EPA-R4-73-012, Vol. d
CR-4-273
IMPACTS OF TRANSPORTATION CONTROL
STRATEGIES ON LOS ANGELES AIR QUALITY
Contract No. 68-02-0336
May 1973
J. R. Martinez
R. A. Nordsieck
A. Q. Eschenroeder
Prepared for
Environmental Protection Agency
GENERAL fl
RESEARCH «{9 CORPORATION
P.O. BOX 3587, SANTA BARBARA, CALIFORNIA 93105
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In addition to approval by the Project Leader
and Department Head, General Research Corporation
reports are subject to independent review by a
staff member not connected with the project.
This report was reviewed by W. H. Jago.
The work upon which this publication is based
was performed pursuant to Contract 68-02-0336
with the Environmental Protection Agency.
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CR-4-273
IMPACTS OF TRANSPORTATION CONTROL
STRATEGIES ON LOS ANGELES AIR QUALITY
May 1973
J. R. Martinez
R. A. Nordsieck
A. Q. Eschenroeder
Prepared for
Environmental Protection Agency
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ABSTRACT
The General Research Corporation photochemical/diffusion simulation
model is employed to evaluate four control strategies for reducing air
pollution in Los Angeles. Three representative air trajectories (for which
validation tests have been run) serve as baseline cases using 1969 emission
levels. Transportation controls are emulated by reducing source emissions
in accordance with hypothetical plans worked out with the Division of
Meteorology of the Environmental Protection Agency. Straight reductions
of vehicle miles traveled do not give ozone reduction percentages that
are as large as the emission reduction percentages. Strong influence of
initial pollutant load of the air in the morning is noted. Day-to-day
pollution carryover must be carefully adjusted through the initial condi-
tions to account for continuous strategies in contrast with intermittent
strategies. Ratios of nitrogen oxides to reactive hydrocarbon affect the
ozone buildup markedly. It is found that control of the mixture ratio can
be more important than straight reduction in emissions.
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ii
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CONTENTS
SECTION PAGE
ABSTRACT i
1 INTRODUCTION I
2 STUDY PLAN 3
2.1 Trajectories for Baseline Cases 3
2.2 Strategies Tested 3
3 IMPACTS 10
3.1 The 30 Percent Strategy 10
3.2 The Reduced Downtown Emissions Strategy 21
3.3 The EQL Strategy 29
3.4 Zero Emissions Intermittent Control Strategy 39
4 EFFECT OF INITIAL CONDITIONS SCALING ON THE EQL
STRATEGY RESULTS 47
5 CONCLUDING REMARKS 54
REFERENCES 57
ill
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IV
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ILLUSTRATIONS
NO. PAGE
2.1 Trajectory No. 1 4
2.2 Trajectory No. 2 5
2.3 Trajectory No. 3 6
3.1 Comparison of CO Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 1 11
3.2 Comparison of NO and N0_ Levels for Baseline Case and 30%
Reduction Strategy, Trajectory No. 1 12
3.3 Comparison of Ozone Levels for Baseline Case and 30% Reduc-
tion Strategy, Trajectory No. 1 13
3.4 Comparison of CO Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 2 14
3.5 Comparison of NO and NO Levels for Baseline Case and 30%
Reduction Strategy, Trajectory No. 2 15
3.6 Comparison of Ozone Levels for Baseline Case and 30% Reduc-
tion Strategy, Trajectory No. 2 16
3.7 Comparison of CO Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 3 17
3.8 Comparison of NO and N02 Levels for Baseline Case and 30%
Reduction Strategy, Trajectory No. 3 18
3.9 Comparison of Ozone Levels for Baseline Case and 30% Reduc-
tion Strategy, Trajectory No. 3 19
3.10 Comparison of CO Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 1 22
3.11 Comparison of NO and N0£ Levels for Baseline Case and
Reduced-Downtown-Emissions Strategy, Trajectory No. 1 23
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Illustrations (Cont.)
NO. PAGE
3.12 Comparison of Ozone Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 1 24
3.13 Comparison of CO Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 3 25
3.14 Comparison of NO and N02 Levels for Baseline Case and
Reduced-Downtown-Emissions Strategy, Trajectory No. 3 26
3.15 Comparison of Ozone Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 3 27
3.16 Comparison of CO Levels for Baseline Case and EQL Strategy,
Trajectory No. 1 30
3.17 Comparison of NO and NOo Levels for Baseline Case and EQL
Strategy, Trajectory No.l 31
3.18 Comparison of Ozone Levels for Baseline Case and EQL
Strategy, Trajectory No. 1 32
3.19 Comparison of CO Levels for Baseline Case and EQL Strategy,
Trajectory No. 2 33
3.20 Comparison of NO and N0~ Levels for Baseline Case and EQL
Strategy, Trajectory No. 2 34
3.21 Comparison of Ozone Levels for Baseline Case and EQL Strategy,
Trajectory No. 2 35
3.22 Comparison of CO Levels for Baseline Case and EQL Strategy,
Trajectory No. 3 36
3.23 Comparison of NO and N02 Levels for Baseline Case and EQL
Strategy, Trajectory No. 3 37
3.24 Comparison of Ozone Levels for Baseline Case and EQL
Strategy, Trajectory No. 3 38
3.25 Comparison of NO and N02 Levels for Baseline Case and
Zero-Emissions Strategy, Trajectory No. 1 41
3.26 Comparison of Ozone Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 1 42
VI
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Illustrations (Cont.)
NO. PAGE
3.27 Comparison of NO and N02 Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 2 43
3.28 Comparison of Ozone Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 2 44
3.29 Comparison of NO and N02 Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 3 45
3.30 Comparison of Ozone Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 3 46
4.1 Effect of Changes in HC/NO Ratio and Initial Load Level
for Trajectory 1, Zero Emissions Strategy
4.2 Effect of Varying Initial Load Level with Constant HC/NO
v
Ratio = 2 for Trajectory 1, Zero Emissions Strategy 52
vn
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VI11
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TABLES
NO. PAGE
2.1 Directory of Air Quality and Meteorological Monitoring
Stations in the Los Angeles Basin 7
3.1 Effect of 30% Reduction in Mobile Source Emissions 10
3.2 Ratio of Total Emissions After 30% Reduction on Mobile Source
Emissions to Total Emissions Before Controls on Mobile Sources 20
3.3 Ratio of Selected Parameters after 90% Reduction in Miles
Traveled in the Downtown Area to the Parameters without
Reduction in Miles Traveled 28
3.4 Ratio of Selected Parameters After Application of EQL
Strategy to the Baseline Values 29
3.5 Ratio of Selected Parameters Computed Without Emissions to
Baseline Values with Initial Conditions Unchanged 40
4.1 HC/NOX Ratio, Initial Load Level, and Ozone Dosage for
Trajectories Used in Transportation Control Strategy
Studies 49
4.2 Effect of Changes in Initial Load Level of (HC+NOx)
on Ozone Peak and Dosage with HC/NO =2 52
X
IX
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1 INTRODUCTION
In compliance with the Clean Air Act as amended (PL 91-604), each
state must submit an implementation plan showing how it proposes to meet
air quality standards. An element of the plan must be a control strategy
for each region where ambient levels of a pollutant exceed the applicable
national standard. The plan submitted by California for the Los Angeles
Air Quality Control Region (AQCR) recommends relatively large percentage
reductions in mobile source emissions as follows: CO: 80%, NO : 57%,
X
and enough hydrocarbon reduction to lower oxidant by 79%. These emission
reductions were estimated to produce improvements in air quality as follows:
CO concentration reduction >78%, N0~ concentration reduction -45%, and
oxidant concentration reduction =73%.
Part of the plan proposed by California was disapproved by EPA on
the grounds that the proposed reductions in hydrocarbon emissions would
not result in oxidant levels which meet the national air quality standards
of 0.08 parts per million (ppm) for one hour. Following a court ruling,
EPA promulgated its own strategy, which recommends a reduction in hydro-
carbon emissions of 87%. The EPA plan has been involved in controversy
because it appears that the only way to reduce HC emissions by 87% is by
a drastic decrease in the use of vehicles in Los Angeles during the smog
season.
The 87% hydrocarbon emissions reduction called for by EPA was obtained
by the application of the so-called linear rollback formula. The linear
rollback formula assumes that air quality levels are directly proportional
to emissions and is based on the equation
S \
percent emissions reduction = (1 - —I x 100
where S = air quality standard
A = actual air quality
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It is not the purpose of this report to examine either the State
or Federal implementation plans. The latter is evaluated in another
2
report based on the testimony of one of the authors (A. Eschenroeder).
This report is basically exploratory and treats four hypothetical trans-
portation control strategies using the General Research Corporation (GRC)
3
photochemical/diffusion simulation model.
In contrast to the oversimplifications of linear rollback, the
results we present here are based on a deterministic prediction of expected
reduction. Such a prediction is now possible through the application of
the GRC simulation model. The method of applying the technique is to
establish baseline values for times and conditions for which meteorological
and air quality variables have been measured. Then the emission control
strategy is imposed on the existing inventories as reductions in certain
emission sources with respect to the specific pollutant, the location, and
the time. In this manner, changes in air quality can be associated directly
with changes in emissions for established conditions of atmospheric trans-
port and sunlight intensity.
The specific objective of these exercises is to determine the effect
of various amounts of emission reductions on air pollution levels at
selected points in the Los Angeles Basin. Days with high pollution levels
were selected for the simulation. The ground rules for the study were
established by EPA by selecting the days, the air trajectories, and the
emission reductions to be tested. The exercise demonstrates the flexi-
bility and utility of the model approach while providing quantitative
information which allows us to evaluate the effectiveness of the various
abatement strategies studies.
This report first describes the study plan in terms of the trajec-
tories and the strategies tested. Then it details the results obtained
by simulating the strategies.
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2 STUDY PLAN
2.1 TRAJECTORIES FOR BASELINE CASES
Three air trajectories were obtained from a previous phase of our
4
studies which gives full details on evaluating the validity of the model
for these and 21 other trajectories. Comprehensive discussions on emissions
statistics, meteorological inputs, and chemical kinetics are given in
Ref. 4 and will not be repeated here. The three trajectories chosen for
the study consisted of two trajectories on September 29, 1969, and one on
November 4, 1969. The main criterion used in the selection of these
trajectories was the presence of high concentrations of ozone. The maps
shown in Figs. 2.1-2.3 illustrate the path of the air parcels as they
traverse the Los Angeles Basin. Table 2.1 lists the monitoring stations
and abbreviations used in the figures. The trajectories shall be identi-
fied using the following numbering scheme:
*
• Trajectory No. 1 for September 29, 1969 starts at 0530 hours
in Downtown Los Angeles and ends at 1230 hours near Pomona
in the San Gabriel Valley.
• Trajectory No. 2 for September 29, 1969 starts at 0230 hours
near the coast and ends at 1230 hours in Anaheim.
• Trajectory No. 3 for November 4, 1969 starts at 0530 hours
in Downtown Los Angeles and ends at 1430 hours near Mission
Hills in the San Fernando Valley.
2.2 STRATEGIES TESTED
Four emission control strategies for reducing emissions of carbon
monoxide, reactive hydrocarbons, and nitric oxide were applied to each
trajectory. These control strategies are:
1. 30% reduction in CO, reactive hydrocarbons, and nitric
oxide emissions from mobile sources only. This was believed
All times are given in Pacific Standard Time,
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60 ESGV
• ELM
0530fDOLA
80 SE
75 EGA
WNTT
Figure 2.1. Trajectory No. 1
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80 SE
1230
ANAHEIM
1030 1130
ORANGE CO.
AIRPORT
9/29/69
Figure 2.2. Trajectory No. 2
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D SAU
• NEWHALL
u-i
1X1
CANOGA
PARK *
MISSION HILLS
1430
RESEDA
LA CANADA
LA INTERNATIONAL
AIRPORT
EL MONTE
BKT
D
Figure 2.3. Trajectory No. 3
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TABLE 2.1
DIRECTORY OF AIR QUALITY AND METEOROLOGICAL
MONITORING STATIONS IN THE LOS ANGELES BASIN
Abbreviation
ALMB
AZU
BRT
BUR
BURK
COMA
CPK
DOLA
DOM
ELM
ENC
FOX
HOL
KFI
LACA
LANC
LAX
LENX
LGB
LONB
MALC
MDR
Location
Alhambra
Azusa - East San Gabrial Valley
Brackett
Hollywood-Burbank Airport
Burbank - East San Fernando Valley
Compton
Canoga Park
Downtown Los Angeles - LAAPCD Headquarters
Dominguez
El Monte
Encino
Gen. Wm. J. Fox Airfield
Hollywood
KFI Transmitter
La Canada
Lancaster
Los Angeles International Airport
Lennox
Long Beach Airport
Long Beach - South Coast
Malibu
Marina del Ray
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TABLE 2.1 (Cont.)
Abbreviation
MISH
MWS
NEW
NP
NTB
ONT
PASA
PICO
PMD
POMA
RB
EESD
RLA
RVA
SAU
SM
SP
VEN
VER
WEST
WHTR
WNTT
ZUM
Location
Mission Hills
Mount Wilson
Newhall
Newport Beach
Los Alamitos Naval Air Station
Ontario International Airport
Pasadena - West San Gabriel Valley
Pico
Palmdale Airport
Pomona
Redondo Beach
Reseda
Rancho Los Amigos
Rivera
Saugus
Santa Monica
San Pedro
Venice
Vernon
West Los Angeles
Whittier
Walnut
Zuma Beach
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to be a maximum reduction obtainable by placing sanctions
on vehicle operations without any technological changes in
the vehicle itself.
2. A nearly vehicle-free area involving 90% reduction in
2
mileage traveled in a 60 mi area approximately centered
in Downtown Los Angeles.
&
3. An approximation to the Environmental Quality Laboratory s
(EQL) strategy which consists of:
a. 62% reduction in CO emissions together with a
50% cut in the initial CO load
b. 79% reduction in reactive hydrocarbon emissions from
mobile sources together with a 63% cut in the initial
load
c. 73% reduction in nitric oxide emissions from mobile
sources together with a 58% cut in initial NO load
4. The ultimate in intermittent control strategies which is
modeled by total elimination of all emissions without changing
initial conditions.
Except for the third strategy-, all other strategies were tested using the
initial concentrations obtained from air monitoring data for each of the
three trajectories. The selection of these strategies is motivated by a
need to investigate relative effects; therefore, it should not be inter-
preted as an endorsement of these courses of action.
The numbers are interpretations by EPA of the results of applying the
EQL strategy.
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3 IMPACTS
3.1 THE 30 PERCENT STRATEGY
Table 3.1 shows the changes obtained in peak ozone, ozone dosage, and
CO peak for the first strategy. The numbers shown on Table 3.1 are the
ratio of the quantity after the emission controls are applied to the quan-
tity before applying emission controls. Concentration histories along the
ground track of the air parcels are shown in Figs. 3.1 through 3.9 for the
baseline case and for the 30 percent strategy. It should be noted that the
dosage shown in Table 3.1, as well as in subsequent sections, is the inte-
gral of the concentration-time curve for ozone. Hence it is the ozone dose
that would be experienced by an observer traveling with the air parcel.
TABLE 3.1
EFFECT OF 30% REDUCTION IN MOBILE SOURCE EMISSIONS
(Numbers shown are ratios of the quantity after applying
controls to the quantity before controls are applied.)
Trajectory
1
2
3
0 Peak
0.99
0.93
0.84
0,, Dosage
1.04
0.96
0.92
CO Peak
0.87
0.79
0.87
From Table 3.1, it can be seen that CO shows the greatest response
to the emission controls. This is to be expected since atmospheric CO
concentrations are wholly due to mobile sources and the full force of
the controls can be felt by the air parcel. Actually, the response of
CO has a one-to-one relationship to uniform changes in emissions. Thus
a uniform 30% reduction in CO emissions should result in a 30% decrease
in CO peak provided that transient effects due to initial conditions are
removed. The results reported in Table 3.1 are based on ratios obtained
with initial conditions included, hence the ratio is 0.87 instead of 0.70.
10
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14
12
£ io
o
K-l
f—
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0530
BASELINE
30% STRATEGY
MODEL RESULTS
0730
0930
TIME (PST)
1130
1330
Figure 3.2.
Comparison of NO and N0? Levels for Baseline Case and 30%
Reduction Strategy, Trajectory No. 1
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30
25
Q-
Q.
20
O
CJ>
15
10
0530
BASELINE
30% STRATEGY
MODEL RESULTS
0730
0930
TIME (PST)
1130
CT-
l-Tl
1330
Figure 3.3. Comparison of Ozone Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 1
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12
g; 10
a:
BASELINE
30% STRATEGY
1X2
MODEL RESULTS
I
0230
0630 1030
TIME (PST)
1430
Figure 3.4. Comparison of CO Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 2
14
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20 r
NO,
0430
0630 0830
TIME (PST)
1030
1230
Figure 3.5. Comparison of NO and NO- Levels for Baseline Case and 30%
Reduction Strategy, Trajectory No. 2
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40 i-
30
CL
CL.
20
o
CJ
10
0
0430
BASELINE
30% STRATEGY
MODEL RESULTS
SUNRISE
0630
0830
TIME (PST)
1030
1230
Figure 3.6. Comparison of Ozone Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 2
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25 i-
CL
Q.
o
i—i
i—
-------
MODEL RESULTS
Q.
CL
-------
401-
CL
CL
a:
20
CD
<
o:
0630
BASELINE
30% STRATEGY
MODEL RESULTS
0830
1030
TIME (PST)
1230
1430
Figure 3.9. Comparison of Ozone Levels for Baseline Case and 30% Reduction
Strategy, Trajectory No. 3
19
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Once the system relaxes and the transients have decayed, the ratio of
the asymptotic CO concentration with the 30% reduction in emissions to
the concentration without the reduction should be found to be 0.70.
The changes in peak ozone and ozone dosage are seen to be so small
as to be insignificant. Although the last trajectory shows a 16% decrease
in peak ozone, the dosage is only reduced by 8%. As mentioned previously,
the first and third trajectories contain relatively large initial loads
of reactive pollutants and are not very sensitive to source emissions.
Table 3.2 shows the ratio of emissions after controls to emissions
before controls. The emissions considered here and subsequently are the
emissions received by the air parcel as it sweeps over the Los Angeles
Basin. If the full 30% reduction were in effect for total emissions,
all the ratios would be equal to 0.7. From Table 3.2, it is seen that
the contribution of stationary sources reduces the impact of the controls
for the reactive species: The NO reductions range from 13% to 26% and
the hydrocarbon reductions from 19% to 22%. From Tables 3.1 and 3.2 we
see that the emissions cutbacks and the peak concentration of ozone and
CO are positively correlated, but that the relationship is far weaker
than a one-to-one proportionality. This casts some doubt on the validity
of linear rollback assumptions for secondary pollutants such as ozone if
reduction of vehicle miles travelled is the action contemplated.
TABLE 3.2
RATIO OF TOTAL EMISSIONS AFTER 30% REDUCTION ON MOBILE
SOURCE EMISSIONS TO TOTAL EMISSIONS BEFORE CONTROLS ON MOBILE SOURCES
Reactive
Trajectory NO Hydrocarbons CO
1
2
3
0.87
0.81
0.74
0.81
0.78
0.78
0.7
0.7
0.7
20
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Table 3.1 also shows that, in the case of the first trajectory,
even though the peak ozone concentration decreased slightly, the ozone
dosage increased about 4%. Referring to Fig. 3.3, we can see that the
reason for the increase in ozone dosage is that the ozone curve for the
30% emissions reduction shows slight increases in concentration during
the hours 0930-1130. The cause for these increases is the lower concen-
tration of NO which, through the fast reaction NO + 0 -> N0_ + 0 , tends
to keep the ozone in check until the NO decays to a low value. Thus the
reductions in NO emissions tend to speed up the accumulation of ozone
and this results in a slight dosage increase. However, the lower NO
emissions also work to lower the amount of NO. present, as can be seen
in Fig. 3.2. Because the NO concentration is lower, the production rate
of ozone will be eventually slowed down and the resulting ozone peak will
be reduced. It should be noted that the peak ozone concentration occurs
at 1230, the end of the trajectory. Because of the reduced NO levels,
the difference in peak ozone and dosage between the baseline and 30%
strategy cases should increase if the computation were continued beyond
1230. Finally, we note that initial concentrations also play a large
role in the results shown in Table 3.1. A fuller explanation of these
effects is given in Sec. 4.
3.2 THE REDUCED DOWNTOWN EMISSIONS STRATEGY
The second control strategy consists of reducing by 90% the vehicle
2
miles traveled in an area of 60 mi approximately centered on Downtown
Los Angeles. Only trajectories 1 and 3 could be used to evaluate the
effect of this strategy since the second trajectory does not traverse the
affected area. It should also be noted from Fig. 2.1 that in the case
of trajectory 1 the air parcel does not spend very much time downtown
and the observed effects are therefore very small. However, trajectory 3
does spend a considerable amount of time in the downtown area and the
effects of the strategy are much more significant. Figures 3.10 through
3.15 compare the ground concentrations along the ground track with and
without the strategy applied.
21
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12
10
•BASELINE
REDUCED DOWNTOWN
EMISSIONS
MODEL RESULTS
0
0530
I
I
0730
0930
TIME (PST)
1130
Figure 3.10.
Comparison of CO Levels for Baseline Case and Reduced-Downtown-
Emissions Strategy, Trajectory No. 1
22
-------
30
25
_
O-
CL
„ 20
15
10
.BASELINE
-REDUCED DOWNTOWN
EMISSIONS
MODEL RESULTS
0530
0730
0930
TIME (PST)
1130
1330
Figure 3.11.
Comparison of NO and N0? Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 1
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r-o
-p-
REDUCED DOWNTOWN EMISSIONS
0530
0730
0930
TIME (PST)
1130
1330
Figure 3.12.
Comparison of Ozone Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 1
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25r
BASELINE
REDUCED DOWNTOWN
EMISSIONS
MODEL RESULTS
0730
0930
1130
TIME (PST)
1330
1530
Figure 3.13.
Comparison of CO Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 3
-------
0530
BASELINE \
REDUCED DOWNTOWN |MODEL RESULTS
EMISSIONS
0730
0930
1130
1330
TIME (PST)
Figure 3.14. Comparison of NO and NO,., Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 3
-------
CL
0.
30 I-
20
10
BASELINE
REDUCED DOWNTOWN EMISSIONS
MODEL RESULTS
Ol
0530
0730
0930
1130
1330
TIME (PST)
Figure 3.15.
Comparison of Ozone Levels for Baseline Case and Reduced-
Downtown-Emissions Strategy, Trajectory No. 3
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Table 3.3 shows the ratio of the 0» peak, 0 dosage, CO peak, and
NO, HC, and CO emissions after controls to the quantities before controls.
From Table 3.3 it can be observed that for trajectory 1, slight increases
in ozone peak and dosage result. For the same trajectory, it is apparent
that the emissions reductions are minimal for NO and HC. The increases
in ozone peak and dosage can be ascribed to initial condition effects
(see Sec. 4 for a detailed explanation of these effects). It should be
noted that in this case, the concentration changes expected for CO do not
follow a one-to-one relationship with the emissions reductions because
the flux changes are not uniform.
TABLE 3.3
RATIO OF SELECTED PARAMETERS AFTER 90% REDUCTION IN MILES
TRAVELED IN THE DOWNTOWN AREA TO THE PARAMETERS
WITHOUT REDUCTION IN MILES TRAVELED
Trajectory
1
3
Air Quality Effects
0 Peak
1.01
0.73
0 Dosage
1.04
0.77
CO Peak
0.82
0.66
Emission Effects
NO
0.96
0.45
HC
0.90
0.56
CO
0.83
0.39
The increase in peak ozone and dosage shown in Table 3.3 may be
somewhat misleading, because in addition to the initial condition effects,
the peak ozone concentration occurs at the end of the trajectory. Thus
it is possible that if the computation were continued beyond that point
that the peak ozone and dosage for the case with reduced emissions would
eventually be lower than for the baseline case. This same comment applies
to the results discussed in Sec. 3.3. See also the remarks in Sec. 3.1
concerning ozone dosage increases.
For the third trajectory, it is apparent that the emissions reduc-
tions are substantial and the air quality improvements are similarly
significant. The trajectory spends about 40% of the time in the downtown
28
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area and the reductions in ozone peak and dosage are thus indicative of
the influence that is exerted on late-time oxidant formation by reductions
in early-morning emissions.
3.3 THE EQL STRATEGY
Table 3.4 shows the ratios of various parameters after abatement
is applied to the same quantities before applying controls according to
the EQL strategy. Figures 3.16 through 3.24 show concentration compari-
sons for the EQL case.
TABLE 3.4
EATIO OF SELECTED PARAMETERS AFTER APPLICATION
OF EQL STRATEGY TO THE BASELINE VALUES
Trajectory
1
2
3
Air Quality Effects
0 Peak
1.01
0.67
0.90
0_ Dosage
1.35
0.75
1.12
CO Peak
0.45
0.45
0.45
Emission Effects
NO
0.53
0.53
0.53
HC
0.51
0.42
0.42
CO
0.38
0.38
0.38
We note that the total NO and HC emissions exceed by considerable
margins the expected emissions from mobile sources alone. The expected
ratios for mobile source emissions are 0.27 and 0.21 for NO and HC,
respectively. Thus we find that the contribution from stationary sources
assumes greater importance, generally matching the contributions of the
highly controlled mobile sources. Concentrating on the second trajectory,
we see significant reductions in both ozone peak and dosage. However,
again we note that although total emissions have been essentially halved,
the reductions in ozone peak and dosage are 33% and 25% respectively.
The reader is referred to Sec. 4 for further elaboration on the other
results.
29
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14 i-
12
• BASELINE
•EQL STRATEGY
MODEL RESULTS
10
Q-
D-
co
(_>
^
o
C3
§ 6
o:
=>
o
I
I
0530
0730
0930
TIME (PST)
1130
Figure 3.16.
Comparison of CO Levels for Baseline Case and EQL Strategy,
Trajectory No. 1
30
-------
30 i-
25
20
15
^ 10
ID
O
BASELINE |
EQL STRATEGY |
MODEL RESULTS
NO
0530
0730
0930
TIME (PST)
1130
Figure 3.17. Comparison of NO and N0? Levels for Baseline Case and EQL
Strategy, Trajectory No. 1
31
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30 -
0-
CL
0730
0930
TIME (PST)
1130
Figure 3.18. Comparison of Ozone Levels for Baseline Case and EQL Strategy,
Trajectory No. 1
32
-------
12
10
CL
CL
O
C_J
o
CJ3
0
0230
\
BASELINE
EQL STRATEGY
MODEL RESULTS
0630
TIME (PST)
1030
Figure 3.19. Comparison of CO Levels for Baseline Case and EQL Strategy,
Trajectory No. 2
33
-------
40
30
20
10
BASELINE
EQL STRATEGY
MODEL RESULTS
NO
0?30
0430
0630
0830
1030
1230
TIME (PST)
Figure 3.20. Comparison of NO and N0? Levels for Baseline Case and EQL
Strategy, Trajectory No. 2
-------
40 i-
30
CL
Q.
20
C_J
^
O
10
0430
•BASELINE
•EQL STRATEGY
MODEL RESULTS
SUNRISE
0630
0830
TIME (PST)
1030
1230
Figure 3.21. Comparison of Ozone Levels for Baseline Case and EQL Strategy,
Trajectory No. 2
-------
25 i-
BASELINE
EQL STRATEGY
MODEL RESULTS
0730
0930 1130
TIME (PST)
1330
1530
Figure 3.22. Comparison of CO Levels for Baseline Case and EQL Strategy,
Trajectory No. 3
-------
50
40
Q.
CX
30
o
o
< 20
o:
=>
o
10
BASELINE
EQL STRATEGY
MODEL RESULTS
0530
0730 0930 1130
TIME (PST)
1330
Figure 3.23. Comparison of NO and NO™ Levels for Baseline Case and EQL
Strategy, Trajectory No. 3
37
-------
0730
0930
TIME (PST)
1130
1330
Figure 3.24. Comparison of Ozone Levels for Baseline Case and EQL Strategy,
Trajectory No. 3
38
-------
The comments made about the CO ratios reported in Table 3.1 also
apply to the ratios shown on Table 3.4 since the reduction in CO emissions
is uniform in the EQL strategy.
The results obtained with the EQL strategy show increases in ozone
dosage for trajectories 1 and 3 and in peak ozone for trajectory 1.
However, the second trajectory showed marked reductions in both cate-
gories. The reasons for the increases found in trajectories 1 and 3 are
fully explained in Sec. 4. At this time, it suffices to say that a
combination of changes in initial HC/NO ratio together with initial
X
concentration levels are the causes for the results obtained with these
two trajectories. The same effects did not occur with the second trajec-
tory because the initial concentration levels are very low and this
trajectory is thus much more sensitive to changes in the emissions.
Consequently, the second trajectory is considered to be a much better
test of the effects which this abatement strategy is likely to produce.
Let us digress here momentarily to state that any future tests of abate-
ment strategies should involve trajectories which start early enough to
have very low initial concentrations and thereby cause the computed
concentrations to be sensitive to emissions.
3.4 ZERO EMISSIONS INTERMITTENT CONTROL STRATEGY
Much of the previous day's pollution is carried over in the initial
morning conditions during a pollution episode. Testing this highly ideal-
ized intermittent strategy gives us an upper-limit optimistic view of
the effectiveness of shut-downs after an episode has begun. It is seen
from Table 3.5 that for all but the third trajectory, ozone still stays
unacceptably high. Figures 3.25 through 3.30 compare the concentration
histories for zero emission trajectories with baseline values.
39
-------
TABLE 3.5
RATIO OF SELECTED PARAMETERS COMPUTED WITHOUT EMISSIONS TO BASELINE
VALUES WITH INITIAL CONDITIONS UNCHANGED
Trajectory 0 Peak 0 Dose
1 0.79 0.93
2 0.77 1.07
3 0.50 0.57
40
-------
Q.
Q-
a:
i—
^
LU
ZT
O
UJ
CD
a;
UJ
;>
>-
cc
o
10 -
5 -
0530
MODEL RESULTS
ZERO EMISSIONS
0730
0930
TIME (PST)
1130
1330
Figure 3.25.
Comparison of NO and NO,-, Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 1
-------
-p-
NJ
30 i-
O-
Q.
o
I—I
I—
•=c
o
o
o:
3
o
25
20
15
10
0530
BASELINE
ZERO EMISSIONS
MODEL RESULTS
0730
1130
Figure 3.26.
0930
TIME (PST)
Comparison of Ozone Levels for Baseline Case and Zero-Emissions
Strategy, Trajectory No. 1
-------
0430
0630 0830
TIME (PST)
1030
1230
Figure 3.27. Comparison of NO and N0« Levels for Baseline Case and Zero-
Emissions Strategy, Trajectory No. 2
-------
40 r
CL
Q-
o
O
0630
0830
TIME (PST)
1030
1230
Figure 3.28. Comparison of Ozone Levels for Baseline Case and Zero-Emissions
Strategy, Trajectory No. 2
-------
60
CL
CL
O
I—I
I—
-------
30
Q-
Q.
20
C_J>
o
CD
< 10
BASELINE
ZERO EMISSIONS
MODEL RESULTS
0530
0730
0930 1130
TIME (PST)
1330
1530
Figure 3.30.
Comparison of Ozone Levels for Baseline Case and Zero-Emissions
Strategy, Trajectory No. 3
46
-------
4 EFFECT OF INITIAL CONDITIONS SCALING ON THE EQL STRATEGY RESULTS
The most striking result obtained using the EQL strategy is that
the ozone dosage increased in two of the three cases tested: the Sept. 29
and Nov. 4 trajectories, both of which start at 0530 in Downtown Los
Angeles. The ozone dosage decreased considerably in the case of the
Sept. 29 trajectory which starts at 0230 near the coast and ends at
Anaheim at 1230. The following remarks are intended to explain these
results.
Two parameters are of paramount importance in the analysis: the
initial HC/NO ratio and the total initial load level of HC and NO . (The
x x
load level is defined as the sum of HC and NO concentrations.) Since
x
we know that the chemical reaction rate is very sensitive to HC/NO ratio
X
as well as concentration, the model's response to changes in these param-
eters accounts for the results mentioned above.
Figure 4.1 shows the ozone concentration computed by the model in
response to changes in HC/NO ratio and in initial load level for the
X
Sept. 29 trajectory which starts at 0530 in Downtown Los Angeles. For
this set of tests, the emissions have been turned off in order to high-
light the effects of the initial conditions. The four cases depicted
in Fig. 4.1 correspond to two HC/NO ratios and two initial load levels.
X
Case I corresponds to the baseline case with HC/NO = 2 and load level
equal to 60 pphm. Case II corresponds to the EQL strategy, with
HC/NO =1.76 and load level equal to 23.2 pphm. Cases III and IV
X
represent the remaining combinations of HC/NO ratio and initial load
X
level of the first two cases.
Figure 4.1 shows that lowering the HC/NO ratio while maintaining
X
a constant initial load level [cases (I, III) and (II, IV)] lowers both
the ozone peak and the dosage. However, lowering the initial load level
while retaining a constant HC/NO ratio has the effect of increasing the
X
ozone peak as well as the dosage [cases (I, IV) and (II, III)]. If both
47
-------
-p-
oo
25
E
1L 20
0-
z
O
1
•=£
\HC/NOy
N. "
\v
LEVEL\
BASE
(60)
EQL
(23.2)
2
I
IV
1.76
III
II
15
O
CJ>
O
NJ
O
CD
•zf.
QL
r>
o
10
SUNRISE
0530
0730
0930
TIME (PST)
1130
Figure 4.1. Effect of Changes in HC/NO Ratio and Initial Load Level for
X
Trajectory 1, Zero Emissions Strategy
-------
the HC/NO ratio and the Initial level are lowered, as is done in going
X
from case I to case II, then the two changes work against each other and
the relative magnitude of the perturbations will determine which way the
system goes. In going from case I to II the ozone peak is obviously
decreased, but the dosage increases by about 7%. In going from Case III
to IV, the changes work in the same direction and we get the expected
increases in both peak concentration and dosage.
The results shown in Fig. 4.1 can now be used to explain the increase
of ozone dosage in two instances when the EQL strategy was applied. What
happens in these two trajectories is that, although the EQL strategy
lowers the HC/NO ratio, it also lowers the initial load level in such a
X
manner as to increase the ozone dosage. Table 4.1 shows the parameters
for the trajectories.
TABLE 4.1
HC/NO RATIO, INITIAL LOAD LEVEL, AND OZONE DOSAGE FOR
TRAJECTORIES USED IN TRANSPORTATION CONTROL STRATEGY STUDIES
Trajectory
1
2
3
HC/N
Base
2
1.64
0.83
0
X
EQL
1.76
1.44
0.73
(HC + NO )
X
pphm
Base
60
29
88
EQL
23.2
10.2
35
Ozone Dosage Ratio
(EQL/Base)
1.35
0.75
1.12
From Table 4.1, we see that the first and third trajectories showed
increases in ozone dosage of 35% and 12%, respectively. The second trajec-
tory, on the other hand, showed a decrease in dosage of 25%. Clearly,
all cases we have reductions in HC/NO^ ratio and in initial load level
from the baseline case.
in
49
-------
A possible explanation for the increase in dosage seen in the first
trajectory is that the decrease in HC/NO ratio is insufficient to offset
X
the dosage increases caused by the lower initial load levels. In addition,
we note that although the EQL strategy under study calls for reductions
in automotive emissions of 79% for reactive hydrocarbons and of 73% for
nitric oxide, the reductions in total emissions (auto + stationary)
achieved for this trajectory are 49% and 47%, respectively. Thus sta-
tionary sources play a significant role in the emissions of this trajec-
tory and may also be responsible for part of the dosage increase.
The dosage increase experienced in the Nov. 4 trajectory is small.
The smallness of the increase is most probably due to the low value of
the HC/NO ratio. The ratio is low enough to compensate for the sizable
X
reductions in initial load level. It is likely that the system would
show a decrease in ozone dosage if additional reductions in HC/NO ratio
x
are implemented. It should also be noted that the total emissions
(auto + stationary) were reduced by 58% for reactive hydrocarbons and
by 62% for nitric oxide compared to the base case. These reductions more
closely approximate the cutbacks prescribed by the strategy for automotive
sources. Thus, in this instance we have a situation which is more sensi-
tive to the strategy's goals.
The Sept. 29 trajectory which starts at 0230 near the coast and
ends at Anaheim at 1230 showed a 25% decrease in ozone dosage and a reduc-
tion in peak ozone of 33%. These reductions are due to the fact that the
initial load level has been made too low to sustain the reaction. In the
two cases discussed previously, the lower initial levels remained large
enough to sustain the reaction. However, as is explained below, it
appears that there is a threshold level below which we get reduced pro-
duction of secondary pollutants and that in this trajectory the initial
load level is below the threshold. Finally, it should be noted that the
reductions in total emissions obtained in this trajectory were 58% for
reactive hydrocarbons and 45% for nitric oxide.
50
-------
The threshold effect is illustrated in Fig. 4.2 and Table 4.2.
Figure 4.2 shows the ozone concentration for three different initial
load levels and HC/NO held constant at a value of two. Reducing the
X
level from 60 to 23.2 increases both peak ozone and dosage. Further
reducing the level to 5 lowers the peak and the dosage. Table 4.2 shows
the pertinent quantities.
Table 4.2 shows that the dosage for the highest and lowest level
is almost the same, in spite of the fact that the peak concentration has
been cut in half. The existence of a threshold region raises some
difficulties in evaluating control strategies, because it emphasizes
an effect of initial conditions which are assumed rather than modeled
and it underscores the need to consider nonlinearities by the use of
models instead of simple rollback.
51
-------
Ln
CO
25 I-
Q.
0.
o
1-vl
Qi
LU
0730
0930
TIME (PST)
1130
1330
Figure 4.2. Effect of Varying Initial Load Level with Constant HC/NO
Ratio = 2 for Trajectory 1, Zero Emissions Strategy
-------
TABLE 4.2
EFFECT OF CHANGES IN INITIAL LOAD LEVEL OF (HC + NO )
x
ON OZONE PEAK AND DOSAGE WITH HC/NO = 2
x
Peak Ozone Concentration, Ozone Dosage,
Level pphm pphm-min
60 22.1 2681
23.2 22.3 3401
5 11.4 2679
53
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5 CONCLUDING REMARKS
The work presented shows the utility of applying simulation modeling
to the problem of implementation planning. The need for considering many
receptor points in the basin becomes obvious in examining the results.
Also, it is apparent that HC/NO -ratio effects can be as important as
X
total loadings or emissions.
The effects of the controls vary widely according to pollution
sources encountered by the air mass and to details of the initial loading
of pollutants in the air mass. In particular, the 30% cutbacks produced
relatively small reductions in peak ozone concentration and in ozone
dosage. However, it should be noted that the first and third trajectories
are dominated by initial pollutant loading. Hence, reductions in emis-
sions without concurrent decreases in initial concentration lowers the
system's sensitivity to the abatement strategy.
The reduced downtown emission strategy (nearly vehicle-free zone)
only has an effect on areas swept out by the downtown plume. In a city
like Los Angeles, there is such a wide dispersion of intense sources
that a blanket strategy must be applied. In a highly centralized urban
region, perhaps vehicle-free zones might have a better chance of improving
overall air quality.
The need for sweeping reductions across the board is underscored
by the relative success of the EQL strategy for the Los Angeles Air Quality
Control Region. This is the only case where we felt justified in decreas-
ing initial loadings of pollutants in the morning air. Even with large
cutbacks in emissions, however, surprising things happen with ozone buildup
because of peculiarities of hydrocarbon/nitrogen oxides mixture effects.
The zero emission intermittent strategy scenario shows the extreme
sensitivity to initial condition and mixture effects.
54
-------
Future work using photochemical/diffusion simulation models for
abatement evaluation should consider periods of several days and should
inject statistical variations about the mean input quantities. These
requirements may involve geometric increases in computing expenditures;
however, the large costs of controls should justify a more elaborate
analysis.
55
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56
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REFERENCES
1. Federal Register, Vol. 38, No. 14, Jan. 22, 1973, pp. 2194-2200.
2. A. Eschenroeder, Comments on California Air Quality Standards:
Transportation Control Strategy, General Research Corporation
IM-1741, April 1973.
3. A. Eschenroeder, J. Martinez, "Concepts and Applications of Photo-
chemical Smog Modeling," "Advances in Chemistry," Series No. 113
entitled Photochemical Smog and Ozone Reactions, American Chemical
Society, Washington, December 1972, pp. 101-168.
4. A. Eschenroeder, J. Martinez, R. Nordsieck, Evaluation of a Diffusion
Model for Photochemical Smog Simulation, General Research Corpora-
tion CR-1-273, October 1972.
5. Smog: A Report to the People of the South Coast Air Basin, Cali-
fornia Institute of Technology Environmental Quality Laboratory,
Report No. 4, January 1972.
57
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