EPA-600-3-77-048
June 1977
Ecological Research Series
EFFECT OF SELECTED PARAMETERS
ON PREDICTIONS OF A
PHOTOCHEMICAL MODEL
Environmental Sciences Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
-------
RESEARCH REPORTING SERIES
.«
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ECOLOGICAL RESEARCH series. This series
describes research on the effects of pollution on humans, plant and animal spe-
cies, and materials. Problems are assessed for their long- and short-term influ-
ences. Investigations include formation, transport, and pathway studies to deter-
mine the fate of pollutants and their effects. This work provides the technical basis
for setting standards to minimize undesirable changes in living organisms in the
aquatic, terrestrial, and atmospheric environments.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
-------
EPA-600/3-77/048
June 1977
EFFECT OF SELECTED PARAMETERS ON PREDICTIONS
OF A PHOTOCHEMICAL MODEL
by
Marcia C. Dodge
Chemistry and Physics 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
-------
DISCLAIMER
This report has been reviewed by the Environmental Sciences Research
Laboratory, U.S. Environmental Protection Agency, and approved for publication.
Mention of trade names or commercial products does not constitute endorsement
or recommendation for use.
ii
-------
ABSTRACT
A sensitivity study was undertaken to assess the effect of selected
parameters on the predictions of a photochemical kinetics model. The model
was previously developed for use in designing control requirements for ozone
reduction in urban areas. The parameters that were varied in the present study
included (1) solar energy, (2) dilution rate, (3) post-9 A.M. emissions, and
(4) hydrocarbon composition of 6-9 A.M. emissions. Based on the results of
the simulations for each of these parameters, 0, isopleths as a function of
initial NMHC and NO were constructed. A comparison of the degree of hydro-
A
carbon control predicted to achieve the air quality standard for 0, was
made for each set of isopleths. It was found that the predictions of the
model are largely insensitive to the parameters investigated when the
results of the simulations are interpreted in a relative sense.
111
-------
CONTENTS
Abstract iii
Figures V1
Tables vii
1. Introduction 1
2. Results of Sensitivity Studies 5
Light intensity 5
Dilution rate 11
Post-9 A.M. emissions 15
Hydrocarbon composition 22
3. Discussion 34
References 38
Appendix 40
-------
FIGURES
Number Page
1 0_ isopleths for estimating control requirements. .... ............. 2
O
2 0_ isopleths for reduced light intensity .......................... 8
o
3 Comparison of isopleths generated at different light
intensities . . ................. . ................................
4 0, isopleths for 20 percent per hour dilution ..................... 12
o
5 Comparison of isopleths generated for. different dilution
rates [[[ 13
6 0, isopleths for post - 9 A.M. emissions,
19
7 Comparison of isopleths with and without post - 9 A.M.
emissions 20
8 0_ isopleths for NMHC mix of 90% butane and 10% propylene 25
9 Comparison of isopleths for NMHC mixtures of low and medium
reactivity 26
10 0 isopleths for NMHC mix of 50% butane and 50% propylene 30
O
11 Comparison of isopleths for NMHC mixtures of high and medium
-------
TABLES
Number Page
1 Effect of Light Intensity on Maximum 1-Hour 0_ Levels 6
2 Effect of Light Intensity on Percent NMHC
Reduction Needed to Achieve CL Standard 10
3 Effect of Dilution on Maximum 1-Hour 0_ Levels 14
4 Effect of Dilution on Percent NMHC Reduction Needed to Achieve
0 Standard ; 16
5 Effect of Post - 9 A.M. Emissions on Maximum 1-Hour 0
Levels 7 18
6 Effect of Post - 9 A.M. Emissions on Percent NMHC Reduction
Needed to Achieve 0_ Standard 21
7 Effect of Decreasing Hydrocarbon Reactivity on Maximum 1-Hour
0 Levels 24
8 Effect of Decreasing Hydrocarbon Reactivity on Percent NMHC
Reduction Needed to Achieve 0_ Standard 27
9 Effect of Increasing Reactivity on Maximum 1-Hour 0_ Levels 29
10 Effect of Increasing Hydrocarbon Reactivity on Percent NMHC
Reduction Needed to Achieve 0, Standard ^
o
11 Comparison of Selected Control Strategies Applied to Six Sets
of 0_ Isopleths 36
vn
-------
SECTION 1
INTRODUCTION
A method (1) was proposed recently for deriving ozone-precursor
relationships for use in planning control requirements for urban ozone
reduction. The method was based on the combined results of smog chamber
data and photochemical modeling techniques. A model was first developed
to fit the maximum 1-hour average 0_ levels obtained in smog chamber
*J
studies (2,3) of irradiated auto exhaust and oxides of nitrogen (NO ) mix-
A.
tures. The model was then adjusted to conditions that more closely approx-
imate those of the polluted atmosphere. This adjusted model was used to
construct a series of ozone isopleths over a wide range of initial pollutant
levels. A detailed version of these isopleths, for typical urban concen-
trations of nonmethane hydrocarbon (NMHC) and NO , is shown in Figure 1.
J\
The chemical kinetics mechanism used to construct this set of isopleths
is given in the Appendix.
A complete description of the conditions used to generate the isopleths
is found elsewhere (1) and only the highlights will be included in this
present work. The principal components of the model used to derive the
isopleths of Figure 1 are as follows:
(1) The hydrocarbon mix consisted of 25% propylene and 75% n-butane (as
carbon). Initial NO levels were taken to be 25% of the initial NO
£. A
concentrations.
(2) Diurnal 1-hour average values of the photolytic rate constants,
corresponding to the summer solstice for Los Angeles (34 N latitude),
were used.
(3) Simulations were carried out for a 9-hour period corresponding to the
hours between 8 A.M. and 5 P.M. LOT (local daylight saving time).
(4) Simulations were begun with a full charge of reactants. There was no
addition of fresh emissions in the subsequent 9 hours of the simulations.
-------
0.28
0.24
0.20
0.16
X
o
0.12
0.08
0.04
03 = 0.08 0.12 0.16 0.20 0.24 0.280.300.32 0.34 0.36
1.0
NMHC. ppmC
-------
(5) A dispersion rate of 3 percent per hour was included in the calculations.
This low dispersion rate was chosen to simulate conditions of high
stagnation in urban areas where the afternoon mixing height is relatively
low. Such conditions are found along the West Coast during the summer
months.
The purpose for constructing a set of isopleths was to offer an alternative
to the existing Appendix J method (4) for calculating ozone-precursor control
requirements. A detailed description of how these isopleths can be used to
estimate the degree of reduction in ambient precursor levels needed to attain
a specified level of ozone can be found elsewhere (5). It is the intent of
this method to offer a single set of isopleths that can be applied to any
urban area. The sensitivity study presented here was undertaken in an
effort to estimate whether or not the set of isopleths shown in Figure 1
could be applied universally to calculate control requirements. There are
a number of limitations arising from the assumptions that were made to
derive the ozone isopleths. These assumptions may be too restrictive to
allow universal application of the isopleths. Some of the most serious
limitations are:
(1) The model was developed to fit chamber data (2,3) of irradiated auto
exhaust and NO mixtures. The method, therefore, ignores organic emissions
from non-exhaust sources. It is known, however, that non-exhaust sources
can account for a significant fraction of the organic emissions in urban
areas (6,7). The reactivity, therefore, of the hydrocarbon mix used in
this modeling exercise may not be comparable to the reactivity of the
organic emissions in various control districts throughout the country.
(2) The light intensity selected for this modeling study corresponds to
the summer solstice for Los Angeles. This is substantially higher than
the insolation prevalent in northern cities. The isopleths, therefore,
may not be applicable to northern locations.
(3) A small dilution rate of only 3 percent per hour was used in the sim-
ulations to reflect the dispersion of pollutants. Dispersion rates in
other areas of the country are significantly greater, and, consequently,
the isopleths may not be applicable to these other areas.
(4) The impact of post - 9 A.M. emissions was not considered in the modeling
-------
study. This over-simplification of the real-world situation may negate
the usefulness of the 0_ isopleths.
To determine how the assumptions cited above affect the predictions of
the model, a sensitivity study was undertaken. Results of this sensitivity
study can be used to provide insight about the general applicability of the
isopleths for estimating the impact of control strategies. In this study
selected parameters were varied in order to assess the effect of these param-
eter on the shape and spacing of the 0 isopleths. The parameters considered
J
were the following:
light intensity
dilution rate
post - 9 A.M. emissions
hydrocarbon composition of the 6-9 A.M. emissions
In the following section, the results of each of these changes on the
predictions of the model are discussed. Also presented is a discussion on
how these changes relate to proposed control requirements.
-------
SECTION 2
RESULTS OF SENSITIVITY STUDIES
LIGHT INTENSITY
The isopleths shown in Figure 1 were constructed using photolytic rate
constants that correspond to the summer solstice for 34 N latitude (Los
Angeles). This is close to the maximum solar intensity occurring in the
continental United States. Northeast areas of the country generally ex-
perience their worst air pollution episodes in late summer or early fall.
The available solar energy at these times and locations is substantially
less than the energy available on June 21st in Los Angeles. To assess the
impact of a reduction in light intensity, the model was exercised using rate
constants for the various photolytic reactions that correspond to September
15th for a 40 N latitude. (Philadelphia is located approximately at
this latitude.) At the new location and time, the integrated rate constant
for the photodissociation of NO- (k..) over the 9-hour period of the simulations
is 20% less than its integrated value for June 21st at 34 N latitude. The
peak value of k.. for the new case is lower by approximately 10%.
The effect of light intensity on the absolute levels of 0_ produced
and how these differences in 0, levels affect predicted control require-
ments are discussed separately.
Effect on Predicted Maximum 0, Levels
The effect of decreasing the light intensity on the maximum 1-hour
average 0, concentration is given in Table 1 for selected simulations. The
NMHC-to-NO ratio was varied from 1.25 to 50. Column (4) in the table lists
x v J
the maximum 1-hour average 0 concentrations achieved when photolytic rate
constants corresponding to the summer solstice and 34 N latitude were used.
Column (5) lists the 0_ values obtained for September 15th at 40 N latitude.
Column (6) gives the percent decrease in peak 0, resulting from the reduced
-------
TABLE 1. EFFECT OF LIGHT INTENSITY ON MAXIMUM 1-HOUR 0 LEVELS
C1)
NMHC/NO
X
(ppmC/ppm)
1.25
1.67
2.5
3.33
5
6.67
10
10
12.5
20
20
40
50
(2)
NMHC
(ppmC)
0.25
0.25
0.25
0.50
0.25
1.0
2.0
0.5
0.25
1.0
2.0
2.0
1.0
(3)
NO
X
(ppm)
0.20
0.15
0.10
0.15
0.05
0.15
0.20
0.05
0.02
0.05
0.10
0.05
0.02
(4)
Maximum
Summer 34 N
(ppm)
0.030
0.056
0.104
0.196
0.126
0.312
0.426
0.170
0 . 098
0 . 207
0.318
0.224
0.134
(5)
1-hour ozone
Fall 40°N
(ppm)
0.023
0.043
0.088
0.177
0.118
0.295
0.407
0.164
0.094
0.193
0.295
0 . 202
0.124
(6)
%
Decrease
23
23
15
10
6
5
4
4
4
7
7
10
7
-------
solar intensity. The decrease in 0, ranges from 23% at the very low NMHC/NO
O A.
ratios to 4% at the higher ratios. The greater decrease at the low NMHC/NO
A.
ratios is the result of NO inhibition. In this range, the concentration of
NO is large relative to the hydrocarbon concentration. Nitric oxide, there-
fore, is not oxidized until late in the simulation. Because the onset of 0
J
formation is delayed, the reduced light intensity leads to a proportionately
greater decrease in 0_ concentration than is found for the more reactive NMHC
J
and NO systems.
Although the change in 0, levels varies from 4 to 23% for the simulations
cited in Table 1, the change in maximum 0, varies between only 4 and 7% for
NMHC-to-NO ratios of 5:1 to 20:1. This is the range of NMHC-to-NO ratios
X X
that is most commonly encountered in urban areas C$) A decrease in light
intensity within this range leads to a proportionate decrease in maximum 0_
levels. A set of isopleths, therefore, generated at the lower light intensity
should have the same shape and relative spacing as the set generated at the
higher light intensity. If the shape and spacing of two sets of isopleths are
identical, the control requirements calculated from the two sets should also
be identical. It is shown in the following section that this is the case.
Effect on Predicted Control Requirements
The proposed control method (5) is applied by calculating the percent
reduction in ambient precursor levels needed to achieve a specified level
of ozone. It is advantageous, therefore, to look at the effect of light
intensity in terms of this application rather than to test the sensitivity
of the model only in terms of the absolute values predicted for 0, concen-
trations. To gauge the effect of varying the light intensity on control
requirements, a set of 0, isopleths was constructed for the reduced solar
intensity. The new set is shown in Figure 2. There is little difference
in the shape and spacing of these isopleths from the original set shown in
Figure 1. This is demonstrated in Figure 3 where the 0.08 and 0.30 ppm
0_ isopleths are shown for the two cases. The solid lines are the isopleths
generated at the reduced light intensity. The dashed lines are the corresponding
isopleths of Figure 1 generated at the higher light intensity.
The proposed control method for relating ozone to its precursors depends
only on the shape and relative spacing of the isopleths and not on the absolute
-------
0.28r
03 = 0.08 0.12 0.16 0.20 0,24 0.30
0.36
0.24
0.20
0.16
X
O
0.12
0.08
0.04
1.0 1.2
NMHC, ppmC
l;igure 2. 0 isopleths for reduced light intensity.
*J
-------
0.28
0.24
0.20
E
c.
o.
X
O
0.16
0.12
0.08
0.04 j
FALL40°N
SUMMER 34°N
0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
NMHC.ppmC
Figure 3. Comparison of isopleths generated at different light intensities,
values of 0_ predicted for given NMiC and NO levels. Since the relative
5 X
spacing and shape of the curves shown in Figures 1 and 2 are little changed,
control requirements based on the two sets of isopleths should be nearly the
same. The example diagrammed in Figure 3 indicates that this is the case. In
this example, the degree of NMHC control needed to reduce ozone from a value of
0.30 ppm to the air quality standard of 0.08 ppm is depicted for a NMHC-to-NO
x
ratio of 8:1. At the lower light intensity, to reduce 0 from 0.30 ppm to 0.08
ppm at constant NO , it is necessary to move from point a to point b on the
J\
diagram. This corresponds to a decrease in NMHC of from 1.10 to 0.27 ppm.
This is a reduction in NMHC of 75%. To meet the standard at the higher
light intensity, it is necessary to move from point c to point d. This
entails reducing NMHC from 1.01 to 0.25 ppm. This also corresponds to a
hydrocarbon reduction of 75%.
Other examples of the percent reduction in NMHC determined from the
9
-------
TABLE 2. EFFECT OF LIGHT INTENSITY ON PERCENT NMHC REDUCTION NEEDED TO ACHIEVE 0 STANDARD
(1)
(2)
(3)
(4)
(5)
(6)
Summer 34 N
NMHC/NO
X
(ppmC/ppm)
5:1
5:1
5:1
5:1
7:1
8:1
8:1
10:1
10:1
10:1
15:1
20:1
*
% Change =
X
(ppm)
0.16
. 0.20
0.24
0.30
0.24
0.24
0.30
0.16
0.24
0.36
0.30
0.24
Col (5) - Col (8)
Col (5)
NMHC(X)
(ppmC)
0.37
0.50
0.62
0.86
0.69
0.72
1.01
0.45
0.81
1.50
1.48
1.27
NMHC (.08)
(ppmC)
0.18
0.21
0.24
0.32
0.21
0.20
0.25
0.14
0.19
0.28
0.22
0.16
Red
(%)
51
58
61
63
70
72
75
69
77
81
85
87
NMHC (X)
(PpmC)
0.38
0.52
0.70
0.96
0.73
0.76
1.10
0.49
0.86
1.60
1.64
1.51
(7)
Fall 40°N
NMHC (.08)
(ppmC)
0.19
0.23
0.28
0.36
0.23
0.22
0.27
0.16
0.20
0.31
0.24
0.19
Average
(8)
Red
(%)
50
56
60
62
68
71
75
67
77
81
85
87
Change :
(9)
% Change
2
3
' 2
2
3
1
0
3
0
0
0
0
1%
X 100
-------
two sets of isopleths are given in Table 2. In this table, the percent re-
duction in NMHC needed to reduce 0 from a value of "X" to the standard of
O
0.08 ppm is shown for typical urban NMHC-to-NO ratios ranging from 5:1 to
X
20:1. Columns (3) and (6) list the NMHC values corresponding to an 0 con-
«!)
centration of "X" for the high and low solar intensity cases, respectively.
Columns (4) and (7) give the NMHC values corresponding to 0.08 ppm ozone for
the two cases. The percent reduction in NMHC needed to reduce 0 concentra-
tions from CL = X to CL = 0.08 ppm at constant NO is given for both cases in
O «_) X
columns (5) and (8). Column (9) lists the relative percent change in the
amount of NMHC control predicted from the two sets of isopleths. For all of
the examples in this table, the relative change in control requirements cal-
culated from the two isopleths varies at most by 3%. On the average, the
relative change in needed NMHC control is only 1%, with greater control needed
at the higher light intensity. Since this difference is minimal, it can be
concluded that predicted control requirements for hydrocarbons are relatively
insensitive to variations in light intensity.
DILUTION RATE
The isopleths in Figure 1 were generated using a constant dilution rate
of 3 percent per hour throughout the nine-hour simulation period. This low
rate of dispersion is reflective of the West Coast area where in summer
months there is normally only a 100-meter difference between the mean morning
and afternoon mixing heights (8). In other regions of the country, the after-
noon mixing height can be substantially greater than the morning mixing height.
As an example, in Houston, the mean summer afternoon mixing height is 1500
meters whereas the mean morning mixing height is only 650 meters (8). If
uniform lifting of the inversion layer occurs over a 6-hour period, this
difference in mixing heights corresponds approximately to a dilution rate of
20 percent per hour.
To assess the effect of dilution rate on the shape and spacing of the
isopleths, the simulations used to derive Figure 1 were repeated using a
constant dilution rate of 20 percent per hour. The impact of this change
on ozone formation and on proposed control requirements is discussed in the
following sections.
11
-------
0.28
0.241
0.20
0.16
X
O
0.12
0.08
0.04
1.0 1.2
NMHC. ppmC
Figure 4. 0 isopleths for 20 percent per hour dilution.
-------
Effect on Predicted Maximum 0 Levels
The differences in maximum 1-hour average 0, concentrations predicted
when the dilution rate is increased from 3 to 20 percent per hour are shown
in Table 3 for a few simulations selected at random. The percent decrease
in 0, obtained when the dilution rate was increased to 20 percent per hour
J
varied from 39 to 52%, with an average decrease of 45%. The variation seems
to be independent of the NMHC-to-NO ratio. In general, the smallest de-
crease in 0, occurred at the higher hydrocarbon concentrations.
Effect on Predicted Control Requirements
The isopleths generated at the high dilution rate are shown in_Figure 4.
They can be compared most easily to the original isopleths of Figure 1 by
looking at the differences in the 0.08 and 0.20 ppm 0, isopleths shown in
Figure 5. It can be seen that the shape of the two sets of isopleths is
approximately the same, but there is a difference in their relative spacing.
0.28
0.24
0.20
E
Q.
a.
X
o
0.16
20% PER HOUR
3%PER HOURi
0.12
0.08
0.04
0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
NMHC, ppmC
Figure 5. Comparison of isopleths generated for different dilution rates.
13
-------
TABLE 3. EFFECT OF DILUTION ON MAXIMUM 1-HOUR 0 LEVELS
(1)
NMHC/NO
X
(ppmC/ppm)
2.5
5
5
5
6.67
10
10
10
12.5
13.33
20
25
40
50
75
(2)
NMHC
(ppmC)
0.25
0.25
0.50
1.0
1.0
0.50
1.0
2.0
0.25
2.0
2.0
0.50
2.0
1.0
1.5
(3)
NO
X
(ppm)
0.10
0.05
0.10
0.20
0.15
0.05
0.10
0.20
0.02
0.15
0.10
O.;02
0.05
0.02
0.02
(4)
Maximum
3% per hour
'(PP.m)
0.104
0.126
0.200
0.332
0.312
0.170
0.274
0.426
0.098
0.380
0.318
0.118
0.224
0.134
0.140
(5)
1-hour ozone
20% per hour
(ppm)
0.056
0.060
0.096
0.160
0.162
0.094
0.146
0.248
0.049
0.231
0.195
0.064
0.137
0.076
0.083
(6)
%
Decrease
46
52
52
52
48
i . 45
47
42
50
39
39
46
39
43
41
-------
An example of how this difference in relative spacing affects control
requirements is depicted in Figure 5. At a NMHC-to-NO ratio of 8:1 and an
A.
0, level of 0.20 ppm, to meet the 0, standard at a dilution rate of 20 per-
J J
cent per hour, the NMHC level should be reduced from 1.36 ppm (point a) to
0.44 ppm (point b) or a predicted reduction of 68%. Similarly, at a dilution
rate of 3 percent per hour, the NMHC should be decreased along line cd from
0.59 to 0.18 ppm or a predicted hydrocarbon reduction of 69%. There is,
therefore, a difference of only 1% in the degree of hydrocarbon control pre-
dicted from these two sets of isopleths. This example and others are sum-
marized in Table 4. The two sets of isopleths predict relative percent changes
in NMHC control requirements that vary by only 1 to 5%. On the average
there is a 3% relative change in control requirements calculated from the
two sets of isopleths. In general, greater control is needed at the lower
dilution rate.
POST - 9 A.M. EMISSIONS
The simulations used to generate the 0 isopleths of Figure 1 were carried
o
out assuming full loading of hydrocarbon and NO emissions at 8 A.M. LOT when
J\
the simulations were begun. The initial concentrations of NMHC and NO used
6 x
in the modeling runs are intended to represent the mean 6-9 A.M. ambient
level of these pollutants. The modeling studies ignore the impact of post -
9 A.M. emissions. In a typical urban area, the vehicular miles driven be-
tween 9 A.M. and 4 P.M. can be at least as great as the number of miles driven
between 6 and 9 A.M. (9). It is not unreasonable, therefore, to expect a
doubling of the early morning emission levels during the 9-hour period of the
simulations.
To assess the impact of continuous emissions on the predictions of the
model, the simulations used to derive the Figure 1 isopleths were repeated
assuming there was a 100% increase in the 6-9 A.M. NMHC and NO levels be-
J\
tween the hours of 9 A.M. and 5 P.M. LOT. The same initial concentrations
of hydrocarbon and NO reactants were used to start the simulations at 8 A.M.
LOT, but between the hours of 9 A.M. and 5 P.M., NMHC and NO emissions, at
A.
a constant rate of 12.5 percent per hour, were added to the system. (Fresh
emissions were not added between 8 and 9 A.M. because the initial starting
reactants are taken to represent the mean 6-9 A.M. levels of NMHC and NO .)
A.
15
-------
TABLE 4. EFFECT OF DILUTION ON PERCENT NMHC REDUCTION NEEDED TO ACHIEVE
STANDARD
CD (2)
(3) (4)
(SO
3% per hour dilution
NMHC/NO X
(ppmC/ppm) (ppm)
5:1 0.12
5:1 0.16
6:1 0.16
6:1 0.20
7:1 0.16
7:1 0.20
8:1 0.12
8:1 0.20
10:1 0.16
10:1 0.20
15:1 0.12
15:1 0.20
20:1 0.16
NMHC(X) NMHC (.08)
(ppmC) (ppmC)
0.23 0.14
0.37 0 . 18
0.38 0.16
0.53 0.20
0.40 0.15
0.56 0.19
0.27 0.14
0.59 0.18
0.45 0.14
0.66 0.17
0.36 0.14
0.80 0.15
0.64 0.14
Red
C%0
39
51
58
62
62
66
4.8
.69
69
74
61
81
78
(6)
20% .per
NMHC(X)
(ppmC)
0.64
0.99
0.97
1 . 35
0.99
1.33
0.72
1.36
1.11
1.44
0.91
1.72
1.57
(7) "'
(8)
(9)
hour dilution
NMHC (.08)
(ppmC)
0.38
0.50
0.43
0.-56
0.39
0.48
0,36
0.44
0.37
0.40
0.37
0.37
0.36
Red
(%)
41
49
56
59
61
64
50
68
67
7?
59
78
77
Average Change:
* - Chance - Col(5)
o tnange CQ
- Col (8) v
L(5) X 1UU
*
% Change
5
4
3
5
2
3
4
1
3
3
3
4
1
3%
-------
The composition of the added hydrocarbon emissions was the same as the com-
position of the 6-9 A.M. hydrocarbon mix (i.e. 75% n-butane and 25% propylene).
The NO _ concentration of the added continuous injection was taken to be 10%
of the NO since almost all oxides of nitrogen are emitted in the form of NO.
A.
(The 6-9 A.M. NO. concentration, however, was taken to be 25% of the initial
NO as in the original simulations. This higher NO concentration was used
X ^
to reflect the presence of aged pollutants in an urban area resulting from
carry-over from the preceding day or transport from upwind locations.) The
only change, therefore, between these simulations and those used to generate
the isopleths of Figure 1 is that there is a doubling of hydrocarbons and NO
X
reactants over the nine-hour period.
Effect on Predicted Maximum 0_ Levels
The impact of continuous emissions on the predicted maximum 1-hour average
0_ concentration is shown in Table 5 for selected simulations with NMHC/NO
o X
ranging from 1.25 to 25. Column (6) lists the percent increase in maximum 0_
o
that results when continuous emissions are added to the model. The increase
ranges from -33% to + 37%. At the low NMHC/NO ratio (<2.5:1), there is a
decrease in peak 0, levels when emissions are added throughout the simulation
because of the inhibition effect of NO. In this range, NO is already present
at a level that is high compared to the hydrocarbon level. The addition of
fresh sources of NO tends to suppress 0, formation. At the higher NMHC-to-NO
Jv
ratios (>2.5:1), the added emissions further drive the system and lead to an
increase in 0,. However, even at these higher ratios, the nonlinearity of
J
the smog system is readily apparent. For example, at NMHC-to-NO ratios
commonly encountered in urban areas (5:1 to 20:1), a 100% increase in reactants
results in an increase in 0 of between only 12 and 37%, with an average in-
O
crease of 25%.
Effect on Predicted Control Requirements
The 0_ isopleths generated when continuous emissions were included in
the model are shown in Figure 6. The shapes of the two sets of curves are com-
parable, but the relative spacing of the new set of isopleths is somewhat
different from the spacing of the isopleths of Figure 1. This is more
apparent in Figure 7 where the 0.08 and 0.30 ppm isopleths of Figures 1
17
-------
TABLE 5. EFFECT OF POST-9 A.M. EMISSIONS ON MAXIMUM 1-HOUR 0~ LEVELS
oo
(1)
NMHC/NO
A
(ppmC/ppm)
I. 25
1.67
2.5
3.33
5
5
5
10
10
12.5
20
20
25
(2)
NMHC
(ppmC)
0.25
0.25
0.50
0.50
1.0
0.50
0.25
2.0
1.0
0.25
2.0
1.0
0.50
(3)
NO
X
(ppm)
0.20
0.15
0.20
0.15
0.20
0.10 ,
0.05
0.20
0.10
0.02
0.10
0.05
0.02
(4)
Maximum 1 -hour
Without Added
Emissions
(ppm)
0.030
0.056
0.152
0.196
0.332
0.200
0.126
0.426
0.274
0.098
0.318
0.207
0.118
(5)
ozone
With Added
Emissions
(ppm)
0.020
0.042
0.150
0.247
0.412
0.268
0.172
0.493
0.338
0.129
0.355
0.253
0.152
(6)
%
Increase
-33
-25
- 1
26
24
34
37
16
23
32
12
22
29
-------
0.28
0.24
0.20
0.16
X
O
0.12
0.08
0.04
03 = 0.08 0.12 0.20 0.30 0.36 0.40
1.0
NMHC, ppmC
Figure 6. 0 isoplcths for post - 9 A.M. emissions.
-------
0.28
0.24
WITH POST - 9 a.m. EMISSIONS
WITHOUT POST 9 a.m. EMISSIONS
0.2 0.4 0.6 ,0.8 1.0 1.2 1.4 1.6 1.8 2.0
Figure 7. Comparison of isopleths with and without post-9 A.M. emissions,
and 6 are compared.
An example .of the effect of including fresh emissions on the degree of
NMHC control predicted to achieve the 0, standard is diagrammed in Figure 7.
With continuous emissions Csolid lines), to reduce 0_ from 0.30 to 0.08 ppm
at NMHC/NO =8:1, NMHC should be decreased along line ab from 0.72 to 0.19
A.
ppm. This amounts to a hydrocarbon reduction of 74%. When continuous
emissions are excluded from the model (dashed lines), to meet the standards
NMHC should be decreased along line cd from 1.01 to 0.25 ppm or a reduction
of 75%. For this .case, a difference of 1% in degree of NMHC control is
predicted from the two sets of isopleths.
Additional examples of differences in control requirements predicted by
the two sets of isopleths are given in Table 6. The relative change in
percent hydrocarbon reduction needed to achieve the CL standard varies from
20
-------
TABLE 6. EFFECT OF POST-9 A.M. EMISSIONS ON PERCENT NM1IC REDUCTION NEEDED TO ACHIEVE 0, STANDARD
(1) (2)
NMHC/NO X
A.
(ppmC/ppm) (ppm)
5:1 0.16
5:1 0.24
5:1 0.30
6:1 0.30
7:1 0.24
8:1 0.24
8:1 0.30
10:1 0.16
10:1 0.24
10:1 0.30
15:1 0.24
15:1 0.30
20:1 0.16
* °- Chance - C°1(5) -
o Change CQI
(3) (4)
Without post - 9 A.M.
NMHC(X) NMHC(.OS)
(ppmC) (ppmC)
0.37 0.18
0.62 0.24
0.86 0.32
0.91 0.29
0.69 0.21
0.72 0.20
1.01 0.25
0.45 0.14
0.81 0.19
1.14 0.23
1.05 0.15
1.48 0.22
0.64 0.14
Col (8)
l^ J
(5)
emissions
Red
(%)
51
61
63
68
70
72
75
69
77
80
86
85
78
(6)
With post-9
(7)
A.M.
(8)
emissions
NMHC(X) NMHC(.OS) Red
(ppmC) (ppmC) (%)
0.22
0.42
0.60
0.63
0.47
0.50
0.72
0.25
0.56
0.81
0.73
1.08
0.39
0.11
0.18
0.25
0.22
0.15
0.14
0.19
0.08
0.13
0.18
0.12
0.16
0.08
50
57
58
65
68
72
74
68
77
78
84
85
79
Average Change :
(9)
*
% Change
2
7
8
4
3
0
1
1
0
2
2
0
1
2%
-------
0 to 8%. The average relative change in predicted control requirements is only
2%, with greater reduction needed when continuous emissions are excluded from the
model.
HYDROCARBON COMPOSITION
The 0_ isopleths shown in Figure 1 were generated for a hydrocarbon sys-
tem comprised of 75% n-butane and 25% propylene as carbon. This composite
mixture produced the best fit to smog chamber experiments of irradiated auto
exhaust and NO mixtures. However, even in Los Angeles non-exhaust organics
A.
may comprise as much, as 30-50% of the total organic emissions (6,7). Even if
local emissions could be attributed solely to auto exhaust,, the composition of
auto exhaust may undergo change because of the impact of emission control
devices (10).
Because the hydrocarbon reactivity of a particular urban area, may be
substantially different from the reactivity of' the hydrocarbon mix employed
in the smog chamber studies, it was desirable to test the sensitivity of the
model predictions to changes in hydrocarbon composition. In order to gauge
the maximum effect of a change in hydrocarbon composition, the composition
was varied between two extremes in reactivity. In one case the n-butane
content was increased to 90% and the propylene content was decreased to
10%. In the other case, a 50-50 mix of butane and propylene was used. The
ratio of butane to propylene, therefore, was varied between 9:1 and 1:1, or a
difference of a factor of three from the original hydrocarbon mix of 3:1.
This variation in reactivity is probably considerably greater than the vari-
ations one might reasonably expect to find among urban areas. Detailed hydro-
carbon analyses were made of urban air samples collected in St. Louis, Denver,
Los Angeles, New Jersey, New York, and the Boston area (7, 11-13). The
paraffinic content of the atmospheric samples was found to vary only from a
low of 41% of the total nonmethane carbon in Los Angeles to a high of 58%
in Denver and outside of Boston. The sum of the olefins and aromatic hydro-
carbons in these samples ranged from 42% of the nonmethane carbon in St.
Louis to 54% in Brooklyn and Los Angeles. This variation in composition is
considerably less than the factor of three variation in the butane-to-pro-
pylene ratio used in this sensitivity study. The effects, therefore, of
22
-------
these changes on the model predictions are expected to be significantly greater
than the effect resulting from variations in hydrocarbon composition that
might be found in urban areas.
The results of decreasing and increasing the reactivity of the hydro-
carbon mix are discussed separately.
Decreasing Hydrocarbon Reactivity
To assess the impact of a decrease in hydrocarbon reactivity on control
requirements, the simulations used to generate the isopleths of Figure 1 were
repeated using a hydrocarbon mix comprised of 90% n-butane and 10% propylene
(as carbon). The effect of this decrease in reactivity on the predicted 0_
O
levels and the degree of hydrocarbon control needed to meet the 0_ standard
are described in the following two sections.
Effect on Predicted Maximum 0_ Levels
The impact of decreasing hydrocarbon reactivity on predicted levels of
ozone is summarized in Table 7. The decrease in CL predicted for this less
reactive mixture ranges from -1% at a NMHC/NO ratio of 100:1 to + 43% at
A.
a NMHC/NO ratio of 1:1. The increased 0, concentration obtained in the
A. O
high NMHC/NO simulation is the result of the decrease in olefinic content
of the new mix. At this high ratio, hydrocarbon is present in excess. The
decreased olefinic content of the less reactive mixture results in less
destruction of 0, through reaction of olefins with 0_. Ozone levels, there-
J ->
fore, actually increase although the overall reactivity of the system has
declined. If one excludes the very high and low NMHC-to-NO ratios that
A
are generally not found in urban areas, the change in 0 yield is seen to
o
vary from about 2 to 11% with an average difference of about 8%.
Effect on Predicted Control Requirements
The 0_ isopleths generated for the low reactivity hydrocarbon mix are
shown in Figure 8. The difference between this set of isopleths and the set
depicted in Figure 1 can be seen most readily by comparing the 0.08 and 0.30
ppm isopleths of Figure 9. It can be seen that the relative spacing of the
isopleths is fairly consistent, but the shape of the new set of isopleths
is somewhat different. There is more curvature to the new set in the high
23
-------
TABLE 7. EFFECT OF DECREASING HYDROCARBON REACTIVITY ON MAXIMUM 1-HOUR 0^ LEVELS
(1)
NMHC/NO
X
(ppmC/ppm)
1.0
2.5
3.33
5.0
5.0
6.67
10
10
12.5
20
50
100
(2)
NMHC
(ppmC)
0.10
0.25
0.50
0.50
0.25
1.0
1.0
2.0
0.25
2.0
1.0
2.0
(3)
NO
X
(ppm)
0.10
0.10
0.15
0.10
0.05
0.15
0.10
0.20
0.02
0.10
0.02
0.02
(4)
;Maximum
75% Butane
(ppm)
0.021
0.104
0.196
0.200
0.126
0.312
0.274
0.426
0.098
0.318
0.134
0.142
(5)
1-hour ozone
90% Butane
(ppm)
0.012
0.069
0.148
0.179
0.112
0.277
0.252
0.402
0.090
0.312
0.132
0.144
(6)
%
Decrease
43
34
24
10
11
11
8
6
8
2
1
-1
-------
0.28
tn
0.24
0.20
0.16
X
O
0.12
0.08
0.04
03 = 0.08 0.12 0.16 0.20 0.24
1.0
NMHC, ppmC
l;igurc 8. 0 isoplcths for NMI1C mix of 90% butane and 10% propylene.
-------
0.28
0.24
0.20
0.16
x
o
90% BUTANE
75% BUTANE
03 = 0.08 0.08
/
0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8
0.12
0.08
0.04
Figure 9. Comparison of isopleths for NMHC mixtures of low and medium
reactivity.
NO region than is in the original set of isopleths (Tigure !)
x
Figure 9 also includes an example of the effect of decreasing hydrocarbon
reactivity on the degree of control predicted to achieve the ozone standard
of 0.08 ppm. At a NMHC-to-NO ratio of 8:1, to decrease 0 from 0.30 to 0.08
J\
ppm using the low reactivity set of isopleths (solid lines), NMHC should be
reduced along line ab from 1.13 to 0.35 ppm. This amounts to a hydrocarbon
reduction of 69%. Using the original set of isopleths (dashed lines), NMHC
should be reduced along line cd from 1.01 to 0.25 ppm, or a hydrocarbon re-
duction of 75%. An absolute difference, therefore, of 6%, or a relative
change of 8%, in degree of NMHC control is predicted from these two sets of
isopleths. Other examples of the percent change in control requirements pre-
dicted from the two sets of isopleths are given in column (9) of Table 8. On
26
-------
TABLE 8. EFFECT OF DECREASING HYDROCABRON REACTIVITY ON PERCENT NMHC REDUCTION NEEDED TO ACHIEVE 0 STANDARD
(1) (2)
(3) (4)
(5)
7S°« Butanc-25?6 Propylene
NMHC/NO X
(ppmC/ppra) (ppm)
5:1 0.16
5:1 0.20
5:1 0.24
6:1 0.30
7:1 0.24
7:1 0.30
8:1 0.24
8:1 0.30
8:1 0.40
10:1 0.16
10:1 0.24
10:1 0.30
15:1 0.24
15:1 0.30
.20:1 0.30
* *n,«,fi. = Col (5) -
Col
NMHC(X) NMHC (.08)
(ppmC) (ppmC)
0.37 0.18
0.50 0.21
0.62 0.24
0.91 0.29
0.69 0.21
0.96 0.26
0.72 0.20
1.01 0.25
1.58 0.35
0.45 0.14
0.81 0.19
1.14 0.23
1.05 0.15
1.48 0.22
1.78 0.20
Col (8)
rr< A 1 UU
(5)
Red
f O. "\
\ V I
51
58
61
68
70
73
72
75
78
69
77
80
86
85
89
(6)
(7)
(8)
(9)
90% Butane-10% Propylene
NMHC(X)
(ppmC)
0.45
0.61
0.83
1.05
0.81
1.08
0.84
1.13
1.77
0.50
0.92
1.24
1.11
1.59
1.87
NMHC (.08) Red
(ppmC)
0.24
0.30
0.39
0.41
0.29
0.37
0.27
0.35
0.53
0.17
0.25
0.31
0.21
0.27
0.25
(%)
47
51
53
61
64
66
68
69
70
66
73
75
81
83
87
Average
% Change
8
12
13
10
9
10
6
8
10
4
5
6
6
2
2
Change: 7%
-------
the average, the hydrocarbon control predicted by the less reactive model is
7% less stringent than the control predicted by the original model containing
the more reactive hydrocarbon mixture.
Increasing Hydrocarbon Reactivity
To assess the full impact of hydrocarbon reactivity, the simulations em-
ployed to generate the isopleths of Figure 1 were repeated using a hydrocarbon
mixture that contained equal amounts of n-butane and propylene (as carbon).
The effects of this increase in reactivity of the hydrocarbon mix on both the
maximum 0 levels and the predicted control requirements are discussed below.
Effect on Predicted Maximum 0_ Levels
The results of increasing hydrocarbon reactivity on peak 0, values are
summarized in Table 9. The increase in maximum 0, levels attained with the
more reactive mixture varies from +76 to -25%. The decrease in CL yields
J
at the very high NMHC-to-NO ratios is the result of the increased olefinic
X
content of the more reactive mix. At these high ratios, hydrocarbon is
present in excess of ^he amount needed to'drive the reaction. Since more of
this excess hydrocarbon is olefinic, rather than paraffinic, in nature, more
0, is consumed through reaction with propylene. At lower NMHC-to-NO ratios,
O A
where the reaction is hydrocarbon-limited, the increased reactivity of the
hydrocarbon mix leads to an increase in maximum 0, levels. If one considers
only the range of NMHC/NO commonly found in urban areas (ratios between 5:1
A.
and 20:1), the percent increase in 0, is found to vary from +13 to -9%. This
is considerably less variation than is found over the entire range of NMHC-
to-NO ratios.
x
Effect on Predicted Control Requirements
The 0_ isopleths generated for the 50-50 mix of n-butane and propylene
are shown in Figure 10. A direct comparison between these isopleths and
those shown in Figure 1 is given in Figure 11. The relative spacing of
these isopleths is similar, but the shape of the two sets is significantly
different. The effect of this change in shape on predicted control strategy
28
-------
TABLE 9. EFFECT OF INCREASING HYDROCARBON REACTIVITY ON MAXIMUM 1-HOUR
LEVELS
(1)
NMHC/NO
A.
(ppmC/ppm)
1.0
2.5
3.33
5.0
5.0
6.67
10
10
12.5
20
50
100
(2)
NM1IC
(ppmC)
0.10
0.25
0.50
0.50
0.25
1.0
1.0
2.0
0.25
2.0
1.0
2.0
(3)
NO
X
(ppm)
0.10
0.10
0.15
0.10
0.05
0.15
0.10
0.20
0.02
0.10
0.02
0.02
(4)
Maximum
75% Butane
(ppm)
0.021
0.104
0.196
0.200
0.126
0.312
0.274
0.426
0.098
0.318
0.134
0.142
(5)
1-hour ozone
50% Butane
(ppm)
0.037
0.150
0.248
0.226
0.139
0.333
0.282
0.423
0.102
0.290
0.123
0.106
(6)
%
Increase
76
44
27
13
10
7
3
-1
4
-9
-8
-25
-------
0.28
0.24
0.20
0.16
o.
o.
X
O
0.12
0.08
0.04
03 = 0.08 0.16 0.24 0.30
Figure 10. 0 isoplcths for NMHC mix of 50% butane and 50% propylene.
-------
0.28
0.24-
0.20
0.16
x
o
0.12
0.08
0.04
50% BUTANE
75% BUTANE
0.8 1.0 1.2
NMHC, ppmC
Figure 11. Comparison of isopleths for NMHC mixtures of high and medium
reactivity.
is illustrated in Figure 11 for a NMHC-to-NO ratio of 6:1 and a peak 0
JC 3
level of 0.30 ppm. For the highly reactive system (solid lines), the model
indicates that NMHC should be decreased along line ab from 0.80 to 0.19 ppm,
or a hydrocarbon reduction of 76%. Using the original set of isopleths
(dashed lines) for the less reactive mix, XMHC should be reduced along line
cd from 0.91 to 0.29 ppm, or a hydrocarbon control of 68%. The new set of
isopleths, therefore, indicates the need for an 8% greater reduction of
hydrocarbons, or, a relative increase in control requirements of 12%. Additional
examples of the predicted differences in hydrocarbon reduction derived from
the two sets of isopleths are given in Table 10. The average relative change
in-predicted hydrocarbon control is 8%, with greater control required for the
hydrocarbon mix of high reactivity.
. 31 .
-------
[ABLE 10. EFFECT OF INCREASING HYDROCARBON REACTIVITY ON
CD (2)
(3)
(4)
(5)
75% Butane-25% Propylene
NMHC/NO X
Jv
(ppmC/ppra) (ppm)
5:1 0.20
5:1 0.24
6:1 0.30
6:1 0.40
7:1 0.24
7:1 0.30
8:1 0.24
8:1 0.30
8:1 0.40
10:1 0.16
10:1 0.24
10:1 0.30
15:1 0.24
15:1 0.30
20:1 0.24
NMHC(X)
(ppmC)
0.50
0.62
0.91
1.42
0.69
0.96
0.72
1.01
1.58
0.45
0.81
1.14
1.05
1.48
1.27
NMHC (.08)
(ppmC)
0.21
0.24
0.29
0.42
0.21
0.26
0.20
0.25
0.35
0.14
0.19
0.23
0.15
0.22
0.16
Red
/.ft,"\
I "O J
58
61
68
70
70'
73
72
75
78
69
77
80
86
85
87
PERCENT NMHC REDUCTION NEEDED
(6)
(7).
TO ACHIEVE 0
(8)
STANDARD
(9)
50% Butane-50% Propylene
NMHC(X)
(ppmC)
0.40
0.55
0.80
1.20
0.64
0.87
0.68
0.94
1.47
0.40
0.76
1.13
1.02
1.62
1.40
NMHC (.08)
(ppmC)
0.14
0.17
0.19
0.25
0.15
0.18
0.14
0.17
0.23
0.11
0.13
0.16
0.12
0.16
0.12
Red
00 %
65
69
76
79
77
79
79
82
84
72
83
86
88
90
91
Average Change:
* o ~. Col (5)
LC
- Col(8)
1(5) X 10
*
Change
12
13
12
13
10
8
10
9
8
4
8
7
2
6
5
8%
-------
Summary of Reactivity Effects
The sensitivity studies of hydrocarbon reactivity presented above
indicate that a factor of three variation in the butane-to-propylene ratio
results in an average change in predicted hydrocarbon control requirements
of only 7-8%. The variation in hydrocarbon reactivity used in these studies
is suspected to be considerably greater than the variation in reactivity
that might be found in urban areas. It is reasonable to conclude, therefore,
that predicted control requirements are relatively insensitive to expected
variations in hydrocarbon reactivity.
In addition to investigating the effect of hydrocarbon reactivity, the
sensitivity of the model to changes in the initial NO_-to-NO ratio was also
fc X
investigated. The isopleths of Figure 1 were generated for an initial NO
X
mix comprised of 25% NO and 75% NO. Almost all oxides of nitrogen are emitted
in the form of NO. For example, more than 90% of the NO emissions from
power plants are in. the form of NO (14). The 6-9 A.M. ratio of NO.-to-NO
J X
of 1:4 used in the simulations was chosen to reflect the.presence of aged
pollutants in an urban area. These aged pollutants may result from carry-
over from the preceding day or transport from upwind locations. It is
reasonable to expect that the 6-9 A.M. ratio of NO_-to-NO may vary among
^ X
urban areas. To assess the effect of such variations on the predictions
of the model, two series of simulations were carried out. In one series,
the initial N09 concentration was taken to be 10% of the initial NO . In
^ J\.
the other series of runs, N0_ was taken to be 50% of the initial NO concen-
L. X
tration. Ten pairs of simulations were carried out for NMHC-to-NO ratios
X
that ranged from 5:1 to 50:1. It was found that the time to the 0, peak
o
depended on the initial N02-to-NO ratio as one would expect. 0_ reached
a maximum earlier in the day in those simulations where N0» was taken to be
50% of the NO . The absolute peak 0, levels, however, were largely insensitive
X O
to the initial NO- concentration. The difference in maximum 0, concentration
for each pair of runs was 3% or less. For all ten pairs of runs where NO-
was 10% and 50% of the initial NO , the average change in peak ozone concen-
X
tration was 1%. Since variations in the NO -to-NO ratio had negligible effect
£* X
on the absolute 0, levels, it can be concluded that control requirements also
are not affected by this parameter.
33
-------
SECTION 3
DISCUSSION
The preceding section presented the results of sensitivity studies
that were conducted to assess the impact of various parameters on the pre-
dictions of the photochemical model. Ozone isopleths were constructed for
each of the five test cases considered. These sets of isopleths were found
to differ somewhat from the original isopleths of Figure 1 in either shape or
relative spacing or both. The absolute positioning of the 0, isopleths is of
" ** O
little concern since the isopleths will be applied in a relative sense. The
isopleths will be used only to assess the sensitivity of peak 0, concentra-
tions to changes in 6-9 A.M. levels of NMHC and NO . Our concern, therefore,
A,
is only with the differences in shape and spacing of the various isopleths and
how these differences affect the -predicted benefit in ambient 0_ levels to be
gained from various control strategies. To this end, four hypothetical
control strategies have been selected. The results anticipated by applying
these strategies to each of the six sets of isopleths will be compared.
For purposes of illustration, assume a maximum 0_ concentration of 0.24 ppm
is observed in a given urban area with a median NMHC-to-NO. ratio of 8:1. The
A.
four control strategies under consideration are:
Strategy I: Determine the percent reduction in 6-9 A.M. NMHC needed to obtain
the 0.08 ppm 0, standard assuming no change in ambient NO levels is anticipated.
O X\
Strategy II: Determine the percent reduction in 6-9 A.M. NMHC needed to obtain
the 0.08 ppm 0.. standard if a 25% reduction in ambient NO levels is anticipated.
»J A.
Strategy III: Determine the reduction in 0, levels anticipated if NMHC emissions
are reduced by 50% while NO emissions remain the same.
J\.
Strategy IV: Determine the reduction in 0 levels anticipated if both NMHC
O
and NO emissions are reduced by 50%.
x .
34 .
-------
These four control strategies were applied to each of the six sets of
isopleths (Figures 1,2,4,6,8, and 10). The results are summarized in Table
11. Columns (1) and (2) describe the isopleths used to calculate the effects
of the various control strategies. Columns (3) and (4) list the percent hydro-
carbon reduction needed to achieve Strategies I and II, respectively. Columns
(5) and (6) give the anticipated 0 level to be achieved when Strategies III
and IV are applied, respectively.
As an example of how the calculations were made, consider the four
strategies involving the use of Figure 1. An 0 level of 0.24 ppm at a NMHC-
to-NO ratio of 8:1 corresponds to NMHC =0.72 ppm and NO = 0.092 ppm. Strategy
.A. .A.
I is implemented by reducing NMHC at constant NO until it intercepts the 0.08
A
ppm 0 isopleth. This occurs at a NMHC concentration of 0.20 ppm or a reduction
in NMHC levels of 72%.
Strategy II calls for a 25% reduction in NO levels from NO = 0.092 to
X X
NO = 0.069 ppm. Strategy II is applied by reducing NMHC at this lower NO
X X
level of 0.069 ppm until it intercepts the 0.08 ppm 0, isopleth. This occurs
at a NMHC concentration of 0.17 ppm, or a reduction in NMHC levels of 76%.
To apply Strategy III, a 50% reduction in nonmethane hydrocarbon corre-
sponds to 0.72/2 =0.36 ppm. This NMHC value and the original NO level of 0.092
X
ppm intercept the 0.16 ppm 0, isopleth.
To apply Strategy IV, NO is reduced by 50% from 0.092 to 0.046 ppm. This
A.
NO concentration and a NMHC concentration of 0.36 ppm define a point located
A
between the 0.12 and 0.16 ppm 0 isopleths. Extrapolating, it appears this
point corresponds to an 0, concentration of about 0.15 ppm.
Similarly, the calculations were made with the other five sets of isopleths.
For all four control strategies, the agreement is good. For control Strategy
I, the absolute percent reduction in NMHC levels varies from 68 to 79%. If the
isopleths of Figure 1, therefore, were selected for use in planning control
strategies, the control of hydrocarbon emissions derived from Figure 1 might
be too stringent by 4% or too lenient by 7%, based on these sensitivity studies.
For Strategy II, the percent reduction in NMHC levels needed to achieve the 0
«J
standard varies from 74 to 81%. If the isopleths of Figure 1 are used in
planning control requirements, the control of NMHC might be too stringent by
35
-------
TABLE ll. COMPARISON OF SELECTED CONTROL STRATEGIES APPLIED TO SIX SETS OF 0 ISOPLETHS
(1)
Fig.
1
2
4
6
8
10
(2)
0 Isopleths
Description
Standard
Decreased light intensity
Increased dilution rate
Post-9 A.M. emissions
Decreased reactivity
Increased reactivity
(3)
I
NMIIC Red
(const. NO )
% X
72
71
68
72
68
79
(4)
Strategy
II
NMHC Red
(reduced NO )
% X
76
76
76
76
74
81
(5)
III
0, Max
(const. NO )
ppm
0.16
0.16
~0.14
0.17
0.14
~0.18
(6)
IV
0 Max
(reduced NO )
ppm
~ 0.15
0.15
~ 0.14
0.16
0.14
0.16
-------
2% or too lenient by 5%. Likewise, for Strategy III, the anticipated 0 re-
duction to 0.16 ppm might be as great at 0.14 ppiri or as little as 0.18 ppm,
a difference of 0.02 ppm or approximately 12%. For Strategy IV, there is
a difference of only 0.01 ppm or a relative change of 7% in 0_ levels pre-
O
dieted by using Figure 1 rather than one of the other sets of isopleths.
These results indicate that the selection of initial conditions has
little effect on the predictions of the model in relation to the expected
benefit to be derived from various control strategy options. The six sets
of isopleths give essentially identical results when applied in a relative
sense. Although the isopleths of Figure 1 were derived for conditions that
perhaps would be found more often in Los Angeles than in other areas of the
country, the isopleths should still be applicable to other localities.
The studies presented here only test the sensitivity of the model to
changes in initial conditions. How well the results relate to the real-
world situation is, of course, subject to speculation. The proposed method
was developed through analysis of smog chamber data, with the intent of
accurately representing the chemistry occurring in static smog systems. It
is a compromise between the existing Appendix J method, which ignores the
role of NO in ozone formation, and the urban diffusion models under develop-
ment that have the capacity to treat meteorology as well as chemistry. Viewed
in this respect, the advantages and limitations of the proposed method are
apparent. The limitations associated with the method are such that the
0, isopleths of Figure 1 should not be interpreted in an absolute sense. The
o
results of the sensitivity studies, however, indicate that the isopleths appear
valid when viewed in a relative sense.
37
-------
REFERENCES
1. Dodge, M.C. Combined Use of Modeling Techniques and Smog Chamber Data to
Derive Ozone-Precursor Relationships. In: Proceedings of the International
Conference on Photochemical Oxidant Pollution and Its Control. EPA-600/3-
77-OOlb, U.S. Environmental Protection Agency, Research Triangle Park, N.C.,
1977. pp. 881-889.
2. Dimitriades, B. Effects of Hydrocarbon and Nitrogen Oxides on Photochemical
Smog Formation. Environ. Sci. Technol. 6: 253-260, 1972.
3. Dimitriades, B. On the Function of Hydrocarbon and Nitrogen Oxides in
Photochemical Smog Formation. U.S. Bureau of.Mines, Report of Investigations,
RI-7433, 1970. 37 pp.
4. Federal Register. Requirements for Preparation, Adoption, and Submittal of
Implementation Plans. Vol. 36, No. 158, Aug. 14, 1971. pp. 115486-115506.
5. U.S. Environmental Protection Agency. Alternatives for Estimating the
Effectiveness of State Implementation Plans for Oxidant (Draft). Monitoring
and Data Analysis Division, Office of'Air Quality Planning and Standards,
Research Triangle Park, N.C., March 1977.
6. Mayrsohn, H., and J. Crabtree. Source Reconciliation of Atmospheric
Hydrocarbons. Atmospheric Studies Section, California Air Resources
Board, El Monte, California, March 1975.
7. Lonneman, W.A., S. L. Kopczynski, P.E. Darley, and F.D. Sutterfield.
Hydrocarbon Composition of Urban Air Pollution. Environ. Sci. Technol.
8: 229-236, 1974.
8. Holzworth, G.C. Mixing Heights, Wind Speeds, and Potential for Urban
Air Pollution Throughout the Contiguous United States. AP-101, U.S.
Environmental Protection Agency, Research Triangle Park, N.C., 1972.
118 pp.
9. Peat, Marwick, Mitchell, and Co. An Analysis of Urban Area Travel by
Time of Day. FH-11-7519, U.S. Department of Transportation, Federal
Highway Administration, Washington, D.C., 1972.
10. Black, F. The Impact of Emissions Control Technology on Passenger Car
Hydrocarbon Emission Rates and Patterns. In: Proceedings of the
International Conference on Photochemical Oxidant Pollution and Its Control.
EPA-600/3-77-001b, U.S. Environmental Protection Agency, Research Triangle
Park, N.C., 1977. pp. 1053-1067.
38
-------
11. Kopczynski, S.L., W.A. Lonneman, F.D. Sutterfield, and P.E. Darley.
Photochemistry of Atmospheric Samples in Los Angeles. Environ. Sci.
Technol. 6: 342-347, 1972.
12. Kopczynski, S.L., W. A. Lonneman, T. Winfield, and R. Seila. Gaseous
Pollutants in St. Louis and Other Cities. J. Air Poll. Control Assoc.
25: 251-255, 1975.
13. Lonneman, W.A., R.L. Seila, and S.A. Meeks. Preliminary Results of
Hydrocarbon and Other Pollutant Measurements Taken During the 1975
Northeast Study. In: Proceedings of Symposium on 1975 Northeast
Oxidant Transport Study. EPA 600/3-77-017, U.S. Environmental Pro-
tection Agency, Research Triangle Park, N.C., 1977. pp. 40-53.
14. Burtok, W., A.R. Crawford, A.R. Cunningham, H.J. Mall, E.H. Manny, and
A. Skopp. Systems Study of Nitrogen Oxide Control Methods for Stationary
Sources. Contract PH-22-68-55, National Air Pollution Control Association,
November 1969.
39
-------
APPENDIX
REACTION MECHANISM USED TO GENERATE 03 ISOPLETHS
Number
Reaction
Rate Constant
1
2
3
4
5
6
7
8
9
IP
11
12
13
14
15
16
17
18
19
20
21
22
N02 4 hv -» NO + 0(3P)
0(3P)
0 4
3
N02 +
N024
N034
N02 4
N205
N2°5
NO +
+ 0 4 M ->. 0_ 4 M
2 o
NO -v NO 40
2 2
03 + N03 4 02
0(3P)^-NO 4 02
NO -tf 2N02
NQ3 + N205
-, N02 4 N03
- H20. . 2HNQ3
NO 4 H20 -». 2HONQ
2HONQ -> NO 4 NO + H_0
HONO
OH 4
OH 4
H02 4
H02 4
HOOH
V
°3 +
O^D)
O^D)
OH +
4 lw -» OH 4 NO
NO 2 ^ HN03
NO ^ HONO
NO -»- NO 4 OH
H02 -* HOOH 4 02
4hv ^ 20H
hv -* 0(1D)
hv -» 0(3P)
4 M * 0(3P) 4 M
4 H2Q -» 20H
0 + HO, 4 0
vary
2?0 X 10"5 ppm'^in'1
25.0
0.045
1.3 X 104
1.3 X 104
5.6 X 103
22.0min"1
2.5 X 10"6
-9 -2 -1
1.0 X 10 ppm min
1.0 X 10"3
k
vary
8.0 X 103
3.0 X 10J
1.2.X 103
8.4 X 103
k
vary
vary
k
vary
8.7 X 104
5.1 X 105
84.0
40
-------
Number
Reaction
Rate Constant
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
°3 +
PROP
ADD
ADD
ADD
ADD
ADD
ADD
ADD
H02 + OH + 202
+ OH -K ADD
+ NO -» X + NO
+ ADD ->- 2X
+ MeO,, » X + MeO
i
+ c~o_ -» x + c_o
+ C70_ + X + C_0
32 3
+ C.O- + X + C.O
42 4
+ Sc02 -» X + ScO
X -» HCHO + ALD2 + HO,,
PROP
PROP
BUT
BUT
NO +
NO +
NO +
NO +
NO +
C4°
ScO
C3°
c2o
c.o
4
ScO
+ 0 + OH + HO + ALD2
O fc
+ 0_ -> OH + C20 + HCHO
+ OH + Sc02
+ OH + C.00
4 2
C.O- -» NO- + C.O
42 24
Sc02 -» N02 + ScO
C302 -> N02 + C30
C202 -> N02 + C20
Me02 -v N02 + MeO
-> HCHO + C302
-* ALD2 + C-0-
2 2
+ HCHO + C202
* HCHO + Me02
+ 0- -> ALD4 + H0_
2 2
+ 0^ -> MEK + HO^
2.4
2.5 X 104
1.0 X 103
1.2 X 104
1.0 X 103
1.0 X 103
1.0 X 103
1.0 X 103
1.0 X 103
1.0 X 105 min"1
_3
8.0 X 10
_3
8.0 X 10
1.8 X 103
1.8 X 103
1.8 X 103
1.8 X 103
1.8 X 103
1.8 X 103
1.8 X 103
7.5 X 104 min"1
1.0 X 105 min"1
8.0 X 103 min"1
4.0 X 103 min"1
0.7
1.4
41
-------
Number
Reaction
Rate Constant
48
49
50
51
52
53
54
55
56
57
58
5.9
60
61
62
63
64
55
66
67
68
69
70
71
c3o + o2 +
c2o + o2 ->
MeO + 0- -» .
HCHO + hv f
HCHO + hv ->
HCHO + OH +
ALD2 + hv ->
ALD2 + hv -»
ALD2
ALD3
ALD3
ALD3
ALD4
ALD4
ALD4
C4°3
C3°3
C.0_
2 3
A *7
4 3
C.O.
3 3
C_0,
2 3
*- ,. ^o
4 2
C_0_
3 2
Sc02
+ OH ->
+ hv ->
+ hv >
+ OH -»
+ hv ->
+ hv ->
+ OH ->
+ NO ->-
+ NO -*
+ NO -»
+ N0_ *
2
+ N00 *
2
+ N0_ -*
2
* HO ->
2
+ H00 +
2
2 ^
ALD3 + H02
ALD2 + H02
HCHO + H02
Stable Products
2H02
Stable Products
MeO,, + HO^
C
/ L
<>07
2 3
Stable Products
\^ n
2
C
0_ + HO.
2 2
7°7
3 3
Stable Products
W ry
3
C
C
C
0_ + H00
2 2
4°3
3°2 + N°2
2°3 + N°2
MeO« + NO^
z /
PAN-
PAN
PAN
Stable Products
Stable Products
Stable Products
0.5
0.4
0.4
k
vary
k
vary
1.5 X
k
vary
k
io4
vary
1
6
2
4
6
1
4
8
8
8
1
1
1
4
4
4
.5
.0
.5
.5
.0
.9
.5
.0
.0
.0
.0
.0
.0
.0
.0
.0
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
io4
io-5
10
,-3
min
min~
io4
10
10
10
10
10
10
10
10
10
10
10
10
-5
-3
4
2
2
2
2
2
2
3
3
3
min
min"
42
-------
Number
Reaction
Rate Constant
72
73
74
75
76
C^CL + HO -* Stable Products
Me02 + HO. +- Stable Products
C.O, + HO- -» Stable Products
T" O ^
C,0, + HO- * Stable Products
*J O ^
C_0 + HO- * Stable Products
4.0 X 10'
4.0 X 10*
4.0 X 10*
4.0 X 10*
4.0 X 10*
* -1 -1
Units of ppm min unless otherwise indicated
Symbol
Definition
vary
PROP
BUT
ADD
X
MeO_
C2°2
C3°2
C4°2
Sc02
ALD2
ALD3
ALD4
Diurnal 1-hour average photolytic rate constant
C3H6
CH3CH(OH)CH200
CH3CH(OH)CH20
CH3°2
CH3CHO
CH3CH2CHO
C2°3
C3°3
C4°3
CH3C03
43
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
i. REPORT wo.
EPA-600/3-77-048
2.
3. RECIPIENT'S ACCESSIOI»NO.
4. TITLE AND SUBTITLE , .
EFFECT 'OF SELECTED PARAMETERS ON PREDICTIONS OF A
PHOTOCHEMICAL MODEL
5. REPORT DATE
June 1977
6. PERFORMING ORGANIZATION CODE
7. AUTHCR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Marcia C. Dodge
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Environmental Sciences Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
PROGRAM ELEMENT NO.
1AA603 (AC-18)
11. CONTRACT/GRANT NO.
12. SPQNSORING AGENCY ^AME AND ADDRESS
Environmental Sciences Research Laboratory-RTP, NC
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
In-House
14. SPONSORING AGENCY CODE
EPA/600/09
15. SUPPLEMENTARY NOTES
16. ABSTRACT
A sensitivity study was undertaken to assess the effect of selected parameters
on the predictions of a photochemical kinetics model. The model was previously
developed for use in designing control requirements for ozone reduction in urban
areas. The, parameters varied in the present study included (1) solar energy, (2)
dilution rate, (3) post 9-A.M. emissions, and (4)' hydrocarbon composition of 6-9
A.M. emissions. Based on the results of the simulation? for each of these parameters,
0 isopleths as a function of initial non-methane hydrocarbon and NO' were con-
structed. A comparison of the degree of hydrocarbon control predicted to achieve the
air quality standard for 0_ was made for each set of isopleths. It was found that
the predictions of the model are largely insensitive to the parameters investigated
when the results of the simulations are interpreted in a relative sense.
7.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COS AT I Field/Group
* Air pollution
* Ozone
* Nitrogen oxides
* Computerized simulation
* Mathematical models
* Atmospheric models
* Photochemical reactions
* Reaction kinetics
13B
07B
14B
12A
04A
18. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (ThisReport)
UNCLASSIFIED
21. NO. OF PAGES
52
20. SECURITY CLASS (This page)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
44
------- |