600783059
THE ENAMAP-2 AIR POLLUTION MODEL
FOR LONG-RANGE TRANSPORT OF SULFUR
AND NITROGEN COMPOUNDS
by
R. M. Endlich, K. C. Nitz,
R. Brodzinsky, and C. M. Bhumralkar
SRI International
333 Ravenswood Avenue
Menlo Park, CA 94025
Contract 68-02-3424
Project Officer
Terry L. Clark
Meteorology and Assessment Division
Environmental Sciences Research Laboratory
Research Triangle Park, North Carolina 27711
ENVIRONMENTAL SCIENCES RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711
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DISCLAIMER
This report has been reviewed by the Office of Research and Development,
U.S. Environmental Protection Agency, and approved for publication. Approval
does not signify that the contents necessarily reflect the views and policies
of the U.S. Environmental Protection Agency, nor does mention of trade names
or commercial products constitute endorsement or recommendation for use.
n
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ABSTRACT
This report describes the Eastern North American Model for Air Pollution
(EMAMAP-2) that simulates long-range air pollution transport over eastern
North America. The ENAMAP-2S version of the model uses SOX emissions data
inventories and standard daily weather reports to compute the airborne
concentrations of S0£ and sulfate and their deposition on the earth's
surface. ENAHAP-2S operates in a Lagrangian manner by tracking pollution
puffs emitted periodically over the grid domain. As each puff travels with
the winds, chemical processes occur, and the puff loses pollutants by dry and
wet deposition processes. For each grid cell the deposition amounts and
airborne pollution concentrations are summarized for periods generally taken
as one month.
The newest form of the model includes the influences of smoothed terrain
on the winds and divides the atmospheric boundary layer into three parts,
allowing pollution emissions to be partitioned among the layers. Vertical
mixing is controlled by diffusion coefficients computed from fields of wind
shear, stability, and mixing depth. The transformation and wet and dry depo-
sition rates are based on recent information; however, there are still sub-
stantial uncertainties about them.
Monthly average patterns of the concentration and deposition of sulfur
compounds have been computed for January and August 1977. The sensitivity of
the output fields to the values selected for input parameters (transformation
rate of SO? to sulfate, deposition rates, and partitioning of pollution
injections) has been determined, and the optimum values of the parameters are
given. The simulated airborne monthly concentrations of S02 and sulfate
generally agree reasonably well with measured air quality values; agreement
is within a factor of two.
ENAMAP-2N is a separate version of the model that applies to the long-
range transport of oxides of nitrogen. ENAMAP-2N is similar in structure to
ENAMAP-2S and represents what we believe to be the first attempt to simulate
the chemistry of nitrogen pollutants in a long-range Lagrangian transport
model. ENAMAP-2N uses NOX emissions data and treats the five principal
nitrogen compounds: NO, NOg, PAN, HN03 (all gases), and nitrates (aerosols).
All these compounds are deposited on the earth by dry and wet processes.
ENAMAP-2N has been run for the months of January and August 1977, and the
results appear to be quite reasonable.
This report was submitted in partial fulfillment of Contract 68-02-3424
by SRI International under the sponsorship of the U.S. Environmental Protec-
tion Agency; it covers the period 17 July 1980 to 31 December 1982.
iii
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CONTENTS
Abstract in
Figures vi
Tables viii
1. Introduction 1
2. Comparison of ENAMAP-1A and ENAMAP-2S 4
3. Detailed Description of ENAMAP-2S 9
Use of multiple layers 9
Terrain adjustment to winds 10
Emission input in layers 12
Vertical diffusion coefficients 12
Vertical mixing 15
4. Application of ENAMAP-2S 18
Comparison of ENAMAP-2S and ENAMAP-1A budgets 18
Model results 18
Interregional exchange tables 21
Significance of results 21
5. Sensitivity Tests of ENAMAP-2S 30
Varying the transformation rate 30
Varying the deposition rates 32
Varying the injection of nighttime emissions 32
Varying the vertical diffusion coefficients 3'3
Overall adjustment 33
6. ENAMAP-2N: Adaptation of the Model for Nitrogen
Emissions 37
Chemical transformations 37
Transformation rates 40
Deposition processes 40
Model results 43
7. Summary and Conclusions 47
References 49
Appendices 52
A. Comparison of ENAMAP-25 and ENAMAP-1A results for
sulfur compounds for August 1977 52
B. Interregional exchange tables for sulfur compounds 59
Part 1 January 1977 60
Part 2 August 1977 78
C. ENAMAP results for nitrogen componds 96
Part 1 January 1977 97
Part 2 August 1977 112
D. Interregional exchange tables for nitrogen compounds . . . .127
Part 1 January 1977 128
Part 2 August 1977 173
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FIGURES
Number Page
1 Functional parts of the ENAMAP-2 pollutant transport model .... 2
2 Model domain covering eastern North America 6
3 Summary of ENAMAP-2 transformation and deposition rates 8
4 Division of the atmospheric boundary layer into three parts
using terrain-foilowing coordinates 9
5 Map of smoothed terrain heights for the model domain 11
6 Annual S02 and sulfate emissions for 1977 13
7 Nighttime injection of emissions in layers 14
8 Mesh Geometry used in vertical mixing computations 17
9 S02 concentrations for January 1977 20
10 SOg dry deposition for January 1977 22
11 S02 wet deposition for January 1977 23
12 Sulfate concentrations for January 1977 24
13 Sulfate dry deposition for January 1977 25
14 Sulfate wet deposition for January 1977 26
15 Comparison of ENAMAP-2S concentrations for the nominal case
and using adjusted parameters 34
16 Comparison of ENAMAP-2S dry deposition for the nominal case
and using adjusted parameters 35
17 Comparison of ENAMAP-2S wet deposition for the nominal case
and using adjusted parameters ... 36
18 Far-field power plant plume simulation, 4.5 ppmC urban
hydrocarbon mixture, 1.0 ppm S02 38
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Number Page
19 Chemical reactions and rates used in the "five compound"
nitrogen algorithm 39
20 The steps used in calculating changes in nitrogen compounds .... 41
21 Illustration of the "five compound" algorithm for a
hypothetical puff 42
22 Calculated concentration of airborne N02 for January 1977 45
23 Calculated concentration of airborne PAN for August 1977 46
vn
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TABLES
Number Page
1 Elements and Parameters Used in the ENAMAP Programs 5
2 Transformation Rate for S02 and $04 Based on
Homogeneous Mechanisms ..... 6
3 S02 Dry Deposition Velocities by Land-Use Type 7
4 SO? Dry Deposition Velocities by Land-Use Type 7
5 Wet Deposition Rate for S02 and S0| Based
on the Precipitation Rate 8
6 Comparison of ENAMAP-1A and ENAMAP-2S Budgets for Illinois,
Indiana, and Ohio Emissions for January 1977 19
7 Comparison of ENAMAP-1A and ENAMAP-2S Budgets for Illinois,
Indiana, and Ohio Emissions for August 1977 19
8 Computed Sulfur Deposition Due to Interregional Exchanges
of Airborne Sulfur for August 1977 27
9 The Effects of Varying Parameters in ENAMAP-2S 31
10 Dry Deposition Velocities for Atmospheric Nitrogen Compounds ... 43
11 Wet Deposition Rates for Atmospheric Nitrogen Compounds
Expressed as Fraction of Rates for SOX 43
vm
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SECTION 1
INTRODUCTION
The transport of air pollution over long distances by winds has become
a topic of public concern in relation to air quality and also to acid rain.
SRI International (SRI) has developed a numerical model for calculating the
airborne concentration of air pollution and the deposition of pollution on
the earth's surface. This research has been sponsored by EPA for application
to eastern North America, and by Umweltbundesamt of the Federal Republic of
Germany for application to Europe (Johnson et a!., 1978; Bhumralkar et a!.,
1981). The model uses recent pollution emissions data. Standard weather
observations of temperature and wind (from radiosondes), as well as hourly
precipitation amounts, are analyzed in order to retain the spatial and
temporal detail of meteorological events. In the ENAMAP model, the emissions
data and meteorological data are represented on a grid that covers the
eastern parts of the United States and Canada. The model shows the patterns
of pollution from emission to deposition, and it calculates the exchanges of
airborne sulfur compounds and nitrogen compounds among various regions such
as states or provinces. These latter computations show how much pollution
originates locally and how much is carried in by winds from other areas of
the domain.
Previous SRI International reports covered the subject matter outlined
below:
• Bhumralkar et al. (1980a) described the basic structure of the ENAMAP
model. In this model, the emission puffs (comprised of S02 and
sulfates) are released every 12 hours from each emission cell and are
transported with the low-level winds in 3-hour time steps. During
each time step, the transformation of S02 to sulfate and the dry
and wet deposition amounts are computed in each receptor area.
• The application of ENAMAP-1 to data for January and August 1977 was
described by Bhumralkar et al. (1980b).
• Mayerhofer et al. (1981) described the revised model called
ENAMAP-1A, which covers a larger domain that includes southeastern
Canada. Also, the transformation and deposition rates were changed
to agree with recently published values. The monthly average concen-
trations of S02 calculated by the model were in fairly good agree-
ment with air quality measurements; however, the computed sulfate
concentrations were approximately twice the measured values. This
indicates that the transformation rate was too large or that the
sulfate deposition was. too low.
1
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In the present report, vie describe the further refinements that are
included in the model ENAMAP-2. The functional parts of ENAMAP-2 are shown
in Figure 1. The transformation and deposition rates are the same as in
ENAMAP-1A, except that the dry deposition rate for sulfate at night has been
made equal to the daytime rate in order to correct the previous use of
unrealistically low rates at night. The transport winds have been adjusted
for the effects of smoothed terrain on the flow. (This is done by making the
originally analyzed winds nondivergent.)
The atmospheric boundary layer has been divided into three parts.
Initially, the pollutant emissions are allocated to one or more of the
layers; thereafter, vertical mixing is controlled by vertical diffusion
coefficients calculated from grid-point analyses of wind shear, stability,
and mixing depth.
POLLUTION EMISSIONS
TRANSPORT BY WINDS
VERTICAL MIXING
CHEMISTRY Transformation, Dry Deposition, Wet Deposition
RESULTS Maps, Interstate Pollution Exchange Tables
VERIFICATION Comparison to Air Quality Measurements
Figure 1. Functional parts of the ENAMAP-2 pollutant transport model.
Section 2 of this report gives a comparison of results from ENAMAP-1A
and ENAMAP-2, and Section 3 describes in detail the special features of
ENAMAP-2. The calculations of sulfur pollutants for January and August 1977
and comparisons with measurements are described in Section 4. Section 5
describes sensitivity tests made with ENAMAP-2S (the S designates the version
for sulfur compounds). Values of model parameters that give the best
agreement with air quality data are presented. Section 6 discusses
modifications made to the model to enable it to be applied to NOX
emissions. A simplified representation of the complex chemistry of nitrogen
compounds is used in this version of the model (designated ENAMAP-2N). The
computed patterns of the nitrogen compounds are shown. Section 7 gives
conclusions and recommendations.
This study has attempted to strike a balance that represents the com-
plicated meteorological and chemical processes of air pollution within the
framework of a practical and efficient numerical model. Similar research
concerning long-range pollutant transport includes the European OECD-sponsored
Long-Range Transport of Air Pollutants (LRTAP) study (Ottar, 1978), and the
Sulfate Regional Experiment (SURE) in the United States. Comprehensive
reviews of long-range pollution modeling have been presented recently by
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SECTION 2
COMPARISON OF ENAMAP-1A AND ENAMAP-2S
The features of ENAMAP-1A, including its chemical transformation rate and
the algorithms used for wet and dry deposition, were discussed by Mayerhofer
et al. (1981). These features, along with the comparable features of the new
version, ENAMAP-2S, are summarized in Table 1. ENAMAP-2S uses the same grid
as ENAMAP-1A; the grid covers the eastern United States and southeastern
Canada as shown in Figure 2. ENAMAP-2S uses three layers to represent the
atmospheric boundary layer. The pollution emissions are subdivided appropri-
ately between the layers as described in detail in Section 3. Vertical dif-
fusion coefficients are calculated at layer boundaries from values of wind
shear and thermal stability; these coefficients control the mixing between
the layers (see Section 3). The transformation rate for S0£ to sulfate is
expressed as the sum of two components: a homogeneous transformation rate
(based on the work of Altshuller, 1979) and a heterogeneous transformation
rate. The values for the homogeneous component are a function of solar
insolation and are shown in Table 2 (from Mayerhofer et al., 1981). The
heterogeneous component is taken as 0.005 (0.5 percent h'1). The dry
deposition follows the development of She in et al., (1979) and depends on
land-use type (surface characteristics and vegetation), and thermal stability
as shown in Tables 3 and 4 (from Mayerhofer et al., 1981). Mayerhofer et
al., however, reduced the nighttime deposition velocities for both S02 and
sulfate to 0.07 cm s~^. For sulfates, this very low value appeared to be
unrealistic and to give too little deposition and too large concentrations
during the night, so in ENAMAP-2S the sulfate dry deposition values are the
same both day and night. The wet deposition rates are a function of rainfall
type (dependent on season) and rainfall rate following the work of Scott
(1978). The rates are shown in Table 5 (from Mayerhofer et al., 1981). The
chemical processes for sulfur compounds are summarized in Figure 3.
In this report we use the same sulfur emissions data for 1977 for the
eastern United States and southeastern Canada as used by Mayerhofer et al.
(1981), and also the same meteorological data, including the grid-point
analyses of transport winds and precipitation.
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TABLE 1. ELEMENTS AND PARAMETERS USED IN THE ENAMAP PROGRAMS
Element
Model
ENAMAP-1 A*
ENAMAP-2S
Number of layers
Grid size
Emission data
1
70 km
Data provided by season
3
Same as ENAMAP-1A
Same as ENAMAP-1A except
Domain
Puff frequency
Tracking increment
Weather data
Mixing height (km)
H = h0 + ;At
Puff height
Transport windspeed
(V) and direction
(0)
Vertical diffusion
Horizontal diffusion
SOg/SO? transformation
rate (h'1)
Dry deposition rates
(h-1)
SO 2
Wet deposition rates
(h-1)
S02 and
Eastern United States
and southeastern
Canada
12 hours
3 hours
Standard daily
observations
h0 = 1.3; C = -0.15
Same as mixing height
Based on surface and
850-mb winds inte-
grated over boundary
layer
Immediate uniform mixing
up to mixing height
Constant expansion rate
Depends on solar
insolation (see Table 2)
that the emissions may
be initially subdivided
between layers
Same as ENAMAP-1A
Same as ENAMAP-1A
Same as ENAMAP-1A
Same as ENAMAP-1A
Varies diurnally (clima-
tological values)
Not used explicitly
Same as ENAMAP-1A except
adjusted for terrain
effects
Mixing between layers is
controlled by diffusion
coefficients computed
from wind shear and
stability
Same as ENAMAP-1A
Same as ENAMAP-1A
Depends on surface char-
acteristics, stability,
and time of day (see
Table 3)
See Table 4
Depends on rain type and
rate (see Table 5)
Same as ENAMAP-1A
Same as ENAMAP-1A
Same as ENAMAP-1A
See Mayerhofer et al. (1981).
'A is a seasonal parameter equal to +1 in winter, -1 in summer, and 0 in
spring and fall.
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54.5° IN —
104.8° W
60.6° W
28.7° N —
— 54.5° N
I 103.5" W 71.3° W
Figure 2. Model domain covering eastern North America.
— 28.7° N
TABLE 2. TRANSFORMATION RATE (rT1) FOR SO2 AND SOJ
BASED ON HOMOGENEOUS MECHANISMS
Rate:
2[a + b In (latitude °N)]/100
Season
Summer
Fall/spring
Winter
Empirical Constants
a b
6.3 -1 .4
4.4 -1.0
2.5 -0.61
Transformation
Rate (h"1) at
35'N Latitude
0.0265
0.0169
0.0066
45°N Latitude
0.0194
0.0119
0.0036
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rAGLE 3. 5O2 DRY DEPOSITION VELOCITIES (cm s ) BY LAND-LiSc TYPE
Land-Use Type
Swamp
Marshland
Metropolitan city
Lake or ocean
Cropland and pasture
Cropland, woodland and
grazing pasture
Irrigated crops
Grazed forest
and woodland
Ungrazed forest
and woodland
Subhumid grassland and
semiarid grazing land
Open, grazed woodland
Desert shrubland
Slightly
Stable
0.45
0.25
0.55
0.35
0.25
0.55
0.25
0.25
0.25
0.25
0.25
0.25
Winter
Neutral
0.65
0.35
0.65
0.75
0.45
0.75
0.35
0.35
0.35
0.45
0.45
0.35
Slightly
Unstable
0.65
0.35
0.65
0.55
0.45
0.75
0.35
0.35
0.35
0.45
0.45
0.35
Slightly
Stable
0.55
0.05
0.05
0.35
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
Summer
Neutral
0.95
0.35
0.05
0.75
0.35
0.35
0.35
0.35
0.35
0.25
0.25
0.35
Slightly
Unstable
0.75
0.85
0.05
0.55
0.75
0.75
0.85
0.85
0.85
0.75
0.75
0.85
TABLE 4. SOJ DRY DEPOSITION VELOCITIES (cm s~1) BY LAND-USE TYPE
Land-Use Type
Swamp
Marshland
Metropolitan city
Lake or ocean
Cropland and pasture
Cropland, woodland and
grazing pasture
Irrigated crops
Grazed forest
and woodland
Ungrazed forest
and woodland
Subhumid grassland and
semiarid grazing land
Open, grazed woodland
Desert shrubland ^
Slightly
Stable
0.65
0.85
0.85
0.25
0.35
0.65
0.85
0.85
0.45
0.35
0.35
0.85
Winter
Neutral
0.75
0.95
0.95
0.35
0.55
0.85
0.95
0.95
0.95
0.55
0.55
0.95
Slightly
Unstable
0.75
0.95
0.95
0.35
0.45
0.85
0.95
0.95
0.95
0.45
0.45
0.95
Slightly
Stable
0.65
0.85
0.85
0.25
0.65
0.75
0.85
0.85
0.85
0.65
0.65
0.85
Summer
Neutral
0.85
0.95
0.95
0.35
0.85
0.85
0.95
0.95
0.95
0.85
0.85
0.95
Slightly
Unstable
0.85
0.95
0.95
0.35
0.85
0.85
0.95
0.95
0.95
0.85
0.85
0.95
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TABLE 5. WET DEPOSITION RATE (rT1) FOR S02 AND SC
BASED ON THE PRECIPITATION RATE, R (mm-1)
Rate: Kv
(aRb)
Pollutant
SO2
so4-
Season
Summer
Fall/spring
Winter
Summer
Fall/spring
Winter
Empirical
a
0.14
0.036
0.009
0.39
0.091
0.021
Constants
b
0.12
0.53
0.70
0.06
0.27
0.70
Wet Deposition
Rate (h~1) for
5 mm h~1 of Rain
0.1698
0.0845
0.0278
0.4295
0.1405
0.0648
CHEMICAL PROCESSES FOR SULFUR COMPOUNDS
TRANSFORMATION OF S02 TO S04=
DEPENDS ON SOLAR INSOLATION. VARIES FROM 0.01 rH (1%rH)
IN WINTER TO 0.04 h~1 IN SUMMER.
WET DEPOSITION RATE
S02: DEPENDS ON RAINFALL TYPE AND RATE. FOR 5 mm rr1 OF
RAIN, VARIES FROM 0.03 rr1 (WINTER) TO 0.17 rr1 (SUMMER).
S04": SIMILAR TO S02. FOR 5 mm h'1 OF RAIN, VARIES FROM 0.06
h-l (WINTER) TO 0.43 h'1 (SUMMER).
DRY DEPOSITION VELOCITY
S02: DEPENDS ON LAND CHARACTERISTICS AND VEGETATION, STA-
BILITY, SEASON AND TIME OF DAY. VALUES VARY FROM 0.05
cms'1 TO 0.95 cms'1.
S04=: SIMILAR TO S02 EXCEPT NO DEPENDENCE ON TIME OF DAY.
VALUES VARY FROM 0.25 cms-1 TO 0.95 cms-1.
Figure 3. Summary of ENAMAP-2 transformation and deposition rates.
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SECTION 3
DETAILED DESCRIPTION OF ENAMAP-2S
USE OF MULTIPLE LAYERS
In ENAMAP-1A the lower atmosphere was treated as a single layer in which
uniform mixing up to the mixing depth occurred immediately after release of
pollutants. This is a simplification that does not account for differences
between emissions from area sources (which may enter the atmosphere close to
the ground) and those from point sources (which enter several hundred meters
above ground). Also, vertical mixing is not instantaneous; it is dependent
on diffusion rates that vary from day to night and also depend on position
above or below the mixing depth.
In the interest of physical realism, in ENAMAP-2S we divided the lower
atmosphere into three layers. This is done using terrain-following coordi-
nates (sigma surfaces) that divide the boundary layer into proportionate
parts (Figure 4). The formula for the value of sigma (a) at height z (above
sea level) is
BOUNDARY LAYER TOP
(ADJUSTED SEASONALLY)
Figure 4. Division of the atmospheric boundary layer into three parts using terrain-following coordinates.
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z -
~ H(x,y) - hlx.y) '
where h(x,y) is the height of the terrain (above sea level), and H(x,y) is
the corresponding height of the boundary layer top at that time and place.
The a values are chosen so that for locations near sea level the lowest
surface is at anemometer height (10 m). The next a surface is chosen to be
at approximately 200 m above ground (for locations near sea level ). The
third CT surface is at 700 m (for locations near sea level), and the boundary
layer top is the uppermost CT surface. The boundary layer top is taken at
1150 m in winter 1450 m in summer, and 1300 m in spring or autumn, except
over a few points where the smoothed terrain is relatively high. Over high
terrain, the thickness of the boundary layer tends to be large during the
daytime (particularly in summer) and relatively small at night (particularly
when winds are light). We selected a value of 500 m as a typical minimum
boundary layer thickness over mountainous terrain.
TERRAIN ADJUSTMENT TO WINDS
The terrain within the ENAMAP domain is shown in Figure 5. The terrain
heights were selected from global terrain-height data obtained from the
National Center for Atmospheric Research (CAR) at Boulder, Colorado. The
NCAR magnetic tapes of global terrain data contain smoothed values at 30-
minute intersections of latitude and longitude. The values are approximately
50 km apart; we interpolated these data to obtain values at points of the
70 km ENAMAP grid. This smoothed terrain does not represent local maximum
and minimum values (such as mountain peaks or small valleys). The effects of
this smoothed terrain on winds are, therefore, on the subsynoptic scale and
do not include mesoscale phenomena such as mountain waves or the trapping of
air under inversions in small valleys.
We have computed the influence of the smoothed terrain on the boundary
layer flow in a manner similar to that described by Bhumralkar et al . (1980c)
and Endlich et al . (1982). The grid point winds as initially estimated are
modified so that the flow passes over and around the mountain barriers of
Figure 5 in a realistic manner. This is done by adjusting the flow so that
it becomes nondivergent. The steps in the calculation are:
• Step 1 : From the 850-mb and 10-m wind analyses, we compute the winds
on the internal a surfaces by interpolation, assuming that u and v
vary linearly with the logarithm of the height above terrain. This
gives smooth changes of u and v (and wind speed and direction) with
height.
• Step 2: We make the reasonable assumption (supported by the computa-
tions of Bhumralkar et al . , 1980c) that the flow is parallel to the
surfaces. For each volume element (defined by grid points and sigma
surfaces) the inflow or outflow is computed. The inflow on a given
face of an element is proportional to the winds normal to the face
and to the area of the face. Ideally, the net inflow for a volume
element should be zero. If it is not, small alterations are made to
the wind components to make the flow nondivergent.
10
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400
200 400
400
800 400 200
Figure 5. Smoothed terrain heights (m).
11
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This type of iterative solution has been described by Endlich (1967),
Liu and Goodin (1976), and Chen (1980). The method works well for the ENAMAP
applications and it has the advantage that altered wind values can be com-
puted separately for each layer, thereby minimizing computer storage and
running time. (The results of applying this methodology to data for January
1977 are described later.)
EMISSION INPUT IN LAYERS
The emissions used in ENAMAP-2S (based on data from the SURE and NEDS
inventories and from Environment Canada) are shown in Figure 6. (More recent
information indicates that these values may be as much as 25 percent too high
in industrial areas.) The rationale for the initial vertical injection of
emissions, as decided in consultation with the Project Officer, is the
following. In the daytime, pollutants become well mixed within approximately
one-half hour after they are emitted. This time interval is equivalent to a
travel distance of about 15 km or less even for strong winds, and this
distance is much smaller than the receptor grid size (70 km). There-
fore, we assume instantaneous, complete mixing within the three layers of the
model during daylight hours. Computationally, this is achieved by dividing
the emissions between the layers in proportion to the layer depths, thereby
giving uniform initial concentrations.
At night, mixing is, of course, limited by stable lapse rates. For
point sources of either S0£ or NOX, the typical plume rise is several hun-
dred meters (Briggs, 1972); therefore, point sources initially enter layer 2
(see Figure 7). The 1977 $62 emissions were predominantly (92 percent) from
point sources (U.S. Environmental Protection Agency, 1980); therefore, at
night all S02 emissions are placed initially in layer 2. NOX pollutants
are divided approximately evenly between point and area sources. Point
source NOX is placed initially in layer 2 for the same reasons given
above. On the other hand, approximately 90 percent of NOX area emissions
come from vehicles; therefore, as shown in Figure 7, all NOX area emissions
are placed initially in layer 1.
VERTICAL DIFFUSION COEFFICIENTS
The layers shown in Figure 4 are also used in the vertical diffusion
computation. We compute vertical eddy-diffusion coefficients, D2, at layer
boundaries as a function of wind shear and stability (following Bhumralkar,
1976) using the formulas:
DZ = L2OV/az)(l - <*(S-4)), (Unstable) (2)
Dz = L2OV/az)/(l + «(S-4), (Stable) (3)
9 9 1/2
where av/az = [(au/azr + (av/az) 1
The stability parameter (S) is computed from solar insolation (latitude and
time of day) and wind speed following Turner (1969); it varies from 1
12
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>
" 7ii/SC/i > "^ -^\ovx0'i
5< -i^^^'rvr-r1
(a) SO.
40
13
<$• ••-.-.'•
'-'• :'(&>•
48
^
IW
V"
2
10
-;--V©- --.. W? -.. \r^ : '- ^'
^ "•^••?:-: •• "---® ,- v2A^-
§5\ ,'ff\ -^ ' J2;- '< _ _ /^r' •^••/,?)
' (('r'^''
/V*
W(A,2i^^
^ ...reg-'/^
(b) SULFATE
-1
Figure 6. Annual SO, and sulfate emissions for 1977 (10 ton km )
13
-------
1450
SUMMER
1150
WINTER
— LAYER 3
o
oc
uJ 700
O
co
01
I
200
Figure 7. Nightime injection of emissions in layers.
14
-------
(unstable) to 6 (stable). (A value of 4 is neutral.) The mixing length (L)
depends on height above the terrain; it is defined as 0.4z/(l+0.4z/13.5).
The empirical parameter a is 3.
The above formulas are appropriate for giving diffusion coefficients (in
the units m2 s~^) beneath the mixing depth; however, the large diurnal
variability in the mixing depth needs to be considered. At each a surface in
a vertical column, a check is needed to determine whether the point is above
the mixing depth, and if it is, the diffusion coefficient must be reduced to
an appropriately low value. This will give a profile of diffusion
coefficients that increases away from the ground and drops off to a low value
above the mixing depth.
We have introduced the mixing depth into the computation of Dz in the
following way: climatological values of mixing depth for the proper time of
year are determined at grid points for early morning and afternoon from maps
given by Holzworth (1972). (The morning values represent urban areas and are
higher than in non-urban regions.) Grid point values of mixing depths are
entered as arrays in VERTDF, the program that computes Dz. The afternoon
values of mixing depth are used to represent the daytime hours of 10,13, 16,
and 19 EST, and the morning values are used to represent the nighttime hours.
Each point in the three-dimensional grid of ENAMAP is tested to determine if
it is above the mixing depth appropriate to that location and hour.
The empirical factors in Equations 2 and 3 have been adjusted so that
values of Dz lie in the range from 1.5 to 10.0 m2 s~^ for points
beneath the mixing depth. The higher values are, of course, associated with
large wind shear and thermal instability. For points above the mixing depth,
Dz is set to 1.0 m2 s'^during daytime hours, and to 0.5 m2 s~1
during nighttime hours. These values are typical of weak vertical diffusion.
VERTICAL MIXING
The vertical diffusion expression
r~ T
— ^ in Ow I / «\
at " az L z az J m
is represented by the finite difference form
AZj-ihj AZJ hj
at
LJ-IJJ' LJ-lJ J J-l '
(5)
L Z0hj J
where:
Cj is the concentration of a species at the jth spatial mesh point
AZJ is the distance between the jth and (j+J_)th mesh points
hj is the cell height, defined by hj = (zj_i + Zj)/2
15
-------
Dj-i/2 is the diffusion coefficient at the midpoint between the (j_-J_)
arsd jth mesh points
Dj+-|/2 is the diffusion coefficient at the midpoint between the jth
and (j+J_)th mesh points.
There is an equation of this type for each concentration in the vertical (in
our case, for three layers). The geometry of the mesh is shown in Figure 8.
In the Crank-Nicolson method (see Crank, 1967) one solves simultaneously
for a new set of concentrations in all layers of a column. Denoting current,
past, and predicted values of concentration by C°, C", and C+ respectively,
the finite-difference approximation for the local change of concentration at
point n is
C+ - C"
dC m m
If we assume for simplicity that the grid increments are uniform, then the
space second derivative at point m is represented by
32C Cm+l " 2Cm + Cm-l
At time T+(l/2) T
8C°
Also the space derivative at time T+(1/2)AT is taken as the average of Equa-
tion 7 and a corresponding equation at T + AT. This leads to
AT
|^__ ^BW O
m m 2(AZ)2
Cl) -'fc + cj) + (£,+£,) (9)
The matrix of simultaneous equations for the points in a column has non-
zero coefficients only on the diagonal and immediately adjacent to it. The
solution is obtained using an efficient algorithm for the tridiagonal matrix
given by Todd (1962).
The boundary conditions used are as follows: For the lower boundary
condition, we use an image point and assume its concentration is the same as
that in layer 1 (see Figure 4). This is tantamount to assuming zero flux at
the ground and is consistent with the input of pollution puffs. For the
upper boundary conditions, one could specify the flux (generally upwards) if
it were known; unfortunately it is usually not known. It would probably be
feasible to set the upward flux on an arbitrary basis, e.g., as a fraction
of the pollutant mass in the three layers of the column. For the present,
however, the upward flux has been set to zero.
16
-------
AZ:
Di-Va -A
C;
AZ:
C;j
Figure 8. Mesh geometry used in vertical
mixing computations.
17
-------
SECTION 4
APPLICATION OF ENAMAP-2S
ENAMAP-2S has been run for the months of January and August 1977 with
the emissions data and meteorological fields used previously by Mayerhofer
et al. (1981). Computations were made separately for each of the 41 regions
(states and provinces) that compose the computational domain and were com-
bined to give overall results. The large amount of computation involved can
be seen from the following example. For the emissions for Ohio (1 region out
of the total of 41) for January 1977, ENAMAP tracked approximately 1,000 puffs
for a total of approximately 24,000 tracking steps, and the average puff was
followed for 78 hours before passing out of the model domain. The results
are shown below in the form of maps and exchange tables for airborne concen-
trations and dry and wet deposition of S02 and sulfate, and comparisons are
given with the previous results from ENAMAP-1A.
COMPARISON OF ENAMAP-2S AND ENAMAP-1A BUDGETS
The computations for the three states of Ohio, Indiana, and Illinois may
be used to compare the two models for January (Table 6) and August (Table 7).
For the S02 computations, the two models do not differ to a major degree.
For sulfate, comparison shows greatly increased dry deposition in ENAMAP-2S.
This is due mainly to the replacement of low nighttime rates with the same
rates that are used in the daytime. Also, sulfate wet deposition is de-
creased. Combined dry and wet deposition of sulfate computed by ENAMAP-2S
is approximately 90 percent greater than ENAMAP-1A for January and only 8
percent greater for August. The differences between the budgets of the two
models are mainly due to the different rates used for nighttime dry deposi-
tion of sulfate rather than to differences in their vertical structure or in
the injection of emissions.
MODEL RESULTS
The average airborne S02 concentration field computed using ENAMAP-2S
with emissions from all regions for the month of January 1977 is shown in
Figure 9. The concentrations shown are those for the lowest layer of the
model. The pattern of greatest amounts reflects the largest emission sources
in the Ohio River Valley and extends downwind to the East Coast. It is
assumed that the air coming into the domain from the west is pollution free,
which is not entirely true, as shown by the measured concentrations in
eastern Colorado and western Texas (Figure 9c). The S0£ concentrations
given by ENAMAP-2S are slightly higher than those given by ENAMAP-1A. The
patterns of computed and measured concentrations are in general agreement;
however, the computed values are smoother and have less small-scale structure.
18
-------
TABLE 6. COMPARISON OF ENAMAP-7A AND ENAMAP-2S BUDGETS
FOR ILLINOIS, INDIANA, AND OHIO EMISSIONS (kton)
FOR JANUARY 1977
Process
Total emitted
Wet deposition
Dry deposition
Flux*
Transformation (S02 50$)
S0|
Emitted
Total emitted and transformed
Wet deposition
Dry deposition
Flux*
ENAMAP-1A
645.1
-7.2
-213.5
-165.4
-259.0
15.3
403.8
-11.7
-131.7
-260.4
ENAMAP-2S
645.1
-7.5
-242.6
-126.7
-268.4
15.3
417.9
-8.6
-262.6
-146.7
*Flux is the amount of S02 or $04 that was transported
out of the model domain by the wind.
TABLE 7. COMPARISON OF ENAMAP-1A AND ENAMAP-2S BUDGETS
FOR ILLINOIS, INDIANA, AND OHIO EMISSIONS (kton)
FOR AUGUST 1977
Process
so2
Total emitted
Wet deposition
Dry deposition
Flux*
Transformation (S02 S02p
50$
Emitted
Total emitted and transformed
Wet deposition
Dry deposition
Flux*
ENAMAP-1A
582.9
-164.7
-68.1
-7.5
-342.3
12.4
525.9
-305.7
-170.7
-49.5
ENAMAP-2S
582.9
-153.9
-88.7
-1.7
-338.5
12.4
520.3
-238.4
-273.4
-8.5
*Flux is the amount of S0£ or SOzf that was transported
out of the model domain by the wind.
19
-------
(a) CALCULATED BY ENAMAP-2S
(b) CALCULATED BY ENAMAP-1A
Y-S-r. * iy««, ' ',
' X i.^"' 32 '
r66/,B B . J..-,
u3/^l/*4 (' 5ftI|T;«\IB-'
32
(c) MEASURED
Figure 9. SO, concentrations (^g m~3) for January 1977
20
-------
The S02 monthly average dry deposition computed using ENAMAP-2S is
shown in Figure lOa. The deposition is based on the SCb concentration in
the lowest layer of the model. The values are slightly larger than those
given by ENAMAP-1A. The 502 wet deposition amounts from ENAMAP-2S (based
on precipitation amounts and the total S02 in the three layers) are shown
in Figure lla. They are quite similar to tnose computed by ENAMAP-1A (Fig-
ure lib).
As shown in Table 6, the amounts of S02 transformed to sulfate are
approximately the same in ENAMAP-2S and ENAMAP-1A. The monthly average air-
borne concentrations of sulfate from the two models are shown in Figure 12.
The differences are minor, and both sets of values are consistently larger
than the measured concentrations (Figure 12c). Figure 13 shows that the
ENAMAP-2S sulfate dry deposition is somewhat larger than for ENAMAP-1A. As
mentioned previously, this is due to the increased rate used at night (the
same as the daytime rate) in ENAMAP-2S. The ENAMAP-2S wet deposition of
sulfate is about the same as that for ENAMAP-1A (Figure 14).
Maps of ENAMAP-2S and ENAMAP-1A results for August 1977 similar to those
shown above are given in Appendix A.
INTERREGIONAL EXCHANGE TABLES
Complete exchange tables (showing the total amount of sulfur deposited
in each state or province and the places where it originated) are given in
Appendix B. Table 8 (for August 1977) is an example. (Total sulfur in kilo-
tons is computed as S = S02/2 + SO^/S.) An example of how to interpret this
table follows: The values along the diagonal of the matrix represent the
amount deposited within each emitter region from its own emissions; for ex-
ample, 26.4 kton of the sulfur depositions within Alabama (Emitter Region 1)
came from its own emissions. Similarly, Illinois (Emitter Region 7) receives
from itself 40.6 kton of sulfur deposition. The values in each column (for a
given emitter region) show the amount of deposition it received from each of
the other emitter regions. For example, Indiana (Emitter Region 8) received
1.5 kton from Alabama, 0.1 kton from Arkansas, 15.3 kton from Illinois, and
so forth.
SIGNIFICANCE OF RESULTS
The computations discussed above show that the ENAMAP-2S results aver-
aged for a month are very similar to those obtained previously with ENAMAP-1A
(Mayerhofer et al., 1981), except in regard to the dry and wet deposition of
sulfate. The use in ENAMAP-2S of three vertical layers, nighttime emissions
introduced into layer 2, and transport winds corrected for smoothed terrain
did not substantially change the results compared to the use of a single mixed
layer and uncorrected winds in ENAMAP-1B. This indicates that the effects of
the greater complexity of ENAMAP-2S are smoothed out over a period as long as
a month. For example, the nighttime emissions injected into layer 2 mix down-
ward on succeeding days so that low-level concentrations and depositions are
fairly close to those computed using a single mixed layer. On the other hand,
for particular short-term episodes we expect that significant differences will
exist between the results of the two models. This has not yet been verified.
21
-------
(a) CALCULATED BY ENAMAP-2S
(b) CALCULATED BY ENAWIAP-1A
Figure 10. SO- dry deposition (mg m~2) for January 1977.
22
-------
p
V.
US
(a) CALCULATED BY ENAMAP-2S
(b) CALCULATED BY ENAMAP-1A
Figure 11. SO, wet deposition (mg nrf2) for January 1977
23
-------
-15 00—\/
(a) CALCULATED BY ENAMAP -2S
(b) CALCULATED BY ENAMAP-1A
(c) MEASURED
Figure 12. Sulfate concentrations (jug m ) for January 1977.
24
-------
(a) CALCULATED BY ENAMAP-2S
V
(b) CALCULATED BY ENAMAP-1A
Figure 13. Sulfate dry deposition (mg m~2) for January 1977.
25
-------
(a) CALCULATED BY ENAMAP-2S
(b) CALCULATED BY ENAMAP-1A
_**
Figure 14. Sulfate wet deposition (mg m ) for January 1977.
26
-------
TABLE 8. COMPUTED SULFUR DEPOSITION DUE TO INTERREGIONAL
EXCHANGES OF AIRBORNE SULFUR FOR AUGUST 1977
EMITTER
REGION
1
2
3
4
5
6
7
a
9
10
11
12
13
U
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
ALABAMA
ARKANSAS
COLORADO
OEL/NO/OC
FLORIDA
GEORGIA
ILLINOIS
INDIANA
IOWA
KANSAS
KENTUCKY
LOUISIANA
MAINE
MICHIGAN
MINNESOTA
HISS.
MISSOURI
MONTANA
NEBRASKA
NH/VT
NEW JERSEY
NEW MEXICO
NEW YORK
N CAROLINA
N DAKOTA
OHIO
OKLAHOMA
PENN.
RI/MA/CT
S CAROLINA
S DAKOTA
TENNESSEE
TEXAS
VIRGINIA
M VIRGINIA
WISCONSIN
MANITOBA
N BRUNS
ONTARIO
QUEBEC
NEWFOUND
TOTAL
1
26.4
.0
C.
.0
.6
7.9
.2
.4
.0
0.
1.2
.5
0.
.0
0.
.5
.1
0.
0.
0.
0.
0.
0.
.6
0.
.2
0.
.0
0.
.6
0.
1.2
.0
.2
.1
.0
0.
0.
0.
0.
0.
CONTRIBUTIONS TO
234
3.0
1.3
0.
.0
.1
.3
2.6
.4
.0
.0
.2
1.1
0.
0.
.0
.7
1.4
0.
.0
0.
0.
0.
0.
.0
0.
0.
.1
0.
0.
.0
0.
1.8
.4
.0
.0
.0
0.
0.
0.
0.
0.
.0
.0
0.
.0
0.
.0
0.
0.
.0
.0
0.
.0
0.
0.
0.
.0
.0
0.
.0
0.
0.
0.
0.
.0
.0
0.
.0
0.
0.
.0
.0
.0
.2
0.
0.
0.
0.
0.
0.
0.
0.
.0
.0
0.
5.0
.0
.0
.1
.2
.0
0.
.4
.0
0.
.0
.0
.0
.0
0.
0.
0.
.2
0.
.1
.4
0.
2.2
0.
5.9
.0
.0
0.
.1
0.
3.0
4.0
.0
0.
0.
.0
0.
0.
S DEPOSITIONS WITHIN RECEPTOR REGIONS
5 6 7 8 9 10 11
4.5
.0
0.
.0
2.7
1.0
0.
.0
0.
0.
.0
.5
0.
0.
0.
.2
.0
0.
0.
0.
.0
0.
0.
.2
0.
0.
0.
.0
0.
.3
0.
.0
.0
.0
.0
0.
0.
0.
0.
0.
0.
4.0
.0
0.
.1
1.2
16.3
.0
.1
0.
0.
.2
.2
0.
0.
0.
.1
.0
0.
0.
0.
.0
0.
0.
1.9
0.
.0
0.
.0
0.
3.4
0.
.5
.0
.7
.1
0.
0.
0.
0.
0.
0.
1.0
.3
0.
0.
.0
.0
40.6
3.8
.9
.1
.4
.2
0.
.2
.3
.1
13.3
0.
.0
0.
0.
0.
0.
.0
.0
.0
.1
0.
0.
.0
.0
.8
.2
.0
.0
1.2
0.
0.
.0
0.
0.
1.5
.1
0.
.0
.0
.2
15.3
27.0
.2
.0
3.2
.0
0.
.9
.1
.0
2.4
0.
.0
0.
0.
0.
0.
.0
.0
.4
.0
0.
0.
.0
.0
2.0
.0
.0
.0
.6
0.
0.
.0
0.
0.
.0
.0
0.
.0
.0
.0
3.0
.0
5.8
.3
.0
.1
0.
.0
.8
.0
3.2
0.
.2
0.
0.
0.
0.
.0
.1
0.
.3
0.
0.
.0
.0
.0
.3
.0
0.
.7
.0
0.
0.
0.
0.
.1
.0
0.
.0
.0
.0
.0
.0
.2
.6
.0
.1
0.
0.
.0
.0
3.2
0.
.0
0.
0.
0.
0.
.0
.0
0.
1.1
0.
0.
.0
.0
.1
1.4
.0
0.
0.
0.
0.
0.
0.
0.
3.6
.1
0.
.0
.0
1.4
4.5
10.7
.0
0.
29.4
.0
0.
.4
.0
.1
.6
0.
.0
0.
0.
0.
0.
.5
0.
3.7
.0
0.
0.
.1
0.
8.4
.0
.3
.8
.2
0.
0.
.0
0.
0.
12
7.4
.1
0.
.0
.8
1.1
.4
.2
.0
.0
.4
10.8
0.
0.
0.
2.4
.1
0.
0.
0.
0.
0.
0.
.1
0.
0.
.0
.0
0.
.4
0.
.8
.6
.0
.0
0.
0.
0.
0.
0.
0.
13
.0
.0
0.
.0
0.
.0
.4
.9
.0
.0
.2
.0
4.8
2.6
.0
.0
.1
0.
.0
2.1
.0
0.
3.0
.0
.0
2.4
.0
2.1
.1
.0
.0
.0
.0
.0
1.7
.1
.0
.2
2.5
3.5
0.
14
.2
.0
0.
0.
0.
.0
4.7
5.8
.7
.0
.3
.0
0.
14.2
1.3
.0
.5
0.
.0
0.
0.
0.
0.
.0
.0
.1
.0
0.
0.
.0
.0
.3
.0
0.
0.
5.5
.0
0.
1.4
0.
0.
15
0.
.0
0.
Q.
0.
0.
.0
0.
.8
.0
0.
0.
0.
.0
3.8
0.
.2
0.
.0
0.
0.
0.
0.
0.
.2
0.
.0
0.
0.
0.
.0
0.
.0
0.
0.
.2
.2
0.
.0
0.
Q.
TOTAL (KTON S)
40.4 13.6
.3 22.0 9.4 28.8 63.4 59.0 15.0 6.8 64.6 25.5 26.8 35.1 S.5
27
-------
TABLE 8. (Continued)
EMITTER
REGION
TOTAL CONTRIBUTIONS TO
16 17 18 19
S OPPOSITIONS WITHIN RECEPTOR REGIONS
20 21 22 23 24 25 26
27
28
29
30
1 ALABAMA
2 ARKANSAS
3 COLORADO
^ OEL/ND/OC
5 FLORIDA
6 GEORGIA
7 ILLINOIS
8 INDIANA
9 IOWA
10 KANSAS
11 KENTUCKY
12 LOUISIANA
13 MAINE
U MICHIGAN
15 MINNESOTA
16 MISS.
17 MISSOURI
18 MONTANA
19 NEBRASKA
20 NH/VT
21 NEW JERSEY
22 NEW MEXICO
23 NEW YORK
24 N CAROLINA
25 N DAKOTA
26 OHIO
27 OKLAHOMA
28 PENN.
29 RI/MA/CT
30 S CAROLINA
31 S DAKOTA
32 TENNESSEE
33 TEXAS
34 VIRGINIA
35 W VIRGINIA
36 WISCONSIN
37 MANITOBA
33 N BRUNS
39 ONTARIO
40 QUEBEC
41 NEWFOUND
TOTAL (KTON S)
20.4
.1
0.
.0
.5
1.6
1.0
1.3
.0
.0
2.2
1.3
0.
.0
0.
2.8
.Z
0.
0.
0.
0.
0.
0.
.2
G.
.0
.0
.0
0.
.3
0.
3.6
.0
.0
.0
.0
0.
0.
0.
0.
0.
.6
.5
0.
0.
.0
.0
6.9
.6
.4
.3
.1
.5
0.
.0
.1
.2
19.3
0.
.0
0.
0.
0.
0.
.0
.0
0.
.6
0.
0.
.0
.0
.5
.5
.0
.0
.0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
c.
0.
0.
c.
0.
0.
0.
0.
0.
0.
0.
0.
0.
.0
0.
0.
0.
0.
0.
.0
a.
c.
0.
0.
0.
.0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
.0
.0
0.
.0
0.
.0
.0
0.
.2
.1
0.
.0
0.
c.
.0
.0
.1
0.
.1
0.
0.
0.
0.
.0
.0
0.
.1
0.
0.
.0
.0
.0
.2
.0
0.
0.
0.
0.
0.
0.
0.
.0
.0
a.
.1
0.
.0
.2
.7
.0
.0
.2
.0
.3
1.5
.0
.0
.0
0.
c.
2.1
.0
0.
3.8
.0
0.
1.8
.0
3.1
.1
.0
0.
.0
.0
.0
1.4
.1
.0
0.
1.7
.8
0.
.0
.0
0.
1.1
.0
.0
.0
.1
.0
0.
.2
0.
0.
.1
.0
.0
.0
a.
0.
.0
4.3
0.
2.3
.0
0.
1.2
0.
3.5
.0
.0
0.
.0
0.
.5
1.4
.0
0.
0.
.0
0.
0.
.0
.0
a.
.0
.0
.0
0.
0.
0.
.0
0.
.0
0.
0.
0.
.0
.0
0.
,0
0.
0.
0.
0.
.0
0.
0.
.0
0.
0.
.0
0.
.0
.6
0.
0.
0.
0.
0.
0.
0.
0.
.0
.0
0.
.3
.0
.0
1.3
2.8
.0
.0
1.5
.0
0.
6.3
.0
.0
.2
0.
.0
.1
1.0
0.
9.9
.0
.0
12.5
.0
11.0
.1
.0
.0
.1
.0
.2
7.8
.4
.0
0.
4.9
.3
0.
.3
.0
0.
.5
.0
1.2
.1
.1
0.
0.
.4
0.
0.
.0
0.
.0
.0
0.
0.
0.
.2
0.
.0
13.5
0.
.5
0.
.4
.0
2.7
0.
1.3
0.
4.5
.8
0.
0.
0.
.0
0.
a.
0.
0.
0.
C.
0.
0.
0.
0.
.0
.0
0.
0.
0.
0.
.0
0.
.0
0.
.0
0.
0.
0.
0.
0.
.4
0.
.0
0.
0.
0.
.0
0.
.0
0.
0.
0.
.1
0.
.0
0.
0.
.9
.0
0.
.0
.0
.6
5.5
20.5
.0
.0
18.1
.0
0.
6.3
.1
.0
1.0
0.
.0
0.
0.
0.
0.
.2
.0
25.5
.0
.6
0.
.0
.0
1.1
.0
.0
6.0
.4
0.
0.
.3
0.
a.
.2
.1
Q.
.0
.0
.0
.2
.0
.0
.1
.0
.6
0.
c.
c.
.1
1.4
0.
.0
0.
0.
0.
0.
.0
0.
0.
2.0
0.
0.
.0
0.
.1
2.3
.0
0.
0.
0.
0.
0.
0.
0.
.0
.0
c.
1.1
.0
.0
.7
4.0
.0
.0
3.2
.0
0.
2.6
.0
.0
.2
0.
0.
0.
.4
0.
.9
.0
.0
20.1
.0
34.0
0.
.0
0.
.2
.0
.7
26.7
.2
0.
0.
.7
0.
Q.
.0
.0
0.
.4
0.
.0
.0
.3
.0
0.
.3
.0
.0
.2
.0
.0
.0
0.
0.
1.5
.9
0.
6.8
.0
0.
1.8
.0
5.2
1.8
.0
0.
.0
0.
.1
2.4
.1
0.
0.
.2
.0
0.
.0
.0
0.
.1
.0
1.1
.0
.0
0.
0.
.1
.0
0.
0.
0.
.0
.0
0.
0.
0.
.0
0.
.0
2.7
0.
.1
0.
.1
.0
7.5
0.
.0
0.
.5
.1
0.
0.
0.
0.
0.
0.
35.5 31.3
.0
.9 17.9 14.8
.6 60.8 26.6
.6 87.2 7.2 95.8 22.1 12.4
28
-------
TABLE 8. (Concluded)
EMITTER
REGION
TOTAL CONTRIBUTIONS TO
31 32 33 34
S DEPOSITIONS WITHIN RECEPTOR REGIONS
35 36 37 38 39 40 41
ALABAMA
ARKANSAS
COLORADO
OEL/HD/DC
FLORIDA
GEORGIA
7 ILLINOIS
8 INDIANA
9 IOWA
10 KANSAS
11 KENTUCKY
12 LOUISIANA
13 MAINE
14 MICHIGAN
15 MINNESOTA
16 MISS.
17 MISSOURI
18 MONTANA
19 NEBRASKA
NH/VT
NEW JERSEY
22 NEW MEXICO
23 NEW YORK
24 N CAROLINA
25 N DAKOTA
26 OHIO
27 OKLAHOMA
28 PENN.
RI/MA/CT
S CAROLINA
S DAKOTA
32 TENNESSEE
33 TEXAS
34 VIRGINIA
35 U VIRGINIA
36 WISCONSIN
37 MANITOBA
38 N BRUNS
39 ONTARIO
40 QUEBEC
41 NEMFOUNO
20
21
29
30
31
.0
.0
0.
c.
0.
0.
0.
0.
.0
.0
0.
.0
0.
0.
.0
.0
.0
0.
.1
0.
0.
0.
0.
0.
.5
0.
.0
0.
0.
0.
.1
.0
.0
0.
0.
0.
.0
c.
0.
0.
0.
10.2
.1
0.
.0
.0
4.5
2.8
2.5
.0
.0
7.7
.0
0.
.0
.0
.1
.3
0.
.0
0.
0.
0.
0.
.8
0.
.6
.0
0.
0.
.2
0.
14.2
.0
.4
.2
.1
0.
0.
0.
0.
0.
5.1
.3
0.
.0
.2
.9
.5
.0
.0
.0
.1
7.6
0.
0.
0.
1.1
.3
0.
.0
0.
0.
0.
0.
.1
0.
0.
.1
.0
0.
.2
0.
.8
14.0
.0
0.
0.
0.
0.
0.
0.
0.
.5
.0
0.
2.2
.0
.5
.2
.2
.0
0.
1.3
0.
0.
.0
0.
.0
.0
0.
0.
0.
.2
0.
.1
3.5
0.
1.3
0.
2.5
.0
.2
0.
1.8
0.
15.1
4.3
.0
0.
0.
.0
0.
0.
.2
.0
0.
.2
.0
.6
.5
1.7
.0
0.
4.9
.0
0.
.4
.0
.0
.0
0.
0.
0.
.0
0.
.0
.2
0.
14.1
.0
4.5
0.
.0
0.
1.3
.0
2.1
23.3
.0
0.
0.
.0
0.
0.
.0
.0
0.
0.
0.
0.
3.0
.3
2.5
.1
.0
.0
0.
.3
5.9
.0
1.0
0.
.0
0.
0.
0.
0.
0.
.0
0.
.1
0.
0.
0.
.0
.0
.1
0.
0.
9.6
.0
0.
.0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
.0
0.
0.
0.
0.
0.
.0
0.
0.
0.
.0
0.
0.
0.
0.
0.
.1
0.
0.
0.
0.
0.
.0
0.
0.
0.
0.
0.
.2
0.
.0
0.
0.
.0
.0
0.
.0
0.
.0
.1
.3
.0
.0
.1
.0
1.7
1.0
.0
.0
.0
0.
.0
.8
.1
0.
1.7
.0
.0
1.6
.0
1.2
.4
.0
.0
.0
.0
.0
.9
.1
.0
2.8
1.3
2.2
0.
.3
.0
0.
0.
0.
.1
5.7
8.6
.7
.0
3.4
.0
0.
30.4
3.3
.0
.7
0.
.0
0.
0.
0.
1.9
.0
.1
6.1
.0
1.5
0.
.0
.0
.5
.0
.0
.3
7.0
.4
0.
28.7
2.0
0.
.0
.0
0.
0.'
0.
.0
2.7
3.3
.1
.0
1.4
.0
.0
8.6
.9
.0
.5
0.
.0
.0
0.
0.
1.7
.0
.0
2.3
.0
.6
.0
.0
.0
.3
.0
.0
.4
2.7
.1
.6
21.3
28.1
0.
0.
.0
0.
0.
0.
0.
.1
.1
.0
.0
.0
0.
.0
.3
.0
0.
.0
0.
.0
.0
0.
0.
.0
0.
.0
.0
.0
.0
0.
0.
.0
.0
.0
0.
0.
.0
.0
.0
.9
1.5
0.
TOTAL (KTON S)
.8 44.7 31.5 34.0 54.1 22.9
.3 16.5 102.0 75.8 3.1
29
-------
SECTION 5
SENSITIVITY TESTS OF ENAMAP-2S
The meteorological and chemical processes occurring in the atmospheric
boundary layer are complex, and the model algorithms simulate them to only a
limited extent. Also, meteorological measurements are scattered in space and
time, and analyses based on these reports are imperfect. Emissions estimates
made by different investigators vary significantly, indicating that their
degree of uncertainty is approximately _+20 percent. Chemical reaction rates
used in the model are based mainly on laboratory measurements, and may vary
from rates in the real atmosphere. Deposition rates are difficult to measure
experimentally, and the values used in the model are somewhat uncertain.
Also, air quality measurements used to validate the model results contain
errors and are local, whereas model computations pertain to large areas. In
summary, there are uncertainties in the model itself and in the information
that it uses. The model output is sensitive to the values selected for
various parameters. In this section we discuss the sensitivity of ENAMAP-2S
to the model parameters, and we also recommend values for the parameters that
appear.to give the highest accuracy when the model results are compared to
air quality data.
In order to keep the costs of the sensitivity tests within reasonable
bounds, we made calculations of concentration and deposition for the entire
grid using emissions from the state of Ohio (near the center of the grid) for
August 1977. These computations are typical and serve adequately to
illustrate the sensitivity. The baseline (nominal) computation uses
parameter values described in Section 3 and in Mayerhofer et al. (1981). The
nominal results are shown in column A of Table 9.
The features that were varied include
(1) The S02 to sulfate transformation rate
(2) The wet and dry deposition rates for S02 and sulfate
(3) The proportion of nighttime emissions introduced in layer 1
(4) The vertical diffusion coefficients.
VARYING THE TRANSFORMATION RATE
As discussed by Mayerhofer et al. (1981), there are significant uncer-
tanties in estimates of the transformation rate in the real polluted atmo-
sphere. 30
-------
•o
a) -
c o
(— C CJ
•O 03 O '<-
O) U -i- U
**: > T- VI *i-
•r- 1/1 O
z •»- m
E
+-> o un
.c ••- r-.
01 to i
•r- t/l in
Q. i—
O) ID fO
Q r-. c
Q. r—
O) Ln ro
o r-* c
Ul I
o E co '
0) C .
E O
O> *4- It •
Q) l/>
§C C
ro o :
QJ 4- II -.-
cn 1/1 E
O C C O
•— o
10
o
•— o
CO
l£>
O
CO
o
VO
O
01 o
o
O o o
•MO-*-*
csj-O-^.
O
00
•M to C 2 C
O O O •— O
•4-> Q. -t~> M— -M
01 J^ ^£
C\J"O >—• CM*—'
O O
!-•»-> Q. _
: i o>^ a;-— -—
JE tVOC OJT3C OJ C
o •*-> o *-> o
01
its 4
31
-------
In ENAMAP-25, the transformation rate for SOg to sulfate is expressed
as the sum of two components: a homogeneous transformation rate (based on
the work of Altshuller, 1979) and a heterogeneous transformation rate. We
calculated the homogeneous rate as a function of solar insolation (i.e.,
latitude and season) from the rates for clean air given in Altshuller's
Figure 2. To account for higher rates in polluted air, the homogeneous rate
is multiplied by an additional arbitrary factor of 2. The results based on
this value (Section 4) indicate that the calculated sulfate concentrations
are higher than the air quality measurements. Even though the sulfate
measurements are sparse, an adjustment in the artibrary factor seems
advisable. Therefore, tests were made with this factor reduced to 1.75 and
to 1.5. The overall results are shown in columns B and C of Table 9. In
comparison to the nominal computation (column A), one can see that the
sulfate concentration and depositions are significantly reduced. On the
other hand, the SOg concentration is essentially unchanged, as desired.
VARYING TH€ DEPOSITION RATES
The dry deposition rates in ENAMAP-2S have a complicated dependence on
land-use type, and the range of values is wide as discussed in Section 3 and
by Mayerhofer et al . (1981). The computations of concentration are sensitive
to the rates. We made computations for Ohio with the nominal rates increased
and decreased by 25 percent. The results are shown in columns D and E of
Table 9. Greater dry removal of S02 and sulfate substantially reduced the
concentrations of the two compounds, and lesser removal had the opposite
effect.
The effect of varying the wet removal rates for $03 and sulfate is
generally similar to that described above, except that wet removal does not
produce large amounts of deposition in the winter. Therefore, variations in
the overall sulfur budget caused by varying the wintertime wet deposition
rates are relatively minor. But in summer (specifically August 1977), wet
removal is an important process, and variations of +25 percent in the nominal
rates have substantial effects on the deposition and concentration patterns,
similar to those reported above for dry deposition, as shown in columns P and
G of Table 9.
VARYING THE INJECTION OF NIGHTTIME EMISSIONS
As discussed in Section 3, all nighttime SOX (which are predominantly
from tall stacks) are initially placed in layer 2. One can argue, however,
that there is a certain proportion of low stacks whose emissions should be
introduced into the layer nearest the surface. Computer runs were made in
which 25 percent of the emissions were introduced into layer 1, and 75 per-
cent in layer 2 (column H in Table 9), and also a 50/50 division (column I).
One can see that the overall statistics are changed very little from the
nominal values. On the other hand, the mapped patterns (not shown) just
downwind of the source show substantially larger values of S02 concen-
trations and dry deposition than the nominal values; however, the sulfate
patterns are changed by only small amounts. Thus, the vertical partitioning
of emissions is important in controlling the S02 patterns immediately
downwind from major pollution sources.
32
-------
VARYING THE VERTICAL DIFFUSION COEFFICIENTS
The computation of vertical diffusion coefficients was described in
Section 3. An empirical factor in the computation was adjusted so that the
range of values would be from approximately 1 to 10 m^ s"'. Tests were made
doubling and halving these values, and the overall results are given in col-
umns J and K of Table 9. With larger coefficients (faster mixing), the pat-
terns show a tendency for slightly larger than nominal concentrations and dry
deposition of S02 and sulfate close to the sources. Decreasing the coeffi-
cients had the opposite effect. For the total emissions grid of ENAMAP,
which consists of numerous distributed sources, the effect of either greater
or lesser mixing, however, would be less than shown by the Ohio computations
because of cancellation of positive and negative influences.
OVERALL ADJUSTMENT
In comparison to air quality data, the ENAMAP results showed that the
main error was too-large values of sulfate concentration. On the other hand,
S02 concentrations did not show any consistent bias. The results of the
sensitivity tests indicate that a combination of reducing the transformation
(replacing the arbitrary "dirty air" factor by 1.5 instead of 2), increasing
the wet and dry deposition by 25 percent, and partitioning the nighttime
pollution injections 25 percent in layer 1 and 75 percent in layer 2, would
give results that compare well to measurements. The overall effect of this
combination is shown in column L of Table 9; it combines the effects of
columns B, 0, F, and H. (It would be desirable to use this combination of
parameters for a simulation for August 1977 for all 41 areas of the model
domain; however, this computation was beyond the scope of the present study.)
Maps showing concentration, dry deposition, and wet deposition patterns
produced by Ohio emissions for August 1977 are shown in Figures 15, 16, and
17. The nominal case (using values of parameters given in Section 3) is
shown in the upper parts of the figures, and the adjusted case (using the
combined effects corresponding to column L in Table 9) is shown in the lower
parts. One can see that in the adjusted case the central values of S02
concentrations and S02 dry and wet deposition are slightly larger than the
values for the nominal case, as was also true for the overall statistics of
Table 9. This is due mainly to the 25/75 introduction of emissions and to
the higher deposition rates. The sulfate concentrations of the adjusted case
are lower than those for the nominal case, because the transformation rate is
lower than the nominal rate and also because more S02 was deposited in the
adjusted case. The sulfate dry deposition pattern of the adjusted case is
essentially unchanged, except for slightly lower values overall. The sulfate
wet deposition of the adjusted case has noticeably lower amounts.
Pending further experimentation with more recent air quality measure-
ments, we recommend use of these adjusted parameters in ENAMAP-2S simulations.
33
-------
(a) SO2 CONCENTRATION, NOMINAL CASE
(c) SULFATE CONCENTRATION, NOMINAL CASE
(b) SO2 CONCENTRATION, ADJUSTED CASE
(d) SULFATE CONCENTRATION, ADJUSTED CASE
Figure 15. Comparison of ENAMAP-2S concentrations (fj.g m~3)
for the nominal case and using adjusted parameters.
34
-------
(a) SO2 DRY DEPOSITION, NOMINAL CASE
(c) SULFATE DRY DEPOSITION, NOMINAL CASE
(b) S02 DRY DEPOSITION, ADJUSTED CASE
(d) SULFATE DRY DEPOSITION, ADJUSTED CASE
Figure 16. Comparison of EIMAMAP-2S dry deposition (mg rrf2)
for the nominal case and using adjusted parameters.
35
-------
(a) SO2 WET DEPOSITION, NOMINAL CASE
(c) SULFATE WET DEPOSITION, NOMINAL CASE
(b) SO2 WET DEPOSITION, ADJUSTED CASE
(d) SULFATE WET DEPOSITION, ADJUSTED CASE
Figure 17. Comparison of ENAMAP-2S wet deposition (mg m~2)
for the nominal case and using adjusted parameters.
36
-------
SECTION 6
ENAMAP-2N: ADAPTATION OF THE MODEL FOR NITROGEN EMISSIONS
Until quite recently, treatment of nitrogen pollutants in the atmo-
sphere—specifically in Lagrangian long-range transport models—has been held
in abeyance in favor of sulfur pollutants. This is partly because of emphasis
on sulfur pollutants in the past few years and also because nitrogen chemistry
was considered to be "too complex" to attempt to'handle in a simple model.
This latter circumstance is probably the result of the wealth of information
on nitrogen chemistry that has been developed in the last 20 years in various
smog chambers studies; it may be a case of knowing too much about nitrogen
chemistry to be able to treat it simply in an atmospheric model. This atti-
tude has changed markedly in the past 2 years as a result of efforts to do
comprehensive measurements of nitrogen compounds in the atmosphere and
because of successful applications of complex model codes to laboratory
smog-chamber measurements.
Figure 18 illustrates typical results of a laboratory measurement of
nitrogen compounds in a smog chamber experiment (Sverdrup et a!., 1982). In
the middle graph of Figure 18, the upper curve labeled "A" represents the
amount of oxidized nitrogen that remains in the chamber at a given time. As
can be seen, approximately 80 to 90 percent of this amount can be accounted
for by nitric oxide (NO), nitrogen dioxide (N02), peroxyacetyl nitrate (PAN),
nitic acid (HN03) and particulate nitrate (NOj). These are the five com-
pounds ENAMAP-2N uses in a simplified reaction algorithm to model the
nitrogen chemistry in the manner shown in these experiments.
CHEMICAL TRANSFORMATIONS
Figure 19 shows the chemical transformations and the rate equations
governing the concentrations of the five compounds modeled in the reaction
algorithm. The primary gaseous pollutants, NO and N02, form an initial
puff over an emitter region. The concentrations of the two are calculated
and equilibrated with a diurnally varying equilibrium constant. The NO? can
react to form PAN, HN03 and NOg, with the products formed in a 5:4:1 molar
ratio. The reaction rate of N02 varies diurnally.
During the day, the PAN that exists in the puff reacts (with the same
rate as the N02) to form PAN, HN03 and NOj in the same 5:4:1 molar ratio.
By having half of the reaction's product be the reactant, PAN becomes a tem-
porary reservoir (Singh and Hanst, 1981) for the nitrogen-containing species
and permits transport further downwind. At night, PAN reacts slowly to
37
-------
400-
0
LO
0.9
Q8
Q7
06
Uf0.5
04
03
02
0.1
0
4
TVTvt ftrs
20
IB
L6
14
L2
:0g
08
06
04
02
0
Figure 18. Far-field power plant plume simulation, 4.5 ppmC urban
hydrocarbon mixture, 1.0 ppm SO2 (from Sverdrup et al., 1982).
38
-------
NITROGEN CHEMISTRY
NO ^ N02; K = 2 ; K = 2 (Day), K = 50 (Night)
[NO]
k1
NO2 =* PAN + HN03 + NOs; k1 = 0.1 (Day), ^ = 0.02 (Night)
k2
PAN =* PAN + HN03 + NOJ; k2 = 0.1 (Day), k2 = 0.0 (Night)
k3
PAN => N02 ; k3 = O(Day), k3 = 0.02 (Night)
d [NO2]
= -k1 [N02] + k3[PAN] - (k'DRY + k'WET)[NO2]
d[NO]
-- = -(k'DRY + k'WET)[NO]
d[PAN]
- = 0.5 (k1 [N02] + k2[PAN]) - (k2 + k3)[PAN]
d[HN03]
- 0.4 (k, [N02] + k2[PAN]) - (k5'RY + kJ(,'ET)[HN03]
= 0.1 (k1 [N02] + k2[PAN]) - (kB'R
*
.
at
Figure 19. Chemical reactions and rates (h~1 ) used in the "five compound" nitrogen algorithm.
39
-------
reform N02- This models the thermal decomposition of PAN that occurs in
the absence of light:
i! .
PAN ^ CH3C02 + N02
Due to the number of compounds and widely varying molecular weights in the
nitrogen algorithm, all transformations are calculated on a molar basis,
whereas in the sulfur algorithm, the simplicity of the SC>2 to sulfate
transformation does not require conversion to molar units.
TRANSFORMATION RATES
Figure 19 summarizes the transformation rates used in the reaction al-
gorithm. All rates and equilibria vary diurnally, due to the photochemical
nature of the NOv reactions. The N02/NO equilibrium constants reflect
the photolysis of N0£ to NO and the photo and thermal pathways of NO-to-N02
conversion. At every time step the N02/NO equilibrium is calculated both
before and after transformation calculations. The computations are made as
shown in Figure 20.
The N02 transformation rate is 0.1 h~^ during the day and 0.02 h"1
at night (10 and 2 percent per hour). Smog chamber studies of urban air
(Sverdrup et al., 1982) suggest daytime N02 loss rates of 0.15 to 0.25 h~l,
while measurements in the urban plume of Boston (Spicer, 1982) show an aver-
age rate of 0.18 h'l. Lower (nonurban) hydrocarbon concentrations in cham-
ber studies show lower rates. Due to the large, mostly rural region covered
by the ENAMAP domain, a rate of 0.10 h"^ was chosen. The nighttime rate of
0.02 h"^ reflects the thermal reaction rates.
The products of the N02 transformation are PAN, HN03 and NOg in a
5:4:1 molar ratio (i.e., 1 mole of N02 reacts to form 0.5 mole PAN, 0.4 mole
HH03 and 0.1 mole NO*.) The 4:1 ratio of HNOs to NOj reflects the predom-
inence of HN03 for N(V) species in the air. This is due to: (1) reaction
pathways that form the gaseous HN03, and (2) acidification of NOg and
its vaporization as HN03 in the presence of other strong acids, in
particular
Figure 21 illustrates the chemical reactions by following the concentra-
tions of the five nitrogen species in a hypothetical puff (without deposition
processes or puff expansion). One-hour time steps are used for the calcula-
tion, and the diurnal variation in rates is handled by assuming day the first
12 hours, then 12 hours of night. The relative amounts of NO and N02
change markedly at the transition from day to night, or night to day. The
overall pattern is a conversion of NO and N0£ to HN03 and nitrates.
These curves are a reasonably good approximation to the laboratory
measurements of Sverdrup et al. (1982).
DEPOSITION PROCESSES
The daytime dry deposition velocities used in the nitrogen algorithm
are summarized in Table 10. These values corne from the works of McMahon and
Denison (1979), Sehmel (1980),- and Garland and Penkett (1976). Unlike the
40
-------
EQUILIBRATE NO AND NO2
CALCULATE CHANGES IN CONCENTRATION
CALCULATE NEW CONCENTRATIONS
EQUILIBRATE NO AND NO2
CONTINUE ENAMAP AS BEFORE
Figure 20. The steps used in calculating changes in nitrogen compounds.
41
-------
100
TIME hours
Figure 21. Illustration of the "five compound" algorithm for a hypothetical puff.
42
-------
TABLE 10. DRY DEPOSITION VELOCITIES
FOR ATMOSPHERIC NITROGEN COMPOUNDS
Compound
N02, NO
HMO,
0
PAN
N03 (aerosol)
Vd (cm
Day
0.2
1.0
0.25
0.6
s'1)
flight
0.07
0.07
0.07
0.6
sulfur dry depositions, there is no variability of the velocities with land
use and stability class within the model. A dry deposition velocity of 0.07
cm s~l is used for the four gaseous species (NO, N02, PAN, and HNOs) at night-
analagous to the way $02 deposition is treated.
Wet deposition is treated in an identical manner as in the sulfur
algorithm,
k = a Rb
where R is the rainfall rate and a and b vary by species and season. The
rates for the nitrogenous species are calculated relative to S02 and sulfate.
Table 11 shows these relationships.
TABLE 11. WET DEPOSITION RATES FOR ATMOSPHERIC
NITROGEN COMPOUNDS EXPRESSED AS FRACTION
OF RATES ( a)FOR SOX
Compound Relative Rate
N02, NO 0.25
HN03 0.50
PAN 0.50
(aerosol)
MODEL RESULTS
Calculated concentration and wet and dry deposition patterns for the
months of January and August 1977 of all five ENAMAP-2N species (NO, N02, PAN,
HN03, and NOJ) are shown in Appendix C. In general, the patterns shown are
quite reasonable in terms of what one would expect for regionally averaged
43
-------
concentrations. Unfortunately, no air quality measurements exist for 1977
that can be used to judge the model's accuracy.
The patterns of calculated N02 concentrations for January 1977 (Figure
22) clearly show the definite local effects of major urban areas such as New
York City, Boston, and Detroit. It is interesting that the model preserves
this local source dominance of the primary pollutants even though the grid
uses a 70-km mesh. The patterns of the secondary pollutants (PAN,
HNCh, and NO^) are broader and more diffuse than those of the two primary
pollutants. For example, Figure 23 shows this feature of the calculated PAN
concentrations for August 1977. As mentioned earlier, PAN is used as a res-
ervoir in the algorithm, and the final products are mainly HN03 and NO^.
Nevertheless, the calculated PAN concentrations can be compared approximately
to recent PAN measurements made by Singh (private communication, 1982). His
measurements indicate that PAN is ubiquitous and has a concentration of
approximately 0.1 ppb (1 ppb = 5 [ag m~3) in air entering the northwest
coast of California. The calculated PAN concentrations of 15 to 30 M.g nr3
(3 to 6 ppb) in Figure 23 are reasonable in the light of these new mea-
surements.
The interregional exchange tables for nitrogen compounds for January and
August 1977 are given in Appendix D.
It would be very desirable to apply ENAMAP-2N to a recent year so that
the results could be compared to air quality measurements that have been made
only recently. The model could be evaluated in this way.
44
-------
Figure 22. Calculated concentration (#g m ) of airborne NO, for January 1977.
45
-------
Figure 23. Calculated concentration (jug m~3) of airborne PAN for August 1977.
46
-------
SECTION 7
SUMMARY AND CONCLUSIONS
The development of ENAMAP-2S for the long-range transport of sulfur
compounds has been completed. The model includes three layers in the verti-
cal, and it corrects the low-level winds for the influences of the smoothed
terrain. Pollution emissions may be partitioned among the three layers to
simulate both daytime and nighttime conditions. The model has been used to
compute monthly average values of the airborne concentrations of S0£ and
sulfate, and the computed values agree reasonably well with air quality
measurements. On the other hand, when ENAMAP-2S results are calculated for
a month, a substantial amount of smoothing occurs, and monthly average pollu-
tion patterns (specifically for January and August 1977) are not much differ-
ent from those computed previously using the single-layer version, ENAMAP-1A.
Also, the interregional exchange tables given by ENAMAP-2S and ENAMAP-1A are
quite similar for the same reason.
The parameters of ENAMAP-2S (such as transformation and deposition rates)
can be altered as further empirical information about them becomes available.
This will increase the accuracy of the computed patterns of airborne concen-
tration and deposition. The recommended values of various parameters are
given in Section 5.
A separate version of the model that applies to the long-range transport
of nitrogen compounds has also been completed. This version (called ENAMAP-
2N) is considerably more complicated than the other version because it treats
five nitrogen compounds in place of the two compounds used for sulfur model-
ing. An algorithm has been developed to simulate the chemistry of the five
compounds NO, N02, PAN, HN03, and nitrates. All of these compounds are
subject to deposition processes. Their patterns of concentration have been
computed for NOX emissions data for the model domain for the months of
January and August 1977, and the results appear to be quite reasonable.
ENAMAP-2N is the first model to be applied to the long-range transport of
NOX pollutants over eastern North America, and we believe that its devel-
opment marks a significant milestone in this field.
In this report ENAMAP-2 has been used to compute monthly average values
of pollution concentration and deposition. For a period this long, many
random errors due to model assumptions and to imperfections in input data
tend to average to negligible magnitudes. For shorter periods there is less
averaging; however, we believe that the new model versions simulate the atmo-
sphere in sufficient detail that computations can be made meaningfully for
periods of a few days and perhaps as short as 24 hours. This remains to be
47
-------
verified by making computations for pollution episodes and verifying them
with suitable air quality measurements.
We believe that these models represent the current state of the art in
calculating the long-range transport of airborne sulfur and nitrogen com-
pounds. The models give the geographical patterns of pollution and deposi-
tion and also provide interregional exchange tables that show how much of the
pollution in a region was emitted locally and how much originated in other
specified areas.
At present, measuring programs are being carried out to increase our
knowledge of airborne sulfur and nitrogen compounds, and of neutralizing
agents such as ammonia. Such information is required for computation of the
effects of sulfur and nitrogen compounds in producing acid rain. As this
information becomes available it will become possible to use the ENAMAP-2
simulations in the study of the effects of sulfur and nitrogen emissions on
acid rain. Even with limited information on airborne cations, it may be
possible to compute the worst-case acidity due to these pollutants.
Readers interested in using ENAMAP-2 should refer to a separate document
entitled, "ENAMAP-2 User's and Programmer's Manual" (Nitz and Endlich, 1983).
-------
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Contract 68-02-2959, SRI International, Menlo Park, California.
Bhumralkar, C. M., R. L. Mancuso, D. E. Wolf, K. C. Nitz, and W. B. Johnson.
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49
-------
Crank, J. 13G7: The Mathematics of Diffusion (Oxford University Press,
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Fisher, B.E.A. 1978: "The Calculation of Long Term Sulphur Deposition in
Europe," Atmos. Environ. 12:489.
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Nitrate and Ozone and Natural Surfaces," Atmos. Env. 10:1127.
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Patterns and Transfrontier Exchanges of Airborne Sulfur Pollution in
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and Applications," Proc. llth Int. Tech. meeting on Air Poll. Modeling^
and Its Applications (Plenum Press).
Liu, C. Y., and W. R. Goodin. 1976: "An Iterative Algorithm for Objective
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-------
Mayerhofer, P. M., R. M. Endlich, B. E. Cantrall, R. Brochinsky, C. M.
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51
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APPENDIX A
COMPARISON OF ENAMAP-25 AND ENAMAP-1A RESULTS FOR
SULFUR COMPOUNDS FOR AUGUST 1977
-------
Calculated by ENAMAP -2S
Calculated by ENAMAP-1A
5 4
MEASURED
FIGURE A-1. SO- CONCENTRATION (jug m"3).
53
-------
Calculated by ENAMAP-2S
Calculated by EIMAMAP-1A
FIGURE A-2. S02 DRY DEPOSITION (mg
.-2,
54
-------
J..
Calculated by ENAMAP-2S
Calculated by ENAMAP-1A
FIGURE A-3. S02 WET DEPOSITION (mg
.-2,
55
-------
Calculated by ENAMAP - 2S
Calculated by ENAMAP-1A
•-7 4
MEASURED
FIGURE A-4. SULFATE CONCENTRATIONS
-------
! "f V-N
1,^.000—' Us/ .^ro?
Calculated by ENAMAP-2S
Calculated by ENAMAP-1A
FIGURE A-5. SULFATE DRY DEPOSITION (mg m"2).
57
-------
Calculated by EIMAMAP-2S
Calculated by ENAMAP-1A
FIGURE A-6. SULFATE WET DEPOSITION (mg m
58
-2,
-------
Appendix B.
INTERREGIONAL EXCHANGE TABLES FOR SULFUR COMPOUNDS
-------
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Appendix C
ENAMAP RESULTS FOR NITROGEN COMPOUNDS
-------
Figure C-l. NO Concentration (yg m~ ), January 1977.
97
-------
_2
Figure C-2. NO Dry Deposition (mg m ), January 1977.
98
-------
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Figure C-3. NO Wet Deposition (mg m ), January 1977.
99
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_3
Figure C-4. N02 Concentration (ug m ), January 1977.
TOO
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Figure C-5. N0? Dry Deposition (rag m ), January 1977,
101
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Figure C-6. N0? Wet Deposition (mg m ), January 1977.
102
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Figure C-7. PAN Concentration (yg m ), January 1977.
103
-------
_2
Figure C-8. PAN Dry Deposition (mg m ), January 1977.
104
-------
_2
Figure C-9. PAN Wet Deposition (mg m ), January 1977.
105
-------
-3,
Figure C-10. HNO- Concentration (yg m ), January 1977
106
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V
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Figure C-ll. HNO^ Dry Deposition (mg m ), January 1977.
107
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Figure C-12.
_2
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108
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Figure C-13. NO- Concentration (wn m ), January 1977
109
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-2,
Figure C-14. NO Dry Deposition (mg m ), January 1977.
no
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Figure C-15. NO., Wet Deposition (mg m ), January 1977.
m
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Figure C-16. NO Concentration (yg m ), August 1977.
112
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Figure C-17. NO Dry Deposition (mg m ), August 1977.
113
-------
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Figure C-18. NO Wet Deposition (tag m ), August 1977.
114
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Figure C-19. NCL Concentration (ug m ), August 1977.
115
-------
-2,
Figure C-20. N0~ Dry Deposition (mg m ), August 1977.
'116'
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Figure C-21. NO Wet Deposition (mg m 2) , August 1977.
117
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Figure C-22. PAN Concentration (yg m ), August 1977.
118
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Figure C-23. PAN Dry Deposition (mg m ), August 1977.
-------
Figure C-24. PAN Wet Deposition (mg m ), August 1977.
120
-------
-3
Figure C-25. HNO Concentration (yg m ), August 1977.
121
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Figure C-26. HNO Dry Deposition (mg m ), August 1977.
122
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Figure C-27. HNO, Wet Deposition (mg m ), August 1977.
123
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Figure C-28. NO Concentration (ug m ), August 1977.
124
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Figure C-29. NO., Dry Deposition (mg m ), August 1977.
125"
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Figure C-30. NO- Wet Deposition (mg m ), August 1977.
126
-------
Appendix D
INTERREGIONAL EXCHANGE TABLES FOR NITROGEN COMPOUNDS
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41 ONTRIRUT IONS TO W12 WFT OPPOSITIONS WITHIN PFCEPTOR PFGIONS
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TECHNICAL REPORT DATA
(Please read Inwjcnons on tl'.e reverse before comnlctinz)
• REPORT NO. 2.
4. TITLE AND SUBTITLE
THE ENAMAP-2 AIR POLLUTION MODEL FOR LONG-RANGE
TRANSPORT OF SULFUR AND NITROGEN CONPOUNDS
7 AUTHOR(S)
R. M. Endlich, K. C. Nitz, R. Brodzinsky and
C. M. Bhumralkar
9. PERFORMING ORGANIZATION NAME AND ADDRESS
SRI Internationa]
333 Ravenswood Avenue
Menlo Park, CA 94025
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Sciences Research Laboratory-RTP, NC
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
3. RECIPIENT'S ACCESSION>NO.
5. REPORT DATE
6. PERFORMING ORGANIZATION CODE
8. PERFORMING ORGANIZATION REPORT NO
10. PROGRAM ELEMENT NO.
CCVN1A/01-0511
11. CONTHACTyGRANT NO.
68-02-3424
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
EPA/600/09
15. SUPPLEMENTARY NOTES
16. ABSTRACT
This report describes the Eastern North American Model for Air Pollution
(ENAMAP-2), which simulates the long-range transport and deposition of air
pollutants across eastern North America. There are two versions of the model -
one for sulfur compounds (ENAMAP-2S) and one for nitrogen compounds (ENAMAP-2N)
January and August 1977 S0£ and sulfate wet and dry depositions and average
ambient concentrations were simulated by ENAMAP-2S and compared to those simu-
lated by an earlier version of the model. In addition, a sensitivity study was
conducted to estimate model uncertainties resulting from uncertainties in the
values of the model parameters. Finally, January and August NO, N02» PAN,_HN03,
and NO^ wet and dry depositions and average ambient concentrations were simu-
lated.
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
13. DISTRIBUTION STATEMENT
RELEASE TO THE PUBLIC
b.lDENTlFIERS/OPEN ENDED TERMS
19. SECURITY CLASS (This Report)
UNCLASSIFIED
20. SECURITY ri ace /Th,, i
c. COSATI Field/Group
21. NO. OF PAGES
T5 DO 1 r-c
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