated using the default EKMA reactivity. For the ethanol-
blended fuel cases, these emissions will have higher total VOC and lower CO emis-
sions and will not account for the lower reactivity of ethanol-blended fuels.
The second set of EKMA simulations will be performed in the same manner as the
first set, but the county VOC emissions will be speciated according to the source-
specific speciation profiles for the emission scenario in question. Thus for the etha-
nol fuel cases, there will be a higher VOC emissions rate, but these simulations will
take into account the lower reactivity of emissions from ethanol-blended fuels.
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References
Benkley, C. W., and L. L. Schulman. 1979. Estimating hourly mixing depths from
historical meteorological data. 3. Appl. Meteorol., 18:772.
Burton, C. S. 1988. Comments on "Ozone Air Quality Models." To be published in 3.
Air Pollut. Control Assoc.
Douglas, S., and R. Kessler. 1988. "User's Guide to the Diagnostic Wind Model.
Version 1.0." Systems Applications, Inc., San Rafael, California.
Emison, G. A. 1988. Memo to William G. Laxton, EPA-OAQPS. May 1988.
Garrett, A. 3. 1981. Comparison of observed mixed-layer depths to model estimates
using observed temperatures and wind and MUS forecasts. 3. Appl. Meteorol.,
20:1277.
Gery, M. W., G. Z. Whitten, and 3. P. Killus. 1988. "Development and Testing of the
CBM-IV for Urban and Regional Modeling." Systems Applications, Inc., San
Rafael, California (SYSAPP-88/002).
Hogo, H., and M. W. Gery. 1988. "Guidelines for Using OZIPM-4 with CBM-IV or
Optional Mechanisms, Volume 1: Description of the Ozone Isopleth Plotting
Package, Version 4." Systems Applications, Inc., San Rafael, California
(SYSAPP-88/001).
Morris, R. E., R. C. Kessler, S. G. Douglas, and K. R. Styles. 1987. "Rocky Mountain
Acid Deposition Model Assessment: Evaluation of Mesoscale Models for Use in
Complex Terrain." U.S. Environmental Protection Agency (EPA-600/3-87-013;
NTIS PB87-180584-AS).
Pechan, E. H., and Associates. 1988. "National Assessment of VOC, CO, and NOX
Emissions and Costs for Attainment of the Ozone and CO Standards."
Rao, S. T. 1987. "Application of the Urban Airshed Model to the New York Metro-
politan Area." Bureau of Air Research, Division of Air Resources, New York
State Department of Environmental Conservation, Albany, New York (CA No.
CX811945-01-0; EPA-450/4-87-011).
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Seinfeld, J. H. 1988. Ozone air quality models. A critical review. 3. Air Pollut.
Control Assoc., 38(5):616.
Sheih, B. F., N. L. Wesely, and C. J. Walcek. 1986. The Dry Deposition Module
for Regional Acid Deposition Models." Argonne National Laboratories
(DW89930060-01).
Whitten, G. Z. 1988. "Evaluation of the Impact of Ethanol/Gasoline Blends on Urban
Ozone Formation." Systems Applications, Inc., San Rafael, California (SYSAPP-
88/029.
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Appendix B
PROTOCOL DOCUMENT FOR URBAN AIRSHED
AND EKMA MODELING IN THE
ST. LOUIS METROPOLITAN AREA
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Final Report
PROTOCOL DOCUMENT FOR URBAN AIRSHED
AND EKMA MODELING IN THE
ST. LOUIS METROPOLITAN AREA
SYSAPP-88/150
September 1988
Prepared for
Mr. John Chamberlin
U.S. Environmental Protection Agency
Office of Policy Planning and Evaluation
Washington, DC 20460
and
Mr. Richard Scheffe
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
Prepared by
Systems Applications, Inc.
101 Lucas Valley Road
San Rafael, CA 94903
(415)472-4011
Q9510 88139rl
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INTRODUCTION
BACKGROUND
Four offices of the U.S. Environmental Protection Agency are involved in a joint
EPA-sponsored research study to investigate urban ozone air quality in a number of
U.S. cities. The offices involved are the following: Office of Air Quality Planning
and Standards (OAQPS), Office of Research and Development (ORD), Office of
Mobile Sources (OMS), and the Office of Policy, Planning and Evaluation (OPPE).
The urban areas to be studied include New York, St. Louis, Philadelphia, Dallas, and
Atlanta. A photochemical modeling analysis will be conducted in each of these urban
areas. This protocol addresses the St. Louis application in particular.
Over 60 urban areas in the United States have failed to meet the legislated deadline
(31 December 1987) for ozone attainment. Possible reasons for this include one or
more of the following: the failure to actually reduce emissions or enforce emission
control requirements, the underestimation of actual urban hydrocarbon emissions,
and/or reliance on overly simplistic modeling approaches for calculating emission
control requirements. In the past, many air quality planners have relied on the
EKMA procedure (Empirical Kinetics Modeling Approach) to provide control
requirements for ozone attainment purposes. The EKMA procedure uses a trajectory
model (OZIPM) to simulate ozone formation of an observed design value concentra-
tion at a downwind monitor. An ozone isopleth diagram is created (from multiple
simulations) that depicts ozone concentrations as a function of initial NOX and VOC
concentration. The diagram can be used to equate emission control requirements to
the required percentage change between the observed ozone design value isopleth
and the isopleth of the National Ambient Air Quality Standard (NAAQS) (0.12 ppm).
An approach to estimating the effectiveness of alternative ozone attainment strate-
gies uses grid models such as the Urban Airshed Model (UAM). The UAM numerically
simulates the effects of emissions, interurban transport of ozone and precursors,
advection, diffusion, chemistry, and surface removal processes on pollutant concen-
trations in a three-dimensional grid covering an urban area. The UAM has been
applied in a number of urban areas across the United States, Europe, and the Far
East, but some air quality planners have been reluctant to use the model in other
urban areas mainly because of the time and costs involved in collecting input data
and undertaking extensive performance evaluations. However, depending on the
complexity of the ozone problem of the urban area and the particular needs of
the air quality planners, extensive data bases and model evaluations may not be
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necessary for an application of UAM. Indeed, no other air quality model currently in
use is subject to this level of performance evaluation. Moreover, even a "simplified"
or less stringent application of UAM appears desirable because it incorporates a rea-
sonably complete mathematical treatment of the physical and chemical processes
believed to govern ozone formation. Furthermore, because this treatment appears to
be capable of reliably reproducing peak ozone concentrations and ozone concentra-
tions under episode conditions, the UAM provides more useful air quality planning
information than does EKMA (Seinfeld, 1988; Burton, 1988). As one aspect of this
study, the application of UAM will follow the simplified approach for the five urban
areas to demonstrate and test the utility of such an approach for air quality planning
purposes and future applications in other urban areas.
In recent years, air quality regulators have found it increasingly difficult to identify
additional urban hydrocarbon emissions that can be controlled in an effort to reduce
ozone concentrations. Yet at the same time there has been interest in using renew-
able fuels such as ethanol, which increase the evaporative emissions from light duty
vehicles while reducing exhaust CO emissions. Automobiles can be operated without
modification using 10 percent ethanol blended into gasoline. Substantial utilization
of ethanol can reduce the need for imported oil, the trade deficit, and farm sub-
sidies, but concern over increased evaporative emissions has hindered its widespread
use, especially in nonattainment areas. A recent EKMA modeling study of ethanol-
blended gasoline in seven urban areas showed a near balance in ozone increases due
to increased evaporative volatile organic compound (VOC) emissions and ozone
decreases from reduced exhaust emissions of carbon monoxide (CO). When the
chemistry of the evaporative emissions was explicitly treated in the model, the
results always showed a net reduction in ozone associated with the use of ethanol
blends (Whitten, 1988). The results of this study have been questioned recently by
the EPA (Emison, 1988).
Because there is considerable interest nationwide in the potential benefits from the
expanded use of ethanol as an automotive fuel, more studies are needed to support or
refute the findings of the initial EKMA study. Such studies will provide guidance for
other urban areas. The current effort will use the Urban Airshed Model and EKMA
to examine the effects of using ethanol fuels in the five urban areas. A comparison
of results will be performed to test the reliability of EKMA for such evaluations. In
addition to the ethanol emission sensitivity work, the effects of VOC reactivity in
control strategy evaluation will be examined, and future year control strategy simu-
lations will be performed for the five urban areas.
The version of the UAM used in this project (UAM CBM-IV) contains several
improvements: (1) a new chemical mechanism of ozone formation that is further
extended here to treat ethanol and methanol explicitly; (2) a new numerical integra-
tion scheme for horizontal advection and transport; and (3) revised estimates of dry
deposition.
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STUDY OBJECTIVES
The five key objectives to be accomplished in the overall 5-city study are as follows:
1. Demonstrate the simplified, limited-data application of UAM for air
quality planning;
2. Determine the effects of Reid vapor pressure (RVP) and ethanol blended
gasoline on urban ozone concentrations in a number of urban areas, and
compare UAM results with those obtained with EKMA;
3. Investigate and clarify the effects of VOC reactivity potential in emis-
sion control strategy evaluation;
4. Perform SIP control strategy simulations with UAM and EKMA for air
quality planning and comparison of the two modeling approaches;
5. Transfer the UAM modeling data bases and application technology to the
5 states and EPA.
PURPOSE OF THE STUDY PROTOCOL
This protocol is intended to serve as the basis for the performance and successful
completion of a photochemical modeling analysis of the St. Louis metropolitan area
(separate protocols will be prepared for each of the 5 urban areas in the overall
study). The purpose of this protocol is to describe the methodologies to be followed
throughout the study. It should be viewed as a set of general guidelines that provide
focus, consistency, and a basis for consensus for all parties involved in the study. It
will be reviewed and approved by all participants at the beginning of the study.
At this time, some portions of the modeling analysis have not been finalized in this
document (e.g., the specific emission sensitivity scenarios). For those items that
have not been finalized, we provide lists of options that may be followed. For some
items, it will be up to the study participants to choose from the list of options as the
study evolves.
OVERVIEW OF THE STUDY
The ozone air quality study in the St. Louis metropolitan area comprises the follow-
ing tasks:
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1. Prepare a protocol document (this document) that describes the back-
ground, purpose, and objectives of the study, and the procedures to be
followed in the remainder of the study. A draft protocol will be prepared
and sent to all participants for consensus and approval before the bulk of
the technical work is initiated.
2. Select a modeling episode from a set of four days simulated in a previous
application of UAM using data collected during the Regional Air Pollution
Study (RAPS) in 1975 and 1976.
3. Prepare future base year and ethanol-use sensitivity inventories for the
application of UAM for St. Louis that will use the latest version of the
model containing the Carbon-Bond IV chemical mechanism. The future
year inventories will be prepared for 1995 and will be projected from the
existing 1985 NAPAP inventory.
4. Perform an EKMA analysis for the St. Louis area, following the 1987 EPA
modeling guidelines, using the future year base case and ethanol-use
sensitivity inventories.
5. Perform an application of UAM for the future year base case and etha-
nol-use scenarios. Examine the results and compare with those obtained
in the EKMA analysis.
6. Prepare an interim report that will summarize the ethanol sensitivity
studies for EKMA and UAM, and provide an overview of the current
understanding of the factors that influence the effectiveness of precursor
control, such as VOC reactivity, NOX emissions character, timing, and
spatial emission source distribution.
7. Perform SIP control strategy simulations using both UAM and EKMA for
air quality planning and comparison of the two modeling approaches.
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2 UAM MODELING METHODOLOGY
This section of the protocol provides details of the Urban Airshed Model (UAM)
application in the St. Louis area including episode selection, input preparation
procedures, base case simulations, and preparation of future year emission scenario
inventories. The results of these simulations will be compared to the results of the
EKMA modeling described in Section 3 of this protocol.
EPISODE SELECTION
This section provides a summary of the procedures that will be used to select the
ozone episode for the CBM-IV UAM modeling. Time constraints do not permit
identification of new ozone episodes or development of additional modeling data
bases for this project. Instead, an ozone episode day will be chosen from a set of
episode days that were developed as part of the original St. Louis Ozone Modeling
Project (EPA, 1983). These days are the following:
Thursday, May 22, 1975
Saturday, July 26, 1975
Tuesday, July 13, 1976
Friday, October 1, 1976
The following referenced reports will be used to perform the episode selection:
1. Regional Air Monitoring System Flow and Procedures Manual (Rockwell,
1977).
2. Final Evaluation of Urban-Scale Photochemical Air Quality Simulation
Models (ESRL, 1982).
3. The St. Louis Ozone Modeling Project (EPA, 1983).
4. The Surface Ozone Record for the Regional Air Pollution Study, 1975-
1976 (Atmospheric Environment, 1982).
Data bases containing hourly ozone concentrations are not available for review
during the selection process. Some ozone data was plotted for selected stations in
various reports; however, only peak ozone concentrations for these days are known.
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Observed wind data used to create the original three-dimensional wind fields for
UAM will be used to create interpolated surface wind fields with a distance-weighted
interpolation algorithm. Surface wind fields will be created to determine the hourly
flow patterns for each episode day. These surface wind fields will be used to track
air parcels released at various times and locations to determine (a) the timing of the
"flushing" of initial conditions from the modeling domain, (b) the general area of
origin of material affecting peak observed ozone concentrations, and (c) the
influence of boundary conditions on calculated ozone concentrations.
The episode will be selected on the basis of the following criteria:
High and widespread ozone concentrations
Minimal effects of boundary conditions
Organized transport conditions
No atypical meteorological conditions
The episode selection will be performed immediately following the completion of the
protocol. The episode selection will be summarized in a technical memorandum and
sent to all participating members for review.
UAM INPUT PREPARATION PROCEDURES
As summarized in the previous section, one of the modeling days formulated in the
previous EPA UAM study will be used in this study. The latest version of the UAM
containing the Carbon-Bond IV (CBM-IV) chemical mechanism (Gery et al., 1988) will
be applied in this study. To ensure that the modeling data base for the episode
selected has been properly converted on our in-house computer system, a base case
simulation will be re-run using the Carbon-Bond II version of UAM. All subsequent
modeling will involve the CBM-IV version of UAM.
UAM Modeling Grid Specification
The modeling will be performed on the original St. Louis modeling grid, which con-
sists of 17 by 22 grid cells with a horizontal dimension of 4 km, covering an area 68
by 88 km. The modeling grid is depicted in Figure 2-1. It covers parts of Missouri
and Illinois, encompassing the majority of the smaller, outlying urban areas
surrounding metropolitan St. Louis. The grid is located in UTM zone 15 with the
origin set at 706,000. m Easting and 4,326,000. m Northing.
The following 13 input files are required for UAM modeling analyses:
DIFFBREAK This file contains the daytime mixing height or nighttime inversion
height for each column of cells at the beginning and end of each
hour of the simulation.
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FIGURE 2-1. The St. Louis metropolitan area UAM modeling grid and RAPS station
locations. (Grid cells are 4 x 4 km). (Source: EPA, 1983).
B81 39
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REGIONTOP
WIND
METSCALARS
AIRQUALITY
BOUNDARY
TOPCONC
This file contains the height of each column of cells at the begin-
ning and end of each hour of the simulation. If this height is
greater than the mixing height, the cell or cells above the mixing
height are assumed to be within an inversion.
This file contains the x and y components of the wind velocity for
every grid cell for each hour of the simulation. Also the maximum
wind speed for the entire grid and average wind speeds at each
boundary for each hour are included in this file.
This file contains the hourly values of the meteorological
parameters that do not vary spatially. These scalars are the NC>2
photolysis rate constant, the concentration of water vapor, the
temperature gradient above and below the inversion base, the
atmospheric pressure, and the exposure class.
This file contains the initial concentrations of each species for
each grid cell at the start of the simulation.
This file contains the location of the modeling region boundaries.
This file also contains the concentration of each species that is
used as the boundary condition along each boundary segment at
each vertical level.
This file contains the concentration of each species for the area
above the modeling region. These concentrations are the boundary
conditions for vertical integration.
TEMPERATURE This file contains the hourly temperature for each surface layer
grid cell.
EMISSIONS
PTSOURCE
TERRAIN
This file contains the ground-level emissions of NO, NO2, seven
carbon bond categories, and CO for each grid square for each hour
of the simulation.
This file contains the point source information, including the stack
height, temperature and flow rate, the plume rise, the grid cell
into which the emissions are emitted, and the emissions rates for
NO, NO2> seven carbon bond categories, and CO for each point
source for each hour.
This file contains the value of the surface roughness and deposition
factor for each grid square.
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CHEMPARAM This file contains information regarding the chemical species to be
simulated including reaction rate constants, upper and lower
bounds, activation energy, and reference temperature.
SIMCONTROL This file contains the simulation control information such as the
time of the simulation, file option information, default informa-
tion, and information on integration and chemistry time steps.
The majority of the input files used in the previous St. Louis application of UAM will
be used "as is" in this application. However, the WIND file will be recreated using a
new technique, and other files affected by the change to CBM-IV will also be
updated. The recommended procedures for preparing those files that will be changed
in the St. Louis application are summarized in the following subsections.
REGIONTOP - The original St. Louis application used a temporally varying height for
the top of the region that was situated 400 m above the hourly mixing height
(DIFFBREAK) value. For the current study, we will use a constant value for
the top of the region, tentatively chosen to be 1600 m. The final selection for
the top of the region will be based on the maximum mixing height used in the
modeling day selected.
WIND - The wind fields created for the original St. Louis application used the
WINDSET preprocessor algorithm. The three-dimensional wind fields created
for a number of the modeling days, however, did not always replicate the
measured data well. In the new application, we recommend using a wind model
along with the measured data to derive new wind fields in an attempt to avoid
problems encountered in the past. Hourly wind speed and direction data will be
used along with the Hybrid Diagnostic Wind Model (HDWM) (Douglas and
Kessler, 1988; Morris et al., 1987) to create new three-dimensional modeling
wind fields.
METSCALARS - The parameters contained in this file will be examined and reviewed
to determine whether they are to be changed/updated. Available
meteorological data collected in the modeling region will be used to complete
this file for those parameters that are changed. The spatially constant,
temporally varying parameters include estimates for NC>2 photolysis rate,
water concentration, exposure class, atmospheric pressure, and temperature
gradients above and below the mixing height. Because of changes in the CBM-
IV chemistry, the NC^ photolysis rate constants may need updating. Because
of changes to the REGIONTOP file, the temperature gradients above the
mixing height will have to be updated.
AIRQUALITY - The species initial concentration field, the AIRQUALITY file, will be
created by using air quality data collected at monitors in the modeling
88 I39r I 2
B- 9
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domain. The values will correspond to the specific initial hour of the simula-
tion, which is not known at this time. The upper-layer initial field will use
values specified in the TOPCONC file. The AIRQUALITY file will be updated
with the new CBM-IV species.
BOUNDARY - The new CBM-IV species will be added to the BOUNDARY file for the
CBM-IV simulations.
TOPCONC - New CBM-IV species will be added to this file before the UAM CBM-IV
is exercised.
EMISSIONS - The original inventory used in the previous St. Louis application
containing information on the CBM-II species will be updated to correspond to
a CBM-IV inventory. This will be accomplished by splitting total aromatics
(ARO) into the new CBM-IV species toluene (TOL) and xylene (XYL), and
splitting total carbonyls (CARB) into the new CBM-IV species formaldehyde
(FORM) and other aldehydes (ALD2). The splitting factors for the new CBM-IV
species will be taken from the recently published EKMA guidelines for CBM-IV
(Hogo and Gery, 1988). This new base year CBM-IV inventory is needed for a
new CBM-IV base case simulation to ensure that the changes made to all of the
other input files have been correctly implemented. The methodology for creat-
ing the future year emission scenario inventories is presented in the next sec-
tion.
PTSOURCE - The CBM-II input file containing point source information will be up-
dated for the new CBM-IV base case simulation following the procedure per-
formed for the low level emissions. Methodology for deriving the future year
base case and emission scenario point source files is presented in the next sec-
tion.
TERRAIN - This file will be updated using land-use information. It will contain
surface roughness and deposition information as a function of land use (no
terrain height information). The deposition values as a function of land use are
derived from studies performed by the Argonne National Laboratory (Sheih et
al., 1986). These values are summarized in Table 2-1.
CHEMPARAM - The CHEMPARAM file contains information regarding (1) the
species to be modeled by the UAM; (2) upper and lower bounds on numerical
and steady-state calculations along with species "resistance" to dry deposition;
and (3) the rate constants for the photochemical reactions. Before the CBM-IV
base case simulation is performed, the CHEMPARAM file will be updated to
correspond to the new species simulated with the new mechanism.
SIMCONTROL - The SIMCONTROL file controls the actual simulation parameters of
the UAM run (i.e., simulation time period, minimum time steps, output time
intervals). At this time it is not known when the simulation will be initiated;
88139rl 2
B- 10
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TABLE 2-1. Surface roughness and deposition factors
based on studies by Argonne National Laboratories.
Land Use Surface Roughness Deposition
Category (meters) Factor
Urban
Agricultural
Range
Deciduous Forest
Coniferous Forest
including wetland
Mixed Forest
Water
Barren land
Nonforest Wetlands
Mixed Agricultural
and range
Rocky (low shrubs)
3.00
0.25
0.05
1.00
1.00
1.00
0.0001
0.002
0.15
0.10
0.10
0.2
0.5
0.4
0.4
0.3
0.3
0.03
0.2
0.3
0.5
0.3
88139rl 3 B- 11
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however, all other information contained in the file will not change from one
simulation to another.
Assessment of Model Performance for the Base Case
After the modeling inputs have been finalized and rendered consistent with UAM
CBM-IV requirements, a new base case simulation will be run. Before using the
updated modeling data base in any future year emission scenario simulations, it is
essential that at least a limited assessment of model performance be undertaken,
even in this low-cost, simplified UAM application. The model's ability to predict the
level and spatial orientation of the observed ozone field will be assessed by compar-
ing the UAM-calcuiated concentrations with the measured data.
If we can locate the observed hourly data, we will compute a limited set of model
performance statistics that summarize error, bias, and the model's ability to
calculate the peak ozone concentration. In this application, no specific performance
criteria will be established, and no strict performance evaluation will be
undertaken. However, if the modeling system shows very poor performance, we may
undertake one (or more as time allows) diagnostic simulation(s) to identify a range of
alternatives for improving model performance. For example, a diagnostic simulation
may involve changes to the three-dimensional wind field (within the range of the
uncertainty of the data used to prepare the field) if spatial alignment problems occur
in the base case simulation. If necessary, these diagnostic simulations will only be
undertaken after consultation with the project's technical representative. Future
year emission scenario simulations using the CBM-IV modeling data base will be
performed only after there is agreement from participating technical representatives
that performance in the base case is adequate.
Future Year Emission Inventory Development
Improved Urban Airshed Model performance is achieved when emissions data in a
very specific and detailed format is available. UAM requires a spatially
disaggregated and temporally allocated emissions inventory. Performance is
improved if a chemically speciated emissions inventory is obtained, although
speciation could be achieved by using default speciation profiles, as is customarily
done with EKMA. Meeting these requirements often entails the collection of
additional emissions-related information such as population distribution and
industrial activity data.
In this study we will be using the 1985 NAPAP (National Acid Precipitation Assess-
ment Program) Emissions Inventory as the base year from which all future year emis-
sion scenarios will be developed. The future year selected for use in this study is
1995. The 1985 NAPAP Emissions Inventory consists of annual county-wide area
source emissions (including mobile sources), and annual emissions for large point
88139rl 2
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sources along with stack parameters (i.e., stack height, diameter, flow rate, and
temperature). The county-wide area source emissions will be disaggregated onto the
gridded modeling domain using the gridded population distribution. Source categories
will be classified as related to the population distribution, inversely related to the
population distribution, or not related at all to population, and gridded accordingly.
The annual emission rates will be adjusted for each source category to summer
weekday emissions by using scaling factors based upon typical values of monthly
throughputs and weekday factors. Likewise, hourly variations in emissions will be
based upon typical diurnal activity levels for each source category.
The stationary source emissions for the 1995 scenario year will be projected from
1985 NAPAP emissions by utilizing growth factors by source category available from
an EPA-sponsored study (Pechan, 1988). Mobile source emissions will be prepared
using scaling factors provided by the EPA Office of Mobile Sources specifically for
each scenario to be analyzed.
Several emissions inventories will be used for the limited performance evaluation of
the UAM and assessment of the effects of alternative fuel use and SIP control
strategies. The following list describes each of the emission scenarios:
CBM-II 1975 or 1976 case - the inventory used for the past UAM/CBM-II appli-
cations. This emissions scenario will be used to verify that the UAM inputs are
set up correctly on the Systems Applications' computer. This inventory is valid
for 1975 or 1976.
CBM-IV 1975 or 1976 case - a modified version of the CBM-II meteorological
case for CBM-IV species. This inventory will be used to verify that the
UAM/CBM-IV is operating properly and predicts ozone patterns comparable to
those predicted by the UAM/CBM-II. This inventory is valid for 1975 or 1976.
The creation of this inventory was described in the input preparation section
above.
1985 NAPAP - gridding of 1985 NAPAP inventory for CBM-IV species, as is, to
the modeling domain.
1995 base case - this inventory is based on the 1985 NAPAP county inventory.
Stationary source emissions are projected to 1995 using growth factors from
EPA (Pechan, 1988). Mobile source emissions will be based on values provided
by OMS. The emission scenarios will correspond to different assumptions in the
mobile source emissions.
1995 Emission Scenarios - these inventories will reflect changes in VOC, NO ,
and CO due to assumptions of future changes in mobile source emission rates
such as changes in Reid vapor pressure (RVP) and use of ethanol blended fuels.
For St. Louis, EPA/OPPE has defined 4 separate emission scenarios as follows:
88139rl 2 B-13
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Scenario #1 - 1995 base case with mobile emissions at current RVP values
(11.5 psi) with running losses
Scenario #2 - 1995 base case with mobile emissions at low RVP values
(9.0 psi) with running losses
Scenario #5 - 1995 base case with 50 percent ethanol penetration* and a
10 percent ethanol blend at low RVP (9.0 psi) plus 1 psi exemption with
running losses
Scenario #7 - 1995 base case with 100 percent penetration and enough
Ethyl Tertiary Butyl Ether (ETBE) to produce 2 percent oxygenated fuels
with running losses
SO? Inventory Development
In addition to the ethanol blended fuels inventories prepared to determine ozone sen-
sitivity information, an inventory reflecting SIP information for the St. Louis area
will be prepared based on the 1985 NAPAP inventory. This inventory will be
developed in consultation with representatives from the State of Missouri, the State
of Illinois, EPA Region VII, and EPA OAQPS.
Emission Scenario Simulations
On the basis of emission scenario options outlined in the previous section, a subset
will be chosen for UAM modeling. In addition to changes in the input emissions files,
the initial condition (AIRQUALITY) and boundary condition (BOUNDARY) files will
be changed to reflect general estimates of future year air quality. Estimates for
initial conditions will be changed (increased/decreased) to reflect changes in the
emission inventory for the St. Louis metropolitan area from 1975 to 1995 based on
projected growth and anticipated future emission controls. To calculate a future
year estimate, the urban background estimate will first be subtracted from the
actual meteorological base year concentration for 1975 or 1976. The resulting con-
centration will be changed in proportion to changes in emissions. The background
will then be added to this concentration to arrive at a future year estimate. Simi-
larly, on the basis of emission changes in the St. Louis area, the upwind inflow boun-
dary conditions will be changed to reflect forecasted changes in emissions between
* In this context, "penetration" is defined as the change from one type of fuel to
another. A 50 percent ethanol penetration scenario is one in which 50 percent
of fuel used in vehicles is converted from gasoline to an ethanol-blended fuel.
88139rl 2 - ,.
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1975 and 1995. Only one set of future year initial and boundary conditions will be
selected and used for all modeling pertaining to a given future year. We will not use
multiple sets that reflect specific differences in emissions between scenarios.
The results of the UAM simulations will be presented in the form of ozone difference
plots. These plots are created by subtracting the calculated ozone concentration of
the future year base case (for each grid cell, for each hour) from the concentration
obtained in the emission sensitivity simulations. This results in hourly isopleth maps
that show both the magnitude and spatial extent of differences in ozone concentra-
tions due to changes in emissions. Changes in calculated peak ozone will also be
summarized in tabular format.
SIP Emission Scenario UAM Simulation
After a SIP modeling inventory has been prepared and approved by all affected
participants, at least one future year SIP simulation will be undertaken. It is antici-
pated that the initial and boundary condition values may have to be changed to
reflect the forecasted changes in the inventory from 1985 to some future year.
Initial and boundary conditions will be changed in the same manner as described
above for the future year ethanol sensitivity simulations. The results of this SIP
simulation will be compared to results obtained with EKMA.
88139rl 2 B-15
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3 EKMA MODELING METHODOLOGY
BACKGROUND
A recent study used the simple photochemical modeling approach known as EKMA
(Empirical Kinetics Modeling Approach) to investigate the possible impacts on urban
ozone formation from the use of ethanol-blended gasoline fuels (Whitten, 1988). The
study addressed the comparative reactivities of the relevant ozone precursor emis-
sions affected by the use of ethanol blends. Atmospheric conditions were varied to
represent those found in seven cities. The key finding of the study was a near
balance between ozone increases from enhanced evaporative emissions of VOC and
ozone decreases from reduced exhaust emissions of CO. This was the first study to
consider mitigation of ozone VOC precursors through CO reductions. When the
chemistry of the individual evaporative emissions species was explicitly treated in
the model, the results always showed a net reduction in ozone associated with the
use of ethanol blends. However, the U.S. EPA recommends simplified treatment of
reactivity in the EKMA, whereby the reactivity of all VOC emissions species is
treated as being equal to the reactivity of overall average VOC. While this simpli-
fied treatment overestimates the reactivity of the increased evaporative emissions,
the EKMA modeling results indicated small net reductions in ozone formation from
the use of ethanol blends in some cases, and in others the simplified reactivity
assumption showed a small net increase in ozone. Although the existing EKMA
model can explicitly treat the chemistry of evaporative automotive emissions, the
simplified treatment of reactivity is more consistent with the overall simplified
philosophy embodied in regulatory applications of EKMA.
The negative or positive direction of the small ozone impacts derived from the
simplified treatment of VOC reactivity and the size of the ozone reductions derived
from the explicit chemical treatment of the affected emissions appear to depend on
the mobile-related fraction of total VOC and the ratio of CO emissions to VOC emis-
sions. Areas with low mobile-related VOC fractions and high CO-to-VOC ratios are
expected to show the largest net ozone reductions if ethanol fuels are used because,
under these conditions, the overall ambient increases in VOC will be smaller, and the
decreases in ambient CO concentrations will be larger. However, it is important to
increase the confidence in the preliminary EKMA analyses thus far carried out.
Further UAM and EKMA evaluations are thus warranted, and will be carried out as a
part of this study.
B-17
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The study by Whitten (1988) used EKMA episodes previously set up for 1982 SIP cal-
culations plus CO estimates based on the CO-to-VOC ratios in the NEDS data base.
Also, RVP changes and volatility increases due to ethanol blends were estimated
from a 1987 RVP impact study by the EPA. Since the release of the Whitten study,
new emissions guidelines for alternate fuels have been released by the EPA (29 Janu-
ary 1988). Therefore, new EKMA simulations, which use the new EPA guidelines for
alternate fuels, and are appropriate to 1995 projections in St. Louis, are needed.
COMPARISON OF EKMA AND UAM
Some factors regarding changes in mobile-related emissions cannot be addressed with
the EKMA. These factors can be treated by UAM. For example, the diurnal timing
and location of evaporative emissions are not always equal to those of exhaust emis-
sions. The UAM is capable of treating cold-start, hot-soak, highway-cruising and
congested-traffic emissions separately depending on local data for hourly tempera-
tures, spatially resolved traffic counts, average speeds, and vehicle miles traveled.
Alternatively, EKMA uses constant grams per mile emissions based on data from
standard federal trip and mileage test procedures (FTP) and estimates of local auto-
mobile populations.
The principal differences between EKMA and UAM stem from the trajectory nature
of EKMA versus the grid nature of UAM. EKMA treats the atmospheric chemistry of
a single parcel of air as representative of one reaching an observed ozone maxi-
mum. The model simulation begins at 0800 hours with an initial loading of precur-
sors, and more emissions are added each hour on the basis of county-wide emission
averages. The UAM treats gridded points throughout the urban region (resolved both
horizontally and vertically) for a day or more preceding an ozone episode. Precur-
sors are emitted and move about within the gridded model region according to the
physical equations governing wind flow, dispersion, and surface deposition. The
secondary pollutants (such as ozone) are formed in both models on the basis of atmo-
spheric chemistry. Hence EKMA provides information at one point in time and space
on the basis of a few hours' highly averaged information, whereas UAM provides
information at all points in time and space on the basis of a day or more of highly
resolved information.
It is possible that the UAM will provide results that are significantly different from
those of the EKMA-based study because of UAM's ability to treat spatially varying
emissions. However, this discussion illustrates the vast differences in complexity
and sophistication between the EKMA and UAM models and the potential for some-
what different results.
PURPOSE OF ANALYSIS
The purpose of using EKMA to simulate the same scenarios as those simulated by
UAM is threefold. The first is to use the UAM to support or refute the EKMA
88139rl 2 B-18
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results obtained in the previous study on the effects of ethanol fuel use on urban
ozone concentrations in seven U.S. cities (Whitten, 1988).
The second purpose of the EKMA simulations is to estimate the uncertainties invol-
ved in using a trajectory model like EKMA to examine the effects of different emis-
sion scenarios such as alternative fuel use. Even though the changes in the observed
maximum ozone may be in agreement for both models, the different reactivities,
source configurations, and three-dimensional structure of the UAM may result in the
UAM predicting new hot spots of high ozone concentrations occurring outside of the
EKMA trajectory.
The third purpose of the EKMA simulations is to study the effects of reactivity of
VOC emissions on ozone formation. EKMA's use of the default and actual reactivity
of the emission scenarios will provide insight into the uncertainties produced by
these assumptions.
EKMA MODELING METHODOLOGY
Two sets of EKMA calculations will be made for each UAM scenario. The first will
be performed in strict accordance with EPA guidelines for using EKMA for post-1987
State Implementation Plans (SIPs) (Hogo and Gery, 1988). The UAM modeling period
will be viewed as a "design day" in setting up the OZIPM simulation. However, in
keeping with EKMA guidance, none of the UAM inputs will be used for creating the
EKMA inputs. County total emissions of NOX, VOC, CO, and other species (correc-
ted for season and MOBILE 3.9) will be used for each emissions scenario. The VOC
emissions will be speciated using the default EKMA reactivity. For the ethanol-
blended fuel cases, these emissions will have higher total VOC and lower CO emis-
sions and will not account for the lower reactivity of ethanol-blended fuels.
The second set of EKMA simulations will be performed in the same manner as the
first set, but the county VOC emissions will be speciated according to the source-
specific speciation profiles for the emission scenario in question. Thus for the etha-
nol fuel cases, there will be a higher VOC emissions rate, but these simulations will
take into account the lower reactivity of emissions from ethanol-blended fuels.
SIP Emission Scenario EKMA Simulation
In addition to the ethanol fuel sensitivity simulation using EKMA, a SIP simulation
will also be performed. Emission inventory information derived from the UAM grid-
ded SIP inventory will be used to supply information for the application of EKMA.
The results of this analysis will be compared to the information derived from the
UAM SIP simulation for St. Louis.
88139rl 2 B-19
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References
Benkley, C. W., and L. L. Schulman. 1979. Estimating hourly mixing depths from
historical meteorological data. 3. Appl. Meteorol., 18:772.
Burton, C. S. 1988. Comments on "Ozone Air Quality Models." Submitted to 3. Air
Pollut. Control Assoc.
Cole, H. S., D. E. Layland, G. K. Moss, and C. F. Newberry. 1983. "The St. Louis
Ozone Modeling Project." U.S. Environmental Protection Agency, Research Tri-
angle Park, North Carolina (EPA-450/4-83-019).
Douglas, S., and R. Kessler. 1988. "User's Guide to the Diagnostic Wind Model.
Version 1.0." Systems Applications, Inc., San Rafael, California.
Emison, G. A. 1988. Memo to William G. Laxton, EPA-OAQPS, May 1988.
Gery, M. W., G. Z. Whitten, and J. P. Killus. 1988. "Development and Testing of the
CBM-IV for Urban and Regional Modeling." Systems Applications, Inc., San
Rafael, California (SYSAPP-88/002).
Hogo, H., and M. W. Gery. 1988. "Guidelines for Using OZIPM-f with CBM-IV or
Optional Mechanisms, Volume 1: Description of the Ozone Isopleth Plotting
Package, Version 4." Systems Applications, Inc., San Rafael, California
(SYSAPP-88/001).
Morris, R. E., R. C. Kessler, S. G. Douglas, and K. R. Styles. 1987. "Rocky Mountain
Acid Deposition Model Assessment: Evaluation of Mesoscale Models for Use in
Complex Terrain." U.S. Environmental Protection Agency (EPA-600/3-87-013;
NTIS PB87-180584-AS).
Pechan, E. H., and Associates. 1988. "National Assessment of VOC, CO, and NOX
Emissions and Costs for Attainment of the Ozone and CO Standards."
Rao, S. T. 1987. "Application of the Urban Airshed Model to the New York Metro-
politan Area." Bureau of Air Research, Division of Air Resources, New York
State Department of Environmental Conservation, Albany, New York (CA No.
CX811945-01 -0; EPA-450/4-87-011).
-------
Seinfeld, J. H. 1988. Ozone air quality models. A critical review. 3. Air Pollut.
Control Assoc., 38(5):616.
Sheih, B. F., N. L. Wesely, and C. J. Walcek. 1986. "The Dry Deposition Module
for Regional Acid Deposition Models." Argonne National Laboratories
(DW89930060-01).
Whitten, G. Z. 1988. "Evaluation of the Impact of Ethanol/Gasoline Blends on Urban
Ozone Formation." Systems Applications, Inc., San Rafael, California (SYSAPP-
88/029.
•a OT
88139rl "t
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Appendix C
EPISODE SELECTION FOR ST. LOUIS UAM MODELING
88151
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Appendix C
EPISODE SELECTION FOR ST. LOUIS UAM MODELING
INTRODUCTION
This appendix provides a summary of the procedures that were used to select an
ozone episode for the CBM-IV UAM modeling of St. Louis for the EPA Five Cities
modeling project. Time constraints did not permit identification of new ozone epi-
sodes or development of additional modeling data bases for this project. Instead, an
ozone episode day was chosen from a set of four episode days that were developed as
part of the original St. Louis Ozone Modeling Project (EPA, 1983). The modeling
data bases for these days were obtained from EPA. The raw data from which the
inputs were created were not available for review. The modeling days include the
following:
Thursday, 22 May 1975
Saturday, 26 July 1975
Tuesday, 13 July 1976
Friday, 1 October 1976
The episode selection was based on the UAM input files and information that could
be derived from the following reports:
1. Regional Air Monitoring System Flow and Procedures Manual (Rockwell,
1977).
2. Final Evaluation of Urban-Scale Photochemical Air Quality Simulation
Models (ESRL, 1982).
3. The St. Louis Ozone Modeling Project (EPA, 1983).
4. The Surface Ozone Record for the Regional Air Pollution Study, 1975-
1976 (Atmospheric Environment, 1982).
88151 14 C-l
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SELECTION METHODOLOGY
The episode-selection process in which candidate days are chosen for UAM modeling
usually involves an intense review of all available meteorological and air quality
data. Air quality data are examined to determine days with high and widespread
ozone concentrations. Meteorological data are examined to determine the specific
factors causing the high observed ozone (e.g., temperatures, winds, sky cover).
Urban areas located in complex geographical locations may observe high ozone con-
centrations resulting from different meteorological mechanisms. For these loca-
tions, a number of episodes should be chosen to include all of the meteorological
regimes that cause high ozone in the urban area. In this study, we were constrained
to choosing only one modeling day, and only a limited amount of data were
examined. Data bases containing hourly ozone concentrations were not available for
review during the selection process. Some ozone data were plotted for selected sta-
tions in various reports; however, only peak ozone concentrations for these days are
known. Table C-l presents a summary of the meteorological and air quality
parameters for the episode days.
TABLE C-1. Summary of meteorological and air quality parameters
observed for selected days in St. Louis.
Date
5/22/75
7/26/75
7/13/76
•10/1/76
WS
(m/s)
1.1
1.0
2.3
0.6
WD
(deg)
224 '
139
1H5
222
Temp
(°C)
29
26
28
22
Solar
(ly/min)
1.12
0.98
1.02
0.78
Max MH
(m)
1504
1477
1853
527
Max Oo
(pphm)
19.5
18.5
22.3
24.6
The modeling episode was selected on the basis of the following criteria:
High and widespread ozone concentrations
Minimal effects of boundary conditions
Organized transport conditions
No atypical meteorological conditions
Because the 1 October 1976 day was an atypical ozone event that occurred outside
the normal ozone season and was characterized by unusually low mixing heights, cool
temperatures, and stagnation conditions, it was not considered further in the
selection process. Although it is an interesting event, it is not reflective of a normal
summertime ozone event in St. Louis.
88151
C-2
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Data from the remaining days were examined further to determine differences in the
flow fields and effects of boundary and initial conditions on modeled concentra-
tions. The wind files for each of the modeling days were used to track air parcels
released at various times and locations to determine (1) the timing of the "flushing"
of initial conditions from the modeling domain, (2) the general area of origin of
material affecting peak observed ozone concentrations, and (3) the influence of
boundary conditions on calculated ozone concentrations.
Three sets of surface air parcel trajectories were performed for each of the three
modeling days. These trajectories include the following:
1. Forward trajectories starting at 0500 LST in the center of, and surround-
ing, the city of St. Louis. These trajectories were tracked until the end
of the day or until they moved out of the modeling domain. They were
released to determine the fate of the initial condition field in the center
of the city.
2. A backward trajectory from the site and time of the observed ozone
maximum. This trajectory was run to determine the general origin of the
parcel affecting the monitor showing peak observed ozone concentra-
tions.
3. Forward trajectories from the edges of the inflow boundaries starting at
0500 LST, with additional releases every two hours until 1900 LST. These
trajectories were released to determine the extent and influence of the
boundary conditions on the calculated ozone concentrations. The inflow
boundaries were determined after examination of the plotted surface
wind fields.
Figures C-l, C-2, and C-3 present these three types of trajectories, respectively, for
22 May 1975, 26 July 1975, and 13 July 1976.
Thursday, 22 May 1975
The relatively slow southwesterly flow on this day has transported the 0500 LST
initial condition field north and east, and only the northern portions of the initial
conditions have been transported out of the region by the time of the peak observed
ozone (1500 LST). The peak observed ozone was measured at RAPS station 101,
located in downtown St. Louis along the Mississippi River. The back trajectory shows
the general origin of the parcel to be south of the city. Boundary conditions from
the southern and western boundaries are not transported near the location of the
peak observed ozone concentration.
C-3
88151 li*
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Saturday, 26 July 1975
Because of the light southeasterly winds, the 0500 LSI initial condition field for this
day is transported northwestward and not flushed from the modeling region by the
time of the observed peak (1500 LSI). The peak observed ozone was measured at
RAPS station 113, located just north of downtown St. Louis. The backward trajec-
tory shows the origin of the parcel to be located near the southern edge of the St.
Louis metropolitan area at 0500 LST. Inflow boundary conditions from the east and
south do not influence the area of the observed peak ozone.
Tuesday, 13 July 1976
The relatively strong southerly flow on this day has transported a large portion of the
0500 LST initial condition field to the north and west, out of the modeling domain by
the time of the observed peak ozone (1600 LST). Peak ozone was observed at RAPS
station 114, located north of downtown St. Louis. The back trajectory shows that the
parcel arriving at this station at the time of the peak originated just north of Belle-
ville, Illinois. Because of higher wind speeds (compared to the other two days) for
this day, the boundary conditions influence a larger portion of the modeling domain
by the time of the peak; however, the area of the peak is free from the influence of
boundary conditions.
Given the selection criteria and the results of the trajectory analysis, it appears that
any of these three episodes would be suitable for (JAM modeling. The 13 July 1976
day is attractive because it (1) has the largest observed ozone of the three days, (2)
has well-organized transport conditions, and (3) is relatively free of the effects of
initial conditions. However, the 13 July 1976 day also is the most influenced by
boundary conditions of the three candidate days, although the boundary conditions do
not appear to influence the region of maximum ozone concentrations. Stagnant
meteorological conditions are prevalent on both 22 May and 26 July 1975. Initial
conditions for both of the 1975 days may affect concentrations in the region of the
maximum ozone concentrations. The 26 July day is a Saturday, when atypical
emission characteristics exist. The 22 May day occurs fairly early in the ozone
season; however, it appears to have meteorological conditions fairly typical of an
ozone episode. Since the 13 July 1976 day contains the highest observed ozone of the
candidate days, has well-organized transport conditions, and is minimally affected by
initial and boundary conditions, it was chosen as the episode day for the PLANR use
of the UAM (CB-IV) for St. Louis.
88151 11
C-4
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FIGURE 1
AIR PARCEL TRAJECTORIES FOR
ST. LOUIS FOR THURSDAY, MAY 22, 1975
88 15 1 1>*
-------
NORTH
706
20
10
J I
756
10
SOUTH
j I
1;>00
4286
4236
Initialized on
0 500 ON 5/22/75
(f) 500 ON 5/22/75
(5) 500 ON 5/22/75
0 500 ON 5/22/75
(§) 500 ON 5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Far-ward Trajectories
C-6
-------
NORTH
106 711 716 721 726 731 736 741 746 751 756 761 766 771
<££
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
(
I I 1 1 1 I I 1 1 1 I I 1
_ —
-
-
—
- -
-
-
—
>-
200
~
- —
—
-
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1
SOUTH
Initialized on
4321
4316
4311
4306
4301
4296
4291
4286
4281
4276
4271
4266
4261
4256
4251
4246
4241
,£236
l&OO ON 5/22/7S Backward Trajectories
ST. LOUIS REGIONAL OZONE ANALYSIS
C-7
-------
NORTH
706
20
756
10
2400
4286
X2400
0
10
4236
SOUTH
Initialized
7) 500 ON
f) 500 ON
g) 500 ON
0 500 ON
gl 500 ON
rS\ OK
on
5/22/75
5/22/75
5/22/75
5/22/75
5/22/75
5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-8
-------
NORTH
706
756
20
10
2400
4286
2400
1800
0
10
4236
SOUTH
Initialized on
0 700 ON 5/22/75
(§) 700 ON 5/22/75
(5) 700 ON 5/22/75
0 700 ON 5/22/75
(§) 700 ON 5/22/75
fa TOO OH 5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Fonrard Trajectories
C-9
-------
NORTH
706
20
756
10
2400
4836
laoo
1200
10
4236
SOUTH
Initialized on
7)
D
[5)
5)
§)
^
900
900
900
900
900
ooo
ON
ON
ON
ON
ON
CM
5/22/75
5/22/75
5/22/75
5/22/75
5/22/75
5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-10
-------
NORTH
706
756
20
10
0.
2400
4286
2400
X2400
2400
1SOO
1800
iaoo
0
10
4236
SOUTH
Unitialized on
0 1100 ON 5/22/75
(§) 1100 ON 5/22/75
(|) 1100 ON 5/22/75
0 1100 ON 5/22/75
(5) 1100 ON 5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-ll
-------
NORTH
706
756
20
10
2400
1800
4286
2400
<2400
2400
1800
1800
1800
10
4236
SOUTH
Initialized
0
(§)
(D
0
(D
rtfN
1300
1SOO
1300
1300
1300
1OOO
ON
ON
ON
ON
ON
ON
on
5/22/75
5/22/75
5/22/75
5/22/75
5/22/75
5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-12
-------
NORTH
706
20
10
2400
1800
2400
1800
756
2400
1800
10
4286
2400 -
1800
4236
SOUTH
Initialized on
0 1500 ON 5/22/75
(2) 1500 ON 5/22/75
(5) 1500 ON 5/22/75
0 15OO ON 5/22/75
(5) 1500 ON 5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-13
-------
706
20
10
X2400
2400
1800
1800
I I
CD 2400
y
NORTH
2400
1800
756
10
SOUTH
4286
2400
1800
Initialized on
0 1700 ON 5/22/75
(§) 1700 ON 5/22/75
(f) 1700 ON 5/22/75
0 1700 ON 5/22/75
(5) 1700 ON 5/22/75
/*\ 17OO ON
ST. LOUIS REGIONAL OZONE ANALYSIS
Fox-ward Trajectories
014
-------
NORTH
706
756
20
13
10
4286
(D2400
X2400
2400
j i I I i
i t i
10
4236
SOUTH
Initialized on
0 1900 ON 5/22/75
(2) 1900 ON 5/22/75
(5) 1900 ON 5/22/75
0 1900 ON 5/22/75
0 1900 ON 5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-15
-------
706
20
10
X2400
[D2400
2400
2400
NORTH
756
2400
I I
10
SOUTH
4286
2400
1 I I
4236
Initialized on
0 2100 ON 5/22/75
(§) 2100 ON 5/22/75
(3) 2100 ON 5/22/75
0 2100 ON 5/22/75
(§) 2100 ON 5/22/75
^ ftlOO OK 5/22/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-16
-------
NORTH
706
20
756
10
o
4286
2400
. E2400
2400
2400
2400
2400
10
4236
SOUTH
Initialized on
0 2300 ON 5/22/75
(f) 2300 ON 5/22/75
(3) 2300 ON 5/22/75
0 2300 ON 5/22/75
(§) 2300 ON 5/22/75
fii\ aaoo ON 5/22/7S
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-17
-------
FIGURE 2
AIR PARCEL TRAJECTORIES FOR
ST. LOUIS FOR SATURDAY, JULY 26, 1975
C-19
88151 It
-------
706
20
10
NORTH
756
800
4 2400
2400
I I
I I I I I I
'600
10
SOUTH
4286
i i i
4236
Initialized on
0 500 ON 7/26/75
(2) 500 ON 7/26/75
(3) 500 ON 7/26/75
0 500 ON 7/26/75
(§) 500 ON 7/26/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-20
-------
NORTH
106 711 716 721 726 731 736 741 746 751 756 761 766 771
«££
21
20
19
18
17
16
15
14
13
12
11
10
9
w^
8
7
6
5
4
3
2
(
1 1 I 1 1 1 1 1 1 I 1 I I
—
- -
—
—
-
-
—
-
~ —
—
Q ~
V
(D 1200
IS) 600
—
-
-
-
-
- —
~ —
-
-
-
_
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1
4321
4316
4311
4306
4301
4296
4291
4286
4281
4276
4271
4266
4261
4256
4251
4246
4241
7*236
Initialized on
) 1500 ON 7/26/76
SOUTH
Backward Trajectories
ST. LOUIS REGIONAL OZONE ANALYSIS
C-21
-------
NORTH
106 711 716 721 726 731 736 741 746 751 756 761 766 771
- 4321
I i I I I I I I I I I I
1200 W600
I I I I I I I I
III
23456
7 8 9 10 11 12 13 14 15 16
SOUTH
Initialized on
Q 500 ON 7/26/75
(§) soo ON 7/26/75
(§) 500 ON 7/26/75
0 500 ON 7/26/75
(S) 500 ON 7/26/75
® 500 ON 7/26/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Fonrard Trajectories
022
-------
NORTH
?06 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
I I I I I I
I I I i
22400
i i
1800
1200
X2400
42400
120(3
I I I I
01234
Initialized on
0 700 ON 7/26/75
(5) 700 ON 7/26/75
0 700 ON 7/26/75
0 700 ON 7/26/75
0 700 ON 7/26/75
0 700 ON 7/26/75
7 8 9 10 11 12 13 14 15 16 1
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
For-wrard Trajectories
C-23
4321
4316
4311
4306
4301
4296
4291
4286
4281!
I
4276
4271
4266
4261
4256
4251
4246
4241
7*236
-------
£
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
NORTH
O6 711 716 721 726 731 736 741 746 751 756 761 766 771
II!)
T
I I I I
2400
T
_ 0)2400
X2400
1800
120C
I I I I I I
4321
4316
4311
4306
4301
4296
4291
4286
4281!
4
(
4276
oo
4271
4266
4261
4256
4246
4241
01234
Initialized on
0 900 ON 7/26/75
(2) 900 ON 7/26/75
(3) 900 ON 7/26/75
0 900 ON 7/26/75
0 900 ON 7/26/75
0 900 ON 7/26/75
1 4
5 6 7 8 9 10 11 12 13 14 15 16 17
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-24
236
-------
NORTH
tt>6 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
I
1
I
I
1
1
I
I
I
1 1 I I
X24OO
©2400
X2400
2400
1800
01234
Initialized on
0 1100 ON 7/26/75
(§) 1100 ON 7/26/75
(3) 1100 ON 7/26/75
0 1100 ON 7/26/75
(S) 1100 ON 7/26/75
(D 1100 ON 7/26/75
6 7 8 9 10 11 12 13 14 15 16 1
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-25
4321
4316
4311
4306
4301
4296
4291
1200
4286
4281!
i
4276
4271
4266
4261
4256
4251
4246
4241
7*236
-------
NORTH
toe 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
e
5
4
3
2
1
I I
I I II
(
- 4321
-------
NORTH
206 711 716 721 726 731 736 741 746 751 756 761 766 771
<££
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
(
1 1 1 1 1 1 1 1 1 1 1 1 1
- -
—
-
—
- -
~ —
; <*-
—
- -
© -
—
© 2400
"
\ 0 "
TS1800
Q ® ®
i i i i i i i i i i i i i i i i
> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1
4321
4316
4311
4306
4301
4296
4291
4286
4281
4276
4271
4266
4261
4256
4251
4246
4241
^236
Initialized on
0 1SOO ON 7/26/75
(|) 1500 ON 7/26/75
(5) 1500 ON 7/26/75
0 1500 ON 7/26/75
(5) 1500 ON 7/26/75
(S) 1500 ON 7/26/75
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
For-ward Trajectories
C-27
-------
NORTH
711 716 721 726 731 736 741 746 751 756 761 766 771
<& 2400 x 2400 A 2400 __
\> V \
\ \ \
V V © V^®
^•wtsoo ^^-Tisoo ^-ifiaoo
i i i t w i i i i i i i i i i i i
3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1
SOUTH
4321
4316
4311
4306
4301
4296
4291
4286
4281
4276
4271
4266
4261
4256
4251
4246
.4241
^236
Initialized on
0 1700 ON 7/26/75
(§) 1700 ON 7/26/7S
(5) 1700 ON 7/26/75
0 1700 ON 7/26/75
(6) 1700 ON 7/26/75
(5) 1700 ON 7/26/75
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-28
-------
NORTH
711 716 721 726 731 736 741 746 751 756 761 766 771
•££
21
20
19
16
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
°<
I I I I 1 1 I I I I I 1 I
_ —
~ —
—
X 2400
-
y
012400
-
v
\D -
-------
FIGURE 3
AIR PARCEL TRAJECTORIES FOR
ST. LOUIS FOR TUESDAY, JULY 13, 1976
C-31
88151 11
-------
NORTH
706
756
20
10
4286
0
10
4236
SOUTH
Initialized on
0 500 ON 7/13/76
(S) 500 ON 7/13/76
(5) 500 ON 7/13/76
0 500 ON 7/13/76
(S) 500 ON 7/13/76
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-32
-------
NORTH
106 711 716 721 726 731 736 741 746 751 756 761 766 771
iSS
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
(
1 1 1 1 1 I 1 I 1 1 1 1 1
- —
~ —
-
—
- -
X~
-
-
_
600
—
—
- -
—
—
1 1 1 1 1 1 I 1 1 1 1 1 1 1 1 1
) 1 2 3 4 5 6 7 6 9 10 11 12 13 14 15 16 1
SOUTH
Initialized on
4321
4316
4311
4306
4301
4296
4291
4286
4281
4276
4271
4266
4261
4256
4251
4246
4241
^236
1600 ON 7/13/76 Backward Trajectories
ST. LOUIS REGIONAL OZONE ANALYSIS
C-33
-------
NORTH
206 711 716 721 726 731 736 741 746 751 756 761 766 771
i i i i i i i i i i i
I I i ~ i I I I I I ~ i i I i i ~ i I
0
2345
Initialized on
0 500 ON 7/13/76
(f) 500 ON 7/13/76
(5) 500 ON 7/13/76
0 SOO ON 7/13/76
(6) 500 ON 7/13/76
(?) 500 ON 7/13/76
7 8 9 10 11 12 13 14 15 16
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-34
-------
NORTH
106 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
- Q 1200
I
I
I
I
I
I
I
I
4321
4316
4311
4306
4301
4296
4291
4286
4281!
i
4276
4271
4266
4261
4256
4251
4246
4241
01234
Initialized on
0 700 ON 7/13/76
(§) 700 ON 7/13/76
(3) 700 ON 7/13/76
0 700 ON 7/13/76
(5) 700 ON 7/13/76
(«) 700 ON 7/13/76
6 7 8 9 10 11 12 13 14 15 16
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Fonrard Trajectories
C-35
#23
6
-------
NORTH
£06 711 716 721 726 731 736 741 746 751 756 761 766 771
13
21-
20-
19-
18-
17-
16-
15-
14-
13-
12-
11-
10-
9-
8-
7-
6-
5-
4-
3-
2-
1-
I I II I I I \ I I I I r
2400
1800
1200
2400
1800
1200
1200
I I
I I I I I
1 1 I I v I I
Initialized on
0 9OO ON 7/13/76
(§) 900 ON 7/13/76
(3) 900 ON 7/13/76
0 900 ON 7/13/76
(§) 900 ON 7/13/76
(?) 900 ON 7/13/76
6 7 8 9 10 11 12 13 14 15 16
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSE
Forward Trajectories
C-36
4321
4316
4311
4306
4301
4296
4291
4286
4281!
i
4276
4271
4266
4261
4256
4251
4246
4241
7*236
-------
NORTH
106 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
I 1 I I I I I I I T I I I
I I
2400
2400
1800
180C
1200 J
I I II I I I I
1200
18)'
L20C
180
I I
4321
4316
4286
4281!
}4266
4261
4246
4241
01234
Initialized on
0 1100 ON 7/13/76
(f) 1100 ON 7/13/76
(5) 1100 ON 7/13/76
0 1100 ON 7/13/76
(6) 1100 ON 7/13/76
(e) 1100 ON 7/13/76
5 6 7 8 9 10 11 12 13 14 15 16 1
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Fonrard. Trajectories
C-37
7*236
-------
NORTH
£06 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
i
r
ii I i IT IIIFI
640 >
2400
2400
1600
I I I I I
I I I II I
4321
4316
4311
4306
4301
4296
4291
4286
4281!
Initialized on
0 1300 ON 7/13/76
(|) 1300 ON 7/13/76
0 1300 ON 7/13/76
0 1300 ON 7/13/76
0 1300 ON 7/13/76
0 1300 ON 7/13/76
7 8 9 10 11 12 13 14 15 16
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-38
4276
4271
4266
4261
4256
4251
4246
4241
236
-------
NORTH
t06 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
16
17
16
15
14
13
12
11
10
9
6
7
6
5
4
3
2
1
T
T
T I I 1 I I I I I I
2400
2400
I I I I
1800
I I
I I
4321
4316
4311
4306
4301
4296
4291
4266
428 li
BOO |
4276
yd1271
4266
4261
4256
4251
4246
4241
Initialized on
0 1500 ON 7/13/76
(§) 1500 ON 7/13/76
(5) 1500 ON 7/13/76
0 1500 ON 7/13/76
(6) 1500 ON 7/13/76
(S) 1500 ON 7/13/76
5 6 7 6 9 10 11 12 13 14 15 16
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-39
V
236
-------
NORTH
lOe 711 716 721 726 731 736 741 746 751 756 761 766 771
21
20
19
13
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
1 I 1 1 1 1
1
I 1 I I I I
i i i
3400
18C
u
i 1 1 1
1800
I 1 1 1 II
4321
4316
4306
4301
4296
4291
0
4286
42811
i
4276
.00
4271
4 5 6 7 8 9 10 11 12 13 14 15 16
SOUTH
1236
Initialized on
0 1700 ON 7/13/76
® 1700 ON 7/13/76
(5) 1700 ON 7/13/76
0 1700 ON 7/13/76
(6) 1700 ON 7/13/76
(5) 1700 ON 7/13/76
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-40
-------
NORTH
&
21
20
19
ia
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
°<
)6 711 716 721 726 731 736 741 746 751 756 761 766 771
I I I I I I I I I 1 I 1
- -
—
- r
/ -
_ «••
1 F2'
- 1
i
I "
1 -
-
J) 2400 X 2400 * 2AOQ
' / I li-
'- -
1 1 1
(y © ©
1 1 II 1 1 1 1 II 1 1 1 ls^l 1
) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1
4321
4316
4311
44806
4301
4296
00
4291
4286
4281
4276
4271
4266
4261
4256
4251
4246
4241
7*236
Initialized on
0 1900 ON 7/13/76
(D 1900 ON 7/13/76
(3) 1SOO ON 7/13/76
0 1900 ON 7/13/76
(?) 1900 ON 7/13/76
(5) 1900 ON 7/13/76
SOUTH
ST. LOUIS REGIONAL OZONE ANALYSIS
Forward Trajectories
C-41
-------
Appendix D
ISOPLETHS OF HOURLY OZONE CONCENTRATIONS (PPHM)
AND HOURLY OZONE CONCENTRATION DIFFERENCES (PPB)
BETWEEN SCENARIOS FOR THE NEW YORK APPLICATION OF
THE UAM ON THE AFTERNOON OF 8 AUGUST 1980
FIGURE D-h Scenario 1
FIGURE D-2: Scenario 2
FIGURE D-3: Differences between Scenario 1 and Scenario 2
FIGURE D-4: Scenario 3
FIGURE D-3: Differences between Scenario 2 and Scenario 3
FIGURE D-6: Scenario 4
FIGURE D-7: Differences between Scenario 4 and Scenario 1
88151 Ap
-------
00
9
2
888S
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Appendix E
ISOPLETHS OF HOURLY OZONE CONCENTRATIONS (PPHM)
AND HOURLY OZONE CONCENTRATION DIFFERENCES (PPB)
BETWEEN SCENARIOS FOR THE ST. LOUIS APPLICATION OF THE
UAM ON THE AFTERNOON OF 13 JULY 1976
FIGURE E-l:
FIGURE E-2:
FIGURE E-3:
FIGURE E-4:
FIGURE E-5:
FIGURE E-6:
FIGURE E-7:
FIGURE E-8:
FIGURE E-9:
FIGURE E-10:
FIGURE E-l 1:
FIGURE E-12:
FIGURE E-13:
Scenario 1
Scenario 2
Differences between Scenario 1 and Scenario 2
Scenario 5
Scenario 6
Differences between Scenario 2 and Scenario 5
Differences between Scenario 2 and Scenario 6
Scenario 7
Differences between Scenario 1 and Scenario 8
SIP Scenario A
SIP Scenario B
Differences between Scenario 1 and SIP Scenario A
Differences between Scenario 1 and SIP Scenario B
88151 Ap
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO. 2.
EPA 450/4-90-006E
4. TITLE AND SUBTITLE URBAN AIRSHED MODEL STUDY OF FIVE
CITIES - A Low Cost Application of the Urban Airshed
Model to the New York Metropolitan Area and the City of
St. Louis EPA 450/4-90-006E
7. AUTHOR(S)
Ralph E. Morris, Thomas C. Myers, Henry Hogo, Lyle R.
Chinkin, LuAnn Gardner, Robert G. Johnson
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Systems Applications, Inc.
101 Lucas Valley Road
San Rafael, CA 94903
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
15. SUPPLEMENTARY NOTES
3. RECIPIENT'S ACCESSION NO.
5. REPORT DATE
April 1990
6. PERFORMING ORGANIZATION
8. PERFORMING ORGANIZATION
CODE
REPORT NO.
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
16. ABSTRACT
This document presents Urban Airshed Modeling results for New York and St.
Included are a series of emissions strategies based on Reid Vapor Pressure
reduction and alcohol/gasoline blended fuels.
Louis.
(RVP)
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS b.lDENTIFIERS/OPEN ENDED TERMS
Ozone
Urban Airshed Model
Photochemistry
Ethanol
18. DISTRIBUTION STATEMENT 19. SECURITY CLASS (This Report)
20. SECURITY CLASS (This page )
c. COSATI Field/Group
21. NO. OF PAGES
319
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
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INSTRUCTIONS
1. REPORT NUMBER
Insert the EPA report number as it appears on the cover of the publication.
2. LEAVE BLANK
3. RECIPIENTS ACCESSION NUMBER
Reserved for use by each report recipient.
4. TITLE AND SUBTITLE
Title should indicate clearly and briefly the subject coverage of the report, and be displayed prominently. Sot subtitle, it' used, in smulicr
type or otherwise subordinate it to main title. When a report is prepared in more than one volume, repeat the primary title, add volume
number and include subtitle for the specific title.
5. REPORT DATE
Each report shall carry a date indicating at least month and year. Indicate the basis on which it was selected (e.g., date of issue, date of
approval, date of preparation, etc.),
6. PERFORMING ORGANIZATION CODE
Leave blank.
7. AUTHOR(S)
Give name(s) in conventional order (John R. Doe, J. Robert Doe, efc.J. List author's affiliation if it differs from the performing organi-
zation.
8. PERFORMING ORGANIZATION REPORT NUMBER
Insert if performing organization wishes to assign this number. ~~
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Give name, street, city, state, and ZIP code. List no more than two levels of an organizational hirearchy.
10. PROGRAM ELEMENT NUMBER
Use the program element number under which the report was prepared. Subordinate numbers may be included in parentheses.
11. CONTRACT/GRANT NUMBER
Insert contract or grant number under which report was prepared.
12. SPONSORING AGENCY NAME AND ADDRESS
Include ZIP code.
13. TYPE OF REPORT AND PERIOD COVERED
Indicate interim final, etc., and if applicable, dates covered.
74. SPONSORING AGENCY CODE
Insert appropriate code.
15. SUPPLEMENTARY NOTES
Enter information not included elsewhere but useful, such as: Prepared in cooperation with. Translation of. Presented a) conference of,
To be published in. Supersedes, Supplements, etc.
16. ABSTRACT
Include a brief ^200 words or less) factual summary of the most significant information contained in the report. If the report contains u
significant bibliography or literature survey, mention it here.
17. KEY WORDS AND DOCUMENT ANALYSIS
(a) DESCRIPTORS - Select from the Thesaurus of Engineering and Scientific Terms the proper authori/ed terms that identify the major
concept of the research and are sufficiently specific and precise to be used as index entries for cataloging.
(b) IDENTIFIERS AND OPEN-ENDED TERMS - Use identifiers for project names, code names, equipment designators, etc. Use open-
ended terms written in descriptor form for those subjects for which no descriptor exists.
(c) COSATI HELD GROUP - Field and group assignments are to be taken from the 1965 COSATI Subject Category List. Since the ma-
jority of documents are multidisciplinary in nature, the Primary Field/Group assignment^) will be specific discipline, area of human
endeavor, or type of physical object. The application(s) will be cross-referenced with secondary Held/Group assignments that will follow
the primary posting(s).
18. DISTRIBUTION STATEMENT
Denote releasability to the public or limitation for reasons other than security for example "Release Unlimited." Cite any availability to
the public, with address and price.
19. &20. SECURITY CLASSIFICATION
DO NOT submit classified reports to the National Technical Information service.
21. NUMBER OF PAGES
Insert the total number of pages, including this one and unnumbered pages, but exclude distribution list, il any.
22. PRICE
Insert the price set by the National Technical Information Service or the Government Printing Office, if known.
EPA Form 2220-1 (Rev. 4-77) (Reverse)
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